169 research outputs found

    Needs of Head and Neck Cancer Patients and Stakeholders During Rehabilitation

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    The foreseen growth of Head and Neck cancer (HNC) incidents will require future rehabilitation services to meet the needs of a wider population. This study reports the empirical findings of a case study conducted at a cancer rehabilitation center in Copenhagen, aiming to elicit the needs of HNC patients, informal caregivers and healthcare professionals (HCPs). Our results point out that patients and stakeholders' needs are interrelated, as they faced common challenges pertinent to provision and distribution of information. This study, though preliminary, underlines the importance of inclusion of all actors in the design of future interventions

    Is the Kaiser Permanente model superior in terms of clinical integration?: a comparative study of Kaiser Permanente, Northern California and the Danish healthcare system

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    <p>Abstract</p> <p>Background</p> <p>Integration of medical care across clinicians and settings could enhance the quality of care for patients. To date, there is limited data on the levels of integration in practice. Our objective was to compare primary care clinicians' perceptions of clinical integration and three sub-aspects in two healthcare systems: Kaiser Permanente, Northern California (KPNC) and the Danish healthcare system (DHS). Further, we examined the associations between specific organizational factors and clinical integration within each system.</p> <p>Methods</p> <p>Comparable questionnaires were sent to a random sample of primary care clinicians in KPNC (n = 1103) and general practitioners in DHS (n = 700). Data were analysed using multiple logistic regression models.</p> <p>Results</p> <p>More clinicians in KPNC perceived to be part of a clinical integrated environment than did general practitioners in the DHS (OR = 3.06, 95% CI: 2.28, 4.12). Further, more KPNC clinicians reported timeliness of information transfer (OR = 2.25, 95% CI: 1.62, 3.13), agreement on roles and responsibilities (OR = 1.79, 95% CI: 1.30, 2.47) and established coordination mechanisms in place to ensure effective handoffs (OR = 6.80, 95% CI: 4.60, 10.06). None of the considered organizational factors in the sub-country analysis explained a substantial proportion of the variation in clinical integration.</p> <p>Conclusions</p> <p>More primary care clinicians in KPNC reported clinical integration than did general practitioners in the DHS. Focused measures of clinical integration are needed to develop the field of clinical integration and to create the scientific foundation to guide managers searching for evidence based approaches.</p

    Codesigning a Measure of Person-Centred Coordinated Care to Capture the Experience of the Patient: The Development of the P3CEQ

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    Background: Person-centred coordinated care (P3C) is a priority for stakeholders (ie, patients, carers, professionals, policy makers). As a part of the development of an evaluation framework for P3C, we set out to identify patient-reported experience measures (PREMs) suitable for routine measurement and feedback during the development of services. Methods: A rapid review of the literature was undertaken to identity existing PREMs suitable for the probing person-centred and/or coordinated care. Of 74 measures identified, 7 met our inclusion criteria. We critically examined these against core domains and subdomains of P3C. Measures were then presented to stakeholders in codesign workshops to explore acceptability, utility, and their strengths/weaknesses. Results: The Long-Term Condition 6 questionnaire was preferred for its short length, utility, and tone. However, it lacked key questions in each core domain, and in response to requests from our codesign group, new questions were added to cover consideration as a whole person, coordination, care plans, carer involvement, and a single coordinator. Cognitive interviews, on-going codesign, and mapping to core P3C domains resulted in the refinement of the questionnaire to 11 items with 1 trigger question. The 11-item modified version was renamed the P3C Experiences Questionnaire. Conclusions: Due to a dearth of brief measures available to capture people’s experience of P3C for routine practice, an existing measure was modified using an iterative process of adaption and validation through codesign workshops. Next steps include psychometric validation and modification for people with dementia and learning difficulties.</p

    EHRA expert consensus document on the management of arrhythmias in frailty syndrome, endorsed by the Heart Rhythm Society (HRS), Asia Pacific Heart Rhythm Society (APHRS), Latin America Heart Rhythm Society (LAHRS), and Cardiac Arrhythmia Society of Southern Africa (CASSA)

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    There is an increasing proportion of the general population surviving to old age with significant chronic disease, multimorbidity, and disability. The prevalence of pre-frail state and frailty syndrome increases exponentially with advancing age and is associated with greater morbidity, disability, hospitalization, institutionalization, mortality, and health care resource use. Frailty represents a global problem, making early identification, evaluation, and treatment to prevent the cascade of events leading from functional decline to disability and death, one of the challenges of geriatric and general medicine. Cardiac arrhythmias are common in advancing age, chronic illness, and frailty and include a broad spectrum of rhythm and conduction abnormalities. However, no systematic studies or recommendations on the management of arrhythmias are available specifically for the elderly and frail population, and the uptake of many effective antiarrhythmic therapies in these patients remains the slowest. This European Heart Rhythm Association (EHRA) consensus document focuses on the biology of frailty, common comorbidities, and methods of assessing frailty, in respect to a specific issue of arrhythmias and conduction disease, provide evidence base advice on the management of arrhythmias in patients with frailty syndrome, and identifies knowledge gaps and directions for future research

    Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies

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    Background Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence. Methods and findings We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother-child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child's birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: -0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries. Conclusions This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term.This collaborative project received funding from the European Union's Horizon 2020 research and innovation programme (Grant Agreement No. 733206 LifeCycle, Grand Recipient VWVJ; Grant Agreement No. 824989 EUCAN-Connect, Grand Recipient AMNA). Please, see S1 Appendix for list of cohort-specific funding/support. DAL is supported by the UK Medical Research Council (MC_UU_00011/6) and British Heart Foundation (CH/F/20/90003 and AA/18/7/34219). RCW is supported by UKRI Innovation Fellowship with Health Data Research UK [MR/S003959/1]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
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