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Bauer J, Busse M, Kopetzky T, Seggewies C, Fromm MF, Dörje F. Interprofessional Evaluation of a Medication Clinical Decision Support System Prior to Implementation. Appl Clin Inform 2024; 15:637-649. [PMID: 39084615 PMCID: PMC11290949 DOI: 10.1055/s-0044-1787184] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 04/01/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND Computerized physician order entry (CPOE) and clinical decision support systems (CDSS) are widespread due to increasing digitalization of hospitals. They can be associated with reduced medication errors and improved patient safety, but also with well-known risks (e.g., overalerting, nonadoption). OBJECTIVES Therefore, we aimed to evaluate a commonly used CDSS containing Medication-Safety-Validators (e.g., drug-drug interactions), which can be locally activated or deactivated, to identify limitations and thereby potentially optimize the use of the CDSS in clinical routine. METHODS Within the implementation process of Meona (commercial CPOE/CDSS) at a German University hospital, we conducted an interprofessional evaluation of the CDSS and its included Medication-Safety-Validators following a defined algorithm: (1) general evaluation, (2) systematic technical and content-related validation, (3) decision of activation or deactivation, and possibly (4) choosing the activation mode (interruptive or passive). We completed the in-depth evaluation for exemplarily chosen Medication-Safety-Validators. Moreover, we performed a survey among 12 German University hospitals using Meona to compare their configurations. RESULTS Based on the evaluation, we deactivated 3 of 10 Medication-Safety-Validators due to technical or content-related limitations. For the seven activated Medication-Safety-Validators, we chose the interruptive option ["PUSH-(&PULL)-modus"] four times (4/7), and a new, on-demand option ["only-PULL-modus"] three times (3/7). The site-specific configuration (activation or deactivation) differed across all participating hospitals in the survey and led to varying medication safety alerts for identical patient cases. CONCLUSION An interprofessional evaluation of CPOE and CDSS prior to implementation in clinical routine is crucial to detect limitations. This can contribute to a sustainable utilization and thereby possibly increase medication safety.
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Affiliation(s)
- Jacqueline Bauer
- Pharmacy Department, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Marika Busse
- Pharmacy Department, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Tanja Kopetzky
- Medical Center for Information and Communication Technology (MIK), Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Christof Seggewies
- Medical Center for Information and Communication Technology (MIK), Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Martin F. Fromm
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- FAU NeW—Research Center New Bioactive Compounds, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Frank Dörje
- Pharmacy Department, Universitätsklinikum Erlangen and Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
- FAU NeW—Research Center New Bioactive Compounds, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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Felisberto M, Lima GDS, Celuppi IC, Fantonelli MDS, Zanotto WL, Dias de Oliveira JM, Mohr ETB, Dos Santos RA, Scandolara DH, Cunha CL, Hammes JF, da Rosa JS, Demarchi IG, Wazlawick RS, Dalmarco EM. Override rate of drug-drug interaction alerts in clinical decision support systems: A brief systematic review and meta-analysis. Health Informatics J 2024; 30:14604582241263242. [PMID: 38899788 DOI: 10.1177/14604582241263242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
Primary studies have demonstrated that despite being useful, most of the drug-drug interaction (DDI) alerts generated by clinical decision support systems are overridden by prescribers. To provide more information about this issue, we conducted a systematic review and meta-analysis on the prevalence of DDI alerts generated by CDSS and alert overrides by physicians. The search strategy was implemented by applying the terms and MeSH headings and conducted in the MEDLINE/PubMed, EMBASE, Web of Science, Scopus, LILACS, and Google Scholar databases. Blinded reviewers screened 1873 records and 86 full studies, and 16 articles were included for analysis. The overall prevalence of alert generated by CDSS was 13% (CI95% 5-24%, p-value <0.0001, I^2 = 100%), and the overall prevalence of alert override by physicians was 90% (CI95% 85-95%, p-value <0.0001, I^2 = 100%). This systematic review and meta-analysis presents a high rate of alert overrides, even after CDSS adjustments that significantly reduced the number of alerts. After analyzing the articles included in this review, it was clear that the CDSS alerts physicians about potential DDI should be developed with a focus on the user experience, thus increasing their confidence and satisfaction, which may increase patient clinical safety.
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Affiliation(s)
- Mariano Felisberto
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
- Department of Clinical Analysis, Federal University of Santa Catarina, Florianópolis, Brazil
| | - Geovana Dos Santos Lima
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
- Department of Nursing, Federal University of Santa Catarina, Florianópolis, Brazil
| | - Ianka Cristina Celuppi
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
- Department of Nursing, Federal University of Santa Catarina, Florianópolis, Brazil
| | | | - Wagner Luiz Zanotto
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
| | - Júlia Meller Dias de Oliveira
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
- Graduate Program in Dentistry, Federal University of Santa Catarina, Florianópolis, Brazil
| | - Eduarda Talita Bramorski Mohr
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
- Department of Clinical Analysis, Federal University of Santa Catarina, Florianópolis, Brazil
| | - Ranieri Alves Dos Santos
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
| | | | - Célio Luiz Cunha
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
| | - Jades Fernando Hammes
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
| | - Júlia Salvan da Rosa
- Department of Clinical Analysis, Federal University of Santa Catarina, Florianópolis, Brazil
| | | | - Raul Sidnei Wazlawick
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
| | - Eduardo Monguilhott Dalmarco
- Bridge Laboratory, Technological Center, Federal University of Santa Catarina, Florianópolis, Brazil
- Department of Clinical Analysis, Federal University of Santa Catarina, Florianópolis, Brazil
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3
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Dolin RH, Shenvi E, Alvarez C, Barrows RC, Boxwala A, Lee B, Nathanson BH, Kleyner Y, Hagemann R, Hongsermeier T, Kapusnik-Uner J, Lakdawala A, Shalaby J. PillHarmonics: An Orchestrated Pharmacogenetics Medication Clinical Decision Support Service. Appl Clin Inform 2024; 15:378-387. [PMID: 38388174 PMCID: PMC11098593 DOI: 10.1055/a-2274-6763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Accepted: 02/07/2024] [Indexed: 02/24/2024] Open
Abstract
OBJECTIVES Pharmacogenetics (PGx) is increasingly important in individualizing therapeutic management plans, but is often implemented apart from other types of medication clinical decision support (CDS). The lack of integration of PGx into existing CDS may result in incomplete interaction information, which may pose patient safety concerns. We sought to develop a cloud-based orchestrated medication CDS service that integrates PGx with a broad set of drug screening alerts and evaluate it through a clinician utility study. METHODS We developed the PillHarmonics service for implementation per the CDS Hooks protocol, algorithmically integrating a wide range of drug interaction knowledge using cloud-based screening services from First Databank (drug-drug/allergy/condition), PharmGKB (drug-gene), and locally curated content (drug-renal/hepatic/race). We performed a user study, presenting 13 clinicians and pharmacists with a prototype of the system's usage in synthetic patient scenarios. We collected feedback via a standard questionnaire and structured interview. RESULTS Clinician assessment of PillHarmonics via the Technology Acceptance Model questionnaire shows significant evidence of perceived utility. Thematic analysis of structured interviews revealed that aggregated knowledge, concise actionable summaries, and information accessibility were highly valued, and that clinicians would use the service in their practice. CONCLUSION Medication safety and optimizing efficacy of therapy regimens remain significant issues. A comprehensive medication CDS system that leverages patient clinical and genomic data to perform a wide range of interaction checking and presents a concise and holistic view of medication knowledge back to the clinician is feasible and perceived as highly valuable for more informed decision-making. Such a system can potentially address many of the challenges identified with current medication-related CDS.
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Affiliation(s)
| | - Edna Shenvi
- Elimu Informatics, El Cerrito, California, United States
| | - Carla Alvarez
- Elimu Informatics, El Cerrito, California, United States
| | | | - Aziz Boxwala
- Elimu Informatics, El Cerrito, California, United States
| | - Benson Lee
- College of Pharmacy, Touro University California, Vallejo, California, United States
| | | | - Yelena Kleyner
- Elimu Informatics, El Cerrito, California, United States
| | - Rachel Hagemann
- Independent Contractor, San Francisco, California, United States
| | | | | | | | - James Shalaby
- Elimu Informatics, El Cerrito, California, United States
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Zhang T, Gephart SM, Subbian V, Boyce RD, Villa-Zapata L, Tan MS, Horn J, Gomez-Lumbreras A, Romero AV, Malone DC. Barriers to Adoption of Tailored Drug-Drug Interaction Clinical Decision Support. Appl Clin Inform 2023; 14:779-788. [PMID: 37793617 PMCID: PMC10550365 DOI: 10.1055/s-0043-1772686] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 07/20/2023] [Indexed: 10/06/2023] Open
Abstract
OBJECTIVE Despite the benefits of the tailored drug-drug interaction (DDI) alerts and the broad dissemination strategy, the uptake of our tailored DDI alert algorithms that are enhanced with patient-specific and context-specific factors has been limited. The goal of the study was to examine barriers and health care system dynamics related to implementing tailored DDI alerts and identify the factors that would drive optimization and improvement of DDI alerts. METHODS We employed a qualitative research approach, conducting interviews with a participant interview guide framed based on Proctor's taxonomy of implementation outcomes and informed by the Theoretical Domains Framework. Participants included pharmacists with informatics roles within hospitals, chief medical informatics officers, and associate medical informatics directors/officers. Our data analysis was informed by the technique used in grounded theory analysis, and the reporting of open coding results was based on a modified version of the Safety-Related Electronic Health Record Research Reporting Framework. RESULTS Our analysis generated 15 barriers, and we mapped the interconnections of these barriers, which clustered around three entities (i.e., users, organizations, and technical stakeholders). Our findings revealed that misaligned interests regarding DDI alert performance and misaligned expectations regarding DDI alert optimizations among these entities within health care organizations could result in system inertia in implementing tailored DDI alerts. CONCLUSION Health care organizations primarily determine the implementation and optimization of DDI alerts, and it is essential to identify and demonstrate value metrics that health care organizations prioritize to enable tailored DDI alert implementation. This could be achieved via a multifaceted approach, such as partnering with health care organizations that have the capacity to adopt tailored DDI alerts and identifying specialists who know users' needs, liaise with organizations and vendors, and facilitate technical stakeholders' work. In the future, researchers can adopt the systematic approach to study tailored DDI implementation problems from other system perspectives (e.g., the vendors' system).
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Affiliation(s)
- Tianyi Zhang
- Department of Systems and Industrial Engineering, College of Engineering, University of Arizona, Tucson, Arizona
| | - Sheila M. Gephart
- Advanced Nursing Practice and Science Division, College of Nursing, University of Arizona, Tucson, Arizona
| | - Vignesh Subbian
- Department of Systems and Industrial Engineering, College of Engineering, University of Arizona, Tucson, Arizona
| | - Richard D. Boyce
- Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Lorenzo Villa-Zapata
- Clinical and Administrative Pharmacy, College of Pharmacy, University of Georgia, Athens, Georgia
| | - Malinda S. Tan
- Department of Pharmacotherapy, College of Pharmacy, University of Utah, Salt Lake City, Utah
| | - John Horn
- Department of Pharmacy, School of Pharmacy, University of Washington, Seattle, Washington
| | - Ainhoa Gomez-Lumbreras
- Department of Pharmacotherapy, College of Pharmacy, University of Utah, Salt Lake City, Utah
| | | | - Daniel C. Malone
- Department of Pharmacotherapy, College of Pharmacy, University of Utah, Salt Lake City, Utah
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5
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Stettner S, Adie S, Hanigan S, Thomas M, Pogue K, Zimmerman C. Effect of Replacing Vendor QTc Alerts with a Custom QTc Risk Alert in Inpatients. Appl Clin Inform 2022; 13:19-29. [PMID: 34986493 PMCID: PMC8731239 DOI: 10.1055/s-0041-1740483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
OBJECTIVE The aim of the study is to implement a customized QTc interval clinical decision support (CDS) alert strategy in our electronic health record for hospitalized patients and aimed at providers with the following objectives: minimize QTc prolongation, minimize exposure to QTc prolonging medications, and decrease overall QTc-related alerts. A strategy that was based on the validated QTc risk scoring tool and replacing medication knowledge vendor alerts with custom QTc prolongation alerts was implemented. METHODS This is a retrospective quasi-experimental study with a pre-intervention period (August 2019 to October 2019) and post-intervention period (December 2019 to February 2020). The custom alert was implemented in November 2019. RESULTS In the pre-implementation group, 361 (19.3%) patients developed QTc prolongation, and in the post-implementation group, 357 (19.6%) patients developed QTc prolongation (OR: 1.02, 95% CI: 0.87-1.20, p = 0.81). The odds ratio of an action taken post-implementation compared with pre-implementation was 18.90 (95% CI: 14.03-25.47, p <0. 001). There was also a decrease in total orders for QTc prolonging medications from 7,921 (5.5%) to 7,566 (5.3%) with an odds ratio of 0.96 (95% CI: 0.93-0.99, p = 0.01). CONCLUSION We were able to decrease patient exposure to QTc prolonging medications while not increasing the rate of QTc prolongation as well as improving alert action rate. Additionally, there was a decrease in QTc prolonging medication orders which illustrates the benefit of using a validated risk score with a customized CDS approach compared with a traditional vendor-based strategy. Further research is needed to confirm if an approach implemented at our organization can reduce QTc prolongation rates.
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Affiliation(s)
- Steven Stettner
- Department of Pharmacy, New York-Presbyterian/Weill Cornell Medical Center, New York, New York, United States
| | - Sarah Adie
- Department of Pharmacy Services, Michigan Medicine, Ann Arbor, Michigan, United States
| | - Sarah Hanigan
- Department of Pharmacy Services, Michigan Medicine, Ann Arbor, Michigan, United States
| | - Michael Thomas
- Department of Internal Medicine-Cardiology, Michigan Medicine, Ann Arbor, Michigan, United States
| | - Kristen Pogue
- Department of Pharmacy Services, Michigan Medicine, Ann Arbor, Michigan, United States
| | - Christopher Zimmerman
- Department of Health Information and Technology Services, Michigan Medicine, Ann Arbor, Michigan, United States,Address for correspondence Christopher Zimmerman, PharmD Health Information and Technology Services, Michigan MedicineSuite 500; 510-05, 777 E. Eisenhower Parkway, Ann Arbor, MI 48108-3273United States
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6
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Olakotan OO, Mohd Yusof M. The appropriateness of clinical decision support systems alerts in supporting clinical workflows: A systematic review. Health Informatics J 2021; 27:14604582211007536. [PMID: 33853395 DOI: 10.1177/14604582211007536] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
A CDSS generates a high number of inappropriate alerts that interrupt the clinical workflow. As a result, clinicians silence, disable, or ignore alerts, thereby undermining patient safety. Therefore, the effectiveness and appropriateness of CDSS alerts need to be evaluated. A systematic review was carried out to identify the factors that affect CDSS alert appropriateness in supporting clinical workflow. Seven electronic databases (PubMed, Scopus, ACM, Science Direct, IEEE, Ovid Medline, and Ebscohost) were searched for English language articles published between 1997 and 2018. Seventy six papers met the inclusion criteria, of which 26, 24, 15, and 11 papers are retrospective cohort, qualitative, quantitative, and mixed-method studies, respectively. The review highlights various factors influencing the appropriateness and efficiencies of CDSS alerts. These factors are categorized into technology, human, organization, and process aspects using a combination of approaches, including socio-technical framework, five rights of CDSS, and Lean. Most CDSS alerts were not properly designed based on human factor methods and principles, explaining high alert overrides in clinical practices. The identified factors and recommendations from the review may offer valuable insights into how CDSS alerts can be designed appropriately to support clinical workflow.
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Abstract
OBJECTIVE Human factors and ergonomics (HF/E) frameworks and methods are becoming embedded in the health informatics community. There is now broad recognition that health informatics tools must account for the diverse needs, characteristics, and abilities of end users, as well as their context of use. The objective of this review is to synthesize the current nature and scope of HF/E integration into the health informatics community. METHODS Because the focus of this synthesis is on understanding the current integration of the HF/E and health informatics research communities, we manually reviewed all manuscripts published in primary HF/E and health informatics journals during 2020. RESULTS HF/E-focused health informatics studies included in this synthesis focused heavily on EHR customizations, specifically clinical decision support customizations and customized data displays, and on mobile health innovations. While HF/E methods aimed to jointly improve end user safety, performance, and satisfaction, most HF/E-focused health informatics studies measured only end user satisfaction. CONCLUSION HF/E-focused health informatics researchers need to identify and communicate methodological standards specific to health informatics, to better synthesize findings across resource intensive HF/E-focused health informatics studies. Important gaps in the HF/E design and evaluation process should be addressed in future work, including support for technology development platforms and training programs so that health informatics designers are as diverse as end users.
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8
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Joglekar NN, Patel Y, Keller MS. Evaluation of Clinical Decision Support to Reduce Sedative-Hypnotic Prescribing in Older Adults. Appl Clin Inform 2021; 12:436-444. [PMID: 34107541 PMCID: PMC8189759 DOI: 10.1055/s-0041-1730030] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
OBJECTIVE We sought to characterize the performance of inpatient and outpatient computerized clinical decision support (CDS) alerts aimed at reducing inappropriate benzodiazepine and nonbenzodiazepine sedative medication prescribing in older adults 18 months after implementation. METHODS We reviewed the performance of two CDS alerts in the outpatient and inpatient settings in 2019. To examine the alerts' effectiveness, we analyzed metrics including overall alert adherence, provider-level adherence, and reasons for alert trigger and override. RESULTS In 2019, we identified a total of 14,534 and 4,834 alerts triggered in the outpatient and inpatient settings, respectively. Providers followed only 1% of outpatient and 3% of inpatient alerts. Most alerts were ignored (68% outpatient and 60% inpatient), while providers selected to override the remaining alerts. In each setting, the top 2% of clinicians were responsible for approximately 25% of all ignored or overridden alerts. However, a small proportion of clinicians (2% outpatient and 4% inpatient) followed the alert at least half of the time and accounted for a disproportionally large fraction of the total followed alerts. Our analysis of the free-text comments revealed that many alerts were to continue outpatient prescriptions or for situational anxiety. CONCLUSION Our findings highlight the importance of evaluation of CDS performance after implementation. We found large variation in response to the inpatient and outpatient alerts, both with respect to follow and ignore rates. Reevaluating the alert design by providing decision support by indication may be more helpful and may reduce alert fatigue.
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Affiliation(s)
- Natasha N. Joglekar
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Boston, Massachusetts, United Sates
| | - Yatindra Patel
- Division of General Internal Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, United Sates
| | - Michelle S. Keller
- Division of General Internal Medicine, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, United Sates,Division of Informatics, Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California, United Sates,Department of Health Policy and Management, Fielding School of Public Health, University of California-Los Angeles, Los Angeles, California, United Sates,Address for correspondence Michelle S. Keller, PhD, MPH Division of General Internal Medicine, Department of Medicine, Cedars-Sinai Medical CenterLos Angeles, CA 90048United Sates
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9
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Trinkley KE, Pell JM, Martinez DD, Maude NR, Hale G, Rosenberg MA. Assessing Prescriber Behavior with a Clinical Decision Support Tool to Prevent Drug-Induced Long QT Syndrome. Appl Clin Inform 2021; 12:190-197. [PMID: 33694143 DOI: 10.1055/s-0041-1724043] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Abstract
OBJECTIVE Clinical decision support (CDS) alerts built into the electronic health record (EHR) have the potential to reduce the risk of drug-induced long QT syndrome (diLQTS) in susceptible patients. However, the degree to which providers incorporate this information into prescription behavior and the impact on patient outcomes is often unknown. METHODS We examined provider response data over a period from October 8, 2016 until November 8, 2018 for a CDS alert deployed within the EHR from a 13-hospital integrated health care system that fires when a patient with a QTc ≥ 500 ms within the past 14 days is prescribed a known QT-prolonging medication. We used multivariate generalized estimating equations to analyze the impact of therapeutic alternatives, relative risk of diLQTS for specific medications, and patient characteristics on provider response to the CDS and overall patient mortality. RESULTS The CDS alert fired 15,002 times for 7,510 patients for which the most common response (51.0%) was to override the alert and order the culprit medication. In multivariate models, we found that patient age, relative risk of diLQTS, and presence of alternative agents were significant predictors of adherence to the CDS alerts and that nonadherence itself was a predictor of mortality. Risk of diLQTS and presence of an alternative agent are major factors in provider adherence to a CDS to prevent diLQTS; however, provider nonadherence was associated with a decreased risk of mortality. CONCLUSION Surrogate endpoints, such as provider adherence, can be useful measures of CDS value but attention to hard outcomes, such as mortality, is likely needed.
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Affiliation(s)
- Katy E Trinkley
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, Colorado, United States.,Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado, United States.,Department of Clinical Informatics, University of Colorado Health, Aurora, Colorado, United States
| | - Jonathan M Pell
- Department of Medicine, University of Colorado School of Medicine, Aurora, Colorado, United States.,Department of Clinical Informatics, University of Colorado Health, Aurora, Colorado, United States
| | - Dario D Martinez
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, Colorado, United States
| | - Nicola R Maude
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, Colorado, United States
| | - Gary Hale
- Department of Clinical Informatics, University of Colorado Health, Aurora, Colorado, United States
| | - Michael A Rosenberg
- Division of Cardiac Electrophysiology, University of Colorado School of Medicine, Aurora, Colorado, United States.,Division of Biomedical Informatics and Personalized Medicine, University of Colorado School of Medicine, Aurora, Colorado, United States
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10
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Friebe MP, LeGrand JR, Shepherd BE, Breeden EA, Nelson SD. Reducing Inappropriate Outpatient Medication Prescribing in Older Adults across Electronic Health Record Systems. Appl Clin Inform 2020; 11:865-872. [PMID: 33378781 DOI: 10.1055/s-0040-1721398] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
Abstract
BACKGROUND The American Geriatrics Society recommends against the use of certain potentially inappropriate medications (PIMs) in older adults. Prescribing of these medications correlates with higher rates of hospital readmissions, morbidity, and mortality. Vanderbilt University Medical Center previously deployed clinical decision support (CDS) to decrease PIM prescribing rates, but recently transitioned to a new electronic health record (EHR). OBJECTIVE The goal of this study was to evaluate PIM prescribing rates for older adults before and after migration to the new EHR system. METHODS We reviewed prescribing rates of PIMs in adults 65 years and older, normalized per 100 total prescriptions from the legacy and new EHR systems between July 1, 2014 and December 31, 2019. The PIM prescribing rates before and after EHR migration during November 2017 were compared using a U-chart and Poisson regression model. Secondary analysis descriptively evaluated the frequency of prescriber acceptance rates in the new EHR. RESULTS Prescribing rates of PIMs decreased 5.2% (13.5 per 100 prescriptions to 12.8 per 100 prescriptions; p < 0.0001) corresponding to the implementation of alternatives CDS in the legacy EHR. After migration of the alternative CDS from the legacy to the new EHR system, PIM prescribing rates dropped an additional 18.8% (10.4 per 100 prescriptions; p < 0.0001). Acceptance rates of the alternative recommendations for PIMs was low overall at 11.1%. CONCLUSION The prescribing rate of PIMs in adults aged 65 years and older was successfully decreased with the implementation of prescribing CDS. This decrease was not only maintained but strengthened by the transition to a new EHR system.
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Affiliation(s)
- Michael P Friebe
- Lipscomb University College of Pharmacy and Health Sciences, Nashville, Tennessee, United States
| | - Joseph R LeGrand
- HealthIT, Vanderbilt University Medical Center, Nashville, Tennessee, United States
| | - Bryan E Shepherd
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
| | - Elizabeth A Breeden
- Lipscomb University College of Pharmacy and Health Sciences, Nashville, Tennessee, United States
| | - Scott D Nelson
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States
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