scholarly journals 375 Comparison of Electronic Clinical Decision Support for the Diagnosis of Suspected Pulmonary Embolism in Three Health Care Systems

2018 ◽  
Vol 72 (4) ◽  
pp. S147-S148 ◽  
Author(s):  
J. Bledsoe ◽  
S.S. Stevens ◽  
S.C. Woller ◽  
I.P. Brown ◽  
T. Madsen ◽  
...  
Keyword(s):  
Health Care ◽  
Pulmonary Embolism ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Health Care Systems ◽  
Clinical Decision ◽  
Suspected Pulmonary Embolism ◽  
Care Systems ◽  
Electronic Clinical Decision Support

scholarly journals Towards a Maturity Model for Clinical Decision Support Operations

2019 ◽  
Vol 10 (05) ◽  
pp. 810-819
Author(s):  
Evan W. Orenstein ◽  
Naveen Muthu ◽  
Asli O. Weitkamp ◽  
Daria F. Ferro ◽  
Mike D. Zeidlhack ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Health Care Organizations ◽  
Health Care Systems ◽  
Model Development ◽  
Clinical Decision ◽  
Maturity Model ◽  
Iterative Model ◽  
Care Systems

AbstractClinical decision support (CDS) systems delivered through the electronic health record are an important element of quality and safety initiatives within a health care system. However, managing a large CDS knowledge base can be an overwhelming task for informatics teams. Additionally, it can be difficult for these informatics teams to communicate their goals with external operational stakeholders and define concrete steps for improvement. We aimed to develop a maturity model that describes a roadmap toward organizational functions and processes that help health care systems use CDS more effectively to drive better outcomes. We developed a maturity model for CDS operations through discussions with health care leaders at 80 organizations, iterative model development by four clinical informaticists, and subsequent review with 19 health care organizations. We ceased iterations when feedback from three organizations did not result in any changes to the model. The proposed CDS maturity model includes three main “pillars”: “Content Creation,” “Analytics and Reporting,” and “Governance and Management.” Each pillar contains five levels—advancing along each pillar provides CDS teams a deeper understanding of the processes CDS systems are intended to improve. A “roof” represents the CDS functions that become attainable after advancing along each of the pillars. Organizations are not required to advance in order and can develop in one pillar separately from another. However, we hypothesize that optimal deployment of preceding levels and advancing in tandem along the pillars increase the value of organizational investment in higher levels of CDS maturity. In addition to describing the maturity model and its development, we also provide three case studies of health care organizations using the model for self-assessment and determine next steps in CDS development.

scholarly journals Trends in Imaging for Suspected Pulmonary Embolism Across US Health Care Systems, 2004 to 2016

2020 ◽  
Vol 3 (11) ◽  
pp. e2026930
Author(s):  
Ralph C. Wang ◽  
Diana L. Miglioretti ◽  
Emily C. Marlow ◽  
Marilyn L. Kwan ◽  
May K. Theis ◽  
...  
Keyword(s):  
Health Care ◽  
Pulmonary Embolism ◽  
Health Care Systems ◽  
Suspected Pulmonary Embolism ◽  
Care Systems

scholarly journals Differences, Opportunities, and Strategies in Drug Alert Optimization—Experiences of Two Different Integrated Health Care Systems

2019 ◽  
Vol 10 (05) ◽  
pp. 777-782 ◽  
Author(s):  
Salim M. Saiyed ◽  
Katherine R. Davis ◽  
David C. Kaelber
Keyword(s):  
Health Care ◽  
Decision Support ◽  
Systematic Approach ◽  
Drug Information ◽  
Health Care Systems ◽  
Clinical Decision ◽  
Health Record ◽  
Alarm Fatigue ◽  
Care Systems ◽  
Guidelines And Recommendations

Abstract Background Concerns about the number of automated medication alerts issued within the electronic health record (EHR), and the subsequent potential for alarm fatigue, led us to examine strategies and methods to optimize the configuration of our drug alerts. Objectives This article reports on comprehensive drug alerting rates and develops strategies across two different health care systems to reduce the number of drug alerts. Methods Standardized reports compared drug alert rates between the two systems, among 13 categories of drug alerts. Both health care systems made modifications to the out-of-box alerts available from their EHR and drug information vendors, focusing on system-wide approaches, when relevant, while performing more drug-specific changes when necessary. Results Drug alerting rates even after initial optimization were 38 alerts and 51 alerts per 100 drug orders, respectively. Eight principles were identified and developed to reflect the themes in the implementation and optimization of drug alerting. Conclusion A team-based, systematic approach to optimizing drug-alerting strategies can reduce the number of drug alerts, but alert rates still remain high. In addition to strategic principles, additional tactical guidelines and recommendations need to be developed to enhance out-of-the-box clinical decision support for drug alerts.

scholarly journals MP38: Barriers and facilitators to physician use of computerized clinical decision support for mild traumatic brain injury and suspected pulmonary embolism

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S54-S54
Author(s):  
S. Arnold ◽  
D. Grigat ◽  
J. E. Andruchow ◽  
A. D. McRae ◽  
G. Innes ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Pulmonary Embolism ◽  
Decision Support ◽  
Brain Injury ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Barriers And Facilitators ◽  
Evidence Based ◽  
Emergency Physicians ◽  
Suspected Pulmonary Embolism

Introduction: As utilization of CT imaging has risen dramatically, evidence-based decision rules and clinical decision support (CDS) tools have been developed to avoid unnecessary CT use in low risk patients. However, their ability to change physician practice has been limited to date, with a number of barriers cited. The purpose of this study was to identify the barriers and facilitators to CDS adoption following a local CDS implementation. Methods: All emergency physicians at 4 urban EDs and 1 urgent care center were randomized to voluntary evidence-based CT imaging CDS for patients with either mild traumatic brain injury (MTBI) or suspected pulmonary embolism (PE). CDS was integrated into the computerized physician order entry (CPOE) software and triggered whenever a CT scan for an eligible patient was ordered. Physicians in both the MTBI and PE arms were ranked according to their CDS use, and a stratified sampling strategy was used to randomly select 5 physicians from each of the low, medium and high CDS use tertiles in each study arm. Each physician was invited to participate in a 30-minute semi-structured interview to assess the barriers and facilitators to CDS use. Physician responses were reported using a thematic analysis. Results: A total of 202 emergency physicians were randomized to receive CDS for either MTBI or PE, triggering CDS 4561 times, and interacting with the CDS software 1936 times (42.4%). Variation in CDS use ranged from 0% to 88.9% of eligible encounters by physician. Fourteen physicians have participated in interviews to date, and data collection is ongoing. Physicians reported that CDS use was facilitated by their confidence in the evidence supporting the CDS algorithms and that it provided documentation to reduce medico-legal risk. CDS use was not impeded by concerns over missed diagnoses or patient expectations. Reported barriers to CDS use included suboptimal integration into the CPOE such as the inability to auto-populate test results, it disrupted the ordering process and was time consuming. A common concern was that CDS was implemented too late in workflow as most decision making takes place at the bedside. Physicians did not view CDS as infringing on physician autonomy, however they advised that CDS should be a passive educational option and should not automatically trigger for all physicians and eligible encounters. Conclusion: Physicians were generally supportive of CDS integration into practice, and were confident that CDS is an evidence-based way to reduce unnecessary CT studies. However, concerns were raised about the optimal integration of CDS into CPOE and workflow. Physicians also stated a preference to a passive educational approach to CDS rather than an automatic triggering mechanism requiring clinical documentation.

scholarly journals LO73: A randomized controlled trial of electronic clinical decision support to reduce unnecessary CT imaging for patients with suspected pulmonary embolism

CJEM ◽  
2018 ◽  
Vol 20 (S1) ◽  
pp. S32-S33
Author(s):  
J.E. Andruchow ◽  
D. Grigat ◽  
A.D. McRae ◽  
T. Abedin ◽  
D. Wang ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Randomized Controlled Trial ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Controlled Trial ◽  
Clinical Decision ◽  
Evidence Based ◽  
Index Visit ◽  
Randomized Controlled ◽  
Electronic Clinical Decision Support

Introduction: Utilization of CT pulmonary angiography (CTPA) to rule out pulmonary embolism (PE) has risen dramatically but diagnostic yield has fallen over the past several decades, suggesting that lower risk patients are being tested. Given little evidence to suggest improved patient outcomes with higher CTPA utilization, and increasing evidence of harm, evidence-based guidelines have been developed to reduce unnecessary CTPA use. The objective of this study was to assess the impact of an electronic clinical decision support (CDS) intervention to reduce unnecessary CTPA utilization for emergency department (ED) patients with suspected PE. Methods: This was a cluster-randomized, controlled trial with physicians as the unit of randomization. All emergency physicians (EPs) at 4 urban adult EDs and 1 urgent care center were randomly assigned to receive either evidence-based imaging CDS for patients with suspected PE (intervention) or no CDS (control) over a 1-year study period. CDS was launched in an external web browser whenever an intervention EP ordered a CTPA from the computerized physician order entry software for ED patients CTAS 2-5; however, physician interaction with CDS was voluntary. The CDS tool enabled calculation of patient-specific information, including the patients Wells score, PERC score, and age-adjusted D-dimer, as well as prediction of each patients pre-test risk of PE along with an imaging/no imaging recommendation. CDS recommendations could be printed for the medical record as could educational patient handouts to support physician decision-making. The primary outcome was CTPA utilization for patients with CEDIS chief complaints of shortness of breath or chest pain on the index visit. Secondary outcomes included index visit length of stay (LOS), and CTPA use or VTE diagnosis within 90-days. This study was REB approved. Results: Demographics were similar among intervention and control EPs; however, during a 2-year pre-intervention period control EPs had a higher baseline CTPA rate (8.5% vs 7.7%, p<0.001). In the first 8-months following CDS implementation, 94 intervention EPs saw 9,609 patients and voluntarily interacted with the CDS tool on 43.2% of eligible encounters while 91 control EPs saw 9,498 patients. CTPA utilization was higher among intervention EPs than control (9.6% vs 8.3%, p<0.001) as was ED LOS (302 vs 287 minutes, p<0.001). There was no difference in 90-day CTPA use or VTE diagnoses. Conclusion: In one of the largest RCTs of CDS to date, exposure to CDS was associated with higher rates of CTPA utilization and longer ED LOS on the index visit, and no difference in 90-day CT use or VTE diagnoses. These results differ from a concurrent study of CDS for patients with mild traumatic brain injury in the same physician population and may relate to the implementation of the CDS intervention and/or complexity of the underlying evidence-based algorithms.

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