Browsing by Subject "Clinical decision support systems"

Now showing 1 - 5 of 5
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    A research agenda to support the development and implementation of genomics-based clinical informatics tools and resources
    (Oxford University Press, 2022) Wiley, Ken; Findley, Laura; Goldrich, Madison; Rakhra-Burris, Tejinder K.; Stevens, Ana; Williams, Pamela; Bult, Carol J.; Chisholm, Rex; Deverka, Patricia; Ginsburg, Geoffrey S.; Green, Eric D.; Jarvik, Gail; Mensah, George A.; Ramos, Erin; Relling, Mary V.; Roden, Dan M.; Rowley, Robb; Alterovitz, Gil; Aronson, Samuel; Bastarache, Lisa; Cimino, James J.; Crowgey, Erin L.; Del Fiol, Guilherme; Freimuth, Robert R.; Hoffman, Mark A.; Jeff, Janina; Johnson, Kevin; Kawamoto, Kensaku; Madhavan, Subha; Mendonca, Eneida A.; Ohno-Machado, Lucila; Pratap, Siddharth; Overby Taylor, Casey; Ritchie, Marylyn D.; Walton, Nephi; Weng, Chunhua; Zayas-Cabán, Teresa; Manolio, Teri A.; Williams, Marc S.; Pediatrics, School of Medicine
    Objective: The Genomic Medicine Working Group of the National Advisory Council for Human Genome Research virtually hosted its 13th genomic medicine meeting titled "Developing a Clinical Genomic Informatics Research Agenda". The meeting's goal was to articulate a research strategy to develop Genomics-based Clinical Informatics Tools and Resources (GCIT) to improve the detection, treatment, and reporting of genetic disorders in clinical settings. Materials and methods: Experts from government agencies, the private sector, and academia in genomic medicine and clinical informatics were invited to address the meeting's goals. Invitees were also asked to complete a survey to assess important considerations needed to develop a genomic-based clinical informatics research strategy. Results: Outcomes from the meeting included identifying short-term research needs, such as designing and implementing standards-based interfaces between laboratory information systems and electronic health records, as well as long-term projects, such as identifying and addressing barriers related to the establishment and implementation of genomic data exchange systems that, in turn, the research community could help address. Discussion: Discussions centered on identifying gaps and barriers that impede the use of GCIT in genomic medicine. Emergent themes from the meeting included developing an implementation science framework, defining a value proposition for all stakeholders, fostering engagement with patients and partners to develop applications under patient control, promoting the use of relevant clinical workflows in research, and lowering related barriers to regulatory processes. Another key theme was recognizing pervasive biases in data and information systems, algorithms, access, value, and knowledge repositories and identifying ways to resolve them.
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    Health care providers’ perceptions of use and influence of clinical decision support reminders: qualitative study following a randomized trial to improve HPV vaccination rates
    (BMC, 2017-08-10) Dixon, Brian E.; Kasting, Monica L.; Wilson, Shannon; Kulkarni, Amit; Zimet, Gregory D.; Downs, Stephen M.; Epidemiology, School of Public Health
    Background Human Papillomavirus (HPV) leads to serious health issues and remains the most common sexually transmitted infection. Despite availability of effective vaccines, HPV vaccination rates are suboptimal. Furthermore, providers recommend the HPV vaccine less than half the time for eligible patients. Prior informatics research has demonstrated the effectiveness of computer-based clinical decision support (CDS) in changing provider behavior, especially in the area of preventative services. Methods Following a randomized clinical trial to test the effect of a CDS intervention on HPV vaccination rates, we conducted semi-structured interviews with health care providers to understand whether they noticed the CDS reminders and why providers did or did not respond to the prompts. Eighteen providers, a mix of medical doctors and nurse practitioners, were interviewed from five publicly-funded, urban health clinics. Interview data were qualitatively analyzed by two independent researchers using inductive content analysis. Results While most providers recalled seeing the CDS reminders, few of them perceived the intervention as effective in changing their behavior. Providers stated many reasons for why they did not perceive a change in their behavior, yet the results of the trial showed HPV vaccination rates increased as a result of the intervention. Conclusions CDS reminders may be effective at changing provider behavior even if providers perceive them to be of little use. Trial registration ClinicalTrials.gov Identifier: NCT02551887 , Registered on September 15, 2015 Electronic supplementary material The online version of this article (doi:10.1186/s12911-017-0521-6) contains supplementary material, which is available to authorized users.
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    Improving Patient-Centered Communication about Sudden Unexpected Death in Epilepsy through Computerized Clinical Decision Support
    (Thieme, 2021) Grout, Randall W.; Buchhalter, Jeffrey; Patel, Anup D.; Brin, Amy; Clark, Ann A.; Holmay, Mary; Story, Tyler J.; Downs, Stephen M.; Pediatrics, School of Medicine
    Background: Sudden unexpected death in epilepsy (SUDEP) is a rare but fatal risk that patients, parents, and professional societies clearly recommend discussing with patients and families. However, this conversation does not routinely happen. Objectives: This pilot study aimed to demonstrate whether computerized decision support could increase patient communication about SUDEP. Methods: A prospective before-and-after study of the effect of computerized decision support on delivery of SUDEP counseling. The intervention was a screening, alerting, education, and follow-up SUDEP module for an existing computerized decision support system (the Child Health Improvement through Computer Automation [CHICA]) in five urban pediatric primary care clinics. Families of children with epilepsy were contacted by telephone before and after implementation to assess if the clinician discussed SUDEP at their respective encounters. Results: The CHICA-SUDEP module screened 7,154 children age 0 to 21 years for seizures over 7 months; 108 (1.5%) reported epilepsy. We interviewed 101 families after primary care encounters (75 before and 26 after implementation) over 9 months. After starting CHICA-SUDEP, the number of caregivers who reported discussing SUDEP with their child's clinician more than doubled from 21% (16/75) to 46% (12/26; p = 0.03), and when the parent recalled who brought up the topic, 80% of the time it was the clinician. The differences between timing and sampling methodologies of before and after intervention cohorts could have led to potential sampling and recall bias. Conclusion: Clinician-family discussions about SUDEP significantly increased in pediatric primary care clinics after introducing a systematic, computerized screening and decision support module. These tools demonstrate potential for increasing patient-centered education about SUDEP, as well as incorporating other guideline-recommended algorithms into primary and subspecialty cares.
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    Iterative Development and Evaluation of a Pharmacogenomic-Guided Clinical Decision Support System for Warfarin Dosing
    (Schattauer, 2016-11-23) Melton, Brittany L.; Zillich, Alan J.; Saleem, Jason J.; Russ, Alissa L.; Tisdale, James E.; Overholser, Brian R.; Medicine, School of Medicine
    Objective Pharmacogenomic-guided dosing has the potential to improve patient outcomes but its implementation has been met with clinical challenges. Our objective was to develop and evaluate a clinical decision support system (CDSS) for pharmacogenomic-guided warfarin dosing designed for physicians and pharmacists. Methods Twelve physicians and pharmacists completed 6 prescribing tasks using simulated patient scenarios in two iterations (development and validation phases) of a newly developed pharmacogenomic-driven CDSS prototype. For each scenario, usability was measured via efficiency, recorded as time to task completion, and participants’ perceived satisfaction which were compared using Kruskal-Wallis and Mann Whitney U tests, respectively. Debrief interviews were conducted and qualitatively analyzed. Usability findings from the first (i.e. development) iteration were incorporated into the CDSS design for the second (i.e. validation) iteration. Results During the CDSS validation iteration, participants took more time to complete tasks with a median (IQR) of 183 (124–247) seconds versus 101 (73.5–197) seconds in the development iteration (p=0.01). This increase in time on task was due to the increase in time spent in the CDSS corresponding to several design changes. Efficiency differences that were observed between pharmacists and physicians in the development iteration were eliminated in the validation iteration. The increased use of the CDSS corresponded to a greater acceptance of CDSS recommended doses in the validation iteration (4% in the first iteration vs. 37.5% in the second iteration, p<0.001). Overall satisfaction did not change statistically between the iterations but the qualitative analysis revealed greater trust in the second prototype. Conclusions A pharmacogenomic-guided CDSS has been developed using warfarin as the test drug. The final CDSS prototype was trusted by prescribers and significantly increased the time using the tool and acceptance of the recommended doses. This study is an important step toward incorporating pharmacogenomics into CDSS design for clinical testing.
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    Transforming primary medical research knowledge into clinical decision
    (American Medical Informatics Association, 2021-01-25) Dexter, Paul R.; Grout, Randall W.; Embi, Peter J.; Medicine, School of Medicine
    While the utility of computerized clinical decision support (CCDS) for multiple select clinical domains has been clearly demonstrated, much less is known about the full breadth of domains to which CCDS approaches could be productively applied. To explore the applicability of CCDS to general medical knowledge, we sampled a total of 500 primary research articles from 4 high-impact medical journals. Employing rule-based templates, we created high-level CCDS rules for 72% (361/500) of primary medical research articles. We subsequently identified data sources needed to implement those rules. Ourfindings suggest that CCDS approaches, perhaps in the form of non-interruptive infobuttons, could be much more broadly applied. In addition, our analytic methods appear to provide a means of prioritizing and quantitating the relative utility of available data sources for purposes of CCDS.