Personal Continuity and Appropriate Prescribing in Primary Care.

PURPOSE: Personal continuity between patient and physician is a core value of primary care. Although previous studies suggest that personal continuity is associated with fewer potentially inappropriate prescriptions, evidence on continuity and prescribing in primary care is scarce. We aimed to determine the association between personal continuity and potentially inappropriate prescriptions, which encompasses potentially inappropriate medications (PIMs) and potential prescribing omissions (PPOs), by family physicians among older patients. METHODS: We conducted an observational cohort study using routine care data from patients enlisted in 48 Dutch family practices from 2013 to 2018. All 25,854 patients aged 65 years and older having at least 5 contacts with their practice in 6 years were included. We calculated personal continuity using 3 established measures: the usual provider of care measure, the Bice-Boxerman Index, and the Herfindahl Index. We used the Screening Tool of Older Person's Prescriptions (STOPP) and the Screening Tool to Alert doctors to Right Treatment (START) specific to the Netherlands version 2 criteria to calculate the prevalence of potentially inappropriate prescriptions. To assess associations, we conducted multilevel negative binomial regression analyses, with and without adjustment for number of chronic conditions, age, and sex. RESULTS: The patients' mean (SD) values for the usual provider of care measure, the Bice-Boxerman Continuity of Care Index, and the Herfindahl Index were 0.70 (0.19), 0.55 (0.24), and 0.59 (0.22), respectively. In our population, 72.2% and 74.3% of patients had at least 1 PIM and PPO, respectively; 30.9% and 34.2% had at least 3 PIMs and PPOs, respectively. All 3 measures of personal continuity were positively and significantly associated with fewer potentially inappropriate prescriptions. CONCLUSIONS: A higher level of personal continuity is associated with more appropriate prescribing. Increasing personal continuity may improve the quality of prescriptions and reduce harmful consequences.

Development and Internal Validation of a Prediction Model for Falls Using Electronic Health Records in a Hospital Setting.

OBJECTIVE: Fall prevention is important in many hospitals. Current fall-risk-screening tools have limited predictive accuracy specifically for older inpatients. Their administration can be time-consuming. A reliable and easy-to-administer tool is desirable to identify older inpatients at higher fall risk. We aimed to develop and internally validate a prognostic prediction model for inpatient falls for older patients. DESIGN: Retrospective analysis of a large cohort drawn from hospital electronic health record data. SETTING AND PARTICIPANTS: Older patients (≥70 years) admitted to a university medical center (2016 until 2021). METHODS: The outcome was an inpatient fall (≥24 hours of admission). Two prediction models were developed using regularized logistic regression in 5 imputed data sets: one model without predictors indicating missing values (Model-without) and one model with these additional predictors indicating missing values (Model-with). We internally validated our whole model development strategy using 10-fold stratified cross-validation. The models were evaluated using discrimination (area under the receiver operating characteristic curve) and calibration (plot assessment). We determined whether the areas under the receiver operating characteristic curves (AUCs) of the models were significantly different using DeLong test. RESULTS: Our data set included 21,286 admissions. In total, 470 (2.2%) had a fall after 24 hours of admission. The Model-without had 12 predictors and Model-with 13, of which 4 were indicators of missing values. The AUCs of the Model-without and Model-with were 0.676 (95% CI 0.646-0.707) and 0.695 (95% CI 0.667-0.724). The AUCs between both models were significantly different (P = .013). Calibration was good for both models. CONCLUSIONS AND IMPLICATIONS: Both the Model-with and Model-without indicators of missing values showed good calibration and fair discrimination, where the Model-with performed better. Our models showed competitive performance to well-established fall-risk-screening tools, and they have the advantage of being based on routinely collected data. This may substantially reduce the burden on nurses, compared with nonautomatic fall-risk-screening tools.

External validation of the Johns Hopkins Fall Risk Assessment Tool in older Dutch hospitalized patients.

PURPOSE: Fall prevention is a safety goal in many hospitals. The performance of the Johns Hopkins Fall Risk Assessment Tool (JHFRAT) in older inpatients is largely unknown. We aimed to assess the JHFRAT performance in a large sample of Dutch older inpatients, including its trend over time. METHODS: We used an Electronic Health Records (EHR) dataset with hospitalized patients (≥ 70), admitted for ≥ 24 h between 2016 and 2021. Inpatient falls were extracted from structured and free-text data. We assessed the association between JHFRAT and falls using logistic regression. For test accuracy, we calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Discrimination was measured by the AUC. For calibration, we plotted the predicted fall probability with the actual probability of falls. For time-related effects, we calculated the AUC per 6 months (using data of patients admitted during the 6 months' time interval) and plotted these different AUC values over time. Furthermore, we compared the model (JHFRAT and falls) with and without adjusting for seasonal influenza, COVID-19, spring, summer, fall or winter periods. RESULTS: Data included 17,263 admissions with at least 1 JHFRAT measurement, a median age of 76 and a percentage female of 47%. The in-hospital fall prevalence was 2.5%. JHFRAT [OR = 1.11 (1.03-1.20)] and its subcategories were significantly associated with falls. For medium/high risk of falls (JHFRAT > 5), sensitivity was 73%, specificity 51%, PPV 4% and NPV 99%. The overall AUC was 0.67, varying over time between 0.62 and 0.71 (for 6 months' time intervals). Seasonal influenza did affect the association between JHFRAT and falls. COVID-19, spring, summer, fall or winter did not affect the association. CONCLUSIONS: Our results show an association between JHFRAT and falls, a low discrimination by JHFRAT for older inpatients and over-prediction in the calibration. Improvements in the fall-risk assessment are warranted to improve efficiency.

Potentially inappropriate medications and their effect on falls during hospital admission.

OBJECTIVE: to investigate the effect of potentially inappropriate medications (PIMs) on inpatient falls and to identify whether PIMs as defined by STOPPFall or the designated section K for falls of STOPP v2 have a stronger association with inpatient falls when compared to the general tool STOPP v2. METHODS: a retrospective observational matching study using an electronic health records dataset of patients (≥70 years) admitted to an academic hospital (2015-19), including free text to identify inpatient falls. PIMs were identified using the STOPP v2, section K of STOPP v2 and STOPPFall. We first matched admissions with PIMs to those without PIMs on confounding factors. We then applied multinomial logistic regression analysis and Cox proportional hazards analysis on the matched datasets to identify effects of PIMs on inpatient falls. RESULTS: the dataset included 16,678 hospital admissions, with a mean age of 77.2 years. Inpatient falls occurred during 446 (2.7%) admissions. Adjusted odds ratio (OR) (95% confidence interval (CI)) for the association between PIM exposure and falls were 7.9 (6.1-10.3) for STOPP section K, 2.2 (2.0-2.5) for STOPP and 1.4 (1.3-1.5) for STOPPFall. Adjusted hazard ratio (HR) (95% CI) for the effect on time to first fall were 2.8 (2.3-3.5) for STOPP section K, 1.5 (1.3-1.6) for STOPP and 1.3 (1.2-1.5) for STOPPFall. CONCLUSIONS: we identified an independent association of PIMs on inpatient falls for all applied (de)prescribing tools. The strongest effect was identified for STOPP section K, which is restricted to high-risk medication for falls. Our results suggest that decreasing PIM exposure during hospital stay might benefit fall prevention, but intervention studies are warranted.

Clinical validation of clinical decision support systems for medication review: A scoping review.

The aim of this scoping review is to summarize approaches and outcomes of clinical validation studies of clinical decision support systems (CDSSs) to support (part of) a medication review. A literature search was conducted in Embase and Medline. In total, 30 articles validating a CDSS were ultimately included. Most of the studies focused on detection of adverse drug events, potentially inappropriate medications and drug-related problems. We categorized the included articles in three groups: studies subjectively reviewing the clinical relevance of CDSS's output (21/30 studies) resulting in a positive predictive value (PPV) for clinical relevance of 4-80%; studies determining the relationship between alerts and actual events (10/30 studies) resulting in a PPV for actual events of 5-80%; and studies comparing output of CDSSs to chart/medication reviews in the whole study population (10/30 studies) resulting in a sensitivity of 28-85% and specificity of 42-75%. We found heterogeneity in the methods used and in the outcome measures. The validation studies did not report the use of a published CDSS validation strategy. To improve the effectiveness and uptake of CDSSs supporting a medication review, future research would benefit from a more systematic and comprehensive validation strategy.

Effect of Interventions With a Clinical Decision Support System for Hospitalized Older Patients: Systematic Review Mapping Implementation and Design Factors.

BACKGROUND: Clinical decision support systems (CDSSs) form an implementation strategy that can facilitate and support health care professionals in the care of older hospitalized patients. OBJECTIVE: Our study aims to systematically review the effects of CDSS interventions in older hospitalized patients. As a secondary aim, we aim to summarize the implementation and design factors described in effective and ineffective interventions and identify gaps in the current literature. METHODS: We conducted a systematic review with a search strategy combining the categories older patients, geriatric topic, hospital, CDSS, and intervention in the databases MEDLINE, Embase, and SCOPUS. We included controlled studies, extracted data of all reported outcomes, and potentially beneficial design and implementation factors. We structured these factors using the Grol and Wensing Implementation of Change model, the GUIDES (Guideline Implementation with Decision Support) checklist, and the two-stream model. The risk of bias of the included studies was assessed using the Cochrane Collaboration's Effective Practice and Organisation of Care risk of bias approach. RESULTS: Our systematic review included 18 interventions, of which 13 (72%) were effective in improving care. Among these interventions, 8 (6 effective) focused on medication review, 8 (6 effective) on delirium, 7 (4 effective) on falls, 5 (4 effective) on functional decline, 4 (3 effective) on discharge or aftercare, and 2 (0 effective) on pressure ulcers. In 77% (10/13) effective interventions, the effect was based on process-related outcomes, in 15% (2/13) interventions on both process- and patient-related outcomes, and in 8% (1/13) interventions on patient-related outcomes. The following implementation and design factors were potentially associated with effectiveness: a priori problem or performance analyses (described in 9/13, 69% effective vs 0/5, 0% ineffective interventions), multifaceted interventions (8/13, 62% vs 1/5, 20%), and consideration of the workflow (9/13, 69% vs 1/5, 20%). CONCLUSIONS: CDSS interventions can improve the hospital care of older patients, mostly on process-related outcomes. We identified 2 implementation factors and 1 design factor that were reported more frequently in articles on effective interventions. More studies with strong designs are needed to measure the effect of CDSS on relevant patient-related outcomes, investigate personalized (data-driven) interventions, and quantify the impact of implementation and design factors on CDSS effectiveness. TRIAL REGISTRATION: PROSPERO (International Prospective Register of Systematic Reviews): CRD42019124470; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=124470.

Potentially inappropriate prescribing in older hospitalized Dutch patients according to the STOPP/START criteria v2: a longitudinal study.

PURPOSE: To investigate prevalence, independent associations, and variation over time of potentially inappropriate prescriptions in a population of older hospitalized patients. METHODS: A longitudinal study using a large dataset of hospital admissions of older patients (≥ 70 years) based on an electronic health records cohort including data from 2015 to 2019. Potentially inappropriate medication (PIM) and potential prescribing omission (PPO) prevalence during hospital stay were identified based on the Dutch STOPP/START criteria v2. Univariate and multivariate logistic regression were used for analyzing associations and trends over time. RESULTS: The data included 16,687 admissions. Of all admissions, 56% had ≥ 1 PIM and 58% had ≥ 1 PPO. Gender, age, number of medications, number of diagnoses, Charlson score, and length of stay were independently associated with both PIMs and PPOs. Additionally, number of departments and number of prescribing specialties were independently associated with PIMs. Over the years, the PIM prevalence did not change (OR = 1.00, p = .95), whereas PPO prevalence increased (OR = 1.08, p < .001). However, when corrected for changes in patient characteristics such as number of diagnoses, the PIM (aOR = 0.91, p < .001) and PPO prevalence (aOR = 0.94, p < .001) decreased over the years. CONCLUSION: We found potentially inappropriate prescriptions in the majority of admissions of older patients. Prescribing relatively improved over time when considering complexity of the admissions. Nevertheless, the high prevalence shows a clear need to better address this issue in clinical practice. Studies seeking effective (re)prescribing interventions are warranted.