Timothy J van Dover1, David D Kim2. 1. Department of Medicine, Tufts University School of Medicine, Boston, MA, USA. 2. Department of Medicine, Tufts University School of Medicine, Boston, MA, USA; Center for the Evaluation of Value and Risk in Health, Tufts Medical Center, Boston, MA, USA. Electronic address: dkim3@tuftsmedicalcenter.org.
Abstract
OBJECTIVES: Despite its importance of quality measures used by the Centers for Medicare and Medicaid Services, the underlying cost-effectiveness evidence has not been examined. This study aimed to analyze cost-effectiveness evidence associated with the Centers for Medicare and Medicaid Services quality measures. METHODS: After classifying 23 quality measures with the Donabedian's structure-process-outcome quality of care model, we identified cost-effectiveness analyses (CEAs) relevant to these measures from the Tufts Medical Center CEA Registry based on the PICOTS (population, intervention, comparator, outcome, time horizon, and setting) framework. We then summarized available incremental cost-effectiveness ratios (ICERs) to determine the cost-effectiveness of the quality measures. RESULTS: The 23 quality measures were categorized into 14 process, 7 outcome, and 2 structure measures. Cost-effectiveness evidence was only available for 8 of 14 process measures. Two measures (Tobacco Screening and Hemoglobin bA1c Control) were cost-saving and quality-adjusted life-years (QALYs) improving, and 5 (Depression Screening, Influenza Immunization, Colon Cancer Screening, Breast Cancer Screening, and Statin Therapy) were highly cost-effective (median ICER ≤ $50 000/QALY). The remaining measure (Fall Screening) had a median ICER of $120 000/QALY. No CEAs were available for 15 measures: 10 defined by subjective patient ratings and 5 employed outcome measures without specifying an intervention or process. CONCLUSIONS: When relevant CEAs were available, cost-effectiveness evidence was consistent with quality measures (measures were cost-effective). Nevertheless, most quality measures were based on subjective ratings or outcome measures, posing a challenge in identifying supporting economic evidence. Refining and aligning quality measures with cost-effectiveness evidence can help further improve healthcare efficiency by demonstrating that they are good indicators of both quality and cost-effectiveness of care.
OBJECTIVES: Despite its importance of quality measures used by the Centers for Medicare and Medicaid Services, the underlying cost-effectiveness evidence has not been examined. This study aimed to analyze cost-effectiveness evidence associated with the Centers for Medicare and Medicaid Services quality measures. METHODS: After classifying 23 quality measures with the Donabedian's structure-process-outcome quality of care model, we identified cost-effectiveness analyses (CEAs) relevant to these measures from the Tufts Medical Center CEA Registry based on the PICOTS (population, intervention, comparator, outcome, time horizon, and setting) framework. We then summarized available incremental cost-effectiveness ratios (ICERs) to determine the cost-effectiveness of the quality measures. RESULTS: The 23 quality measures were categorized into 14 process, 7 outcome, and 2 structure measures. Cost-effectiveness evidence was only available for 8 of 14 process measures. Two measures (Tobacco Screening and Hemoglobin bA1c Control) were cost-saving and quality-adjusted life-years (QALYs) improving, and 5 (Depression Screening, Influenza Immunization, Colon Cancer Screening, Breast Cancer Screening, and Statin Therapy) were highly cost-effective (median ICER ≤ $50 000/QALY). The remaining measure (Fall Screening) had a median ICER of $120 000/QALY. No CEAs were available for 15 measures: 10 defined by subjective patient ratings and 5 employed outcome measures without specifying an intervention or process. CONCLUSIONS: When relevant CEAs were available, cost-effectiveness evidence was consistent with quality measures (measures were cost-effective). Nevertheless, most quality measures were based on subjective ratings or outcome measures, posing a challenge in identifying supporting economic evidence. Refining and aligning quality measures with cost-effectiveness evidence can help further improve healthcare efficiency by demonstrating that they are good indicators of both quality and cost-effectiveness of care.
Authors: Brandon L Ellsworth; Allan K Metz; Nicole M Mott; Ruby Kazemi; Michael Stover; Tasha Hughes; Lesly A Dossett Journal: Ann Surg Oncol Date: 2022-02-06 Impact factor: 5.344