Predicting adverse drug reactions in older adults; a systematic review of the risk prediction models

Potentially Inappropriate Medication Use and Polypharmacy Before and After Admission to Internal Medicine for Older Patients

BACKGROUND

With the aging of the population and the increase in chronic diseases, there is an inherent risk of polypharmacy and inappropriate medication use. This study aimed to determine the prevalence and incidence of potentially inappropriate medication use and its correlation with polypharmacy.

METHODS

This was a retrospective, population-based cohort study among patients ≥ 65 years hospitalized at The National University Hospital of Iceland from 2010-2020. Data on medication usage were retrieved from the National Prescription Medicine Registry. Based on the number of medications filled in the year prior to admission and post-discharge, participants were categorized as non-polypharmacy (<5), polypharmacy (5-9), and hyper-polypharmacy (≥10). The prevalence and incidence of potentially inappropriate medication use was assessed based on the 2019 Beers criteria. Regression models were used to correlate sociodemographic, clinical, and pharmacoepidemiologic variables and the odds of new potentially inappropriate medication use.

RESULTS

The cohort comprised 55,859 patients (48.5% male) with a median [interquartile range] age of 80 [73-86] years. The prevalence of inappropriate medication use in the year preceding admission was 34.0%, 77.7%, and 96.4% for patients with non-polypharmacy, polypharmacy, and hyper-polypharmacy, respectively. The incidence of new potentially inappropriate medication use was 46.7% (95% confidence interval 45.6%-47.6%) among those with no potentially inappropriate medication use pre-admission. Factors associated with higher odds of new potentially inappropriate medication use after discharge were the use of multi-dose dispensing services, dementia, polypharmacy, and hyper-polypharmacy.

CONCLUSIONS

An increased emphasis is needed to review and reevaluate the appropriateness of medication use among the older population in internal medicine.

Protocol for the development and validation of a Polypharmacy Assessment Score

BACKGROUND

An increasing number of people are using multiple medications each day, named polypharmacy. This is driven by an ageing population, increasing multimorbidity, and single disease-focussed guidelines. Medications carry obvious benefits, yet polypharmacy is also linked to adverse consequences including adverse drug events, drug-drug and drug-disease interactions, poor patient experience and wasted resources. Problematic polypharmacy is 'the prescribing of multiple medicines inappropriately, or where the intended benefits are not realised'. Identifying people with problematic polypharmacy is complex, as multiple medicines can be suitable for people with several chronic conditions requiring more treatment. Hence, polypharmacy is often potentially problematic, rather than always inappropriate, dependent on clinical context and individual benefit vs risk. There is a need to improve how we identify and evaluate these patients by extending beyond simple counts of medicines to include individual factors and long-term conditions.

AIM

To produce a Polypharmacy Assessment Score to identify a population with unusual levels of prescribing who may be at risk of potentially problematic polypharmacy.

METHODS

Analyses will be performed in three parts: 1. A prediction model will be constructed using observed medications count as the dependent variable, with age, gender and long-term conditions as independent variables. A 'Polypharmacy Assessment Score' will then be constructed through calculating the differences between the observed and expected count of prescribed medications, thereby highlighting people that have unexpected levels of prescribing. Parts 2 and 3 will examine different aspects of validity of the Polypharmacy Assessment Score: 2. To assess 'construct validity', cross-sectional analyses will evaluate high-risk prescribing within populations defined by a range of Polypharmacy Assessment Scores, using both explicit (STOPP/START criteria) and implicit (Medication Appropriateness Index) measures of inappropriate prescribing. 3. To assess 'predictive validity', a retrospective cohort study will explore differences in clinical outcomes (adverse drug reactions, unplanned hospitalisation and all-cause mortality) between differing scores.

DISCUSSION

Developing a cross-cutting measure of polypharmacy may allow healthcare professionals to prioritise and risk stratify patients with polypharmacy using unusual levels of prescribing. This would be an improvement from current approaches of either using simple cutoffs or narrow prescribing criteria.

Risk of emergency hospital admission related to adverse events after antibiotic treatment in adults with a common infection: impact of COVID-19 and derivation and validation of risk prediction models

BACKGROUND

With the global challenge of antimicrobial resistance intensified during the COVID-19 pandemic, evaluating adverse events (AEs) post-antibiotic treatment for common infections is crucial. This study aims to examines the changes in incidence rates of AEs during the COVID-19 pandemic and predict AE risk following antibiotic prescriptions for common infections, considering their previous antibiotic exposure and other long-term clinical conditions.

METHODS

With the approval of NHS England, we used OpenSAFELY platform and analysed electronic health records from patients aged 18-110, prescribed antibiotics for urinary tract infection (UTI), lower respiratory tract infections (LRTI), upper respiratory tract infections (URTI), sinusitis, otitis externa, and otitis media between January 2019 and June 2023. We evaluated the temporal trends in the incidence rate of AEs for each infection, analysing monthly changes over time. The survival probability of emergency AE hospitalisation was estimated in each COVID-19 period (period 1: 1 January 2019 to 25 March 2020, period 2: 26 March 2020 to 8 March 2021, period 3: 9 March 2021 to 30 June 2023) using the Kaplan-Meier approach. Prognostic models, using Cox proportional hazards regression, were developed and validated to predict AE risk within 30 days post-prescription using the records in Period 1.

RESULTS

Out of 9.4 million patients who received antibiotics, 0.6% of UTI, 0.3% of URTI, and 0.5% of LRTI patients experienced AEs. UTI and LRTI patients demonstrated a higher risk of AEs, with a noted increase in AE incidence during the COVID-19 pandemic. Higher comorbidity and recent antibiotic use emerged as significant AE predictors. The developed models exhibited good calibration and discrimination, especially for UTIs and LRTIs, with a C-statistic above 0.70.

CONCLUSIONS

The study reveals a variable incidence of AEs post-antibiotic treatment for common infections, with UTI and LRTI patients facing higher risks. AE risks varied between infections and COVID-19 periods. These findings underscore the necessity for cautious antibiotic prescribing and call for further exploration into the intricate dynamics between antibiotic use, AEs, and the pandemic.

The association of degree of polypharmacy before and after among hospitalised internal medicine patients and clinical outcomes: a retrospective, population-based cohort study

OBJECTIVES

To determine the prevalence and incidence of polypharmacy/hyperpolypharmacy and which medications are most prescribed to patients with varying burden of polypharmacy.

DESIGN

Retrospective, population-based cohort study.

SETTING

Iceland.

PARTICIPANTS

Including patients (≥18 years) admitted to internal medicine services at Landspitali - The National University Hospital of Iceland, between 1 January 2010 with a follow-up of clinical outcomes through 17 March 2022.

MAIN OUTCOMES MEASURES

Participants were categorised into medication use categories of non-polypharmacy (<5), polypharmacy (5-10) and hyperpolypharmacy (>10) based on the number of medications filled in the year predischarge and postdischarge. The primary outcome was prevalence and incidence of new polypharmacy. Secondary outcomes were mortality, length of hospital stay and re-admission.

RESULTS

Among 85 942 admissions (51% male), the median (IQR) age was 73 (60-83) years. The prevalence of preadmission non-polypharmacy was 15.1% (95% CI 14.9 to 15.3), polypharmacy was 22.9% (95% CI 22.6 to 23.2) and hyperpolypharmacy was 62.5% (95% CI 62.2 to 62.9). The incidence of new postdischarge polypharmacy was 33.4% (95% CI 32.9 to 33.9), and for hyperpolypharmacy was 28.9% (95% CI 28.3 to 29.5) for patients with preadmission polypharmacy. Patients with a higher level of medication use were more likely to use multidose drug dispensing and have a diagnosis of adverse drug reaction. Other comorbidities, including responsible subspeciality and estimates of comorbidity and frailty burden, were identical between groups of varying polypharmacy. There was no difference in length of stay, re-admission rate and mortality.

CONCLUSIONS

Preadmission polypharmacy/hyperpolypharmacy and postdischarge new polypharmacy/hyperpolypharmacy is common amongst patients admitted to internal medicine. A higher level of medication use category was not found to be associated with demographic, comorbidity and clinical outcomes. Medications that are frequently inappropriately prescribed were among the most prescribed medications in the group. An increased focus on optimising medication usage is needed after hospital admission.

TRIAL REGISTRATION NUMBER

NCT05756400.

Strategies for translating proteomics discoveries into drug discovery for dementia

Tauopathies, diseases characterized by neuropathological aggregates of tau including Alzheimer's disease and subtypes of frontotemporal dementia, make up the vast majority of dementia cases. Although there have been recent developments in tauopathy biomarkers and disease-modifying treatments, ongoing progress is required to ensure these are effective, economical, and accessible for the globally ageing population. As such, continued identification of new potential drug targets and biomarkers is critical. "Big data" studies, such as proteomics, can generate information on thousands of possible new targets for dementia diagnostics and therapeutics, but currently remain underutilized due to the lack of a clear process by which targets are selected for future drug development. In this review, we discuss current tauopathy biomarkers and therapeutics, and highlight areas in need of improvement, particularly when addressing the needs of frail, comorbid and cognitively impaired populations. We highlight biomarkers which have been developed from proteomic data, and outline possible future directions in this field. We propose new criteria by which potential targets in proteomics studies can be objectively ranked as favorable for drug development, and demonstrate its application to our group's recent tau interactome dataset as an example.

Medication clusters at hospital discharge and risk of adverse drug events at 30 days postdischarge: A population-based cohort study of older adults

AIMS

Certain combinations of medications can be harmful and may lead to serious adverse drug events (ADEs). Identifying potentially problematic medication clusters could help guide prescribing and/or deprescribing decisions in hospital. The aim of this study is to characterize medication prescribing patterns at hospital discharge and determine which medication clusters were associated with an increased risk of ADEs in the 30-day posthospital discharge.

METHODS

All residents of the province of Ontario in Canada aged 66 years or older admitted to hospital between March 2016 and February 2017 were included. Identification of medication clusters prescribed at hospital discharge was conducted using latent class analysis. Cluster identification and categorization were based on medications dispensed up to 30-day posthospitalization. Multivariable logistic regression was used to assess the potential association between membership to a particular medication cluster and ADEs postdischarge, while also evaluating other patient characteristics.

RESULTS

In total, 188 354 patients were included in the study cohort. Median age (interquartile range) was 77 (71-84) years, and patients had a median (IQR) (interquartile range [IQR]) of 9 (6-13) medications dispensed prior to admission. Within the study population, 6 separate clusters of dispensing patterns were identified: cardiovascular (14%), respiratory (26%), complex care needs (12%), cardiovascular and metabolic (15%), infection (10%), and surgical (24%). Overall, 12 680 (7%) patients had an ADE in the 30 days following discharge. After considering other patient characteristics, those belonging to the respiratory cluster had the highest risk of ADEs (adjusted odds ratio: 1.12, 95% confidence interval: 1.08-1.17) compared with all the other clusters, while those in the complex care needs cluster had the lowest risk (adjusted odds ratio: 0.82, 95% confidence interval: 0.77-0.87).

CONCLUSION

This study suggests that ADEs post hospital discharge can be linked with identifiable medication clusters. This information may help clinicians and researchers better understand patient populations that are more or less likely to benefit from peri-hospital discharge interventions aimed at reducing ADEs.

Costs associated with adverse drug reactions in an older population admitted to hospital: a prospective cohort study

PURPOSE

This study examines healthcare costs associated with adverse drug reactions (ADR) in an older population admitted acutely to an Irish tertiary hospital.

METHODS

Prospective cohort study involving older persons admitted to hospital with and without an ADR. Data was collected at baseline, during hospitalisation and post-discharge. Participants provided information on healthcare resource use three months before admission (baseline) and three months after discharge (follow-up). For each healthcare resource, unit costs were derived and applied. The average cost (standard deviation (SD)) associated with the hospital admission for the ADR and non-ADR are presented. In addition, baseline and follow-up care costs were compared using difference-in-difference analysis and presented with 95% confidence intervals (CI). Costs by preventability and severity of ADR are also presented.

RESULTS

A total of n = 230 participants were included (n = 93 ADR and n = 137 without ADR). The average cost associated with hospital admission for an ADR was €9538 (SD €10442) and €9828 (SD €11770) for non-ADR. The additional follow-up costs (difference-in-difference) associated with the ADR was estimated at €2047 (95% CI: -€889 to €4983). The mean incremental follow-up cost of definite preventable ADRs was estimated at €1648 (95% CI: -€4310 to €7605), possible preventable ADRs €2259 (95 CI: -€1194 to €5712) and unavoidable ADRs €1757 (95% CI: -€3377 to €6890). The mean incremental follow-up cost associated with moderate severe ADRs was estimated at €1922 (95% CI: -€1088 to €4932) and €3580 (95% CI: -€4898 to €12,058) for severe ADRs.  CONCLUSION: ADRs leading to hospital admission are associated with modest incremental healthcare costs during and three months after admission. Severe and possibly preventable ADRs were associated with higher costs.

Metabolic adverse events of multitarget kinase inhibitors: a systematic review

PURPOSE

Multitargeted kinase inhibitors (MKIs) are used for the treatment of several cancers. By targeting multiple signaling pathways, MKIs have become cornerstones of the oncologic treatment. Although their use leads to important results in terms of survival, treatment with MKIs can determine important side effects the clinician must be aware of. Among those, arterial hypertension, mucositis and skin lesions are universally reported, while data about metabolic alterations are scarce. In our review, we focused on glucose and lipid alterations in MKI-treated patients.

METHODS

We searched for articles, published between January 2012 and December 2022, evaluating the effects on lipid and glucose metabolism of four MKIs (Cabozantinib, Lenvatinib, Sorafenib, and Vandetanib) in adult patients with cancer. We focused on drugs approved for thyroid malignancies, since a worse metabolic control may potentially impact life expectancy, due to their better overall survival rate.

RESULTS

As for glucose metabolism, the majority of the studies reported elevation of glucose levels (prevalence: 1-17%) with different grades of severity, including death. As for cholesterol, 12 studies reported worsening or new-onset hypercholesterolemia (prevalence: 4-40%). Finally, 19 studies reported different grades of hypertriglyceridemia (prevalence: 1-86%), sometimes leading to life-threatening events.

CONCLUSIONS

Despite some inherent limitations, our analysis may cast light upon some of the MKIs metabolic disorders that can impact on patients' health, especially when long-term survival is expected. Future clinical trials should consider routine assessment of glucose and lipid levels, because underdetection and underreporting of alterations can lead to the overlooking of important adverse events.

Detection of Adverse Drug Reactions in COVID-19 Hospitalized Patients in Saudi Arabia: A Retrospective Study by ADR Prompt Indicators

Seeking an alternative approach for detecting adverse drug reactions (ADRs) in coronavirus patients (COVID-19) and enhancing drug safety, a retrospective study of six months was conducted utilizing an electronic medical record (EMR) database to detect ADRs in hospitalized patients for COVID-19, using "ADR prompt indicators" (APIs). Consequently, confirmed ADRs were subjected to multifaceted analyses, such as demographic attribution, relationship with specific drugs and implication for organs and systems of the body, incidence rate, type, severity, and preventability of ADR. The incidence rate of ADRs is 37%, the predisposition of organs and systems to ADR is observed remarkably in the hepatobiliary and gastrointestinal systems at 41.8% vs. 36.2%, p < 0.0001, and the classes of drugs implicated in the ADRs are lopinavir-ritonavir 16.3%, antibiotics 24.1%, and hydroxychloroquine12.8%. Furthermore, the duration of hospitalization and polypharmacy are significantly higher in patients with ADRs at 14.13 ± 7.87 versus 9.55 ± 7.90, p < 0.001, and 9.74 ± 5.51 versus 6.98 ± 4.36, p < 0.0001, respectively. Comorbidities are detected in 42.5% of patients and 75.2%, of patients with DM, and HTN, displaying significant ADRs, p-value < 0.05. This is a symbolic study providing a comprehensive acquaintance of the importance of APIs in detecting hospitalized ADRs, revealing increased detection rates and robust assertive values with insignificant costs, incorporating the hospital EMR database, and enhancing transparency and time effectiveness.

Hospital pharmacists' opinions on a risk prediction tool for medication-related harm in older people

AIM

Older adults are particularly affected by medication-related harm (MRH) during transitions of care. There are no clinical tools predicting those at highest risk of MRH post hospital discharge. The PRIME study (prospective study to develop a model to stratify the risk of MRH in hospitalized patients) developed and internally validated a risk-prediction tool (RPT) that provides a percentage score of MRH in adults over 65 in the 8 weeks following hospital discharge. This qualitative study aimed to explore the views of hospital pharmacists around enablers and barriers to clinical implementation of the PRIME-RPT.

METHODS

Ten hospital pharmacists: (band 6, n = 3; band 7, n = 2; band 8, n = 5) participated in semistructured interviews at the Royal Sussex County Hospital (Brighton, UK). The pharmacists were presented with five case-vignettes each with a calculated PRIME-RPT score to help guide discussion. Case-vignettes were designed to be representative of common clinical encounters. Data were thematically analysed using a "framework" approach.

RESULTS

Seven themes emerged in relation to the PRIME-RPT: (1) providing a medicine-prioritisation aide; (2) acting as a deprescribing alert; (3) facilitating a holistic review of patient medication management; (4) simplifying communication of MRH to patients and the multidisciplinary team; (5) streamlining community follow-up and integration of risk discussion into clinical practice; (6) identifying barriers for the RPTs integration in clinical practice; and (7) acknowledging its limitations.

CONCLUSION

Hospital pharmacists found the PRIME-RPT beneficial in identifying older patients at high risk of MRH following hospital discharge, facilitating prioritising interventions to those at highest risk while still acknowledging its limitations.

Adverse drug reactions and associated patient characteristics in older community-dwelling adults: a 6-year prospective cohort study

BACKGROUND

To date, research on adverse drug reactions (ADRs) has focused on secondary care, and there is a paucity of studies that have prospectively examined ADRs affecting older adults in general practice.

AIM

To examine the cumulative incidence and severity of ADRs and associated patient characteristics in a sample of community-dwelling older adults.

DESIGN AND SETTING

Prospective cohort study of older adults (aged ≥70 years, N = 592) recruited from 15 general practices in the Republic of Ireland.

METHOD

Manual review of the participant's general practice electronic medical record, linked to the national dispensed prescription medicine database, and a detailed, self-reported patient postal questionnaire. The primary outcomes were ADR occurrence and severity over a 6-year period (2010-2016). Unadjusted and adjusted logistic regression models examined potential associations between patient characteristics and ADR occurrence.

RESULTS

A total of 211 ADRs were recorded for 159 participants, resulting in a cumulative incidence of 26.9% over 6 years. The majority of ADRs detected were mild (89.1%), with the remainder classified as moderate (10.9%). Eight moderate ADRs, representing 34.8% of moderate ADRs and 3.8% of all ADRs, required an emergency hospital admission. ADRs were independently associated with female sex (adjusted odds ratio [OR] 1.83, 95% confidence interval [CI] = 1.17 to 2.85; P = 0.008), polypharmacy (5-9 drug classes) (adjusted OR 1.81, 95% CI = 1.17 to 2.82; P = 0.008), and major polypharmacy (≥10 drug classes) (adjusted OR = 3.33, 95% CI = 1.62 to 6.85; P = 0.001).

CONCLUSION

This prospective cohort study of ADRs in general practice shows that over one-quarter of older adults experienced an ADR over a 6-year period. Polypharmacy is independently associated with ADR risk in general practice and older adults on ≥10 drug classes should be prioritised for regular medication review.

Comparing risk prediction models aimed at predicting hospitalizations for adverse drug events in community dwelling older adults: a protocol paper

Background

The objective of this paper is to describe the creation, validation, and comparison of two risk prediction modeling approaches for community-dwelling older adults to identify individuals at highest risk for adverse drug event-related hospitalizations. One approach will use traditional statistical methods, the second will use a machine learning approach.

Methods

We will construct medication, clinical, health care utilization, and other variables known to be associated with adverse drug event-related hospitalizations. To create the cohort, we will include older adults (≥ 65 years of age) empaneled to a primary care physician within the Cedars-Sinai Health System primary care clinics with polypharmacy (≥ 5 medications) or at least 1 medication commonly implicated in ADEs (certain oral hypoglycemics, anti-coagulants, anti-platelets, and insulins). We will use a Fine-Gray Cox proportional hazards model for one risk modeling approach and DataRobot, a data science and analytics platform, to run and compare several widely used supervised machine learning algorithms, including Random Forest, Support Vector Machine, Extreme Gradient Boosting (XGBoost), Decision Tree, Naïve Bayes, and K-Nearest Neighbors. We will use a variety of metrics to compare model performance and to assess the risk of algorithmic bias.

Discussion

In conclusion, we hope to develop a pragmatic model that can be implemented in the primary care setting to risk stratify older adults to further optimize medication management.

Adverse drug reactions in an ageing PopulaTion (ADAPT) study: Prevalence and risk factors associated with adverse drug reaction-related hospital admissions in older patients

Background: Older people experience greater morbidity with a corresponding increase in medication use resulting in a potentially higher risk of adverse drug reactions (ADRs). Objectives: The aim of this study was to; 1) determine the prevalence and characteristics of ADR-related hospital admissions among older patients (≥65 years) in Ireland; and 2) identify the risk factors associated with ADR-related hospital admissions. Methods: A cross-sectional study of ADR prevalence in patients aged ≥65 years admitted acutely to hospital in Ireland over a 8 month period (November 2016- June 2017). A multifaceted review of each hospital admission was undertaken to assess the likelihood of an ADR being a reason for admission (cause of admission or contributing to admission) in the context of the patient's medication, clinical conditions, comorbidities and investigations. A number of decision aids were applied by two independent reviewers to assess ADR causality, avoidability and severity. A random sample of patients, determined not to have a suspected ADR on screening, were assigned to a non-ADR control group. Multivariable logistic regression was used to assess the association between potential risk factors for ADR-related admissions compared with non-ADR-related admissions. Results: In total, 3,760 hospital admission episodes (in 3,091 patients) were screened and 377 admissions were considered ADR-related (10.0%, 95% CI 9.1%, 11.0%). 219 (58.1%) ADR-related admissions were caused by an ADR, while ADRs contributed to 158 (41.9%) admissions. 268 (71.1%) of all ADR-related admissions were deemed definitely or possibly preventable/avoidable. 350 (92.8%) ADRs were classified as being of moderate severity, with 27 (7.2%) classified as severe. Antithrombotic agents, mainly aspirin and warfarin, were the drugs most frequently associated with ADR-related admissions (gastrointestinal and vascular haemorrhagic disorders). In multivariable analysis, immobility, frailty, having delirium or ulcer disease and taking anticoagulant and antiplatelet medication on admission were significantly associated with an ADR-related hospital admission. Conclusion: One in ten hospital admissions, among those aged 65 + years, were considered ADR-related, with approximately 70% potentially avoidable. Reliable and validated ADR detection and prediction tools are needed to develop prevention strategies.

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).

Systematic Review of Risk Factors Assessed in Predictive Scoring Tools for Drug-Related Problems in Inpatients

Drug-related problems (DRP, defined as adverse drug events/reactions and medication errors) are a common threat for patient safety. With the aim to aid improved allocation of specialist resources and to improve detection and prevention of DRP, numerous predictive scoring tools have been proposed. The external validation and evidence for the transferability of these tools still faces limitations. However, the proposed scoring tools include partly overlapping sets of similar factors, which may allow a new approach to estimate the external usability and validity of individual risk factors. Therefore, we conducted this systematic review and analysis. We identified 14 key studies that assessed 844 candidate risk factors for inclusion into predictive scoring tools. After consolidation to account for overlapping terminology and variable definitions, we assessed each risk factor in the number of studies it was assessed, and, if it was found to be a significant predictor of DRP, whether it was included in a final scoring tool. The latter included intake of ≥ 8 drugs, drugs of the Anatomical Therapeutic Chemical (ATC) class N, ≥1 comorbidity, an estimated glomerular filtration rate (eGFR) <30 mL/min and age ≥60 years. The methodological approach and the individual risk factors presented in this review may provide a new starting point for improved risk assessment.

Detection tools for prediction and identification of adverse drug reactions in older patients: a systematic review and meta-analysis

Tools to accurately predict and detect adverse drug reactions (ADR) in elderly patients have not been developed. We aimed to identify and evaluate reports on tools that predict and detect ADR in elderly patients (≥ 60 years). In this review, we followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Databases were searched until January 2022 using key terms "elderly," "adverse drug reaction," and "detection instruments." Eighteen studies met the inclusion criteria, and they examined assorted interventions: STOPP/START version 1/2 (n = 10), Beers Criteria 2012 or 2015 (n = 4), Systematic Tool to Reduce Inappropriate Prescribing (STRIP) (n = 2), Tool to Reduce Inappropriate Medications (TRIM) (n = 1), Medication Risk Score (MERIS) (n = 1), Computerized alert systems (n = 1), and Norwegian General Practice-Nursing Home criteria (n = 1). The interventions affected the number of potential prescription omissions (OR, 0.50 [0.37-0.69]; p < 0.0001; four studies). No apparent reduction in the number of drug interactions within 2 months (OR, 0.84 [0.70-1.02]; p = 0.08; two studies) and mortality (OR, 0.92 [0.76-1.12]; p = 0.41; three studies) was observed. In conclusion, there is no definitive and validated assessment tool for detecting and predicting ADR in elderly patients. Thus, more research on refining existing tools or developing new ones is warranted.

Development and Validation of ‘Prediction of Adverse Drug Reactions in Older Inpatients (PADROI)’ Risk Assessment Tool

Background

Adverse drug reactions (ADR) detection and prediction methods in hospitalized older adults remain imprecise. The identification of the risk factors for ADRs in this group of patients is crucial to develop plausible prediction models.

Objective

This study aimed at developing and validating a “Prediction of ADR in Older Inpatients (PADROI)” risk assessment tool in hospitalized older adults.

Methods and Materials

We had previously conducted a derivational study that aimed to determine the risk factors of ADRs in hospitalized older adults. We developed the PADROI model as a potential ADR risk assessment tool incorporating 8 predictors each given a score by rounding off the respective adjusted odds ratios (AORs) to the nearest whole number. Subsequently, we conducted another prospective cohort among adults aged 60 years and older admitted to Gynecology and Obstetrics, Medical, Oncology, Surgery, and Psychiatry wards at Mbarara Regional Referral Hospital (MRRH) from July 5 to September 17, 2021.

Results

A total of 124 participants, 70 females and 54 males aged 60–95 years, were included in this validation cohort; 62 of them experienced 90 ADRs. When applied to the derivational cohort, the area under receiver operating characteristic curve (AUROC) for the PADROI model was shown to be 0.896 (0.869–0.923; at 95% CI). In the validation study, AUROC of PADROI was 0.917 (0.864–0.971 at 95% CI; p < 0.001). Overall, PADROI correctly predicted 91.7% of those who experienced an ADR.

Conclusion

Using the adjusted odds ratios from our derivational cohort, we developed an ADR prediction tool (PADROI) that achieved an excellent AUROC (0.917), high sensitivity (87.1%) and specificity (90.3%). The current model demonstrated a high potential for clinical applicability which can be strengthened if similar results are reproduced in larger and multi-centered studies.

Self-Efficacy, Social Activity, and Spirituality in the Care of Elderly Patients with Polypharmacy in Germany-A Multicentric Cross-Sectional Study within the HoPES3 Trial

About one third of Europe’s elderly population takes ≥5 drugs. Polypharmacy increases their risk of adverse drug reactions. To ensure drug safety, innovative approaches are needed. The aim of this cross-sectional study was to explore the relationship between psychosocial factors and medication-related beliefs and behaviors. Medication lists of 297 patients were recorded according to the ATC classification. Correlations between the dependent variables, Medication Adherence (MARS) and Beliefs about Medicines (BMQ), and independent variables, General Self-Efficacy (GSE), self-efficacy for managing chronic diseases (SES6G), spiritual needs (SpNQ), patient activity (PAM), loneliness (DJG), and social networks (LSNS), were measured. Patients with higher self-efficacy (OR: 1.113; 95% CI [1.056–1.174]; p < 0.001) or self-confidence in managing their chronic condition (OR: 1.188; 95% CI [1.048–1.346]; p < 0.007) also showed higher adherence. Lonely patients (OR: 0.420; 95% CI [0.267–0.660]; p < 0.001) and those with a need for inner peace (OR: 0.613; 95% CI [0.444–0.846], p = 0.003) were more likely nonadherent. Stronger positive beliefs about medications’ usefulness weakly correlated with higher scores on the SES6G (ρ = 0.178, p = 0.003) and GSES scale (ρ = 0.121, p = 0.042), patient activity (ρ = 0.155, p = 0.010) and functioning social networks scale (ρ = 0.159, p = 0.008). A weak positive correlation was found between loneliness and the belief that drugs were harmful (ρ = 0.194, p = 0.001). Furthermore, interesting correlations were detected regarding the number of medications and overuse beliefs. Psychosocial factors, such as self-efficacy, loneliness, and spiritual needs and medication-related beliefs and behaviors seem to interrelate. Addressing these factors may improve medication management and drug safety.

Emerging approaches to polypharmacy among older adults

Polypharmacy is a major health issue for older adults. Entangled with several geriatric syndromes, including frailty, falls and cognitive decline, research focused on polypharmacy has been challenged by heterogeneity in its definition, confounding by comorbidities and limited prospective data. In this Review, we discuss varying definitions for polypharmacy and highlight the need for a uniform definition for future studies. We critically appraise strategies for reducing medication prescriptions and implementing deprescribing as a mechanism to reduce the potential harmful effects of polypharmacy. As we look to the future, we assess the role of novel analytics and high-throughput technology, including multiomics profiling, to advance research in polypharmacy and the development of new strategies for risk stratification in the age of precision medicine.

Prediction of Major Depressive Disorder Following Beta-Blocker Therapy in Patients with Cardiovascular Diseases

Incident depression has been reported to be associated with poor prognosis in patients with cardiovascular disease (CVD), which might be associated with beta-blocker therapy. Because early detection and intervention can alleviate the severity of depression, we aimed to develop a machine learning (ML) model predicting the onset of major depressive disorder (MDD). A model based on L1 regularized logistic regression was trained against the South Korean nationwide administrative claims database to identify risk factors for the incident MDD after beta-blocker therapy in patients with CVD. We identified 50,397 patients initiating beta-blockers for CVD, with 774 patients developing MDD within 365 days after initiating beta-blocker therapy. An area under the receiver operating characteristic curve (AUC) of 0.74 was achieved. A history of non-selective beta-blockers and factors related to anxiety disorder, sleeping problems, and other chronic diseases were the most strong predictors. AUCs of 0.62–0.71 were achieved in the external validation conducted on six independent electronic health records and claims databases in the USA and South Korea. In conclusion, an ML model that identifies patients at high-risk for incident MDD was developed. Application of ML to identify susceptible patients for adverse events of treatment may serve as an important approach for personalized medicine.

Development and internal validation of prognostic models to predict negative health outcomes in older patients with multimorbidity and polypharmacy in general practice

BACKGROUND

Polypharmacy interventions are resource-intensive and should be targeted to those at risk of negative health outcomes. Our aim was to develop and internally validate prognostic models to predict health-related quality of life (HRQoL) and the combined outcome of falls, hospitalisation, institutionalisation and nursing care needs, in older patients with multimorbidity and polypharmacy in general practices.

METHODS

Design: two independent data sets, one comprising health insurance claims data (n=592 456), the other data from the PRIoritising MUltimedication in Multimorbidity (PRIMUM) cluster randomised controlled trial (n=502). Population: ≥60 years, ≥5 drugs, ≥3 chronic diseases, excluding dementia. Outcomes: combined outcome of falls, hospitalisation, institutionalisation and nursing care needs (after 6, 9 and 24 months) (claims data); and HRQoL (after 6 and 9 months) (trial data). Predictor variables in both data sets: age, sex, morbidity-related variables (disease count), medication-related variables (European Union-Potentially Inappropriate Medication list (EU-PIM list)) and health service utilisation. Predictor variables exclusively in trial data: additional socio-demographics, morbidity-related variables (Cumulative Illness Rating Scale, depression), Medication Appropriateness Index (MAI), lifestyle, functional status and HRQoL (EuroQol EQ-5D-3L). Analysis: mixed regression models, combined with stepwise variable selection, 10-fold cross validation and sensitivity analyses.

RESULTS

Most important predictors of EQ-5D-3L at 6 months in best model (Nagelkerke's R² 0.507) were depressive symptoms (-2.73 (95% CI: -3.56 to -1.91)), MAI (-0.39 (95% CI: -0.7 to -0.08)), baseline EQ-5D-3L (0.55 (95% CI: 0.47 to 0.64)). Models based on claims data and those predicting long-term outcomes based on both data sets produced low R² values. In claims data-based model with highest explanatory power (R²=0.16), previous falls/fall-related injuries, previous hospitalisations, age, number of involved physicians and disease count were most important predictor variables.

CONCLUSIONS

Best trial data-based model predicted HRQoL after 6 months well and included parameters of well-being not found in claims. Performance of claims data-based models and models predicting long-term outcomes was relatively weak. For generalisability, future studies should refit models by considering parameters representing well-being and functional status.

The Double Burden of the COVID-19 Pandemic and Polypharmacy on Geriatric Population - Public Health Implications

COVID-19 pandemic is inducing acute respiratory distress syndrome, multi-organ failure, and eventual death. Respiratory failure is the leading cause of mortality in the elderly population with pre-existing medical conditions. This group is particularly vulnerable to infections due to a declined immune system, comorbidities, geriatric syndrome, and potentially inappropriate polypharmacy. These conditions make the elderly population more susceptible to the harmful effects of medications and the deleterious consequences of infections, including MERS-CoV, SARS-CoV, and SARS-CoV-2. Chronic diseases among elderlies, including respiratory diseases, hypertension, diabetes, and coronary heart diseases, present a significant challenge for healthcare professionals. To comply with the clinical guidelines, the practitioner may prescribe a complex medication regimen that adds up to the burden of pre-existing treatment, potentially inducing adverse drug reactions and leading to harmful side-effects. Consequently, the geriatric population is at increased risk of falls, frailty, and dependence that enhances their susceptibility to morbidity and mortality due to SARS-CoV-2 respiratory syndrome, particularly interstitial pneumonia. The major challenge resides in the detection of infection that may present as atypical manifestations in this age group. Healthy aging can be possible with adequate preventive measures and appropriate medication regimen and follow-up. Adherence to the guidelines and recommendations of WHO, CDC, and other national/regional/international agencies can reduce the risks of SARS-CoV-2 infection. Better training programs are needed to enhance the skill of health care professionals and patient’s caregivers. This review explains the public health implications associated with polypharmacy on the geriatric population with pre-existing co-morbidities during the COVID-19 pandemic.

Screening Tools Used by Clinical Pharmacists to Identify Elderly Patients at Risk of Drug-Related Problems on Hospital Admission: A Systematic Review

None of the models met the four key stages required to create a quality risk prediction model. Further research is needed to either refine the tools developed to date or develop new ones that have good performance and have been externally validated before considering the potential impact and implementation of such tools.

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

OBJECTIVES

To 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, PARTICIPANTS

Multicentre, prospective cohort study recruiting older adults (≥65 years) discharged from five UK teaching hospitals between 2013 and 2015.

PRIMARY OUTCOME MEASURE

Participants 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.

RESULTS

1116 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.

CONCLUSIONS

The 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.

Medication-related harm: a geriatric syndrome

The WHO Global Patient Safety Challenge: Medication Without Harm recognises medication-related harm (MRH) as a global public health issue. Increased life-expectancy coupled with multimorbidity and polypharmacy leads to an increased incidence of MRH, especially in older adults: at a cost of approximately £400 million to the National Health Service (NHS) in England. Harm from medicines has long been recognised by geriatricians, and strategies have been developed to mitigate harm. In general, these have focused on the challenges of polypharmacy and appropriateness of medicines, but impact on the quality of life, clinical and economic outcomes has been variable and often disappointing. The problem of MRH in older adults will continue to grow unless a new approach is adopted. Emerging evidence suggests that we need to take a broader approach as described in our conceptual model, where well-recognised physiological changes are incorporated, as well as other rarely considered psychosocial issues that influences MRH. Parallels may be drawn between this approach and the management of geriatric syndromes. We propose there must be a greater emphasis on MRH, and it, of itself, should be considered as a geriatric syndrome, to bring the spotlight onto the problem and to send a clear signal from geriatric experts that this is an important issue that needs to be addressed using a co-ordinated and tailored approach across health and social care boundaries. This requires a more proactive approach to monitor and review the medicines of older adults in response to their changing need.

Do the 2015 Beers Criteria predict medication-related harm in older adults? Analysis from a multicentre prospective study in the United Kingdom

PURPOSE

To investigate whether inappropriate prescribing, defined by the Beers Criteria, is associated with medication-related harm (MRH), hospital admission, and mortality in older adults in England.

METHODS

A multicentre, prospective cohort study recruited 1280 patients (median age 82 years) at hospital discharge. Patients were followed-up in the community by pharmacists for 8 weeks to identify MRH (harm from adverse drug reactions, non-adherence, and medication errors) and hospital admissions. One-year mortality was determined using hospital records. Potentially inappropriate medications (PIMs) were determined using the 2015 version of the Beers criteria. Logistic regression was used to investigate the relationship between patients prescribed PIMs and adverse outcomes.

RESULTS

Two hundred and seventy-six patients (22%) were prescribed one or more PIMs at hospital discharge. The main PIM classes prescribed at hospital discharge were benzodiazepines and related drugs (30%) and antidepressants (27%). 1116 out of 1280 patients completed follow-up and 413 (37%) experienced MRH. In 51 cases (12%), MRH was attributable to a PIM. There was no significant relationship between patients prescribed PIMs and overall MRH, hospital readmission or all-cause one-year mortality. Multiple PIMs at discharge was independently associated with an increased risk of ADR (OR 2.32, 95% CI 1.03-5.23).

CONCLUSION

The prescribing of PIMs is common at hospital discharge of older adults in England. The 2015 Beers criteria have a limited clinical value to predict adverse outcomes following hospital discharge in this setting.

Predictors of adverse drug reactions in geriatric patients: An exploratory study among cancer patients

Objectives:

The objective of this study was to study the predictors of adverse drug reactions (ADRs) among geriatric patients in the Department of Medical Oncology.

Methods:

A hospital-based prospective observational study was carried out among 153 inpatients in the Department of Medical Oncology for 6 months. Patients above 60 years of age with a confirmed history of malignancy were included in the study. The potential risk factors for ADR were defined in relation to the patient and chemotherapeutic regimen and relationship between them was assessed by univariate and multivariate logistic regression analysis.

Results:

Among 153 patients, 94 (64.43%) experienced ADRs. The mean ADR per patient was 0.88 ± 1.2. The common ADRs found were alopecia (30.18%) and diarrhea (28.68%). Risk estimates revealed that there was a significant association between smokers (odds ratio [OR] = 10.326; 95% confidence interval [CI] 2.345–45.47, P = 0.001), alcoholics (OR = 10.897; 95% CI 2.479–47.902, P = 0.001), increasing age (OR = 2.22; 95% CI 1.698–2.909, P = 0.001), overweight (OR = 16.68; 95% CI 2.179–127.741, P = 0.001), and male participants (OR = 0.143; 95% CI 0.05–0.390 P = 0.001) with the development of ADRs. The risk of carboplatin (OR = 13.359; 95% CI 3.056–58.406 P = 0.001) and 5-fluorouracil (OR = 1.938 95% CI 1.266–2.935 P = 0.001) use and occurrence of ADRs were also found to be high.

Conclusion:

The study findings showed that smoking, alcohol consumption, age more than 70 years, and overweight had a high risk for developing ADRs in geriatric patients who underwent chemotherapy. The independent risk factors identified should be targeted for preventive measures to improve anticancer agent prescription and reduce the risk of ADRs.

Detection and prevention of adverse drug reactions in multi-morbid older patients

Adverse drug reactions (ADRs) are a recognised unintentional form of iatrogenic harm, which commonly occur in older adults who have high levels of multi-morbidity and associated polypharmacy. Previous studies estimate that at least one in 10 hospitalised older patients will experience an ADR. While recent research indicates that this could be as high as 39% in hospitalised multi-morbid, older adults, up to two-thirds of these ADRs can be considered preventable and therefore potentially avoidable. In addition to increasing patient morbidity and contributing to avoidable mortality, there is an associated cost implication with ADR occurrence. This commentary summarises current mainstream research in terms of ADR detection, prediction and prevention in multi-morbid older patients. At present, the biggest barrier to understanding and comparing ADRs in the literature is the large heterogeneity that exists in the population and study methods. Furthermore, there is the lack of standardised universally accepted methodology for ADR prediction, detection, causality assessment and subsequent prevention in older people. Standard available methods of ADR prediction applied to a heterogeneous multi-morbid population are generally unsatisfactory. Without an instrument that consistently and reliably predicts ADR risk in a reproducible manner, ADR prevention in multi-morbid older patients is challenging. Further attention should be focused on the culprit drugs that commonly lead to major ADRs in older multi-morbid hospitalised patients with polypharmacy. Risk associated with particular drug classes may possibly predict ADR occurrence better than patient characteristics alone. Current research is examining this drug class focus for ADR prevention in multi-morbid older people.

Prediction of Drug-Related Risks Using Clinical Context Information in Longitudinal Claims Data

OBJECTIVES

To develop and internally validate prediction models for medication-related risks arising from overuse, misuse, and underuse that utilize clinical context information and are suitable for routine risk assessment in claims data (i.e., medication-based models predicting the risk for hospital admission apparent in routine claims data or MEDI-RADAR).

METHODS

Based on nationwide claims from health-insured persons in Germany between 2010 and 2012, we drew a random sample of people aged ≥65 years (N = 22,500 randomly allocated to training set, N = 7500 to validation set). Individual duration of drug supply was estimated from prescription patterns to yield time-varying drug exposure windows. Together with concurrent medical conditions (ICD-10 diagnoses), exposure to the STOPP/START (screening tool of older persons' potentially inappropriate prescriptions/screening tool to alert doctors to the right treatment) criteria was derived. These were tested as time-dependent covariates together with time-constant covariates (patient demographics, baseline comorbidities) in regularized Cox regression models.

RESULTS

STOPP/START variables were iteratively refined and selected by regularization to include 2 up to 11 START variables and 8 up to 31 STOPP variables in parsimonious and liberal selections in the prediction modeling. The models discriminated well between patients with and without all-cause hospitalizations, potentially drug-induced hospitalizations, and mortality (parsimonious model c-indices with 95% confidence intervals: 0.63 [0.62-0.64], 0.67 [0.65-0.68], and 0.78 [0.76-0.80]).

CONCLUSIONS

The STOPP/START criteria proved to efficiently predict medication-related risk in models possessing good performance. Timely detection of such risks by routine monitoring in claims data can support tailored interventions targeting these modifiable risk factors. Their impact on older peoples' medication safety and effectiveness can now be explored in future implementation studies.

Have you SCAND MMe Please? A framework to prevent harm during acute hospitalisation of older persons: A retrospective audit

AIMS AND OBJECTIVES

To test the mnemonic Have you SCAND MMe Please? as a framework to audit nursing care to prevent harms common to older inpatients.

BACKGROUND

It is not known if acute hospital care comprehensively addresses eight interrelated factors that contribute to preventable harms common in older hospitalised patients.

DESIGN

Retrospective audit of medical records.

METHODS

A random selection of 400 medical records of inpatients over 65 years of age with an unplanned admission of longer than 72 hr in acute medical wards at four hospitals in Victoria, Australia, during 2011-12, was examined for frequency of documented evidence of assessments, interventions or new problems related to eight factors contributing to common preventable harms during hospitalisation.

RESULTS

Assessments of skin integrity (94%-97%), mobility (95%-98%) and pain (93%-97%) were most often documented. Gaps in assessment of continence (4%-31%), nutrition (9%-49%), cognition (delirium, depression and dementia) (10%-24%) were most common. No patient record had evidence of all eight factors being assessed. Almost 80% of records had interventions documented for one or more factors that contribute to preventable harms. In almost 20% of patient records, a new preventable harm was documented during hospitalisation.

CONCLUSIONS

The mnemonic Have you SCAND MMe Please? brings together eight factors known to contribute to preventable harms common in older hospitalised patients. This framework was useful to identify gaps in assessment and interventions for factors that contribute to preventable harms during acute hospital care. Future research should test if the mnemonic can assist nurses with comprehensive harm prevention during acute hospitalisation.

RELEVANCE TO CLINICAL PRACTICE

The mnemonic Have you SCAND MMe Please? represents eight factors that contribute to preventable harms common in older hospitalised patients. This framework provides a model for harm prevention to assist nurses to implement comprehensive harm prevention to improve quality of care and safety for older hospitalised patients.

Prediction of clinically relevant adverse drug events in surgical patients

BACKGROUND

Risk stratification of hospital patients for adverse drug events would enable targeting patients who may benefit from interventions aimed at reducing drug-related morbidity. It would support clinicians and hospital pharmacists in selecting patients to deliver a more efficient health care service. This study aimed to develop a prediction model that helps to identify patients on the day of hospital admission who are at increased risk of developing a clinically relevant, preventable adverse drug event during their stay on a surgical ward.

METHODS

Data of the pre-intervention measurement period of the P-REVIEW study were used. This study was designed to assess the impact of a multifaceted educational intervention on clinically relevant, preventable adverse drug events in surgical patients. Thirty-nine variables were evaluated in a univariate and multivariate logistic regression analysis, respectively. Model performance was expressed in the Area Under the Receiver Operating Characteristics. Bootstrapping was used for model validation.

RESULTS

6780 admissions of patients at surgical wards were included during the pre-intervention period of the PREVIEW trial. 102 patients experienced a clinically relevant, adverse drug event during their hospital stay. The prediction model comprised five variables: age, number of biochemical tests ordered, heparin/LMWH in therapeutic dose, use of opioids, and use of cardiovascular drugs. The AUROC was 0.86 (95% CI 0.83-0.88). The model had a sensitivity of 80.4% and a specificity of 73.4%. The positive and negative predictive values were 4.5% and 99.6%, respectively. Bootstrapping generated parameters in the same boundaries.

CONCLUSIONS

The combined use of a limited set of easily ascertainable patient characteristics can help physicians and pharmacists to identify, at the time of admission, surgical patients who are at increased risk of developing ADEs during their hospital stay. This may serve as a basis for taking extra precautions to ensure medication safety in those patients.

Can doctors identify older patients at risk of medication harm following hospital discharge? A multicentre prospective study in the UK

AIMS

Medication-related harm (MRH) is common in older adults following hospital discharge. In resource-limited health systems, interventions to reduce this risk can be targeted at high-risk patients. This study aims to determine whether (1) doctors can predict which older patients will experience MRH requiring healthcare following hospital discharge, (2) clinical experience and confidence in prediction influence the accuracy of the prediction.

METHODS

This was a multicentre observational prospective study involving five teaching hospitals in England between September 2013 and November 2015. Doctors discharging patients (aged ≥65 years) from medical wards predicted the likelihood of their patient experiencing MRH requiring healthcare (hospital readmission or community healthcare) in the initial 8-week period post-discharge. Patients were followed up by senior pharmacists to determine MRH occurrence.

RESULTS

Data of 1066 patients (83%) with completed predictions and follow-up, out of 1280 recruited patients, were analysed. Patients had a median age of 82 years (65-103 years), and 58% were female. Most predictions (85%) were made by junior doctors with less than 5 years' clinical experience. There was no relationship between doctors' predictions and patient MRH (OR 1.10, 95% CI 0.82-1.46, P = 0.53), irrespective of years of clinical experience. Doctors' predictions were more likely to be accurate when they reported higher confidence in their prediction, especially in predicting MRH-associated hospital readmissions (OR 1.58, 95% CI 1.42-1.76, P < 0.001).

CONCLUSIONS

Clinical judgement of doctors is not a reliable tool to predict MRH in older adults post-discharge.

Incidence and cost of medication harm in older adults following hospital discharge: a multicentre prospective study in the UK

Aims

Polypharmacy 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.

Methods

An 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.

Results

Overall, 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.

Conclusions

MRH is common in older adults following hospital discharge, and results in substantial use of healthcare resources.

Systematic review of predictive risk models for adverse drug events in hospitalized patients

AIM

An emerging approach to reducing hospital adverse drug events is the use of predictive risk scores. The aim of this systematic review was to critically appraise models developed for predicting adverse drug event risk in inpatients.

METHODS

Embase, PubMed, CINAHL and Scopus databases were used to identify studies of predictive risk models for hospitalized adult inpatients. Studies had to have used multivariable logistic regression for model development, resulting in a score or rule with two or more variables, to predict the likelihood of inpatient adverse drug events. The Checklist for the critical Appraisal and data extraction for systematic Reviews of prediction Modelling Studies (CHARMS) was used to critically appraise eligible studies.

RESULTS

Eleven studies met the inclusion criteria and were included in the review. Ten described the development of a new model, whilst one study revalidated and updated an existing score. Studies used different definitions for outcome but were synonymous with or closely related to adverse drug events. Four studies undertook external validation, five internally validated and two studies did not validate their model. No studies evaluated impact of risk scores on patient outcomes.

CONCLUSION

Adverse drug event risk prediction is a complex endeavour but could help to improve patient safety and hospital resource management. Studies in this review had some limitations in their methods for model development, reporting and validation. Two studies, the BADRI and Trivalle's risk scores, used better model development and validation methods and reported reasonable performance, and so could be considered for further research.

Improving Pharmacists' Targeting of Patients for Medication Review and Deprescription

Background: In an acute hospital setting, a multi-disciplinary approach to medication review can improve prescribing and medicine selection in patients with frailty. There is a need for a clear understanding of the roles and responsibilities of pharmacists to ensure that interventions have the greatest impact on patient care. Aim: To use a consensus building process to produce guidance for pharmacists to support the identification of patients at risk from their medicines, and to articulate expected actions and escalation processes. Methods: A literature search was conducted and evidence used to establish a set of ten scenarios often encountered in hospitalised patients, with six or more possible actions. Four consultant physicians and four senior pharmacists ranked their levels of agreement with the listed actions. The process was redrafted and repeated until consensus was reached and interventions were defined. Outcome: Generalised guidance for reviewing older adults' medicines was developed, alongside escalation processes that should be followed in a specific set of clinical situations. The panel agreed that both pharmacists and physicians have an active role to play in medication review, and face-to-face communication is always preferable to facilitate informed decision making. Only prescribers should deprescribe, however pharmacists who are not also trained as prescribers may temporarily "hold" medications in the best interests of the patient with appropriate documentation and a follow up discussion with the prescribing team. The consensus was that a combination of age, problematic polypharmacy, and the presence of medication-related problems, were the most important factors in the identification of patients who would benefit most from a comprehensive medication review. Conclusions: Guidance on the identification of patients on inappropriate medicines, and subsequent pharmacist-led intervention to prompt and promote deprescribing, has been developed for implementation in an acute hospital.

Validation of a score to identify inpatients at risk of a drug-related problem during a 4-year period

Objective

Drug-related problems (DRP) produce high morbidity and mortality. It is therefore essential to identify patients at higher risk of these events. This study aimed to validate a DRP risk score in a large number of inpatients.

Material and methods

Validation of a previously designed score to identify inpatients at risk of experiencing at least one DRP in a tertiary university hospital from 2010 to 2013. DRP were detected by a pharmacy warning system integrated in the electronic medical record. The score included the following variables associated with a higher risk of DRP: prescription of a higher number of drugs, greater comorbidity, advanced age, specific ATC groups and certain major diagnostic categories.

Results

The study included a total of 52,987 admissions; of these, at least one DRP occurred in 14.9%. After validation of the score (period range, 2010–2013: 0.746–0.764), the area under the curve (AUC) was 0.751 (95% CI: 0.745–0.756).

Conclusions

This value is higher than those reported in other studies describing validation of risk scores. The score showed good capacity to identify those patients at higher risk of DRP in a much larger sample of inpatients than previously described in the literature. This tool allows optimization of drug therapy monitoring in admitted patients.

Predicting the Risk of Adverse Drug Reactions in Older Inpatients: External Validation of the GerontoNet ADR Risk Score Using the CRIME Cohort

BACKGROUND

Adverse drug reactions (ADRs) in older people are often preventable, indicating that screening and prevention programs aimed at reducing their rate are needed in this population.

OBJECTIVE

The aim of this study was to externally validate the GerontoNet ADR risk score and to assess its validity in specific subpopulations of older inpatients.

METHODS

Data from the prospective CRIteria to assess appropriate Medication use among Elderly complex patients (CRIME) cohort were used. Dose-dependent and predictable ADRs were classified as type A, probable or definite ADRs were defined according to the Naranjo algorithm, and diagnostic accuracy was tested using receiver operating characteristic (ROC) analyses. Sensitivity and specificity were calculated for a cut-off point of 4.

RESULTS

The mean age of the 1075 patients was 81.4 years (standard deviation 7.4) and the median number of drugs was 10 (range 7-13). At least one ADR was observed in 70 patients (6.5%); ADRs were classified as type A in 50 patients (4.7%) and defined as probable or definite in 41 patients (3.8%). Fair diagnostic accuracy to predict both type A and probable or definite ADRs was found in subpopulations aged <70 or ≥80 years with heart failure, diabetes, or a previous ADR. Good accuracy to predict type A ADRs was found in patients with a low body mass index (BMI; >18.5 kg/m²) and a Mini-Mental State Examination (MMSE) score of >24/30 points, as well as in patients with osteoarthritis. The cut-off point of 4 points yielded very good sensitivity but poor specificity results in these subpopulations.

CONCLUSION

This study suggests that the GerontoNet ADR risk score might represent a pragmatic approach to identifying specific subpopulations of older inpatients at increased risk of an ADR with a fair to good diagnostic accuracy.

Intra-Target Microdosing - A Novel Drug Development Approach: Proof of Concept, Safety, and Feasibility Study in Humans

Intra‐Target Microdosing (ITM) is a novel drug development approach aimed at increasing the efficiency of first‐in‐human (FIH) testing of new molecular entities (NMEs). ITM combines intra‐target drug delivery and “microdosing,” the subpharmacological systemic exposure. We hypothesized that when the target tissue is small (about 1/100th of total body mass), ITM can lead to target therapeutic‐level exposure with minimal (microdose) systemic exposure. Each of five healthy male volunteers received insulin microdose into the radial artery or full therapeutic dose intravenously in separate visits. Insulin and glucose levels were similar between systemic administration and ITM administration in the ipsilateral hand, and glucose levels demonstrated a reduction in the ipsilateral hand but not in the contralateral hand. Positron emission tomography (PET) imaging of ¹⁸F‐fluorodeoxyglucose (FDG) uptake demonstrated differences between the ipsilateral and contralateral arms. The procedures were safe and well‐tolerated. Results are consistent with ITM proof‐of‐concept (POC) and demonstrate the ethical, regulatory, and logistical feasibility of the approach.

Current and future perspectives on the management of polypharmacy

BACKGROUND

Because of ageing populations, the growth in the number of people with multi-morbidity and greater compliance with disease-specific guidelines, polypharmacy is becoming increasingly common. Although the correct drug treatment in patients with complex medical problems can improve clinical outcomes, quality of life and life expectancy, polypharmacy is also associated with an increased risk of adverse drug events, some severe enough to result in hospital admission and even death. Hence, having systems in place to ensure that medications are started only when there is a suitable indication, ensuring patients are fully aware of the benefits and complications that may arise from their treatment, and reviewing patients regularly to ensure their medication regime remains appropriate, are essential.

DISCUSSION

The development and rapid uptake of electronic patient records - particularly in primary care settings where the majority of prescribing takes place - makes monitoring of patients more straightforward than in the past; and allows identification of sub-groups of patients at particularly high risk of adverse drug events and complications. It also facilitates 'deprescribing' the process by which medications are reviewed and stopped if not clinically beneficial. In recent years, we have also seen the development of smartphone 'apps' to improve communication between patients and healthcare professionals, improve people's understanding of their conditions and their treatment, and maintain a record of changes made to patient's medication. In the longer term, developments such as the introduction of artificial intelligence and clinical decision support systems also have the potential to improve prescribing and minimise the risks from polypharmacy. Finally, there is considerable scope to improve the quality of prescribing and reduce risks from poly-pharmacy using non-medical groups such as pharmacists, specialist nurses and physician assistants. Polypharmacy has increased in recent decades and will continue to increase as populations age and the number of people with multiple long-term conditions increases. As with all areas of medicine, the evidence-base in this area continues to evolve. Further trials on the impact on patients with polypharmacy of new interventions such as technology-based solutions and the use of different professional groups are needed to improve the evidence-base in this area.

Validation of the assessment of risk tool: patient prioritisation technology for clinical pharmacist interventions

Background

Adverse drug events (ADEs) pose a heavy burden on health systems worldwide. The assessment of risk tool (ART) was developed to help prioritise hospitalised patients for interventions such as medication reconciliation (MR) and review, and to reduce potential ADEs from unintentional medication discrepancies and prescribing errors.

Aim

To validate ART, and to determine which of the selected 25 flags were significantly associated with risk of unintentional medication discrepancies and prescribing errors.

Method

This was a prospective observational study of 247 admissions to two medical teams in a New Zealand hospital. Study pharmacists undertook MR and review for all eligible admissions over 5 months. A Kruskal-Wallis test was used to determine differences in numbers of unintentional medication discrepancies and prescribing errors, followed by generalised linear modelling, to find the estimated ratio of the mean number of unintentional medication discrepancies between the three ART groups. In part 2 of the study, using multivariable logistic regression, combinations of flags significantly associated with risk were identified.

Results

Significant differences in the number of unintentional medication discrepancieswere found between the ART risk groups (p<0.0001, Kruskal-Wallis test). Patients in the high-risk group had a significantly greater number of unintentional medication discrepancies than those in the medium- and low-risk groups. There were no significant differences in prescribing errors between the ART risk groups (p=0.08, Kruskal-Wallis test). Flags significantly associated with risk, included 'more than eight admission medications', OR=3.7 (95% CI 2.2 to 6.4) and 'readmission within 30 days', OR=6.8 (95% CI 3.0 to 15.2), p<0.0001.

Conclusion

ART was effective for prioritising patients for interventions such as MR.

Factors associated with adverse drug reactions in older inpatients in teaching hospital

Background Adverse drug reactions (ADRs) occur frequently during hospital stays and are an important public health problem, particularly in the care of the older. Objectives This study aimed to determine the prevalence of ADRs among older inpatients and the factors associated with their occurrence. Setting Brazilian teaching hospital. Methods This was a cross-sectional study with older inpatients in the internal medicine ward of a teaching hospital. The dependent variable was the occurrence of an ADR during hospitalization. The independent variables were gender, age, length of hospitalization, number of health problems, medications, and potentially inappropriate medications for the older. Logistic regression was performed to analyze the association between an ADR and the independent variables. Main outcome measure Factors associated with ADR in older inpatients. Results Among the 237 inpatients investigated, 50 (21.1%) developed at least one ADR. The total number of ADRs observed was 62 and the most frequent were acute kidney injury, hypotension, and cutaneous adverse reactions A multivariate analysis demonstrated a positive and independent association between the occurrence of an ADR and the presence of heart failure [odds ratio (OR) 2.4; 95% confidence interval (CI) 1.2-4.6], and with hospitalization time exceeding 12 days (OR 2.3; 95% CI 1.2-4.4). Conclusions The study showed a high prevalence of ADRs among the older and a positive association with hospitalization time and heart failure. Understanding the factors associated with the occurrence of ADRs among older inpatients provides elements for improving the safety of care and optimization of pharmacotherapy.

How can we define and analyse drug exposure more precisely to improve the prediction of hospitalizations in longitudinal (claims) data?

BACKGROUND

Risk prediction models can be powerful tools to support clinical decision-making, to help targeting interventions, and, thus, to improve clinical and economic outcomes, provided that model performance is good and sensitivity and specificity are well balanced. Drug utilization as a potential risk factor for unplanned hospitalizations has recently emerged as a meaningful predictor variable in such models. Drug treatment is a rather unstable (i.e. time-dependent) phenomenon and most drug-induced events are concentration-dependent and therefore individual drug exposure will likely modulate the risk. This especially applies to longitudinal monitoring of appropriate drug treatment within claims data as another promising application for prediction models.

METHODS AND RESULTS

To guide future research towards this direction, we firstly reviewed current risk prediction models for unplanned hospitalizations that explicitly included information on drug utilization and were surprised to find that these models rarely attempted to consider dose and frequent modulators of drug clearance such as interactions with co-medication or co-morbidities. As another example, they often presumed class effects where in fact, differences between active moieties were well established. In addition, the study designs and statistical risk analysis disregarded the fact that medication and risk modulators and, thus, adverse events can vary over time. In a simulation study, we therefore evaluated the potential benefit of time-dependent Cox models over standard binary regression approaches with a fixed follow-up period.

CONCLUSIONS

Longitudinal drug information could be utilized much more efficiently both by precisely estimating individual drug exposure and by applying more refined statistical methodology to account for time-dependent drug utilization patterns.

Predicting risk of adverse drug reactions in older adults

Adverse drug reactions (ADRs) are common in older adults, with falls, orthostatic hypotension, delirium, renal failure, gastrointestinal and intracranial bleeding being amongst the most common clinical manifestations. ADR risk increases with age-related changes in pharmacokinetics and pharmacodynamics, increasing burden of comorbidity, polypharmacy, inappropriate prescribing and suboptimal monitoring of drugs. ADRs are a preventable cause of harm to patients and an unnecessary waste of healthcare resources. Several ADR risk tools exist but none has sufficient predictive value for clinical practice. Good clinical practice for detecting and predicting ADRs in vulnerable patients includes detailed documentation and regular review of prescribed and over-the-counter medications through standardized medication reconciliation. New medications should be prescribed cautiously with clear therapeutic goals and recognition of the impact a drug can have on multiple organ systems. Prescribers should regularly review medication efficacy and be vigilant for ADRs and their contributory risk factors. Deprescribing should occur at an individual level when drugs are no longer efficacious or beneficial or when safer alternatives exist. Inappropriate prescribing and unnecessary polypharmacy should be minimized. Comprehensive geriatric assessment and the use of explicit prescribing criteria can be useful in this regard.

Geriatric patients with cognitive impairment

BACKGROUND

Hospitals are now faced with increasing numbers of cognitively impaired patients aged 80 and older who are at increased risk of treatment complications. This study concerns the outcomes when such patients are treated in a specialized ward for cognitive geriatric medicine.

METHODS

Observation of a cohort of 2084 patients from 2009 to 2014, supplemented by a sample of 380 patients from the hospital cohort of the Longitudinal Urban Cohort Ageing Study (LUCAS) for the years 2010 and 2011.

RESULTS

Geriatric inpatients with cognitive impairment tend to be multimorbid. Half of the patients studied (1031 of 2084 patients) were admitted to the hospital on an emergency basis. Complications arising on the ward that necessitated transfer elsewhere arose in 2.6% (51 of 2084 patients). Moreover, analysis of the sample of 380 patients from the LUCAS cohort revealed that the treatments they underwent during hospitalization were associated with an improvement of their functional state: their mean overall score on the Barthel index rose from 39.8 ± 24.3 (median, 35) on admission to 52.7 ± 27.0 (median, 55) on discharge. The percentage of patients being treated with 5 or more drugs fell from 98.2% (373/380) on admission to 79.3% (314/362) on discharge. The percentage receiving potentially inappropriate medications (PIM), as defined by the PRISCUS list, fell from 45% to 13.3%, while the percentage of drug orders and prescriptions involving PIM fell from 7.8 % (327/4181) to 2.0% (53/2600). 70% of the patients were discharged to the same living situation where they had been before admission.

CONCLUSION

In this study, structured geriatric treatment in a cohort of older acutely ill patients with cognitive impairment was associated with improvement of functions that are relevant to everyday life, as well as with a reduction of polypharmacy. Controlled studies are needed to confirm the observed benefit.