Medication-related harm in older adults following hospital discharge: development and validation of a prediction tool

The adverse inpatient medication event and frailty (AIME-frail) risk prediction model

BACKGROUND

Medication harm affects between 5 and 15% of hospitalised patients, with approximately half of the harm events considered preventable through timely intervention. The Adverse Inpatient Medication Event (AIME) risk prediction model was previously developed to guide a systematic approach to patient prioritisation for targeted clinician review, but frailty was not tested as a candidate predictor variable.

AIM

To evaluate the predictive performance of an updated AIME model, incorporating a measure of frailty, when applied to a new multisite cohort of hospitalised adult inpatients.

METHODS

A retrospective cohort study was conducted at two tertiary Australian hospitals on patients discharged between 1st January and April 31, 2020. Data were extracted from electronic medical records (EMRs) and clinical coding databases. Medication harm was identified using ICD-10 Y-codes and confirmed by senior pharmacist review of medical records. The Hospital Frailty Risk Score (HFRS) was calculated for each patient. Logistic regression analysis was used to construct a modified AIME model. Candidate variables of the original AIME model, together with new variables including HFRS were tested. Performance of the final model was reported using area under the curve (AUC) and decision curve analysis (DCA).

RESULTS

A total of 4089 patient admissions were included, with a mean age ± standard deviation (SD) of 64 years (±19 years), 2050 patients (50%) were males, and mean HFRS was 6.2 (±5.9). 184 patients (4.5%) experienced one or more medication harm events during hospitalisation. The new AIME-Frail risk model incorporated 5 of the original variables: length of stay (LOS), anti-psychotics, antiarrhythmics, immunosuppressants, and INR greater than 3, as well as 5 new variables: HFRS, anticoagulants, antibiotics, insulin, and opioid use. The AUC was 0.79 (95% CI: 0.76-0.83) which was superior to the original model (AUC = 0.70, 95% CI: 0.65-0.74) with a sensitivity of 69%, specificity of 81%, positive predictive value of 0.14 (95% CI: 0.10-0.17) and negative predictive value of 0.98 (95% CI: 0.97-0.99). The DCA identified the model as having potential clinical utility between the probability thresholds of 0.05-0.4.

CONCLUSION

The inclusion of a frailty measure improved the predictive performance of the AIME model. Screening inpatients using the AIME-Frail tool could identify more patients at high-risk of medication harm who warrant timely clinician review.

Assessment of inter-rater reliability of screening tools to identify patients at risk of medication-related problems across the emergency department continuum of care

BACKGROUND

Following a national multicentre study, two emergency department (ED) screening tools were developed to determine risk of medication-related problems; one for use at ED presentation and another at ED discharge to the community. This study aimed to determine the inter-rater reliability amongst ED health professionals when applying these screening tools to a series of case scenarios.

METHODS

A prospective, cross-sectional study was undertaken in the ED of a major metropolitan hospital. Twelve case scenarios were developed following ED observation of a range of patients, which were incorporated into a questionnaire and distributed to 50 health professionals. Inter-rater reliabilities of each explanatory variable of the screening tools and overall assessment were calculated using Fleiss' multi-rater kappa.

RESULTS

The questionnaire was completed by 15 doctors, 19 nurses and 16 pharmacists. Fleiss' kappa showed an overall inter-rater reliability for the ED presentation tool of 0.83 (95% CI 0.83-0.84), indicating near perfect agreement. Fleiss' kappa for the ED discharge tool was 0.83 (95% CI 0.83-0.85), which also showed near perfect agreement.

CONCLUSIONS

The screening tools produced favourable inter-rater reliability amongst ED health professionals. These results have important implications for ensuring consistency of ED decision-making in screening patients at risk of developing medication-related problems.

Introducing a pharmacist-led transmural care program to reduce drug-related problems in orthogeriatric patients: a prospective interventional study

BACKGROUND

Orthogeriatric patients have an increased risk for complications due to underlying comorbidities, chronic drug therapy and frequent treatment changes during hospitalization. The clinical pharmacist (CP) plays a key role in transmural communication concerning polypharmacy to improve continuity of care by the general practitioner (GP) after discharge. In this study, a pharmacist-led transmural care program, tailored to orthogeriatric patients, was evaluated to reduce drug related problems (DRPs) after discharge.

METHODS

An interventional study was performed (pre-period: 1/10/2021-31/12/2021; post-period: 1/01/2022-31/03/2022). Patients (≥ 65 years) from the orthopedic department were included. The pre-group received usual care, the post-group received the pharmacist-led transmural care program. The DRP reduction rate one month after discharge was calculated. Associated factors for the DRP reduction rate were determined in a multiple linear regression analysis. The GP acceptance rate was determined for the proposed interventions, as well as their clinical impact using the Clinical, Economic and Organizational (CLEO) tool. Readmissions one month after discharge were evaluated.

RESULTS

Overall, 127 patients were included (control n = 61, intervention n = 66). The DRP reduction rate was statistically significantly higher in the intervention group compared to the control group (p < 0.001). The pharmacist's intervention was associated with an increased DRP reduction rate (+ 1.750, 95% confidence interval 1.222-2.278). In total, 141 interventions were suggested by the CP, of which 71% were accepted one month after discharge. In both periods, four patients were readmitted one month after discharge. 58% of the interventions had a clinical impact (≥ 2 C level using the CLEO-tool) according to the geriatrician and for the CP it was 45%, indicating that they had the potential to avoid patient harm.

CONCLUSIONS

The pharmacist-led transmural care program significantly reduced DRPs in geriatric patients from the orthopedic department one month after discharge. The transmural communication with GPs resulted in a high acceptance rate of the proposed interventions.

Carer involvement in medication adherence: carer views and experiences of facilitating medication adherence using pharmacy-filled multi-compartment medication compliance aids and other methods of adherence support-a questionnaire survey

INTRODUCTION

Unpaid carers are an increasing proportion of the UK population. One of the many ways in which they help those they care for is assisting with medication adherence. Many older adults have medicines dispensed in pharmacy-filled multi-compartment medication compliance aids (pMCAs). However, evidence suggests that pMCAs may increase medication-related harm, and little is known about the interaction between the user, medication adherence systems and the carer.

AIM

To explore the views of carers supporting older adults to manage their medications with and without a pMCA.

METHOD

A researcher-administered questionnaire survey of carers supporting older adults to manage their medicines with or without a pMCA. Participants were recruited from inpatient wards, outpatient clinics and community services in central London. Responses were analysed by two independent researchers to identify overarching themes.

RESULTS

Eighty-eight unpaid carers were interviewed and responses were categorised according to the medication adherence method used; 47 supported a user with a pMCA and 41 supported without a pMCA. The main themes were: Time, Responsibility and Mistakes, Waste and Sustainability, and Polypharmacy, with sub-themes of design of multi-compartment medication compliance aids, organisation and reassurance.

CONCLUSION

Supporting medication adherence puts considerable burden on carers regardless of whether a self- or pharmacy-filled medication compliance aid is used or not. Prescribers could alleviate this burden through regular medication review by considering the prescribing frequency and duration and medication rationalisation. Redesign of both pMCAs and systems surrounding their use could also help reduce carer's burden and environmental burden.

Identifying older adults at increased risk of medication-related readmission to hospital within 30 days of discharge: development and validation of a risk assessment tool

OBJECTIVE

Developing and validating a risk assessment tool aiming to identify older adults (≥65 years) at increased risk of possibly medication-related readmission to hospital within 30 days of discharge.

DESIGN

Retrospective cohort study.

SETTING

The risk score was developed using data from a hospital in southern Sweden and validated using data from four hospitals in the mid-eastern part of Sweden.

PARTICIPANTS

The development cohort (n=720) was admitted to hospital during 2017, whereas the validation cohort (n=892) was admitted during 2017-2018.

MEASURES

The risk assessment tool aims to predict possibly medication-related readmission to hospital within 30 days of discharge. Variables known at first admission and individually associated with possibly medication-related readmission were used in development. The included variables were assigned points, and Youden's index was used to decide a threshold score. The risk score was calculated for all individuals in both cohorts. Area under the receiver operating characteristic (ROC) curve (c-index) was used to measure the discrimination of the developed risk score. Sensitivity, specificity and positive and negative predictive values were calculated using cross-tabulation.

RESULTS

The developed risk assessment tool, the Hospitalisations, Own home, Medications, and Emergency admission (HOME) Score, had a c-index of 0.69 in the development cohort and 0.65 in the validation cohort. It showed sensitivity 76%, specificity 54%, positive predictive value 29% and negative predictive value 90% at the threshold score in the development cohort.

CONCLUSION

The HOME Score can be used to identify older adults at increased risk of possibly medication-related readmission within 30 days of discharge. The tool is easy to use and includes variables available in electronic health records at admission, thus making it possible to implement risk-reducing activities during the hospital stay as well as at discharge and in transitions of care. Further studies are needed to investigate the clinical usefulness of the HOME Score as well as the benefits of implemented activities.

Uptake of pharmacist recommendations by patients after discharge: Implementation study of a patient-centered medicines review service

BACKGROUND

Polypharmacy and potentially inappropriate medicine use is common in older people, resulting in harm increased by lack of patient-centred care. Hospital clinical pharmacy services may reduce such harm, particularly prevalent at transitions of care. An implementation program to achieve such services can be a complex long-term process.

OBJECTIVES

To describe an implementation program and discuss its application in the development of a patient-centred discharge medicine review service; to assess service impact on older patients and their caregivers.

METHOD

An implementation program was begun in 2006. To assess program effectiveness, 100 patients were recruited for follow-up after discharge from a private hospital between July 2019 and March 2020. There were no exclusion criteria other than age less than 65 years. Medicine review and education were provided for each patient/caregiver by a clinical pharmacist, including recommendations for future management, written in lay language. Patients were asked to consult their general practitioner to discuss those recommendations important to them. Patients were followed-up after discharge.

RESULTS

Of 368 recommendations made, 351 (95%) were actioned by patients, resulting in 284 (77% of those actioned) being implemented, and 206 regularly taken medicines (19.7 % of all regular medicines) deprescribed.

CONCLUSION

Implementation of a patient-centred medicine review discharge service resulted in patient-reported reduction in potentially inappropriate medicine use and hospital funding of this service. This study was registered retrospectively on 12^th July 2022 with the ISRCTN registry, ISRCTN21156862, https://www.isrctn.com/ISRCTN21156862 .

Development and validation of a risk prediction model for medication administration errors among neonates in the neonatal intensive care unit: a study protocol

INTRODUCTION

Medication administration errors (MAEs) are the most common type of medication error. Furthermore, they are more common among neonates as compared with adults. MAEs can result in severe patient harm, subsequently causing a significant economic burden to the healthcare system. Targeting and prioritising neonates at high risk of MAEs is crucial in reducing MAEs. To the best of our knowledge, there is no predictive risk score available for the identification of neonates at risk of MAEs. Therefore, this study aims to develop and validate a risk prediction model to identify neonates at risk of MAEs.

METHODS AND ANALYSIS

This is a prospective direct observational study that will be conducted in five neonatal intensive care units. A minimum sample size of 820 drug preparations and administrations will be observed. Data including patient characteristics, drug preparation-related and administration-related information and other procedures will be recorded. After each round of observation, the observers will compare his/her observations with the prescriber's medication order, hospital policies and manufacturer's recommendations to determine whether MAE has occurred. To ensure reliability, the error identification will be independently performed by two clinical pharmacists after the completion of data collection for all study sites. Any disagreements will be discussed with the research team for consensus. To reduce overfitting and improve the quality of risk predictions, we have prespecified a priori the analytical plan, that is, prespecifying the candidate predictor variables, handling missing data and validation of the developed model. The model's performance will also be assessed. Finally, various modes of presentation formats such as a simplified scoring tool or web-based electronic risk calculators will be considered.

Risk factors predictive of adverse drug events and drug-related falls in aged care residents: secondary analysis from the ReMInDAR trial

BACKGROUND

Residents of aged-care facilities have high rates of adverse drug events. This study aimed to identify risk factors for adverse drug events in aged-care residents.

METHOD

This was a secondary study using data from a multicentre randomised controlled trial. Data from 224 residents for whom there was 6 months of baseline information were analysed. We assessed the risk of adverse drug events and falls (post hoc) in the subsequent 6 months. Adverse events were identified via a key word search of the resident care record and adjudicated by a multidisciplinary panel using a modified version of the Naranjo criteria. Covariates identified through univariable logistic regression, including age, sex, medicines, physical activity, cognition (Montreal Cognitive Assessment), previous adverse events and health service use were included in multivariable models.

RESULTS

Overall, 224 residents were included, with a mean age of 86 years; 70% were female. 107 (48%) residents had an adverse drug event during the 6-month follow-up. Falls and bleeding were experienced by 73 (33%) and 28 (13%) residents, respectively. Age (odds ratio [OR] 1.05, 95% confidence interval [CI] 1.01-1.10), weight (OR 1.02, 95% CI 1.002-1.04), previous fall (OR 2.58, 95% CI 1.34-4.98) and sedative or hypnotic medicine use (OR 1.98, 95% CI 1.52-2.60) were associated with increased risk of adverse drug events. Increased cognition (OR 0.89, 95% CI 0.83-0.95) was protective. Risk factors for falls were previous fall (OR 3.27, 95% CI 1.68-6.35) and sedative or hypnotic medicines (OR 3.05, 95% CI 1.14-8.16). Increased cognition (OR 0.88, 95% CI 0.83-0.95) was protective.

CONCLUSION

Our results suggest residents with a previous fall, reduced cognition, and prescription of sedative or hypnotic medicines were at higher risk of adverse drug events and should be considered for proactive prevention.

Implementation of a medicine management plan (MMP) to reduce medication-related harm (MRH) in older people post-hospital discharge: a randomised controlled trial

Background

Medication-related harm (MRH) is an escalating global challenge especially among older adults. The period following hospital discharge carries high-risk for MRH due to medication discrepancies, limited patient/carer education and support, and poor communication between hospital and community professionals. Discharge Medical Service (DMS), a newly introduced NHS scheme, aims to reduce post-discharge MRH through an electronic communication between hospital and community pharmacists. Our study team has previously developed a risk-prediction tool (RPT) for MRH in the 8-weeks period post discharge from a UK hospital cohort of 1280 patients. In this study, we aim to find out if a Medicines Management Plan (MMP) linked to the DMS is more effective than the DMS alone in reducing rates of MRH.

Method

Using a randomized control trial design, 682 older adults ≥ 65 years due to be discharged from hospital will be recruited from 4 sites. Participants will be randomized to an intervention arm (individualised medicine management plan (MMP) plus DMS) or a control arm (DMS only) using a 1:1 ratio stratification. Baseline data will include patients’ clinical and social demographics, and admission and discharge medications. At 8-weeks post-discharge, a telephone interview and review of GP records by the study pharmacist will verify MRH in both arms. An economic and process evaluation will assess the cost and acceptability of the study methods.

Data analysis

Univariate analysis will be done for baseline variables comparing the intervention and control arms. A multivariate logistic regression will be done incorporating these variables. Economic evaluation will compare the cost-of-service use among the study arms and modelled to provide national estimates. Qualitative data from focus-group interviews will explore practitioners’ understanding, and acceptance of the MMP, DMS and the RPT.

Conclusion

This study will inform the use of an objective, validated RPT for MRH among older adults after hospital discharge, and provide a clinical, economic, and service evaluation of a specific medicines management plan alongside the DMS in the National Health Service (UK).

Development of Screening Tools to Predict Medication-Related Problems Across the Continuum of Emergency Department Care: A Prospective, Multicenter Study

Background: Medication-related problems (MRPs) occur across the continuum of emergency department (ED) care: they may contribute to ED presentation, occur in the ED/short-stay unit (SSU), at hospital admission, or shortly after discharge to the community. This project aimed to determine predictors for MRPs across the continuum of ED care and incorporate these into screening tools (one for use at ED presentation and one at ED/SSU discharge), to identify patients at greatest risk, who could be targeted by ED pharmacists.

Methods: A prospective, observational, multicenter study was undertaken in nine EDs, between July 2016 and August 2017. Blocks of ten consecutive adult patients presenting at pre-specified times were identified. Within 1 week of ED discharge, a pharmacist interviewed patients and undertook a medical record review to determine a medication history, patient understanding of treatment, risk factors for MRPs and to manage the MRPs. Logistic regression was undertaken to determine predictor variables. Multivariable regression beta coefficients were used to develop a scoring system for the two screening tools.

Results: Of 1,238 patients meeting all inclusion criteria, 904 were recruited. Characteristics predicting MRPs related to ED presentation were: patient self-administers regular medications (OR = 7.95, 95%CI = 3.79–16.65), carer assists with medication administration (OR = 15.46, 95%CI = 6.52–36.67), or health-professional administers (OR = 5.01, 95%CI = 1.77–14.19); medication-related ED presentation (OR = 9.95, 95%CI = 4.92–20.10); age ≥80 years (OR = 3.63, 95%CI = 1.96–6.71), or age 65–79 years (OR = 2.01, 95%CI = 1.17–3.46); potential medication adherence issue (OR = 2.27, 95%CI = 1.38–3.73); medical specialist seen in past 6-months (OR = 2.02, 95%CI = 1.42–2.85); pharmaceutical benefit/pension/concession cardholder (OR = 1.89, 95%CI = 1.28–2.78); inpatient in previous 4-weeks (OR = 1.60, 95%CI = 1.02–2.52); being male (OR = 1.48, 95%CI = 1.05–2.10); and difficulties reading labels (OR = 0.63, 95%CI = 0.40–0.99). Characteristics predicting MRPs related to ED discharge were: potential medication adherence issue (OR = 6.80, 95%CI = 3.97–11.64); stay in ED > 8 h (OR = 3.23, 95%CI = 1.47–7.78); difficulties reading labels (OR = 2.33, 95%CI = 1.30–4.16); and medication regimen changed in ED (OR = 3.91, 95%CI = 2.43–6.30). For ED presentation, the model had a C-statistic of 0.84 (95% CI 0.81–0.86) (sensitivity = 80%, specificity = 70%). For ED discharge, the model had a C-statistic of 0.78 (95% CI 0.73–0.83) (sensitivity = 82%, specificity = 57%).

Conclusion: Predictors of MRPs are readily available at the bedside and may be used to screen for patients at greatest risk upon ED presentation and upon ED/SSU discharge to the community. These screening tools now require external validation and implementation studies to evaluate the impact of using such tools on patient care outcomes.

Is a High Medication Risk Score Associated With Increased Risk of 30-Day Readmission? A Population-Based Cohort Study From CROSS-TRACKS

OBJECTIVES

The primary aim of this study was to evaluate whether a high Medication Risk Score (MERIS) upon admission to an emergency department is associated with increased risk of 30-day readmission in patients discharged directly home. Mortality, visit to general practitioner, and drug changes within 30 days were included as secondary outcomes.

METHODS

This is a historical cohort study with data from the Danish population-based open-cohort CROSS-TRACKS. Cox regression analyses were used to determine whether a high MERIS score was associated with increased risk of 30-day readmission and mortality. Visit to general practitioner and drug changes were tested with χ2 test and Wilcoxon rank sum test.

RESULTS

A total of 2106 patients were eligible: 2017 had a MERIS score lower than 14 (low-risk group), and 89 had a score of 14 or higher (high-risk group). The proportion of patients in the high-risk group who were readmitted was 21.3% compared with 16.3% in the low-risk group, resulting in a hazard ratio for readmission of 1.43 (95% confidence interval, 0.9-1.3). The hazard ratio for mortality was 8.3 (95% confidence interval, 3.0-22.8). No statistical significant difference was found in general practitioner visits; however, significantly more drug changes were observed in the high-risk group.

CONCLUSIONS

A high MERIS score was associated with increased risk of readmissions and can potentially assist healthcare professionals in the prioritizing of patients who may benefit from further exam, for example, additional medication review in acute care setting. Further investigation of MERIS and exploration of causal inferences between medication-related harm and medication-related readmissions are warranted.

Development and Pilot Implementation of a Training Framework to Prepare and Integrate Pharmacy Students into a Multicentre Hospital Research Study

A unique approach was introduced to integrate pharmacy students into a multicentre patient-centred research project predicting medication related harm (MRH) post-discharge. A training framework was developed to prepare students for research participation and integration. The framework aligned research project tasks with the pharmacists’ national competency standards framework. The framework was piloted on four research placement students from two local universities during three hospital placements, from October 2020 to August 2021. Following their initial orientation and training, students collected data from 38 patients and were involved in patient screening processes, interviewing, data collection and analysis. Patients’ MRH risk scores correlated with re-admission rates with 16/38 (42%) of patients re-admitted within eight weeks following discharge. Their participation in the research enabled students to obtain skills in (1) literature searching, (2) maintaining patient confidentiality, (3) interviewing patients, (4) obtaining data from medical records, (5) communicating with patients and clinicians, and (6) the use of clinical information to predict MRH risk.

A multi-centre cohort study on healthcare use due to medication-related harm: the role of frailty and polypharmacy

Objectives

To determine the association between frailty and medication-related harm requiring healthcare utilisation.

Design

Prospective observational cohort study.

Setting

Six primary and five secondary care sites across South East England, September 2013–November 2015.

Participants

One thousand and two hundred and eighty participants, ≥65 years old, who were due for discharge from general medicine and older persons’ wards following an acute episode of care. Exclusion criteria were limited life expectancy, transfer to another hospital and consent not gained.

Main outcome measures

Medication-related harm requiring healthcare utilisation (including primary, secondary or tertiary care consultations related to MRH), including adverse drug reactions, non-adherence and medication error determined via the review of data from three sources: patient/carer reports gathered through a structured telephone interview; primary care medical record review; and prospective consultant-led review of readmission to recruiting hospital. Frailty was measured using a Frailty Index, developed using a standardised approach. Marginal estimates were obtained from logistic regression models to examine how probabilities of healthcare service use due to medication-related harm were associated with increasing number of medicines and frailty.

Results

Healthcare utilisation due to medication-related harm was significantly associated with frailty (OR = 10.06, 95% CI 2.06–49.26, P = 0.004), independent of age, gender, and number of medicines. With increasing frailty, the need for healthcare use as a result of MRH increases from a probability of around 0.2–0.4. This is also the case for the number of medicines.

Conclusions

Frailty is associated with MRH, independent of polypharmacy. Reducing the burden of frailty through an integrated health and social care approach, alongside strategies to reduce inappropriate polypharmacy, may reduce MRH related healthcare utilisation.

Developing PHarmacie-R: A bedside risk prediction tool with a medicines management focus to identify risk of hospital readmission

BACKGROUND

The imperative to identify patients at risk of medication-related harm has never been greater. Hospital clinicians cannot easily predict risk of readmission or harm. Candidate variables associated with medication-related harm derived from the literature or significantly represented in a complex patient cohort have been previously described by PHarmacie-4. With a focus on polypharmacy and high-risk medicines in vulnerable patient cohorts, PHarmacie-4 was easy to use and highlighted risks. However it over-estimated risk, reducing its usefulness in stratifying risk of readmission.

OBJECTIVE

Develop a risk prediction tool built into a smart phone app, enabling clinicians to identify and refer high-risk patients for an early post-discharge medicines review. Demonstrate usability, real world application and validity in an independent dataset.

METHODS

A retrospective, observational study was conducted with 1201 randomly selected patients admitted to Sir Charles Gairdner Hospital between June 1, 2016 to December 31, 2016. Patient characteristics and outcomes of interest were reported, including unplanned hospital utilisation at 30, 60 and 90 days post-discharge. Using multivariable logistic regression modelling, an algorithm was developed, built into a smart phone app and used and validated in an independent dataset.

RESULTS

738 patients (61%) were included in the derivation sample. The best predictive performance was achieved by PHarmacie-R (C-statistic 0.72, 95% CI 0.68-0.75) which included PHarmacie-4 risk variables, a non-linear effect of age, unplanned hospital utilisation in the preceding six months and gender. The independent validation dataset had a C-statistic of 0.64 (95% CI 0.56-0.72).

CONCLUSION

PHarmacie-R is the first readmission risk prediction tool, built into a smart phone app, focussing on polypharmacy and high-risk medicines in vulnerable patients. It can assist clinical pharmacists to identify medical inpatients who may benefit from early post-discharge medication management services. External validation is needed to enable application in other clinical settings.

Differences in Pharmaceutical Intervention Triggers for the Optimization of Medication by Patient Age: A University Hospital Study

Optimization of medication therapy for the elderly is a matter of rapidly growing importance, which is addressed by pharmacists through comprehensive reviews. In this study, the impact of medication review by pharmacists on medication optimization and avoidance of adverse drug events (ADE) was investigated, as well as differences in the triggers for pharmaceutical intervention to allow for optimization of medication by patient age. Data for this study were collected from reports recorded between April 2013 and March 2019 for patients admitted to the Hiroshima University Hospital. In response to pharmacists' proposals, prescriptions were modified in 18932 cases, comprising 17% of the total 111479 patients during hospitalization. The frequency of such intervention was higher in elderly patients aged ≥65 years than in those <65 years (20 vs. 14%, p < 0.01). The reasons for pharmacists' intervention were primarily (67%) medication history or clinical symptoms in all age groups. Patient complaint was a minor reason in patients aged ≥75 years, accounting for only 2% of all interventions; laboratory results were a more typical reason, accounting for 24% of all interventions. These findings reveal the importance of pharmacists' interventions for optimizing medication and preventing ADEs, particularly in elderly patients. Thus, pharmacists must evaluate the medications and conditions, including laboratory results, in the medical records of elderly patients more carefully than those of younger patients as elderly patients might be unable to communicate about subjective symptoms.

Prevalence and Nature of Medication Errors and Medication-Related Harm Following Discharge from Hospital to Community Settings: A Systematic Review

Background

Little is known about the epidemiology of medication errors and medication-related harm following transition from secondary to primary care. This systematic review aims to identify and critically evaluate the available evidence on the prevalence and nature of medication errors and medication-related harm following hospital discharge.

Methods

Studies published between January 1990 and March 2019 were searched across ten electronic databases and the grey literature. No restrictions were applied with publication language or patient population studied. Studies were included if they contained data concerning the rate of medication errors, unintentional medication discrepancies, or adverse drug events. Two authors independently extracted study data.

Results

Fifty-four studies were included, most of which were rated as moderate (39/54) or high (7/54) quality. For adult patients, the median rate of medication errors and unintentional medication discrepancies following discharge was 53% [interquartile range 33–60.5] (n = 5 studies) and 50% [interquartile range 39–76] (n = 11), respectively. Five studies reported adverse drug reaction rates with a median of 27% [interquartile range 18–40.5] and seven studies reported adverse drug event rates with a median of 19% [interquartile range 16–24]. For paediatric patients, one study reported a medication error rate of 66.3% and another an adverse drug event rate of 9%. Almost a quarter of studies (13/54, 24%) utilised a follow-up period post-discharge of 1 month (range 2–180 days). Drug classes most commonly implicated with adverse drug events were antibiotics, antidiabetics, analgesics and cardiovascular drugs.

Conclusions

This is the first systematic review to explore the prevalence and nature of medication errors and adverse drug events following hospital discharge. Targets for future work have been identified.

Electronic supplementary material

The online version of this article (10.1007/s40264-020-00918-3) contains supplementary material, which is available to authorized users.

Research Trends in Artificial Intelligence Applications in Human Factors Health Care: Mapping Review

BACKGROUND

Despite advancements in artificial intelligence (AI) to develop prediction and classification models, little research has been devoted to real-world translations with a user-centered design approach. AI development studies in the health care context have often ignored two critical factors of ecological validity and human cognition, creating challenges at the interface with clinicians and the clinical environment.

OBJECTIVE

The aim of this literature review was to investigate the contributions made by major human factors communities in health care AI applications. This review also discusses emerging research gaps, and provides future research directions to facilitate a safer and user-centered integration of AI into the clinical workflow.

METHODS

We performed an extensive mapping review to capture all relevant articles published within the last 10 years in the major human factors journals and conference proceedings listed in the "Human Factors and Ergonomics" category of the Scopus Master List. In each published volume, we searched for studies reporting qualitative or quantitative findings in the context of AI in health care. Studies are discussed based on the key principles such as evaluating workload, usability, trust in technology, perception, and user-centered design.

RESULTS

Forty-eight articles were included in the final review. Most of the studies emphasized user perception, the usability of AI-based devices or technologies, cognitive workload, and user's trust in AI. The review revealed a nascent but growing body of literature focusing on augmenting health care AI; however, little effort has been made to ensure ecological validity with user-centered design approaches. Moreover, few studies (n=5 against clinical/baseline standards, n=5 against clinicians) compared their AI models against a standard measure.

CONCLUSIONS

Human factors researchers should actively be part of efforts in AI design and implementation, as well as dynamic assessments of AI systems' effects on interaction, workflow, and patient outcomes. An AI system is part of a greater sociotechnical system. Investigators with human factors and ergonomics expertise are essential when defining the dynamic interaction of AI within each element, process, and result of the work system.

Medication-related hospital readmissions within 30 days of discharge-A retrospective study of risk factors in older adults

Background

Previous studies have shown that approximately 20% of hospital readmissions can be medication-related and 70% of these readmissions are possibly preventable. This retrospective medical records study aimed to find risk factors associated with medication-related readmissions to hospital within 30 days of discharge in older adults (≥65 years).

Methods

30-day readmissions (n = 360) were assessed as being either possibly or unlikely medication-related after which selected variables were used to individually compare the two groups to a comparison group (n = 360). The aim was to find individual risk factors of possibly medication-related readmissions focusing on living arrangements, polypharmacy, potentially inappropriate medication therapy, and changes made to medication regimens at initial discharge.

Results

A total of 143 of the 360 readmissions (40%) were assessed as being possibly medication-related. Charlson Comorbidity Index (OR 1.15, 95%CI 1.5–1.25), excessive polypharmacy (OR 1.74, 95%CI 1.07–2.81), having adjustments made to medication dosages at initial discharge (OR 1.63, 95%CI 1.03–2.58) and living in your own home, alone, were variables identified as risk factors of such readmissions. Living in your own home, alone, increased the odds of a possibly medication-related readmission 1.69 times compared to living in your own home with someone (p-value 0.025) and 2.22 times compared to living in a nursing home (p-value 0.037).

Conclusion

Possibly medication-related readmissions within 30 days of discharge, in patients 65 years and older, are common. The odds of such readmissions increase in comorbid, highly medicated patients living in their own home, alone, and if having medication dosages adjusted at initial discharge. These results indicate that care planning before discharge and the provision of help with, for example, managing medications after discharge, are factors especially important if aiming to reduce the amount of medication-related readmissions among this population. Further research is needed to confirm this hypothesis.

The effect of a transitional pharmaceutical care program on the occurrence of ADEs after discharge from hospital in patients with polypharmacy

INTRODUCTION

Transitional care programs (i.e. interventions delivered both in hospital and in primary care), could increase continuity and consequently quality of care. However, limited studies on the effect of these programs on Adverse Drug Events (ADEs) post-discharge are available. Therefore, the aim of this study was to investigate the effect of a transitional pharmaceutical care program on the occurrence of ADEs 4 weeks post-discharge.

METHODS

A multicentre prospective before-after study was performed in a general teaching hospital, a university hospital and 49 community pharmacies. The transitional pharmaceutical care program consisted of: teach-back to the patient at discharge, a pharmaceutical discharge letter, a home visit by a community pharmacist and a clinical medication review by both the community and the clinical pharmacist, on top of usual care. Usual care consisted of medication reconciliation at admission and discharge by pharmacy teams. The primary outcome was the proportion of patients who reported at least 1 ADE 4 weeks post-discharge. Multivariable logistic regression was used to adjust for potential confounders.

RESULTS

In total, 369 patients were included (control: n = 195, intervention: n = 174). The proportion of patients with at least 1 ADE did not statistically significant differ between the intervention and control group (general teaching hospital: 59% vs. 67%, OR_adj 0.70 [95% CI 0.38-1.31], university hospital: 63% vs 50%, OR _adj 1.76 [95% CI 0.75-4.13]).

CONCLUSION

The transitional pharmaceutical care program did not decrease the proportion of patients with ADEs after discharge. ADEs after discharge were common and more than 50% of patients reported at least 1 ADE. A process evaluation is needed to gain insight into how a transitional pharmaceutical care program could diminish those ADEs.

Preventable medication harm across health care settings: a systematic review and meta-analysis

BACKGROUND

Mitigating or reducing the risk of medication harm is a global policy priority. But evidence reflecting preventable medication harm in medical care and the factors that derive this harm remain unknown. Therefore, we aimed to quantify the prevalence, severity and type of preventable medication harm across medical care settings.

METHODS

We performed a systematic review and meta-analysis of observational studies to compare the prevalence of preventable medication harm. Searches were carried out in Medline, Cochrane library, CINAHL, Embase and PsycINFO from 2000 to 27 January 2020. Data extraction and critical appraisal was undertaken by two independent reviewers. Random-effects meta-analysis was employed followed by univariable and multivariable meta-regression. Heterogeneity was quantified using the I² statistic, and publication bias was evaluated.

PROSPERO

CRD42020164156.

RESULTS

Of the 7780 articles, 81 studies involving 285,687 patients were included. The pooled prevalence for preventable medication harm was 3% (95% confidence interval (CI) 2 to 4%, I² = 99%) and for overall medication harm was 9% (95% CI 7 to 11%, I² = 99.5%) of all patient incidence records. The highest rates of preventable medication harm were seen in elderly patient care settings (11%, 95% 7 to 15%, n = 7), intensive care (7%, 4 to 12%, n = 6), highly specialised or surgical care (6%, 3 to 11%, n = 13) and emergency medicine (5%, 2 to 12%, n = 12). The proportion of mild preventable medication harm was 39% (28 to 51%, n = 20, I² = 96.4%), moderate preventable harm 40% (31 to 49%, n = 22, I² = 93.6%) and clinically severe or life-threatening preventable harm 26% (15 to 37%, n = 28, I² = 97%). The source of the highest prevalence rates of preventable harm were at the prescribing (58%, 42 to 73%, n = 9, I² = 94%) and monitoring (47%, 21 to 73%, n = 8, I² = 99%) stages of medication use. Preventable harm was greatest in medicines affecting the 'central nervous system' and 'cardiovascular system'.

CONCLUSIONS

This is the largest meta-analysis to assess preventable medication harm. We conclude that around one in 30 patients are exposed to preventable medication harm in medical care, and more than a quarter of this harm is considered severe or life-threatening. Our results support the World Health Organisation's push for the detection and mitigation of medication-related harm as being a top priority, whilst highlighting other key potential targets for remedial intervention that should be a priority focus for future research.

Development and validation of the Adverse Inpatient Medication Event model (AIME)

AIMS

Medication harm has negative clinical and economic consequences, contributing to hospitalisation, morbidity and mortality. The incidence ranges from 4 to 14%, of which up to 50% of events may be preventable. A predictive model for identifying high-risk inpatients can guide a timely and systematic approach to prioritisation. The aim of this study is to develop and internally validate a risk prediction model for prioritisation of hospitalised patients at risk of medication harm.

METHODS

A retrospective cohort study was conducted in general medical and geriatric specialties at an Australian hospital over six months. Medication harm was identified using International Classification of Disease (ICD-10) codes and the hospital's incident database. Sixty-eight variables, including medications and laboratory results, were extracted from the hospital's databases. Multivariable logistic regression was used to develop the final risk model. Performance was evaluated using area under the receiver operative characteristic curve (AuROC) and clinical utility was determined using decision curve analysis.

RESULTS

The study cohort included 1982 patients with median age 74 years, of which 136 (7%) experienced at least one adverse medication event(s). The model included: length of stay, hospital re-admission within 12 months, venous or arterial thrombosis and/or embolism, ≥ 8 medications, serum sodium < 126 mmol/L, INR > 3, anti-psychotic, antiarrhythmic and immunosuppressant medications, and history of medication allergy. Validation gave an AuROC of 0.70 (95% CI: 0.65-0.74). Decision curve analysis identified that the AIME may be clinically useful to help guide decision making in practice.

CONCLUSION

We have developed a predictive model with reasonable performance. Future steps include external validation and impact evaluation.

Medication adherence: understanding the issues and finding solutions

Medication is the most frequent treatment intervention, and its success depends on patients taking their medicines in line with their prescribed regimen to yield the full benefit of the treatment. Adherence is especially difficult to ensure in those with multimorbidity, who take multiple medications to manage their conditions. Non-adherence is costly for the health service, both through wastage and increased ill health. Non-adherence may be intentional or non-intentional, and many factors affect an individual's compliance with a medication regimen. There are a variety of aids that may be helpful; however, the interaction with a health professional is very important, both for understanding the reason for non-adherence and for promoting adherence.

The effect of an inpatient geriatric stewardship on drug-related problems reported by patients after discharge

Background Drug-related problems after discharge are common among older adults with polypharmacy. Medication review during hospitalization has been proposed as one solution. Inpatient medication review is often based on clinical records only. An obstacle is the lack of insight into the outpatient history. Therefore, a geriatric stewardship was designed and involved an inpatient medication review by a hospital pharmacist and geriatrician based on (I) clinical records to draft initial recommendations, (II) consultations with primary care providers (general practitioner and community pharmacist) to discuss the hospital-based recommendations, (III) patient interviews to assess their needs, and (IV) a multidisciplinary evaluation of all previous steps to draft final recommendations. Objective To assess the effect of the geriatric stewardship on drug-related problems reported by patients after discharge. Setting General teaching hospital. Methods An implementation study (pre-post design) was performed. Orthopaedic and surgical patients (≥ 65 years) with polypharmacy and a frailty risk factor were included. The pre-group received usual care, the post-group received the geriatric stewardship intervention. Two weeks post-discharge, patient-reported drug-related problems were assessed using a validated questionnaire. Drug-related problems were classified into drug-related complaints, practical problems, and questions about medication. Outcomes The outcomes were the number and type of drug-related problems per patient (primary) and the number of initial recommendations that were altered due to primary care provider and patient input (secondary). Results In total, 127 patients were analysed (usual care n = 74, intervention n = 53). Intervention patients reported fewer drug-related problems compared to usual care: 2.8 versus 3.3 per patient (Adjusted relative risk 0.83, 95% confidence interval 0.66-1.05). This difference resulted from a halving in drug-related complaints (p < 0.05), for example pain, drowsiness, nausea or constipation. Nearly 30% of the initial recommendations based on the clinical records were discarded or modified after primary care provider consultations and patient interviews. Conclusion The geriatric stewardship did not significantly reduce drug-related problems, but it significantly halved drug-related complaints. One-in-three initial recommendations were altered due to primary care provider and patient input. Inpatient medication reviews should not be based on clinical records only; they require transmural collaboration and patient participation to ensure continuity of patient care.

Medication Regimen Complexity Index Prediction of Adverse Drug Reaction-Related Hospital Admissions

BACKGROUND

The relationship between the medication regimen complexity index (MRCI) and adverse drug reaction (ADR)-related hospital admissions has not yet specifically been investigated.

OBJECTIVE

To evaluate the MRCI and compare with medication count for prediction of ADR-related hospital admissions in older patients.

METHODS

This was a retrospective analysis of a prospectively collected convenience sample of 768 unplanned medical admissions of Australians aged 65 years old and older. The sample consisted of 115 (15.0%) ADR-related unplanned hospital admissions and 653 (85.0%) non-ADR-related unplanned medical admissions. The MRCI score was calculated from the medical records and analyzed to predict ADR-related hospital admissions.

RESULTS

The cohort had a median age of 81 years, 5 comorbidities, and 11 medications, with a slight majority of women. The MRCI score was not significantly different in patients who had ADR-related admissions compared with other medical admissions-38.5 versus 34.0, respectively; Wilcoxon Rank Sum test W = 33 522; P = 0.067. The medication count was significantly different between the ADR-related admissions compared with other medical admissions: 12 versus 10; W = 32 508; P = 0.021. However, the medication count was not a strong predictor of ADR-related admissions; unadjusted odds ratio = 1.044; 95% CI = 1.006-1.084.

CONCLUSION AND RELEVANCE

The MRCI score did not discriminate between ADR-related admissions and other medical admissions despite taking time to calculate with potential for inconsistent application. Medication count is more readily applicable with marginally greater relevance in this cohort; however, both measures do not appear to be useful when used alone for clinicians to identify patients at risk of ADRs.