PT  - JOURNAL ARTICLE
AU  - Jessica E Moulton
AU  - Nishadi Nethmini Withanage
AU  - Asvini K Subasinghe
AU  - Danielle Mazza
TI  - Nurse-led service delivery models in primary care: a scoping review protocol
AID  - 10.3399/BJGPO.2021.0194
DP  - 2022 Sep 01
TA  - BJGP Open
PG  - BJGPO.2021.0194
VI  - 6
IP  - 3
4099  - http://bjgpopen.org/content/6/3/BJGPO.2021.0194.short
4100  - http://bjgpopen.org/content/6/3/BJGPO.2021.0194.full
SO  - BJGP Open2022 Sep 01; 6
AB  - Background Ensuring equitable access to health care is reliant on the strengthening of primary care services. Increasing the utilisation of task-sharing and telehealth models is one strategy to improve patient access and outcomes in primary care. This protocol details the methodology of a proposed scoping review of nurse and midwife involvement in task-sharing and telehealth models in primary care.Aim To identify what task-sharing and telehealth models have been utilised in the primary care setting globally, and to capture the characteristics and health and economic outcomes of the models, and whether they are acceptable and feasible.Design & setting This protocol was developed in line with the Joanna Briggs Institute (JBI) methodology for scoping reviews and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols (PRISMA-P).Method Five databases (Ovid MEDLINE, Embase, PubMed, Cumulative Index to Nursing and Allied Health Literature [CINAHL] and Cochrane Library) will be searched for relevant studies published in English. Articles will be screened for inclusion in Covidence by three authors, with data extracted and synthesised using a chart designed for this review. Evidence will be mapped in both tabular and narrative forms to show characteristics, outcomes, and acceptability of the models of care.Conclusion Understanding how nurse- and midwife-led models of care may operate is crucial to strengthening service provision in primary care. Evidence on nurse and midwife-led primary care models will be collated and synthesised to inform future models.