DISEASE-SPECIFIC DISTRIBUTION OF HEALTH CARE QUALITY MEASURES IN THE UNITED STATES
Author(s)
Nicholson GL, Halbert RJ
ICON plc, El Segundo, CA, USA
OBJECTIVES: Quality improvement initiatives in US health care increasingly focus on physician and hospital performance against rigorous, evidence-based quality measures (QMs). Over the last decade, the universe of QMs has grown exponentially and continues to grow. We examined the landscape of current QMs across multiple diseases to better understand the evolving nature of quality measurement. METHODS: Publicly available databases of QMs were searched to identify indicators in a wide range of disease states over a period of 3 years. All identified QMs were bundled by disease area and plotted on a landscape matrix, assessing the maturity of quality science and burden of disease (based on prevalence, public health impact, and cost). The distribution of QMs in the matrix was validated through in-depth interviews with payers (n=20) and providers (n=7). RESULTS: QMs in disease areas with low disease burden and immature quality science (e.g., schizophrenia) are rare or non-existent. Disease areas with significant disease burden but less developed quality science (e.g., oncology) have relatively few QMs in adoption but are rapidly adding new QMs and refining current QMs. High-burden diseases with mature quality science (e.g., diabetes) have multiple QMs that are well-entrenched and stable, with relatively less addition or refinement. Findings from the landscape matrix exercise were validated through interviews with payers and provider groups, focusing on their current and future quality improvement agendas, and quality activities linked to incentives. CONCLUSIONS: Implementation of quality measures varies by disease state characteristics, including public health impact and the maturity of measurement science. A tight focus on producing new metrics may not be the best way to advance quality in every area. For some diseases, efforts may be more productive if directed toward strengthening the quality infrastructure. Examples include improving measurement capability, establishing quality domains, or standardizing clinical practice guidelines.
Conference/Value in Health Info
2015-05, ISPOR 2015, Philadelphia, PA, USA
Value in Health, Vol. 18, No. 3 (May 2015)
Code
PHS171
Topic
Health Service Delivery & Process of Care
Topic Subcategory
Quality of Care Measurement
Disease
Multiple Diseases