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Appendix H Commissioned Paper: Efficiency/Value-Based Measures for Services, Defined Populations, Acute Episodes, and Chronic Conditions--Kyle L. Grazier
Appendix H Commissioned Paper: Efficiency/Value-Based Measures for Services, Defined Populations, Acute Episodes, and Chronic Conditions--Kyle L. Grazier
Pages 222-249
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DEFINITION OF EFFICIENCY Central to this work is the manner in which "efficiency" and "value based" are defined. Among others, the economics, statistics, management science, and health services research literatures have contributed variations on these definitions that differ in their specificity to health care and their generalizability beyond the economic costs of health care services.
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. But as many authors have noted recently, the definition of quality, as in quality care or quality improvement, has not reached national consensus (Berwick, 2002; McGlynn, 1995; McGlynn et al., 2003; McKee, 2001; Palmer and Torgerson, 1999; Wennberg et al., 2002)
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Finally, deficits in management costing have limited the ability to measure accurately the resources consumed in the care delivery process and the quantitative outcomes. In the discourse on performance measurement in health care, "efficiency" is used in many contexts and for many purposes.
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. While extensive, the list is not exhaustive: · Improve quality of care · Encourage payer involvement · Integrate responsibility for employment, payment, health status · Reduce waste · Re/appoint/certify medical staff for network participation · Increase financial risk associated with practice decisions · Alter practice patterns · Assist in cost containment · Encourage/steer selection of efficient health plans · Allocate service resources differently · Deploy alternative labor and capital · Track/evaluate relationships to health management, health status, survival MEASUREMENT CONSIDERATIONS Validity There are generic guidelines for selecting measurement criteria, not all of which can be met in the current efforts to measure efficiency.
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By varying the methods used in measuring the inputs, and comparing the consistency of the outputs, production efficiency is captured. By establishing the "stability" of the output measure over time, over different types of physician specialties and patient panel sizes, one can learn more about potential variation in the inputs and outputs, and the financial and health consequences.
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Data The data sources for these efforts have traditionally included encounter and claims data supplied through an employer, insurer, or plan's administrative data systems. In some cases, the administrative data have been validated against medical records, but these efforts have been inconclusive in determining which source is better than another for these purposes (Hannan et al., 2003)
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Patient interviews, surveys, claims records, medical records, or some combination of these have been suggested as sources for data on health or medical risk (Ash et al., 2001; Grazier and Thomas, 2002; Hornbrook and Goodman, 1996; Newhouse et al., 1997; Pope et al., 2004; Street, 2003; Worthington, 2004; Zhao et al., 2001)
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endorsed national voluntary consensus standards for hospital care performance measures. The initial 39 measures were "intended to promote both public accountability and quality improvement." The Institute for Healthcare Improvement, through several programs and as described in several white papers as part of their innovation series, has initiated efforts among hospitals to improve the outcomes and experiences of patients and providers on medical/surgical units.
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. The Joint Commission on Accreditation of Healthcare Organizations (JCAHO)
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Inclusion of Quality Dimensions in the Measures Significant progress has been made in identifying process and outcomes components of quality care, particularly for certain conditions treated in
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and Financial Data A number of studies have examined the validity of self-reported data, medical records, and administrative data and found that, with some caveats, claims data are adequate for many purposes related to value measurement. Although recent, these studies may not be generalizable to future information systems in which the electronic medical record, integrated services/ encounter data, and advanced cost accounting systems are the norm.
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What appears on claims records and what is extracted from them as part of measurement algorithms can differ across claims administrators, payers and product designers. Provider characteristics, including specialty and details on physicians' panels, referrals patterns, and physician payment algorithms are normally not readily available from administrative data sources.
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While these data are for patients and not per physician, the effect of such cases on a panel from one year to the next could be misinterpreted if multiple years of data were not captured in the algorithms. More than one year of data would be needed to establish a fuller picture of use, and to accommodate "clean periods" for episodes that span the limits of inforce coverage contracts or reflect care for chronic conditions.
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APPENDIX H 235 Medicare claims, then pharmacy data should be removed from both sets prior to combination for analysis. Most large employers are requiring their third-party administrators or their health coverage carriers to collect and link pharmacy with medical claims information for analysis.
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Measurement of processes and outcomes associated with quality care for patients with certain conditions, such as cardiovascular disease, diabetes, and Chronic Obstructive Pulmonary Disease (COPD) , is highly advanced.
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For instance, agreement that high-quality, efficient allocation of resources to the public demands that value-based methods include measure of population health status. As another example, consensus as to the importance of the principle of fairness in the application of these metrics across plans, providers, and over time implicitly imposes a commitment to evaluate the consistency of the processes and the validity of the measures.
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Multiple years of linked data improve identification of full episodes of care, evaluation of chronic care delivery models, and reliability of patient or member risk levels. Risk adjustment methods continue to be refined and evaluated.
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2003. Provider profiling and quality improvement efforts in coronary artery bypass graft surgery: The effect on short-term mortality among Medicare beneficiaries.
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2003. Establishing na tional goals for quality improvement.
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1992. Choos ing quality of care measures based on the expected impact of improved care on health.
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nursing home (Mary Naylor)
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APPENDIX H 243 Required Enhancements/ Methods Data Sources Output Measure Risk adjustment using Hospital-reported data; Patient health status; provider ETGs payer claims paid charges payment; patient disposition; for procedure codes patient, provider satisfaction (CPT-9-CMxxxx, .
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; clinical quality measures for heart/stroke care Provider Recognition Programs Cardiac Care Link; adoption of electronic medical records and other office systems:
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APPENDIX H 245 Required Enhancements/ Methods Data Sources Output Measure Unexpected nursing home admission (Source: OBQM) Discharge to the community (Source: OASIS/OBQI)
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246 APPENDIX H TABLE H-1 continued Stated Health Care Measures Definition: Input:Output Purpose/Function Setting Physician Office Link: Clinical Information Systems/EvidenceBased Medicine (See Bridges to Excellence) Leapfrog Group: Presence of systems; use Electronic prescribing Hospitals Computer physician systems that intercept order entry (CPOE)
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APPENDIX H 247 Required Enhancements/ Methods Data Sources Output Measure Upfront capital Voluntary hospital self- Explicit: extent to which report; data survey standards are met, relative to other hospitals; implicit: costs of adverse drug events: mortality, morbidity; other costs An EHR standard does not Hospitals to report their apply to hospitals that do volume and process or not perform the procedure performance information or treat the condition. for these procedures and Patients under 18 are conditions by responding excluded to the Leapfrog Hospital Patient Safety Survey on the Leapfrog Website Hospitals with adult or Presence/absence of inten pediatric ICUs to respond sivists in ICU; organization of to the Leapfrog Group closed/open ICU Voluntary online survey (continued on next page)
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are measures in part, through highof health care quality outpatient care quality Inpatient QIs reflect quality of care inside hospitals including inpa tient mortality for medical conditions and surgical procedures Patient Safety Indicators also reflect quality of care inside hospitals, but focus on potentially avoidable complications and iatro genic events
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APPENDIX H 249 Required Enhancements/ Methods Data Sources Output Measure Exclude transferred Hospital: random sample Rate of adherence to endorsed patients; expired patients of at least 60 cases with process measures of quality the condition; principal or secondary discharge diagnosis Measure health care quality Currently being considered for using administrative data; uses other than tracking update for ICD codes quality improvement; namely provider payment and public reporting
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