Evaluation of Clinical Decision Support to Reduce Sedative-Hypnotic Prescribing in Older Adults

Effect of chair placement on physicians' behavior and patients' satisfaction: randomized deception trial

OBJECTIVE

To evaluate the effect of chair placement on length of time physicians sit during a bedside consultation and patients' satisfaction.

DESIGN

Single center, double blind, randomized controlled deception trial.

SETTING

County hospital in Texas, USA.

PARTICIPANTS

51 hospitalist physicians providing direct care services, and 125 observed encounters of patients who could answer four orientation questions correctly before study entry, April 2022 to February 2023.

INTERVENTION

Each patient encounter was randomized to either chair placement (≤3 feet (0.9 m) of patient's bedside and facing the bed) or usual chair location (control).

MAIN OUTCOME MEASURES

The primary outcome was the binary decision of the physician to sit or not sit at any point during a patient encounter. Secondary outcomes included patient satisfaction, as assessed with the Tool to Assess Inpatient Satisfaction with Care from Hospitalists (TAISCH) and the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys, time in the room, and both physicians' and patients' perception of time in the room.

RESULTS

125 patient encounters were randomized (60 to chair placement and 65 to control). 38 of the 60 physicians in the chair placement group sat during the patient encounter compared with five of the 65 physicians in the control group (odds ratio 20.7, 95% confidence interval 7.2 to 59.4; P<0.001). The absolute risk difference between the intervention and control groups was 0.55 (95% confidence interval 0.42 to 0.69). Overall, 1.8 chairs needed to be placed for a physician to sit. Intervention was associated with 3.9% greater TAISCH scores (effect estimate 3.9, 95% confidence interval 0.9 to 7.0; P=0.01) and 5.1 greater odds of complete scores on HCAHPS (95% confidence interval 1.06 to 24.9, P=0.04). Chair placement was not associated with time spent in the room (10.6 minutes v control 10.6 minutes) nor perception of time in the room for physicians (9.4 minutes v 9.8 minutes) or patients (13.1 minutes v 13.5 minutes).

CONCLUSION

Chair placement is a simple, no cost, low tech intervention that increases a physician's likelihood of sitting during a bedside consultation and resulted in higher patients' scores for both satisfaction and communication.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05250778.

Meaningful time-related aspects of alerts in Clinical Decision Support Systems. A unified framework

Alerts are a common functionality of clinical decision support systems (CDSSs). Although they have proven to be useful in clinical practice, the alert burden can lead to alert fatigue and significantly reduce their usability and acceptance. Based on a literature review, we propose a unified framework consisting of a set of meaningful timestamps that allows the use of state-of-the-art measures for alert burden, such as alert dwell time, alert think time, and response time. In addition, it can be used to investigate other measures that could be relevant as regards dealing with this problem. Furthermore, we provide a case study concerning three different types of alerts to which the framework was successfully applied. We consider that our framework can easily be adapted to other CDSSs and that it could be useful for dealing with alert burden measurement thus contributing to its appropriate management.

Comparative Risk of Harm Associated with Zopiclone or Trazodone Use in Nursing Home Residents: a Retrospective Cohort Study in Alberta, Canada

Background

There is growing evidence of harm associated with trazodone and nonbenzodiazepine sedative hypnotics (e.g., zopiclone); however, their comparative risk of harm is unknown.

Methods

We conducted a retrospective cohort study with linked health administrative data, which enrolled older (≥66 years old) nursing home residents living in Alberta, Canada, between December 1, 2009, and December 31, 2018; the last follow-up date was June 30, 2019. We compared the rate of injurious falls and major osteoporotic fractures (primary outcome) and all-cause mortality (secondary outcome) within 180 days of first prescription of zopiclone or trazodone with cause-specific hazard models and inverse probability of treatment weights to control for confounding; primary analysis was intention-to-treat and secondary analysis was per-protocol (i.e., residents censored if dispensed the other exposure drug).

Results

Our cohort included 1,403 residents newly dispensed trazodone and 1,599 residents newly dispensed zopiclone. At cohort entry, the mean resident age was 85.7 (standard deviation [SD] 7.4), 61.6% were female, and 81.2% had dementia. New zopiclone use was associated with similar rates of injurious falls and major osteoporotic fractures (intention-to-treat-weighted hazard ratio 1.15, 95% confidence interval [CI] 0.90-1.48; per-protocol-weighted hazard ratio 0.85, 95% CI 0.60-1.21) and all-cause mortality (intention-to-treat-weighted hazard ratio 0.96, 95% CI 0.79-1.16; per-protocol-weighted hazard ratio 0.90, 95% CI 0.66-1.23) compared to trazodone.

Conclusions

Zopiclone was associated with a similar rate of injurious falls, major osteoporotic fractures, and all-cause mortality compared to trazodone-suggesting one medication should not be used in lieu of the other. Appropriate prescribing initiatives should also target zopiclone and trazodone.

A Qualitative Description of Clinician Free-Text Rationales Entered within Accountable Justification Interventions

BACKGROUND

Requiring accountable justifications-visible, clinician-recorded explanations for not following a clinical decision support (CDS) alert-has been used to steer clinicians away from potentially guideline-discordant decisions. Understanding themes from justifications across clinical content areas may reveal how clinicians rationalize decisions and could help inform CDS alerts.

METHODS

We conducted a qualitative evaluation of the free-text justifications entered by primary care physicians from three pilot interventions designed to reduce opioid prescribing and, in older adults, high-risk polypharmacy and overtesting. Clinicians encountered alerts when triggering conditions were met within the chart. Clinicians were asked to change their course of action or enter a justification for the action that would be displayed in the chart. We extracted all justifications and grouped justifications with common themes. Two authors independently coded each justification and resolved differences via discussion. Three physicians used a modified Delphi technique to rate the clinical appropriateness of the justifications.

RESULTS

There were 560 justifications from 50 unique clinicians. We grouped these into three main themes used to justify an action: (1) report of a particular diagnosis or symptom (e.g., for "anxiety" or "acute pain"); (2) provision of further contextual details about the clinical case (e.g., tried and failed alternatives, short-term supply, or chronic medication); and (3) noting communication between clinician and patient (e.g., "risks and benefits discussed"). Most accountable justifications (65%) were of uncertain clinical appropriateness.

CONCLUSION

Most justifications clinicians entered across three separate clinical content areas fit within a small number of themes, and these common rationales may aid in the design of effective accountable justification interventions. Justifications varied in terms of level of clinical detail. On their own, most justifications did not clearly represent appropriate clinical decision making.

Modulators Influencing Medication Alert Acceptance: An Explorative Review

OBJECTIVES

Clinical decision support systems (CDSSs) use alerts to enhance medication safety and reduce medication error rates. A major challenge of medication alerts is their low acceptance rate, limiting their potential benefit. A structured overview about modulators influencing alert acceptance is lacking. Therefore, we aimed to review and compile qualitative and quantitative modulators of alert acceptance and organize them in a comprehensive model.

METHODS

In accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guideline, a literature search in PubMed was started in February 2018 and continued until October 2021. From all included articles, qualitative and quantitative parameters and their impact on alert acceptance were extracted. Related parameters were then grouped into factors, allocated to superordinate determinants, and subsequently further allocated into five categories that were already known to influence alert acceptance.

RESULTS

Out of 539 articles, 60 were included. A total of 391 single parameters were extracted (e.g., patients' comorbidity) and grouped into 75 factors (e.g., comorbidity), and 25 determinants (e.g., complexity) were consequently assigned to the predefined five categories, i.e., CDSS, care provider, patient, setting, and involved drug. More than half of all factors were qualitatively assessed (n = 21) or quantitatively inconclusive (n = 19). Furthermore, 33 quantitative factors clearly influenced alert acceptance (positive correlation: e.g., alert type, patients' comorbidity; negative correlation: e.g., number of alerts per care provider, moment of alert display in the workflow). Two factors (alert frequency, laboratory value) showed contradictory effects, meaning that acceptance was significantly influenced both positively and negatively by these factors, depending on the study. Interventional studies have been performed for only 12 factors while all other factors were evaluated descriptively.

CONCLUSION

This review compiles modulators of alert acceptance distinguished by being studied quantitatively or qualitatively and indicates their effect magnitude whenever possible. Additionally, it describes how further research should be designed to comprehensively quantify the effect of alert modulators.

Low Efficacy of Medication Shortage Clinical Decision Support Alerts

OBJECTIVE

 We examined clinical decision support (CDS) alerts designed specifically for medication shortages to characterize and assess provider behavior in response to these short-term clinical situations.

MATERIALS AND METHODS

 We conducted a retrospective analysis of the usage of medication shortage alerts (MSAs) that included at least one alternative medication suggestion and were active for 60 or more days during the 2-year study period, January 1, 2018 to December 31, 2019, in a large health care system. We characterized ordering provider behavior in response to inpatient MSAs. We then developed a linear regression model to predict provider response to alerts using the characteristics of the ordering provider and alert frequency groupings.

RESULTS

 During the study period, there were 67 MSAs in use that focused on 42 distinct medications in shortage. The MSAs suggested an average of 3.9 alternative medications. Adjusting for the different alerts, fellows (p = 0.004), residents (p = 0.03), and physician assistants (p = 0.02) were less likely to accept alerts on average compared with attending physicians. Further, female ordering clinicians (p < 0.001) were more likely to accept alerts on average compared with male ordering clinicians.

CONCLUSION

 Our findings demonstrate that providers tended to reject MSAs, even those who were sometimes flexible about their responses. The low overall acceptance rate supports the theory that alerts appearing at the time of order entry may have limited value, as they may be presented too late in the decision-making process. Though MSAs are designed to be attention-grabbing and higher impact than traditional CDS, our findings suggest that providers rarely change their clinical decisions when presented with these alerts.