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

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.

Drug therapy-related problem management in Nigeria community pharmacy - process evaluation with simulated patient

BACKGROUND

Unresolved drug therapy-related problems (DTRPs) have economic and clinical consequences and are common causes of patients' morbidity and mortality. This study evaluated the ability of community pharmacists to identify and resolve DTRPs and assessed the perceived barriers to DTRP identification and resolution.

METHODS

A cross-sectional study which employed the use of three simulated patients (SPs) visit to 36 selected community pharmacies in 11 local government areas in Ibadan, Nigeria. The SPs played the role of a patient with prescription for multiple ailments (23-year-old male), type 2 diabetes and hypertensive patient with medication packs (45-year-old male) and hypertensive patient with gastric ulcer with a prescription (37-year-old female). They re-enacted three rehearsed vignettes when they spoke with the pharmacists. A five-member panel of experts predetermined the DTRPs present in the vignettes (n = 11), actions to take to investigate the DTRPs (n = 9) and recommendations to resolve the DTRPs (n = 9). Pharmacists' perceived barriers to the identification and resolution of DTRPs were assessed with a self-administered questionnaire. The percentage ability to detect and resolve DTRPs was determined and classified as poor ability (≤30%), fair ability (> 30 - ≤50%), moderate ability (> 50 - ≤70%) and high ability (> 70%).

RESULTS

One hundred and eight visits were made by the three SPs to the pharmacies. In total, 4.42/11 (40.2%) DTRPs were identified, 3.50/9 (38.9%) actions were taken, and 3.94/9 (43.8%) recommendations were made to resolve the identified DTRPs. The percentage ability of the community pharmacists to detect and resolve DTRPs varied slightly from one vignette to another (vignette 1-49.3%, vignette 2-39.1%, vignette 3-38.8%). But overall, it was fair (40.9%). Pharmacists' perceived barriers to DTRP detection and resolution included lack of access to patient's/client's medical history and lack of software for DTRP detection.

CONCLUSIONS

The community pharmacists displayed fair ability in detecting and resolving DTRPs. Several barriers preventing the optimal performance of pharmacist in DTRP identification and resolution were identified including inaccessibility of patient's/client's medical history. The regulatory authority of pharmacy education and practice in Nigeria need to mount Continuing Education Program to address this deficit among community pharmacists.

Clinical usefulness of prediction tools to identify adult hospitalized patients at risk of drug-related problems: A systematic review of clinical prediction models and risk assessment tools

AIMS

This study aimed to review systematically all available prediction tools identifying adult hospitalized patients at risk of drug-related problems, and to synthesize the evidence on performance and clinical usefulness.

METHODS

PubMed, Scopus, Web of Science, Embase, and CINAHL databases were searched for relevant studies. Titles, abstracts and full-text studies were sequentially screened for inclusion by two independent reviewers. The Prediction Model Risk of Bias Assessment Tool (PROBAST) and the Revised Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) checklists were used to assess risk of bias and applicability of prediction tools. A narrative synthesis was performed.

RESULTS

A total of 21 studies were included, 14 of which described the development of new prediction tools (four risk assessment tools and ten clinical prediction models) and six studies were validation based and one an impact study. There were variations in tool development processes, outcome measures and included predictors. Overall, tool performance had limitations in reporting and consistency, with the discriminatory ability based on area under the curve receiver operating characteristics (AUROC) ranging from poor to good (0.62-0.81), sensitivity and specificity ranging from 57.0% to 89.9% and 30.2% to 88.0%, respectively. The Medicines Optimisation Assessment tool and Assessment of Risk tool were prediction tools with the lowest risk of bias and low concern for applicability. Studies reporting external validation and impact on patient outcomes were scarce.

CONCLUSION

Most prediction tools have limitations in development and validation processes, as well as scarce evidence of clinical usefulness. Future studies should attempt to either refine currently available tools or apply a rigorous process capturing evidence of acceptance, usefulness, performance and outcomes.

Opioids, Polypharmacy, and Drug Interactions: A Technological Paradigm Shift Is Needed to Ameliorate the Ongoing Opioid Epidemic

Polypharmacy is a common phenomenon among adults using opioids, which may influence the frequency, severity, and complexity of drug–drug interactions (DDIs) experienced. Clinicians must be able to easily identify and resolve DDIs since opioid-related DDIs are common and can be life-threatening. Given that clinicians often rely on technological aids—such as clinical decision support systems (CDSS) and drug interaction software—to identify and resolve DDIs in patients with complex drug regimens, this narrative review provides an appraisal of the performance of existing technologies. Opioid-specific CDSS have several system- and content-related limitations that need to be overcome. Specifically, we found that these CDSS often analyze DDIs in a pairwise manner, do not account for relevant pharmacogenomic results, and do not integrate well with electronic health records. In the context of polypharmacy, existing systems may encourage inadvertent serious alert dismissal due to the generation of multiple incoherent alerts. Future technological systems should minimize alert fatigue, limit manual input, allow for simultaneous multidrug interaction assessments, incorporate pharmacogenomic data, conduct iterative risk simulations, and integrate seamlessly with normal workflow.

Association of a Novel Medication Risk Score with Adverse Drug Events and Other Pertinent Outcomes Among Participants of the Programs of All-Inclusive Care for the Elderly

Preventable adverse drug events (ADEs) represent a significant public health challenge for the older adult population, since they are associated with higher medical expenditures and more hospitalizations and emergency department (ED) visits. This study examines whether a novel medication risk prediction tool, the MedWise Risk Score™ (MRS), is associated with ADEs and other pertinent outcomes in participants of the Programs of All-Inclusive Care for the Elderly (PACE). Unlike other risk predictors, this tool produces actionable information that pharmacists can easily use to reduce ADE risk. This was a retrospective cross-sectional study that analyzed administrative medical claims data of 1965 PACE participants in 2018. To detect ADEs, we identified all claims that had ADE-related International Classification of Diseases and Health Related Problems, 10th revision (ICD-10) codes. Using logistic and linear regression models, we examined the association between the MRS and a variety of outcomes, including the number of PACE participants with an ADE, total medical expenditures, ED visits, hospitalizations, and hospital length of stay. We found significant associations for every outcome. Specifically, every point increase in the MRS corresponded to an 8.6% increase in the odds of having one or more ADEs per year (OR = 1.086, 95% CI: 1.060, 1.113), $1037 USD in additional annual medical spending (adjusted R² of 0.739; p < 0.001), 3.2 additional ED visits per 100 participants per year (adjusted R² of 0.568; p < 0.001), and 2.1 additional hospitalizations per 100 participants per year (adjusted R² of 0.804; p < 0.001). Therefore, the MRS can risk stratify PACE participants and predict a host of important and relevant outcomes pertaining to medication-related morbidity.