The support of medication reviews in hospitalised patients using a clinical decision support system

Clinical decision support system supported interventions in hospitalized older patients: a matter of natural course and adequate timing

BACKGROUND

Drug-related problems (DRPs) and potentially inappropriate prescribing (PIP) are associated with adverse patient and health care outcomes. In the setting of hospitalized older patients, Clinical Decision Support Systems (CDSSs) could reduce PIP and therefore improve clinical outcomes. However, prior research showed a low proportion of adherence to CDSS recommendations by clinicians with possible explanatory factors such as little clinical relevance and alert fatigue.

OBJECTIVE

To investigate the use of a CDSS in a real-life setting of hospitalized older patients. We aim to (I) report the natural course and interventions based on the top 20 rule alerts (the 20 most frequently generated alerts per clinical rule) of generated red CDSS alerts (those requiring action) over time from day 1 to 7 of hospitalization; and (II) to explore whether an optimal timing can be defined (in terms of day per rule).

METHODS

All hospitalized patients aged ≥ 60 years, admitted to Zuyderland Medical Centre (the Netherlands) were included. The evaluation of the CDSS was investigated using a database used for standard care. Our CDSS was run daily and was evaluated on day 1 to 7 of hospitalization. We collected demographic and clinical data, and moreover the total number of CDSS alerts; the total number of top 20 rule alerts; those that resulted in an action by the pharmacist and the course of outcome of the alerts on days 1 to 7 of hospitalization.

RESULTS

In total 3574 unique hospitalized patients, mean age 76.7 (SD 8.3) years and 53% female, were included. From these patients, in total 8073 alerts were generated; with the top 20 of rule alerts we covered roughly 90% of the total. For most rules in the top 20 the highest percentage of resolved alerts lies somewhere between day 4 and 5 of hospitalization, after which there is equalization or a decrease. Although for some rules, there is a gradual increase in resolved alerts until day 7. The level of resolved rule alerts varied between the different clinical rules; varying from > 50-70% (potassium levels, anticoagulation, renal function) to less than 25%.

CONCLUSION

This study reports the course of the 20 most frequently generated alerts of a CDSS in a setting of hospitalized older patients. We have shown that for most rules, irrespective of an intervention by the pharmacist, the highest percentage of resolved rules is between day 4 and 5 of hospitalization. The difference in level of resolved alerts between the different rules, could point to more or less clinical relevance and advocates further research to explore ways of optimizing CDSSs by adjustment in timing and number of alerts to prevent alert fatigue.

Appropriate medication use in Dutch terminal care: study protocol of a multicentre stepped-wedge cluster randomized controlled trial (the AMUSE study)

BACKGROUND

Polypharmacy is common among patients with a limited life expectancy, even shortly before death. This is partly inevitable, because these patients often have multiple symptoms which need to be alleviated. However, the use of potentially inappropriate medications (PIMs) in these patients is also common. Although patients and relatives are often willing to deprescribe medication, physicians are sometimes reluctant due to the lack of evidence on appropriate medication management for patients in the last phase of life. The aim of the AMUSE study is to investigate whether the use of CDSS-OPTIMED, a software program that gives weekly personalized medication recommendations to attending physicians of patients with a limited life expectancy, improves patients' quality of life.

METHODS

A multicentre stepped-wedge cluster randomized controlled trial will be conducted among patients with a life expectancy of three months or less. The stepped-wedge cluster design, where the clusters are the different study sites, involves sequential crossover of clusters from control to intervention until all clusters are exposed. In total, seven sites (4 hospitals, 2 general practices and 1 hospice from the Netherlands) will participate in this study. During the control period, patients will receive 'care as usual'. During the intervention period, CDSS-OPTIMED will be activated. CDSS-OPTIMED is a validated software program that analyses the use of medication based on a specific set of clinical rules for patients with a limited life expectancy. The software program will provide the attending physicians with weekly personalized medication recommendations. The primary outcome of this study is patients' quality of life two weeks after baseline assessment as measured by the EORTC QLQ-C15-PAL questionnaire, quality of life question.

DISCUSSION

This will be the first study investigating the effect of weekly personalized medication recommendations to attending physicians on the quality of life of patients with a limited life expectancy. We hypothesize that the CDSS-OPTIMED intervention could lead to improved quality of life in patients with a life expectancy of three months or less.

TRIAL REGISTRATION

This trial is registered at ClinicalTrials.gov (NCT05351281, Registration Date: April 11, 2022).

Clinical Decision Support Systems in Hospitalized Older Patients: An Exploratory Analysis in a Real-Life Clinical Setting

BACKGROUND

Inappropriate prescribing is associated with negative patient outcomes. In hospitalized patients, the use of Clinical Decision Support Systems (CDSSs) may reduce inappropriate prescribing and thereby improve patient-related outcomes. However, recently published large clinical trials (OPERAM and SENATOR) have shown negative results on the use of CDSSs and patient outcomes and strikingly low acceptance of recommendations.

OBJECTIVE

The purpose of the present study was to investigate the use of a CDSS in a real-life clinical setting of hospitalized older patients. As such, we report on the real-life pattern of this in-hospital implemented CDSS, including (i) whether generated alerts were resolved; (ii) whether a recorded action by the pharmacist led to an improved number of resolved alerts; and (iii) the natural course of generated alerts, in particular of those in the non-intervention group; as these data are largely lacking in current studies.

METHODS

Hospitalized patients, aged 60 years and older, admitted to Zuyderland Medical Centre, the Netherlands, in 2018 were included. The evaluation of the CDSS was investigated using a database used for standard care. Alongside demographic and clinical data, we also collected the total numbers of CDSS alerts, the number of alerts 'handled' by the pharmacist, those that resulted in an action by the pharmacist, and finally the outcome of the alerts at day 1 and day 3 after the alert was generated.

RESULTS

A total of 3574 unique hospitalized patients, mean age 76.7 (SD 8.3) years and 53% female, were included. From these patients, 8073 alerts were generated, of which 7907 (97.9% of total) were handled by the pharmacist (day 1). In 51.6% of the alerts handled by the pharmacist, an action was initiated, resulting in 36.1% of the alerts resolved after day 1, compared with 27.3% if the pharmacist did not perform an action (p < 0.001). On day 3, in 52.6% of the alerts an action by the pharmacist was initiated, resulting in 62.4% resolved alerts, compared with 48.0% when no action was performed (p < 0.001). In the category renal function, the percentages differed significantly between an action versus no action of the pharmacist at day 1 and at day 3 (16.6% vs 10.6%, p < 0.001 [day 1]; 29.8% vs 19.4%, p < 0.001 [day 3]).

CONCLUSION

This study demonstrates the pattern and natural course of clinical alerts of an in-hospital implemented CDSS in a real-life clinical setting of hospitalized older patients. Besides the already known beneficial effect of actions by pharmacists, we have also shown that many alerts become resolved without any specific intervention. As such, our study provides an important insight into the spontaneous course of resolved alerts, since these data are currently lacking in the literature.

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Control in the Hospital by Extensive Clinical rules for Unplanned hospitalizations in older Patients (CHECkUP); study design of a multicentre randomized study

Background

Due to ageing of the population the incidence of multimorbidity and polypharmacy is rising. Polypharmacy is a risk factor for medication-related (re)admission and therefore places a significant burden on the healthcare system. The reported incidence of medication-related (re)admissions varies widely due to the lack of a clear definition. Some medications are known to increase the risk for medication-related admission and are therefore published in the triggerlist of the Dutch guideline for Polypharmacy in older patients. Different interventions to support medication optimization have been studied to reduce medication-related (re)admissions. However, the optimal template of medication optimization is still unknown, which contributes to the large heterogeneity of their effect on hospital readmissions. Therefore, we implemented a clinical decision support system (CDSS) to optimize medication lists and investigate whether continuous use of a CDSS reduces the number of hospital readmissions in older patients, who previously have had an unplanned probably medication-related hospitalization.

Methods

The CHECkUP study is a multicentre randomized study in older (≥60 years) patients with an unplanned hospitalization, polypharmacy (≥5 medications) and using at least two medications from the triggerlist, from Zuyderland Medical Centre and Maastricht University Medical Centre+ in the Netherlands. Patients will be randomized. The intervention consists of continuous (weekly) use of a CDSS, which generates a Medication Optimization Profile, which will be sent to the patient’s general practitioner and pharmacist. The control group will receive standard care. The primary outcome is hospital readmission within 1 year after study inclusion. Secondary outcomes are one-year mortality, number of emergency department visits, nursing home admissions, time to hospital readmissions and we will evaluate the quality of life and socio-economic status.

Discussion

This study is expected to add evidence on the knowledge of medication optimization and whether use of a continuous CDSS ameliorates the risk of adverse outcomes in older patients, already at an increased risk of medication-related (re)admission. To our knowledge, this is the first large study, providing one-year follow-up data and reporting not only on quality of care indicators, but also on quality-of-life.

Trial registration

The trial was registered in the Netherlands Trial Register on October 14, 2018, identifier: NL7449 (NTR7691). https://www.trialregister.nl/trial/7449.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02723-8.

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.

Medication-related hospital admissions and readmissions in older patients: an overview of literature

Background The number of medication related hospital admissions and readmissions are increasing over the years due to the ageing population. Medication related hospital admissions and readmissions lead to decreased quality of life and high healthcare costs. Aim of the review To assess what is currently known about medication related hospital admissions, medication related hospital readmissions, their risk factors, and possible interventions which reduce medication related hospital readmissions. Method We searched PubMed for articles about the topic medication related hospital admissions and readmissions. Overall 54 studies were selected for the overview of literature. Results Between the different selected studies there was much heterogeneity in definitions for medication related admission and readmissions, in study population and the way studies were performed. Multiple risk factors are found in the studies for example: polypharmacy, comorbidities, therapy non adherence, cognitive impairment, depending living situation, high risk medications and higher age. Different interventions are studied to reduce the number of medication related readmission, some of these interventions may reduce the readmissions like the participation of a pharmacist, education programmes and transition-of-care interventions and the use of digital assistance in the form of Clinical Decision Support Systems. However the methods and the results of these interventions show heterogeneity in the different researches. Conclusion There is much heterogeneity in incidence and definitions for both medication related hospital admissions and readmissions. Some risk factors are known for medication related admissions and readmissions such as polypharmacy, older age and additional diseases. Known interventions that could possibly lead to a decrease in medication related hospital readmissions are spare being the involvement of a pharmacist, education programs and transition-care interventions the most mentioned ones although controversial results have been reported. More research is needed to gather more information on this topic.

Mediating role of the perceived benefits of using a medication safety system in the relationship between transformational leadership and the medication-error management climate

Background

Evidence indicates that applying technology to medication safety will improve the quality of medical services and enhance the medication-error management climate. The perceived benefits of using the medication safety system are an important factor for adopting a system.

Aims

The purpose of this study was to investigate the mediating role of the perceived benefits of using a medication safety system in the relationship between transformational leadership and the medication-error management climate.

Methods

A total of 153 staff nurses from 11 secondary or tertiary hospitals in Korea were included. Descriptive statistics, t-tests, analysis of variance, Pearson correlations and multiple regression analyses were used.

Results

Transformational leadership was significantly correlated with the perceived benefits of the system use (r = .17, p = .032) and medication-error management climate (r = .55, p < .001). The perceived benefit of using the medication safety system was a mediator between transformational leadership and the medication-error management climate.

Conclusions

When chief executive officers construct and implement a medication safety system in their hospitals, transformational leadership can enhance the perceived benefits of system use, which is an important factor that contributes to a positive medication-error management climate.

Are patients with a nasally placed feeding tube at risk of potential drug-drug interactions? A multicentre cross-sectional study

Aims

The primary aims were to determine the rate of potential drug-drug interactions (pDDIs) in patients with nasally placed feeding tubes (NPFT) and the factors significantly associated with pDDIs. The secondary aim was to assess the change in pDDIs for patients between admission and discharge.

Material and methods

This multicentre study applied a cross-sectional design and was conducted in six Brazilian hospitals, from October 2016 to July 2018. Data from patients with NPFT were collected through electronic forms. All regular medications prescribed were recorded. Medications were classified according to the World Health Organization (WHO) Anatomical Therapeutic Chemical code. Drug-drug interaction screening software was used to screen patients’ medications for pDDIs. Negative binomial regression was used to account for the over dispersed nature of the pDDI count. Since the number of pDDIs was closely related to the number of prescribed medications, we modelled the rate of pDDIs with the count of pDDIs as the numerator and the number of prescribed medications as the denominator; six variables were considered for inclusion: time (admission or discharge), patient age, patient gender, age-adjusted Charlson Comorbidity Index (CCI) score, type of prescription (electronic or handwritten) and patient care complexity. To account for correlation within the two time points (admission and discharge) for each patient a generalised estimating equations approach was used to adjust the standard error estimates. To test the change in pDDI rate between admission and discharge a full model of six variables was fitted to generate an adjusted estimate.

Results

In this study, 327 patients were included. At least one pDDI was found in more than 91% of patients on admission and discharge and most of these pDDIs were classified as major severity. Three factors were significantly associated with the rate of pDDIs per medication: patient age, patient care complexity and prescription type (handwritten vs electronic). There was no evidence of a difference in pDDI rate between admission and discharge.

Conclusion

Patients with a NPFT are at high risk of pDDIs. Drug interaction screening tools and computerized clinical decision support systems could be effective risk mitigation strategies for this patient group.

Canonical correlations between individual self-efficacy/organizational bottom-up approach and perceived barriers to reporting medication errors: a multicenter study

Background

Individual and organizational factors correlate with perceived barriers to error reporting. Understanding medication administration errors (MAEs) reduces confusion about error definitions, raises perceptions of MAEs, and allows healthcare providers to report perceived and identified errors more frequently. Therefore, an emphasis must be placed on medication competence, including medication administration knowledge and decision-making. It can be helpful to utilize an organizational approach, such as collaboration between nurses and physicians, but this type of approach is difficult to establish and maintain because patient-safety culture starts at the highest levels of the healthcare organization. This study aimed to examine the canonical correlations of an individual self-efficacy/bottom-up organizational approach variable set with perceived barriers to reporting MAEs among nurses.

Methods

We surveyed 218 staff nurses in Korea. The measurement tools included a questionnaire on knowledge of high-alert medication, nursing decision-making, nurse-physician collaboration satisfaction, and barriers to reporting MAEs. Descriptive statistics, t-tests, analysis of variance (ANOVA), Pearson’s correlation coefficient, and canonical correlations were used to analyze results.

Results

Two canonical variables were significant. The first variate indicated that less knowledge about medication administration (− 0.83) and a higher perception of nurse-physician collaboration (0.42) were related to higher disagreement over medication error (0.64). The second variate showed that intuitive clinical decision-making (− 0.57) and a higher perception of nurse-physician collaboration (0.84) were related to lower perceived barriers to reporting MAEs.

Conclusions

Enhancing positive collaboration among healthcare professionals and promoting analytic decision-making supported by sufficient knowledge could facilitate MAE reporting by nurses. In the clinical phase, providing medication administration education and improving collaboration may reduce disagreement about the occurrence of errors and facilitate MAE reporting. In the policy phase, developing an evidence-based reporting system that informs analytic decision-making may reduce the perceived barriers to MAE reporting.

Development and implementation of "Check of Medication Appropriateness" (CMA): advanced pharmacotherapy-related clinical rules to support medication surveillance

Background

To improve medication surveillance and provide pharmacotherapeutic support in University Hospitals Leuven, a back-office clinical service, called “Check of Medication Appropriateness” (CMA), was developed, consisting of clinical rule based screening for medication inappropriateness. The aim of this study is twofold: 1) describing the development of CMA and 2) evaluating the preliminary results, more specifically the number of clinical rule alerts, number of actions on the alerts and acceptance rate by physicians.

Methods

CMA focuses on patients at risk for potentially inappropriate medication and involves the daily checking by a pharmacist of high-risk prescriptions generated by advanced clinical rules integrating patient specific characteristics with details on medication. Pharmacists’ actions are performed by adding an electronic note in the patients’ medical record or by contacting the physician by phone. A retrospective observational study was performed to evaluate the primary outcomes during an 18-month study period.

Results

39,481 clinical rule alerts were checked by pharmacists for which 2568 (7%) electronic notes were sent and 637 (1.6%) phone calls were performed. 37,782 (96%) alerts were checked within four pharmacotherapeutic categories: drug use in renal insufficiency (25%), QTc interval prolonging drugs (11%), drugs with a restricted indication or dosing (14%) and overruled very severe drug-drug interactions (50%). The emergency department was a frequently involved ward and anticoagulants are the drug class for which actions are most frequently carried out. From the 458 actions performed for the four abovementioned categories, 69% were accepted by physicians.

Conclusions

These results demonstrate the added value of CMA to support medication surveillance in synergy with already integrated basic clinical decision support and bedside clinical pharmacy. Otherwise, the study also highlighted a number of limitations, allowing improvement of the service.

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0748-5) contains supplementary material, which is available to authorized users.

Barriers for Hospital-Based Nurse Practitioners Utilizing Clinical Decision Support Systems: A Systematic Review

There is a national focus on the adoption of healthcare technology to improve the delivery of safe, efficient, and high-quality patient care. Nurse practitioners fulfill an emerging strategic role in the hospital setting. A comprehensive literature review focused on the question: What are the barriers for nurse practitioners utilizing clinical decision support in the hospital setting? Nine studies conducted from 2011 to 2017 were the basis for this review, which identified 13 barriers for nurse practitioners utilizing clinical decision support in the hospital. Having the right information, including up-to-date evidence-based practice guidelines, accurate clinical pathways, and current clinical algorithms, was the most common barrier. Providing reliable clinical decision support is crucial as nurse practitioners become more dependent on hospital technology systems in the delivery of safe patient care. Eliminating barriers to the use of clinical decision support is important for informaticists and nurse practitioners because both groups concentrate on acceptance of decision support systems in the hospital to meet the goal of safe and high-quality patient care.

Better specification of triggers to reduce the number of drug interaction alerts in primary care

OBJECTIVE

Drug interaction alerts (drug-drug and drug-disease interaction alerts) for chronic medications substantially contribute to alert fatigue in primary care. The aim of this study was to determine which events require (re)assessment of a drug interaction and whether using these events as triggers in clinical decision support systems (CDSSs) would affect the alert rate.

METHODS

Two random 5% data samples from the CDSSs of 123 community pharmacies were used: dataset 1 and 2. The top 10 of most frequent drug interaction alerts not involving laboratory values were selected. To reach consensus on events that should trigger alerts (e.g. first time dispensing, dose modification) for these drug interactions, a two-step consensus process was used. An expert panel of community pharmacists participated in an online survey and a subsequent consensus meeting. A CDSS with alerts based on the consensus was simulated in both datasets.

RESULTS

Dataset 1 and 2 together contained 1,672,169 prescriptions which led to 591,073 alerts. Consensus on events requiring alerts was reached for the ten selected drug interactions. The simulation showed a reduction of the alert rate of 93.0% for the ten selected drug interactions (comparable for dataset 1 and 2), corresponding with a 28.3% decrease of the overall drug interaction alert rate.

CONCLUSION

By consensus-based better specification of the events that trigger drug interaction alerts in primary care, the alert rate for these drug interactions was reduced by over 90%. This promising approach deserves further investigation to assess its consequences and applicability in daily practice.