Volume 10 Supplement 1
Coordinated performance measurement and improvement efforts in California's safety net systems: early experience and lessons
© Sarkar et al. 2015
Published: 14 August 2015
Safety-net health systems often lack incentives and resources to support performance measurement and improvement activities. The California Delivery System Reform Incentive Program (DSRIP) is a pay-for-performance initiative that incentivizes the state's public health care systems to improve quality of care. Health system participants must report on metrics in both inpatient and outpatient settings. To enhance DSRIP participants' capacity to engage in (1) best practices to improve quality of care and (2) reporting of DRSIP-required metrics, the California Association of Public Hospitals and UCSF established the Public Healthcare systems Evidence Network and Innovation eXchange (PHoENIX), with funding from AHRQ. PHoENIX priorities are meeting the HEDIS Medicare PPO 90th percentile thresholds for mammography screening (76.6%) and cholesterol control (LDL-C) for diabetes (<100 mg/dl, 62.2%).
Using a mixed methods approach and applying the Consolidated Framework for Implementation Research to characterize improvement efforts, we identified barriers and enablers for meeting the performance metrics.
Engagement in improvement was high, with all systems implementing quarterly performance measurement and participating in web-based and in-person learning sessions. Barriers include: lack of personnel for data reporting/management; structural barriers, such as fragmented electronic health records, lack of equipment (e.g., mammogram machines); competing priorities, such as providing access to care for the newly insured; and a change in the national guideline for cholesterol control. Enablers included: strong leadership, integrated data systems. To date, 82% of the health systems improved their performance on mammography and 53% improved on LDL.
Public health systems can collectively engage in performance measurement and improvement; implementation science methods identify barriers and enablers of change which can be applied to real-world improvement efforts.
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.