Applying the consolidated framework for implementation research to evaluate the community rapid intervention service.

BACKGROUND: Developed in 2019, the Community Rapid Intervention Service (CRIS) is a community intervention service aiming to prevent hospital admissions. CRIS provides a response within two hours to patients with sub-acute medical needs in their usual place of residence. This evaluation aimed to identify challenges and facilitators to implementation of the service, with a view to informing future service development, optimising patient care and disseminating learning to other areas looking to implement similar services. METHODS: This study used the Consolidated Framework for Implementation Research (CFIR) as an evaluation framework. We conducted semi-structured interviews with local healthcare system leaders, clinicians that worked within the CRIS, and clinicians who interfaced with the CRIS. The CFIR was used to guide data collection and analysis. Two Community of Practice (CoP) meetings were held to gather stakeholders' perspectives of the evaluation. RESULTS: Three key themes were identified from the analysis of 13 interviews: contextual factors influencing implementation, service identity and navigating complexity. Contextual factors such the influence of the Covid 19 pandemic upon health services and the expansion of the CRIS were discussed by participants. The adaptability of the service was deemed both a facilitator and challenge of implementation. Ways to build-on and improve the existing CRIS model were suggested. CONCLUSION: This evaluation has shown that the CRIS may need to be redefined with clarity provided as to how the service interfaces with other urgent and planned care offered in acute, primary, community and social services. Structuring the evaluation around the CFIR was helpful in identifying facilitators and challenges that influenced the implementation of the CRIS.

Trends in the Annual Consultation Incidence and Prevalence of Low Back Pain and Osteoarthritis in England from 2000 to 2019: Comparative Estimates from Two Clinical Practice Databases.

PURPOSE: To compare estimates of annual person-consulting incidence and prevalence of low back pain (LBP) and osteoarthritis for two national English electronic health record databases (Clinical Practice Research Datalink (CPRD) Aurum and CPRD GOLD). PATIENTS AND METHODS: Retrospective, population-based, longitudinal cohort study. LBP and osteoarthritis cases were defined using established codelists in people aged ≥15 and ≥45 years, respectively. Incident cases were new recorded cases in a given calendar year with no relevant consultation in the previous 3 years (denominator = exact person-time in the same calendar year for the at-risk population). Prevalent cases were individuals with ≥1 consultation for the condition of interest recorded in a given calendar year, irrespective of prior consultations for the same condition (denominator = all patients with complete registration history in the previous 3 years). We estimated age-sex standardised incidence and annual (12-month period) prevalence for both conditions in 2000-2019, overall, and by sex, age group, and region. RESULTS: Standardised incidence and prevalence of LBP from Aurum were lower than those from GOLD until 2014, after which estimates were similar. Both databases showed recent declines in incidence and prevalence of LBP: declines began earlier in GOLD (after 2012-2014) than Aurum (after 2014-2015). Standardised incidence (after 2011) and prevalence of osteoarthritis (after 2003) were higher in Aurum than GOLD and showed different trends: incidence and prevalence were stable or increasing in Aurum, decreasing in GOLD. Stratified estimates in CPRD Aurum suggested consistently higher occurrence among women, older age groups, and those living in the north of England. CONCLUSION: Comparative analyses of two English databases produced conflicting estimates and trends for two common musculoskeletal conditions. Aurum estimates appeared more consistent with external sources and may be useful for monitoring population musculoskeletal health and healthcare demand, but they remain sensitive to analytic decisions and data quality.