Impact of Statewide Prevention and Reduction of Clostridioides difficile (SPARC), a Maryland public health-academic collaborative: an evaluation of a quality improvement intervention.

To evaluate changes in Clostridioides difficile incidence rates for Maryland hospitals that participated in the Statewide Prevention and Reduction of C. difficile (SPARC) collaborative. Pre-post, difference-in-difference analysis of non-randomised intervention using four quarters of preintervention and six quarters of postintervention National Healthcare Safety Network data for SPARC hospitals (April 2017 to March 2020) and 10 quarters for control hospitals (October 2017 to March 2020). Mixed-effects negative binomial models were used to assess changes over time. Process evaluation using hospital intervention implementation plans, assessments and interviews with staff at eight SPARC hospitals. Maryland, USA. All Maryland acute care hospitals; 12 intervention and 36 control hospitals. Participation in SPARC, a public health-academic collaborative made available to Maryland hospitals, with staggered enrolment between June 2018 and August 2019. Hospitals with higher C. difficile rates were recruited via email and phone. SPARC included assessments, feedback reports and ongoing technical assistance. Primary outcomes were C. difficile incidence rate measured as the quarterly number of C. difficile infections per 10 000 patient-days (outcome measure) and SPARC intervention hospitals' experiences participating in the collaborative (process measures). SPARC invited 13 hospitals to participate in the intervention, with 92% (n=12) participating. The 36 hospitals that did not participate served as control hospitals. SPARC hospitals were associated with 45% greater C. difficile reduction as compared with control hospitals (incidence rate ratio=0.55, 95% CI 0.35 to 0.88, p=0.012). Key SPARC activities, including access to trusted external experts, technical assistance, multidisciplinary collaboration, an accountability structure, peer-to-peer learning opportunities and educational resources, were associated with hospitals reporting positive experiences with SPARC. SPARC intervention hospitals experienced 45% greater reduction in C. difficile rates than control hospitals. A public health-academic collaborative might help reduce C. difficile and other hospital-acquired infections in individual hospitals and at state or regional levels.

Building and strengthening infrastructure for data exchange: lessons from the beacon communities.

INTRODUCTION: The Beacon Community Cooperative Agreement Program supports interventions, including care-delivery innovations, provider performance measurement and feedback initiatives, and tools for providers and consumers to enhance care. Using a learning health system framework, we examine the Beacon Communities' processes in building and strengthening health IT (HIT) infrastructures, specifically successes and challenges in sharing patient information to improve clinical care. BACKGROUND: In 2010, the Office of the National Coordinator for Health Information Technology (ONC) launched the three-year program, which provided $250 million to 17 Beacon Communities to invest in HIT and health information exchange (HIE) infrastructure. Beacon Communities used this funding to develop and disseminate HIT-enabled quality improvement practices found effective in particular community and practice environments. METHODS: NORC conducted 7 site visits, November 2012-March 2013, selecting Communities to represent diverse program features. From August-October 2013, NORC held discussions with the remaining 10 Communities. Following each visit or discussion, NORC summarized the information gathered, including transcripts, team observations, and other documents the Community provided, to facilitate a within-Community analysis of context and stakeholders, intervention strategies, enabling factors, and challenges. RESULTS: Although each Community designed and implemented data-sharing strategies in a unique environment, similar challenges and enabling factors emerged across the Beacons. From a learning health system perspective, their strategies to build and strengthen data-sharing infrastructures address the following crosscutting priorities: promoting technical advances and innovations by helping providers adapt EHRs for data exchange and performance measurement with customizable IT and offering technical support to smaller, independent providers; engaging key stakeholders; and fostering transparent governance and stewardship of the infrastructure with neutral conveners. CONCLUSION: While all the Communities developed or strengthened data-exchange infrastructure, each did this in a unique environment of existing health care market and legal factors. The Communities, however, encountered similar challenges and enabling factors. Organizations undertaking collaborative data sharing, performance measurement and clinical transformation can learn from the Beacon Communities' experience.