No abstract

ObjectiveThis study aimed to estimate global inpatient, outpatient, prescribing and care home costs for patients with atrial fibrillation using population-based, individual-level linked data.DesignA two-part model was employed to estimate the probability of resource utilisation and costs conditional on positive utilisation using individual-level linked data.SettingsScotland, 5 years following first hospitalisation for AF between 1997 and 2015.ParticipantsPatients hospitalised with a known diagnosis of AF or atrial flutter.Primary and secondary outcome measuresInpatient, outpatient, prescribing and care home costs.ResultsThe mean annual cost for a patient with AF was estimated at £3785 (95% CI £3767 to £3804). Inpatient admissions and outpatient visits accounted for 79% and 8% of total costs, respectively; prescriptions and care home stay accounted for 7% and 6% of total costs. Inpatient cost was the main driver across all age groups. While inpatient cost contributions (~80%) were constant between 0 and 84 years, they decreased for patients over 85 years. This is offset by increasing care home cost contributions. Mean annual costs associated with AF increased significantly with increasing number of comorbidities.ConclusionThis study used a contemporary and representative cohort, and a comprehensive approach to estimate global costs associated with AF, taking into account resource utilisation beyond hospital care. While overall costs, considerably affected by comorbidity, did not increase with increasing age, care home costs increased proportionally with age. Inpatient admission was the main contributor to the overall financial burden of AF, highlighting the need for improved mechanisms of early diagnosis to prevent hospitalisations.

Objective To explore methodological challenges when using real-world evidence (RWE) to estimate comparative-effectiveness in the context of Health Technology Assessment of direct oral anticoagulants (DOACs) in Scotland. Methods We used linkage data from the Prescribing Information System (PIS), Scottish Morbidity Records (SMR) and mortality records for newly anticoagulated patients to explore methodological challenges in the use of Propensity score (PS) matching, Inverse Probability Weighting (IPW) and covariate adjustment with PS. Model performance was assessed by standardised difference. Clinical outcomes (stroke and major bleeding) and mortality were compared for all DOACs (including apixaban, dabigatran and rivaroxaban) versus warfarin. Patients were followed for 2 years from first oral anticoagulant prescription to first clinical event or death. Censoring was applied for treatment switching or discontinuation. Results Overall, a good balance of patients’ covariates was obtained with every PS model tested. IPW was found to be the best performing method in assessing covariate balance when applied to subgroups with relatively large sample sizes (combined-DOACs versus warfarin). With the IPTW-IPCW approach, the treatment effect tends to be larger, but still in line with the treatment effect estimated using other PS methods. Covariate adjustment with PS in the outcome model performed well when applied to subgroups with smaller sample sizes (dabigatran versus warfarin), as this method does not require further reduction of sample size, and trimming or truncation of extreme weights. Conclusion The choice of adequate PS methods may vary according to the characteristics of the data. If assumptions of unobserved confounding hold, multiple approaches should be identified and tested. PS based methods can be implemented using routinely collected linked data, thus supporting Health Technology decision-making.

Background Pathways into care are poorly understood but important life events for individuals and their families. UK policy is to avoid moving-in to care homes from acute hospital settings. This assumes that moves from secondary care represent a system failure. However, those moving to care homes from community and hospital settings may be fundamentally different groups, each requiring differing care approaches. Objective To characterise individuals who move-in to a care home from hospital and compare with those moving-in from the community. Design and setting A retrospective cohort study using cross-sectoral data linkage of care home data. Methods We included adults moving-in to care homes between 1/4/13 and 31/3/16, recorded in the Scottish Care Home Census. Care home data were linked to general and psychiatric hospital admissions, community prescribing and mortality records to ascertain comorbidities, significant diagnoses, hospital resource use, polypharmacy and frailty. Multivariate logistic regression identified predictors of moving-in from hospital compared to from community. Results We included 23,892 individuals moving-in to a care home, 13,564 (56.8%) from hospital and 10,328 (43.2%) from the community. High frailty risk adjusted Odds Ratio (aOR) 5.11 (95% Confidence Interval (CI): 4.60–5.68), hospital discharge with diagnosis of fracture aOR 3.91 (95%CI: 3.41–4.47) or stroke aOR 8.42 (95%CI: 6.90–10.29) were associated with moving-in from hospital. Discharge from in-patient psychiatry was also a highly significant predictor aOR 19.12 (95%CI: 16.26–22.48). Conclusions Individuals moving-in to care homes directly from hospital are clinically distinct from those from the community. Linkage of cross-sectoral data can allow exploration of pathways into care at scale.