Primary Care: Harnessing Data for Improvement

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Presentation transcript:

Primary Care: Harnessing Data for Improvement W.L. Clifford, M.D., M.Sc.F., FCFP Paul Murray, M.B. 2012.10.25

The why – high quality primary care The how – measurement, self reflection, population health awareness, system design/transformation The what – distributed data questions

“Care is coordinated, continuous and comprehensive with patients having access to an interdisciplinary team”

NH Community Care Shared EHR

Physician’s overestimate performance by at least 10% (30% for LDL in diabetes) Diabetes composite 2.5% McCrate et al. CFP 2010

Hypertension and BP < 140/90 Steinman et al. Am J Med 2004 Steinman et al. Am J Med 2004

Practice Routinely Receives and Reviews Data on Patient Clinical Outcomes Percent Source: 2009 Commonwealth Fund International Health Policy Survey of Primary Care Physicians.

Practice Routinely Receives Data Comparing Clinical Performance to Other Practices Percent * Question asked differently in Italy. Source: 2009 Commonwealth Fund International Health Policy Survey of Primary Care Physicians.

Measures must be connected to the doers Collect measures from meaningful documentation Value add from system

Point of Care Practice Population

Point of Care Practice Population

Point of Care

Point of Care Patient Specific Information Clinical Decision Support Messaging / Tasks Interdisciplinary Care Coordination of Care

Information Flow - CDM

Practice

Patient Specific Information Access Registries and Gaps in Care Recall Practice Patient Specific Information Access Registries and Gaps in Care Recall

Test Result Rate of Change

Population

Population Demographics Disease Prevalence Screening Prevention Chronic Disease Management Mortality Access Costs Satisfaction / Experience

Population Level Measurement Privacy for patient and provider Right measures Timely Available

Aggregates are often good enough for the population level Can’t be reworked or linked (“mining”) Provides pointer to population which can then apply usual research methods (ethics/consent)

Generate Aggregates from Queries F I r e w a l l EMR Generate Aggregates from Queries Interface Aggregate (e.g. numerator & denominator) Collector F I r e w a l l EMR Generate Aggregates from Queries Interface

Prince George versus NH as a whole

Comparison Charts to Identify Best Practices Copyright © 2011 Southcentral Foundation. All Rights Reserved.