Correlation between the number of patient-reported adverse events, adverse drug events, and quality of life in older patients: an observational study.

BACKGROUND: Previous studies on medication therapy management services, e.g. medication reconciliation and medication review, do not show consistent improvements in patient's health-related quality of life. However, these services can reduce adverse drug events. AIM: To evaluate the correlation between health-related quality of life and adverse events/adverse drug events reported by patients. METHOD: Older patients (≥ 65 years) with polypharmacy (≥ 5 medicines) admitted to orthopaedic or surgical wards were included. Patients were contacted post-discharge to evaluate patient-reported adverse events, health-related quality of life using the EuroQol questionnaire and self-perceived health status on a 5-point Likert scale. The outcomes were the correlation between health-related quality of life and the number of adverse events/adverse drug events, and potential predictors for these events. Spearman correlation and Poisson regression were used for data analysis. RESULTS: 102 patients were included. The correlation between health-related quality of life and adverse events was weak but significant (Spearman correlation coefficient: - 0.328, p = 0.001). No correlation was found for adverse drug events (- 0.064, p = 0.521). Self-perceived health status was a predictor for adverse events, not for adverse drug events. Health-related quality of life was neither a predictor for adverse events, nor for adverse drug events. CONCLUSION: The correlation between the number of patient-reported adverse events, adverse drug events and health-related quality of life measured by the EuroQol was weak. There is a need for a questionnaire that includes the impact of medication use and is sensitive to outcomes that are affected by medication therapy management services.

Conversion of STOPP/START version 2 into coded algorithms for software implementation: A multidisciplinary consensus procedure.

BACKGROUND: The rapid digitalization of medical practice has attracted growing interest in developing software applications for clinical guidelines and explicit screening tools to detect potentially inappropriate prescribing, such as STOPP/START criteria. The aim of the current study was to develop and provide logically unambiguous algorithms of STOPP/START criteria version 2, encoded with international disease and medication classification codes, to facilitate the development of software applications for multiple purposes. METHODS: A four round multidisciplinary consensus and validation procedure was conducted to develop implementable coded algorithms for software applications of STOPP/START criteria version 2, based on ICD, ICPC, LOINC and ATC classification databases. RESULTS: Consensus was reached for all 34 START criteria and 76 out of 80 STOPP criteria. The resulting 110 algorithms, modeled as inference rules in decision tables, are provided as supplementary data. CONCLUSION: This is the first study providing implementable algorithms for software applications based on STOPP/START version 2, validated in a computer decision support system. These algorithms could serve as a template for applying STOPP/START criteria version 2 to any software application, allowing for adaptations of the included ICD, ICPC and ATC codes and changing the cut-off levels for laboratory measurements to match local guidelines or clinical expertise.