Retrospective analysis of the impact of electronic medical record alerts on low value care in a pediatric hospital.

OBJECTIVES: Hospital costs continue to rise unsustainably. Up to 20% of care is wasteful including low value care (LVC). This study aimed to understand whether electronic medical record (EMR) alerts are effective at reducing pediatric LVC and measure the impact on hospital costs. MATERIALS AND METHODS: Using EMR data over a 76-month period, we evaluated changes in 4 LVC practices following the implementation of EMR alerts, using time series analysis to control for underlying time-based trends, in a large pediatric hospital in Australia. The main outcome measure was the change in rate of each LVC practice. Balancing measures included the rate of alert adherence as a proxy measure for risk of alert fatigue. Hospital costs were calculated by the volume of LVC avoided multiplied by the unit costs. Costs of the intervention were calculated from clinician and analyst time required. RESULTS: All 4 LVC practices showed a statistically significant reduction following alert implementation. Two LVC practices (blood tests) showed an abrupt change, associated with high rates of alert adherence. The other 2 LVC practices (bronchodilator use in bronchiolitis and electrocardiogram ordering for sleeping bradycardia) showed an accelerated rate of improvement compared to baseline trends with lower rates of alert adherence. Hospital savings were $325 to $180 000 per alert. DISCUSSION AND CONCLUSION: EMR alerts are effective in reducing pediatric LVC practices and offer a cost-saving opportunity to the hospital. Further efforts to leverage EMR alerts in pediatric settings to reduce LVC are likely to support future sustainable healthcare delivery.

An Observational Study to Identify Drug-related Problems (DRP) in Routine Care and An Expert Panel Assessment to Rate Clinical Risk and Preventability by Unit-dose Dispensing Systems (UDDS) with Computerized Physician Order Entry (CPOE) and Clinical Decision-Support Systems (CDSS).

Background and aim: Drug-related problems (DRP) jeopardize patient safety. Unit-dose dispensing systems (UDDS) with computerized-physician-order-entry (CPOE) and clinical-decision-support-systems (CDSS) were reported as a promising concept for preventing DRP. We aimed at identifying and categorizing DRP in peroral drug administration considering their clinical risk and preventability by UDSS/CPOE/CDSS. Investigations: In surgical and internal-medicine departments, we observed routine procedures in peroral drug administration for DRP. An expert panel including pharmaceutical and nursing expertise categorized the identified 18 DRP categories into three levels: DRP that have not yet resulted in medication errors (ME) (Level-I), DRP where ME have occurred but have not yet reached the patient (Level-II), and DRP where ME have occurred and have reached the patient (Level-III). Additionally, the panel categorized DRP according to their clinical risk and whether the implementation of UDSS/CPOE/CDSS can prevent them. Results: In 77 surgical patients, 1,849 peroral drug administration procedures, and in 149 internal-medicine patients, 1,405 procedures were observed. The 18 DRP categories were identified with a frequency of 0.6%-26.7% (Level-I), 0.1%-21.5% (Level-II), and 0.0%-1.0% (Level-III). Of those, four categories were considered of high clinical risk: "Name of the medication is not readable", "Prescribed medication is not prepared for administration", "An incorrect or non-prescribed medication is prepared", and "A medication is prepared for the wrong patient (mix-up)". Twelve DRP categories were categorized as highly preventable by UDSS/CPOE/CDSS. Conclusions:Under routine conditions, we identified a substantial number of DRPs. An expert panel categorized many of those DRPs as clinically highly relevant and highly preventable by UDSS/CPOE/CDSS.

Human factors and safety analysis methods used in the design and redesign of electronic medication management systems: A systematic review.

INTRODUCTION: Poorly designed electronic medication management systems (EMMS) or computerized physician order entry (CPOE) systems in hospital settings can result in usability issues and in turn, patient safety risks. As a safety science, human factors and safety analysis methods have potential to support the safe and usable design of EMMS. OBJECTIVE: To identify and describe human factors and safety analysis methods that have been used in the design or redesign of EMMS used in hospital settings. MATERIALS AND METHODS: A systematic review, following PRISMA guidelines, was conducted by searching online databases and relevant journals from January 2011 to May 2022. Studies were included if they described the practical application of human factors and safety analysis methods to support the design or redesign of a clinician-facing EMMS, or its components. Methods used were extracted and mapped to human centered design (HCD) activities: understanding context of use; specifying user requirements; producing design solutions; and evaluating the design. RESULTS: Twenty-one papers met the inclusion criteria. Overall, 21 human factors and safety analysis methods were used in the design or redesign of EMMS with prototyping, usability testing, participant surveys/questionnaires and interviews the most frequent. Human factors and safety analysis methods were most frequently used to evaluate the design of a system (n = 67; 56.3%). Nineteen of 21 (90%) methods used aimed to identify usability issues and/or support iterative design; only one paper utilized a safety-oriented method and one, a mental workload assessment method. DISCUSSION AND CONCLUSION: While the review identified 21 methods, EMMS design primarily utilized a subset of available methods, and rarely a method focused on safety. Given the high-risk nature of medication management in complex hospital environments, and the potential for harm due to poorly designed EMMS, there is significant potential to apply more safety-oriented human factors and safety analysis methods to support EMMS design.

Improving medication safety in a paediatric hospital: a mixed-methods evaluation of a newly implemented computerised provider order entry system.

OBJECTIVES: Computerised provider order entry (CPOE) systems have been implemented around the world as a solution to reduce ordering and transcription errors. However, previous literature documented many challenges to attain this goal, especially in paediatric settings. The objectives of this study were to (1) analyse the impact of a paediatric CPOE system on medication safety and (2) suggest potential error prevention strategies. METHODS: A pre-post observational study was conducted at the pilot ward (n=60 beds) of a paediatric academic health centre through mixed methods. The implementation project and medication management workflows were described through active participation to the project management team, observation, discussions and analysis of related documents. Furthermore, using incident reports, the nature of each error and error rate was compared between the preperiod and postperiod. RESULTS: The global error rate was lower, but non-statistically significant, in the post implementation phase, which was mostly driven by a significant reduction in errors during order acknowledgement, transmission and transcription. Few errors occurred at the prescription step, and most errors occurred during medication administration. Furthermore, some errors could have been prevented using a CPOE in the pre-implementation period, and the CPOE led to few technology-related errors. DISCUSSION AND CONCLUSION: This study identified both intended and unintended effects of CPOE adoption through the entire medication management workflow. This study revealed the importance of simplifying the acknowledgement, transmission and transcribing steps through the implementation of a CPOE to reduce medication errors. Improving the usability of the electronic medication administration record could help further improve medication safety.

Can CPOE Based on Electronic Order Sets Cause Unintended Consequences (Expensive and Unnecessary Tests) at the Emergency Department?

Computerized Provider Order Entry (CPOE) systems may cause unintended consequences. This study aimed to describe the on-going system for CPOE order sets, and to explore an economic evaluation at the Emergency Department. First, we developed a costs dashboard which showed us the significant and excessive use of medical tests per consultation. We identified the top 10 most widely used and most expensive tests. Additionally we noticed that the labs seemed to continually increase. Then, we found that 27% of the consultations have at least one item of laboratory practice between January and February 2020, and this represents more than 80% of the consultation costs. Health care spending has reached epic proportions globally. We think that it is time to rethink effective strategies. Maybe it is time to deactivate/remove electronic order sets (EOSs) and the functionality to develop and create their own "private" order sets, in order to eliminate waste and inefficiencies.

Development and assessment of PharmaCheck: an electronic screening tool for the prevention of twenty major adverse drug events.

BACKGROUND: Adverse drug events (ADEs) can be prevented by deploying clinical decision support systems (CDSS) that directly assist physicians, via computerized order entry systems, and clinical pharmacists performing medication reviews as part of medical rounds. However, physicians using CDSS are known to be exposed to the alert-fatigue phenomenon. Our study aimed to assess the performance of PharmaCheck-a CDSS to help clinical pharmacists detect high-risk situations with the potential to lead to ADEs-and its impact on clinical pharmacists' activities. METHODS: Twenty clinical rules, divided into four risk classes, were set for the daily screening of high-risk situations in the electronic health records of patients admitted to our General Internal Medicine Department. Alerts to clinical pharmacists encouraged them to telephone prescribers and suggest any necessary treatment adjustments. PharmaCheck's performance was assessed using the intervention's positive predictive value (PPV), which characterizes the proportion of interventions for each alert triggered. PharmaCheck's impact was assessed by considering clinical pharmacists as a filter for ruling out futile alerts and by comparing the final clinical PPV with a pharmacist (the proportion of interventions that led to a change in the medical regimen) to the final clinical PPV without a pharmacist. RESULTS: Over 132 days, 447 alerts were triggered for 383 patients, leading to 90 interventions (overall intervention PPV = 20.1%). By risk class, intervention PPVs made up 26.9% (n = 65/242) of abnormal laboratory value alerts, 3.1% (4/127) of alerts for contraindicated medications or medications to be used with caution, 28.2% (20/71) of drug-drug interaction alerts, and 14.3% (1/7) of inadequate mode of administration alerts. Clinical PPVs reached 71.0% (64/90) when pharmacists filtered alerts and 14% (64/242) if they were not doing it. CONCLUSION: PharmaCheck enabled clinical pharmacists to improve their traditional processes and broaden their coverage by focusing on 20 high-risk situations. Alert management by pharmacists seemed to be a more effective way of preventing risky situations and alert-fatigue than a model addressing alerts to physicians exclusively. Some fine-tuning could enhance PharmaCheck's performance by considering the information quality of triggers, the variability of clinical settings, and the fact that some prescription processes are already highly secured.

Retrospective descriptive assessment of clinical decision support medication-related alerts in two Saudi Arabian hospitals.

OBJECTIVES: To determine the frequency of clinical decision support system (CDSS) medication-related alerts generated, accepted, or overridden, to assess appropriateness of alert display and overrides, and to characterise the documentation of clinician justification for these overrides in an academic medical centre in Saudi Arabia. MATERIALS AND METHODS: System-generated CDSS reports for the period June 2015 to December 2017 were retrospectively reviewed and analysed. Alerts were classified into different types, and rates of alert overrides calculated as percentages of all generated alerts. A subset of 307 overridden alerts was assessed for appropriateness of display and override by two clinical pharmacists. Physician documentation of reasons for overriding alerts were categorised. RESULTS: A total of 4,446,730 medication-related alerts were generated from both inpatient and outpatient settings, and 4,231,743 (95.2%) were overridden. The most common alert type was 'duplicate drug', accounting for 3,549,736 (79.8%) of alerts. Of 307 alerts assessed for appropriateness, 246 (80%) were judged to be appropriately displayed and 244 (79%) were overridden appropriately. New drug allergy and drug allergy alerts had the highest percentage of being judged as inappropriately overridden. For 1,594,313 alerts (37.7%), 'no overridden reason selected' was chosen from the drop-down menu. CONCLUSIONS: The alert generation and override rate were higher than reported previously in the literature. The small sample size of 307 alerts assessed for appropriateness of alert display and override is a potential limitation. Revision of the CDSS rules for alerts (focusing on specificity and relevance for the local context) is now recommended. Future research should prospectively assess providers' perspectives, and determine patient harm associated with overridden alerts.

Development, Validation, and Assessment of Clinical Impact of Real-time Alerts to Detect Inpatient As-Needed Opioid Orders With Duplicate Indications: Prospective Study.

BACKGROUND: As-needed (PRN) opioid orders with duplicate indications can lead to medication errors and opioid-related adverse drug events. OBJECTIVE: The objective of our study was to build and validate real-time alerts that detect duplicate PRN opioid orders and assist clinicians in optimizing the safety of opioid orders. METHODS: This single-center, prospective study used an iterative, 3-step process to refine alert performance by advancing from small sample evaluations of positive predictive values (PPVs) (step 1) through intensive evaluations of accuracy (step 2) to evaluations of clinical impact (step 3). Validation cohorts were randomly sampled from eligible patients for each step. RESULTS: During step 1, the PPV was 100% (one-sided, 97.5% CI 70%-100%) for moderate and severe pain alerts. During step 2, duplication of 1 or more PRN opioid orders was identified for 17% (34/201; 95% CI, 12%-23%) of patients during chart review. This bundle of alerts showed 94% sensitivity (95% CI 80%-99%) and 96% specificity (95% CI 92%-98%) for identifying patients who had duplicate PRN opioid orders. During step 3, at least 1 intervention was made to the medication profile for 77% (46/60; 95% CI 64%-87%) of patients, and at least 1 inappropriate duplicate PRN opioid order was discontinued for 53% (32/60; 95% CI 40%-66%) of patients. CONCLUSIONS: The bundle of alerts developed in this study was validated against chart review by a pharmacist and identified patients who benefited from medication safety interventions to optimize PRN opioid orders.

Retrospective Evaluation of Artificial Intelligence Leveraging Free-Text Imaging Order Entry to Facilitate Federally Required Clinical Decision Support.

OBJECTIVE: The Protecting Access to Medicare Act mandates clinical decision support (CDS) at imaging order entry, necessitating the use of structured indications to map CDS scores. We evaluated the performance of a commercially available artificial intelligence (AI) tool leveraging free-text order entry to facilitate provider selection of the necessary structured indications. METHODS: Our institution implemented an AI tool offering predicted structured indications based upon the ordering provider's entry of a free-text reason for examination. Providers remained able to order via the traditional direct search for structured indications. Alternatively, they could take the new free-text-AI approach allowing them to select from AI-predicted indications, perform additional direct searches, indicate no matching indication, or exit CDS workflow. We hypothesized the free-text-AI approach would be elected more often and the AI tool would be successful in facilitating selection of structured indications. We reviewed advanced imaging orders (n = 40,053) for the first 3 months (February to May 2020) since implementation. RESULTS: Providers were more likely (P < .001) to choose the free-text-AI approach (23,580; 58.9%) to order entry over direct search for structured indications (16,473; 41.1%). The AI tool yielded alerts with predicted indications in 91.7% (n = 21,631) of orders with free text. Ultimately, providers chose AI-predicted indications in 57.7% (n = 12,490) of cases in which they were offered by the tool. DISCUSSION: Providers significantly more often elected the new free-text-AI approach to order entry for CDS, suggesting provider preference over the traditional approach. The AI tool commonly predicted indications acceptable to ordering providers.

Lessons From the Free-Text Epidemic: Opportunities to Optimize Deployment of Imaging Clinical Decision Support.

OBJECTIVE: The Protecting Access to Medicare Act of 2014 requires clinicians to consult Appropriate Use Criteria (AUC) when ordering advanced imaging procedures. Free-text order indications are available when there is no applicable structured indication but are unscored by the AUC. We determined the proportion of free-text indications among all advanced imaging orders and the proportion of free-text indications that could be mapped to a single structured indication. METHODS: All outpatient advanced diagnostic imaging orders placed in a large multisite health system were recorded after initial AUC deployment (November 20, 2017, to December 19, 2017). Clinicians were prompted upon order entry to select a structured indication or enter a free-text indication. We manually reviewed the two imaging examinations with the highest rate of free-text indications: enhanced CT abdomen/pelvis and unenhanced CT head. Regression analysis examined differences in patient-, imaging-, context-, and provider-level characteristics between scored and unscored examinations. RESULTS: Among all 39,533 orders for advanced imaging procedures, 59% (23,267 of 39,533) were unscored by the system. The regression model c-statistic (0.50-0.55) demonstrated poor model fit to evaluate for differences between scored and unscored examinations. Free-text indications were found in 71% (16,440 of 23,267) of unscored examinations and 42% (16,440 of 39,533) of all examinations. Manual review of all 1,693 CT abdomen/pelvis and 1,527 CT head examinations with free-text indications revealed that 3,132 free-text indications (97%) could be mapped to a single existing structured indication. DISCUSSION: Of all initially placed outpatient advanced imaging procedure orders, 42% included free-text indications and 97% of manually reviewed free-text indications could be mapped to a single structured indication.

Racial Disparity in Clinical Alert Overrides.

The existence of systemic racism in US health care is widely recognized, but the role that informatics plays has received little attention. Clinical guidelines, which can incorporate implicit racial bias or be adhered to in racially disparate ways, are often the basis for clinical alerting systems. It is also possible that clinicians might be discriminatory in their response to alerts (for example, by deciding whether to agree or override the alert). We sought to study whether alert logic in our hospital uses patient race as part of its criteria and if alert override rates show any racial disparities. We obtained data on 5,120,114 alert events at the University of Alabama at Birmingham (UAB) Hospital and examined override the rates and reasons with respect to patient race. We found override rates of 82.27% and 81.30% for Black or African American patients and White patients, respectively. Some differences by alert were statistically significant but generally small. Override patterns varied by clinician but reasons given were generally not disparate, suggesting that if racist behavior is present, it is not widely systemic. However, the great variability in individual clinician behavior suggests that deeper analysis is warranted to determine whether disparities are indeed racist in nature.

Physician-Nurse Communication Surrounding Computerized Physician Order Entry Systems From Social and Technical Perspective: An Ethnographic Study.

Although computerized physician order entry systems improve order transmission and patient safety, overdependence on these systems can impede users' communication. This ethnographic study explored physician-nurse communication surrounding computerized physician order entry systems using a sociotechnical framework. Fieldwork conducted in a tertiary teaching hospital comprised 89 hours of participant observation, and individual semistructured interviews were held with seven nurses and five physicians. In addition, documents and artifacts were collected. Three core themes emerged. First, computerized physician order entry quality-related issues undermined the work efficiency of physicians and nurses. Specifically, usability was error prone because of cognitive overload, and the system was unable to perform relevant traces and raise alerts, demonstrating poor interoperability. Second, social factors, including insufficient training, unclear responsibilities, and a lack of awareness concerning interdisciplinary communication, compounded communication problems. Last, environmental factors, including noncoterminous spaces and times and insufficient technical support, impeded the resolution of communication problems. Technical and social contextual factors relating to computerized physician order entry systems jointly affected physician-nurse communication. Cognitive issues and insufficient alerts impacted work efficiency the most and were compounded by contextual individual- and team-related factors and environmental factors. Therefore, improved functions of computerized physician order entry systems and interprofessional communication training are required to optimize technical and social aspects of physician-nurse communication.

The human resource costs of implementing autopend clinical decision support to improve health maintenance.

OBJECTIVES: Sutter Health developed a novel autopend, or automated laboratory test ordering, clinical decision support (CDS) tool to coordinate the patient and physician process of completing preventive services. This study estimated the costs of developing and implementing the autopend functionality within an existing electronic health maintenance (HM) reminder system. STUDY DESIGN: Human resource time was measured by triangulating in-depth key informant interviews with Microsoft Outlook Calendar metadata (meetings attended) for managers and hourly data from a time-based project management tool (Project Web App) for Epic programmers. Employee time spent was multiplied by the Bureau of Labor Statistics California state hourly wages. Sutter Health is an integrated health care delivery network with more than 12,000 physicians across 100 communities serving 3 million patients. METHODS: Activity-based costing methodology was used to divide the implementation into activities and the human resources required to complete them. RESULTS: Developing and implementing the autopend CDS took more than 3 years, involved 6 managers and 3 Epic programmers, and cost $201,500 (2013 US$) (2670 total hours), which excluded the costs of implementing the initial HM reminder system. Managers spent 90.5% of the total costs (86.6% of total hours) integrating autopend into the health system compared with 9.5% of the total costs (13.4% of total hours) spent programming the functionality. CONCLUSIONS: The autopend CDS might be similarly costly for other organizations to implement if their managers need to complete comparable activities. However, electronic health record vendors could include autopend as a standard package to reduce development costs and improve the uptake of this promising CDS tool.

Passive Verification: A Flawed System Putting Patients' Sight at Risk.

OBJECTIVE: To assess the rate of erroneous or expired (invalid) contact lens prescriptions submitted for passive verification at two practice sites in Cleveland, OH. METHODS: Passive verification facsimile (FAX) requests were collected from office staff at a county hospital (MetroHealth [MH]), and at a private ophthalmology group office (University Ophthalmology Associates [UOA]) in Cleveland, Ohio, from January 2013 to January 2018. RESULTS: A total of 415 verification requests were evaluated (339 MH, 75 UOA), 28.2% (104 MH, 13 UOA) were expired, 11.8% (48 MH, one UOA) were not under the care of the doctor to whom the request was directed, 8.9% (32 MH, 5 UOA) were incorrect, and 3.9% (16 MH, 0 UOA) did not complete fitting. The total rate of invalid prescriptions was 52.8% (200 MH, 19 UOA). CONCLUSIONS: There is a high rate of invalid prescriptions presented for passive verification. Although the majority of prescriptions are simply expired, there is a fraction of prescriptions that contain incorrect specification of lens parameters or no record of prescription by that doctor. The current mechanism of passive verification, with the burden on the provider for denial within a short time window, makes it likely that such prescriptions would be filled, potentially putting patient comfort and safety at risk.

Enteral and Parenteral Order Writing Survey-A Collaborative Evaluation Between the Academy of Nutrition and Dietetics' Dietitians in Nutrition Support Dietetics Practice Group and the American Society for Parenteral and Enteral Nutrition (ASPEN) Dietetics Practice Section.

INTRODUCTION: In 2014 and 2017, the Centers for Medicare and Medicaid Services authorized nutrition-related ordering privileges for registered dietitian nutritionists (RDNs) in hospital and long-term care settings, respectively. Despite this practice advancement, information describing current parenteral nutrition (PN) and enteral nutrition (EN) ordering practices is lacking. Dietitians in Nutrition Support, a dietetic practice group of the Academy of Nutrition and Dietetics and the Dietetics Practice Section of the American Society of Parenteral and Enteral Nutrition (ASPEN) utilized a survey to describe PN and EN ordering practices among RDNs in the United States. METHODS: A cross-sectional study design was utilized to describe RDN PN and EN ordering privileges. Respondents were asked to describe PN and EN ordering privileges, primary practice setting, primary patient population served, nutrition specialty certification, highest degree earned, career length, and, if applicable, the nature of prior denials for ordering privileges or reasons for not applying for ordering privileges. RESULTS: Seven hundred two RDNs completed the survey (12% response rate), with 664 RDNs providing complete data. The majority of respondents (n=558) cared for adult/geriatric patients. Among this subset, 47% had no PN ordering privileges; 14% could order and sign PN; 28% could order PN with provider cosignature; and 10% could order partial PN with provider cosignature. Nineteen percent of RDNs had no EN ordering privileges; 37% could order and sign EN; and 44% could order EN with provider cosignature. RDNs with ordering privileges were more likely to have a nutrition specialty certification and work in an academic or community hospital setting. CONCLUSION: PN and EN ordering privileges are varied because of institution and state requirements. Future research describing the outcomes associated with RDN ordering privileges is needed. This article has been approved by the Academy's Research, International, and Scientific Affairs team and Council on Research and the ASPEN Board of Directors. This article has been co-published with permission in Nutrition in Clinical Practice. The articles are identical except for minor stylistic and spelling differences in keeping with each journal's style. Either citation can be used when citing this article.

Advanced Data Analytics for Clinical Research Part II: Application to Cardiothoracic Surgery.

In the first part of this series, we introduced the tools of Big Data, including Not Only Standard Query Language data warehouse, natural language processing (NLP), optical character recognition (OCR), and Internet of Things (IoT). There are nuances to the utilization of these analytics tools, which must be well understood by clinicians seeking to take advantage of these innovative research strategies. One must recognize technical challenges to NLP, such as unintended search outcomes and variability in the expression of human written texts. Other caveats include dealing written texts in image formats, which may ultimately be handled with transformation to text format by OCR, though this technology is still under development. IoT is beginning to be used in cardiac monitoring, medication adherence alerts, lifestyle monitoring, and saving traditional labs from equipment failure catastrophes. These technologies will become more prevalent in the future research landscape, and cardiothoracic surgeons should understand the advantages of these technologies to propel our research to the next level. Experience and understanding of technology are needed in building a robust NLP search result, and effective communication with the data management team is a crucial step in successful utilization of these technologies. In this second installment of the series, we provide examples of published investigations utilizing the advanced analytic tools introduced in Part I. We will explain our processes in developing the research question, barriers to achieving the research goals using traditional research methods, tools used to overcome the barriers, and the research findings.

Assessment of a Best Practice Alert and Referral Process for Preprocedure Antithrombotic Medication Management for Patients Undergoing Gastrointestinal Endoscopic Procedures.

Importance: Management of antithrombotic medications presents a challenge for many clinicians and patients before procedures. Anticoagulation clinic involvement may improve preprocedure coordination, satisfaction on the part of patients and clinicians, last-minute procedure cancellations, and patient safety. Objective: To assess the implementation of an electronic medical record (EMR) best practice alert (BPA) and anticoagulation clinic referral process to assist with management of antithrombotic medication before gastrointestinal endoscopic procedures. Design, Setting, and Participants: This multimodal evaluation of a quality improvement intervention using EMRs and survey data included patients using oral antithrombotic medications who were scheduled for elective gastrointestinal endoscopic procedures at an academic medical center along with the clinicians who ordered these procedures. Data were collected from November 1, 2017, through December 19, 2018. Data were analyzed in September 2019. Exposures: Following a multidisciplinary intervention, a BPA and referral process for periprocedural antithrombotic medication management was implemented in November 2017. Main Outcomes and Measures: The following implementation outcomes were assessed through EMR review and surveys through December 2018: use of BPAs, patient and clinician satisfaction with preprocedure anticoagulation management, procedure cancelation rates, reach, and spread by patient and clinician characteristics. Multilevel logistic regression was used to estimate variance in BPA use at the clinician level. Results: A total of 2082 patients (mean [SD] age, 64.1 [11.9] years) and 144 clinicians were included in the analysis. The BPA was used broadly across the health system, resulting in anticoagulation clinic referral for 1389 patients (66.7%). Referral was more common for patients using anticoagulant vs antiplatelet medications (1041 of 1524 [68.3%] vs 346 of 556 [62.2%]; adjusted odds ratio [aOR], 1.51; 95% CI, 1.15-1.98) and for procedures ordered by gastroenterologists vs primary care clinicians (933 of 1241 [75.2%] vs 365 of 618 [59.1%]; aOR, 2.15; 95% CI, 1.46-3.17). Individual clinician behavior patterns explained 26.5% (95% CI, 18.7%-36.1%) of variation in anticoagulation clinic referrals. Implementation of the intervention was associated with high patient satisfaction and improvements in multidimensional measures of clinician satisfaction (clinician response rate, 44.2% [144 of 326]). In multivariable analysis, the odds of altered or canceled procedures because of medication mismanagement declined after implementation (8 of 50 [16.0%] vs 1 of 52 [1.9%]; aOR, 0.11; 95% CI, 0.01-0.96; P = .02). Conclusions and Relevance: A newly implemented BPA and anticoagulation clinic referral process was broadly adopted and used, had high satisfaction by patients and clinicians, and was associated with fewer disruptions to planned procedures caused by medication mismanagement.

How the presentation of patient information and decision-support advisories influences opioid prescribing behavior: A simulation study.

OBJECTIVE: The United States faces an opioid crisis. Integrating prescription drug monitoring programs into electronic health records offers promise to improve opioid prescribing practices. This study aimed to evaluate 2 different user interface designs for prescription drug monitoring program and electronic health record integration. MATERIALS AND METHODS: Twenty-four resident physicians participated in a randomized controlled experiment using 4 simulated patient cases. In the conventional condition, prescription opioid histories were presented in tabular format, and computerized clinical decision support (CDS) was provided via interruptive modal dialogs (ie, pop-ups). The alternative condition featured a graphical opioid history, a cue to visit that history, and noninterruptive CDS. Two attending pain specialists judged prescription appropriateness. RESULTS: Participants in the alternative condition wrote more appropriate prescriptions. When asked after the experiment, most participants stated that they preferred the alternative design to the conventional design. CONCLUSIONS: How patient information and CDS are presented appears to have a significant influence on opioid prescribing behavior.

Quality improvement of intravenous to oral medication conversion using Lean Six Sigma methodologies.

INTRODUCTION: Lack of medication conversion from intravenous to oral contributes to increased risk of infection, delayed discharges and higher medication costs. At our institution, intravenous to oral medication conversion rate was 76% with missed opportunity for conversion of 37%. The goal of the project was to reduce the percent of missed opportunities for intravenous to oral conversion for applicable medications. METHODS: A pharmacy-driven intravenous to oral policy and procedure was implemented. To identify potential opportunities, a patient worklist of applicable intravenous to oral medications was created for pharmacy review in real time. An intravenous to oral conversion order was implemented in the computerised provider order entry. 'Convert to oral' was added as an option in the electronic medication request and highlighted reminders were added to the electronic medication administration record for eligible medications. RESULTS: After improvements, the missed opportunity rate for intravenous to oral conversion decreased from 37% (19/51) to 21% (24/113) (p=0.04, two-proportion test), a 43% improvement. The trend in intravenous to oral conversion rate increased from 76% (39/51) to 85% (171/201) and severity adjusted length of stay was reduced from 8.1 days to 6.4 days post improvements (p<0.001, t-test).