The development of the Primary Care Clusters Multidimensional Assessment (PCCMA): A mixed-methods study. Issue 2 (February 2020)

• Record Type: Journal Article
• Authors: Stanciu, Marian Andrei; Law, Rebecca-Jane; Myres, Paul; Parsonage, Rachel; Hiscock, Julia; Williams, Nefyn; Wilkinson, Clare
• Is Part Of: Health policy. Volume 124:Issue 2(2020)
• Page Start: 152
• Page End: 163
• Publication Date: 2020-02
• Subjects: Primary health care -- Primary care clusters -- Primary care networks -- General practice -- Benchmarking -- Quality assurance; Medical education -- Periodicals; Medical policy -- Periodicals; Delivery of Health Care -- Periodicals; Education, Medical -- Periodicals; Health Education -- Periodicals; Health Planning -- Periodicals; Public Policy -- Periodicals; Enseignement médical -- Périodiques; Politique sanitaire -- Périodiques; Medical education; Medical policy; Periodicals; Electronic journals; Electronic journals; 362.1
• DOI: 10.1016/j.healthpol.2019.12.004
• Languages: English
• ISSNs: 0168-8510

Abstract

Highlights: Developed primary care services encourage providers to work together in multidisciplinary clusters. Primary care clusters assessment is incipient, but comparable frameworks and instruments exist. The present novel instrument allows the quantitative assessment of primary care clusters. The instrument could be further developed for '360-degrees assessment' of clusters. Abstract: A strong primary care (PC) system is essential for an efficient and high-quality healthcare service. Many countries have adopted a model of PC that encourages different healthcare providers to work together, at scale, in multidisciplinary/multiagency teams (PC clusters). The aim of the present work was to develop a quantitative instrument for the systematic and comprehensive assessment of PC clusters. This was a non-experimental, mixed-methods study grouping four work packages (WP), and involving PC cluster leads and a wide range of key stakeholders from across Wales. Interviews with 22 PC cluster leads (34 %) investigated the clusters' functioning (WP1). A systematic review identified relevant PC assessment frameworks and instruments (WP2). An expert group reviewed the evidence and drafted the new assessment tool, further evaluated and amended in two stakeholder workshops (WP3). Thirty-eight cluster leads (62 %) completed the newly developed online assessment (WP4). The final instrument consisted of 53 indicators, across 11 systemic dimensions of PC and produced a comprehensive assessment of the functioning of PC clusters in Wales. This rigorous early development of an innovative instrument to evaluate PC at a scaled-up (cluster) level (particularly in the format of a 360-degree assessment) can inform healthcare policy decisions regarding the expansion and ongoing adjustment of the model in response to local needs and challenges.