AimsPolypharmacy is increasingly common in older adults, placing them at risk of medication‐related harm (MRH). Patients are particularly vulnerable to problems with their medications in the period following hospital discharge due to medication changes and poor information transfer between hospital and primary care. The aim of the present study was to investigate the incidence, severity, preventability and cost of MRH in older adults in England postdischarge.MethodsAn observational, multicentre, prospective cohort study recruited 1280 older adults (median age 82 years) from five teaching hospitals in Southern England, UK. Participants were followed up for 8 weeks by senior pharmacists, using three data sources (hospital readmission review, participant telephone interview and primary care records), to identify MRH and associated health service utilization.ResultsOverall, 413 participants (37%) experienced MRH (556 MRH events per 1000 discharges), of which 336 (81%) cases were serious and 214 (52%) potentially preventable. Four participants experienced fatal MRH. The most common MRH events were gastrointestinal (n = 158, 25%) or neurological (n = 111, 18%). The medicine classes associated with the highest risk of MRH were opiates, antibiotics and benzodiazepines. A total of 328 (79%) participants with MRH sought healthcare over the 8‐week follow‐up. The incidence of MRH‐associated hospital readmission was 78 per 1000 discharges. Postdischarge MRH in older adults is estimated to cost the National Health Service £396 million annually, of which £243 million is potentially preventable.ConclusionsMRH is common in older adults following hospital discharge, and results in substantial use of healthcare resources.
ObjectivesTo develop and validate a tool to predict the risk of an older adult experiencing medication-related harm (MRH) requiring healthcare use following hospital discharge.Design, setting, participantsMulticentre, prospective cohort study recruiting older adults (≥65 years) discharged from five UK teaching hospitals between 2013 and 2015.Primary outcome measureParticipants were followed up for 8 weeks in the community by senior pharmacists to identify MRH (adverse drug reactions, harm from non-adherence, harm from medication error). Three data sources provided MRH and healthcare use information: hospital readmissions, primary care use, participant telephone interview. Candidate variables for prognostic modelling were selected using two systematic reviews, the views of patients with MRH and an expert panel of clinicians. Multivariable logistic regression with backward elimination, based on the Akaike Information Criterion, was used to develop the PRIME tool. The tool was internally validated.Results1116 out of 1280 recruited participants completed follow-up (87%). Uncertain MRH cases (‘possible’ and ‘probable’) were excluded, leaving a tool derivation cohort of 818. 119 (15%) participants experienced ‘definite’ MRH requiring healthcare use and 699 participants did not. Modelling resulted in a prediction tool with eight variables measured at hospital discharge: age, gender, antiplatelet drug, sodium level, antidiabetic drug, past adverse drug reaction, number of medicines, living alone. The tool’s discrimination C-statistic was 0.69 (0.66 after validation) and showed good calibration. Decision curve analysis demonstrated the potential value of the tool to guide clinical decision making compared with alternative approaches.ConclusionsThe PRIME tool could be used to identify older patients at high risk of MRH requiring healthcare use following hospital discharge. Prior to clinical use we recommend the tool’s evaluation in other settings.
BackgroundMedication related harm (MRH) is a common cause of morbidity and hospital admission in the elderly, and has significant cost implications for both primary and secondary healthcare resources. The development of risk prediction models has become an increasingly common phenomenon in medicine and can be useful to guide objective clinical decision making, resource allocation and intervention. There are no risk prediction models that are widely used in clinical practice to identify elderly patients at high risk of MRH following hospital discharge. The aim of this study is to develop a risk prediction model (RPM) to identify elderly patients at high risk of MRH upon discharge from hospital, and to compare this with routine clinical judgment.Methods/DesignThis is a multi-centre, prospective observational study following a cohort of patients for 8 weeks after hospital discharge. Data collection including patient characteristics, medication use, social factors and frailty will take place prior to patient discharge and then the patient will be followed up in the community over the next 8 weeks to determine if they have experienced MRH. Research pharmacists will determine whether patients have experienced MRH by prospectively reviewing records for unplanned emergency department attendance, hospital readmission and GP consultation related to MRH. Research pharmacists will also telephone patients directly to determine self-reported MRH, which patients may not have sought further medical attention for. The data collected will inform the development of a RPM which will be externally validated in a follow-up study.DiscussionThere are no RPMs that are used in clinical practice to help stratify elderly patients at high risk of MRH in the community following hospital discharge, despite this being a significant public health problem. This study plans to develop a clinically useful RPM that is better than routine clinical judgment. As this is a multi-centre study involving clinical settings that serve elderly people of heterogeneous sociodemographic background, it is anticipated that this RPM will be generalizable.Electronic supplementary materialThe online version of this article (doi:10.1186/s12877-016-0191-8) contains supplementary material, which is available to authorized users.
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