National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Adverse Drug Events (ADE) (2)
- Adverse Events (2)
- Antibiotics (1)
- Arthritis (1)
- Behavioral Health (1)
- Blood Pressure (2)
- Blood Thinners (1)
- Brain Injury (1)
- Cardiovascular Conditions (2)
- Children/Adolescents (1)
- Chronic Conditions (3)
- (-) Clinical Decision Support (CDS) (30)
- Communication (1)
- Comparative Effectiveness (1)
- COVID-19 (1)
- Diagnostic Safety and Quality (1)
- Elderly (3)
- Electronic Health Records (EHRs) (4)
- Electronic Prescribing (E-Prescribing) (1)
- Emergency Department (3)
- Emergency Medical Services (EMS) (1)
- Evidence-Based Practice (3)
- Falls (2)
- Healthcare Costs (1)
- Health Information Technology (HIT) (27)
- Health Systems (1)
- Heart Disease and Health (2)
- Hospitals (1)
- Implementation (1)
- Medicaid (1)
- Medication (7)
- Medication: Safety (1)
- Opioids (1)
- Orthopedics (1)
- Pain (2)
- Patient-Centered Healthcare (3)
- Patient-Centered Outcomes Research (4)
- Patient Safety (1)
- Pregnancy (1)
- Prevention (1)
- Primary Care (2)
- Provider: Clinician (1)
- Provider: Physician (1)
- Quality of Care (1)
- Risk (2)
- Sepsis (1)
- Shared Decision Making (14)
- Substance Abuse (1)
- Surgery (1)
- Web-Based (1)
- Women (1)
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 30 Research Studies DisplayedGomez 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
Dorr DA, Richardson JE, Bobo M
Provider perspectives on patient- and provider-facing high blood pressure clinical decision support.
This study tried to partly address the challenge of developing a patient-facing clinician decision support (CDS) for persistent high blood pressure (HBP). The authors sought to understand provider variations and rationales related to HBP guideline recommendations and perceptions regarding patient role and use of digital tools. They implemented a pilot and final survey for hypertension experts and primary care physicians. Five clinical cases were presented that queried clinicians' attitudes related to actions; variations; prioritization; patient input; importance; and barriers for HBP diagnosis, monitoring, and treatment. Fifteen hypertension experts and 14 providers took the pilot and final versions of the survey. The majority (over 80%) of providers felt the recommendations were important yet found them difficult to follow-up to 90% of the time. Provider perceptions of relative amounts of patient input and patient work for effective HBP management ranged from 22 to 100%. Reasons for variation provided included adverse effects of treatment, patient comorbidities, shared decision-making, and health care cost and access issues. Respondents were generally positive toward patient use of electronic CDS applications but worried about access to health care, nuance of recommendations, and patient understanding of the tools.
AHRQ-funded; HS26849.
Citation: Dorr DA, Richardson JE, Bobo M .
Provider perspectives on patient- and provider-facing high blood pressure clinical decision support.
Appl Clin Inform 2022 Oct;13(5):1131-40. doi: 10.1055/a-1926-0199..
Keywords: Blood Pressure, Clinical Decision Support (CDS), Shared Decision Making, Provider: Physician
Dutta S, McEvoy DS, Rubins DM
Clinical decision support improves blood culture collection before intravenous antibiotic administration in the emergency department.
This paper discusses the outcomes of using a clinical decision support (CDS) tool that was implemented in emergency departments (EDs) for sepsis patients to remind healthcare staff to take blood cultures before administration of intravenous (IV) antibiotics. The study compared timely blood culture collection outcomes prior to IV antibiotics for 54,538 adult ED patients 1 year before and after a CDS intervention implementation in the electronic health record. The baseline phase found that 46.1% had blood cultures prior to IV antibiotics, compared to 58.8% after the intervention. The CDS improved blood culture collection rates without increasing overutilization.
AHRQ-funded; HS02717.
Citation: Dutta S, McEvoy DS, Rubins DM .
Clinical decision support improves blood culture collection before intravenous antibiotic administration in the emergency department.
J Am Med Inform Assoc 2022 Sep 12;29(10):1705-14. doi: 10.1093/jamia/ocac115..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Antibiotics, Emergency Department, Medication, Sepsis
Gallo T, Heise CW, Woosley RL
Clinician satisfaction with advanced clinical decision support to reduce the risk of torsades de pointes.
The purpose of this study was to create an advanced torsades de pointes (TdP) clinical decision support (CDS) advisory that provides relevant, patient-specific information, including 1-click management options, and to evaluate clinician satisfaction with the CDS. The researchers implemented the advanced TdP CDS across a health system comprising 29 hospitals. A brief electronic survey was developed to collect clinician feedback on the advisory and was emailed to 442 clinicians who received the advisory. Feedback was generally positive across the 38 responding providers, with 79% of respondents reporting that the advisory assisted with their care for their patients and 87% responding that the alerts clearly specified alternative actions. The researchers concluded that providers who receive an advanced TdP risk CDS alert generally view the alert favorably.
AHRQ-funded; HS026662.
Citation: Gallo T, Heise CW, Woosley RL .
Clinician satisfaction with advanced clinical decision support to reduce the risk of torsades de pointes.
J Patient Saf 2022 Sep 1;18(6):e1010-e13. doi: 10.1097/pts.0000000000000996..
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Risk, Provider: Clinician, Heart Disease and Health, Cardiovascular Conditions
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
Salloum RG, Bilello L, Bian J
Study protocol for a type III hybrid effectiveness-implementation trial to evaluate scaling interoperable clinical decision support for patient-centered chronic pain management in primary care.
The objective of this 3-year project is to study the adaptation and implementation of an existing interoperable clinical decision support (CDS) tool for pain treatment shared decision making, with tailored implementation support, in new clinical settings in the OneFlorida Clinical Research Consortium. The evaluation will be organized by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, with an adaptation and tailoring of PainManager, an open source interoperable CDS tool. It is anticipated that this evaluation will establish the feasibility and obtain preliminary data in preparation for a multi-site pragmatic trial targeting the effectiveness of PainManager and tailored implementation support on shared decision making and patient-reported pain and physical function.
AHRQ-funded; R18 HS028584.
Citation: Salloum RG, Bilello L, Bian J .
Study protocol for a type III hybrid effectiveness-implementation trial to evaluate scaling interoperable clinical decision support for patient-centered chronic pain management in primary care.
Implement Sci 2022 Jul 15;17(1):44. doi: 10.1186/s13012-022-01217-4..
Keywords: Clinical Decision Support (CDS), Pain, Chronic Conditions, Primary Care, Health Information Technology (HIT), Patient-Centered Outcomes Research, Patient-Centered Healthcare
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
Reese T, Wright A, Liu S
Improving the specificity of drug-drug interaction alerts: can it be done?
A lack of accuracy and specificity of medication alerts have an impact on alert fatigue, high rates of override, and harm to the patient. The drugs that activate alerts are frequently grouped inconsistently into value sets, and alerts for drug-drug interactions (DDI) often do not account for the factors that could decrease risk. The purpose of this proof-of-concept study was to identify and bring attention to the inconsistency of drug value sets for activating alerts, as well as provide a method of classifying factors that can be utilized to alter the risk of harm from a DDI. The researchers included 15 well-known DDIs, and utilized 3 drug interaction references to isolate 2 drug value sets as well as order- and patient-related factors for each DDI. The study reported 30 value sets, with 56% of value sets (17) having nonsignificant agreement, with average moderate agreement among the remaining 13 value sets. Thirty-three factors were identified that could decrease risk in 93% (14) of the 15 DDIs. The researchers concluded that the study shows the value of improving the consistency of DDI-alerting drug value sets, and ways in which alert usefulness and specificity can be improved.
AHRQ-funded; HS025984; HS023826.
Citation: Reese T, Wright A, Liu S .
Improving the specificity of drug-drug interaction alerts: can it be done?
Am J Health Syst Pharm 2022 Jun 23;79(13):1086-95. doi: 10.1093/ajhp/zxac045..
Keywords: Adverse Drug Events (ADE), Adverse Events, Medication, Clinical Decision Support (CDS), Health Information Technology (HIT)
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
Villa Zapata L, Subbian V, Boyce RD
Overriding drug-drug interaction alerts in clinical decision support systems: a scoping review.
The authors reviewed published data on the rate of Drug-Drug Interactions (DDI) alert overrides and medications involved in the overrides. Among 34 eligible studies, they found that the override rate of DDI alerts ranged from 55% to 98%, with more than half of the studies reporting the most common drug pairs or medications involved in acceptance or overriding of alerts. They recommended decision support systems that take user, drug, and institutional factors into consideration, as well as actionable metrics to better characterize harm associated with overrides.
AHRQ-funded; HS025984; HS023826.
Citation: Villa Zapata L, Subbian V, Boyce RD .
Overriding drug-drug interaction alerts in clinical decision support systems: a scoping review.
Stud Health Technol Inform 2022 Jun 6;290:380-84. doi: 10.3233/shti220101..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Adverse Drug Events (ADE), Adverse Events, Medication
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)
Allen KS, Danielson EC, Downs SM
Evaluating a prototype clinical decision support tool for chronic pain treatment in primary care.
This study evaluates a prototype decision support tool to aid primary care clinicians when caring for patients with chronic noncancer pain called The Chronic Pain Treatment Tracker (Tx Tracker). The authors conducted 12 semi-structured interviews with primary care clinicians from four Indiana health systems. The interviews were conducted in two waves, with the last 6 interviews prototype and interview guide revisions. The interviews explored the Tx Tracker using a think-aloud approach and a clinical scenario. Evaluation questions were also asked. The researchers identified several themes: the need for clinicians to be presented with a comprehensive patient history, the usefulness of Tx Tracker in patient discussions about treatment planning, potential usefulness of Tx Tracker for patients with high uncertainty or risk, potential usefulness of Tx Tracker in aggregating scattered information, variability in expectations about workflows, skepticism about underlying electronic health record data quality, interest in using Tx Tracker to annotate or update information, interest in using Tx Tracker to translate information to clinical action, desire for interface with visual cues for risks, warnings, or treatment options, and desire for interactive functionality.
AHRQ-funded; HS023306.
Citation: Allen KS, Danielson EC, Downs SM .
Evaluating a prototype clinical decision support tool for chronic pain treatment in primary care.
Appl Clin Inform 2022 May;13(3):602-11. doi: 10.1055/s-0042-1749332..
Keywords: Clinical Decision Support (CDS), Primary Care, Chronic Conditions, Health Information Technology (HIT)
Jiang S, Mathias PC, Hendrix N
Implementation of pharmacogenomic clinical decision support for health systems: a cost-utility analysis.
This paper describes a cost-effectiveness model that was constructed to assess the clinical and economic value of a clinical decision support (CDS) alert program that provides pharmacogenomic (PGx) testing results compared to no alert program in acute coronary syndrome (ACS) and atrial fibrillation (AF) from a health system perspective. The authors projected that 20% of 500,000 health-system members between the ages of 55 and 65 received PGx testing for CYP2C19 (ACS-clopidogrel) and CYP2C9, CYP4F2 and VKORC1 (AF-warfarin) annually. Clinical events, costs, and quality-adjusted life years (QALYs) were calculated for CYP2C19 (ACS-clopidogrel) and CYP2C9, CYP4F2 and VKORC1 (AF-warfarin) testing outcomes annually. Clinical events, costs, and quality-adjusted life years (QALYs) over 20 years were calculated with an annual discount rate of 3%. A total of 3169 alerts would be fired. The CDS alert program was predicted to help avoid 16 major clinical events and 6 deaths for ACS; and 2 clinical events and 0.9 deaths for AF. The incremental cost-effectiveness ratio was measured as $39,477/QALY, which would make the alert program cost-effective.
AHRQ-funded; HS026544.
Citation: Jiang S, Mathias PC, Hendrix N .
Implementation of pharmacogenomic clinical decision support for health systems: a cost-utility analysis.
Pharmacogenomics J 2022 May;22(3):188-97. doi: 10.1038/s41397-022-00275-7..
Keywords: Clinical Decision Support (CDS), Healthcare Costs, Health Systems, Health Information Technology (HIT)
van Leeuwen D, Mittelman M, Fabian L
AHRQ Author: Lomotan EA
Nothing for me or about me, without me: codesign of clinical decision support.
The purpose of this case study was to describe models such as virtual focus groups, social media, and agile software development, for effectively engaging patients and caregivers in a federal program during clinical decision support (CDS) development, and to encourage developers of CDS systems to collaborate with patients and their caregivers to increase the potential impact of CDS. The study found that impact on the federal program was sizable and resulted in a number of improved CDS resources and improved engagement of patient and caregiver communities in continuing projects. The researchers concluded that while a number of approaches may be effective, an iterative, highly collaborative process shows the greatest potential.
AHRQ-authored; AHRQ-funded; 75FCMC18D0047; 75Q80119F80005.
Citation: van Leeuwen D, Mittelman M, Fabian L .
Nothing for me or about me, without me: codesign of clinical decision support.
Appl Clin Inform 2022 May;13(3):641-46. doi: 10.1055/s-0042-1750355..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT)
Grauer A, Kneifati-Hayek J, Reuland B
Indication alerts to improve problem list documentation.
This study examined the effects of alerts integrated into the inpatient and outpatient computerized provider order entry systems to assist in adding problems to the problems list when ordering medications that lacked a corresponding indication. Medication orders from 2 healthcare systems that used an innovative indication alert were analyzed. Data from site 1 was collected between December 2018 and January 2020, and at site 2 between May and June 2021. Alerts were triggered 131,34 times at site 1, and 6178 times at site 2. The authors reviewed samples of 100 charts that had problems added in response to the alert. Of those, reviewers deemed 88% ± 3% at site 1 and 91% ± 3% at site 2 to be accurate, respectively.
AHRQ-funded; HS024945; HS026121.
Citation: Grauer A, Kneifati-Hayek J, Reuland B .
Indication alerts to improve problem list documentation.
J Am Med Inform Assoc 2022 Apr 13;29(5):909-17. doi: 10.1093/jamia/ocab285..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT)
Bui LN, Marshall C, Miller-Rosales C
Hospital adoption of electronic decision support tools for preeclampsia management.
Maternal morbidity and mortality can be reduced by the utilization of evidence-based clinical guidelines for preeclampsia management. Electronic health record (EHR)-based clinical decision support tools can improve the use of those guidelines. The purpose of this study was to investigate the organizational capabilities and hospital adoption of HER-based decision tools for preeclampsia management. The researchers conducted a cross-sectional analysis of hospitals that provided obstetric care in 2017. A total of 739 hospitals that responded to the 2017-2018 National Survey of Healthcare Organizations and Systems (NSHOS) and their results were linked to the 2017 Area Health Resources File (AHRF) and the American Hospital Association (AHA) Annual Survey Database. A final total of 425 hospitals from 49 states were analyzed. The primary outcome of the analysis was whether a hospital adopted EHR-based clinical decision support tools for preeclampsia management. The study found that 68% of the hospitals utilized EHR-based decision support tools for preeclampsia, and that hospitals with a single EHR system were more likely to adopt EHR-based decision support tools for preeclampsia than hospitals with multiple systems, including a combination of EHR and paper-based systems. The researchers also determined that hospitals with more processes to disseminate best patient care practices were more likely to adopt EHR-based decision support tools for preeclampsia management. The study concluded that having standardized EHRs and policies to disseminate evidence can help hospitals advance the use of EHR-based decision support tools for preeclampsia management in those hospitals that have not yet adopted them.
AHRQ-funded; HS024075.
Citation: Bui LN, Marshall C, Miller-Rosales C .
Hospital adoption of electronic decision support tools for preeclampsia management.
Qual Manag Health Care 2022 Apr-Jun;31(2):59-67. doi: 10.1097/qmh.0000000000000328..
Keywords: Clinical Decision Support (CDS), Electronic Health Records (EHRs), Health Information Technology (HIT), Hospitals, Pregnancy, Women
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)
Greenberg JK, Otun A, Kyaw PT
Usability and acceptability of clinical decision support based on the KIIDS-TBI tool for children with mild traumatic brain injuries and intracranial injuries.
The Kids Intracranial Injury Decision Support tool for Traumatic Brain Injury (KIIDS-TBI) is a validated risk prediction model designed to manage children with mild traumatic brain injuries (mTBI) and intracranial injuries. Implementing electronic clinical decision support (CDS) may help integrate this evidence-based guidance into clinical practice. The purpose of this study was to assess the acceptability and usability of an electronic CDS tool for managing children with mTBI and intracranial injuries. Emergency medicine and neurosurgery physicians (10 each) from 10 hospitals in the United States participated in usability testing of a novel CDS prototype within a simulated electronic health record environment. The testing involved a think-aloud protocol, an acceptability and usability survey, and a semi-structured interview. The prototype underwent two updates during testing based on user feedback. Usability issues identified in the videos were categorized using content analysis, while interview transcripts were analyzed using thematic analysis. The study found that of the 20 participants, the majority worked at teaching hospitals (80%), freestanding children's hospitals (95%), and level-1 trauma centers (75%). During the two prototype updates, issues with clarity of terminology and navigation within the CDS interface were identified and resolved. As a result, the number of usability problems decreased from 35 in phase 1 to 8 in phase 3, and the number of errors made dropped from 18 in phase 1 to 2 in phase 3. According to the survey, 90% of participants found the tool easy to use, 95% found the tool useful in determining a patient's level of care, 90% found it likely to improve resource utilization, and 79% found it likely to improve patient safety. Interview themes focused on the CDS's capability to support evidence-based decision-making and enhance clinical workflow, as well as suggested implementation strategies and potential challenges.
AHRQ-funded; HS027075.
Citation: Greenberg JK, Otun A, Kyaw PT .
Usability and acceptability of clinical decision support based on the KIIDS-TBI tool for children with mild traumatic brain injuries and intracranial injuries.
Appl Clin Inform 2022 Mar; 13(2):456-67. doi: 10.1055/s-0042-1745829..
Keywords: Children/Adolescents, Clinical Decision Support (CDS), Brain Injury, 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
Patterson ES, Rayo MF, Edworthy JR
Applying human factors engineering to address the telemetry alarm problem in a large medical center.
Alarms in hospitals are frequently misunderstood, disregarded, and overridden.
The purpose of this study was to address the alarm problem by redesigning, reorganizing, and reprioritizing to better discriminate alarm sounds and displays in a hospital. The investigators concluded that this unique collaboration allowed them to make progress on the alarm problem by making unintuitive leaps, avoiding common missteps, and refuting conventional healthcare approaches.
The purpose of this study was to address the alarm problem by redesigning, reorganizing, and reprioritizing to better discriminate alarm sounds and displays in a hospital. The investigators concluded that this unique collaboration allowed them to make progress on the alarm problem by making unintuitive leaps, avoiding common missteps, and refuting conventional healthcare approaches.
AHRQ-funded; HS024379.
Citation: Patterson ES, Rayo MF, Edworthy JR .
Applying human factors engineering to address the telemetry alarm problem in a large medical center.
Hum Factors 2022 Feb;64(1):126-42. doi: 10.1177/00187208211018883..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT)