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Storylines of Family Medicine is a 12-part series of thematically linked essays with accompanying illustrations that explore the many dimensions of family medicine, as interpreted by individual family physicians and medical educators in the USA and elsewhere around the world. In 'V: ways of thinking-honing the therapeutic self', authors present the following sections: 'Reflective practice in action', 'The doctor as drug-Balint groups', 'Cultivating compassion', 'Towards a humanistic approach to doctoring', 'Intimacy in family medicine', 'The many faces of suffering', 'Transcending suffering' and 'The power of listening to stories.' May readers feel a deeper sense of their own therapeutic agency by reflecting on these essays.

Background: Multimorbidity is rising in low-and middle-income countries such as Nepal, yet the research has not gained pace in this field. We aimed to systematically review the existing multimorbidity literature in Nepal and estimate the prevalence and map its risk factors and consequences. Methods: We reviewed data collated from PubMed, Embase and CINAHL by including original studies that reported prevalence of multimorbidity in Nepal. The quality of included studies was assessed using the Appraisal Tool for Cross-sectional Studies. The summary of the review is presented both qualitatively as well as through meta-analysis to give pooled prevalence. We prospectively registered in PROSPERO (CRD42024499598). Results: We identified 423 studies out of which seven were included in this review. All studies were conducted in a community setting except one which was hospital based. The prevalence reported across various studies ranged from 13.96% to 70.1%. The pooled prevalence of multimorbidity was observed to be 25.05% (95% CI: 16.99 to 34.09). The number of conditions used to assess multimorbidity ranged from four to nine. The major risk factors identified were increasing age, urban residence, and lower literacy rates. Conclusion: A wide variance in the prevalence of multimorbidity was observed. Moreover, multimorbidity assessment tool/conditions considered for assessing multimorbidity were heterogeneous. [ABSTRACT FROM AUTHOR]

Background Multimorbidity prevalence rates vary considerably depending on the conditions considered in the morbidity count, but there is no standardised approach to the number or selection of conditions to include. Methods and findings We conducted a cross-sectional study using English primary care data for 1,168,260 participants who were all people alive and permanently registered with 149 included general practices. Outcome measures of the study were prevalence estimates of multimorbidity (defined as [greater than or equal to]2 conditions) when varying the number and selection of conditions considered for 80 conditions. Included conditions featured in [greater than or equal to]1 of the 9 published lists of conditions examined in the study and/or phenotyping algorithms in the Health Data Research UK (HDR-UK) Phenotype Library. First, multimorbidity prevalence was calculated when considering the individually most common 2 conditions, 3 conditions, etc., up to 80 conditions. Second, prevalence was calculated using 9 condition-lists from published studies. Analyses were stratified by dependent variables age, socioeconomic position, and sex. Prevalence when only the 2 commonest conditions were considered was 4.6% (95% CI [4.6, 4.6] p < 0.001), rising to 29.5% (95% CI [29.5, 29.6] p < 0.001) considering the 10 commonest, 35.2% (95% CI [35.1, 35.3] p < 0.001) considering the 20 commonest, and 40.5% (95% CI [40.4, 40.6] p 99% of that measured when considering all 80 conditions was 52 for the whole population but was lower in older people (29 in >80 years) and higher in younger people (71 in 0- to 9-year-olds). Nine published condition-lists were examined; these were either recommended for measuring multimorbidity, used in previous highly cited studies of multimorbidity prevalence, or widely applied measures of 'comorbidity.' Multimorbidity prevalence using these lists varied from 11.1% to 36.4%. A limitation of the study is that conditions were not always replicated using the same ascertainment rules as previous studies to improve comparability across condition-lists, but this highlights further variability in prevalence estimates across studies. Conclusions In this study, we observed that varying the number and selection of conditions results in very large differences in multimorbidity prevalence, and different numbers of conditions are needed to reach ceiling rates of multimorbidity prevalence in certain groups of people. These findings imply that there is a need for a standardised approach to defining multimorbidity, and to facilitate this, researchers can use existing condition-lists associated with highest multimorbidity prevalence., Author(s): Clare MacRae 1,2,*, Megan McMinn 2, Stewart W. Mercer 1,2, David Henderson 2, David A. McAllister 3, Iris Ho 1,2, Emily Jefferson 4, Daniel R. Morales 4, Jane Lyons [...]

Background: Patients with severe mental illness (SMI) die 10–20 years earlier than the general population. They have a higher risk of cardiovascular disease (CVD) yet may experience lower cardioprotective medication prescribing. Aim: To understand the challenges experienced by GPs in prescribing cardioprotective medication to patients with SMI. Design & setting: A qualitative study with 15 GPs from 11 practices in two Scottish health boards, including practices servicing highly deprived areas (Deep End). Method: Semi-structured one-to-one interviews with fully qualified GPs with clinical experience of patients with SMI. Interviews were transcribed verbatim and analysed thematically. Results: Participants aimed to routinely prescribe cardioprotective medication to relevant patients with SMI but were hampered by various challenges. These structural and contextual barriers included the following: lack of funding for chronic disease management; insufficient consultation time; workforce shortages; IT infrastructure; and navigating boundaries with mental health services. Patient-related barriers included patients’ complex health and social needs, their understandable prioritisation of mental health needs or existing physical conditions, and presentation during crises. Professional barriers comprised GPs' desire to practise holistic medicine rather than treating via cardioprotective prescribing in isolation, and concerns about patients' medication concordance if patients were not prioritising this aspect of their health care at that particular time. In terms of enablers for cardioprotective prescribing, participants emphasised continuity of care as fundamental in engaging this patient group in effective cardiovascular health management. A cross-cutting theme was the current GP workforce crisis leading to ‘firefighting’ and diminishing capacity for primary prevention. This was particularly acute in Deep End practices, which have a high proportion of patients with complex needs and greater resource challenges. Conclusion: Although participants aspire to prescribe cardioprotective medication to patients with SMI, professional-, system- and patient-level barriers often make this challenging, particularly in deprived areas owing to patient complexity and the inverse care law. [ABSTRACT FROM AUTHOR]

PURPOSE To assess the effect of a primary care-based community-links practitioner (CLP) intervention on patients' quality of life and well-being. METHODS Quasi-experimental cluster-randomized controlled trial in socioeconomically deprived areas of Glasgow, Scotland. Adult patients (aged 18 years or older) referred to CLPs in 7 intervention practices were compared with a random sample of adult patients from 8 comparison practices at baseline and 9 months. Primary outcome: health-related quality of life (EQ-5D-5L, a standardized measure of self-reported health-related quality of life that assesses 5 dimensions at 5 levels of severity). Secondary outcomes: well-being (Investigating Choice Experiments for the Preferences of Older People Capability Measure for Adults [ICECAP-A]), depression (Hospital Anxiety and Depression Scale, Depression [HADS-D]), anxiety (Hospital Anxiety and Depression Scale, Anxiety [HADS-A]), and self-reported exercise. Multilevel, multiregression analyses adjusted for baseline differences. Patients were not blinded to the intervention, but outcome analysis was masked. RESULTS Data were collected on 288 and 214 (74.3%) patients in the intervention practices at baseline and follow-up, respectively, and on 612 and 561 (92%) patients in the comparison practices. Intention-to-treat analysis found no differences between the 2 groups for any outcome. In subgroup analyses, patients who saw the CLP on 3 or more occasions (45% of those referred) had significant improvements in EQ-5D-5L, HADS-D, HADS-A, and exercise levels. There was a high positive correlation between CLP consultation rates and patient uptake of suggested community resources. CONCLUSIONS We were unable to prove the effectiveness of referral to CLPs based in primary care in deprived areas for improving patient outcomes. Future efforts to boost uptake and engagement could improve overall outcomes, although the apparent improvements in those who regularly saw the CLPs may be due to reverse causality. Further research is needed before wide-scale deployment of this approach. Key words: general practice; primary care; multimorbidity; complex interventions; health inequalities; social prescribing; community link workers, INTRODUCTION Health inequalities are a global problem, resulting from a fundamental inequity in the distribution of income, power, and wealth. This inequity limits opportunities across the life course, including access [...]

Background Patients with multimorbidities have the greatest healthcare needs and generate the highest expenditure in the health system. There is an increasing focus on identifying specific disease combinations for addressing poor outcomes. Existing research has identified a small number of prevalent 'clusters' in the general population, but the limited number examined might oversimplify the problem and these may not be the ones associated with important outcomes. Combinations with the highest (potentially preventable) secondary care costs may reveal priority targets for intervention or prevention. We aimed to examine the potential of defining multimorbidity clusters for impacting secondary care costs. Methods and findings We used national, Hospital Episode Statistics, data from all hospital admissions in England from 2017/2018 (cohort of over 8 million patients) and defined multimorbidity based on ICD-10 codes for 28 chronic conditions (we backfilled conditions from 2009/2010 to address potential undercoding). We identified the combinations of multimorbidity which contributed to the highest total current and previous 5-year costs of secondary care and costs of potentially preventable emergency hospital admissions in aggregate and per patient. We examined the distribution of costs across unique disease combinations to test the potential of the cluster approach for targeting interventions at high costs. We then estimated the overlap between the unique combinations to test potential of the cluster approach for targeting prevention of accumulated disease. We examined variability in the ranks and distributions across age (over/under 65) and deprivation (area level, deciles) subgroups and sensitivity to considering a smaller number of diseases. There were 8,440,133 unique patients in our sample, over 4 million (53.1%) were female, and over 3 million (37.7%) were aged over 65 years. No clear 'high cost' combinations of multimorbidity emerged as possible targets for intervention. Over 2 million (31.6%) patients had 63,124 unique combinations of multimorbidity, each contributing a small fraction (maximum 3.2%) to current-year or 5-year secondary care costs. Highest total cost combinations tended to have fewer conditions (dyads/triads, most including hypertension) affecting a relatively large population. This contrasted with the combinations that generated the highest cost for individual patients, which were complex sets of many (6+) conditions affecting fewer persons. However, all combinations containing chronic kidney disease and hypertension, or diabetes and hypertension, made up a significant proportion of total secondary care costs, and all combinations containing chronic heart failure, chronic kidney disease, and hypertension had the highest proportion of preventable emergency admission costs, which might offer priority targets for prevention of disease accumulation. The results varied little between age and deprivation subgroups and sensitivity analyses. Key limitations include availability of data only from hospitals and reliance on hospital coding of health conditions. Conclusions Our findings indicate that there are no clear multimorbidity combinations for a cluster-targeted intervention approach to reduce secondary care costs. The role of risk-stratification and focus on individual high-cost patients with interventions is particularly questionable for this aim. However, if aetiology is favourable for preventing further disease, the cluster approach might be useful for targeting disease prevention efforts with potential for cost-savings in secondary care., Author(s): Jonathan Stokes 1,*, Bruce Guthrie 2, Stewart W. Mercer 2, Nigel Rice 3, Matt Sutton 1 Background There are several outcomes that are important to health systems. However, especially [...]