Evaluating the Use of a CPOE for Chemotherapy Protocols

Chemotherapy drugs are one of the most common causes of serious and fatal medication errors, especially during prescribing, where computerized physician order entry (CPOE) take on importance. This study proposes the description of the post-implementation status of a CPOE in a highly specialized hospital between January and June 2018, among patients older than 18 years. Results: a total of 8835 protocols were indicated using the specific CPOE (93% use rate over all protocols) 91% completed the administration, 1.2% were rejected by pharmacy, and 6.8% was canceled. The most frequent cause of rejection by pharmacy and cancellation by oncologist was an inadequate dose. Most of the protocols indicated using the CPOE implemented, with a reject by pharmacy rate of 1.2%, indicates the utility of CPOE as an error prevention strategy.

Improving thiamine prescribing at an academic hospital network using the computerized provider order entry system: a cohort study

BACKGROUND

Oral thiamine therapy is frequently prescribed to patients at risk for thiamine deficiency despite recommendations emphasizing the need for high doses of parenteral thiamine to reverse brain thiamine deficits. We evaluated the effect of changes to the computerized provider order entry system on the proportion of prescriptions for parenteral thiamine treatment (primary outcome) and dosages prescribed (secondary outcome) within our academic hospital network.

METHODS

We obtained data from the pharmacy information system recording thiamine prescribed to inpatients at University Health Network hospitals (Toronto, Ontario) before (Jan. 1, 2010, to Dec. 31, 2011) and after (Nov. 21, 2013, to Apr. 30, 2017) changes to the computerized provider order entry system promoting the use of higher dosages (≥ 200 mg) of parenterally administered thiamine. Patients receiving thiamine as part of total parenteral nutrition were excluded from analyses, as thiamine prescribing was automated and unlikely to be affected by the intervention.

RESULTS

A total of 6105 thiamine prescriptions were written for 2907 patients before the intervention and 12 787 thiamine prescriptions for 8032 patients after the intervention. The proportion of prescriptions for parenteral treatment increased from 55.5% (3386/6105) to 92.5% (11 829/12 787) after the intervention (p < 0.001). Increases in prescribing of parenteral thiamine treatment were sustained or enhanced across the 3.4-year observation period and were realized across all hospital services. Prescriptions for higher dosages of thiamine increased from 1.1% (65/6105) to 61.4% (7845/12 787) after the intervention (p < 0.001).

INTERPRETATION

Changes to the computerized provider order entry system were associated with sustained increases in the proportion of prescriptions for high-dose parenteral thiamine therapy. Similar approaches may be leveraged to align prescriber behaviour with well-accepted practice parameters in other areas of medicine.

Exploring Different Approaches in Measuring EHR-based Adherence to Best Practice - A Case Study with Order Sets and Associated Outcomes

In connection with a recent enterprise-wide rollout of a new electronic health record, Intermountain Healthcare is investing significant effort in building a central library of best-practice order sets. These order sets represent best practice guidelines for specific clinical scenarios and are deployed with the intent of standardizing care, reducing variation, and consistently delivering good clinical outcomes to the populations we serve. The importance of measuring their use and the level to which caregivers adhere to these standards becomes an important factor in understanding and characterizing the impact that they deliver. Notwithstanding the importance of these metrics, well- defined methods for measuring adherence to a given clinical guideline as delivered through an order set are not fully characterized in the medical literature. In this paper, we describe initial efforts at measuring compliance to a defined 'best practice' standard by means of content utilization analysis, a calculated adherence model, and relevant clinical key performance indicators. The degree to which specified clinical outcomes vary across these measurement models are compared for a group of order sets tied to treating coronary artery bypass graft patients and heart failure patients. While the patterns derived from this analysis show some uncertainty, more granular methods that look at line-item, or 'order level' detail reveal more significant differences in the corresponding set of outcomes than higher-level adherence surrogates.

Technology Implementation and Associated Pharmacy Interruptions

This study focuses on interruptions in an inpatient pharmacy setting and the impact of CPOE implementation on the types, frequency, and duration of interruptions. A cross-sectional observation study of pharmacy employees in an inpatient pharmacy was conducted. The independent variables included day of week, time of day, job position of the person interrupted, and description of each interruption. A total of 552 interruptions were observed with a mean frequency of 10.6 interruptions per hour lasting a mean (SD) duration of 1.34 (1.43) minutes. Incoming calls were the most frequent interruption type across all phases. Pharmacy employees spend almost a quarter of their time on interruptions, and pharmacists have longer interruptions than technicians. Immediately after CPOE implementation, durations tend to be one-and-a-half times longer than before. CPOE implementation did not affect the frequency of interruptions. Recommendations included redesign of work processes and job responsibilities.

A Potential Answer to the Alert Override Riddle: Using Patient Attributes to Predict False Positive Alerts

Electronic health records (EHRs) use alerts to help prevent medical errors, yet clinicians override many of these alerts due to desensitization from constant exposure (alert fatigue). We hypothesize that a clinician might override an alert warning about the dangers of a treatment if the patient's health is so poor that the treatment is worth the risk or if a patient's health suggests the treatment is not needed. We used logistic regression with general estimating equations to determine if the Early Warning Score (EWS), a measurement used to predict critical care need, could be used to predict alert overrides. EWS was a significant predictor of overrides for three alerts. Although EWS could not predict overrides for all alert rules, these results suggest that EWS may be helpful for some alerts, but that additional EHR data will be needed for predicting override behavior to a useful degree.

When order sets do not align with clinician workflow: assessing practice patterns in the electronic health record

BACKGROUND

Order sets are widely used tools in the electronic health record (EHR) for improving healthcare quality. However, there is limited insight into how well they facilitate clinician workflow. We assessed four indicators based on order set usage patterns in the EHR that reflect potential misalignment between order set design and clinician workflow needs.

METHODS

We used data from the EHR on all orders of medication, laboratory, imaging and blood product items at an academic hospital and an itemset mining approach to extract orders that frequently co-occurred with order set use. We identified the following four indicators: infrequent ordering of order set items, rapid retraction of medication orders from order sets, additional a la carte ordering of items not included in order sets and a la carte ordering of items despite being listed in the order set.

RESULTS

There was significant variability in workflow alignment across the 11 762 order set items used in the 77 421 inpatient encounters from 2014 to 2017. The median ordering rate was 4.1% (IQR 0.6%-18%) and median medication retraction rate was 4% (IQR 2%-10%). 143 (5%) medications were significantly less likely while 68 (3%) were significantly more likely to be retracted than if the same medication was ordered a la carte. 214 (39%) order sets were associated with least one additional item frequently ordered a la carte and 243 (45%) order sets contained at least one item that was instead more often ordered a la carte.

CONCLUSION

Order sets often do not align with what clinicians need at the point of care. Quantitative insights from EHRs may inform how order sets can be optimised to facilitate clinician workflow.

Using a Machine Learning System to Identify and Prevent Medication Prescribing Errors: A Clinical and Cost Analysis Evaluation

BACKGROUND

Clinical decision support (CDS) alerting tools can identify and reduce medication errors. However, they are typically rule-based and can identify only the errors previously programmed into their alerting logic. Machine learning holds promise for improving medication error detection and reducing costs associated with adverse events. This study evaluates the ability of a machine learning system (MedAware) to generate clinically valid alerts and estimates the cost savings associated with potentially prevented adverse events.

METHODS

Alerts were generated retrospectively by the MedAware system on outpatient data from two academic medical centers between 2009 and 2013. MedAware alerts were compared to alerts in an existing CDS system. A random sample of 300 alerts was selected for medical record review. Frequency and severity of potential outcomes of alerted medication errors of medium and high clinical value were estimated, along with associated health care costs of these potentially prevented adverse events.

RESULTS

A total of 10,668 alerts were generated. Overall, 68.2% of MedAware alerts would not have been generated by the existing CDS system. Ninety-two percent of a random sample of the chart-reviewed alerts were accurate based on structured data available in the record, and 79.7% were clinically valid. Estimated cost of adverse events potentially prevented in an outpatient setting was more than $60 per drug alert and $1.3 million when extrapolating study findings to the full patient population.

CONCLUSION

A machine learning system identified clinically valid medication error alerts that might otherwise be missed with existing CDS systems. Estimates show potential for cost savings associated with potentially prevented adverse events.

Feasible Strategies for Sustaining Guideline Adherence: Cross-sectional Analysis of a National Collaborative

Health care providers' adherence to guidelines declines over time, and feasible strategies for sustaining adherence have not yet been identified. We assessed the long-term feasibility of various strategies for sustaining guideline adherence and described factors influencing their use. We conducted a cross-sectional survey (N = 104) of physician leaders who participated in a national collaborative to improve care of infants with suspected sepsis. Data were collected on long-term use of strategies to promote guideline adherence (use, perceived effectiveness, and barriers to use). Sixty (58%) participants from diverse hospital settings responded. There were significant declines in use of quality improvement and educational strategies, largely driven by lack of time or staff resources and competing priorities. Electronic strategies (eg, order sets) and hospital policies or guidelines were feasible to continue long-term after the collaborative ended and were perceived as effective. Clinicians and healthcare leaders should consider prioritizing these strategies in their efforts to improve care and outcomes for children in hospital settings.

[Closed-loop medication management: Results of a user survey]

BACKGROUND

New technologies, such as bar-code scanning systems, have played a significant role in enhancing medication processes over recent years. Despite the documented benefits, integration, acceptance, and user opinion continue to play an important role in the successful implementation of such systems. To date no studies have been carried out in Switzerland to assess the attitude or acceptance of nurses towards electronically supported medication systems after implementation. This study was conducted in order to close this gap.

METHODS

Following a four-month test phase of a closed-loop medication system on two mixed medical-surgical units in a tertiary teaching hospital, a cross-sectional online survey was conducted among the participating registered nurses (response rate: 62.5%).

RESULTS

The new system was evaluated positively by the majority (70%) of users. Accordingly, the barcode-assisted medication process was proven to be especially beneficial to users during the 24-hour medication preparation process and during the preparation of infusions. However, user compliance decreased significantly during the administration of bedside medication and the preparation of additional single doses. This was mainly due to a lack of time and inadequate system performance.

CONCLUSION

In the study, 75% of participants reported that they were open to or even enthusiastic about using the new technologies and were supportive of their introduction into the medication process. Overall, the majority rated the new system as beneficial to daily clinical practice, provided the technical performance was high.

A Novel Platform to Define Chemotherapy Templates and Their Prescriptions

Medication errors have been identified as a major type of medical errors. Chemotherapy medication errors that occur in the prescription phase appear to be related to more significant adverse outcomes. The use of pre-printed templates increases patient safety. The functionalities required for the prescription of chemotherapy are not usually part of Clinical Physician Order Entry. The implementation of electronic chemotherapy templates will reduce the prescription errors.

Decision Support Tools for Drugs Prescription Process in a Hospital in Argentina

While medications can improve the health of patients, the prescription process is complex and prone to errors. The structured medical order entry systems (CPOE) with clinical decision support (CDS) are increasingly implemented to improve patient safety, however the organizations that decide to implement them will have several challenges: understanding which classes of CDS can admit their systems, ensure that clinical knowledge is adequate and design tools for proper monitoring. We share our experience of over ten years of development and implementation of clinical decision support tools during drugs prescription process and tools that have allowed us to monitor them correctly.

Evidence-Based Usability Principles for Safe Computerized Provider Order Entry (CPOE) Interface Design

There is a dearth of evidence-based tools to design the safest Computerized Provider Order Entry (CPOE) system possible. An evidence-based list of usability principles for the design of the CPOE interface was developed following a literature review, and validated with the Chief Medical Information Officer and CPOE team at Island Health. The list includes 11 usability principles that can be used to inform ongoing CPOE interface design and evaluation efforts to improve patient safety.

Impact of the Performance Gap Between Interactive Alerts and Quality Metrics

Interactive alerts are used to enhance compliance with primary prevention and have been shown to improve quality metrics. However, the degree of impact of these alerts is controversial and there is concern with excessive alerting. Our objective is to develop reliable processes to assess the direct impact of interactive alerts on clinical performance. Here we present preliminary finding related to the evaluation of the performance gaps between alerts and clinical practice.

Clinician preferences for computerised clinical decision support for medications in primary care: a focus group study

BACKGROUND

To improve user-centred design efforts and efficiency; there is a need to disseminate information on modern day clinician preferences for technologies such as computerised clinical decision support (CDS).

OBJECTIVE

To describe clinician perceptions regarding beneficial features of CDS for chronic medications in primary care.

METHODS

This study included focus groups and clinicians individually describing their ideal CDS. Three focus groups were conducted including prescribing clinicians from a variety of disciplines. Outcome measures included identification of favourable features and unintended consequences of CDS for chronic medication management in primary care. We transcribed recordings, performed thematic qualitative analysis and generated counts when possible.

RESULTS

There were 21 participants who identified four categories of beneficial CDS features during the group discussion: non-interruptive alerts, clinically relevant and customisable support, presentation of pertinent clinical information and optimises workflow. Non-interruptive alerts were broadly defined as passive alerts that a user chooses to review, whereas interruptive were active or disruptive alerts that interrupted workflow and one is forced to review before completing a task. The CDS features identified in the individual descriptions were consistent with the focus group discussion, with the exception of non-interruptive alerts. In the individual descriptions, 12 clinicians preferred interruptive CDS compared with seven clinicians describing non-interruptive CDS.

CONCLUSION

Clinicians identified CDS for chronic medications beneficial when they are clinically relevant and customisable, present pertinent clinical information (eg, labs, vitals) and improve their workflow. Although clinicians preferred passive, non-interruptive alerts, most acknowledged that these may not be widely seen and may be less effective. These features align with literature describing best practices in CDS design and emphasise those features clinicians prioritise, which should be considered when designing CDS for medication management in primary care. These findings highlight the disparity between the current state of CDS design and clinician-stated design features associated with beneficial CDS.

Alerts for community pharmacist-provided medication therapy management: recommendations from a heuristic evaluation

BACKGROUND

Medication therapy management (MTM) is a service, most commonly provided by pharmacists, intended to identify and resolve medication therapy problems (MTPs) to enhance patient care. MTM is typically documented by the community pharmacist in an MTM vendor's web-based platform. These platforms often include integrated alerts to assist the pharmacist with assessing MTPs. In order to maximize the usability and usefulness of alerts to the end users (e.g., community pharmacists), MTM alert design should follow principles from human factors science. Therefore, the objectives of this study were to 1) evaluate the extent to which alerts for community pharmacist-delivered MTM align with established human factors principles, and 2) identify areas of opportunity and recommendations to improve MTM alert design.

METHODS

Five categories of MTM alerts submitted by community pharmacists were evaluated: 1) indication, 2) effectiveness; 3) safety; 4) adherence; and 5) cost-containment. This heuristic evaluation was guided by the Instrument for Evaluating Human-Factors Principles in Medication-Related Decision Support Alerts (I-MeDeSA) which we adapted and contained 32 heuristics. For each MTM alert, four analysts' individual ratings were summed and a mean score on the modified I-MeDeSA computed. For each heuristic, we also computed the percent of analyst ratings indicating alignment with the heuristic. We did this for all alerts evaluated to produce an "overall" summary of analysts' ratings for a given heuristic, and we also computed this separately for each alert category. Our results focus on heuristics where ≤50% of analysts' ratings indicated the alerts aligned with the heuristic.

RESULTS

I-MeDeSA scores across the five alert categories were similar. Heuristics pertaining to visibility and color were generally met. Opportunities for improvement across all MTM alert categories pertained to the principles of alert prioritization; text-based information; alarm philosophy; and corrective actions.

CONCLUSIONS

MTM alerts have several opportunities for improvement related to human factors principles, resulting in MTM alert design recommendations. Enhancements to MTM alert design may increase the effectiveness of MTM delivery by community pharmacists and result in improved patient outcomes.

A systematic review of the effects of implementing clinical pathways supported by health information technologies

OBJECTIVE

Health information technology (HIT) interventions include electronic patient records, prescribing, and ordering systems. Clinical pathways are multidisciplinary plans of care that enable the delivery of evidence-based healthcare. Our objective was to systematically review the effects of implementing HIT-supported clinical pathways.

MATERIALS AND METHODS

A systematic review protocol was developed including Medline, Embase, and CENTRAL database searches. We recorded data relating to study design, participants, intervention, and outcome characteristics and formally assessed risk of bias.

RESULTS

Forty-four studies involving more than 270 000 patients were included. Investigation methodologies included before-after (n = 16, 36.4%), noncomparative (n = 14, 31.8%), interrupted time series (n = 5, 11.4%), retrospective cohort (n = 4, 9.1%), cluster randomized (n = 2, 4.5%), controlled before-after (n = 1, 2.3%), prospective case-control (n = 1, 2.3%), and prospective cohort (n = 1, 2.3%) study designs. Clinical decision support (n = 25, 56.8%), modified electronic documentation (n = 23, 52.3%), and computerized provider order entry (n = 23, 52.3%) were the most frequently utilized HIT interventions. The majority of studies (n = 38, 86.4%) reported benefits associated with HIT-supported pathways. These included reported improvements in objectively measured patient outcomes (n = 15, 34.1%), quality of care (n = 29, 65.9%), and healthcare resource utilization (n = 10, n = 22.7%).

DISCUSSION

Although most studies reported improvements in outcomes, the strength of evidence was limited by the study designs that were utilized.

CONCLUSIONS

Ongoing evaluations of HIT-supported clinical pathways are justified but would benefit from study designs that report key outcomes (including adverse events) and minimize the risk of bias.

Clinical decision support for high-cost imaging: A randomized clinical trial

There is widespread concern over the health risks and healthcare costs from potentially inappropriate high-cost imaging. As a result, the Centers for Medicare and Medicaid Services (CMS) will soon require high-cost imaging orders to be accompanied by Clinical Decision Support (CDS): software that provides appropriateness information at the time orders are placed via a best practice alert for targeted (i.e. likely inappropriate) imaging orders, although the impacts of CDS in this context are unclear. In this randomized trial of 3,511 healthcare providers at Aurora Health Care, we study the impacts of CDS on the ordering behavior of providers. We find that CDS reduced targeted imaging orders by a statistically significant 6%, however there was no statistically significant change in the total number of high-cost scans or of low-cost scans. The results suggest that the impending CMS mandate requiring healthcare systems to adopt CDS may modestly increase the appropriateness of high-cost imaging.

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems

IMPORTANCE

The indication (reason for use) for a medication is rarely included on prescriptions despite repeated recommendations to do so. One barrier has been the way existing electronic prescribing systems have been designed.

OBJECTIVE

To evaluate, in comparison with the prescribing modules of 2 leading electronic health record prescribing systems, the efficiency, error rate, and satisfaction with a new computerized provider order entry prototype for the outpatient setting that allows clinicians to initiate prescribing using the indication.

DESIGN, SETTING, AND PARTICIPANTS

This quality improvement study used usability tests requiring internal medicine physicians, residents, and physician assistants to enter prescriptions electronically, including indication, for 8 clinical scenarios. The tool order assignments were randomized and prescribers were asked to use the prototype for 4 of the scenarios and their usual system for the other 4. Time on task, number of clicks, and order details were captured. User satisfaction was measured using posttask ratings and a validated system usability scale. The study participants practiced in 2 health systems' outpatient practices. Usability tests were conducted between April and October of 2017.

MAIN OUTCOMES AND MEASURES

Usability (efficiency, error rate, and satisfaction) of indications-based computerized provider order entry prototype vs the electronic prescribing interface of 2 electronic health record vendors.

RESULTS

Thirty-two participants (17 attending physicians, 13 residents, and 2 physician assistants) used the prototype to complete 256 usability test scenarios. The mean (SD) time on task was 1.78 (1.17) minutes. For the 20 participants who used vendor 1's system, it took a mean (SD) of 3.37 (1.90) minutes to complete a prescription, and for the 12 participants using vendor 2's system, it took a mean (SD) of 2.93 (1.52) minutes. Across all scenarios, when comparing number of clicks, for those participants using the prototype and vendor 1, there was a statistically significant difference from the mean (SD) number of clicks needed (18.39 [12.62] vs 46.50 [27.29]; difference, 28.11; 95% CI, 21.47-34.75; P < .001). For those using the prototype and vendor 2, there was also a statistically significant difference in number of clicks (20.10 [11.52] vs 38.25 [19.77]; difference, 18.14; 95% CI, 11.59-24.70; P < .001). A blinded review of the order details revealed medication errors (eg, drug-allergy interactions) in 38 of 128 prescribing sessions using a vendor system vs 7 of 128 with the prototype.

CONCLUSIONS AND RELEVANCE

Reengineering prescribing to start with the drug indication allowed indications to be captured in an easy and useful way, which may be associated with saved time and effort, reduced medication errors, and increased clinician satisfaction.

Using Digital Health to Support Best Practices: Impact of MRI Ordering Guidelines Embedded Within an Electronic Referral Solution

BACKGROUND

Between 2003 and 2012, the number of MRIs performed in Canada more than doubled to 1.7 million [1]. According to a 2010 Health Council of Canada report nearly 30% of MRIs were inappropriately ordered [2]. The use of diagnostic imaging referral guidelines has been shown to improve the appropriateness of imaging orders [3, 4].

OBJECTIVES

To identify the number of unnecessary pre-consult MRIs ordered for patients with knee pain. As well, the impact that new evidence-based clinical decision support (DS) guidelines embedded within the referral form has had on the number of unnecessary MRIs was investigated.

METHODS

This study employed a retrospective design approach. Charts of all knee pain patients over the age of 55 who were referred for consultation to the 5 participating orthopedic surgeons during the study period were reviewed by three medical students.

RESULTS

270 patient charts were included in this study. MRI was ordered for 60 patients with only 56.7% having had a prior X-ray. Of the 60 ordered MRIs, 50 (84%) were considered inappropriate, while only 10 (16%) were appropriate. Our results were compared to previous results of a quality improvement study implemented at the same clinic. A substantial reduction of 12% in the number of pre-consult MRIs and a 5% increase in the number of ordered X-rays before consultation was demonstrated.

CONCLUSION

This work highlights the impact of including DS tools within an electronic referral form to support clinical best practices.

Identifying dominant inpatient trends leveraging electronic physician orders:The Medical Gopher 1993-2016

The Medical Gopher was one of the first examples of a computerized physician order entry system. For decades, it captured the "best thoughts" of thousands of physicians at their particular moments in medical history. We hypothesized and found that electronic physician orders can identify important overarching trends in medicine through simple graphs, which can prompt both informed reflection and potentially action if redirection is needed.

When an Alert is Not an Alert: A Pilot Study to Characterize Behavior and Cognition Associated with Medication Alerts

Introduction. Preventable adverse drug events are a significant patient-safety concern, yet most medication alerts are disregarded. Pharmacists encounter the highest number of medication alerts and likely have developed behaviors to cope with alerting inefficiencies. The study objective was to better understand alert override behavior relating to a motivational construct framework. Methods. Mixed-methods study of 10 pharmacists (567 verifications) with eye-tracking observations and retrospective think aloud interviews. Results. Pharmacists spent on average 14 seconds longer verifying orders with alerts than orders without alerts (p<0.001). Verification occurred before alerts were triggered, and no order changes occurred after alerts. Pharmacists reported 62% of alerts as unhelpful and 21% as frustrating. Alert interactions took on average 3.9 seconds. Discussion. Pharmacists anticipate alerts by making appropriate checks and changes before alert prompts. Medication alerts seem to be useful. However, the observed pharmacists' behavior suggests changes in the alert context are needed to match cognition.

A Pragmatic Guide to Establishing Clinical Decision Support Governance and Addressing Decision Support Fatigue: a Case Study

There is limited guidance available in the literature for establishing clinical decision support (CDS) governance and improving CDS effectiveness in a pragmatic, resource-efficient manner. Here, we describe how University of Utah Health established enterprise CDS governance in 2015 leveraging existing resources. Key components of the governance include a multi-stakeholder CDS Committee that vets new requests and reviews existing content; a requirement that proposed CDS is actually desired by intended recipients; coordination with other governance bodies; basic data analytics to identify high-frequency, low-value CDS and monitor progress; active solicitation of user issues; the transition of alert and reminder content to other, more appropriate areas in the electronic health record; and the judicious use of experimental designs to guide decision-making regarding CDS effectiveness. In the three years since establishing this governance, new CDS has been continuously added while the overall burden of clinician-facing alerts and reminders has been reduced by 53.8%.

Electronic Decision support for Improvement of Contemporary Therapy for Stroke Prevention

BACKGROUND

Despite ample clinical trial data demonstrating that oral anticoagulation (OAC) treatment is highly effective in reducing stroke for patients with atrial fibrillation (AF), OAC treatment remains underutilized in current clinical practice. Targeting hospitalist and emergency department providers with electronic decision support represents a potential quality improvement opportunity in the use of OAC medication in AF patients.

METHODS

We conducted a 3-center study in which 2 sites utilized an electronic alert (EA) embedded in the electronic health record and 1 site provided usual care. The EA calculated the CHA₂DS₂-VASc score for clinicians. Patients were tracked following discharge from either the emergency department or hospital. We hypothesized that the EA would increase the rate of OAC use by 15% compared to usual care, with a study sample size of 360 patients. Study exclusions included severe heart valve disease, advanced renal disease, and severe dementia. The primary endpoint was OAC use at the time of hospital discharge or 30 days after hospital discharge (whichever was the last observation recorded).

RESULTS

Among 309 patients included for analysis (mean age 70.2 years), the median CHA₂DS₂-VASc score was 3.5. The frequency of OAC use at follow-up at the usual care hospital was 55.9% (95% confidence interval 47.4-67.9). At the 2 EA sites, the rate of OAC use at the last observation point was 43.9% (P = .06). Aspirin use at follow-up was similar at the usual care site and the EA sites (53.8% versus 46.3%). The rate of OAC use in patients greater than 75 years was 60.0% in the usual care site and 48.4% (P = .09) at the EA sites.

CONCLUSIONS

The EA in our study was not sufficient to ameliorate therapeutic inertia in the use of OAC for stroke prevention in AF.

Comparative usability evaluation of consultation order templates in a simulated primary care environment

Communication breakdowns in the referral process negatively impact clinical workflow and patient safety. There is a lack of evidence demonstrating the impact of published design recommendations addressing contributing issues with consultation order templates. This study translated the recommendations into a computer-based prototype and conducted a comparative usability evaluation. With a scenario-based simulation, 30 clinicians (referrers) participated in a within-group, counterbalanced experiment comparing the prototype with their present electronic order entry system. The prototype significantly increased satisfaction (Cohen's d = 1.80, 95% CI [1.19, 2.41], p < .001), and required significantly less mental effort (d = 0.67 [0.14, 1.20], p < .001). Regarding efficiency, the prototype required significantly fewer mouse clicks (mean difference = 29 clicks, p < .001). Although overall task time did not differ significantly (d = -0.05 [-0.56, 0.47]), the prototype significantly quickened identification of the appropriate specialty clinic (mean difference = 12 s, d = 0.98 [0.43, 1.52], p < .001). The experimental evidence demonstrated that clinician-centered interfaces significantly improved system usability during ordering of consultations.