Drug interaction alert override rates in the Meaningful Use era: no evidence of progress

Clinician Perceptions of Timing and Presentation of Drug-Drug Interaction Alerts

OBJECTIVE

Alert presentation of clinical decision support recommendations is a common method for providing information; however, many alerts are overridden suggesting presentation design improvements can be made. This study attempts to assess pediatric prescriber information needs for drug-drug interactions (DDIs) alerts and to evaluate the optimal presentation timing and presentation in the medication ordering process.

METHODS

Six case scenarios presented interactions between medications used in pediatric specialties of general medicine, infectious disease, cardiology, and neurology. Timing varied to include alert interruption at medication selection versus order submission; or was noninterruptive. Interviews were audiotaped, transcribed, and independently analyzed to derive central themes.

RESULTS

Fourteen trainee and attending clinicians trained in pediatrics, cardiology, and neurology participated. Coders derived 8 central themes from 929 quotes. Discordance exists between medication prescribing frequency and DDI knowledge; providers may commonly prescribe medications for which they do not recognize DDIs. Providers wanted alerts at medication selection rather than at order signature. Alert presentation themes included standardizing text, providing interaction-specific incidence/risk information, DDI rating scales, consolidating alerts, and providing alternative therapies. Providers want alerts to be actionable, for example, allowing medication discontinuation and color visual cues for essential information. Despite alert volume, participants did not "mind being reminded because there is always the chance that at that particular moment (they) do not remember it" and acknowledged the importance of alerts as "essential in terms of patient safety."

CONCLUSION

Clinicians unanimously agreed on the importance of receiving DDI alerts to improve patient safety. The perceived alert value can be improved by incorporating clinician preferences for timing and presentation.

Appropriateness of Overridden Alerts in Computerized Physician Order Entry: Systematic Review

BACKGROUND

The clinical decision support system (CDSS) has become an indispensable tool for reducing medication errors and adverse drug events. However, numerous studies have reported that CDSS alerts are often overridden. The increase in override rates has raised questions about the appropriateness of CDSS application along with concerns about patient safety and quality of care.

OBJECTIVE

The aim of this study was to conduct a systematic review to examine the override rate, the reasons for the alert override at the time of prescribing, and evaluate the appropriateness of overrides.

METHODS

We searched electronic databases, including Google Scholar, PubMed, Embase, Scopus, and Web of Science, without language restrictions between January 1, 2000 and March 31, 2019. Two authors independently extracted data and crosschecked the extraction to avoid errors. The quality of the included studies was examined following Cochrane guidelines.

RESULTS

We included 23 articles in our systematic review. The range of average override alerts was 46.2%-96.2%. An average of 29.4%-100% of the overrides alerts were classified as appropriate, and the rate of appropriateness varied according to the alert type (drug-allergy interaction 63.4%-100%, drug-drug interaction 0%-95%, dose 43.9%-88.8%, geriatric 14.3%-57%, renal 27%-87.5%). The interrater reliability for the assessment of override alerts appropriateness was excellent (kappa=0.79-0.97). The most common reasons given for the override were "will monitor" and "patients have tolerated before."

CONCLUSIONS

The findings of our study show that alert override rates are high, and certain categories of overrides such as drug-drug interaction, renal, and geriatric were classified as inappropriate. Nevertheless, large proportions of drug duplication, drug-allergy, and formulary alerts were appropriate, suggesting that these groups of alerts can be primary targets to revise and update the system for reducing alert fatigue. Future efforts should also focus on optimizing alert types, providing clear information, and explaining the rationale of the alert so that essential alerts are not inappropriately overridden.

Role of Opioid-Involved Drug Interactions in Chronic Pain Management

The use of opioids for chronic pain management is extraordinarily common despite substantial evidence of only modest benefits, when compared with nonopioid analgesics. Opioid use is also associated with serious risks, including overdose and death. A growing body of evidence suggests that opioids are involved in significant drug interactions that often go unrecognized in clinical practice. Understanding opioid-involved drug interactions is of great practical importance for all health care professionals caring for patients with chronic pain. In this article, we describe the mechanisms of opioid-involved drug interactions and their potential consequences, which have major public health implications. Additionally, this article provides practical strategies to aid health care professionals in avoiding and mitigating opioid-involved drug interactions in order to obtain a favorable balance in the risk-benefit ratio associated with opioid use. These strategies include using osteopathic principles for chronic pain management, separating the times of administration of the opioid(s) from the nonopioid(s) involved in the interaction, changing the opioid(s) adversely affected by the interaction, changing the nonopioid(s) causing the interaction, and partnering with pharmacists in clinical practice.

Designing, Conducting, and Reporting Clinical Decision Support Studies: Recommendations and Call to Action

By enabling more efficient and effective medical decision making, computer-based clinical decision support (CDS) could unlock widespread benefits from the significant investment in electronic health record (EHR) systems in the United States. Evidence from high-quality CDS studies is needed to enable and support this vision of CDS-facilitated care optimization, but limited guidance is available in the literature for designing and reporting CDS studies. To address this research gap, this article provides recommendations for designing, conducting, and reporting CDS studies to: 1) ensure that EHR data to inform the CDS are available; 2) choose decision rules that are consistent with local care processes; 3) target the right users and workflows; 4) make the CDS easy to access and use; 5) minimize the burden placed on users; 6) incorporate CDS success factors identified in the literature, in particular the automatic provision of CDS as a part of clinician workflow; 7) ensure that the CDS rules are adequately tested; 8) select meaningful evaluation measures; 9) use as rigorous a study design as is feasible; 10) think about how to deploy the CDS beyond the original host organization; 11) report the study in context; 12) help the audience understand why the intervention succeeded or failed; and 13) consider the financial implications. If adopted, these recommendations should help advance the vision of more efficient, effective care facilitated by useful and widely available CDS.

Twilighted Homegrown Systems: The Experience of Six Traditional Electronic Health Record Developers in the Post-Meaningful Use Era

Objectives  This study aimed to understand if and how homegrown electronic health record (EHR) systems are used in the post–Meaningful Use (MU) era according to the experience of six traditional EHR developers.

Methods  We invited informatics leaders from a convenience sample of six health care organizations that have recently replaced their long used homegrown systems with commercial EHRs. Participants were asked to complete a written questionnaire with open-ended questions designed to explore if and how their homegrown system(s) is being used and maintained after adoption of a commercial EHR. We used snowball sampling to identify other potential respondents and institutions.

Results  Participants from all six organizations included in our initial sample completed the questionnaire and provided referrals to four other organizations; from these, two did not respond to our invitations and two had not yet replaced their system and were excluded. Two organizations (Columbia University and University of Alabama at Birmingham) still use their homegrown system for direct patient care and as a downtime system. Four organizations (Intermountain Healthcare, Partners Healthcare, Regenstrief Institute, and Vanderbilt University) kept their systems primarily to access historical data. All organizations reported the need to continue to develop or maintain local applications despite having adopted a commercial EHR. The most common applications developed include display and visualization tools and clinical decision support systems.

Conclusion  Homegrown EHR systems continue to be used for different purposes according to the experience of six traditional homegrown EHR developers. The annual cost to maintain these systems varies from $21,000 to over 1 million. The collective experience of these organizations indicates that commercial EHRs have not been able to provide all functionality needed for patient care and local applications are often developed for multiple purposes, which presents opportunities for future research and EHR development.

Evaluating the alert appropriateness of clinical decision support systems in supporting clinical workflow

The overwhelming number of medication alerts generated by clinical decision support systems (CDSS) has led to inappropriate alert overrides, which may lead to unintended patient harm. This review highlights the factors affecting the alert appropriateness of CDSS and barriers to the fit of CDSS alert with clinical workflow. A literature review was conducted to identify features and functions pertinent to CDSS alert appropriateness using the five rights of CDSS. Moreover, a process improvement method, namely, Lean, was used as a tool to optimise clinical workflows, and the appropriate design for CDSS alert using a human automation interaction (HAI) model was recommended. Evaluating the appropriateness of CDSS alert and its impact on workflow provided insights into how alerts can be designed and triggered effectively to support clinical workflow. The application of Lean methods and tools to analyse alert efficiencies in supporting workflow in this study provides an in-depth understanding of alert-workflow fit problems and their root cause, which is required for improving CDSS design. The application of the HAI model is recommended in the design of CDSS alerts to support various levels and stages of alert automations, namely, information acquisition and analysis, decision action and action implementation.

Potential Drug interactions with Drugs used for Bipolar Disorder: A Comparison of 6 Drug Interaction Database Programs

Background Patients with bipolar disorder frequently experience polypharmacy, putting them at risk for clinically significant drug-drug interactions (DDI). Online drug interaction database programs are used to alert physicians, but there are no internationally recognized standards to define DDI. This study compared the category of potential DDI returned by 6 commercial drug interaction database programs for drug interaction pairs involving drugs commonly prescribed for bipolar disorder.

Methods The category of potential DDI provided by 6 drug interaction database programs (3 subscription, 3 open access) was obtained for 125 drug interaction pairs. The pairs involved 103 drugs (38 psychiatric, 65 nonpsychiatric); 88 pairs included a psychiatric and nonpsychiatric drug; 37 pairs included 2 psychiatric drugs. Every pair contained at least 1 mood stabilizer or antidepressant. The category provided by 6 drug interaction database programs was compared using percent agreement and Fleiss kappa statistic of interrater reliability.

Results For the 125 drug pairs, the overall percent agreement among the 6 drug interaction database programs was 60%; the Fleiss kappa agreement was slight. For drug interaction pairs with any category rating of severe (contraindicated), the kappa agreement was moderate. For drug interaction pairs with any category rating of major, the kappa agreement was slight.

Conclusion There is poor agreement among drug interaction database programs for the category of potential DDI involving psychiatric drugs. Drug interaction database programs provide valuable information, but the lack of consistency should be recognized as a limitation. When assistance is needed, physicians should check more than 1 drug interaction database program.

A Late Attempt to Involve End Users in the Design of Medication-Related Alerts: Survey Study

Background

When users of electronic medical records (EMRs) are presented with large numbers of irrelevant computerized alerts, they experience alert fatigue, begin to ignore alert information, and override alerts without processing or heeding alert recommendations. Anecdotally, doctors at our study site were dissatisfied with the medication-related alerts being generated, both in terms of volume being experienced and clinical relevance.

Objective

This study aimed to involve end users in the redesign of medication-related alerts in a hospital EMR, 4 years post implementation.

Methods

This work was undertaken at a private not-for-profit teaching hospital in Sydney, Australia. Since EMR implementation in 2015, the organization elected to implement all medication-related alert types available in the system for prescribers: allergy and intolerance alerts, therapeutic duplication alerts, pregnancy alerts, and drug-drug interaction alerts. The EMR included no medication administration alerts for nurses. To obtain feedback on current alerts and suggestions for redesign, a Web-based survey was distributed to all doctors and nurses at the site via hospital mailing lists.

Results

Despite a general dissatisfaction with alerts, very few end users completed the survey. In total, only 3.37% (36/1066) of doctors and 14.5% (60/411) of nurses took part. Approximately 90% (30/33) of doctors who responded held the view that too many alerts were triggered in the EMR. Doctors suggested that most alerts be removed and that alerts be more specific and less sensitive. In contrast, 97% (58/60) of the nurse respondents indicated that they would like to receive medication administration alerts in the EMR. Most nurses indicated that they would like to receive all the alert types available at all severity levels.

Conclusions

Attempting to engage with end users several years post implementation was challenging. Involving users so late in the implementation process may lead to clinicians viewing the provision of feedback to be futile. Seeking user feedback on usefulness, volume, and design of alerts is extremely valuable; however, we suggest this is undertaken early, preferably before system implementation.

A systematic approach to optimize electronic health record medication alerts in a health system

PURPOSE

The effectiveness of a systematic, streamlined approach to optimize drug-drug interaction alerts in an electronic health record for a health system was studied.

METHODS

An 81-week quasi-experimental study was conducted to evaluate interventions made to medication-related clinical decision-support (CDS) alerts. Medication-related CDS alerts were systematically reduced using a multi disciplinary healthcare committee. The primary endpoint was weekly overall, modification, and acknowledgement rates of medication alerts after drug-drug interaction reclassification. Secondary endpoints included sub analysis of types of medication alerts (drug-drug interaction and duplicate therapy alerts) and alert use by providers (pharmacist and prescribers). Data was analyzed using interrupted time series regression analysis.

RESULTS

After implementation of the new alert system, total number of weekly inpatient alerts decreased from 68,900 (66,300-70,900) and 50,300 (48,600-53,600) in the postintervention period (p < 0.001). The perentage of alerts acknowledged weekly increased from 11.8% (IQR, 11.4-12.1%) in the preintervention period to 13.7% (IQR, 13.3-14.0%) in the postintervention period (p < 0.001). The percentage of alerts that were modified also increased from 5.0% (IQR, 4.9-5.3%) in the preintervention period to 7.3% (IQR, 7.0-7.6%) in the postintervention period (p < 0.001). Both increases were primarily seen with pharmacists versus other healthcare professionals (p < 0.001).

CONCLUSION

A committee-led systematic approach to optimizing drug-drug interactions facilitated a significant decrease in the overall number of alerts and an increase in both medication alert acknowledgement and modification rates.

Drug information centre queries and responses about drug interactions over 10 years-A descriptive analysis

Many people are treated with ≥1 drug, implying that risks of drug interactions need to be considered. The aim of this study was to describe drug interaction queries from healthcare professionals to a drug information centre in Sweden over 10 years focusing on drugs frequently asked about and the advice provided. Advice was recorded in mutually exclusive groups: Avoid, Adjust dose, Separate intake, Vigilance or No problem. For queries with Avoid, Adjust dose or Separate intake advice, alerts were extracted from an interaction database (Janusmed). Of 4335 queries to the centre in 2008-2017, 589 (14%) concerned interactions. Most were posed by physicians (91%) and concerned a specific patient (83%) before treatment initiation (76%). Sertraline, warfarin and methotrexate were the most frequently asked about, whereas queries about cyclophosphamide and rifampicine occurred most often in relation to the number of exposed patients. Advice provided in 557 (95%) replies comprised Avoid: n = 85 (15%), Adjust dose: n = 57 (10%), Separate intake: n = 17 (3%), Vigilance: n = 235 (42%) or No problem: n = 163 (29%). In all, 113 (71%) of 159 queries with Avoid/Adjust dose/Separate intake advice elicited an action alert on Janusmed, whereas 31 (20%) did not result in any alert at all. Summarized, seven in ten replies from the drug information centre recommended an explicit drug treatment action, regarding either specific prescribing aspects, for instance dose adjustments, or active follow-up including monitoring potential adverse reactions and/or laboratory results. Readily accessible decision support regarding drug interactions often provides relevant action alerts, but cannot be solely relied on.

The Effect of Eliminating Intermediate Severity Drug-Drug Interaction Alerts on Overall Medication Alert Burden and Acceptance Rate

OBJECTIVE

This study aimed to determine the effects of reducing the number of drug-drug interaction (DDI) alerts in an order entry system.

METHODS

Retrospective pre-post analysis at an urban medical center of the rates of medication alerts and alert acceptance during a 5-month period before and 5-month period after the threshold for firing DDI alerts was changed from "intermediate" to "severe." To ensure that we could determine varying response to each alert type, we took an in-depth look at orders generating single alerts.

RESULTS

Before the intervention, 241,915 medication orders were placed, of which 25.6% generated one or more medication alerts; 5.3% of the alerts were accepted. During the postintervention period, 245,757 medication orders were placed of which 16.0% generated one or more medication alerts, a 37.5% relative decrease in alert rate (95% confidence interval [CI]: -38.4 to -36.8%), but only a 9.6% absolute decrease (95% CI: -9.4 to -9.9%). 7.4% of orders generating alerts were accepted postintervention, a 39.6% relative increase in acceptance rate (95% CI: 33.2-47.2%), but only a 2.1% absolute increase (95% CI: 1.8-2.4%). When only orders generating a single medication alert were considered, there was a 69.1% relative decrease in the number of orders generating DDI alerts, and an 85.7% relative increase in the acceptance rate (95% CI: 58.6-126.2%), though only a 1.8% absolute increase (95% CI: 1.3-2.3%).

CONCLUSION

Eliminating intermediate severity DDI alerts resulted in a statistically significant decrease in alert burden and increase in the rate of medication alert acceptance, but alert acceptance remained low overall.

Medication-related clinical decision support alert overrides in inpatients

Objective

To define the types and numbers of inpatient clinical decision support alerts, measure the frequency with which they are overridden, and describe providers' reasons for overriding them and the appropriateness of those reasons.

Materials and Methods

We conducted a cross-sectional study of medication-related clinical decision support alerts over a 3-year period at a 793-bed tertiary-care teaching institution. We measured the rate of alert overrides, the rate of overrides by alert type, the reasons cited for overrides, and the appropriateness of those reasons.

Results

Overall, 73.3% of patient allergy, drug-drug interaction, and duplicate drug alerts were overridden, though the rate of overrides varied by alert type (P < .0001). About 60% of overrides were appropriate, and that proportion also varied by alert type (P < .0001). Few overrides of renal- (2.2%) or age-based (26.4%) medication substitutions were appropriate, while most duplicate drug (98%), patient allergy (96.5%), and formulary substitution (82.5%) alerts were appropriate.

Discussion

Despite warnings of potential significant harm, certain categories of alert overrides were inappropriate >75% of the time. The vast majority of duplicate drug, patient allergy, and formulary substitution alerts were appropriate, suggesting that these categories of alerts might be good targets for refinement to reduce alert fatigue.

Conclusion

Almost three-quarters of alerts were overridden, and 40% of the overrides were not appropriate. Future research should optimize alert types and frequencies to increase their clinical relevance, reducing alert fatigue so that important alerts are not inappropriately overridden.

Adverse drug reactions caused by drug-drug interactions in cardiovascular disease patients: introduction of a simple prediction tool using electronic screening database items

Objective: Cardiovascular disease (CVD) drugs have been frequently implicated in adverse drug reaction (ADR)-related hospitalizations. Drug-drug interactions (DDIs) are common preventable cause of ADRs, but the impact of DDIs in the CVD population has not been investigated. Hence, the primary aim of the study was to identify DDIs associated with ADRs in CVD patients at hospital admission. The second aim was to develop a simple tool to identify high-risk patients for DDI-related adverse events. Methods: An observational study was conducted on the Cardiology Ward of University Clinical Hospital Center. Data were obtained from medical charts. A clinical panel identified DDIs implicated in ADRs, using LexiInteract database and Drug Interaction Probability Scale. Statistics were performed using PASW 22 (SPSS Inc.). Results: DDIs contributed to hospital admission with a total prevalence of 9.69%. DDI-related ADRs affected mainly cardiac function (heart rate or rhythm, 41.07%); bleeding and effect on blood pressure were equally distributed (17.86%). Non-cardiovascular ADRs were found in 23.21% of DDIs. After admission, 73% of the identified DDIs led to changes in prescription. Prediction ability of calculated DDI adverse event probability scores was rated as good (AUC = 0.80, p < .001). Conclusions: CVD patients are highly exposed to adverse DDIs; about one in ten patients hospitalized with CVD might have a DDI contributing to the hospitalization. Given the high prevalence of CVD, DDI-related harm might be a significant burden worldwide. Identification of patients with high DDI adverse event risk might ease the recognition of DDI-related harm and improve the use of electronic databases in clinical practice.

Evaluation of context-specific alerts for potassium-increasing drug-drug interactions: A pre-post study

OBJECTIVE

To investigate whether context-specific alerts for potassium-increasing drug-drug interactions (DDIs) in a clinical decision support system reduced the alert burden, increased alert acceptance, and had an effect on the occurrence of hyperkalemia.

MATERIALS AND METHODS

In the pre-intervention period all alerts for potassium-increasing DDIs were level 1 alerts advising absolute contraindication, while in the post-intervention period the same drug combinations could trigger a level 1 (absolute contraindication), a level 2 (monitor potassium values), or a level 3 alert (informative, not shown to physicians) based on the patient's recent laboratory value of potassium. Alert acceptance was defined as non-prescription or non-administration of the interacting drug combination for level 1 alerts and as monitoring of the potassium levels for level 2 alerts.

RESULTS

The alert burden decreased by 92.8%. The relative risk (RR) for alert acceptance based on prescription rates for level 1 alerts and monitoring rates for level 2 alerts was 15.048 (86.5% vs 5.7%; 95% CI 12.037-18.811; P < 0.001). With alert acceptance for level 1 alerts based on actual administration and for level 2 alerts on monitoring rates, the RR was 3.597 (87.6% vs 24.4%; 95% CI 3.192-4.053; P < 0.001). In the generalized linear mixed model the effect of the intervention on the occurrence of hyperkalemia was not significant (OR 1.091, 95% CI 0.172-6.919).

CONCLUSION

The proposed strategy seems effective to get a grip on the delicate balance between over- and under alerting.

Optimising computerised decision support to transform medication safety and reduce prescriber burden: study protocol for a mixed-methods evaluation of drug-drug interaction alerts

INTRODUCTION

Drug-drug interaction (DDI) alerts in hospital electronic medication management (EMM) systems are generated at the point of prescribing to warn doctors about potential interactions in their patients' medication orders. This project aims to determine the impact of DDI alerts on DDI rates and on patient harm in the inpatient setting. It also aims to identify barriers and facilitators to optimal use of alerts, quantify the alert burden posed to prescribers with implementation of DDI alerts and to develop algorithms to improve the specificity of DDI alerting systems.

METHODS AND ANALYSIS

A controlled pre-post design will be used. Study sites include six major referral hospitals in two Australian states, New South Wales and Queensland. Three hospitals will act as control sites and will implement an EMM system without DDI alerts, and three as intervention sites with DDI alerts. The medical records of 280 patients admitted in the 6 months prior to and 6 months following implementation of the EMM system at each site (total 3360 patients) will be retrospectively reviewed by study pharmacists to identify potential DDIs, clinically relevant DDIs and associated patient harm. To identify barriers and facilitators to optimal use of alerts, 10-15 doctors working at each intervention hospital will take part in observations and interviews. Non-identifiable DDI alert data will be extracted from EMM systems 6-12 months after system implementation in order to quantify alert burden on prescribers. Finally, data collected from chart review and EMM systems will be linked with clinically relevant DDIs to inform the development of algorithms to trigger only clinically relevant DDI alerts in EMM systems.

ETHICS AND DISSEMINATION

This research was approved by the Hunter New England Human Research Ethics Committee (18/02/21/4.07). Study results will be published in peer-reviewed journals and presented at local and international conferences and workshops.

Unintended Consequences of Nationwide Electronic Health Record Adoption: Challenges and Opportunities in the Post-Meaningful Use Era

The US health system has recently achieved widespread adoption of electronic health record (EHR) systems, primarily driven by financial incentives provided by the Meaningful Use (MU) program. Although successful in promoting EHR adoption and use, the program, and other contributing factors, also produced important unintended consequences (UCs) with far-reaching implications for the US health system. Based on our own experiences from large health information technology (HIT) adoption projects and a collection of key studies in HIT evaluation, we discuss the most prominent UCs of MU: failed expectations, EHR market saturation, innovation vacuum, physician burnout, and data obfuscation. We identify challenges resulting from these UCs and provide recommendations for future research to empower the broader medical and informatics communities to realize the full potential of a now digitized health system. We believe that fixing these unanticipated effects will demand efforts from diverse players such as health care providers, administrators, HIT vendors, policy makers, informatics researchers, funding agencies, and outside developers; promotion of new business models; collaboration between academic medical centers and informatics research departments; and improved methods for evaluations of HIT.

Countrywide prevalence of critical drug interactions in Hungarian outpatients: a retrospective analysis of pharmacy dispensing data

Background

Drug-drug interactions (DDIs) present a significant source of adverse drug reactions. Despite being one of the commonly cited risks to patient safety, prevention of DDIs still poses a challenge to healthcare systems. The prevalence of DDIs can be used as a quality indicator for the safety of prescribing. With the analysis of drug utilization databases, real-world data on critical DDIs can be obtained. The aim of this study was to establish a list of critical DDIs and estimate their prevalence in the Hungarian outpatient population.

Methods

Since there is no conclusive and generally accepted repository of high-risk DDIs, a systematic search of the literature for consensus-based lists was performed. Based on these results and their analysis with 5 interaction compendia, we propose a simple methodology to identify critical combinations. Present study focused on DDIs which are (1) of high clinical importance thus being most likely to cause significant harm if not detected, (2) well-supported by available evidence and (3) affect drugs which are routinely dispensed in the community pharmacy setting. A retrospective analysis of prescriptions filled between 2013 and 2016 was performed. The source of drug utilization data was the IQVIA’s national prescription fill database. The number of interacting drug pairs dispensed at the same time to the same patient was established.

Results

After excluding drugs with low dispensing rates, the analysis covered 39 DDIs. The distribution of risk categories of the analysed DDIs was inconsistent among different drug interaction compendia. The total number of prescriptions filled varied between 173924449 and 176368468 per year. The prevalence of the selected potential DDIs ranged from 0.00 to 355.89 per 100000 prescriptions per year. There was significant variation between how the number of cases had changed for each DDI throughout the study period, no general tendency could have been described.

Conclusions

There were 1.8 million cases of co-dispensing each year, where prescribers’ and community pharmacists’ role in recognizing and managing potentially serious interactions was or would have been critical. The method presented to identify high-risk DDIs can serve as a starting point for the much-needed improvement of routine interaction screening.

Electronic supplementary material

The online version of this article (10.1186/s40360-019-0311-0) contains supplementary material, which is available to authorized users.

Drug Interactions in Space: a Cause for Concern?

PURPOSE

Crewmembers aboard the International Space Station (ISS) have free access to an increasing number of medications within medical kits. The aim of the current study was to assess the number, severity and reliability of potential drug-drug interactions (DDIs) involving those medications.

METHODS

We evaluated the information obtained from clinical decision support systems. Searches for potential DDIs were applied to published lists of medications available to US astronauts in medical kits aboard the ISS.

RESULTS

A total of 311 potential DDIs were identified by Lexi-Interact, of which approximately half were recognized by Micromedex as well. Major, moderate and minor interactions consisted 23.5%, 68.5% and 8.0% of entries, respectively. The reliability of 71.1% of alerts was fair. Commonly used drugs, including zolpidem and zaleplon, were involved in multiple potential interactions that were classified as major based on additive CNS depression.

CONCLUSIONS

Most potential DDIs likely to be encountered in space are unestablished even in terrestrial medicine and their assignment is based on class-effects. Yet, some drug combinations may be associated with clinically-relevant consequences. Future DDI rating should be adjusted to space-related outcomes. Until that happens, it would be advisable to avoid non-established drug combinations in space when possible.

A retrospective comparison of inappropriate prescribing of psychotropics in three Norwegian nursing homes in 2000 and 2016 with prescribing quality indicators

Background

Inappropriate prescribing of psychotropics is a persistent and prevalent problem in nursing homes. The present study compared inappropriate prescribing of psychotropics in nursing homes 16 years apart with prescribing quality indicators. The purpose was to identify any change in inappropriate prescribing of relevance for medical informatics.

Methods

Three Norwegian nursing homes were audited in 2000 and 2016 with regard to prescribing quality. Psychotropics among 386 patients in 2000, and 416 patients in 2016, included combinations of antidepressants, antipsychotics, anxiolytics-hypnotics, and antiepileptics. Prescribing quality indicators included psychotropic polypharmacy (defined as concurrent use of three or more psychotropics) and potential inappropriate psychotropic substances or combinations. Furthermore, potential clinically relevant psychotropic interactions were classified as pharmacodynamic or pharmacokinetic using an interaction database. The first ranked (most important) interaction in each patient was selected with the following importance of categories in the database; recommended action > documentation > severity. Three levels (from low to high) within each category were used for ranking.

Results

From 2000 to 2016, psychotropic polypharmacy increased from 6.2 to 29.6%, potential inappropriate psychotropic substances was reduced from 17.9 to 11.3% and potential inappropriate psychotropic combinations increased from 7.8 to 27.9%. Changes in polypharmacy and combinations were predominantly associated with prescribing of anxiolytics-hypnotics. Sixty-three patients (16.3%) had psychotropic interactions in 2000 increasing to 146 patients (35.1%) in 2016. The increase in interactions was associated with prescribing of antidepressants. First ranked interactions, more than 60% of all interactions in both years, were increasingly pharmacodynamic, from 69.9 to 91.0%. Interactions in 2016 were associated with a lower level of recommended action and documentation, but not severity compared to 2000. The inappropriate prescribing of antipsychotics and antiepileptics was reduced in 2016 compared to 2000.

Conclusions

Using prescribing quality indicators we observed the importance of antidepressants and anxiolytics-hypnotics for inappropriate prescribing in 2016 while the role of antipsychotics and antiepileptics were reduced compared to 2000. A change to mainly pharmacodynamic interactions that lack good documentation was also observed. The present findings can be used for medical informatics-based approaches to address specific problems with prescribing, and prescribing quality indicators, in Norwegian nursing homes.

A comparison of potential psychiatric drug interactions from six drug interaction database programs

Harmful drug-drug interactions (DDI) frequently include psychiatric drugs. Drug interaction database programs are viewed as a primary tool to alert physicians of potential DDI, but may provide different results as there is no standard to define DDI. This study compared the category of potential DDI provided by 6 commercial drug interaction database programs (3 subscription, 3 open access) for 100 drug interaction pairs. The pairs involved 94 different drugs; 67 included a psychiatric and non-psychiatric drug, and 33 included two psychiatric drugs. The category assigned to the potential DDI by the 6 programs was compared using percent agreement and Fleiss' kappa interrater reliability measure. The overall percent agreement for the category of potential DDI for the 100 drug interaction pairs was 66%. The Fleiss kappa overall interrater agreement was fair. The kappa agreement was substantial for interaction pairs with any severe category rating, and fair for interaction pairs with any major category rating. The category of potential DDI for drug interaction pairs including psychiatric drugs often differs among drug interaction database programs. Modern technology allows easy access to several interaction database programs. When assistance from a drug interaction database program is needed, the physician should check more than one program.

Do user preferences align with human factors assessment scores of drug-drug interaction alerts?

This study aimed to assess drug-drug interaction alert interfaces and to examine the relationship between compliance with human factors principles and user-preferences of alerts. Three reviewers independently evaluated drug-drug interaction alert interfaces in seven electronic systems using the Instrument-for-Evaluating-Human-Factors-Principles-in-Medication-Related-Decision-Support-Alerts (I-MeDeSA). Fifty-three doctors and pharmacists completed a survey to rate the alert interfaces from best to worst and reported on liked and disliked features. Human factors compliance and user-preferences of alerts were compared. Statistical analysis revealed no significant association between I-MeDeSA scores and user-preferences. However, the strengths and weaknesses of drug-drug interaction alerts from users' perspectives were in-line with the human factors constructs evaluated by the I-MeDeSA. I-MeDeSA in its current form, is unable to identify alerts that are preferred by the users. The design principles assessed by I-MeDeSA appear to be sound, but its arbitrary allocation of points to each human factors construct may not reflect the relative importance that the end-users place on different aspects of alert design.

Automation to optimise physician treatment of individual patients: examples in psychiatry

There is widespread agreement by health-care providers, medical associations, industry, and governments that automation using digital technology could improve the delivery and quality of care in psychiatry, and reduce costs. Many benefits from technology have already been realised, along with the identification of many challenges. In this Review, we discuss some of the challenges to developing effective automation for psychiatry to optimise physician treatment of individual patients. Using the perspective of automation experts in other industries, three examples of automation in the delivery of routine care are reviewed: (1) effects of electronic medical records on the patient interview; (2) effects of complex systems integration on e-prescribing; and (3) use of clinical decision support to assist with clinical decision making. An increased understanding of the experience of automation from other sectors might allow for more effective deployment of technology in psychiatry.

A Case-Crossover-Based Screening Approach to Identifying Clinically Relevant Drug-Drug Interactions in Electronic Healthcare Data

We sought to develop a semiautomated screening approach using electronic healthcare data to identify drug-drug interactions (DDIs) that result in clinical outcomes. Using a case-crossover design with 30-day hazard and referent windows, we evaluated codispensed drugs (potential precipitants) in 7,801 patients who experienced rhabdomyolysis while on cytochrome P450 (CYP)3A4-metabolized statins and in 15,147 who experienced bleeding while on dabigatran. Estimates of direct associations between precipitant drugs and outcomes were used to adjust for bias and precipitants' direct effects. The P values were adjusted for multiple testing using the false discovery rate (FDR). From among 460 drugs codispensed with statins, 1 drug (clarithromycin) generated an alert (adjusted odds ratio (OR) 5.83, FDR < 0.05). From among 485 drugs codispensed with dabigatran, 2 drugs (naproxen and enoxaparin, ORs 2.50 and 2.75; FDR < 0.05) generated an alert. All three signals reflected known pharmacologic interactions, confirming the potential of case-crossover-based approaches for DDI screening in electronic healthcare data.

Navigating the Minefield of QTc Interval-Prolonging Therapy in Nursing Facility Residents

BACKGROUND

The exponential increase in the number of medications associated with clinically important prolongation of the heart rate-corrected QT interval (QTc) places older adults at increased risk of arrhythmias including life-threatening torsade de pointes (TdP) and sudden death. Risk factors, other than age older than 65 years and female sex, include multiple concurrent drugs that prolong QTc and a variety of underlying predisposing conditions. Although electronic medical records and pharmacy dispensing systems can alert clinicians to the risk of QTc-prolonging therapy, more than 95% of safety alerts are overridden, and many systems have deactivated QTc drug interaction alerts. The clinical consequences, magnitude of the effect, mitigation strategies, and recommended monitoring are not well defined for nursing facility (NF) residents.

DESIGN

Narrative review.

SETTING

NFs in the United States.

PARTICIPANTS

NF residents.

RESULTS

Medications known to prolong QTc include selected anti-infectives, antidepressants, urinary anticholinergics, antipsychotics, and cholinesterase inhibitors (eg, donepezil), used commonly in NFs. Drug-drug interactions are a risk when adding a medication that exaggerates the effect or inhibits the metabolism of a QTc-prolonging medication. The vast majority of patients in whom TdP is induced by noncardiac drugs have risk factors that are easily identifiable.

CONCLUSIONS

Recommendations are provided to improve standardization and use of drug interaction alerts, evaluate the risk of QTc-prolonging drugs in older adults receiving generally lower doses, validate a QTc risk score addressing complex multimorbidity, garner evidence to guide clinical decision making, avail NFs of access to electrocardiograms and interpretive recommendations, and develop standards of practice for hosting risk discussions with residents and their families. J Am Geriatr Soc, 1-8, 2019.

Identifying Common Methods Used by Drug Interaction Experts for Finding Evidence About Potential Drug-Drug Interactions: Web-Based Survey

Background

Preventing drug interactions is an important goal to maximize patient benefit from medications. Summarizing potential drug-drug interactions (PDDIs) for clinical decision support is challenging, and there is no single repository for PDDI evidence. Additionally, inconsistencies across compendia and other sources have been well documented. Standard search strategies for complete and current evidence about PDDIs have not heretofore been developed or validated.

Objective

This study aimed to identify common methods for conducting PDDI literature searches used by experts who routinely evaluate such evidence.

Methods

We invited a convenience sample of 70 drug information experts, including compendia editors, knowledge-base vendors, and clinicians, via emails to complete a survey on identifying PDDI evidence. We created a Web-based survey that included questions regarding the (1) development and conduct of searches; (2) resources used, for example, databases, compendia, search engines, etc; (3) types of keywords used to search for the specific PDDI information; (4) study types included and excluded in searches; and (5) search terms used. Search strategy questions focused on 6 topics of the PDDI information—(1) that a PDDI exists; (2) seriousness; (3) clinical consequences; (4) management options; (5) mechanism; and (6) health outcomes.

Results

Twenty participants (response rate, 20/70, 29%) completed the survey. The majority (17/20, 85%) were drug information specialists, drug interaction researchers, compendia editors, or clinical pharmacists, with 60% (12/20) having >10 years’ experience. Over half (11/20, 55%) worked for clinical solutions vendors or knowledge-base vendors. Most participants developed (18/20, 90%) and conducted (19/20, 95%) search strategies without librarian assistance. PubMed (20/20, 100%) and Google Scholar (11/20, 55%) were most commonly searched for papers, followed by Google Web Search (7/20, 35%) and EMBASE (3/20, 15%). No respondents reported using Scopus. A variety of subscription and open-access databases were used, most commonly Lexicomp (9/20, 45%), Micromedex (8/20, 40%), Drugs@FDA (17/20, 85%), and DailyMed (13/20, 65%). Facts and Comparisons was the most commonly used compendia (8/20, 40%). Across the 6 attributes of interest, generic drug name was the most common keyword used. Respondents reported using more types of keywords when searching to identify the existence of PDDIs and determine their mechanism than when searching for the other 4 attributes (seriousness, consequences, management, and health outcomes). Regarding the types of evidence useful for evaluating a PDDI, clinical trials, case reports, and systematic reviews were considered relevant, while animal and in vitro data studies were not.

Conclusions

This study suggests that drug interaction experts use various keyword strategies and various database and Web resources depending on the PDDI evidence they are seeking. Greater automation and standardization across search strategies could improve one’s ability to identify PDDI evidence. Hence, future research focused on enhancing the existing search tools and designing recommended standards is needed.

An Exploration of the Terminology of Clinical Cognition and Reasoning

We hypothesize that the functionality of electronic health records could be improved with the addition of formal representations of clinicians' cognitive processes, including such things as the interpretation and synthesis of patient findings and the rational for diagnostic and therapeutic decisions. We carried out a four-phase analysis of clinical case studies to characterize how such processes are represented through relationships between clinical terms. The result is an terminology of 26 relationships that were validated against published clinical cases with 85.4% interrater reliability. We believe that capturing patient-specific information with these relationships can lead to improvements in clinical decision support systems, information retrieval and learning health systems.

Evaluation of Clinical Relevance of Drug-Drug Interaction Alerts Prior to Implementation

INTRODUCTION

Drug-drug interaction (DDI) alerts are often implemented in the hospital computerized provider order entry (CPOE) systems with limited evaluation. This increases the risk of prescribers experiencing too many irrelevant alerts, resulting in alert fatigue. In this study, we aimed to evaluate clinical relevance of alerts prior to implementation in CPOE using two common approaches: compendia and expert panel review.

METHODS

After generating a list of hypothetical DDI alerts, that is, alerts that would have been triggered if DDI alerts were operational in the CPOE, we calculated the agreement between multiple drug interaction compendia with regards to the severity of these alerts. A subset of DDI alerts (n = 13), with associated patient information, were presented to an expert panel to reach a consensus on whether each alert should be included in the CPOE.

RESULTS

There was poor agreement between compendia in their classifications of DDI severity (Krippendorff's α: 0.03; 95% confidence interval: -0.07 to 0.14). Only 10% of DDI alerts were classed as severe by all compendia. On the other hand, the panel reached consensus on 12 of the 13 alerts that were presented to them regarding whether they should be included in the CPOE.

CONCLUSION

Using an expert panel and allowing them to discuss their views openly likely resulted in high agreement on what alerts should be included in a CPOE system. Presenting alerts in the context of patient cases allowed panelists to identify the conditions under which alerts were clinically relevant. The poor agreement between compendia suggests that this methodology may not be ideal for the evaluation of DDI alerts. Performing preimplementation review of DDI alerts before they are enabled provides an opportunity to minimize the risk of alert fatigue before prescribers are exposed to false-positive alerts.

Warnings for drug-drug interactions in consumer medication information provided by community pharmacies

OBJECTIVES

In 2006, the U.S. Food and Drug Administration (FDA) issued a draft guidance for pharmacies to provide consumer medication information (CMI) to patients receiving prescription medications. The objective of this study was to evaluate CMI leaflets provided by community pharmacies for accuracy and completeness regarding drug-drug interactions (DDIs).

METHODS

CMI leaflets were obtained for 3 commonly prescribed medications (azithromycin, ciprofloxacin, and simvastatin) from 14 community pharmacies that are part of 6 chain organizations that operate in southern Arizona. Three to 4 salient interacting medications for each leaflet medication were identified with the use of 2 well recognized drug compendia. The content of the DDI information in the leaflets was evaluated for completeness. The font size and reading level of each leaflet were assessed as well.

RESULTS

The CMI provided by 14 pharmacies appeared to be produced by 2 information vendors, Wolters Kluwer and First Databank. This was evident based on the identical wording and attribution (e.g., copyright statements) on the leaflets. The CMI from First Databank mentioned 5 of the 11 previously identified interactions with the target medications, although 1 chain in this group chose not to print the DDI section at all and as a result scored 0. The CMI developed by Wolters Kluwer mentioned only 2 of the 11 identified DDIs. The average reading grade level for First Databank leaflets was 10.6 (SD 2.87), and the reading level for the CMI from Wolters Kluwer was 5.0 (SD 1.02). The font sizes varied from 8 to 12 points; FDA recommends that the information be printed in 12-point size or larger.

CONCLUSION

Community pharmacies appear to be distributing CMI leaflets with limited warnings about serious and well known DDIs. The results of this study suggest that consumers are not being informed through the CMI about important known DDIs.

Clinical Utility of Definitive Drug⁻Drug Interaction Testing in Primary Care

Drug–drug interactions (DDIs) are a leading cause of morbidity and mortality. New tools are needed to improve identification and treatment of DDIs. We conducted a randomized controlled trial to assess the clinical utility of a new test to identify DDIs and improve their management. Primary care physicians (PCPs) cared for simulated patients presenting with DDI symptoms from commonly prescribed medications and other ingestants. All physicians, in either control or one of two intervention groups, cared for six patients over two rounds of assessment. Intervention physicians were educated on the DDI test and given access to these test reports when caring for their patients in the second round. At baseline, we saw no significant differences in making the DDI diagnosis (p = 0.071) or DDI-related treatment (p = 0.640) between control and intervention arms. By round two, providers who accessed the DDI test performed significantly better in making the DDI diagnosis (+41.6%) and performing DDI-specific treatment (+12.2%) than in the previous round, and were 9.8 and 20.4 times more likely to diagnose and identify the DDI (p < 0.001 for all). The introduction of a definitive DDI test significantly increased identification, appropriate management, and counseling of DDIs among PCPs, which has the potential to improve clinical care.

Clinical Decision Support Systems for Drug Allergy Checking: Systematic Review

BACKGROUND

Worldwide, the burden of allergies-in particular, drug allergies-is growing. In the process of prescribing, dispensing, or administering a drug, a medication error may occur and can have adverse consequences; for example, a drug may be given to a patient with a documented allergy to that particular drug. Computerized physician order entry (CPOE) systems with built-in clinical decision support systems (CDSS) have the potential to prevent such medication errors and adverse events.

OBJECTIVE

The aim of this review is to provide a comprehensive overview regarding all aspects of CDSS for drug allergy, including documenting, coding, rule bases, alerts and alert fatigue, and outcome evaluation.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed as much as possible and searches were conducted in 5 databases using CPOE, CDSS, alerts, and allergic or allergy as keywords. Bias could not be evaluated according to PRISMA guidelines due to the heterogeneity of study types included in the review.

RESULTS

Of the 3160 articles considered, 60 met the inclusion criteria. A further 9 articles were added based on expert opinion, resulting in a total of 69 articles. An interrater agreement of 90.9% with a reliability Κ=.787 (95% CI 0.686-0.888) was reached. Large heterogeneity across study objectives, study designs, study populations, and reported results was found. Several key findings were identified. Evidence of the usefulness of clinical decision support for drug allergies has been documented. Nevertheless, there are some important problems associated with their use. Accurate and structured documenting of information on drug allergies in electronic health records (EHRs) is difficult, as it is often not clear to healthcare providers how and where to document drug allergies. Besides the underreporting of drug allergies, outdated or inaccurate drug allergy information in EHRs poses an important problem. Research on the use of coding terminologies for documenting drug allergies is sparse. There is no generally accepted standard terminology for structured documentation of allergy information. The final key finding is the consistently reported low specificity of drug allergy alerts. Current systems have high alert override rates of up to 90%, leading to alert fatigue. Important challenges remain for increasing the specificity of drug allergy alerts. We found only one study specifically reporting outcomes related to CDSS for drug allergies. It showed that adverse drug events resulting from overridden drug allergy alerts do not occur frequently.

CONCLUSIONS

Accurate and comprehensive recording of drug allergies is required for good use of CDSS for drug allergy screening. We found considerable variation in the way drug allergy are recorded in EHRs. It remains difficult to reduce drug allergy alert overload while maintaining patient safety as the highest priority. Future research should focus on improving alert specificity, thereby reducing override rates and alert fatigue. Also, the effect on patient outcomes and cost-effectiveness should be evaluated.

Potential Drug-Drug Interactions in a Cohort of Elderly, Polymedicated Primary Care Patients on Antithrombotic Treatment

INTRODUCTION

Drug-drug interactions (DDIs) are an important risk factor for adverse drug reactions. Older, polymedicated patients are particularly affected. Although antithrombotics have been detected as high-risk drugs for DDIs, data on older patients exposed to them are scarce.

METHODS

Baseline data of 365 IDrug study outpatients (≥ 60 years, use of an antithrombotic and one or more additional long-term drug) were analyzed regarding potential drug-drug interactions (pDDIs) with a clinical decision support system. Data included prescription and self-medication drugs.

RESULTS

The prevalence of having one or more pDDI was 85.2%. The median number of alerts per patient was three (range 0-17). For 58.4% of the patients, potential severe/contraindicated interactions were detected. Antiplatelets and non-steroidal anti-inflammatory drugs (NSAIDs) showed the highest number of average pDDI alert involvements per use (2.9 and 2.2, respectively). For NSAIDs, also the highest average number of severe/contraindicated alert involvements per use (1.2) was observed. 91.8% of all pDDI involvements concerned the 25 most frequently used drug classes. 97.5% of the severe/contraindicated pDDIs were attributed to only nine different potential clinical manifestations. The most common management recommendation for severe/contraindicated pDDIs was to intensify monitoring. Number of drugs was the only detected factor significantly associated with increased number of pDDIs (p < 0.001).

CONCLUSION

The findings indicate a high risk for pDDIs in older, polymedicated patients on antithrombotics. As a consequence of patients' frequently similar drug regimens, the variety of potential clinical manifestations was small. Awareness of these pDDI symptoms and the triggering drugs as well as patients' self-medication use may contribute to increased patient safety.

Evaluation of Potential Drug-Drug Interactions With Direct Oral Anticoagulants in a Large Urban Hospital

OBJECTIVE

The aim of this study is to assess patterns of potential drug-drug interactions (DDIs) with direct oral anticoagulants (DOACs) in an inpatient hospital setting.

METHODS

A retrospective chart review was conducted at the Brookdale University Hospital and Medical Center (BUHMC) from January 2014 to November 2016. All adult patients admitted to the BUHMC who were treated with a DOAC for at least 3 days were screened. Among them, those who received selected interacting drugs at any time during the course of DOAC therapy were included in this study.

RESULTS

This study included 165 patients with an average of 73 years (standard deviation [SD] = 12.3) and 233 cases. The most commonly used concomitant drug with a DOAC was aspirin (58%), followed by amiodarone (16%) and P2Y₁₂ inhibitors (11%). The combined use of dual antiplatelet therapy and a DOAC was identified in 18 (6%) cases. Approximately one-third of the cases encountered were classified as the "avoidance" category.

CONCLUSIONS

Despite computerized DDI alerts, potentially significant DDIs with DOACs still occur. While the present study provides insight into the current patterns of DDIs, further studies are needed to evaluate clinical outcomes of the potential DDIs with DOACs in practice.

An Investigation of Drug-Drug Interaction Alert Overrides at a Pediatric Hospital

OBJECTIVES

Drug-drug interactions (DDIs) can result in patient harm. DDI alerts are intended to help prevent harm; when the majority of alerts presented to providers are being overridden, their value is diminished. Our objective was to evaluate the overall rates of DDI alert overrides and how rates varied by specialty, clinician type, and patient complexity.

METHODS

A retrospective study of DDI alert overrides that occurred during 2012 and 2013 within the inpatient setting described at the medication-, hospital-, provider-, and patient encounter-specific levels was performed at an urban, quaternary-care, pediatric hospital.

RESULTS

There were >41 000 DDI alerts presented to clinicians; ∼90% were overridden. The 5 DDI pairs that were most frequently presented and overridden included the following: potassium chloride-spironolactone, methadone-ondansetron, ketorolac-ibuprofen, cyclosporine-fluconazole, and potassium chloride-enalapril, each with an alert override rate of ≥0.89. Override rates across provider groups ranged between 0.84 and 0.97. In general, patients with high complexity had a higher frequency of alert overrides, but the rates of alert overrides for each DDI pairing did not differ significantly.

CONCLUSIONS

High rates of DDI alert overrides occur across medications, provider groups, and patient encounters. Methods to decrease DDI alerts which are likely to be overridden exist, but it is also clear that more robust and intelligent tools are needed. Characteristics exist at the medication, hospital, provider, and patient levels that can be used to help specialize and enhance information transmission.

Updating the Evidence of the Interaction Between Clopidogrel and CYP2C19-Inhibiting Selective Serotonin Reuptake Inhibitors: A Cohort Study and Meta-Analysis

INTRODUCTION

We previously found that patients who initiate clopidogrel while treated with a cytochrome P450 (CYP) 2C19-inhibiting selective serotonin reuptake inhibitor (SSRI) have a higher risk of subsequent ischemic events than patients treated with other SSRIs. It is not known whether initiating an inhibiting SSRI while treated with clopidogrel will also increase risk of ischemic events.

OBJECTIVE

The aim of this study was to assess clinical outcomes following initiation of a CYP2C19-inhibiting SSRI versus initiation of other SSRIs among patients treated with clopidogrel and to update existing evidence on the clinical impact of clopidogrel-SSRI interaction.

METHODS

Using five US databases (1998-2013), we conducted a cohort study of clopidogrel initiators who encountered treatment with SSRI during their clopidogrel therapy. Patients were matched by propensity score (PS) and followed for as long as they were exposed to both clopidogrel and index SSRI group. Outcomes were a composite ischemic event (myocardial infarction, ischemic stroke, or a revascularization procedure, whichever came first) and a composite major bleeding event (gastrointestinal bleed or hemorrhagic stroke, whichever came first). Results were combined via random-effects meta-analysis with previous evidence from subjects initiating clopidogrel while on SSRI therapy.

RESULTS

The PS-matched cohort comprised 2346 clopidogrel users starting CYP2C19-inhibiting SSRI therapy and 16,115 starting other SSRIs (mean age 61 years; 59% female). Compared with those treated with a non-inhibiting SSRI, the hazard ratio (HR) for patients treated with a CYP2C19-inhibiting SSRI was 1.07 (95% confidence interval [CI] 0.82-1.40) for the ischemic outcome and 1.00 (95% CI 0.42-2.36) for bleeding. The pooled estimates were 1.11 (95% CI 1.01-1.22) for ischemic events and 0.80 (95% CI 0.55-1.18) for bleeding.

CONCLUSIONS

We observed similar estimates of association between the two studies. The updated evidence still indicates a small decrease in clopidogrel effectiveness associated with concomitant exposure to clopidogrel and CYP2C19-inhibiting SSRIs.

Aspects influencing patients' preferences for the management of drug-drug interactions: A focus group study

OBJECTIVE

The management of drug-drug interactions (DDIs) involves a complex risk-benefit assessment, in which patients' preferences should be taken into account. The aim of this study was to examine the aspects influencing patients' preferences with regard to DDI management options.

METHODS

A qualitative study consisting of five focus groups with patients chronically using cardiovascular drugs was conducted. Key questions concerned preferences regarding DDI management options for a provided fictitious DDI. Thematic analysis of the verbatim transcripts was performed.

RESULTS

Despite their limited knowledge with respect to DDIs, patients easily chose a management option for the presented DDI. When additional information was provided, preferences showed to be fluid. Ten interdependent aspects influencing preferences were derived from patients' argumentations: risk perception, fear, acceptance of uncertainty, openness to change, willingness to take risk, trust in health care professional, financial & practical burdens, health condition, experience, and knowledge & assumptions.

CONCLUSION

Patients' preferences regarding DDI management options were often determined by provided information. Preferences were dependent on an interplay of diverse aspects.

PRACTICE IMPLICATIONS

Tailored provision of information and individualized counseling is needed for active patient involvement in DDI decision making.

Clinical Decision Support and Optional Point of Care Testing of Renal Function for Safe Use of Antibiotics in Elderly Patients: A Retrospective Study in Community Pharmacy Practice

Objective

The aim was to investigate the management of drug therapy alerts on safe use of antibiotics in elderly patients with (potential) renal impairment and the contribution of optional creatinine point of care testing (PoCT) in community pharmacy practice.

Methods

Community pharmacists used a clinical decision support system (CDSS) for seven antibiotics. Alerts were generated during prescription processing in the case of previously registered renal impairment and when no information on renal function was available for patients aged 70 and over. Pharmacists could perform PoCT when renal function could not be retrieved from other health care professionals. Actions were registered in the CDSS. A retrospective descriptive analysis of alert management, performed PoCT and medication dispensing histories was performed.

Results

A total of 351 pharmacists registered the management of 88,391 alerts for 64,763 patients. For 68,721 alerts (77.7%), the pharmacist retrieved a renal function above the threshold for intervention. 1.7% of the alerts (n = 1532) led to a prescription modification because of renal impairment; in 3.0% of the alerts (n = 2631), the patient had renal impairment, but the pharmacist judged that no intervention was needed. Pharmacists performed 1988 PoCTs (2.2% of the alerts), which led to 15 prescription modifications (0.8% of the PoCT).

Conclusion

Community pharmacists performed CDSS-based interventions to prevent potentially inappropriate (dosing of) antibiotics in elderly patients with renal impairment. Pharmacists were well able to retrieve information on renal function, using PoCT in a limited number of cases. The intervention rate could be greatly increased by better registration of information on renal function. Performing PoCT seems especially worthwhile in the highest age groups.

Nonmodal Clinical Decision Support and Antimicrobial Restriction Effects on Rates of Fluoroquinolone Use in Uncomplicated Infections

BACKGROUND

Medication alert overrides remain persistently high over the past decade, influenced by factors such as "alert fatigue" and lack of provider acceptance.

OBJECTIVE

We compared the aggregate rate of fluoroquinolone (FQ) prescribing for the treatment of acute sinusitis, acute bronchitis, and uncomplicated urinary tract infections (UTIs) in adult inpatients prior to (historical control group) and after (prospective intervention group) implementation of a program requiring indication when ordering FQ antibiotics in combination with a nonmodal best-practice alert regarding the latest U.S. Food and Drug Administration (FDA) recommendations. We then compared rates of prescribing among provider type, severity of infection, and patient age.

METHODS

Qualified orders were defined as new FQ orders for acute sinusitis, acute bronchitis, and uncomplicated UTI for adult inpatients between July 2016 through September 2016 (control) or November 2016 through January 2017 (intervention). The primary endpoint was a provider-initiated FQ order for a target indication. Secondary endpoints included FQ orders by provider type and patient age. Rates of FQ use among the target indications were compared between groups by chi-square test of independence with Yates' correction in the analysis of the primary endpoint and Fisher's exact test for secondary endpoints.

RESULTS

FQ prescribing for acute bronchitis, and uncomplicated UTI occurred at a rate of 86/350 (24.6%) and 62/394 (15.7%) in the control and experimental groups, respectively (p = 0.0035). No patients receiving FQ qualified for a diagnosis of acute sinusitis.

CONCLUSION

A program combining FQ restriction in combination with nonmodal messaging may have decreased the rate of prescribing for acute bronchitis and uncomplicated UTI, although the contributions of each individual element could not be rigorously assessed.

High-priority and low-priority drug-drug interactions in different international electronic health record systems: A comparative study

OBJECTIVES

To investigate whether alert warnings for high-priority and low-priority drug-drug interactions (DDIs) were present in five international electronic health record (EHR) systems, to compare and contrast the severity level assigned to them, and to establish the proportion of alerts that were overridden.

METHODS

We conducted a comparative, retrospective, multinational study using a convenience sample of 5 EHRs from the U.S., U.K., Republic of Korea and Belgium.

RESULTS

Of the 15 previously defined, high-priority, class-based DDIs, alert warnings were found to exist for 11 in both the Korean and UK systems, 9 in the Belgian system, and all 15 in the two US systems. The specific combinations that were included in these class-based DDIs varied considerably in number, type and level of severity amongst systems. Alerts were only active for 8.4% (52/619) and 52.4% (111/212) of the specific drug-drug combinations contained in the Belgian and UK systems, respectively. Hard stops (not possible to override) existed in the US and UK systems only. The override rates for high-priority alerts requiring provider action ranged from 56.7% to 83.3%. Of the 33 previously defined low-priority DDIs, active alerts existed only in the US systems, for three class-based DDIs. The majority were non-interruptive.

CONCLUSIONS

Alert warnings existed for most of the high-priority DDIs in the different EHRs but overriding them was easy in most of the systems. In addition to validating the high- and low-priority DDIs, this study reported a lack of standardization in DDI levels across different international knowledge bases.

Emergency Department Provider Perspectives on Benzodiazepine-Opioid Coprescribing: A Qualitative Study

OBJECTIVE

Benzodiazepines and opioids are prescribed simultaneously (i.e., "coprescribed") in many clinical settings, despite guidelines advising against this practice and mounting evidence that concomitant use of both medications increases overdose risk. This study sought to characterize the contexts in which benzodiazepine-opioid coprescribing occurs and providers' reasons for coprescribing.

METHODS

We conducted focus groups with emergency department (ED) providers (resident and attending physicians, advanced practice providers, and pharmacists) from three hospitals using semistructured interviews to elicit perspectives on benzodiazepine-opioid coprescribing. Discussions were audio-recorded and transcribed. We performed qualitative content analysis of the resulting transcripts using a consensual qualitative research approach, aiming to identify priority categories that describe the phenomenon of benzodiazepine-opioid coprescribing.

RESULTS

Participants acknowledged coprescribing rarely and reluctantly and often provided specific discharge instructions when coprescribing. The decision to coprescribe is multifactorial, often isolated to specific clinical and situational contexts (e.g., low back pain, failed solitary opioid therapy) and strongly influenced by a provider's beliefs about the efficacy of combination therapy. The decision to coprescribe is further influenced by a self-imposed pressure to escalate care or avoid hospital admission. When considering potential interventions to reduce the incidence of coprescribing, participants opposed computerized alerts but were supportive of a pharmacist-assisted intervention. Many providers found the process of participating in peer discussions on prescribing habits to be beneficial.

CONCLUSIONS

In this qualitative study of ED providers, we found that benzodiazepine-opioid coprescribing occurs in specific clinical and situational contexts, such as the treatment of low back pain or failed solitary opioid therapy. The decision to coprescribe is strongly influenced by a provider's beliefs and by self-imposed pressure to escalate care or avoid admission.

Variation in high-priority drug-drug interaction alerts across institutions and electronic health records

Objective: The United States Office of the National Coordinator for Health Information Technology sponsored the development of a “high-priority” list of drug-drug interactions (DDIs) to be used for clinical decision support. We assessed current adoption of this list and current alerting practice for these DDIs with regard to alert implementation (presence or absence of an alert) and display (alert appearance as interruptive or passive).

Materials and methods: We conducted evaluations of electronic health records (EHRs) at a convenience sample of health care organizations across the United States using a standardized testing protocol with simulated orders.

Results: Evaluations of 19 systems were conducted at 13 sites using 14 different EHRs. Across systems, 69% of the high-priority DDI pairs produced alerts. Implementation and display of the DDI alerts tested varied between systems, even when the same EHR vendor was used. Across the drug pairs evaluated, implementation and display of DDI alerts differed, ranging from 27% (4/15) to 93% (14/15) implementation.

Discussion: Currently, there is no standard of care covering which DDI alerts to implement or how to display them to providers. Opportunities to improve DDI alerting include using differential displays based on DDI severity, establishing improved lists of clinically significant DDIs, and thoroughly reviewing organizational implementation decisions regarding DDIs.

Conclusion: DDI alerting is clinically important but not standardized. There is significant room for improvement and standardization around evidence-based DDIs.

Alert override as a habitual behavior - a new perspective on a persistent problem

Quantifying alert override has been the focus of much research in health informatics, with override rate traditionally viewed as a surrogate inverse indicator for alert effectiveness. However, relying on alert override to assess computerized alerts assumes that alerts are being read and determined to be irrelevant by users. Our research suggests that this is unlikely to be the case when users are experiencing alert overload. We propose that over time, alert override becomes habitual. The override response is activated by environmental cues and repeated automatically, with limited conscious intention. In this paper we outline this new perspective on understanding alert override. We present evidence consistent with the notion of alert override as a habitual behavior and discuss implications of this novel perspective for future research on alert override, a common and persistent problem accompanying decision support system implementation.

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.

Drug-drug interactions and their harmful effects in hospitalised patients: a systematic review and meta-analysis

PURPOSE

Drug-drug interactions (DDIs) are often avoidable and, if undetected, can lead to patient harm. This review aimed to determine the prevalence of potential DDIs (pDDIs), clinically relevant DDIs (DDIs that could lead to measurable patient harm, taking into account the patient's individual clinical profile) and DDIs that resulted in actual patient harm during hospitalisation.

METHOD

Four databases were scanned for English papers published from 2000 to 2016. Papers that reported prevalence of DDIs in the outpatient setting, at admission or discharge, involving only specific drugs, or in specific disease populations or age groups were excluded.

RESULTS

Twenty-seven papers met the inclusion criteria and were graded for quality using the Critical Appraisal Skills Programme (CASP) cohort study checklist. Ten papers were rated as 'poor', 14 as 'fair' and only three papers as 'good'. Overall, the meta-analysis revealed that 33% of general patients and 67% of intensive care patients experienced a pDDI during their hospital stay. It was not possible to determine the prevalence of clinically relevant DDIs or DDIs that resulted in actual patient harm as data on these categories were limited. Of the very few studies that reported on harm, only a small proportion of DDIs were found to have resulted in actual patient harm.

CONCLUSIONS

Standardisation of DDI definitions and research methods are required to allow meaningful prevalence rates to be obtained and compared. Studies that go further than measuring pDDIs are critically needed to determine the impact of DDIs on patient safety.

E-Scripts and Cell Phones: A Blessing or Curse?

E-scripts have been used as part of computerized provider order entry implementation for several years now, particularly with the passage of the American Recovery and Reinvestment Act, Meaningful Use, the Health Information Portability and Accountability Act, the Health Information Technology for Economic and Clinical Health Act, and other laws and regulations. This case study seeks to focus on 2 specific aspects of the effect of increasing electronic technology within health care: e-prescriptions and cell phones or smartphones.