scholarly journals The CONCERN Clinical Decision Support Early Warning System: A Cluster Randomized Pragmatic Clinical Trial (Preprint)

10.2196/30238 ◽  
2021 ◽  
Author(s):  
Sarah Collins Rossetti ◽  
Patricia C. Dykes ◽  
Chris Knaplund ◽  
Min-Jeoung Kang ◽  
Kumiko Schnock ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Clinical Decision ◽  
Pragmatic Clinical Trial ◽  
System A ◽  
Cluster Randomized

Protocol for Evaluation of the CONCERN Clinical Decision Support Early Warning System: A Cluster Randomized Pragmatic Clinical Trial (Preprint)

2021 ◽  
Author(s):  
Sarah Collins Rossetti ◽  
Patricia C. Dykes ◽  
Chris Knaplund ◽  
Min-Jeoung Kang ◽  
Kumiko Schnock ◽  
...  
Keyword(s):  
Clinical Trial ◽  
At Risk ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Early Warning ◽  
Clinical Decision ◽  
Clinical Deterioration ◽  
Early Warning Score ◽  
Pragmatic Clinical Trial ◽  
Cluster Randomized

BACKGROUND The overarching goal of the COmmunicating Narrative Concerns Entered by RNs (CONCERN) study is to implement and evaluate an early warning score system which provides clinical decision support (CDS) in electronic health record systems. The CONCERN CDS uses nursing documentation patterns as indicators of nurses’ increased surveillance to predict when patients are at risk of clinical deterioration. OBJECTIVE The objective of this cluster randomized pragmatic clinical trial is to evaluate the effectiveness and usability of the CONCERN CDS system at two different study sites. The specific aim is to decrease hospitalized patients’ negative health outcomes (in-hospital mortality, length of stay, cardiac arrest, unanticipated ICU transfers, and 30-day hospital readmission rates). METHODS A multiple time-series intervention consisting of three phases will be performed through a one-year period during the cluster randomized pragmatic clinical trial. It deals with a series of processes from system release to evaluation. The system release includes CONCERN CDS implementation and user training. Then, a mixed methods approach will be conducted with end-users to assess the system and clinician perspectives. RESULTS Study results are expected in 2022. CONCLUSIONS The CONCERN CDS will increase team-based situational awareness and shared understanding of patients predicted to be at risk for clinical deterioration in need of intervention to prevent mortality and associated harm. CLINICALTRIAL ClinicalTrials.gov | Identifier: NCT03911687

scholarly journals Modified early warning score-based clinical decision support: cost impact and clinical outcomes in sepsis

JAMIA Open ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 261-268
Author(s):  
Devin J Horton ◽  
Kencee K Graves ◽  
Polina V Kukhareva ◽  
Stacy A Johnson ◽  
Maribel Cedillo ◽  
...  
Keyword(s):  
Decision Support ◽  
Acute Care ◽  
Direct Cost ◽  
Clinical Decision Support ◽  
Early Warning ◽  
Clinical Decision ◽  
Early Warning Score ◽  
Total Direct Cost ◽  
Intervention Period ◽  
Support Cost

Abstract Objective The objective of this study was to assess the clinical and financial impact of a quality improvement project that utilized a modified Early Warning Score (mEWS)-based clinical decision support intervention targeting early recognition of sepsis decompensation. Materials and Methods We conducted a retrospective, interrupted time series study on all adult patients who received a diagnosis of sepsis and were exposed to an acute care floor with the intervention. Primary outcomes (total direct cost, length of stay [LOS], and mortality) were aggregated for each study month for the post-intervention period (March 1, 2016–February 28, 2017, n = 2118 visits) and compared to the pre-intervention period (November 1, 2014–October 31, 2015, n = 1546 visits). Results The intervention was associated with a decrease in median total direct cost and hospital LOS by 23% (P = .047) and .63 days (P = .059), respectively. There was no significant change in mortality. Discussion The implementation of an mEWS-based clinical decision support system in eight acute care floors at an academic medical center was associated with reduced total direct cost and LOS for patients hospitalized with sepsis. This was seen without an associated increase in intensive care unit utilization or broad-spectrum antibiotic use. Conclusion An automated sepsis decompensation detection system has the potential to improve clinical and financial outcomes such as LOS and total direct cost. Further evaluation is needed to validate generalizability and to understand the relative importance of individual elements of the intervention.

scholarly journals Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial

2020 ◽  
Author(s):  
Nicolas Delvaux ◽  
Veerle Piessens ◽  
Tine De Burghgraeve ◽  
Pavlos Mamouris ◽  
Bert Vaes ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Laboratory Test ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Diagnostic Error ◽  
Order Sets ◽  
Cluster Randomized ◽  
Physician Order Entry ◽  
Test Ordering

Abstract Background Inappropriate laboratory test ordering poses an important burden for healthcare. Clinical decision support systems (CDSS) have been cited as promising tools to improve laboratory test ordering behavior. The objectives of this study were to evaluate the effects of an intervention that integrated a clinical decision support service into a computerized physician order entry (CPOE) on the appropriateness and volume of laboratory test ordering, and on diagnostic error in primary care.Methods This study was a pragmatic, cluster randomized, open label, controlled clinical trial. Setting 280 general practitioners (GPs) from 72 primary care practices in Belgium. Patients Patients aged ≥18 years with a laboratory test order for at least one of 17 indications; cardiovascular disease management, hypertension, check-up, chronic kidney disease (CKD), thyroid disease, type 2 diabetes mellitus, fatigue, anemia, liver disease, gout, suspicion of acute coronary syndrome (ACS), suspicion of lung embolism, rheumatoid arthritis, sexually transmitted infections (STI), acute diarrhea, chronic diarrhea, and follow-up of medication. Interventions The CDSS was integrated into a computerized physician order entry (CPOE) in the form of evidence-based order sets that suggested appropriate tests based on the indication provided by the general physician. Measurements The primary outcome of the ELMO study was the proportion of appropriate tests over the total number of ordered tests and inappropriately not-requested tests. Secondary outcomes of the ELMO study included diagnostic error, test volume and cascade activities.Results CDSS increased the proportion of appropriate tests by 0.21 (95% CI 0.16 - 0.26, p<.0001) for all tests included in the study. GPs in the CDSS arm ordered 7 (7.15 (95% CI 3.37 - 10.93, p=.0002)) tests fewer per panel. CDSS did not increase diagnostic error. The absolute difference in proportions was a decrease of 0.66% (95% CI 1.4% decrease - 0.05% increase) in possible diagnostic error.Conclusions A CDSS in the form of order sets, integrated within the CPOE improved appropriateness and decreased volume of laboratory test ordering without increasing diagnostic error. Trial Registration Clinicaltrials.gov Identifier: NCT02950142, registered on October 25, 2016Funding source This study was funded through the Belgian Health Care Knowledge Centre (KCE) Trials Programme agreement KCE16011.

The role of experience and clinical decision support in clinical trial accrual within oncology.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1527-1527
Author(s):  
Waqas Haque ◽  
Ann M. Geiger ◽  
Celette Sugg Skinner ◽  
Rasmi Nair ◽  
Simon Craddock Lee ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Clinical Trials ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Principal Investigator ◽  
Physician Practices ◽  
The Past ◽  
The Future ◽  
Clinical Trial Accrual

1527 Background: Patient accrual for cancer clinical trials is suboptimal. The complexity of applying eligibility criteria and enrolling patients may deter oncologists from recommending patients for a trial. As such, there is a need to understand how experience, training, and clinical decision support impact physician practices and intentions related to trial accrual. Methods: From May to September 2017, we conducted a survey on clinical trial accrual in a national sample of medical, surgical, and radiation oncologists. The 20-minute survey assessed barriers and facilitators to clinical trial accrual, including experience (e.g., “In the past 5 years, have you been a study or site PI of a trial?”), training (e.g., “Did you receive training about trial design and recruitment as part of medical school, residency, or fellowship? After fellowship?”), and clinical decision support (e.g., “What kind of clinical decision support has your practice implemented?). We used logistic regression to identify factors associated with frequency of discussing trials (with ≥25% of patients) and likelihood of recommending a trial to a patient (likely or very likely) in the future. Results: Survey respondents (n = 1,030) were mostly medical oncologists (59%), age 35-54 years (67%), male (74%), and not in academic practice (58%). About 18% of respondents (n = 183) reported discussing trials with ≥25% of their patients, and 80% reported being likely or very likely to recommend a trial to a patient in the future. Prior experience as principal investigator of a trial was associated with both frequency of discussing trials (OR 3.27, 95% CI 2.25, 4.75) and likelihood of recommending a trial in the future (OR 5.22, 95% CI 3.71, 7.34), as was receiving additional training in clinical trials after fellowship (discussion with patients: OR 2.48, 95% CI 1.80, 3.42; recommend in future: OR 1.92, 95% CI 1.37, 2.69). Implementing clinical decision support was not associated with discussing trials with ≥25% of patients (OR 1.12, 95% CI 0.76, 1.67), but was associated with being likely to recommend a trial in the future (OR 1.73, 95% CI 1.11, 2.71). Conclusions: In a national survey of oncologists, we observed differences in physician practices and intention related to clinical trial accrual. Whereas the vast majority (80%) reported being likely or very likely to recommend trials in the future, far fewer (20%) reported discussing trials with their patients within the past 5 years. Implementation of clinical decision support – electronic tools intended to optimize patient care and identification of patient eligibility – was not associated with frequency of past discussion of clinical trials but was associated with recommending a trial in the future. Given the stronger association between experience as a site Principal Investigator and recommending a trial, future research should explore how improving opportunities to lead a clinical trial impact trial accrual.

scholarly journals Clinical decision support improves the appropriateness of laboratory test ordering in primary care without increasing diagnostic error: the ELMO cluster randomized trial

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Nicolas Delvaux ◽  
Veerle Piessens ◽  
Tine De Burghgraeve ◽  
Pavlos Mamouris ◽  
Bert Vaes ◽  
...  
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Laboratory Test ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Diagnostic Error ◽  
Order Sets ◽  
Cluster Randomized ◽  
Physician Order Entry ◽  
Test Ordering

Abstract Background Inappropriate laboratory test ordering poses an important burden for healthcare. Clinical decision support systems (CDSS) have been cited as promising tools to improve laboratory test ordering behavior. The objectives of this study were to evaluate the effects of an intervention that integrated a clinical decision support service into a computerized physician order entry (CPOE) on the appropriateness and volume of laboratory test ordering, and on diagnostic error in primary care. Methods This study was a pragmatic, cluster randomized, open-label, controlled clinical trial. Setting Two hundred eighty general practitioners (GPs) from 72 primary care practices in Belgium. Patients Patients aged ≥ 18 years with a laboratory test order for at least one of 17 indications: cardiovascular disease management, hypertension, check-up, chronic kidney disease (CKD), thyroid disease, type 2 diabetes mellitus, fatigue, anemia, liver disease, gout, suspicion of acute coronary syndrome (ACS), suspicion of lung embolism, rheumatoid arthritis, sexually transmitted infections (STI), acute diarrhea, chronic diarrhea, and follow-up of medication. Interventions The CDSS was integrated into a computerized physician order entry (CPOE) in the form of evidence-based order sets that suggested appropriate tests based on the indication provided by the general physician. Measurements The primary outcome of the ELMO study was the proportion of appropriate tests over the total number of ordered tests and inappropriately not-requested tests. Secondary outcomes of the ELMO study included diagnostic error, test volume, and cascade activities. Results CDSS increased the proportion of appropriate tests by 0.21 (95% CI 0.16–0.26, p < 0.0001) for all tests included in the study. GPs in the CDSS arm ordered 7 (7.15 (95% CI 3.37–10.93, p = 0.0002)) tests fewer per panel. CDSS did not increase diagnostic error. The absolute difference in proportions was a decrease of 0.66% (95% CI 1.4% decrease–0.05% increase) in possible diagnostic error. Conclusions A CDSS in the form of order sets, integrated within the CPOE improved appropriateness and decreased volume of laboratory test ordering without increasing diagnostic error. Trial registration ClinicalTrials.gov Identifier: NCT02950142, registered on October 25, 2016

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