National Healthcare Quality and Disparities Report
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Topics
- Adverse Drug Events (ADE) (1)
- Adverse Events (1)
- Arthritis (2)
- Behavioral Health (1)
- Blood Thinners (1)
- Brain Injury (1)
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- Clinical Decision Support (CDS) (17)
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- Elderly (3)
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- Falls (2)
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- Guidelines (1)
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- (-) Health Information Technology (HIT) (26)
- Heart Disease and Health (1)
- Imaging (1)
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- Substance Abuse (1)
- Surgery (2)
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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 25 of 26 Research Studies DisplayedNg MY, Kapur S, Blizinsky KD
The AI life cycle: a holistic approach to creating ethical AI for health decisions.
This article provides an overview of the reimagined artificial intelligence (AI) lifecycle to create ethical AI for health decisions. The lifecycle is data creation, data acquisition, model development, model evaluation, and model deployment. AI biases in each phase are described and recommendations are made to address each one.
AHRQ-funded; HS027434.
Citation: Ng MY, Kapur S, Blizinsky KD .
The AI life cycle: a holistic approach to creating ethical AI for health decisions.
Nat Med 2022 Nov;28(11):2247-49. doi: 10.1038/s41591-022-01993-y..
Keywords: Health Information Technology (HIT), Shared Decision Making
Gomez Lumbreras A, Reese TJ, Del Fiol G
Shared decision-making for drug-drug interactions: formative evaluation of an anticoagulant drug interaction.
This study evaluated a tool called DDInteract that was developed to enhance and support shared decision-making (SDM) between patients and physicians when both warfarin and NSAIDs are used concurrently. The study used case vignettes with physicians and patients on warfarin to conduct simulated virtual clinical encounters where they discussed the use of taking ibuprofen and warfarin concurrently and determined an appropriate therapeutic plan based on the patient’s individualized risk. Participants completed a postsession interview and SDM process survey, including the 9-item Shared Decision-Making Questionnaire (SDM-Q-9), tool usability and workload National Aeronautics and Space Administration (NASA) Task Load Index, Unified Theory of Acceptance and Use of Technology (UTAUT), Perceived Behavioral Control (PBC) scale, System Usability Scale (SUS), and Decision Conflict Scale (DCS). A total of 12 physician-patient dyads were used, with over 91% of the patients over 50 and 75% had been taking warfarin for over 2 years. Most participants rated DDInteract higher than usual care (UC) and would be willing to use the tool for an interaction involving warfarin and NSAIDs.
AHRQ-funded; HS027099.
Citation: Gomez Lumbreras A, Reese TJ, Del Fiol G .
Shared decision-making for drug-drug interactions: formative evaluation of an anticoagulant drug interaction.
JMIR Form Res 2022 Oct 19;6(10):e40018. doi: 10.2196/40018..
Keywords: Shared Decision Making, Medication, Blood Thinners, Clinical Decision Support (CDS), Health Information Technology (HIT), Medication: Safety, Patient Safety
Weiner SJ, Schwartz A, Weaver F
Effect of electronic health record clinical decision support on contextualization of care: a randomized clinical trial.
Researchers sought to determine whether contextualized clinical decision support (CDS) tools in the electronic health record (EHR) improve clinician contextual probing, attention to contextual factors in care planning, and the presentation of contextual red flags. In this randomized clinical trial, they found that contextualized CDS did not improve patients' outcomes but did increase contextualization of their care, suggesting that use of this technology could ultimately help to improve outcomes.
AHRQ-funded; HS025374.
Citation: Weiner SJ, Schwartz A, Weaver F .
Effect of electronic health record clinical decision support on contextualization of care: a randomized clinical trial.
JAMA Netw Open 2022 Oct;5(10):e2238231. doi: 10.1001/jamanetworkopen.2022.38231..
Keywords: Electronic Health Records (EHRs), Clinical Decision Support (CDS), Health Information Technology (HIT), Shared Decision Making
Kagarmanova A, Sparkman H, Laiteerapong N
Improving the management of chronic pain, opioid use, and opioid use disorder in older adults: study protocol for i-cope study.
This article describes a protocol for an upcoming study on the planned implementation and evaluation of I-COPE (Improving Chicago Older Adult Opioid and Pain Management through Patient-centered Clinical Decision Support and Project ECHO®) to improve care for older adults with chronic pain, opioid use, and opioid use disorder (OUD). The study will be implemented in 35 clinical sites across the metropolitan Chicago area for patients aged ≥ 65 with chronic pain, opioid use, or OUD who receive primary care at one of the clinics. I-COPE includes the integration of patient-reported data on symptoms and preferences, clinical decision support tools and shared decision making into routine primary care. Primary care providers will be trained on the tools through web-based videos and an optional Project ECHO® course, entitled "Pain Management and OUD in Older Adults." A framework called RE-AIM will be used to assess the I-COPE implementation. Outcomes considered effective include an increased variety of recommended pain treatments, decreased prescriptions of higher-risk pain treatments, and decreased patient pain scores. Outcomes will be evaluated at 6 and 12 months after implementation, and PCPs participating in Project ECHO® will be evaluated on changes in knowledge, attitudes, and self-efficacy using pre- and post-course surveys.
AHRQ-funded; HS027910.
Citation: Kagarmanova A, Sparkman H, Laiteerapong N .
Improving the management of chronic pain, opioid use, and opioid use disorder in older adults: study protocol for i-cope study.
Trials 2022 Jul 27;23(1):602. doi: 10.1186/s13063-022-06537-w..
Keywords: Elderly, Pain, Chronic Conditions, Opioids, Medication, Substance Abuse, Behavioral Health, Clinical Decision Support (CDS), Shared Decision Making, Health Information Technology (HIT)
Hinson JS, Klein E, Smith A
Multisite implementation of a workflow-integrated machine learning system to optimize COVID-19 hospital admission decisions.
This study’s objective was to develop, implement, and evaluate an electronic health record (EHR) embedded clinical decision support (CDS) system that leveraged machine learning (ML) to estimate short-term risk for clinical deterioration in patients with or under investigation for COVID-19. The system translates model-generated risk for critical care needs within 24 hours and inpatient care needs within 72 hours into rapidly interpretable COVID-19 Deterioration Risk Levels made viewable within ED clinician workflow. A retrospective cohort of 21,452 ED patients who visited one of five ED study sites was used to derive ML models and were prospectively validated in 15,670 ED visits that occurred before (n = 4322) or after (n = 11,348) CDS implementation. Model performance and numerous patient-oriented outcomes including in-hospital mortality were measured across study periods. ML model performance was excellent under all conditions. AUC ranged from 0.85 to 0.91 for prediction of critical care needs and 0.80-0.90 for inpatient care needs. Total mortality was unchanged across study periods but was reduced among high-risk patients after the implementation.
AHRQ-funded; HS026640.
Citation: Hinson JS, Klein E, Smith A .
Multisite implementation of a workflow-integrated machine learning system to optimize COVID-19 hospital admission decisions.
NPJ Digit Med 2022 Jul 16;5(1):94. doi: 10.1038/s41746-022-00646-1..
Keywords: COVID-19, Clinical Decision Support (CDS), Health Information Technology (HIT), Implementation, Electronic Health Records (EHRs), Emergency Department, Shared Decision Making
Nanji KC, Garabedian PM, Langlieb ME
Usability of a perioperative medication-related clinical decision support software application: a randomized controlled trial.
The purpose of this study was assess the usability of a newly developed, comprehensive, medication-related operating room clinical decision support (CDS) software and compare it with the standard electronic health record (EHR) medication workflow. Forty participants were randomized to a CDS group (n=20) or a control group (n=20) and asked to complete 7 simulation tasks. The study found that in a simulation setting the new CDS software improved efficiency and quality of care and reduced task time, excelling over the current EHR workflow.
AHRQ-funded; HS024764.
Citation: Nanji KC, Garabedian PM, Langlieb ME .
Usability of a perioperative medication-related clinical decision support software application: a randomized controlled trial.
J Am Med Inform Assoc 2022 Jul 12;29(8):1416-24. doi: 10.1093/jamia/ocac035..
Keywords: Medication, Clinical Decision Support (CDS), Health Information Technology (HIT), Surgery, Shared Decision Making
Dullabh P, Sandberg SF, Heaney-Huls K
AHRQ Author: Berliner E, Dymek C, Harrison MI, Swiger J
Challenges and opportunities for advancing patient-centered clinical decision support: findings from a horizon scan.
This AHRQ-authored horizon scan identified challenges and opportunities for advancing patient-centered clinical decision support (PC CDS) and future directions for PC CDS. The authors engaged a technical expert panel, conducted a scoping literature review, and interviewed key informants. They quantitatively analyzed literature and interview transcripts and mapped the findings to the 4 phases translating evidence into PC CDS interventions (Prioritizing, Authoring, Implementing, and Measuring) and to external factors. Twelve challenges were identified for PC CDS development with lack of patient input identified as a critical challenge. Lack of patient-centered terminology standards was viewed as a challenge in authoring PC CDS. They also found a dearth of CDS studies that measured clinical outcomes, creating significant gaps in the understanding of PC CDS’ impact.
AHRQ-authored; AHRQ-funded; 233201500023I.
Citation: Dullabh P, Sandberg SF, Heaney-Huls K .
Challenges and opportunities for advancing patient-centered clinical decision support: findings from a horizon scan.
J Am Med Inform Assoc 2022 Jun 14;29(7):1233-43. doi: 10.1093/jamia/ocac059.
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Keywords: Clinical Decision Support (CDS), Patient-Centered Healthcare, Health Information Technology (HIT), Shared Decision Making, Patient-Centered Outcomes Research, Evidence-Based Practice
Gallo T, Heise CW, Woosley RL
Clinician responses to a clinical decision support advisory for high risk of Torsades de pointes.
The purpose of this study was to assess provider actions taken in response to a Clinical decision support (CDS) advisory for Torsade de pointes (TdP) that uses a modified Tisdale QT risk score and presents single click management options. The researchers implemented an inpatient TdP risk advisory across a large, 30 hospital health care system. The CDS advisory was programmed to appear when prescribers attempted to order medications with a known risk of TdP in a patient. The CDS advisory displayed patient-specific information and offered related management options including canceling the requested medication and ordering relevant protocols. The study found that 7794 TdP risk advisories were issued during an 8-month period. The most frequent advisory trigger was antibiotics (33.1%.) The most frequent action taken as a result of the advisory was ordering an ECG (20.3%). Incoming medication orders were canceled in 10.2% of the advisories. The researchers concluded that a single-click, modified Tisdale QT risk score-based CDS resulted in a high action/response rate.
AHRQ-funded; HS026662.
Citation: Gallo T, Heise CW, Woosley RL .
Clinician responses to a clinical decision support advisory for high risk of Torsades de pointes.
J Am Heart Assoc 2022 Jun 7;11(11):e024338. doi: 10.1161/jaha.122.024338..
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Health Information Technology (HIT), Heart Disease and Health, Cardiovascular Conditions
Dullabh P, Heaney-Huls K, Hovey L
The technology landscape of patient-centered clinical decision support - where are we and what is needed?
This paper explores the technology landscape for patient-centered clinical decision support (PC CDS) and what has come out of Patient Centered Outcomes Research (PCOR) and health care delivery system transformation efforts. The authors explore what is needed to make it more shareable, standards-based, and publicly available with the goal of improving patient care and clinical outcomes. Three sources of information were used: (1) a 22-member technical expert panel; (2) a literature review of peer-reviewed and grey literature; and (3) key informant interviews with PC CDS stakeholders. Ten salient technical considerations that span all phases of PC CDS development were identified. Although significant progress has been made, challenges remain.
AHRQ-funded; 233201500023I.
Citation: Dullabh P, Heaney-Huls K, Hovey L .
The technology landscape of patient-centered clinical decision support - where are we and what is needed?
Stud Health Technol Inform 2022 Jun 6;290:350-53. doi: 10.3233/shti220094..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Patient-Centered Outcomes Research, Shared Decision Making
Dullabh P, Heaney-Huls K, Lobach DF
AHRQ Author: Lomotan E, Swiger J, Harrison MI, Dymek C
The technical landscape for patient-centered CDS: progress, gaps, and challenges.
The purpose of this study was to evaluate the technical landscape for patient-centered clinical decision support (PC CDS) methods to assess the gaps in making PC CDS more standard-based, publicly available, and with greater shareability. The researchers utilized qualitative data from a literature review, a panel of technical experts, and interviews with 18 CDS stakeholders to identify 7 technical considerations that span 5 phases of the development of PC CDS. The authors concluded that while there has been progress in the technical landscape, the field of CDS must focus on improving a number of CDS methods and processes, including standards for translating clinical guidelines into patient-centered clinical decision support, procedures to collect, standardize, and incorporate health data generated by patients, and other CDS processes.
AHRQ-authored; AHRQ-funded; 233201500023I.
Citation: Dullabh P, Heaney-Huls K, Lobach DF .
The technical landscape for patient-centered CDS: progress, gaps, and challenges.
J Am Med Inform Assoc 2022 May 11;29(6):1101-05. doi: 10.1093/jamia/ocac029..
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Patient-Centered Healthcare, Health Information Technology (HIT)
Rice H, Garabedian PM, Shear K
Clinical decision support for fall prevention: defining end-user needs.
The purpose of this study was to identify patient and primary care staff needs for development of a tool that will generate clinical decision support (CDS) to prevent falls and injuries in older adults. Community-dwelling patients aged 60 and over and primary care clinic staff were eligible to participate in the study; all were affiliated with the University of Florida Health Archer Family Health Care primary care clinic and the Brigham & Women's Hospital-affiliated primary care clinics. Through qualitative interviews with patients (n=18) and primary care clinic staff (n=24) user needs were identified and then categorized into the following themes: evidence-based safe exercises; expert guidance; individualized resources; in-person assessment of patient condition; motivational tools; patient understanding of fall risk; personal support networks; systematic communication and workload burden. The study concluded that personalized, actionable, and evidence-based clinical decision support may be able to address some of the many gaps that exist in fall prevention management in older adults.
AHRQ-funded; HS027557.
Citation: Rice H, Garabedian PM, Shear K .
Clinical decision support for fall prevention: defining end-user needs.
Appl Clin Inform 2022 May;13(3):647-55. doi: 10.1055/s-0042-1750360..
Keywords: Elderly, Falls, Prevention, Clinical Decision Support (CDS), Shared Decision Making, Health Information Technology (HIT)
Jacobsohn GC, Leaf M, Liao F
Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.
The authors used a collaborative and iterative approach to design and implement an automated clinical decision support system (CDS) for Emergency Department (ED) providers to identify and refer older adult ED patients at high risk of future falls. The system was developed using collaborative input from an interdisciplinary design team and integrated seamlessly into existing ED workflows. A key feature of development was the unique combination of patient experience strategies, human-centered design, and implementation science, which allowed for the CDS tool and intervention implementation strategies to be designed simultaneously. Challenges included: usability problems, data inaccessibility, time constraints, low appointment availability, high volume of patients, and others. The study concluded that using the collaborative, iterative approach was successful in achieving all project goals, and could be applied to other cases.
AHRQ-funded; HS024558.
Citation: Jacobsohn GC, Leaf M, Liao F .
Collaborative design and implementation of a clinical decision support system for automated fall-risk identification and referrals in emergency departments.
Healthc 2022 Mar;10(1):100598. doi: 10.1016/j.hjdsi.2021.100598..
Keywords: Elderly, Clinical Decision Support (CDS), Shared Decision Making, Falls, Risk, Emergency Department, Health Information Technology (HIT)
Lin E, Uhler LM, Finley EP
Incorporating patient-reported outcomes into shared decision-making in the management of patients with osteoarthritis of the knee: a hybrid effectiveness-implementation study protocol.
This article describes a US-based 2-year, two-site hybrid type 1 study to assess clinical effectiveness and implementation of a machine learning-based patient decision aid integrating patient-reported outcomes and clinical variables to support shared decision-making for patients with knee osteoarthritis considering total knee replacement. Study results will be disseminated through conference presentations, publications and professional societies.
AHRQ-funded; HS027037.
Citation: Lin E, Uhler LM, Finley EP .
Incorporating patient-reported outcomes into shared decision-making in the management of patients with osteoarthritis of the knee: a hybrid effectiveness-implementation study protocol.
BMJ Open 2022 Feb 21;12(2):e055933. doi: 10.1136/bmjopen-2021-055933..
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Arthritis, Patient-Centered Outcomes Research, Orthopedics, Health Information Technology (HIT), Evidence-Based Practice
Melnick ER, Hess EP, Guo G
Patient-centered decision support: formative usability evaluation of integrated clinical decision support with a patient decision aid for minor head injury in the emergency department.
The study’s objective was to formatively evaluate an electronic tool that not only helps clinicians at the bedside to determine the need for CT use based on the Canadian CT Head Rule but also promotes evidence-based conversations between patients and clinicians regarding patient-specific risk and patients' specific concerns. It concluded that the Concussion or Brain Bleed app is a useful and usable final product integrating clinical decision support with a patient decision aid.
AHRQ-funded; HS021271.
Citation: Melnick ER, Hess EP, Guo G .
Patient-centered decision support: formative usability evaluation of integrated clinical decision support with a patient decision aid for minor head injury in the emergency department.
J Med Internet Res 2017 May 19;19(5):e174. doi: 10.2196/jmir.7846.
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Keywords: Brain Injury, Shared Decision Making, Emergency Department, Health Information Technology (HIT), Patient-Centered Healthcare
Zikmund-Fisher BJ, Scherer AM, Witteman HO
Graphics help patients distinguish between urgent and non-urgent deviations in laboratory test results.
Most electronic health record systems provide laboratory test results to patients in table format. Researchers tested whether presenting such results in visual displays (number lines) could improve understanding. They found that visual displays reduced respondents' perceived urgency and desire to contact health care providers immediately for near-normal test results compared to tables but did not affect their perceptions of extreme values.
AHRQ-funded; HS021681.
Citation: Zikmund-Fisher BJ, Scherer AM, Witteman HO .
Graphics help patients distinguish between urgent and non-urgent deviations in laboratory test results.
J Am Med Inform Assoc 2017 May 1;24(3):520-28. doi: 10.1093/jamia/ocw169.
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Keywords: Communication, Education: Patient and Caregiver, Shared Decision Making, Electronic Health Records (EHRs), Health Information Technology (HIT)
LeRouge C, Hasselquist MB, Kellogg L
Using heuristic evaluation to enhance the visual display of a provider dashboard for patient-reported outcomes.
A human-centered design (HCD) approach to understanding the data visualization needs for patient-reported outcomes (PRO) in clinical practice can optimize the visual design of an interactive PRO system. Beyond iterative methods, the authors explored the additive value of other HCD methods such as heuristic evaluation. Their evaluation led to several recommendations to improve the display, accessibility, and interpretability of the dashboard’s data.
AHRQ-funded; HS023785.
Citation: LeRouge C, Hasselquist MB, Kellogg L .
Using heuristic evaluation to enhance the visual display of a provider dashboard for patient-reported outcomes.
eGEMS 2017 Apr 20;5(2):Article 6. doi: 10.13063/2327-9214.1283.
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Keywords: Patient-Centered Healthcare, Patient-Centered Outcomes Research, Health Information Technology (HIT), Data, Shared Decision Making
Zheng H, Tulu B, Choi W
Using mHealth app to support treatment decision-making for knee arthritis: patient perspective.
The authors explored patient preferences on content and design of a mobile health app to facilitate daily symptom capture and summary feedback reporting, in order to inform treatment decisions, including use of total knee replacement surgery (TKR). The authors suggest that user input can inform the design and implementation of mHealth technology to meet patient needs for their treatment decisions. Patient priorities must be considered through patient-centered app design.
AHRQ-funded; HS018910.
Citation: Zheng H, Tulu B, Choi W .
Using mHealth app to support treatment decision-making for knee arthritis: patient perspective.
eGEMS 2017 Apr 20;5(2):7. doi: 10.13063/2327-9214.1284..
Keywords: Arthritis, Shared Decision Making, Health Information Technology (HIT), Surgery
Ancker JS, Edwards A, Nosal S
Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system.
In this study, the investigators tested hypotheses arising from two possible alert fatigue mechanisms: (A) cognitive overload associated with amount of work, complexity of work, and effort distinguishing informative from uninformative alerts, and (B) desensitization from repeated exposure to the same alert over time. The investigators found that clinicians became less likely to accept alerts as they received more of them, particularly more repeated alerts. There was no evidence of an effect of workload per se, or of desensitization over time for a newly deployed alert.
AHRQ-funded; HS021531.
Citation: Ancker JS, Edwards A, Nosal S .
Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system.
BMC Med Inform Decis Mak 2017 Apr 10;17(1):1-9. doi: 10.1186/s12911-017-0430-8..
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Safety, Provider, Provider: Nurse, Provider: Physician
Horsky J, Aarts J, Verheul L
Clinical reasoning in the context of active decision support during medication prescribing.
The purpose of this study was to describe and analyze reasoning patterns of clinicians responding to drug-drug interaction alerts in order to understand the role of patient-specific information in the decision-making process about the risks and benefits of medication therapy. The investigators found that declining an alert suggestion was preceded by sometimes brief but often complex reasoning, prioritizing different aspects of care quality and safety, especially when the perceived risk was higher.
AHRQ-funded; HS021094.
Citation: Horsky J, Aarts J, Verheul L .
Clinical reasoning in the context of active decision support during medication prescribing.
Int J Med Inform 2017 Jan;97:1-11. doi: 10.1016/j.ijmedinf.2016.09.004..
Keywords: Adverse Drug Events (ADE), Adverse Events, Clinical Decision Support (CDS), Shared Decision Making, Electronic Health Records (EHRs), Health Information Technology (HIT), Medical Errors, Medication, Patient Safety
Heisler M, Choi H, Palmisano G
Comparison of community health worker-led diabetes medication decision-making support for low-income Latino and African American adults with diabetes using e-health tools versus print materials: a randomized, controlled trial.
This study compared outcomes between community health worker (CHW) use of a tailored, interactive, Web-based, tablet computer-delivered tool specifically developed for the study and use of printed educational materials. In a population of low-income Latino and African American adults with diabetes and relatively low levels of formal education, participants in both CHW-led interventions reported mostly similar improvements in outcomes over 3 months.
AHRQ-funded; HS019256
Citation: Heisler M, Choi H, Palmisano G .
Comparison of community health worker-led diabetes medication decision-making support for low-income Latino and African American adults with diabetes using e-health tools versus print materials: a randomized, controlled trial.
Ann Intern Med. 2014 Nov 18;161(10 Suppl):S13-22. doi: 10.7326/m13-3012..
Keywords: Health Information Technology (HIT), Diabetes, Shared Decision Making, Outcomes, Social Determinants of Health
Lacson R, Prevedello LM, Andriole KP
Four-year impact of an alert notification system on closed-loop communication of critical test results.
The authors evaluated the impact of an alert notification system on policy adherence for communicating critical imaging test results to referring providers and assessed system adoption over the first 4 years after implementation. They concluded that an automated alert notification system for communicating critical imaging results was successfully adopted and was associated with increased adherence to institutional policy for communicating critical test results and with reduced workflow interruptions.
AHRQ-funded; HS019635.
Citation: Lacson R, Prevedello LM, Andriole KP .
Four-year impact of an alert notification system on closed-loop communication of critical test results.
AJR Am J Roentgenol 2014 Nov;203(5):933-8. doi: 10.2214/ajr.14.13064.
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Keywords: Communication, Shared Decision Making, Guidelines, Health Information Technology (HIT), Imaging
Welch BM, Eilbeck K, Del Fiol G
Technical desiderata for the integration of genomic data with clinical decision support.
The objective of this study is to develop and validate a guiding set of technical desiderata for supporting the clinical use of the whole genome sequence (WGS) through clinical decision support (CDS). A panel of domain experts in genomics and CDS developed a proposed set of seven additional requirements. These additional desiderata provide important guiding principles for the technical development of CDS capabilities for the clinical use of WGS information.
AHRQ-funded; HS018352.
Citation: Welch BM, Eilbeck K, Del Fiol G .
Technical desiderata for the integration of genomic data with clinical decision support.
J Biomed Inform 2014 Oct;51:3-7. doi: 10.1016/j.jbi.2014.05.014..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Genetics, Electronic Health Records (EHRs), Shared Decision Making
Longo DR, Woolf HS
Rethinking the information priorities of patients.
Efforts have intensified to provide consumers with online data tools and consumer reports that offer profiles and statistics for evaluating specialists, hospitals, and other clinical facilities. In this article, the authors examine two key questions: what should these resources look like and do patients really want them?
AHRQ-funded; HS021902
Citation: Longo DR, Woolf HS .
Rethinking the information priorities of patients.
JAMA. 2014 May 14;311(18):1857-8. doi: 10.1001/jama.2014.3038..
Keywords: Education: Patient and Caregiver, Shared Decision Making, Quality of Care, Health Information Technology (HIT), Web-Based
Del Fiol G, Workman TE, Gorman PN
Clinical questions raised by clinicians at the point of care: a systematic review.
The researchers conducted a systematic review of studies examining the questions that clinicians raise in the context of patient care decisionmaking. They concluded that clinicians frequently raise questions about patient care in their practice. Although they are effective at finding answers to questions they pursue, roughly half of the questions are never pursued.
AHRQ-funded; HS018352.
Citation: Del Fiol G, Workman TE, Gorman PN .
Clinical questions raised by clinicians at the point of care: a systematic review.
JAMA Intern Med. 2014 May;174(5):710-8. doi: 10.1001/jamainternmed.2014.368..
Keywords: Education: Patient and Caregiver, Shared Decision Making, Health Information Exchange (HIE), Health Information Technology (HIT), Practice Patterns
Bauer NS, Carroll AE, Downs SM
Understanding the acceptability of a computer decision support system in pediatric primary care.
In this study, the investigators examine the attitudes and opinions of pediatric users' toward the Child Health Improvement through Computer Automation (CHICA) system, a computer decision support system linked to an electronic health record in four community pediatric clinics. The investigators found that pediatric users appreciated the system's automation and enhancements that allowed relevant and meaningful clinical data to be accessible at point of care.
AHRQ-funded; HS018453; HS017939.
Citation: Bauer NS, Carroll AE, Downs SM .
Understanding the acceptability of a computer decision support system in pediatric primary care.
J Am Med Inform Assoc 2014 Jan-Feb;21(1):146-53. doi: 10.1136/amiajnl-2013-001851..
Keywords: Children/Adolescents, Clinical Decision Support (CDS), Shared Decision Making, Electronic Health Records (EHRs), Health Information Technology (HIT), Primary Care