Journal of evaluation in clinical practice
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Clinical Trial
Remote control improves quality of life in elderly pacemaker patients versus standard ambulatory-based follow-up.
Health-related quality of life (HRQoL) improves shortly after pacemaker (PM) implantation. No studies have investigated the HRQoL trend for elderly patients with a remote device monitoring follow-up system. ⋯ Remote device monitoring has a significant impact on HRQoL in pacemaker patients, increasing its levels up to 6 months after implant.
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Observational Study
Evaluation of drug-related problems in older polypharmacy primary care patients.
Targeting older patients with predictive factors for drug-related problems (DRPs) could make clinical medication reviews more cost-effective. The aim of this study was to identify the number, type, and potential predictive factors for DRPs in older polypharmacy patients. ⋯ Patients with asthma, hypertension, and diabetes and lack of statin, antithrombotic agent, and/or proton pump inhibitor use were associated with higher risks for DRPs.
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Reducing preventable harm from repeat medication prescriptions is a patient safety priority worldwide. In the United Kingdom, repeat prescriptions items issued has doubled in the last 20 years from 5.8 to 13.3 items per patient per annum. This has significant resource implications and consequences for avoidable patient harms. Consequently, we aimed to test a risk management model to identify, measure, and reduce repeat prescribing system risks in primary care. ⋯ The risk management model tested uncovered important safety concerns and facilitated the development and communication of related improvement recommendations. System-wide information on hazardous repeat prescribing and how this could be mitigated is very limited. The approach reported may have potential to close this gap and improve the reliability of general practice systems and patient safety, which should be of high interest to primary care organisations internationally.
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In evaluating non-randomized interventions, propensity scores (PS) estimate the probability of assignment to the treatment group given observed characteristics. Machine learning algorithms have been proposed as an alternative to conventional logistic regression for modelling PS in order to avoid limitations of linear methods. We introduce classification tree analysis (CTA) to generate PS which is a "decision-tree"-like classification model that provides accurate, parsimonious decision rules that are easy to display and interpret, reports P values derived via permutation tests, and evaluates cross-generalizability. ⋯ Assessing standardized differences in means as a test of covariate balance is inappropriate for machine learning algorithms that segment the sample into two or more strata. Because the CTA algorithm identifies all statistically valid PS models for a sample, it is most likely to identify a correctly specified PS model, and should be considered as an alternative approach to modeling the PS.
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Recent years have seen an increasing shift towards providing care in the community, epitomised by the role of Children's Community Nursing (CCN) teams. However, there have been few attempts to use robust evaluative methods to interrogate the impact of such services. This study sought to evaluate whether reduction in secondary care costs, resulting from the introduction of 2 CCN teams, was sufficient to offset the additional cost of commissioning. ⋯ The study represents an important first step in understanding the role of such teams as a means of providing a high quality of paediatric care in an era of limited resource. While the cost saving from released paediatric bed days was not sufficient to demonstrate cost-effectiveness, the analysis does not incorporate wider measures of health care utilisation and nonmonetary benefits resulting from the CCN teams.