Assessing Performance at Different Levels of the Health Care System Issues Answers III

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PROFILING PRACTICES: HOW MUCH DO WE KNOW? Sharon-Lise Normand Quality Measures Continuous Single A Multiple B Binary SL Normand AcademyHealth 2006 C D 1 SINGLE QUALITY MEASURE (CONTINUOUS) Practice 1 Practice i Practice I Patient 1 Patient n1 Patient 1 Patient nI Single quality measure 2 SL Normand AcademyHealth 2006 SINGLE QUALITY MEASURE (CONTINUOUS) Variation in outcomes: • Between-practice: 2P • Within-practice (among patients): 2W • Total variation: 2 = 2P + 2W Intra-Practice Correlation: P = 2P/(2P + 2W ) Proportion of total variation in outcome due to the practice. Note: 2W = 2(1 - P) 3 SL Normand AcademyHealth 2006 SINGLE QUALITY MEASURE (CONTINUOUS) How many patients per practice, n? • Reliability: – Degree to which repeated measurements will yield the same results. – Why? Users know that the practice measure has a minimum level of reliability (R*). – n = R*(1 - P)/(P (1-R*)) 4 SL Normand AcademyHealth 2006 Number Patients Per Practice to Achieve R*. Intra-Practice Correlation Coefficient R* 0.02 0.05 0.1 0.2 .70 .75 .80 .85 115 147 196 278 45 57 76 108 21 27 36 51 10 12 16 23 5 SL Normand AcademyHealth 2006 WHAT IS OUR EXPERIENCE? (CONTINUOUS) Intra-Practice Correlation Coefficients: Not very much! • Outpatient visit rates – 0.04 (Hofer et al., 1999). • Hemoglobin A1c – 0.18 (Greenfield et al., 2002). 6 SL Normand AcademyHealth 2006 MULTIPLE QUALITY MEASURES (CONTINUOUS) Practice 1 Practice i Practice I Patient 1 Patient n1 Patient 1 Patient nI Multiple quality measures 7 SL Normand AcademyHealth 2006 MULTIPLE QUALITY MEASURES (CONTINUOUS) Variation in outcomes: • Between-practice: 2P • Among-subjects (within practice): 2S • Within-subject (among measures): 2W • Total variation: 2 = 2P + 2S + 2W Intra-Practice Correlation: P = 2P/(2P + 2S + 2W ) Proportion of total variation in outcomes due to the practice. 8 SL Normand AcademyHealth 2006 MULTIPLE QUALITY MEASURES (CONTINUOUS) Intra-Subject Correlation: S = (2P+ 2S)/(2P + 2S + 2W) Correlation for outcomes within subjects. – Assume more similarity among outcomes measured on same subject than among measures attributed to same practice, e.g., S  P 9 SL Normand AcademyHealth 2006 Number Patient-Measures Per Practice to Achieve R*. Intra-Practice Correlation Coefficient R* 0.01 .70 .75 .80 .85 0.02 115 147 196 278 0.05 45 57 76 108 0.1 21 27 36 51 10 231 297 396 561 SL Normand AcademyHealth 2006 WHAT IS OUR EXPERIENCE? (CONTINUOUS) Intra-Practice Correlation Coefficients: Nothing! 11 SL Normand AcademyHealth 2006 SINGLE QUALITY MEASURE (BINARY) Variation in rates: • Between-practice: 2P • Within-practice (among patients): ? • Total variation: 2 = 2P + ? • Some suggested ? = (3.14/3)2 so that P = 2P/(2P + (3.14/3)2) • Others suggestions 12 SL Normand AcademyHealth 2006 SINGLE QUALITY MEASURE (BINARY) Variance Components Inappropriate: • Use the median odds ratio: exp(2 2P) -1(0.75) • Median odds ratio between patients treated by practices having higher quality and practices having lower quality. • If = 1, no practice variation; otherwise it is > 1.0. 13 SL Normand AcademyHealth 2006 REMARKS • Very little experience/knowledge about magnitude of P and S • Formula/concepts assumed continuous variables – More difficulty when measures are binary – Need to link median OR to sample size calculation • Need information about these variance components/correlation coefficients; otherwise usefulness of information questionable. 14 SL Normand AcademyHealth 2006

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