The National Health IT and Delivery System Transformation Summit
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1 The National Health IT and Delivery System Transformation Summit An overview of Health IT Related Aspects of Performance Measurement Initiatives Karen Kmetik, PhD Vice President AMA and Physician Consortium for Performance Improvement June 28, 2011
2 From the perspective of a quality measure developer, Hurray! Designing performance measures with EHRs as the data source emphasis on clinical relevance New "PDSA" cycles for measure development, specification and testing New networks for performance measure development (prototyping), specification, testing
3 Physician Consortium for Performance Improvement (PCPI ) More than 170 organizations National medical specialty societies, state medical associations, medical boards 13 health care professional organizations (eg, American Nurses Association) Council of Medical Specialty Societies American Board of Medical Specialties Liaisons from AHRQ, CMS, NCQA, TJC Consumer/Patient/Purchaser Advisory Panel Convened and staffed by AMA
4 PCPI Measures in CMS Programs PQRS (Physician Quality Reporting System 2010: 179 measures 68% PCPI measures measure groups 10 of 13 PCPI measures registry option, EHR option 3 of 10 PCPI measures group practice all 26 PCPI measures 2011: 194 measures 64% PCPI measures CMS Medicare and Medicaid EHR Incentive Program (Meaningful Use) Stage I (2011, 2012) 3 core, 3 alternate core, 38 about 50% PCPI
5 Use the leverage of an EHR (access to clinical data/behind the scene calculation) to provide timely data on quality measures to providers in ways heretofore not possible
6 When EHR is Primary Data Source: example hypertension Provider Claims: Diagnosis of hypertension (visit) BP measured (with new code) BP within certain ranges (with new codes) 3075F, most recent systolic bp 130 to 139 mm Hg
7 When EHR is Primary Data Source: example hypertension EHR: Diagnosis of hypertension (problem list) BP measured and actual values of diastolic and systolic reported Control: <140/90, <130/80 for diabetes
8 When EHR is Primary Data Source: example hypertension EHR: Diagnosis of hypertension or undiagnosed BP measured and actual values reported Control account for low diastolic bp Action/Care Plan: 2 more medications prescribed
9 When EHR is Primary Data Source: example hypertension Stephen Persell, Abel Kho, Jason Thompson, David Baker Improving Hypertension Quality Measurement Using Electronic Health Records Medical Care, April 2009
10 When EHR is Primary Data Source: example hypertension EHR: Diagnosis of hypertension or undiagnosed BP measured and actual values reported Control account for low diastolic bp Action/Care Plan: 2 more medications prescribed, healthy lifestyles Stratified by race, ethnicity, preferred language Why not 2 or more medications?-exceptions
11 When EHR is Primary Data Source: example hypertension Diane Downie, Dorothee Schmid, Marcus Plescia et al Racial disparities in blood pressure control and treatment differences in a Medicaid population, North Carolina, Prev Chronic Dis 2011;8(3)
12 New PDSA Cycles for Measure Development Historically, linear: Identify gaps/safety issue/overuse Review of evidence Measure development Measure specification Public comment Measure testing Measure and specification reevaluation National endorsement Implementation Feedback
13 PCPI Measure Development Process
14 PDSA-like cycles to evaluate measures and specifications as part of development
15 New networks for prototyping and testing measures for EHRs: TPQeNet Alliance of Chicago Community Health Services Brigham and Women's Primary Care Practice-Based Research Network CHITREC Cleveland Clinic Geisinger Health System HealthPartners, Inc. Indian Health Services Kaiser Permanente Indiana Health Information Exchange Mass General Physicians Organization Mayo Clinic, Rochester Northwestern Medical Faculty Foundation Rush University Medical Center and Rush Health Sisters of Mercy Health System VA Qualis Health/WIREC
16 New networks for prototyping and testing measures for EHRs: TPQeNet Develop measures from user/technical perspectives Build confidence in measure results Feasibility Reliability
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