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      Implementing personalised care planning for older people with frailty: a process evaluation of the PROSPER feasibility trial

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          Abstract

          Background

          Personalised Care Planning (PCP) is a collaborative approach used in the management of chronic conditions. Core components of PCP are shared decision making to achieve joint goal setting and action planning by the clinician and patient. We undertook a process evaluation within the PROSPER feasibility trial to understand how best to implement PCP for older people with frailty in the community.

          Methods

          The trial was set in two localities in England. We observed training sessions and intervention delivery at three time points during the 12-week intervention period. We interviewed delivery teams before, during and after the intervention period, as well as primary care staff. We interviewed older people who had received, declined or withdrawn from PCP. We explored training of staff delivering PCP, structures, mechanisms and resources needed for delivery, and influences on uptake. We undertook a framework approach to data analysis.

          Findings

          We observed thirteen training sessions and interviewed seven delivery staff, five primary care staff, and twenty older people, including seven who had declined or withdrawn from the intervention. Delivery teams successfully acquired skills and knowledge, but felt underprepared for working with people with lower levels of frailty. Timing of training was critical and ‘top-ups’ were needed. Engagement with primary care staff was tenuous. Older people with lower frailty were unclear of the intervention purpose and benefits, goal setting and action planning.

          Conclusions

          PCP has the potential to address the individualised needs of older people with frailty. However, training requires careful tailoring and is ideally on-going. Considerable efforts are required to integrate statutory and voluntary stakeholders, understanding the expectations and contributions of each agency from the outset. In addition, older people with frailty need time and support to adjust to new ways of thinking about their own health now and in the future so they can participate in shared decision making. These key factors will be essential when developing models of care for delivering PCP to support older people with frailty to sustain their independence and quality of life.

          Trial registration

          ISRCTN 12,363,970 – 08/11/2018.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12877-022-03426-4.

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          Most cited references26

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          Process evaluation of complex interventions: Medical Research Council guidance

          Process evaluation is an essential part of designing and testing complex interventions. New MRC guidance provides a framework for conducting and reporting process evaluation studies
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            A refined compilation of implementation strategies: results from the Expert Recommendations for Implementing Change (ERIC) project

            Background Identifying, developing, and testing implementation strategies are important goals of implementation science. However, these efforts have been complicated by the use of inconsistent language and inadequate descriptions of implementation strategies in the literature. The Expert Recommendations for Implementing Change (ERIC) study aimed to refine a published compilation of implementation strategy terms and definitions by systematically gathering input from a wide range of stakeholders with expertise in implementation science and clinical practice. Methods Purposive sampling was used to recruit a panel of experts in implementation and clinical practice who engaged in three rounds of a modified Delphi process to generate consensus on implementation strategies and definitions. The first and second rounds involved Web-based surveys soliciting comments on implementation strategy terms and definitions. After each round, iterative refinements were made based upon participant feedback. The third round involved a live polling and consensus process via a Web-based platform and conference call. Results Participants identified substantial concerns with 31% of the terms and/or definitions and suggested five additional strategies. Seventy-five percent of definitions from the originally published compilation of strategies were retained after voting. Ultimately, the expert panel reached consensus on a final compilation of 73 implementation strategies. Conclusions This research advances the field by improving the conceptual clarity, relevance, and comprehensiveness of implementation strategies that can be used in isolation or combination in implementation research and practice. Future phases of ERIC will focus on developing conceptually distinct categories of strategies as well as ratings for each strategy’s importance and feasibility. Next, the expert panel will recommend multifaceted strategies for hypothetical yet real-world scenarios that vary by sites’ endorsement of evidence-based programs and practices and the strength of contextual supports that surround the effort. Electronic supplementary material The online version of this article (doi:10.1186/s13012-015-0209-1) contains supplementary material, which is available to authorized users.
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              Development and validation of an electronic frailty index using routine primary care electronic health record data

              Background: frailty is an especially problematic expression of population ageing. International guidelines recommend routine identification of frailty to provide evidence-based treatment, but currently available tools require additional resource. Objectives: to develop and validate an electronic frailty index (eFI) using routinely available primary care electronic health record data. Study design and setting: retrospective cohort study. Development and internal validation cohorts were established using a randomly split sample of the ResearchOne primary care database. External validation cohort established using THIN database. Participants: patients aged 65–95, registered with a ResearchOne or THIN practice on 14 October 2008. Predictors: we constructed the eFI using the cumulative deficit frailty model as our theoretical framework. The eFI score is calculated by the presence or absence of individual deficits as a proportion of the total possible. Categories of fit, mild, moderate and severe frailty were defined using population quartiles. Outcomes: outcomes were 1-, 3- and 5-year mortality, hospitalisation and nursing home admission. Statistical analysis: hazard ratios (HRs) were estimated using bivariate and multivariate Cox regression analyses. Discrimination was assessed using receiver operating characteristic (ROC) curves. Calibration was assessed using pseudo-R 2 estimates. Results: we include data from a total of 931,541 patients. The eFI incorporates 36 deficits constructed using 2,171 CTV3 codes. One-year adjusted HR for mortality was 1.92 (95% CI 1.81–2.04) for mild frailty, 3.10 (95% CI 2.91–3.31) for moderate frailty and 4.52 (95% CI 4.16–4.91) for severe frailty. Corresponding estimates for hospitalisation were 1.93 (95% CI 1.86–2.01), 3.04 (95% CI 2.90–3.19) and 4.73 (95% CI 4.43–5.06) and for nursing home admission were 1.89 (95% CI 1.63–2.15), 3.19 (95% CI 2.73–3.73) and 4.76 (95% CI 3.92–5.77), with good to moderate discrimination but low calibration estimates. Conclusions: the eFI uses routine data to identify older people with mild, moderate and severe frailty, with robust predictive validity for outcomes of mortality, hospitalisation and nursing home admission. Routine implementation of the eFI could enable delivery of evidence-based interventions to improve outcomes for this vulnerable group.
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                Author and article information

                Contributors
                Nicola.Kime@bthft.nhs.uk
                Journal
                BMC Geriatr
                BMC Geriatr
                BMC Geriatrics
                BioMed Central (London )
                1471-2318
                16 September 2022
                16 September 2022
                2022
                : 22
                : 760
                Affiliations
                [1 ]GRID grid.418449.4, ISNI 0000 0004 0379 5398, Academic Unit for Ageing and Stroke Research, , University of Leeds, Bradford Institute for Health Research, Bradford Teaching Hospital NHS Foundation Trust, ; Bradford, BD9 6RJ West Yorkshire UK
                [2 ]GRID grid.9909.9, ISNI 0000 0004 1936 8403, Clinical Trials Research Unit, , Leeds Institute of Clinical Trials Research, University of Leeds, ; West Yorkshire, Leeds, LS2 9JT UK
                [3 ]GRID grid.9909.9, ISNI 0000 0004 1936 8403, School of Medicine, , Leeds Institute of Health Sciences, University of Leeds, ; West Yorkshire, Leeds, LS2 9NL UK
                [4 ]GRID grid.9909.9, ISNI 0000 0004 1936 8403, School of Psychology, , University of Leeds, ; West Yorkshire, Leeds, LS2 9JT UK
                [5 ]GRID grid.8391.3, ISNI 0000 0004 1936 8024, Institute of Health Research, , University of Exeter Medical School, St Lukes Campus, ; Exeter, EX1 2LU UK
                Article
                3426
                10.1186/s12877-022-03426-4
                9479257
                cd41d15c-a22f-4cdf-b325-4ab08c312e68
                © The Author(s) 2022

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 31 March 2022
                : 24 August 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000272, National Institute for Health Research;
                Award ID: RP-PG-0216-20003
                Award ID: RP-PG-0216-20003
                Award ID: RP-PG-0216-20003
                Award ID: RP-PG-0216-20003
                Award ID: RP-PG-0216-20003
                Award ID: RP-PG-0216-20003
                Award ID: RP-PG-0216-20003
                Award ID: RP-PG-0216-20003
                Award ID: RP-PG-0216-20003
                Award ID: RP-PG-0216-20003
                Award ID: RP-PG-0216-20003
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Geriatric medicine
                personalised care planning,older people,frailty,feasibility,evaluation
                Geriatric medicine
                personalised care planning, older people, frailty, feasibility, evaluation

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