Interventions for involving older patients with multi‐morbidity in decision‐making during primary care consultations

Background Older patients with multiple health problems (multi‐morbidity) value being involved in decision‐making about their health care. However, they are less frequently involved than younger patients. To maximise quality of life, day‐to‐day function, and patient safety, older patients require support to identify unmet healthcare needs and to prioritise treatment options. Objectives To assess the effects of interventions for older patients with multi‐morbidity aiming to involve them in decision‐making about their health care during primary care consultations. Search methods We searched the Cochrane Central Register of Controlled Trials (CENTRAL; all years to August 2018), in the Cochrane Library; MEDLINE (OvidSP) (1966 to August 2018); Embase (OvidSP) (1988 to August 2018); PsycINFO (OvidSP) (1806 to August 2018); the Cumulative Index to Nursing and Allied Health Literature (CINAHL) (Ovid) (1982 to September 2008), then in Ebsco (2009 to August 2018); Centre for Reviews and Dissemination Databases (Database of Abstracts and Reviews of Effects (DARE)) (all years to August 2018); the Health Technology Assessment (HTA) Database (all years to August 2018); the Ongoing Reviews Database (all years to August 2018); and Dissertation Abstracts International (1861 to August 2018). Selection criteria We sought randomised controlled trials (RCTs), cluster‐RCTs, and quasi‐RCTs of interventions to involve patients in decision‐making about their health care versus usual care/control/another intervention, for patients aged 65 years and older with multi‐morbidity in primary care. Data collection and analysis We used standard Cochrane methodological procedures. Meta‐analysis was not possible; therefore we prepared a narrative synthesis. Main results We included three studies involving 1879 participants: two RCTs and one cluster‐RCT. Interventions consisted of: · patient workshop and individual coaching using behaviour change techniques; · individual patient coaching utilising cognitive‐behavioural therapy and motivational interviewing; and · holistic patient review, multi‐disciplinary practitioner training, and organisational change. No studies reported the primary outcome ‘patient involvement in decision‐making’ or the primary adverse outcome ‘less patient involvement as a result of the intervention’. Comparing interventions (patient workshop and individual coaching, holistic patient review plus practitioner training, and organisational change) to usual care: we are uncertain whether interventions had any effect on patient reports of high self‐rated health (risk ratio (RR) 1.40, 95% confidence interval (CI) 0.36 to 5.49; very low‐certainty evidence) or on patient enablement (mean difference (MD) 0.60, 95% CI ‐9.23 to 10.43; very low‐certainty evidence) compared with usual care. Interventions probably had no effect on health‐related quality of life (adjusted difference in means 0.00, 95% CI ‐0.02 to 0.02; moderate‐certainty evidence) or on medication adherence (MD 0.06, 95% CI ‐0.05 to 0.17; moderate‐certainty evidence) but probably improved the number of patients discussing their priorities (adjusted odds ratio 1.85, 95% CI 1.44 to 2.38; moderate‐certainty evidence) and probably increased the number of nurse consultations (incident rate ratio from adjusted multi‐level Poisson model 1.37, 95% CI 1.17 to 1.61; moderate‐certainty evidence) compared with usual care. Practitioner outcomes were not measured. Interventions were not reported to adversely affect rates of participant death or anxiety, emergency department attendance, or hospital admission compared with usual care. Comparing interventions (patient workshop and coaching, individual patient coaching) to attention‐control conditions: we are uncertain whether interventions affect patient‐reported high self‐rated health (RR 0.38, 95% CI 0.15 to 1.00, favouring attention control, with very low‐certainty evidence; RR 2.17, 95% CI 0.85 to 5.52, favouring the intervention, with very low‐certainty evidence). We are uncertain whether interventions affect patient enablement and engagement by increasing either patient activation (MD 1.20, 95% CI ‐8.21 to 10.61; very low‐certainty evidence) or self‐efficacy (MD 0.29, 95% CI ‐0.21 to 0.79; very low‐certainty evidence); or whether interventions affect the number of general practice visits (MD 0.51, 95% CI ‐0.34 to 1.36; very low‐certainty evidence), compared to attention‐control conditions. The intervention may however lead to more patient‐reported changes in management of their health conditions (RR 1.82, 95% CI 1.35 to 2.44; low‐certainty evidence). Practitioner outcomes were not measured. Interventions were not reported to adversely affect emergency department attendance nor hospital admission when compared with attention control. Comparing one form of intervention with another: not measured. There was 'unclear' risk across studies for performance bias, detection bias, and reporting bias; however, no aspects were 'high' risk. Evidence was downgraded via GRADE, most often because of 'small sample size' and 'evidence from a single study'. Authors' conclusions Limited available evidence does not allow a robust conclusion regarding the objectives of this review. Whilst patient involvement in decision‐making is seen as a key mechanism for improving care, it is rarely examined as an intervention and was not measured by included studies. Consistency in design, analysis, and evaluation of interventions would enable a greater likelihood of robust conclusions in future reviews