CA2053553C - Method for evaluation of health care quality - Google Patents
Method for evaluation of health care quality Download PDFInfo
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- CA2053553C CA2053553C CA002053553A CA2053553A CA2053553C CA 2053553 C CA2053553 C CA 2053553C CA 002053553 A CA002053553 A CA 002053553A CA 2053553 A CA2053553 A CA 2053553A CA 2053553 C CA2053553 C CA 2053553C
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/08—Insurance
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/10—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H70/00—ICT specially adapted for the handling or processing of medical references
- G16H70/60—ICT specially adapted for the handling or processing of medical references relating to pathologies
Abstract
A software-based medical information system performs a method of analyzing health care claims records for an enrolled population (e.g., HMO, Medicaid) to assess and report on quality of care based on conformance to nationally recognized medical practice guidelines or quality indicators. The system analyzes health care received by enrollees having a specified health care condition by:
providing to the system health care claims records for a selected enrollee population; defining at least one health care condition in terms of health care events reportable in health care claims records; identifying in the health care claims records those enrollees meeting the definition for that health care condition;
defining health care quality criteria for that health care condition in terms of health care events reportable in health care claims records; comparing the health care quality criteria for said at least one health care condition to the health care claims records for at least a portion of those enrollees meeting the definition for that health care condition; and developing and outputting from said system a health care quality report based on the comparison and formulating action recommendations to improve care. The system provides an efficient means to supplement claims data with data from patient medical records.
providing to the system health care claims records for a selected enrollee population; defining at least one health care condition in terms of health care events reportable in health care claims records; identifying in the health care claims records those enrollees meeting the definition for that health care condition;
defining health care quality criteria for that health care condition in terms of health care events reportable in health care claims records; comparing the health care quality criteria for said at least one health care condition to the health care claims records for at least a portion of those enrollees meeting the definition for that health care condition; and developing and outputting from said system a health care quality report based on the comparison and formulating action recommendations to improve care. The system provides an efficient means to supplement claims data with data from patient medical records.
Description
2~~3~~3 TECHNICAL FIELD
The present invention relates to a data processing method and system for analyzing health care records and generating information in the form of statistical charts anal graphs, evaluations and recommendations suggesting changes for improving the quality of health care services received by a patient population through a health care benefit organization. In particular, the present invention relates to a quality screening and management system for organizing, describing, analyzing, evaluating and reporting on the quality of health care services received by an enrolled or defined population of health care beneficiaries.
BACKGROUND OF THE INVENTION
The system of medical health care delivery in the United States is facing a critical point in its evolution. The escalating cost of health care, marked variation in the practice patterns of physicians, the increasing number of uninsured or under-insured individuals and the dissatisfaction of the public with the current health care system in this country have all contributed to the crisis currently faced by health care benefit providers. The root of the current crisis is best analyzed from an historical perspective.
The structure of organizations responsible for providing medical insurance benefits has shifted over the course of time from local providers to more complex managed health care systems of providers. The administrative structure developed to support health care providers has also grown more complex and has ~~~~~~3 assumed oversight responsibilities. One of these responsibilities is the quality assessment of health care services.
Previously, if health care providers assessed the quality of health care services received by patients, they generally did so by "incident reporting"
in which quality problems were identified by isolated report or individual case inquiry.
Quality assessment with respect to medical practice patterns of physicians was based on the traditional method of peer review of medical records. These methods, however, are labor-intensive and inefficient. As health care organizations grew, new avenues for evaluating quality of care were explored.
More sophisticated data systems were developed to assist health care organizations, but these focused predominantly on the collection of financial data.
These systems were designed to track the cost of health care by reporting actual cost incurred. While these prior art systems performed adequately for these simpler accounting and administrative functions, they became increasingly inadequate to meet the needs of the more complex managed health care systems.
The prior art health care management systems lacked organized health care data bases and evaluation methods, which permit evaluation of comprehensive health care delivery. Purchasers, providers and administrators have lacked the ability to measure and identify quality of care problems with efficiency and inclusive of whole populations receiving services. In prior art health care management systems, quality issues were generally revealed by inference in conducting utilization reviews, case management or financial analysis or in restricted areas, such as inpatient care only. This is in contrast to the direct study of quality and/or access, two factors that are presently considered crucial to the proper evaluation of health care delivery systems, and in distinction to evaluating comprehensive health care spanning inpatient and outpatient services.
Management that is cost-effective, whether performed by physicians in direct patient care or administrators of managed health care systems, necessitates the collection and integration of information on the health care process, appropriateness of the medical intervention, and effectiveness, viewed in terms of outcomes. To maximize the availability and use of such information for large scale health care evaluation, it should be collected from standardized data. Through the use of such data, comparisons between actual clinical practice and authoritative practice guidelines can be made to identify opportunities to improve health care delivery and health outcomes.
Current practices of quality of care assessment depend primarily on the review and evaluation of medical records, which is costly, intrusive and not conducive to the evaluation and reporting of care delivered to large patient populations, except on a sampling basis. Medical records also may not include full pertinent information on utilization of vital services, such as laboratory or pharmacy services. In addition, current practice often focuses on placing blame on the provider, which fosters resistance by physicians to quality of care assessments, and neglects the need to consider the role of patients, purchasers and health care organizations in quality of health care. Further, current practices concentrate on ..
merely monitoring performance without giving sufficient attention to concrete steps for improving the quality of care received by patients.
The existence of managed health care systems providing reimbursement for health care services to medical professionals, hospitals and pharmacies has led to the building of large collections of data reflecting the payment (and in some cases, the denial of payment) of claims made by individuals who are members of a managed health care plan. However, because these data are collected for financial purposes, they have not been organized or coded in a fashion that permits them to be used readily for purposes other than cost analysis. In particular, these data have not usually been used as a source of information for evaluating the quality of health care provided. Yet these data are frequently maintained on computers and, for health care systems that have several years of experience with significant participant populations, these data report, on a relatively reliable basis, the occurrence of.a large number of health care services transactions for a wide variety of medical conditions, including inpatient, outpatient and pharmacy transactions.
A quality of health care screening system designed for complex managed health care systems, using the significant historical databases of claims records for the evaluation of and reporting on appropriate delivery and receipt of health care services would be a decided improvement over the prior art.
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2~~~~~3 SUMMARY OF THE INVENTION
The problems outlined above are in large measure solved by the quality screening and evaluation system in accordance with the present invention.
The quality screening method in accordance with the present invention uses clinically meaningful indicators to define standards for and monitor the quality of health care received by a defined population. By analysis of computerized data, the method identifies areas with quality improvement potential for appropriate follow-up actions.
The quality screening and evaluation system in accordance with present invention defines a health care condition in terms of a set of predetermined condition criteria; uses the condition criteria to analyze a health care claims data base linking inpatient and outpatient, pharmacy and health plan enrollee records and identify a population of individuals who meet the predetermined condition criteria; defines quality of care criteria for the specific medical condition;
compares the quality of care criteria against the health care claims data base for the identified population; and develops a set of prescriptive and descriptive reports based on that comparison for improving health care delivery. The claims data base for the identified population can be supplemented by data obtained from medical records to provide a more detailed evaluation.
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'"~ 2~~~~~3 BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a block diagram schematically illustrating a data processing system in accordance with the present invention.
FIG. 2 is a flow chart depicting the overall operation of the method of the present invention.
FIG. 3 is a flow chart depicting the data analysis details of the present invention with respect t~ a specific health care condition in the nature of a disease or organic dysfunction.
FIG. 4 is a flow chart depicting the data analysis details of the present invention with respect to a specific health care condition not in the nature of a disease or organic dysfunction.
DETAILED DESCRIPTTON OF THE DRAWINGS
Referring to Figure 1, a data processing system 100 for evaluating the quality of health care received by a defined population is shown in block diagram form. A mainframe central processing unit (CPU) I01 is connected to a magnetic disk memory storage unit 110 and a secondary memory device 120, such as a magnetic tape drive, used to input data to the system 100 for eventual storage on the magnetic disk unit 110. Also connected to the CPU 101 is a printer 130 for producing hard copy reports reflecting the analysis performed by the system 100. A
personal computer processing unit 150 is connected to the mainframe CPU 101 via a data communications line 140 for the purpose of entering data, such as medical records, ..~ 2~~3~53 performing analysis on the medical records or other data and for formatting reports.
Connected to the personal computer 150 is a magnetic disk storage unit 160 for storing medical records or other data entered and a printer 170 for producing hard copy reports and graphics reporting the results of the analysis performed by the system 100 for delivery to customers.
Stored in the magnetic disk memory units 110 and 160 are software instructions that serve as the operating systems and the application software.
These together direct the operations of the CPU 101 and the personal computer 150 on the data in the disk memory units 110 and 160. The application software contains the computer language instructions that cause the system to perform the methods of the present invention.
In the preferred embodiment, the application software is written primarily in a language called SAS, Version 6.06. Certain data entry functions are, however, implemented in dBase IV language. The CPU 101 is preferably an IBM
mainframe utilizing the VM/CMS operating system. The personal computer 150 is preferably an IBM PS/2 utilizing the OS/2 operating system. The structure of the application software and the methods of the present invention are depicted most readily in flow chart form. Figure 2 shows a flow chart depicting the overall operation of the method of the present invention. Figure 3 is a flow chart depicting the data analysis details of the present invention with respect to a specific health care condition in the nature of a disease or organic dysfunction. For purposes of illustration, Figure 3 shows a flow chart for the method of the present invention as ~- 20~3~~3 applied to pediatric asthma. Figure 4 is a flow chart depicting the data analysis details of the present invention with respect to a specific health care condition not in the nature of a disease or organic dysfunction. For purposes of illustration, Figure 4 shows a flow chart for the method of the present invention as applied to caesarian sections. The particular health care conditions discussed in Figures 3 and 4 are illustrative examples only and, as will become clearer in the discussion below, the method of the present invention can be used to address many other health care conditions in a similar manner.
t'he flow charts of Figures 2-4 have the following symbols:
circle - connector (null operation) ellipse - start or stop terminator rectangle - computer process trapezoid - manual process diamond - decision or test rectangle with ctuved bottom - document output rectangle with curved sides - disk file Overall Process Logic Flow a. Initial Screening Analysis Turning now to Figure 2, the overall process of the present invention can be explained. The process will typically be performed at the request of a customer that is a health maintenance organization, indemnity insurer (e.g., Blue Cross), a large, self-insured employer group or a government program (e.g., 2053~J~
Medicaid). Such customers administrate one or more health care benefit plans .~ervicing individuals who are enrolled in a plan. At the start 1, the first step 3 is to obtain the customer specific parameters, such as what time period the customer wishes to ar~alyz~e or whether the customer wants to have some data broken down by particular providers or other grouping variables. The next step is to update the system options and parameters using the customer specifications. Thereafter, the system 100 obtains and loads 5 the customer data, usually consisting of the customer's already-computerized health care claims data for a specified period, together with enrollment data and health care provider data. Typically this information can be provided on magnetic tape and is easily placed in the magnetic disk unit 110 of the systeir. 100 by means of a magnetic tape drive 120.
The enrollment data is extracted 7 so as to identify the enrollees served by the customer that meet a predefined enrollment criterion, such as that each enrollee has been enrolled in the health plan for a specified period. T'he resulting enrollment data 9 contains one record per enrollee. Next, the relevant claims data are extracted 11 from the complete customer data base and are configured through linkages to produce the necessary health records. This involves selecting only the claims data for the time period being examined. It should be noted that the claims data usually includes a code identifying a defined health care procedure or service.
T'he claims data will include claims records for medical professional services (outpatient records), claims records for hospital services 13 (inpatient records) and IO
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claims records fur pharmacy purchases 14 (pharmacy records).' (A particularly focused analysis may not have data of all three types.) Ideally, the customer's data base will contain all of the following data fields:
Enrollment/Membership Data 1.R Unique Member Identifier 2.R Enrollment Date 3.R Expiration Date 4.R Birt.'~ Date 5. R Gender 6. Patient Name (only if a medical record review is requested) 7. Medicare Membership Indicator 8. Medicaid Membership Indicator 9. Zip code Medical Professional Claims Data I.R Unique Member Identifier 2.R Date of Service 3.R Provider Type Code (for physicians this must indicate medical specialty) 4. Unique Provider Identifier (required if Provider Type is not available on the claims record or if medical record review is anticipated) 5. R Diagnosis Code (ICD-9) 6. R Procedure Code (CPT-4) 7.R Place of Service Code (e.g., hospital, doctor's office) Hospital (Inpatient/Emergency Room) Claims Data 1.R Unique Member Identifier 2.R Admission Date 3. Discharge Date 4.R Provider Type Code (for in-patient claims this must indicate type of facility.
e.g., hospital, emergency room, urgi-center) 5. Unique Provider Identifier (required if Provider Type is not available on the claims record or if in-patient medical record review is anticipated) 6. R Ptace of Service Code 7. Unique Admission Identifier 8.R Diagnosis Code (ICD-9) ~~~3~~~
9. Revenue Code (i.e., from UB82 codes) Pharmaceutical Claims Data (not used for all conditions) 1.R Unique Member Identifier 2. R Drug Codes 3. Route of .Administration 4. Quantity of Drug S.R Filled Date The minirnum required fields for the present implementation of the invention are marked with an "R" in the above data definitions.
"CPT-4" in the medical professional data refers to an edition of the Current Procedure Terminology code, published by the American Medical Association. In the medical professional data and the hospital data, "ICD-9" refers to an edition of the International Classification of Diseases; "UB82" refers to revenue codes published by Health Care Finance Administration; and Place of Service Codes are those promulgated by the American Medical Association. Alternative coding systems can be used, based on a code conversion table associating the preceding codes with the alternative coding system.
If the customer desires, provider-specific data is also extracted 16 from the customer data, permitting the later analysis to be broken down by the particular provider of services or products, which may be a particular doctor, clink or hospital.
(The provider data also can be used to identify the possible sources of medical records.) The provider data fields utilized are as follows:
Provider Data (e.g. Physiaan Hospital, Urgi-Center) 1. Unique Provider Identifier 2. Provider Type Code (if not in Claims Files) 20~3~~3 3. Name R.M
4.R~LiStreet Address S.RM City 6. State R.'Li 7. Zip Code R.'~rt 8. Area Code R.M
9.RM Phone Number Additional fields required if a medical record review is to be undertaken are marked with an "RM".
The resulting files are merged 19 to produce uncorrected master files 21. Because claims data are not totally "clean", it will typically be necessary to exclude duplicate claims 23 and claims that have been reversed through the claims adjudication process (coordination of benefits, subrogation, clerical errors).
This produces a master file 25 of health care claims records. No adjustment is performed for claims lag. It is assumed that a customer will not forward data for analysis until the claims have been sufficiently processed for the period of study desired.
At this point the health care claims records are ready to be analyzed for indicators of quality. But this analysis requires two further preliminary steps: (1) defining at least one health care condition in terms of health care events reportable in health care claims records; and (2) defining health care quality criteria for each defined health care condition, also in terms of health care events reportable in health care claims records. This must be done in advance of the analysis of the master file 25 of health care claims records. The reason that it is necessary to define a health care condition is that quality measurements are specific to discrete health care conditions: what a provider should do obviously depends on the member's condition, the symptoms, diagnosis or the health care status (e.g., pregnancy). More ,.....
important for this invention, individual health care claims data items accumulated ir, the normal curse of business by a health care management entity may or may not include a direct and specific diagnosis of the particular health care condition st:ffered by an enrollee or the particular health care condition that is of interest from a quality measurement viewpoint. Even if a diagnosis is present in claims records, it is not necessarily valid to take it at face value. The claims data include one or more codes identifying specific treatment events or outcomes, such as, an office visit, a blood test, a CAT scan, a surgical procedure, a drug prescription, a hospital stay with charges for drugs, X-rays or specific therapeutic regimens, a hospital readmission or a death. It is a selection of such data items and their relationships that becomes the definition of a particular health pare condition.
For purposes of the present invention "health care condition" is broadly defined to mean a condition in the nature of a disease or an organic dysfunction or a "condition" that might also be viewed as a status or an outcome. In its present implementation, the following conditions characterized as diseases or organic dysfunctions or outcomes are addressed: diabetes mellitus, pediatric asthma, hypertension, breast cancer, hospital readmissions and ambulatory surgical complications. The following conditions characterized as status-based are also addressed: pediatric immunizations, breast cancer screening, cervical cancer screening, caesarian section and prenatal care. The point of each condition is to provide a focus for analysis of quality of care, not for medical diagnosis.
Given this orientation, the preceding conditions were selected for implementation, because 2~~3~5~
each can be associated with a cluster of health care events that can be related to health care quality criteria as well as with data that can be used to identify a population having the condition. A proper course of testing and treatment is part of quality care to maximize the health of a person with diabetes mellitus. To protect the health of children with certain age status, a prescribed set of immunizations is agreed to be necessary. To protect the health of women in various age groups and/or meeting other status criteria, certain screening tests and examinations, at prescribed intervals, are agreed to be necessary. To protect the health of newborns and their mothers certain prenatal care is agreed to be advisable. ' As will be seen below, defining some health care conditions for purposes of quality measurement is easier than defining others. The caesarian section condition is usually easy to define, because there will often be a specific claims code when the surgical procedure is performed. However, in some circumstances, there will not be a specific claims code and the condition will be deduced from the presence of a combination of claims codes, perhaps including amniocentesis, frequency of prenatal visits and specific anesthesia or surgery events.
Pediatric asthma is an example of a more subtle condition, and, as will be shown, is defined in terms of a set of medical claims codes, hospital claims codes and pharmacy claims codes with specified Boolean (logical) relationships.
Selecting the codes for such conditions can be difficult, because they are not always diagnosed the same way and may be diagnosed only after repeated visits to a health care provider or may not be diagnosed at all. The code selection definitional effort resembles the 2~~3~~~
diagnostic process performed by a health care professional who studies the medical record of a new patient. That is, defining such a condition is a complex logical process requiring extensive clinical and claims data knowledge to implement the definition in a software algorithm.
For all of the conditions addressed by the present invention, it is necessary to define the health care condition of interest solely in terms of data elements reportable in health care claims records. 7 his is a different task than if the entire medical record were a~railable, with its greatzr range of terminology and information. As noted above, in the preferred embodiment the claims data include outpatient records, inpatient records and pharmacy records. Thus, data from all of the record sources can be used to make a health care condition definition.
This is significant, because provider practice patterns and enrollee behaviors may cause a clear picture of the enrollee's health care status to emerge only when data from all of these sources is considered.
Once a specific definition is created for a health care condition of interest for quality screening, this definition is implemented as a series of logically linked compare operations in the software. Applying the definition of the health care condition to the claims records becomes a matter of performing the compare operations and executing the Boolean logic implicit in the definition (and explicit in the software) to identify those enrollees having claims records in the claims data base that meet the definition. The enrollees so identified are the subset of the universe of health care system enrollees that becomes the focus of the further '"" 2~~~~~3 analysis to determine whether this subset, identified as having the defined health care condition, received quality health care for that condition.
The second prerequisite for analysis of the claims master files 25 is defining health care quality criteria for each defined health care condition, also in terms of health care events reportable in health care claims records. Here, the health care system manager must rely on knowledge sources credible to practicing clinicians. Typically, study of the condition will reveal that quality of care is indicated by the absence of certain kinds of health care claims (e.g., an emergency room visit for a pediatric asthma patient, hospitalization for diabetes mellitus, reoccurrence of breast cancer or other adverse events) and the presence of other kinds of health care claims (e.g., annual inoculations, laboratory testing at specific intervals, visits to appropriate medical/surgical specialists, prescription of specific medications). Specific evaluation criteria are developed from clinical or health services literature -and research, from standards developed by the professional societies and through private or public (federal government) task forces. As with the definition of the health care condition of interest, the health care quality criteria must be implemented in the software as a set of physician office claims codes, hospital claims codes and pharmacy codes with specified Boolean relationships.
Returning to Figure 3, step 29 involves the application of the definitions for the health care condition to identify the population having that condition, followed by an analysis of the claims records for that population (a subset of the master files 25) under the defined quality care criteria. The enrollment data 11 2~~3~ ~3 is accessed in this process, as well. In general, the invention is implemented to examine one year of claims data, which may begin on any date in a year.
Analysis of an enrollee's claims records for the following conditions occurs only when the enrollee has been continuously enrolled for one year: diabetes mellitus, pediatric asthma, hypertension, breast cancer, and breast cancer screening. There is no one year continuous enrollment requirement when the following conditions are analyzed: cervical cancer screening, pediatric immunizations (ages birth to two and four to six), hospital readmission, ambulatory surgical complications and caesarian section. For the prenatal condition, the enrollment requirement is enrollment six months prior to delivery, but enrollment past the date of delivery is not required.
The result of the analysis in step 29 is a report that includes: charts and graphs 31 reporting statistically observed quality of care data in the population defined as having the health care condition of interest (e.g., a graph showing emergency room visits by patient age); a written analysis reporting, from a care quality viewpoint, statistical results considered worthy of highlighting 33, 35 (e.g., a report of use of a particular drug intervention and the occurrence of adverse events associated with the particular health care condition); and a report containing recommendations for actions to improve health care quality 37, 39 (e.g., a suggestion that physician guidelines be developed and promulgated stating that a specified laboratory test be performed annually).
Action recommendations to improve health care quality are produced for each condition studied. These recommendations are selected from a menu of -~ ~0~3J~3 nine quality management action categories developed based on a synthesis of the relevant research literature and management expertise. The nine categories are: (1) reporting the results of the quality analysis to physicians, (2) disseminating practice guidelines to physicians, (3) instituting condition-specific medical record flowsheets, (4) modifying reimbursement to physicians, (5) instituting provider discipline, (6) providing patient education and reminders, (7) establishing case management programs, (8) improving patient access to rare, and (9) changing the benefit design.
As can be seen, these actions are directed toward affecting the behavior not only of physicians, but also patients, purchasers or providers of benefits, and health care organizations. Each condition has a set of condition-specific action recommendations defined for it. The customer's report will include those recommendations from the set that are appropriate in view of the results of the analysis performed in step 29.
Analysis for multiple health care conditions takes place iteratively through the software at step 41, and the process just described, comprising steps 29, 31, 33, and 37 and producing charts and graphs 31 and reports 35, 39 is repeated, using the next health care condition definition to identify the population having that condition, followed by an analysis of the claims records for that population (a subset of the master files 25) under the defined quality care criteria for that next condition. After all th~ specified health care conditions have been processed in this manner, the reports for each condition are assembled 43 into a claims-based quality report 45 that is presented to the customer 47.
2~~3~W
b. Detailed Analysis with Medical Records Because it is recognized that a data base of health care claims, even if it includes data from medical professional services, hospital services and pharmacy services, may not have all the information available in other medical records maintained by the physician or other health care provider, the present invention provides as a supplement, additional methods to gather medical records and perform a more detailed analysis. At step 51, the system recognizes whether there is the need for detailed analysis. If no such need exists, no further data collection or analysis occurs. However, if a need for detailed analysis of any health care condition has been determined, then the population identified as having that condition is subjected to sampling 55 to determine for which enrollees additional medical records information will be collected. Both the master claims data files 27 and provider data I8 are used for this step. The determination of which members will have medical records collected for further analysis is based on varying criteria. For most health care conditions, medical records will be of interest for further study of the medical history if an enrollee has exhibited some unfavorable outcome or unexplained deviation from the quality of care criteria. Such enrollees are in greatest need of intervention and the quality of the care they have received or will receive is of greater significance. For instance, it may be desirable to focus detailed analysis on enrollees having more than a specified number of emergency room visits in a year or those for whom there is a deviation from the recommended drug regimen. To select these members, a further sampling definition is developed..
It is ,~ ~ ~~~~J~3 implemented in software as a set of medical claims codes, hospital claims codes and pharmacy codex with specified Boolean relationships. If the member population remaining after application of these criteria is too large to be economic, it may be reduced in size by appropriate statistical sampling methods. The result of these steps is to define a subset of the population recognized as having the particular medical condition of interest to be subjected to further, more detailed study, based on the additional information available in medical records. Appendix A contains software used to set up the sample for whi.:h medical records data is collec:~ed and to identify the appropriate source for this data (i.e., provider location).
To initiate the gathering of medical records data, a request letter to a physician or other provider is generated. Selecting the appropriate provider to contact may be important, because there may be multiple sources of medical records, some of which will be inadequate for evaluation. The appropriate provider must be selected to receive the letter and be the unit for analysis. In some cases, a second source may also be selected. With the provider's consent, the medical records are abstracted 59 with a particular focus on events that relate to the particular health care condition under study, resulting in a completed medical records abstract form 61. This abstracted information is then entered into the system 63, via personal computer 150 to produce a medical record abstract data file 65. Additional and more highly clinically specific quality of care criteria are then used to analyze the medical record file, in a manner similar to the way the claims data was analyzed.
2o~3J~~
One difference is that the medical record may introduce additional data for medical, hospital or pharmacy activities that can be used to implement the quality care definition in the software. As can be seen, using the present invention means that only a relatively limited amount of medical records data need be assembled for health care quality analysis. Because a condition definition has been employed to identify an enrollee group of interest, only medical records for those enrollees having the condition under analysis are of interest. Moreover, those portions of the medical records relevant to the condition under analysis are abstracted. Thus, the volume of data to be analyzed is kept manageable and cost efficient.
The result of the additional, detailed analysis is charts and graphs reporting statistically observed data in the population defined as having the health care condition of interest 69 and a report containing recommendations for actions to improve health care quality 71, 73. If detailed analysis of medical records is specified for multiple health care conditions, then the preceding steps are repeated until charts and graphs reporting statistically observed data 69 and a report containing recommendations for actions to improve health care quality 71, 73 are developed for each health care condition. (These are drawn from the same set of condition-specific quality management actions as discussed above in connection with steps 37, 39.) After all the specified health care conditions have been processed in this manner, the reports for each condition are assembled 77 into a detail level report 79 that is presented to the customer 81, and the process ends 83.
c. Examples for Particular Conditions To further and more specifically explain the present invention, the data processing steps represented by steps 29 and 31 in Figure 2 will be explained by way of two examples of specific health care conditions for which the present invention has been implemented.
Example 1 - Pediatric Asthma To demonstrate further specifics about the present invention, reference is made to Figure 3, which represents further details about the analysis and development of data for steps 29 and 3I in Figure 2 when the defined health care condition to be studied is pediatric asthma. Still further details about the way in which pediatric asthma health care quality issues are analyzed ir, accordance with the present invention can be found in Appendix B, which is the SAS source code corresponding to steps 29 and 31 in Figure 2 and to Figure 3.
The definition of the pediatric asthma condition used by the system is embodied in steps 303, 305, 307 and 309 of Figure 3, which determine the presence or absence of certain data in the claims data master file 25. If the claims data are coded in ICD-9 (International Code of Diseases, 9th Edition) form, the criteria may be expressed as follows. A member is defined as having pediatric asthma if. he or she is under 19 years of age, is continuously enrolled for the year under study and meets one of the following criteria:
1. At least one hospitalization for asthma (IDC-9 = 493.xx); or ~- ~OJ3~~3 2. At least one emergency room visit for asthma (IDC-9 = 493.xx); or 3. Two or more doctor visits for asthma or asthma related conditions, provided that at least one of the visits is for asthira specifically, determined based on the following codes: asthma (493.xx), croup (464.4), acute bronchitis and bronchitis (4b6.xx), allergic rhinitis (477.xx), unspecified bronchitis (490.xx) and chronic bronchitis (491.xx); or 4. Two or more pharmacy claims for asthma related drugs, at least 45 days apart: beta-2 adreric drugs; methyl xanthine drugs; and selected other bronchodilator related drugs lbeclomethasone, cromolyn, flunsolide) (Criteria 1, 2 and 3 show the ICD-9 code that must be found in order for the Qiteria to be satisfied. The "xx" following these codes means that only the first three digits of these five digit codes are compared to determine a match.) When the above pediatric asthma criteria are satisfied for any member, his or her name is~ added to the asthma member file list 313. The decision at step 311 ensures that the full claims data master file is searched for pediatric asthma cases.
That is, the available records, which comprehensively cover claims records for medical professional services, claims records for hospital services and claims records for pharmaceutical prescriptions, are searched. It has been found that evidence of the asthma condition may appear in only one of these three categories of records.
Yet a proper health care quality study of this condition must identify essentially all enrollees that have the condition, regardless of how the condition is reflected in the available claims records. For possible later analysis, a patient's record in the asthma 2~53~~~
member file list is flagged to indicate its inclusion in an adverse events and pharmaceuticals grouping. The asthma member file list 313 is then used in step to build a new file that is a subset of the claims data master file and contains claims data only for members meeting the pediatric asthma definition. This asthma master file 319 is then used to calculate a variety of statistics on health care events and to develop charts and graphs to present the aggregated and calculated data. The calculations and the resulting reports and graphs are detailed at steps 321-351 in Figure 3.
As noted previously, the asthma member list file 313 is flagged to indicate an adverse events and pharmaceutical grouping. At step 353 of Figure 3 the pharmaceutical asthma subset file is created and subjected to further processing at steps 355, 359, 363, 367. This processing results in the calculation of aggregate statistics of various kinds having to do with prescription drug use for the members identified as pediatric asthma patients. The calculations and the resulting charts are detailed at steps 353-371 of Figure 3.
Shown at Appendix C are examples of the kinds of reports and charts and graphs developed by the present invention when analyzing the pediatric asthma condition. These reports reflect an actual analysis from a health maintenance organization the identity has been deleted) and include:
- General explanation of the pediatric asthma quality review - Chart of demographics of children with asthma ~OJ3~53 - Pie graph of age distribution of pediatric asthma patients - Bar graph of frequency of adverse events - Chart of frequency of emergency room visits - Chart of frequency of hospital admissions - Bar graph of percent of children having an annual office visit for asthma, differen tiated by adverse event occurrence - Bar graph of average number of office visits - Chart of pulmonary function testing - Bar graph of influenza immunization - Chart of serum theophyline level monitoring - Charts of use of beta-agonists, cromolyn, theophylline and barbituates - Summary of key statistical findings - Quality management actions recommendations, including proposed medical record flow sheet for pediatric asthma patients In the present ,instance, the management actions recommendations include all those that are part of the condition-speafic set of action recommendations for pediatric asthma. In a report for another customer, only a subset of these might appear, because fewer corrective actions are necessary.
Example 2 - Caesarian Section To demonstrate further specifics about the present invention, reference is made to Figure 4, which represents further details about the analysis and development of data for steps 29 and 3I in Figure 2 when the defined health care condition to be studied is caesarian sections, Still further details about the way in 2~~3~~~
which caesarian section health care quality issues are analyzed in accordance with the present invention can be found in Appendix D, which is the SAS source code corresponding to steps 29 and 31 and to Figure 4.
The definition of the caesarian section condition used by the system is embodied in steps 405-421, which test for certain data in the claims data master file 403. At steps 405 and 407 a subset of the master file is created that includes all enrollees who were pregnant and thus potential candidates for a caesarian section birth (C-section). From this subject enrollees having miscarriages are deleted 409, producing a smaller working C-section file 41I. This file is divided 413 into a C-section births file 415 and a vaginal births file 417. These two files are then merged 419 to produce the births file 42I.
Although there is no agreement on an ideal C-section birth rate that would provide a health care quality measure, there is agreement that a C-section birth rate above the national average could indicate that health care providers are performing inappropriate C-section procedures. Accordingly, the health care quality definition implemented at steps 425-447 of Figure 4 involves calculation of overall C-section birth rates 425, charting that rate by comparison to the national norm and then charting C-section birth rates by age group 429 and by hospital 431-445.
Finally, a "trombone chart" 441 is produced that shows the C-section birth rate for individual hospitals, plotted against the average for all hospitals in the analysis and a curve showing the upper 95% confidence bound (based on statistical measures adjusting for sample size).
'~. 2~~~~~3 Shown at Appendix E are examples of the kinds of reports and charts and graphs developed by the present invention when analyzing the C-section condition. These reports reflect an actual analysis from a health maintenance organization (the identity has been deleted) and include:
- General explanation of C-section quality review - Bar graph of ~-section rate vs. national norm - Bar graph of C-section rates by age - '"Trombone graph" of C-section rates - Chart of C-section rates by hospital - Summary of key statistical findings - Quality management action recommendations -C-section medical record abstraction form and instructions (for more detailed analysis) To perform a detailed analysis beyond the level of claims-based quality evaluation, the medical record may be obtained. This would usually be performed in specific populations where the overall observed C-section rate was higher than expected.
Therefore, the objective would be to determine whether there were specific indications of medical need for a C-section justifying that the procedure was performed. Appendix E contains the medical record abstraction form and instructions. This data obtained from the medical record would be entered and analyzed in the software of the present invention.
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d. Summary As can be seen from the preceding, the present invention involves a data processing system and analytic method that utilizes multiple sources of health care data to evaluate health care quality. The invention initially utilizes the health care claims data accumulated by a health care benefit organization as its enrollees utilize health care benefits. Specific health care conditions of interest are defined in terms of the claims data and these definitions are implemented in software logic to allow a subset of enrollees to be identified as having the health care condition of interest. The health care claims data for this subset are then analyzed in terms of health care quality criteria, developed from multiple expert clinical sources.
These criteria are also defined in terms of the claims data and implemented in software that develops statistical measures of health care quality. If desired, additional medical record data can be collected for the specific portion of the subset of enrollees identified as having the condition of interest. These additional medical records data supplement the claims data and allow additional, more detailed health care quality a~iteria to be defined. These criteria are analyzed against the additional data.
Further statistical measures of health care quality can then be developed.
After analysis of the original claims data and after analysis of the additional medical record data, descriptive and evaluative reports and recommendations on improving health care quality are developed and provided.
The invention combines at least three primary advantages to improve-over the prior art. First, it permits use to be made of the large claims data bases that a~. 20~35~~
are maintained by health care organizations, which in most cases are already in coanputerized form, permitting large scale health care quality analysis to be performed based on this claims data. Second, it'.imits the laborious and expensi~~e task of assembling medical records data for quality analysis to a population that has been screened and selected as having specific potential need for quality improvement (and is thus smaller than the entire universe of enrollees).
Third, by enabling evaluation of health care quality to be performed in a more standardized and efficient manner, through use of distinctly identified data elements in conjunction with discretely defined clinical algorithms, it permits quality assessment on a larger and more geographically distributed population base and the production of information sought by managers, purchasers, providers and regulators of health care.
LIST OF APPENDICES
APP. A - Software to set up sample for medical records collection APP. B - Software for pediatric asthma screening APP. C - Pediatric asthma report APP. D - Software for C-section screening APP. E - C-section report
The present invention relates to a data processing method and system for analyzing health care records and generating information in the form of statistical charts anal graphs, evaluations and recommendations suggesting changes for improving the quality of health care services received by a patient population through a health care benefit organization. In particular, the present invention relates to a quality screening and management system for organizing, describing, analyzing, evaluating and reporting on the quality of health care services received by an enrolled or defined population of health care beneficiaries.
BACKGROUND OF THE INVENTION
The system of medical health care delivery in the United States is facing a critical point in its evolution. The escalating cost of health care, marked variation in the practice patterns of physicians, the increasing number of uninsured or under-insured individuals and the dissatisfaction of the public with the current health care system in this country have all contributed to the crisis currently faced by health care benefit providers. The root of the current crisis is best analyzed from an historical perspective.
The structure of organizations responsible for providing medical insurance benefits has shifted over the course of time from local providers to more complex managed health care systems of providers. The administrative structure developed to support health care providers has also grown more complex and has ~~~~~~3 assumed oversight responsibilities. One of these responsibilities is the quality assessment of health care services.
Previously, if health care providers assessed the quality of health care services received by patients, they generally did so by "incident reporting"
in which quality problems were identified by isolated report or individual case inquiry.
Quality assessment with respect to medical practice patterns of physicians was based on the traditional method of peer review of medical records. These methods, however, are labor-intensive and inefficient. As health care organizations grew, new avenues for evaluating quality of care were explored.
More sophisticated data systems were developed to assist health care organizations, but these focused predominantly on the collection of financial data.
These systems were designed to track the cost of health care by reporting actual cost incurred. While these prior art systems performed adequately for these simpler accounting and administrative functions, they became increasingly inadequate to meet the needs of the more complex managed health care systems.
The prior art health care management systems lacked organized health care data bases and evaluation methods, which permit evaluation of comprehensive health care delivery. Purchasers, providers and administrators have lacked the ability to measure and identify quality of care problems with efficiency and inclusive of whole populations receiving services. In prior art health care management systems, quality issues were generally revealed by inference in conducting utilization reviews, case management or financial analysis or in restricted areas, such as inpatient care only. This is in contrast to the direct study of quality and/or access, two factors that are presently considered crucial to the proper evaluation of health care delivery systems, and in distinction to evaluating comprehensive health care spanning inpatient and outpatient services.
Management that is cost-effective, whether performed by physicians in direct patient care or administrators of managed health care systems, necessitates the collection and integration of information on the health care process, appropriateness of the medical intervention, and effectiveness, viewed in terms of outcomes. To maximize the availability and use of such information for large scale health care evaluation, it should be collected from standardized data. Through the use of such data, comparisons between actual clinical practice and authoritative practice guidelines can be made to identify opportunities to improve health care delivery and health outcomes.
Current practices of quality of care assessment depend primarily on the review and evaluation of medical records, which is costly, intrusive and not conducive to the evaluation and reporting of care delivered to large patient populations, except on a sampling basis. Medical records also may not include full pertinent information on utilization of vital services, such as laboratory or pharmacy services. In addition, current practice often focuses on placing blame on the provider, which fosters resistance by physicians to quality of care assessments, and neglects the need to consider the role of patients, purchasers and health care organizations in quality of health care. Further, current practices concentrate on ..
merely monitoring performance without giving sufficient attention to concrete steps for improving the quality of care received by patients.
The existence of managed health care systems providing reimbursement for health care services to medical professionals, hospitals and pharmacies has led to the building of large collections of data reflecting the payment (and in some cases, the denial of payment) of claims made by individuals who are members of a managed health care plan. However, because these data are collected for financial purposes, they have not been organized or coded in a fashion that permits them to be used readily for purposes other than cost analysis. In particular, these data have not usually been used as a source of information for evaluating the quality of health care provided. Yet these data are frequently maintained on computers and, for health care systems that have several years of experience with significant participant populations, these data report, on a relatively reliable basis, the occurrence of.a large number of health care services transactions for a wide variety of medical conditions, including inpatient, outpatient and pharmacy transactions.
A quality of health care screening system designed for complex managed health care systems, using the significant historical databases of claims records for the evaluation of and reporting on appropriate delivery and receipt of health care services would be a decided improvement over the prior art.
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2~~~~~3 SUMMARY OF THE INVENTION
The problems outlined above are in large measure solved by the quality screening and evaluation system in accordance with the present invention.
The quality screening method in accordance with the present invention uses clinically meaningful indicators to define standards for and monitor the quality of health care received by a defined population. By analysis of computerized data, the method identifies areas with quality improvement potential for appropriate follow-up actions.
The quality screening and evaluation system in accordance with present invention defines a health care condition in terms of a set of predetermined condition criteria; uses the condition criteria to analyze a health care claims data base linking inpatient and outpatient, pharmacy and health plan enrollee records and identify a population of individuals who meet the predetermined condition criteria; defines quality of care criteria for the specific medical condition;
compares the quality of care criteria against the health care claims data base for the identified population; and develops a set of prescriptive and descriptive reports based on that comparison for improving health care delivery. The claims data base for the identified population can be supplemented by data obtained from medical records to provide a more detailed evaluation.
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'"~ 2~~~~~3 BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a block diagram schematically illustrating a data processing system in accordance with the present invention.
FIG. 2 is a flow chart depicting the overall operation of the method of the present invention.
FIG. 3 is a flow chart depicting the data analysis details of the present invention with respect t~ a specific health care condition in the nature of a disease or organic dysfunction.
FIG. 4 is a flow chart depicting the data analysis details of the present invention with respect to a specific health care condition not in the nature of a disease or organic dysfunction.
DETAILED DESCRIPTTON OF THE DRAWINGS
Referring to Figure 1, a data processing system 100 for evaluating the quality of health care received by a defined population is shown in block diagram form. A mainframe central processing unit (CPU) I01 is connected to a magnetic disk memory storage unit 110 and a secondary memory device 120, such as a magnetic tape drive, used to input data to the system 100 for eventual storage on the magnetic disk unit 110. Also connected to the CPU 101 is a printer 130 for producing hard copy reports reflecting the analysis performed by the system 100. A
personal computer processing unit 150 is connected to the mainframe CPU 101 via a data communications line 140 for the purpose of entering data, such as medical records, ..~ 2~~3~53 performing analysis on the medical records or other data and for formatting reports.
Connected to the personal computer 150 is a magnetic disk storage unit 160 for storing medical records or other data entered and a printer 170 for producing hard copy reports and graphics reporting the results of the analysis performed by the system 100 for delivery to customers.
Stored in the magnetic disk memory units 110 and 160 are software instructions that serve as the operating systems and the application software.
These together direct the operations of the CPU 101 and the personal computer 150 on the data in the disk memory units 110 and 160. The application software contains the computer language instructions that cause the system to perform the methods of the present invention.
In the preferred embodiment, the application software is written primarily in a language called SAS, Version 6.06. Certain data entry functions are, however, implemented in dBase IV language. The CPU 101 is preferably an IBM
mainframe utilizing the VM/CMS operating system. The personal computer 150 is preferably an IBM PS/2 utilizing the OS/2 operating system. The structure of the application software and the methods of the present invention are depicted most readily in flow chart form. Figure 2 shows a flow chart depicting the overall operation of the method of the present invention. Figure 3 is a flow chart depicting the data analysis details of the present invention with respect to a specific health care condition in the nature of a disease or organic dysfunction. For purposes of illustration, Figure 3 shows a flow chart for the method of the present invention as ~- 20~3~~3 applied to pediatric asthma. Figure 4 is a flow chart depicting the data analysis details of the present invention with respect to a specific health care condition not in the nature of a disease or organic dysfunction. For purposes of illustration, Figure 4 shows a flow chart for the method of the present invention as applied to caesarian sections. The particular health care conditions discussed in Figures 3 and 4 are illustrative examples only and, as will become clearer in the discussion below, the method of the present invention can be used to address many other health care conditions in a similar manner.
t'he flow charts of Figures 2-4 have the following symbols:
circle - connector (null operation) ellipse - start or stop terminator rectangle - computer process trapezoid - manual process diamond - decision or test rectangle with ctuved bottom - document output rectangle with curved sides - disk file Overall Process Logic Flow a. Initial Screening Analysis Turning now to Figure 2, the overall process of the present invention can be explained. The process will typically be performed at the request of a customer that is a health maintenance organization, indemnity insurer (e.g., Blue Cross), a large, self-insured employer group or a government program (e.g., 2053~J~
Medicaid). Such customers administrate one or more health care benefit plans .~ervicing individuals who are enrolled in a plan. At the start 1, the first step 3 is to obtain the customer specific parameters, such as what time period the customer wishes to ar~alyz~e or whether the customer wants to have some data broken down by particular providers or other grouping variables. The next step is to update the system options and parameters using the customer specifications. Thereafter, the system 100 obtains and loads 5 the customer data, usually consisting of the customer's already-computerized health care claims data for a specified period, together with enrollment data and health care provider data. Typically this information can be provided on magnetic tape and is easily placed in the magnetic disk unit 110 of the systeir. 100 by means of a magnetic tape drive 120.
The enrollment data is extracted 7 so as to identify the enrollees served by the customer that meet a predefined enrollment criterion, such as that each enrollee has been enrolled in the health plan for a specified period. T'he resulting enrollment data 9 contains one record per enrollee. Next, the relevant claims data are extracted 11 from the complete customer data base and are configured through linkages to produce the necessary health records. This involves selecting only the claims data for the time period being examined. It should be noted that the claims data usually includes a code identifying a defined health care procedure or service.
T'he claims data will include claims records for medical professional services (outpatient records), claims records for hospital services 13 (inpatient records) and IO
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claims records fur pharmacy purchases 14 (pharmacy records).' (A particularly focused analysis may not have data of all three types.) Ideally, the customer's data base will contain all of the following data fields:
Enrollment/Membership Data 1.R Unique Member Identifier 2.R Enrollment Date 3.R Expiration Date 4.R Birt.'~ Date 5. R Gender 6. Patient Name (only if a medical record review is requested) 7. Medicare Membership Indicator 8. Medicaid Membership Indicator 9. Zip code Medical Professional Claims Data I.R Unique Member Identifier 2.R Date of Service 3.R Provider Type Code (for physicians this must indicate medical specialty) 4. Unique Provider Identifier (required if Provider Type is not available on the claims record or if medical record review is anticipated) 5. R Diagnosis Code (ICD-9) 6. R Procedure Code (CPT-4) 7.R Place of Service Code (e.g., hospital, doctor's office) Hospital (Inpatient/Emergency Room) Claims Data 1.R Unique Member Identifier 2.R Admission Date 3. Discharge Date 4.R Provider Type Code (for in-patient claims this must indicate type of facility.
e.g., hospital, emergency room, urgi-center) 5. Unique Provider Identifier (required if Provider Type is not available on the claims record or if in-patient medical record review is anticipated) 6. R Ptace of Service Code 7. Unique Admission Identifier 8.R Diagnosis Code (ICD-9) ~~~3~~~
9. Revenue Code (i.e., from UB82 codes) Pharmaceutical Claims Data (not used for all conditions) 1.R Unique Member Identifier 2. R Drug Codes 3. Route of .Administration 4. Quantity of Drug S.R Filled Date The minirnum required fields for the present implementation of the invention are marked with an "R" in the above data definitions.
"CPT-4" in the medical professional data refers to an edition of the Current Procedure Terminology code, published by the American Medical Association. In the medical professional data and the hospital data, "ICD-9" refers to an edition of the International Classification of Diseases; "UB82" refers to revenue codes published by Health Care Finance Administration; and Place of Service Codes are those promulgated by the American Medical Association. Alternative coding systems can be used, based on a code conversion table associating the preceding codes with the alternative coding system.
If the customer desires, provider-specific data is also extracted 16 from the customer data, permitting the later analysis to be broken down by the particular provider of services or products, which may be a particular doctor, clink or hospital.
(The provider data also can be used to identify the possible sources of medical records.) The provider data fields utilized are as follows:
Provider Data (e.g. Physiaan Hospital, Urgi-Center) 1. Unique Provider Identifier 2. Provider Type Code (if not in Claims Files) 20~3~~3 3. Name R.M
4.R~LiStreet Address S.RM City 6. State R.'Li 7. Zip Code R.'~rt 8. Area Code R.M
9.RM Phone Number Additional fields required if a medical record review is to be undertaken are marked with an "RM".
The resulting files are merged 19 to produce uncorrected master files 21. Because claims data are not totally "clean", it will typically be necessary to exclude duplicate claims 23 and claims that have been reversed through the claims adjudication process (coordination of benefits, subrogation, clerical errors).
This produces a master file 25 of health care claims records. No adjustment is performed for claims lag. It is assumed that a customer will not forward data for analysis until the claims have been sufficiently processed for the period of study desired.
At this point the health care claims records are ready to be analyzed for indicators of quality. But this analysis requires two further preliminary steps: (1) defining at least one health care condition in terms of health care events reportable in health care claims records; and (2) defining health care quality criteria for each defined health care condition, also in terms of health care events reportable in health care claims records. This must be done in advance of the analysis of the master file 25 of health care claims records. The reason that it is necessary to define a health care condition is that quality measurements are specific to discrete health care conditions: what a provider should do obviously depends on the member's condition, the symptoms, diagnosis or the health care status (e.g., pregnancy). More ,.....
important for this invention, individual health care claims data items accumulated ir, the normal curse of business by a health care management entity may or may not include a direct and specific diagnosis of the particular health care condition st:ffered by an enrollee or the particular health care condition that is of interest from a quality measurement viewpoint. Even if a diagnosis is present in claims records, it is not necessarily valid to take it at face value. The claims data include one or more codes identifying specific treatment events or outcomes, such as, an office visit, a blood test, a CAT scan, a surgical procedure, a drug prescription, a hospital stay with charges for drugs, X-rays or specific therapeutic regimens, a hospital readmission or a death. It is a selection of such data items and their relationships that becomes the definition of a particular health pare condition.
For purposes of the present invention "health care condition" is broadly defined to mean a condition in the nature of a disease or an organic dysfunction or a "condition" that might also be viewed as a status or an outcome. In its present implementation, the following conditions characterized as diseases or organic dysfunctions or outcomes are addressed: diabetes mellitus, pediatric asthma, hypertension, breast cancer, hospital readmissions and ambulatory surgical complications. The following conditions characterized as status-based are also addressed: pediatric immunizations, breast cancer screening, cervical cancer screening, caesarian section and prenatal care. The point of each condition is to provide a focus for analysis of quality of care, not for medical diagnosis.
Given this orientation, the preceding conditions were selected for implementation, because 2~~3~5~
each can be associated with a cluster of health care events that can be related to health care quality criteria as well as with data that can be used to identify a population having the condition. A proper course of testing and treatment is part of quality care to maximize the health of a person with diabetes mellitus. To protect the health of children with certain age status, a prescribed set of immunizations is agreed to be necessary. To protect the health of women in various age groups and/or meeting other status criteria, certain screening tests and examinations, at prescribed intervals, are agreed to be necessary. To protect the health of newborns and their mothers certain prenatal care is agreed to be advisable. ' As will be seen below, defining some health care conditions for purposes of quality measurement is easier than defining others. The caesarian section condition is usually easy to define, because there will often be a specific claims code when the surgical procedure is performed. However, in some circumstances, there will not be a specific claims code and the condition will be deduced from the presence of a combination of claims codes, perhaps including amniocentesis, frequency of prenatal visits and specific anesthesia or surgery events.
Pediatric asthma is an example of a more subtle condition, and, as will be shown, is defined in terms of a set of medical claims codes, hospital claims codes and pharmacy claims codes with specified Boolean (logical) relationships.
Selecting the codes for such conditions can be difficult, because they are not always diagnosed the same way and may be diagnosed only after repeated visits to a health care provider or may not be diagnosed at all. The code selection definitional effort resembles the 2~~3~~~
diagnostic process performed by a health care professional who studies the medical record of a new patient. That is, defining such a condition is a complex logical process requiring extensive clinical and claims data knowledge to implement the definition in a software algorithm.
For all of the conditions addressed by the present invention, it is necessary to define the health care condition of interest solely in terms of data elements reportable in health care claims records. 7 his is a different task than if the entire medical record were a~railable, with its greatzr range of terminology and information. As noted above, in the preferred embodiment the claims data include outpatient records, inpatient records and pharmacy records. Thus, data from all of the record sources can be used to make a health care condition definition.
This is significant, because provider practice patterns and enrollee behaviors may cause a clear picture of the enrollee's health care status to emerge only when data from all of these sources is considered.
Once a specific definition is created for a health care condition of interest for quality screening, this definition is implemented as a series of logically linked compare operations in the software. Applying the definition of the health care condition to the claims records becomes a matter of performing the compare operations and executing the Boolean logic implicit in the definition (and explicit in the software) to identify those enrollees having claims records in the claims data base that meet the definition. The enrollees so identified are the subset of the universe of health care system enrollees that becomes the focus of the further '"" 2~~~~~3 analysis to determine whether this subset, identified as having the defined health care condition, received quality health care for that condition.
The second prerequisite for analysis of the claims master files 25 is defining health care quality criteria for each defined health care condition, also in terms of health care events reportable in health care claims records. Here, the health care system manager must rely on knowledge sources credible to practicing clinicians. Typically, study of the condition will reveal that quality of care is indicated by the absence of certain kinds of health care claims (e.g., an emergency room visit for a pediatric asthma patient, hospitalization for diabetes mellitus, reoccurrence of breast cancer or other adverse events) and the presence of other kinds of health care claims (e.g., annual inoculations, laboratory testing at specific intervals, visits to appropriate medical/surgical specialists, prescription of specific medications). Specific evaluation criteria are developed from clinical or health services literature -and research, from standards developed by the professional societies and through private or public (federal government) task forces. As with the definition of the health care condition of interest, the health care quality criteria must be implemented in the software as a set of physician office claims codes, hospital claims codes and pharmacy codes with specified Boolean relationships.
Returning to Figure 3, step 29 involves the application of the definitions for the health care condition to identify the population having that condition, followed by an analysis of the claims records for that population (a subset of the master files 25) under the defined quality care criteria. The enrollment data 11 2~~3~ ~3 is accessed in this process, as well. In general, the invention is implemented to examine one year of claims data, which may begin on any date in a year.
Analysis of an enrollee's claims records for the following conditions occurs only when the enrollee has been continuously enrolled for one year: diabetes mellitus, pediatric asthma, hypertension, breast cancer, and breast cancer screening. There is no one year continuous enrollment requirement when the following conditions are analyzed: cervical cancer screening, pediatric immunizations (ages birth to two and four to six), hospital readmission, ambulatory surgical complications and caesarian section. For the prenatal condition, the enrollment requirement is enrollment six months prior to delivery, but enrollment past the date of delivery is not required.
The result of the analysis in step 29 is a report that includes: charts and graphs 31 reporting statistically observed quality of care data in the population defined as having the health care condition of interest (e.g., a graph showing emergency room visits by patient age); a written analysis reporting, from a care quality viewpoint, statistical results considered worthy of highlighting 33, 35 (e.g., a report of use of a particular drug intervention and the occurrence of adverse events associated with the particular health care condition); and a report containing recommendations for actions to improve health care quality 37, 39 (e.g., a suggestion that physician guidelines be developed and promulgated stating that a specified laboratory test be performed annually).
Action recommendations to improve health care quality are produced for each condition studied. These recommendations are selected from a menu of -~ ~0~3J~3 nine quality management action categories developed based on a synthesis of the relevant research literature and management expertise. The nine categories are: (1) reporting the results of the quality analysis to physicians, (2) disseminating practice guidelines to physicians, (3) instituting condition-specific medical record flowsheets, (4) modifying reimbursement to physicians, (5) instituting provider discipline, (6) providing patient education and reminders, (7) establishing case management programs, (8) improving patient access to rare, and (9) changing the benefit design.
As can be seen, these actions are directed toward affecting the behavior not only of physicians, but also patients, purchasers or providers of benefits, and health care organizations. Each condition has a set of condition-specific action recommendations defined for it. The customer's report will include those recommendations from the set that are appropriate in view of the results of the analysis performed in step 29.
Analysis for multiple health care conditions takes place iteratively through the software at step 41, and the process just described, comprising steps 29, 31, 33, and 37 and producing charts and graphs 31 and reports 35, 39 is repeated, using the next health care condition definition to identify the population having that condition, followed by an analysis of the claims records for that population (a subset of the master files 25) under the defined quality care criteria for that next condition. After all th~ specified health care conditions have been processed in this manner, the reports for each condition are assembled 43 into a claims-based quality report 45 that is presented to the customer 47.
2~~3~W
b. Detailed Analysis with Medical Records Because it is recognized that a data base of health care claims, even if it includes data from medical professional services, hospital services and pharmacy services, may not have all the information available in other medical records maintained by the physician or other health care provider, the present invention provides as a supplement, additional methods to gather medical records and perform a more detailed analysis. At step 51, the system recognizes whether there is the need for detailed analysis. If no such need exists, no further data collection or analysis occurs. However, if a need for detailed analysis of any health care condition has been determined, then the population identified as having that condition is subjected to sampling 55 to determine for which enrollees additional medical records information will be collected. Both the master claims data files 27 and provider data I8 are used for this step. The determination of which members will have medical records collected for further analysis is based on varying criteria. For most health care conditions, medical records will be of interest for further study of the medical history if an enrollee has exhibited some unfavorable outcome or unexplained deviation from the quality of care criteria. Such enrollees are in greatest need of intervention and the quality of the care they have received or will receive is of greater significance. For instance, it may be desirable to focus detailed analysis on enrollees having more than a specified number of emergency room visits in a year or those for whom there is a deviation from the recommended drug regimen. To select these members, a further sampling definition is developed..
It is ,~ ~ ~~~~J~3 implemented in software as a set of medical claims codes, hospital claims codes and pharmacy codex with specified Boolean relationships. If the member population remaining after application of these criteria is too large to be economic, it may be reduced in size by appropriate statistical sampling methods. The result of these steps is to define a subset of the population recognized as having the particular medical condition of interest to be subjected to further, more detailed study, based on the additional information available in medical records. Appendix A contains software used to set up the sample for whi.:h medical records data is collec:~ed and to identify the appropriate source for this data (i.e., provider location).
To initiate the gathering of medical records data, a request letter to a physician or other provider is generated. Selecting the appropriate provider to contact may be important, because there may be multiple sources of medical records, some of which will be inadequate for evaluation. The appropriate provider must be selected to receive the letter and be the unit for analysis. In some cases, a second source may also be selected. With the provider's consent, the medical records are abstracted 59 with a particular focus on events that relate to the particular health care condition under study, resulting in a completed medical records abstract form 61. This abstracted information is then entered into the system 63, via personal computer 150 to produce a medical record abstract data file 65. Additional and more highly clinically specific quality of care criteria are then used to analyze the medical record file, in a manner similar to the way the claims data was analyzed.
2o~3J~~
One difference is that the medical record may introduce additional data for medical, hospital or pharmacy activities that can be used to implement the quality care definition in the software. As can be seen, using the present invention means that only a relatively limited amount of medical records data need be assembled for health care quality analysis. Because a condition definition has been employed to identify an enrollee group of interest, only medical records for those enrollees having the condition under analysis are of interest. Moreover, those portions of the medical records relevant to the condition under analysis are abstracted. Thus, the volume of data to be analyzed is kept manageable and cost efficient.
The result of the additional, detailed analysis is charts and graphs reporting statistically observed data in the population defined as having the health care condition of interest 69 and a report containing recommendations for actions to improve health care quality 71, 73. If detailed analysis of medical records is specified for multiple health care conditions, then the preceding steps are repeated until charts and graphs reporting statistically observed data 69 and a report containing recommendations for actions to improve health care quality 71, 73 are developed for each health care condition. (These are drawn from the same set of condition-specific quality management actions as discussed above in connection with steps 37, 39.) After all the specified health care conditions have been processed in this manner, the reports for each condition are assembled 77 into a detail level report 79 that is presented to the customer 81, and the process ends 83.
c. Examples for Particular Conditions To further and more specifically explain the present invention, the data processing steps represented by steps 29 and 31 in Figure 2 will be explained by way of two examples of specific health care conditions for which the present invention has been implemented.
Example 1 - Pediatric Asthma To demonstrate further specifics about the present invention, reference is made to Figure 3, which represents further details about the analysis and development of data for steps 29 and 3I in Figure 2 when the defined health care condition to be studied is pediatric asthma. Still further details about the way in which pediatric asthma health care quality issues are analyzed ir, accordance with the present invention can be found in Appendix B, which is the SAS source code corresponding to steps 29 and 31 in Figure 2 and to Figure 3.
The definition of the pediatric asthma condition used by the system is embodied in steps 303, 305, 307 and 309 of Figure 3, which determine the presence or absence of certain data in the claims data master file 25. If the claims data are coded in ICD-9 (International Code of Diseases, 9th Edition) form, the criteria may be expressed as follows. A member is defined as having pediatric asthma if. he or she is under 19 years of age, is continuously enrolled for the year under study and meets one of the following criteria:
1. At least one hospitalization for asthma (IDC-9 = 493.xx); or ~- ~OJ3~~3 2. At least one emergency room visit for asthma (IDC-9 = 493.xx); or 3. Two or more doctor visits for asthma or asthma related conditions, provided that at least one of the visits is for asthira specifically, determined based on the following codes: asthma (493.xx), croup (464.4), acute bronchitis and bronchitis (4b6.xx), allergic rhinitis (477.xx), unspecified bronchitis (490.xx) and chronic bronchitis (491.xx); or 4. Two or more pharmacy claims for asthma related drugs, at least 45 days apart: beta-2 adreric drugs; methyl xanthine drugs; and selected other bronchodilator related drugs lbeclomethasone, cromolyn, flunsolide) (Criteria 1, 2 and 3 show the ICD-9 code that must be found in order for the Qiteria to be satisfied. The "xx" following these codes means that only the first three digits of these five digit codes are compared to determine a match.) When the above pediatric asthma criteria are satisfied for any member, his or her name is~ added to the asthma member file list 313. The decision at step 311 ensures that the full claims data master file is searched for pediatric asthma cases.
That is, the available records, which comprehensively cover claims records for medical professional services, claims records for hospital services and claims records for pharmaceutical prescriptions, are searched. It has been found that evidence of the asthma condition may appear in only one of these three categories of records.
Yet a proper health care quality study of this condition must identify essentially all enrollees that have the condition, regardless of how the condition is reflected in the available claims records. For possible later analysis, a patient's record in the asthma 2~53~~~
member file list is flagged to indicate its inclusion in an adverse events and pharmaceuticals grouping. The asthma member file list 313 is then used in step to build a new file that is a subset of the claims data master file and contains claims data only for members meeting the pediatric asthma definition. This asthma master file 319 is then used to calculate a variety of statistics on health care events and to develop charts and graphs to present the aggregated and calculated data. The calculations and the resulting reports and graphs are detailed at steps 321-351 in Figure 3.
As noted previously, the asthma member list file 313 is flagged to indicate an adverse events and pharmaceutical grouping. At step 353 of Figure 3 the pharmaceutical asthma subset file is created and subjected to further processing at steps 355, 359, 363, 367. This processing results in the calculation of aggregate statistics of various kinds having to do with prescription drug use for the members identified as pediatric asthma patients. The calculations and the resulting charts are detailed at steps 353-371 of Figure 3.
Shown at Appendix C are examples of the kinds of reports and charts and graphs developed by the present invention when analyzing the pediatric asthma condition. These reports reflect an actual analysis from a health maintenance organization the identity has been deleted) and include:
- General explanation of the pediatric asthma quality review - Chart of demographics of children with asthma ~OJ3~53 - Pie graph of age distribution of pediatric asthma patients - Bar graph of frequency of adverse events - Chart of frequency of emergency room visits - Chart of frequency of hospital admissions - Bar graph of percent of children having an annual office visit for asthma, differen tiated by adverse event occurrence - Bar graph of average number of office visits - Chart of pulmonary function testing - Bar graph of influenza immunization - Chart of serum theophyline level monitoring - Charts of use of beta-agonists, cromolyn, theophylline and barbituates - Summary of key statistical findings - Quality management actions recommendations, including proposed medical record flow sheet for pediatric asthma patients In the present ,instance, the management actions recommendations include all those that are part of the condition-speafic set of action recommendations for pediatric asthma. In a report for another customer, only a subset of these might appear, because fewer corrective actions are necessary.
Example 2 - Caesarian Section To demonstrate further specifics about the present invention, reference is made to Figure 4, which represents further details about the analysis and development of data for steps 29 and 3I in Figure 2 when the defined health care condition to be studied is caesarian sections, Still further details about the way in 2~~3~~~
which caesarian section health care quality issues are analyzed in accordance with the present invention can be found in Appendix D, which is the SAS source code corresponding to steps 29 and 31 and to Figure 4.
The definition of the caesarian section condition used by the system is embodied in steps 405-421, which test for certain data in the claims data master file 403. At steps 405 and 407 a subset of the master file is created that includes all enrollees who were pregnant and thus potential candidates for a caesarian section birth (C-section). From this subject enrollees having miscarriages are deleted 409, producing a smaller working C-section file 41I. This file is divided 413 into a C-section births file 415 and a vaginal births file 417. These two files are then merged 419 to produce the births file 42I.
Although there is no agreement on an ideal C-section birth rate that would provide a health care quality measure, there is agreement that a C-section birth rate above the national average could indicate that health care providers are performing inappropriate C-section procedures. Accordingly, the health care quality definition implemented at steps 425-447 of Figure 4 involves calculation of overall C-section birth rates 425, charting that rate by comparison to the national norm and then charting C-section birth rates by age group 429 and by hospital 431-445.
Finally, a "trombone chart" 441 is produced that shows the C-section birth rate for individual hospitals, plotted against the average for all hospitals in the analysis and a curve showing the upper 95% confidence bound (based on statistical measures adjusting for sample size).
'~. 2~~~~~3 Shown at Appendix E are examples of the kinds of reports and charts and graphs developed by the present invention when analyzing the C-section condition. These reports reflect an actual analysis from a health maintenance organization (the identity has been deleted) and include:
- General explanation of C-section quality review - Bar graph of ~-section rate vs. national norm - Bar graph of C-section rates by age - '"Trombone graph" of C-section rates - Chart of C-section rates by hospital - Summary of key statistical findings - Quality management action recommendations -C-section medical record abstraction form and instructions (for more detailed analysis) To perform a detailed analysis beyond the level of claims-based quality evaluation, the medical record may be obtained. This would usually be performed in specific populations where the overall observed C-section rate was higher than expected.
Therefore, the objective would be to determine whether there were specific indications of medical need for a C-section justifying that the procedure was performed. Appendix E contains the medical record abstraction form and instructions. This data obtained from the medical record would be entered and analyzed in the software of the present invention.
~.
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d. Summary As can be seen from the preceding, the present invention involves a data processing system and analytic method that utilizes multiple sources of health care data to evaluate health care quality. The invention initially utilizes the health care claims data accumulated by a health care benefit organization as its enrollees utilize health care benefits. Specific health care conditions of interest are defined in terms of the claims data and these definitions are implemented in software logic to allow a subset of enrollees to be identified as having the health care condition of interest. The health care claims data for this subset are then analyzed in terms of health care quality criteria, developed from multiple expert clinical sources.
These criteria are also defined in terms of the claims data and implemented in software that develops statistical measures of health care quality. If desired, additional medical record data can be collected for the specific portion of the subset of enrollees identified as having the condition of interest. These additional medical records data supplement the claims data and allow additional, more detailed health care quality a~iteria to be defined. These criteria are analyzed against the additional data.
Further statistical measures of health care quality can then be developed.
After analysis of the original claims data and after analysis of the additional medical record data, descriptive and evaluative reports and recommendations on improving health care quality are developed and provided.
The invention combines at least three primary advantages to improve-over the prior art. First, it permits use to be made of the large claims data bases that a~. 20~35~~
are maintained by health care organizations, which in most cases are already in coanputerized form, permitting large scale health care quality analysis to be performed based on this claims data. Second, it'.imits the laborious and expensi~~e task of assembling medical records data for quality analysis to a population that has been screened and selected as having specific potential need for quality improvement (and is thus smaller than the entire universe of enrollees).
Third, by enabling evaluation of health care quality to be performed in a more standardized and efficient manner, through use of distinctly identified data elements in conjunction with discretely defined clinical algorithms, it permits quality assessment on a larger and more geographically distributed population base and the production of information sought by managers, purchasers, providers and regulators of health care.
LIST OF APPENDICES
APP. A - Software to set up sample for medical records collection APP. B - Software for pediatric asthma screening APP. C - Pediatric asthma report APP. D - Software for C-section screening APP. E - C-section report
Claims (23)
1. In a medical information system comprising a processing unit, at least one memory unit and means for entering information into said medical information system and for providing commands to said medical information system, a method of analyzing health care claims records for an enrolled population to assess quality of care received by enrollees having a specified health care condition and formulate action recommendations to improve care comprising:
(a) providing to said processing unit of said medical information system health care claims records for a selected enrollee population;
(b) defining in the medical information system at least one health care condition in terms of a specified logical relationship among a plurality of health care events relevant to diagnosis and reported in the health care claims records;
(c) identifying in the health care claims records those enrollees meeting the definition for said at least one health care condition;
(d) defining in the medical information system health care quality criteria for said at least one health care condition in terms of a plurality of health care events reported or reportable in the health care claims records, including at least one intervention based on practice guidelines and related to care for the at least one health care condition;
(e) comparing the health care quality criteria for said at least one health care condition to the health care claims records for at least a portion of those enrollees meeting the definition for said at least one health care condition; and (f) developing and outputting from said medical information system a health care quality report based on the comparison of step (e) and including action recommendations for improving health care quality.
(a) providing to said processing unit of said medical information system health care claims records for a selected enrollee population;
(b) defining in the medical information system at least one health care condition in terms of a specified logical relationship among a plurality of health care events relevant to diagnosis and reported in the health care claims records;
(c) identifying in the health care claims records those enrollees meeting the definition for said at least one health care condition;
(d) defining in the medical information system health care quality criteria for said at least one health care condition in terms of a plurality of health care events reported or reportable in the health care claims records, including at least one intervention based on practice guidelines and related to care for the at least one health care condition;
(e) comparing the health care quality criteria for said at least one health care condition to the health care claims records for at least a portion of those enrollees meeting the definition for said at least one health care condition; and (f) developing and outputting from said medical information system a health care quality report based on the comparison of step (e) and including action recommendations for improving health care quality.
2. The method of claim 1 wherein the step of providing health care claims records comprises providing records from a group consisting of: claims records for medical professional services, claims records for hospital services and claims records for pharmaceutical prescriptions.
3. The method of claim 1 wherein multiple health care conditions and corresponding health care quality criteria for said multiple health care conditions are defined.
4. The method of claim 1 further comprising the steps of:
(g) providing to said processing unit of said medical information system medical records for a selected enrollee population that is a subset of the enrollee population identified as meeting the definition for said at least one health care condition;
(h) defining health care quality criteria for said at least one health care condition also in terms of health care events reported or reportable in the medical records;
(i) comparing the health care quality criteria for said at least one health care condition to the medical records for at least some of those enrollees meeting the definition for said at least one health care condition; and (j) developing and outputting from said medical information system a report based on the comparison of step (i) as well as step (e) and including action recommendations for improving health care quality as defined by said health care quality criteria.
(g) providing to said processing unit of said medical information system medical records for a selected enrollee population that is a subset of the enrollee population identified as meeting the definition for said at least one health care condition;
(h) defining health care quality criteria for said at least one health care condition also in terms of health care events reported or reportable in the medical records;
(i) comparing the health care quality criteria for said at least one health care condition to the medical records for at least some of those enrollees meeting the definition for said at least one health care condition; and (j) developing and outputting from said medical information system a report based on the comparison of step (i) as well as step (e) and including action recommendations for improving health care quality as defined by said health care quality criteria.
5. The method of claim 1 wherein the step of defining at least one health care condition in terms of health care events relevant to diagnosis and reported in the health care claims records comprises defining a specific health care condition in the nature of a disease or organic dysfunction.
6. The method of claim 5 wherein the at least one health care condition is selected from a group consisting of:
pediatric asthma, diabetes mellitus, hypertension, and breast cancer.
pediatric asthma, diabetes mellitus, hypertension, and breast cancer.
7. The method of claim 1 wherein the step of defining at least one health care condition in terms of health care events relevant to diagnosis and reported in the health care claims records further comprises defining a specific health care condition not in the nature of a disease or organic dysfunction.
8. The method of claim 7 wherein the at least one health care condition is selected from a group consisting of:
prenatal care, caesarian section, breast cancer screening, cervical cancer screening and pediatric immunizations for a specified age group.
prenatal care, caesarian section, breast cancer screening, cervical cancer screening and pediatric immunizations for a specified age group.
9. The method of claim 1 wherein step (f) comprises developing and outputting from said medical information system a health care quality report that reports statistics on at least one adverse event as an indicator of a health care quality problem.
10. The method of claim 1 wherein step (f) comprises developing and outputting from said medical information system a health care quality report that reports a frequency of occurrence of at least one health care quality criterion.
11. In a medical information system comprising a processing unit, at least one memory unit and means for entering information into said medical information system and for providing commands to said medical information system, a method of analyzing health care claims records for an enrolled population to assess quality of care received by enrollees having a specified health care condition and formulate action recommendations to improve care comprising:
(a) providing to said processing unit of said medical information system health care claims records for a selected enrollee population, said claims records comprising claims records for medical professional services, claims records for hospital services and claims records for pharmaceutical prescriptions;
(b) defining in the medical information system at least one health care condition in terms of a specified logical relationship among a plurality of health care events relevant to diagnosis and reported in the health care claims records;
(c) identifying in the health care claims records those enrollees meeting the definition for said at least one health care condition;
(d) defining in the medical information system health care quality criteria for said at least one health care condition in terms of a plurality of health care events reported or reportable in the health care claims records, including at least one intervention based on practice guidelines and related to care for the at least one health care condition;
(e) comparing the health care quality criteria for said at least one health care condition to the health care claims records for at least a portion of those enrollees meeting the definition for said at least one health care condition; and (f) developing and outputting from said medical information system a health care quality report based on the comparison of step (e) and including action recommendations for improving health care quality as defined by said health care quality criteria.
(a) providing to said processing unit of said medical information system health care claims records for a selected enrollee population, said claims records comprising claims records for medical professional services, claims records for hospital services and claims records for pharmaceutical prescriptions;
(b) defining in the medical information system at least one health care condition in terms of a specified logical relationship among a plurality of health care events relevant to diagnosis and reported in the health care claims records;
(c) identifying in the health care claims records those enrollees meeting the definition for said at least one health care condition;
(d) defining in the medical information system health care quality criteria for said at least one health care condition in terms of a plurality of health care events reported or reportable in the health care claims records, including at least one intervention based on practice guidelines and related to care for the at least one health care condition;
(e) comparing the health care quality criteria for said at least one health care condition to the health care claims records for at least a portion of those enrollees meeting the definition for said at least one health care condition; and (f) developing and outputting from said medical information system a health care quality report based on the comparison of step (e) and including action recommendations for improving health care quality as defined by said health care quality criteria.
12. The method of claim 11 wherein multiple health care conditions and corresponding health care quality criteria for said multiple health care conditions are defined.
13. The method of claim 11 further comprising the steps of:
(g) providing to said processing unit of said medical information system medical records for a selected enrollee population that is a subset of the enrollee population identified as meeting the definition for said at least one health care condition;
(h) defining health care quality criteria for said at least one health care condition also in terms of health care events reported in the medical records;
(i) comparing the health care quality criteria for said at least one health care condition to the medical records for at least some of those enrollees meeting the definition for said at least one health care condition; and (j) developing and outputting from said medical information system a report based on the comparison of step (i) as well as step (e) and including action recommendations for improving health care quality as defined by said health care quality criteria.
(g) providing to said processing unit of said medical information system medical records for a selected enrollee population that is a subset of the enrollee population identified as meeting the definition for said at least one health care condition;
(h) defining health care quality criteria for said at least one health care condition also in terms of health care events reported in the medical records;
(i) comparing the health care quality criteria for said at least one health care condition to the medical records for at least some of those enrollees meeting the definition for said at least one health care condition; and (j) developing and outputting from said medical information system a report based on the comparison of step (i) as well as step (e) and including action recommendations for improving health care quality as defined by said health care quality criteria.
14. A medical information system for analyzing health care claims records for a health care benefit plan to assess quality of care received by plan members having a specified health care condition and formulate action recommendations to improve care comprising:
(a) a central processing unit;
(b) at least one memory unit connected to said central processing unit;
(c) means for providing to said processing unit health care claims records for a selected enrollee population;
(d) means for defining at least one health care condition in terms of a specified logical relationship among a plurality of health care events relevant to diagnosis and reported in the health care claims records;
(e) means for identifying in the health care claims records those enrollees meeting the definition for said at least one health care condition;
(f) means for defining health care quality criteria for said at least one health care condition in terms of a plurality of health care events reported or reportable in health care claims records, including at least one intervention based on practice guidelines related to care for the at least one health care condition;
(g) means for comparing the health care quality criteria for said at least one health care condition to the health care claims records for at least a portion of those enrollees meeting the definition for said at least one health care condition; and (h) means for developing and outputting from said medical information system a health care quality report based on the comparison performed by means (g) and including action recommendations for improving health care quality as defined by said health care quality criteria.
(a) a central processing unit;
(b) at least one memory unit connected to said central processing unit;
(c) means for providing to said processing unit health care claims records for a selected enrollee population;
(d) means for defining at least one health care condition in terms of a specified logical relationship among a plurality of health care events relevant to diagnosis and reported in the health care claims records;
(e) means for identifying in the health care claims records those enrollees meeting the definition for said at least one health care condition;
(f) means for defining health care quality criteria for said at least one health care condition in terms of a plurality of health care events reported or reportable in health care claims records, including at least one intervention based on practice guidelines related to care for the at least one health care condition;
(g) means for comparing the health care quality criteria for said at least one health care condition to the health care claims records for at least a portion of those enrollees meeting the definition for said at least one health care condition; and (h) means for developing and outputting from said medical information system a health care quality report based on the comparison performed by means (g) and including action recommendations for improving health care quality as defined by said health care quality criteria.
15. The system of claim 14 wherein the means for providing health care claims records comprises means for providing records from a group consisting of: claims records for medical professional services, claims records for hospital services and claims records for pharmaceutical prescriptions.
16. The system of claim 14 further comprising:
(i) means for providing to said processing unit of said medical information system medical records for a selected enrollee population that is a subset of the enrollee population identified as meeting the definition for said at least one health care condition;
(j) means for defining health care quality criteria for said at least one health care condition also in terms of health care events reported or reportable in the medical records;
(k) means for comparing the health care quality criteria for said at least one health care condition to the medical records for at least some of those enrollees meeting the definition for said at least one health care condition;
and (l) means for developing and outputting from said medical information system a report based on the comparison performed by means (k) as well as means (g) and including action recommendations for improving health care quality as defined by said health care quality criteria.
(i) means for providing to said processing unit of said medical information system medical records for a selected enrollee population that is a subset of the enrollee population identified as meeting the definition for said at least one health care condition;
(j) means for defining health care quality criteria for said at least one health care condition also in terms of health care events reported or reportable in the medical records;
(k) means for comparing the health care quality criteria for said at least one health care condition to the medical records for at least some of those enrollees meeting the definition for said at least one health care condition;
and (l) means for developing and outputting from said medical information system a report based on the comparison performed by means (k) as well as means (g) and including action recommendations for improving health care quality as defined by said health care quality criteria.
17. A medical information system for analyzing records for a health care benefit plan, wherein said medical information system assesses quality of care received by plan members having a specified health care condition and formulates action recommendations to improve care, said medical information system comprising:
(a) a processor;
(b) a database, accessible by said processor, wherein said database includes information from health care claim records for a selected enrollee population that is a subset of the enrollee population identified as meeting said definition for said at least one health care condition;
(c) a data storage medium accessible by the processor, wherein the data storage medium has a program stored on it, and wherein the program is configured to cause the processor to:
define at least one health care condition in terms of a specified logical relationship among a plurality of health care events relevant to diagnosis and reported or reportable in said health care claims records, define health care quality criteria in terms of a plurality of health care events reported or reportable in said health care claims records, including at least one intervention based on practice guidelines and related to care for said at least one health care condition, identify enrollees meeting said definition for said at least one health care condition, compare health care quality criteria for said at least one health care condition to said information from said health care claims records for at least a portion of those enrollees meeting said definition for said at least one health care condition, and formulate action recommendations for improving health care quality as defined by said health care quality criteria; and (d) an output device, connected to the processor, for outputting from said medical information system a health care quality report.
(a) a processor;
(b) a database, accessible by said processor, wherein said database includes information from health care claim records for a selected enrollee population that is a subset of the enrollee population identified as meeting said definition for said at least one health care condition;
(c) a data storage medium accessible by the processor, wherein the data storage medium has a program stored on it, and wherein the program is configured to cause the processor to:
define at least one health care condition in terms of a specified logical relationship among a plurality of health care events relevant to diagnosis and reported or reportable in said health care claims records, define health care quality criteria in terms of a plurality of health care events reported or reportable in said health care claims records, including at least one intervention based on practice guidelines and related to care for said at least one health care condition, identify enrollees meeting said definition for said at least one health care condition, compare health care quality criteria for said at least one health care condition to said information from said health care claims records for at least a portion of those enrollees meeting said definition for said at least one health care condition, and formulate action recommendations for improving health care quality as defined by said health care quality criteria; and (d) an output device, connected to the processor, for outputting from said medical information system a health care quality report.
18. A medical information system as claimed in claim 17, wherein said output device is a printer.
19. A medical information system as claimed in claim 17, wherein said output device is a computer display.
20. A medical information system as claimed in claim 17, wherein said claims database includes information from said health care claims records for medical professional services;
information from said health care claims records for hospital services; and information from said health care claims records for pharmaceutical prescriptions.
information from said health care claims records for hospital services; and information from said health care claims records for pharmaceutical prescriptions.
21. The system of claim 17, wherein said data medium includes at least one random access memory device.
22. The system of claim 17, wherein said data medium includes at least one magnetic media disk.
23. A data storage medium for use with a processor that accesses a database of information from health care claim records for an enrolled population, wherein the data storage medium has a program stored on it that causes the processor to:
(a) define at least one health care condition in terms of a specified logical relationship among a plurality of health care events relevant to diagnosis and reported or reportable in said health care claims records;
(b) define health care quality criteria in terms of a plurality of health care events reported or reportable in said health care claims records, including at least one intervention based on practice guidelines and related to care for said at least one health care condition;
(c) identify enrollees meeting said definition for said at least one health care condition;
(d) compare health care quality criteria for said at least one health care condition to said information from said health care claims records for at least a portion of those enrollees meeting said definition for said at least one health care condition; and (e) formulate action recommendations for improving health care quality as defined by said health care quality criteria.
(a) define at least one health care condition in terms of a specified logical relationship among a plurality of health care events relevant to diagnosis and reported or reportable in said health care claims records;
(b) define health care quality criteria in terms of a plurality of health care events reported or reportable in said health care claims records, including at least one intervention based on practice guidelines and related to care for said at least one health care condition;
(c) identify enrollees meeting said definition for said at least one health care condition;
(d) compare health care quality criteria for said at least one health care condition to said information from said health care claims records for at least a portion of those enrollees meeting said definition for said at least one health care condition; and (e) formulate action recommendations for improving health care quality as defined by said health care quality criteria.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US07/739,629 US5544044A (en) | 1991-08-02 | 1991-08-02 | Method for evaluation of health care quality |
| US07/739,629 | 1991-08-02 |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CA2053553A1 CA2053553A1 (en) | 1993-02-03 |
| CA2053553C true CA2053553C (en) | 2001-12-18 |
Family
ID=24973154
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CA002053553A Expired - Lifetime CA2053553C (en) | 1991-08-02 | 1991-10-16 | Method for evaluation of health care quality |
Country Status (2)
| Country | Link |
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| US (1) | US5544044A (en) |
| CA (1) | CA2053553C (en) |
Families Citing this family (172)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20010011224A1 (en) * | 1995-06-07 | 2001-08-02 | Stephen James Brown | Modular microprocessor-based health monitoring system |
| US6119099A (en) * | 1997-03-21 | 2000-09-12 | Walker Asset Management Limited Partnership | Method and system for processing supplementary product sales at a point-of-sale terminal |
| US6267670B1 (en) | 1997-03-21 | 2001-07-31 | Walker Digital, Llc | System and method for performing lottery ticket transactions utilizing point-of-sale terminals |
| US6012035A (en) * | 1993-07-08 | 2000-01-04 | Integral Business Services, Inc. | System and method for supporting delivery of health care |
| US7222079B1 (en) | 1994-06-23 | 2007-05-22 | Ingenix, Inc. | Method and system for generating statistically-based medical provider utilization profiles |
| US5557514A (en) | 1994-06-23 | 1996-09-17 | Medicode, Inc. | Method and system for generating statistically-based medical provider utilization profiles |
| US5946659A (en) * | 1995-02-28 | 1999-08-31 | Clinicomp International, Inc. | System and method for notification and access of patient care information being simultaneously entered |
| US6434531B1 (en) * | 1995-02-28 | 2002-08-13 | Clinicomp International, Inc. | Method and system for facilitating patient care plans |
| US5706441A (en) * | 1995-06-07 | 1998-01-06 | Cigna Health Corporation | Method and apparatus for objectively monitoring and assessing the performance of health-care providers |
| US5845254A (en) * | 1995-06-07 | 1998-12-01 | Cigna Health Corporation | Method and apparatus for objectively monitoring and assessing the performance of health-care providers based on the severity of sickness episodes treated by the providers |
| US5835897C1 (en) * | 1995-06-22 | 2002-02-19 | Symmetry Health Data Systems | Computer-implemented method for profiling medical claims |
| US5924073A (en) * | 1995-11-14 | 1999-07-13 | Beacon Patient Physician Association, Llc | System and method for assessing physician performance using robust multivariate techniques of statistical analysis |
| AU1262997A (en) * | 1996-02-12 | 1997-08-21 | Smithkline Beecham Corporation | Disease management method and system |
| US6108665A (en) * | 1997-07-03 | 2000-08-22 | The Psychological Corporation | System and method for optimizing behaviorial health care collection |
| US6067523A (en) * | 1997-07-03 | 2000-05-23 | The Psychological Corporation | System and method for reporting behavioral health care data |
| US5956689A (en) * | 1997-07-31 | 1999-09-21 | Accordant Health Services, Inc. | Systems, methods and computer program products for using event specificity to identify patients having a specified disease |
| US6195612B1 (en) * | 1998-01-05 | 2001-02-27 | Tama L. Pack-Harris | Pharmacy benefit management system and method of using same |
| US6061657A (en) * | 1998-02-18 | 2000-05-09 | Iameter, Incorporated | Techniques for estimating charges of delivering healthcare services that take complicating factors into account |
| US6117073A (en) * | 1998-03-02 | 2000-09-12 | Jones; Scott J. | Integrated emergency medical transportation database system |
| US6694298B1 (en) | 1998-04-02 | 2004-02-17 | Medco Health Solutions, Inc. | Computer implemented patient medication review system and process for the managed care, health care and/or pharmacy industry |
| US6064968A (en) * | 1998-08-25 | 2000-05-16 | Schanz; Stephen J. | Systems, methods and computer program products for identifying unique and common legal requirements for a regulated activity among multiple legal jurisdictions |
| US6338039B1 (en) | 1999-07-20 | 2002-01-08 | Michael Lonski | Method for automated collection of psychotherapy patient information and generating reports and treatment plans |
| WO2001027842A1 (en) * | 1999-10-12 | 2001-04-19 | Wellpartner, Inc. | Method, apparatus and system for providing health management resources and pharmacy services to consumers |
| US7904317B1 (en) | 1999-10-14 | 2011-03-08 | The TriZetto Group | Method and apparatus for repricing a reimbursement claim against a contract |
| US6879959B1 (en) * | 2000-01-21 | 2005-04-12 | Quality Care Solutions, Inc. | Method of adjudicating medical claims based on scores that determine medical procedure monetary values |
| US6941271B1 (en) * | 2000-02-15 | 2005-09-06 | James W. Soong | Method for accessing component fields of a patient record by applying access rules determined by the patient |
| US7395217B1 (en) * | 2000-02-17 | 2008-07-01 | P2P Link, Llc | Workers compensation information processing system |
| US7379885B1 (en) * | 2000-03-10 | 2008-05-27 | David S. Zakim | System and method for obtaining, processing and evaluating patient information for diagnosing disease and selecting treatment |
| US6957218B1 (en) | 2000-04-06 | 2005-10-18 | Medical Central Online | Method and system for creating a website for a healthcare provider |
| US8301468B2 (en) | 2000-05-15 | 2012-10-30 | Optuminsight, Inc. | System and method of drug disease matching |
| US8388530B2 (en) | 2000-05-30 | 2013-03-05 | Vladimir Shusterman | Personalized monitoring and healthcare information management using physiological basis functions |
| US7485095B2 (en) * | 2000-05-30 | 2009-02-03 | Vladimir Shusterman | Measurement and analysis of trends in physiological and/or health data |
| US9183351B2 (en) | 2000-05-30 | 2015-11-10 | Vladimir Shusterman | Mobile system with network-distributed data processing for biomedical applications |
| US7801591B1 (en) | 2000-05-30 | 2010-09-21 | Vladimir Shusterman | Digital healthcare information management |
| US6826536B1 (en) * | 2000-07-22 | 2004-11-30 | Bert Forman | Health care billing monitor system for detecting health care provider fraud |
| US20020035491A1 (en) * | 2000-09-21 | 2002-03-21 | Access Transport Services, Inc. | System and associated methods for providing claimant services with increased quality assurance |
| US20020091552A1 (en) * | 2000-09-21 | 2002-07-11 | Access Transport Services, Inc. | System and associated methods for providing claimant services and access to claimant records and reports via a computer network |
| US20020077994A1 (en) * | 2000-09-21 | 2002-06-20 | Access Transport Services, Inc. | System and associated methods for providing claimant services with prioritized dispatch |
| US7440904B2 (en) * | 2000-10-11 | 2008-10-21 | Malik M. Hanson | Method and system for generating personal/individual health records |
| US8260635B2 (en) * | 2000-10-11 | 2012-09-04 | Healthtrio Llc | System for communication of health care data |
| EP1328889A4 (en) * | 2000-10-11 | 2005-06-01 | Healthtrio Inc | System for communication of health care data |
| US8321239B2 (en) | 2000-10-11 | 2012-11-27 | Healthtrio Llc | System for communication of health care data |
| US7552063B1 (en) * | 2000-11-03 | 2009-06-23 | Quality Data Management, Inc. | Physician office viewpoint survey system and method |
| US7233905B1 (en) | 2000-11-06 | 2007-06-19 | Golden Hour Data Systems, Inc. | Billing modifier module for integrated emergency medical transportation database system |
| US7734481B1 (en) | 2000-11-06 | 2010-06-08 | Golden Hour Data Systems, Inc. | Compliance audit for integrated emergency medical transportation database system |
| US7668736B2 (en) * | 2000-11-06 | 2010-02-23 | Golden Hour Data Systems, Inc. | Integrated emergency medical transportion database and virtual private network system |
| US7778849B1 (en) | 2000-11-06 | 2010-08-17 | Golden Hour Data Systems, Inc. | Data accuracy filter for integrated emergency medical transportation database system |
| US7392201B1 (en) | 2000-11-15 | 2008-06-24 | Trurisk, Llc | Insurance claim forecasting system |
| AU2002225659A1 (en) | 2000-11-21 | 2002-06-03 | Myhealthbank, Inc. | Health plan management method and apparatus |
| US20020069085A1 (en) * | 2000-12-05 | 2002-06-06 | Patientwise Corporation | System and method for purchasing health-related services |
| US6952695B1 (en) * | 2001-05-15 | 2005-10-04 | Global Safety Surveillance, Inc. | Spontaneous adverse events reporting |
| US8013768B2 (en) * | 2001-06-08 | 2011-09-06 | Broadcom Corporation | Integrated upstream amplifier for cable modems and cable set-top boxes |
| US7493264B1 (en) | 2001-06-11 | 2009-02-17 | Medco Health Solutions, Inc, | Method of care assessment and health management |
| DE10128521A1 (en) * | 2001-06-13 | 2003-01-02 | Siemens Ag | Procedure for monitoring telemedical health services |
| EP1320322A1 (en) * | 2001-08-20 | 2003-06-25 | Inverness Medical Limited | Wireless diabetes management devices and methods for using the same |
| US7505916B1 (en) | 2001-10-01 | 2009-03-17 | Lhc Group, Inc. | System and method for allocating home health services |
| US7756728B2 (en) * | 2001-10-31 | 2010-07-13 | Siemens Medical Solutions Usa, Inc. | Healthcare system and user interface for consolidating patient related information from different sources |
| US20030130871A1 (en) * | 2001-11-02 | 2003-07-10 | Rao R. Bharat | Patient data mining for clinical trials |
| US7457731B2 (en) * | 2001-12-14 | 2008-11-25 | Siemens Medical Solutions Usa, Inc. | Early detection of disease outbreak using electronic patient data to reduce public health threat from bio-terrorism |
| US20030163349A1 (en) * | 2002-02-28 | 2003-08-28 | Pacificare Health Systems, Inc. | Quality rating tool for the health care industry |
| US7490049B2 (en) * | 2002-03-29 | 2009-02-10 | Medco Health Solutions, Inc. | Patient oriented point of care system and method |
| AU2003237900A1 (en) * | 2002-05-16 | 2003-12-02 | Ndchealth Corporation | Systems and methods for identifying fraud and abuse in prescription claims |
| US7680086B2 (en) | 2002-09-09 | 2010-03-16 | Siemens Canada Limited | Wireless local area network with clients having extended freedom of movement |
| US7716068B2 (en) * | 2002-09-25 | 2010-05-11 | Mckesson Financial Holdings Limited | Systems and methods for look-alike sound-alike medication error messaging |
| US20040088190A1 (en) * | 2002-09-30 | 2004-05-06 | Timmons Gina L. | Method for improving the accuracy of transaction data |
| US20040073460A1 (en) * | 2002-10-01 | 2004-04-15 | Erwin W. Gary | Method for managing the healthcare of members of a population |
| US7698155B1 (en) * | 2002-11-29 | 2010-04-13 | Ingenix, Inc. | System for determining a disease category probability for a healthcare plan member |
| US7725330B2 (en) * | 2002-12-03 | 2010-05-25 | Siemens Medical Solutions Usa, Inc. | Systems and methods for automated extraction and processing of billing information in patient records |
| US8460243B2 (en) | 2003-06-10 | 2013-06-11 | Abbott Diabetes Care Inc. | Glucose measuring module and insulin pump combination |
| US7722536B2 (en) | 2003-07-15 | 2010-05-25 | Abbott Diabetes Care Inc. | Glucose measuring device integrated into a holster for a personal area network device |
| US20050086080A1 (en) * | 2003-07-31 | 2005-04-21 | Blue Cross Blue Shield Of Minnesota | Healthcare consumer information tool |
| WO2005015451A1 (en) * | 2003-08-12 | 2005-02-17 | Lms Medical Systems Ltd. | Method and apparatus for evaluating variations between health care service providers |
| US9058629B2 (en) | 2003-10-17 | 2015-06-16 | Optuminsight, Inc. | System and method for assessing healthcare risks |
| US8340981B1 (en) | 2004-03-02 | 2012-12-25 | Cave Consulting Group, Inc. | Method, system, and computer program product for physician efficiency measurement and patient health risk stratification utilizing variable windows for episode creation |
| IL161263A0 (en) * | 2004-04-02 | 2004-09-27 | Crossix Solutions Llc | A privacy preserving data-mining protocol |
| US20050261944A1 (en) * | 2004-05-24 | 2005-11-24 | Rosenberger Ronald L | Method and apparatus for detecting the erroneous processing and adjudication of health care claims |
| US20060010098A1 (en) | 2004-06-04 | 2006-01-12 | Goodnow Timothy T | Diabetes care host-client architecture and data management system |
| GB2415273A (en) * | 2004-06-19 | 2005-12-21 | Foster Ltd Dr | Real time monitoring system |
| EP1782348A1 (en) * | 2004-06-28 | 2007-05-09 | Accenture Global Services GmbH | Direct connectivity system for healthcare administrative transactions |
| US20060074519A1 (en) * | 2004-08-27 | 2006-04-06 | Barker Kenneth N | Medication accuracy comparison system |
| WO2006036660A2 (en) * | 2004-09-27 | 2006-04-06 | Roger Cook | Moving ornamental design element |
| US8768729B2 (en) | 2004-10-14 | 2014-07-01 | Trizetto Corporation | System and method for using a first electronic representation of contract terms for generating a second electronic representation of the contract terms |
| ITBO20050002A1 (en) * | 2005-01-04 | 2006-07-05 | Giacomo Vespasiani | METHOD AND SYSTEM FOR INTERACTIVE MANAGEMENT OF DATA CONCERNING AN INSULIN THERAPY IN SELF-CONTROL FOR A DIABETIC PATIENT |
| US8050945B2 (en) * | 2005-01-06 | 2011-11-01 | Cerner Innovation, Inc. | Computerized system and methods of adjudicating medical appropriateness |
| US7870009B2 (en) * | 2005-01-06 | 2011-01-11 | Cerner Innovation, Inc. | Computerized system and methods for generating and processing integrated transactions for healthcare services |
| US7881950B2 (en) * | 2005-01-06 | 2011-02-01 | Cerner Innovation, Inc. | Computerized system and methods for adjudicating and automatically reimbursing care providers |
| US7801744B2 (en) * | 2005-01-06 | 2010-09-21 | Cerner Innovation, Inc. | Computerized system and methods for adjudicating and reimbursing for healthcare services based on quality |
| US7443303B2 (en) | 2005-01-10 | 2008-10-28 | Hill-Rom Services, Inc. | System and method for managing workflow |
| US20060190295A1 (en) * | 2005-02-22 | 2006-08-24 | Richard Merkin | Systems and methods for assessing and optimizing healthcare administration |
| US7640073B2 (en) * | 2005-04-14 | 2009-12-29 | Jeld-Wen, Inc. | Systems and methods of identifying and manipulating objects |
| US8615409B1 (en) | 2005-04-15 | 2013-12-24 | Recovery Data-Connect, L.L.C. | System and method for identification, perfection, collection, and valuation of third-party claims including subrogation claims |
| US20060241972A1 (en) * | 2005-04-26 | 2006-10-26 | Lang Robert G | Medical outcomes systems |
| US20080275731A1 (en) * | 2005-05-18 | 2008-11-06 | Rao R Bharat | Patient data mining improvements |
| US8321283B2 (en) | 2005-05-27 | 2012-11-27 | Per-Se Technologies | Systems and methods for alerting pharmacies of formulary alternatives |
| WO2006130658A1 (en) * | 2005-05-31 | 2006-12-07 | Siemens Medical Solutions Usa, Inc. | System and method for data sensitive filtering of patient demographic record queries |
| US7555438B2 (en) * | 2005-07-21 | 2009-06-30 | Trurisk, Llc | Computerized medical modeling of group life insurance using medical claims data |
| US7555439B1 (en) | 2005-07-21 | 2009-06-30 | Trurisk, Llc | Computerized medical underwriting of group life insurance using medical claims data |
| US7664662B1 (en) | 2006-03-16 | 2010-02-16 | Trurisk Llc | Computerized medical modeling of group life and disability insurance using medical claims data |
| US7818181B2 (en) * | 2005-10-31 | 2010-10-19 | Focused Medical Analytics Llc | Medical practice pattern tool |
| US7406453B2 (en) * | 2005-11-04 | 2008-07-29 | Microsoft Corporation | Large-scale information collection and mining |
| US20070112597A1 (en) * | 2005-11-04 | 2007-05-17 | Microsoft Corporation | Monetizing large-scale information collection and mining |
| US20070162303A1 (en) | 2005-12-08 | 2007-07-12 | Ndchealth Corporation | Systems and Methods for Shifting Prescription Market Share by Presenting Pricing Differentials for Therapeutic Alternatives |
| US7249040B1 (en) | 2006-03-16 | 2007-07-24 | Trurisk, L.L.C. | Computerized medical underwriting of group life and disability insurance using medical claims data |
| US20070219824A1 (en) * | 2006-03-17 | 2007-09-20 | Jean Rawlings | System and method for identifying and analyzing patterns or aberrations in healthcare claims |
| US20080033750A1 (en) * | 2006-06-02 | 2008-02-07 | The Trizetto Group, Inc. | Enhanced systems and methods for processing of healthcare information |
| US8577933B2 (en) * | 2006-08-02 | 2013-11-05 | Crossix Solutions Inc. | Double blinded privacy-safe distributed data mining protocol |
| US20080065415A1 (en) * | 2006-09-08 | 2008-03-13 | Athenahealth, Inc. | Medical Practice Benchmarking |
| US20080294463A1 (en) * | 2007-01-26 | 2008-11-27 | Cerner Innovation, Inc. | System-determined indication for facilitating the conversion of medication claims to active medications |
| US20080189133A1 (en) * | 2007-02-01 | 2008-08-07 | Asset Health, Inc. | Health care education systems |
| US20090070199A1 (en) * | 2007-06-26 | 2009-03-12 | Adult-Care.Org. Inc. | Adult care information system and method |
| US8069080B2 (en) | 2007-11-14 | 2011-11-29 | Ingenix, Inc. | Methods for generating healthcare provider quality and cost rating data |
| US20090164376A1 (en) * | 2007-12-20 | 2009-06-25 | Mckesson Financial Holdings Limited | Systems and Methods for Controlled Substance Prescription Monitoring Via Real Time Claims Network |
| US8635083B1 (en) | 2008-04-02 | 2014-01-21 | Mckesson Financial Holdings | Systems and methods for facilitating the establishment of pharmaceutical rebate agreements |
| US8744878B1 (en) | 2008-04-11 | 2014-06-03 | Humana Inc. | Method for using financial incentives with member engagement metrics to reduce health care claim costs |
| US20090307006A1 (en) * | 2008-06-04 | 2009-12-10 | International Business Machines Corporation | Method of collaborative evaluation infrastructure to assess the quality of healthcare clnical decision actors |
| US8626525B2 (en) * | 2008-06-23 | 2014-01-07 | Mckesson Financial Holdings | Systems and methods for real-time monitoring and analysis of prescription claim rejections |
| US20090327363A1 (en) * | 2008-06-30 | 2009-12-31 | Peter Cullen | Systems and methods for processing electronically transmitted healthcare related transactions |
| US20090326977A1 (en) * | 2008-06-30 | 2009-12-31 | Mckesson Financial Holding Limited | Systems and Methods for Providing Drug Samples to Patients |
| US8538777B1 (en) | 2008-06-30 | 2013-09-17 | Mckesson Financial Holdings Limited | Systems and methods for providing patient medication history |
| US8311854B1 (en) | 2008-07-01 | 2012-11-13 | Unicor Medical, Inc. | Medical quality performance measurement reporting facilitator |
| US20100004945A1 (en) * | 2008-07-01 | 2010-01-07 | Global Health Outcomes, Inc. | Computer implemented methods, systems, and apparatus for generating and utilizing health outcomes indices and financial derivative instruments based on the indices |
| US20100004956A1 (en) * | 2008-07-03 | 2010-01-07 | Mccallum William Jay | System and method for improved patient care |
| US20100063956A1 (en) * | 2008-09-11 | 2010-03-11 | Mccallum William Jay | System and method for improved patient care and patient record keeping |
| US8706517B2 (en) * | 2008-11-21 | 2014-04-22 | Allmed Healthcare Management, Inc. | Medical practitioner peer review system and method |
| US8046242B1 (en) | 2009-01-22 | 2011-10-25 | Mckesson Financial Holdings Limited | Systems and methods for verifying prescription dosages |
| WO2010138640A2 (en) * | 2009-05-27 | 2010-12-02 | Archimedes, Inc. | Healthcare quality measurement |
| US20100306135A1 (en) * | 2009-05-28 | 2010-12-02 | Mccallum Jack Edward | Method of improving medical diagnoses reporting as diagnosis-related groups |
| US20100324932A1 (en) * | 2009-06-19 | 2010-12-23 | Roche Diagnostics Operations, Inc. | Methods and systems for advising people with diabetes |
| US8489415B1 (en) | 2009-09-30 | 2013-07-16 | Mckesson Financial Holdings Limited | Systems and methods for the coordination of benefits in healthcare claim transactions |
| US20110087500A1 (en) * | 2009-10-12 | 2011-04-14 | Mccallum William Jay | Processing patient data using a computer interface |
| US8788296B1 (en) | 2010-01-29 | 2014-07-22 | Mckesson Financial Holdings | Systems and methods for providing notifications of availability of generic drugs or products |
| US8386276B1 (en) | 2010-02-11 | 2013-02-26 | Mckesson Financial Holdings Limited | Systems and methods for determining prescribing physician activity levels |
| US8321243B1 (en) | 2010-02-15 | 2012-11-27 | Mckesson Financial Holdings Limited | Systems and methods for the intelligent coordination of benefits in healthcare transactions |
| US8548824B1 (en) | 2010-03-26 | 2013-10-01 | Mckesson Financial Holdings Limited | Systems and methods for notifying of duplicate product prescriptions |
| US8688468B1 (en) | 2010-03-30 | 2014-04-01 | Mckesson Financial Holdings | Systems and methods for verifying dosages associated with healthcare transactions |
| US10943676B2 (en) | 2010-06-08 | 2021-03-09 | Cerner Innovation, Inc. | Healthcare information technology system for predicting or preventing readmissions |
| US11610653B2 (en) | 2010-09-01 | 2023-03-21 | Apixio, Inc. | Systems and methods for improved optical character recognition of health records |
| US20130262144A1 (en) | 2010-09-01 | 2013-10-03 | Imran N. Chaudhri | Systems and Methods for Patient Retention in Network Through Referral Analytics |
| US11481411B2 (en) | 2010-09-01 | 2022-10-25 | Apixio, Inc. | Systems and methods for automated generation classifiers |
| US11195213B2 (en) | 2010-09-01 | 2021-12-07 | Apixio, Inc. | Method of optimizing patient-related outcomes |
| US11694239B2 (en) | 2010-09-01 | 2023-07-04 | Apixio, Inc. | Method of optimizing patient-related outcomes |
| US10319467B2 (en) * | 2010-09-01 | 2019-06-11 | Apixio, Inc. | Medical information navigation engine (MINE) system |
| US11544652B2 (en) | 2010-09-01 | 2023-01-03 | Apixio, Inc. | Systems and methods for enhancing workflow efficiency in a healthcare management system |
| US10136845B2 (en) | 2011-02-28 | 2018-11-27 | Abbott Diabetes Care Inc. | Devices, systems, and methods associated with analyte monitoring devices and devices incorporating the same |
| US10445846B2 (en) * | 2011-04-14 | 2019-10-15 | Elwha Llc | Cost-effective resource apportionment technologies suitable for facilitating therapies |
| US10853819B2 (en) | 2011-04-14 | 2020-12-01 | Elwha Llc | Cost-effective resource apportionment technologies suitable for facilitating therapies |
| US8756075B1 (en) | 2011-05-18 | 2014-06-17 | Trizetto Corporation | System and method for processing payment bundles |
| US8630878B1 (en) * | 2011-06-17 | 2014-01-14 | Zenith Insurance Company | Determining likely outcomes of active insurance claims by calculating and examining aggregated outcomes of matching historic claims |
| US10296976B1 (en) | 2011-09-23 | 2019-05-21 | Cognizant Trizetto Software Group, Inc. | System and method for calculating estimated payment based on partial coding data |
| WO2013126866A1 (en) | 2012-02-24 | 2013-08-29 | B3, Llc | Systems and methods for comprehensive insurance loss management and loss minimization |
| US8725532B1 (en) | 2012-06-29 | 2014-05-13 | Mckesson Financial Holdings | Systems and methods for monitoring controlled substance distribution |
| US10318923B1 (en) | 2012-08-01 | 2019-06-11 | Cognizant Trizetto Software Group, Inc. | Payment assurance and claim pre-validation |
| US9075869B1 (en) * | 2012-08-31 | 2015-07-07 | Trizetto Corporation | System and method for facilitating the collection, analysis, use and management of clinical analytics results to improve healthcare |
| US10424032B2 (en) | 2012-12-12 | 2019-09-24 | Quality Standards, Llc | Methods for administering preventative healthcare to a patient population |
| US20140164003A1 (en) * | 2012-12-12 | 2014-06-12 | Debra Thesman | Methods for optimizing managed healthcare administration and achieving objective quality standards |
| US10600516B2 (en) | 2012-12-12 | 2020-03-24 | Advanced Healthcare Systems, Inc. | Healthcare administration method for complex case and disease management |
| US10430555B1 (en) | 2014-03-13 | 2019-10-01 | Mckesson Corporation | Systems and methods for determining and communicating information to a pharmacy indicating patient eligibility for an intervention service |
| US10297344B1 (en) | 2014-03-31 | 2019-05-21 | Mckesson Corporation | Systems and methods for establishing an individual's longitudinal medication history |
| US10192639B2 (en) | 2014-08-22 | 2019-01-29 | Drfirst.Com, Inc. | Method and system for medical suggestion search |
| US10706963B2 (en) | 2014-09-09 | 2020-07-07 | Cambria Health Solutions, Inc. | Systems and methods for a health care E-commerce marketplace |
| US10642957B1 (en) | 2014-10-21 | 2020-05-05 | Mckesson Corporation | Systems and methods for determining, collecting, and configuring patient intervention screening information from a pharmacy |
| US11461848B1 (en) | 2015-01-14 | 2022-10-04 | Alchemy Logic Systems, Inc. | Methods of obtaining high accuracy impairment ratings and to assist data integrity in the impairment rating process |
| US10546654B2 (en) * | 2015-12-17 | 2020-01-28 | Drfirst.Com, Inc. | Method and system for intelligent completion of medical record based on big data analytics |
| US11853973B1 (en) | 2016-07-26 | 2023-12-26 | Alchemy Logic Systems, Inc. | Method of and system for executing an impairment repair process |
| US11854700B1 (en) | 2016-12-06 | 2023-12-26 | Alchemy Logic Systems, Inc. | Method of and system for determining a highly accurate and objective maximum medical improvement status and dating assignment |
| US10650380B1 (en) | 2017-03-31 | 2020-05-12 | Mckesson Corporation | System and method for evaluating requests |
| US20200203021A1 (en) * | 2017-09-06 | 2020-06-25 | Koninklijke Philips N.V. | Visualization of health quality measures |
| US11625687B1 (en) | 2018-10-16 | 2023-04-11 | Alchemy Logic Systems Inc. | Method of and system for parity repair for functional limitation determination and injury profile reports in worker's compensation cases |
| US11257018B2 (en) * | 2018-12-24 | 2022-02-22 | Hartford Fire Insurance Company | Interactive user interface for insurance claim handlers including identifying insurance claim risks and health scores |
| CN109961842A (en) * | 2019-03-28 | 2019-07-02 | 深圳市罗素医药有限公司 | A kind of Hematology Supervise system |
| US11848109B1 (en) | 2019-07-29 | 2023-12-19 | Alchemy Logic Systems, Inc. | System and method of determining financial loss for worker's compensation injury claims |
| CN113470799B (en) * | 2021-07-09 | 2023-08-08 | 深圳前海天智信息技术有限公司 | Intelligent editor of comprehensive quality supervision platform for hospitals |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US3872448A (en) * | 1972-12-11 | 1975-03-18 | Community Health Computing Inc | Hospital data processing system |
| US4667292A (en) * | 1984-02-16 | 1987-05-19 | Iameter Incorporated | Medical reimbursement computer system |
| JPS6176144A (en) * | 1984-09-21 | 1986-04-18 | オリンパス光学工業株式会社 | Medical image file apparatus |
| US5018067A (en) * | 1987-01-12 | 1991-05-21 | Iameter Incorporated | Apparatus and method for improved estimation of health resource consumption through use of diagnostic and/or procedure grouping and severity of illness indicators |
| US4878175A (en) * | 1987-11-03 | 1989-10-31 | Emtek Health Care Systems | Method for generating patient-specific flowsheets by adding/deleting parameters |
-
1991
- 1991-08-02 US US07/739,629 patent/US5544044A/en not_active Expired - Fee Related
- 1991-10-16 CA CA002053553A patent/CA2053553C/en not_active Expired - Lifetime
Also Published As
| Publication number | Publication date |
|---|---|
| US5544044A (en) | 1996-08-06 |
| CA2053553A1 (en) | 1993-02-03 |
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