National Healthcare Quality and Disparities Report
Latest available findings on quality of and access to health care
Data
- Data Infographics
- Data Visualizations
- Data Tools
- Data Innovations
- All-Payer Claims Database
- Healthcare Cost and Utilization Project (HCUP)
- Medical Expenditure Panel Survey (MEPS)
- AHRQ Quality Indicator Tools for Data Analytics
- State Snapshots
- United States Health Information Knowledgebase (USHIK)
- Data Sources Available from AHRQ
Search All Research Studies
AHRQ Research Studies Date
Topics
- Adverse Drug Events (ADE) (15)
- Adverse Events (16)
- Ambulatory Care and Surgery (4)
- Antibiotics (7)
- Antimicrobial Stewardship (4)
- Arthritis (1)
- Asthma (2)
- Autism (2)
- Behavioral Health (4)
- Blood Clots (2)
- Blood Pressure (7)
- Blood Thinners (3)
- Brain Injury (5)
- Burnout (1)
- Cancer (2)
- Cancer: Cervical Cancer (1)
- Cancer: Colorectal Cancer (1)
- Cardiovascular Conditions (7)
- Care Management (3)
- Catheter-Associated Urinary Tract Infection (CAUTI) (1)
- Children/Adolescents (24)
- Chronic Conditions (8)
- (-) Clinical Decision Support (CDS) (201)
- Clinician-Patient Communication (2)
- Colonoscopy (1)
- Communication (3)
- Community-Acquired Infections (1)
- Comparative Effectiveness (2)
- COVID-19 (3)
- Critical Care (1)
- Data (4)
- Dementia (1)
- Depression (2)
- Diabetes (2)
- Diagnostic Safety and Quality (18)
- Digestive Disease and Health (2)
- Disabilities (1)
- Disparities (1)
- Domestic Violence (1)
- Ear Infections (1)
- Education: Continuing Medical Education (1)
- Elderly (6)
- Electronic Health Records (EHRs) (39)
- Electronic Prescribing (E-Prescribing) (3)
- Emergency Department (16)
- Emergency Medical Services (EMS) (4)
- Evidence-Based Practice (20)
- Falls (6)
- Genetics (3)
- Guidelines (6)
- Healthcare-Associated Infections (HAIs) (3)
- Healthcare Cost and Utilization Project (HCUP) (1)
- Healthcare Costs (4)
- Healthcare Delivery (3)
- Healthcare Utilization (2)
- Health Information Exchange (HIE) (1)
- Health Information Technology (HIT) (130)
- Health Services Research (HSR) (2)
- Health Systems (2)
- Heart Disease and Health (7)
- Hepatitis (1)
- Home Healthcare (1)
- Hospital Discharge (1)
- Hospitalization (5)
- Hospital Readmissions (1)
- Hospitals (11)
- Human Immunodeficiency Virus (HIV) (2)
- Imaging (8)
- Implementation (5)
- Infectious Diseases (3)
- Influenza (1)
- Injuries and Wounds (5)
- Inpatient Care (6)
- Intensive Care Unit (ICU) (2)
- Kidney Disease and Health (3)
- Long-Term Care (1)
- Medicaid (1)
- Medical Errors (8)
- Medical Expenditure Panel Survey (MEPS) (1)
- Medication (40)
- Medication: Safety (8)
- Mortality (1)
- Neurological Disorders (3)
- Newborns/Infants (2)
- Nursing (2)
- Nursing Homes (2)
- Nutrition (1)
- Obesity (2)
- Obesity: Weight Management (1)
- Opioids (3)
- Orthopedics (2)
- Outcomes (4)
- Pain (4)
- Patient-Centered Healthcare (10)
- Patient-Centered Outcomes Research (16)
- Patient Adherence/Compliance (1)
- Patient and Family Engagement (1)
- Patient Safety (33)
- Patient Self-Management (1)
- Pneumonia (2)
- Practice Patterns (5)
- Pregnancy (2)
- Pressure Ulcers (2)
- Prevention (13)
- Primary Care (13)
- Primary Care: Models of Care (1)
- Provider (3)
- Provider: Clinician (2)
- Provider: Health Personnel (2)
- Provider: Nurse (2)
- Provider: Pharmacist (1)
- Provider: Physician (3)
- Provider Performance (1)
- Public Health (1)
- Public Reporting (1)
- Quality Improvement (5)
- Quality Indicators (QIs) (1)
- Quality Measures (3)
- Quality of Care (6)
- Racial and Ethnic Minorities (2)
- Registries (1)
- Research Methodologies (1)
- Respiratory Conditions (6)
- Risk (12)
- Rural/Inner-City Residents (1)
- Rural Health (1)
- Screening (6)
- Sepsis (5)
- Shared Decision Making (79)
- Substance Abuse (1)
- Surgery (6)
- Telehealth (1)
- Tobacco Use (1)
- Tobacco Use: Smoking Cessation (1)
- Tools & Toolkits (3)
- Training (1)
- Transplantation (4)
- Trauma (1)
- Urinary Tract Infection (UTI) (1)
- Vaccination (2)
- Web-Based (1)
- Women (2)
- Workflow (3)
AHRQ Research Studies
Sign up: AHRQ Research Studies Email updates
Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 25 of 201 Research Studies DisplayedSalwei ME, Hoonakker P, Carayon P
Usability of a human factors-based clinical decision support in the emergency department: lessons learned for design and implementation.
A human-centered design process was followed to assess the usability and adoption of human factors (HF)-based clinical decision support (CDS) in the emergency department (ED). A CDS was developed to aid in pulmonary embolism (PE) diagnosis, showing high usability in testing. However, despite positive perceptions, actual CDS usage remained low due to integration issues with clinician workflow. The findings highlight the need for ongoing refinement of CDS design to align with clinical workflows and enhance usability.
AHRQ-funded; HS026395; HS024558; HS022086. NIH 142099
Citation: Salwei ME, Hoonakker P, Carayon P .
Usability of a human factors-based clinical decision support in the emergency department: lessons learned for design and implementation.
Hum Factors 2024 Mar; 66(3):647-57. doi: 10.1177/00187208221078625.
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Emergency Department, Implementation
Dullabh P, Leaphart D, Dhopeshwarkar R
Patient-centered clinical decision support-where are we and where to next?
This paper is a literature review of the current state of patient-centered clinical decision support (PC CDS) that includes digital health tools that support patients, caregivers, and care teams in healthcare decisions that incorporate patient-centered factors related to four components: knowledge, data, delivery, and use. It explores the current state of each factor and how each factor promotes patient-centeredness in healthcare. The authors reviewed 175 peer-reviewed and grey literature, and eighteen key informant interviews. They found there is a need for more research on how to incorporate patient input into the guideline selection and prioritization for PC CDS, development and implementation of PC CDS tools, technical challenges for capturing patient contributed data, and optimizing PC CDS across various settings to meet patient and caregiver needs.
AHRQ-funded; 233201500023I.
Citation: Dullabh P, Leaphart D, Dhopeshwarkar R .
Patient-centered clinical decision support-where are we and where to next?
Stud Health Technol Inform 2024 Jan 25; 310:444-48. doi: 10.3233/shti231004..
Keywords: Patient-Centered Healthcare, Clinical Decision Support (CDS), Health Information Technology (HIT)
Hekman DJ, Barton HJ, Maru AP
Dashboarding to monitor machine-learning-based clinical decision support interventions.
This case report described the creation of a dashboard that allowed the intervention development team and operational stakeholders to identify potential issues that may require corrective action by bridging the monitoring gap between model outputs and patient outcomes. The authors proposed that monitoring machine-learning-based clinical decision support (ML-CDS) algorithms with regular dashboards that allow both context-level views of the system and drilled down views of specific components is a critical part of implementing these algorithms to ensure that these tools function appropriately within the broader care system.
AHRQ-funded; HS027735.
Citation: Hekman DJ, Barton HJ, Maru AP .
Dashboarding to monitor machine-learning-based clinical decision support interventions.
Appl Clin Inform 2024 Jan; 15(1):164-69. doi: 10.1055/a-2219-5175.
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT)
Jeffery AD, Reale C, Faiman J
Inpatient nurses' preferences and decisions with risk information visualization.
The purpose of this study was to explore the effect of 4 different risk information formats on inpatient nurses' preferences and decisions with an acute clinical deterioration decision-support system. The researchers implemented a comparative usability evaluation in which participants provided responses to multiple user interface options in a simulated setting. Qualitative data was collected using think aloud methods, asking participants which action they would perform after each time point in 3 different patient scenarios. The 6 participants preferred the probability format over relative risk ratios (n = 2), absolute differences (n = 2), and number of persons out of 100 (n = 0). Participants preferred average lines, having a trend graph to supplement the risk estimate, and consistent colors between trend graphs and possible actions. Participants did not prefer too much text information or the presence of confidence intervals. The utilization of the probability format was related with higher concordance in actions taken by participants compared to the other 3 risk information formats.
AHRQ-funded; HS026395.
Citation: Jeffery AD, Reale C, Faiman J .
Inpatient nurses' preferences and decisions with risk information visualization.
J Am Med Inform Assoc 2023 Dec 22; 31(1):61-69. doi: 10.1093/jamia/ocad209..
Keywords: Provider: Nurse, Clinical Decision Support (CDS), Health Information Technology (HIT)
Strauss AT, Sidoti CN, Sung HC
Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: a qualitative study.
This study’s objective was to use human-centered design methods to elicit providers' perceptions of AI-based clinical decision support (AI-CDS) for liver transplant listing decisions. This multicenter qualitative study involved semistructured interviews with 53 multidisciplinary liver transplant providers from 2 transplant centers. The author’s analysis yielded 6 themes important for the design of fair AI-CDS for liver transplant listing decisions: (1) transparency in the creators behind the AI-CDS and their motivations; (2) understanding how the AI-CDS uses data to support recommendations (ie, interpretability); (3) acknowledgment that AI-CDS could mitigate emotions and biases; (4) AI-CDS as a member of the transplant team, not a replacement; (5) identifying patient resource needs; and (6) including the patient's role in the AI-CDS.
AHRQ-funded; HS024600.
Citation: Strauss AT, Sidoti CN, Sung HC .
Artificial intelligence-based clinical decision support for liver transplant evaluation and considerations about fairness: a qualitative study.
Hepatol Commun 2023 Oct; 7(10). doi: 10.1097/hc9.0000000000000239..
Keywords: Clinical Decision Support (CDS), Transplantation, Health Information Technology (HIT)
Shear K, Horgas AL, Lucero R
Experts' perspectives on use of fast healthcare interoperable resources for computerized clinical decision support.
The purpose of this study was to explore Fast Healthcare Interoperable Resources within the context of interoperability across digital health information and delays in seeking preventative and recommended care. Researchers utilized qualitative analysis of expert interviews. The study found that barriers included differences in electronic health record implementation, limited electronic health record vendor support, ontology variation, limited workforce knowledge, and testing limitations. Experts recommended funders of research require utilization of Fast Healthcare Interoperable Resource, development of an "app store," incentives for clinical organizations and electronic health record vendors, and development of Fast Healthcare Interoperable Resource certification.
AHRQ-funded; HS027557.
Citation: Shear K, Horgas AL, Lucero R .
Experts' perspectives on use of fast healthcare interoperable resources for computerized clinical decision support.
Comput Inform Nurs 2023 Oct; 41(10):752-58. doi: 10.1097/cin.0000000000001033..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT)
Hernandez-Boussard T, Siddique SM, Bierman AS
AHRQ Author: Bierman AS
Promoting equity in clinical decision making: dismantling race-based medicine.
The authors recommended a race-aware approach to clinical decision support to address concerns raised about racial and ethnic biases built into the algorithms that lead to persistent disparities in health and healthcare. The proposed approach will require sustained commitment and effort among stakeholders, research, and technology sectors. Important steps will include increasing diversity in clinical trial populations, broadening the focus of precision medicine, improving education about complex factors that shape health outcomes, and developing new guidelines and policies that enable culturally responsive care.
AHRQ-authored.
Citation: Hernandez-Boussard T, Siddique SM, Bierman AS .
Promoting equity in clinical decision making: dismantling race-based medicine.
Health Affairs 2023 Oct; 42(10):1369-73. doi: 10.1377/hlthaff.2023.00545..
Keywords: Racial and Ethnic Minorities, Clinical Decision Support (CDS), Health Information Technology (HIT)
Shenvi E, Boxwala A, Sittig D
AHRQ Author: Lomotan E, Swiger J
Visualization of patient-generated health data: a scoping review of dashboard designs.
The purpose of this scoping review was to identify best practices in visualizations of physiologic Patient-generated health data (PGHD), for designing a software application as a Patient-centered clinical decision support (PC CDS) tool. The researchers conducted a scoping review of studies of PGHD dashboards that included clinician users in design or evaluations. Only studies that utilized physiologic PGHD from single patients for usage in decision-making were included. The researchers screened 468 titles and abstracts, 63 full-text papers, and identified 15 articles to include in the review. The researchers found that some research primarily sought user input on PGHD presentation, while other studies collected feedback only as a side effort for other objectives such as integration with electronic health records. Development efforts were often in the domains of chronic diseases and collected a mix of physiologic parameters such as blood pressure and heart rate and data on activity. Users' preferences were for data to be presented with statistical summaries and clinical interpretations, alongside other non-PGHD data. Identified themes reflected that users want longitudinal data display, aggregation of multiple data types on the same screen, actionability, and customization. Speed, simplicity, and availability of data for other purposes such as documentation were key to dashboard adoption. Assessments were positive for visualizations using common graphing or table formats, but best practices for implementation have not been determined.
AHRQ-authored; AHRQ-funded; 75Q80120D00018.
Citation: Shenvi E, Boxwala A, Sittig D .
Visualization of patient-generated health data: a scoping review of dashboard designs.
Appl Clin Inform 2023 Oct; 14(5):913-22. doi: 10.1055/a-2174-7820..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT)
Benziger CP, Suess M, Allen CI
Adapting a clinical decision support system to improve identification of pediatric hypertension in a rural health system: design of a pragmatic trial.
This paper’s objective is to describe the protocol for a study that will adapt an electronic health record linked, web-based clinical decision support (CDS) tool called PedsBP that identifies hypertension (HTN) in children for use in a mostly rural health system and to evaluate the effectiveness of PedsBP for repeat of hypertensive level blood pressure (BP) measurements and HTN recognition among youth 6-17 years of age in primary care settings, comparing low-intensity and high-intensity implementation approaches. A pilot of the tool was conducted in 2 primary care clinics and modified prior to the full trial. Forty community-based primary care clinics (or clusters of clinics) were randomly allocated equally to usual care, low-intensity implementation (CDS only), or high-intensity implementation (CDS plus in-person training, monthly use reports, and ongoing communication between study staff and clinics). Eligible patient recruitment started on August 1, 2022 and will continue for 18 months. Primary outcomes will include repeating hypertensive level BP measurements at office visits and clinical recognition of HTN. Secondary outcomes will include lifestyle counseling, dietician referral, and BP at follow-up.
AHRQ-funded; HS027402.
Citation: Benziger CP, Suess M, Allen CI .
Adapting a clinical decision support system to improve identification of pediatric hypertension in a rural health system: design of a pragmatic trial.
Contemp Clin Trials 2023 Sep; 132:107293. doi: 10.1016/j.cct.2023.107293..
Keywords: Clinical Decision Support (CDS), Children/Adolescents, Rural Health, Rural/Inner-City Residents, Blood Pressure
Sittig DF, Boxwala A, Wright A
AHRQ Author: Swiger J, Lomotan EA
A lifecycle framework illustrates eight stages necessary for realizing the benefits of patient-centered clinical decision support.
The authors developed a patient-centered clinical decision support (PC CDS) lifecycle framework to promote a language for communication among researchers, patients, clinicians, and policymakers. The framework placed the patient and/or their caregiver at the center and its use could ensure that patients and the clinicians caring for them are explicitly involved at each stage.
AHRQ-authored; AHRQ-funded; 75Q80120D00018.
Citation: Sittig DF, Boxwala A, Wright A .
A lifecycle framework illustrates eight stages necessary for realizing the benefits of patient-centered clinical decision support.
J Am Med Inform Assoc 2023 Aug 18; 30(9):1583-89. doi: 10.1093/jamia/ocad122..
Keywords: Patient-Centered Healthcare, Clinical Decision Support (CDS), Health Information Technology (HIT)
Hekman DJ, Cochran AL, Maru AP
Effectiveness of an emergency department-based machine learning clinical decision support tool to prevent outpatient falls among older adults: protocol for a quasi-experimental study.
This article described a research protocol for evaluating the effectiveness of an automated screening and referral intervention tool for patients receiving falls risk intervention. The study will attempt to quantify the impact of a machine learning (ML) clinical decision support intervention on patient behavior and outcomes. The primary analysis will obtain referral completion rates from different emergency departments. The findings will inform ongoing discussion on the use of ML and artificial intelligence to augment medical decision-making.
AHRQ-funded; HS027735.
Citation: Hekman DJ, Cochran AL, Maru AP .
Effectiveness of an emergency department-based machine learning clinical decision support tool to prevent outpatient falls among older adults: protocol for a quasi-experimental study.
JMIR Res Protoc 2023 Aug 3; 12:e48128. doi: 10.2196/48128..
Keywords: Clinical Decision Support (CDS), Emergency Department, Health Information Technology (HIT), Elderly, Falls
Jones EK, Ninkovic I, Bahr M
A novel, evidence-based, comprehensive clinical decision support system improves outcomes for patients with traumatic rib fractures.
This study’s objective to investigate if a traumatic rib fracture clinical decision support system (CDSS) reduced hospital length of stay (LOS), 90-day and 1-year mortality, unplanned ICU transfer, and the need for mechanical ventilation. The CDSS included an admission evidence-based (EB) order set and a pain-inspiratory-cough (PIC) score early warning system (EWS). The CDSS was implemented at 9 US trauma centers, with 3,279 patients meeting inclusion criteria. Hospital LOS pre vs post-intervention was unchanged but unplanned transfer to the ICU was reduced, as was 1-year mortality. Provider utilization was associated with significantly reduced LOS. The EWS triggered on 34.4% of patients; however, it was not associated with a significant reduction in hospital LOS.
AHRQ-funded; HS026379.
Citation: Jones EK, Ninkovic I, Bahr M .
A novel, evidence-based, comprehensive clinical decision support system improves outcomes for patients with traumatic rib fractures.
J Trauma Acute Care Surg 2023 Aug 1; 95(2):161-71. doi: 10.1097/ta.0000000000003866..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Evidence-Based Practice, Injuries and Wounds, Trauma
Rolfzen ML, Wick A, Mascha EJ
Best Practice Alerts Informed by Inpatient Opioid Intake to Reduce Opioid Prescribing after Surgery (PRIOR): a cluster randomized multiple crossover trial.
This study tested the hypothesis that a decision-support tool embedded in electronic health records (EHRs) leads clinicians to prescribe fewer opioids at discharge after inpatient surgery. Over 21,000 surgical inpatient discharges in a cluster randomized multiple crossover trial in four Colorado hospitals were included. The results indicated that within the context of vigorous opioid education and awareness efforts a decision-support tool incorporated into EHRs did not reduce discharge opioid prescribing for postoperative patients. The authors concluded that opioid prescribing alerts might be valuable in other contexts.
AHRQ-funded; HS027795.
Citation: Rolfzen ML, Wick A, Mascha EJ .
Best Practice Alerts Informed by Inpatient Opioid Intake to Reduce Opioid Prescribing after Surgery (PRIOR): a cluster randomized multiple crossover trial.
Anesthesiology 2023 Aug 1; 139(2):186-96. doi: 10.1097/aln.0000000000004607..
Keywords: Opioids, Medication, Surgery, Inpatient Care, Clinical Decision Support (CDS), Health Information Technology (HIT)
Krishnan JA, Margellos-Anast H, Kumar R
Coordinated Health Care Interventions for Childhood Asthma Gaps in Outcomes (CHICAGO) plan.
The purpose of this clinical trial was to compare an emergency-department- (ED) only intervention and home visits by community health workers for 6 months (ED-plus-home) and enhanced usual care (UC). The study enrolled children aged 5 to 11 years with uncontrolled asthma. The primary outcomes were change over 6 months in the Patient-Reported Outcomes Measurement Information System Asthma Impact Scale score in children and Satisfaction with Participation in Social Roles score in caregivers. The secondary outcomes included guideline-recommended ED discharge care and self-management. The study found that of the 373 children recruited, only 63% completed the 6-month follow-up visit. Differences in Asthma Impact Scores or caregivers' Satisfaction with Participation in Social Roles scores were not significant. However, in the intervention groups guideline-recommended ED discharge care improved significantly versus in the UC group, and self-management behaviors were significantly improved in the ED-plus-home group versus in the ED-only and UC groups.
AHRQ-funded; HS027804.
Citation: Krishnan JA, Margellos-Anast H, Kumar R .
Coordinated Health Care Interventions for Childhood Asthma Gaps in Outcomes (CHICAGO) plan.
J Allergy Clin Immunol Glob 2023 Aug; 2(3). doi: 10.1016/j.jacig.2023.100100..
Keywords: Children/Adolescents, Asthma, Respiratory Conditions, Outcomes, Patient-Centered Outcomes Research, Evidence-Based Practice, Emergency Department, Clinical Decision Support (CDS), Health Information Technology (HIT), Racial and Ethnic Minorities
Roberts MM, Marino M, Wells R
Differences in use of clinical decision support tools and implementation of aspirin, blood pressure control, cholesterol management, and smoking cessation quality metrics in small practices by race and sex.
The objective of this cross-sectional study was to evaluate the association between population-based clinical decision support (CDS) tools and racial and sex disparities in the aspirin use, blood pressure control, cholesterol management, and smoking cessation (ABCS) care quality metrics among smaller primary care practices. Researchers used practice-level data from the EvidenceNOW initiative, from practices that submitted both survey data and electronic health record (EHR)-derived ABCS data stratified by race and sex. Their findings suggested that practices using CDS tools had small disparities but were not statistically significant; however, CDS tools were not associated with reductions in disparities. They concluded that more research was needed on effective practice-level interventions to mitigate disparities.
AHRQ-funded; HS023940.
Citation: Roberts MM, Marino M, Wells R .
Differences in use of clinical decision support tools and implementation of aspirin, blood pressure control, cholesterol management, and smoking cessation quality metrics in small practices by race and sex.
JAMA Netw Open 2023 Aug; 6(8):e2326905. doi: 10.1001/jamanetworkopen.2023.26905..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Cardiovascular Conditions, Tobacco Use, Tobacco Use: Smoking Cessation, Primary Care, Evidence-Based Practice, Prevention
Soares A, Afshar M, Moesel C
AHRQ Author: Lomotan EA
Playing in the clinical decision support sandbox: tools and training for all.
This AHRQ-authored paper introduces the CDS-Sandbox, a cloud-based virtual machine created to facilitate Clinical Decision Support (CDS) developers and implementers in the use of FHIR- and CQL-based open-source tools and technologies for building and testing CDS artifacts. The CDS-Sandbox was demonstrated at two workshops at the 2020 and 2021 AMIA Annual Symposia and includes components that enable workflows for authoring and testing CDS artifacts. At both workshops, participants demonstrated use and understanding of the workshop materials and provided positive feedback after the workshops.
AHRQ-authored; AHRQ-funded; 75FCMC18D0047; 75Q80119F8005.
Citation: Soares A, Afshar M, Moesel C .
Playing in the clinical decision support sandbox: tools and training for all.
JAMIA Open 2023 Jul; 6(2):ooad038. doi: 10.1093/jamiaopen/ooad038..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Training
Blecker S, Gannon M, De Leon S
Practice facilitation for scale up of clinical decision support for hypertension management: study protocol for a cluster randomized control trial.
This paper describes a protocol for a study that will be conducted to compare the effect of hypertension-focused clinical decision support (CDS) plus practice facilitation on blood pressure (BP) control, as compared to CDS alone. The investigators will conduct a cluster randomized control trial that will include initial training on the CDS and a review of current guidelines along with follow-up for coaching and integration support. They will randomize 46 small primary care practices in New York City who use the same electronic health record vendor to intervention or control. They will also assess implementation of CDS in all practices and practice facilitation in the intervention group.
AHRQ-funded; HS027120.
Citation: Blecker S, Gannon M, De Leon S .
Practice facilitation for scale up of clinical decision support for hypertension management: study protocol for a cluster randomized control trial.
Contemp Clin Trials 2023 Jun; 129:107177. doi: 10.1016/j.cct.2023.107177..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Blood Pressure, Cardiovascular Conditions
Dhopeshwarkar RV, Freij M, Callaham M
AHRQ Author: Harrison MI, Swiger J, Lomotan EA, Dymek C
Lessons learned from a national initiative promoting publicly available standards-based clinical decision support.
The purpose of this study was to discuss lessons learned from a national program promoting publicly available, standards-based Clinical decision support (CDS) resources, describe the challenges encountered with their use, and make suggestions for areas of improvement. The source of the findings was an evaluation of the Agency for Healthcare Research and Quality (AHRQ) Patient-Centered Outcomes Research CDS Initiative, the purpose of which was to advance evidence into practice through standards-based and publicly available CDS. The researchers utilized a review of literature and program materials, conducted key informant interviews, and administered a web-based survey about a public repository of CDS archives and tools for writing standards-based CDS. The review identified key lessons for developing and implementing standards-based CDS through publicly available repositories such as CDS Connect. The researchers identified trust as a key factor in uptake, which can be strengthened by transparent information on underlying evidence, collaboration with experts, and feedback loops between users and developers to support continuous quality improvement. In addition, lower-resourced health systems will need more support to ensure effective implementation and utilization. Finally, the study found that health systems want more information about patient-centered, clinical, and cost-related outcomes to facilitate justifying the investment required to implement publicly available, standards-based CDS.
AHRQ-authored; AHRQ-funded; 233201500023I.
Citation: Dhopeshwarkar RV, Freij M, Callaham M .
Lessons learned from a national initiative promoting publicly available standards-based clinical decision support.
Appl Clin Inform 2023 May; 14(3):566-74. doi: 10.1055/s-0043-1769911..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Patient-Centered Outcomes Research
Lee AH, McEvoy DS, Stump T
Implementation of an electronic alert to improve timeliness of second dose antibiotics for patients with suspected serious infections in the emergency department: a quasi-randomized controlled trial.
This study analyzed the influence of clinical decision support (CDS) to prevent delays in second doses of broad-spectrum antibiotics in the emergency department (ED). The authors allocated adult patients who received cefepime or piperacillin/tazobactam in 9 EDs within an integrated health care system to an electronic alert that reminded ED clinicians to reorder antibiotics at the appropriate interval vs usual care. Primary outcome was a median delay in antibiotic administration, and secondary outcomes were rates of intensive care unit (ICU) admission, hospital mortality, and hospital length of stay. A total of 1,113 ED patients treated with cefepime or piperacillin/tazobactam were enrolled in the study, of whom 420 remained under ED care when their second dose was due. The electronic alert system was associated with reduced antibiotic delays, but there were no differences in ICU transfers, inpatient mortality, or hospital length of stay.
AHRQ-funded; HS027170.
Citation: Lee AH, McEvoy DS, Stump T .
Implementation of an electronic alert to improve timeliness of second dose antibiotics for patients with suspected serious infections in the emergency department: a quasi-randomized controlled trial.
Ann Emerg Med 2023 Apr;81(4):485-91. doi: 10.1016/j.annemergmed.2022.10.022.
Keywords: Antibiotics, Medication, Emergency Department, Clinical Decision Support (CDS), Health Information Technology (HIT)
Ingraham NE, Jones EK, King S
Re-aiming equity evaluation in clinical decision support: a scoping review of equity assessments in surgical decision support systems.
This scoping review explored surgical literature to determine frequency and rigor of clinical decision support (CDS) equity assessments and offer recommendations to improve CDS equity by appending existing frameworks. The authors performed a scoping review of PubMed and Google Scholar and identified 1,415 citations with 229 abstracts meeting criteria for review. A total of 84 papers underwent full review after 145 were excluded if they did not assess outcomes of an electronic CDS tool or have a surgical use case. Only 6% of surgical CDS systems reported equity analyses, suggesting that current methods for optimizing equity in surgical CDS are inadequate. The authors proposed revising the RE-AIM framework to include an Equity element (RE2-AIM) specifying that CDS foundational analyses and algorithms are performed or trained on balanced datasets with sociodemographic characteristics that accurately represent the CDS target population and are assessed by sensitivity analyses focused on vulnerable subpopulations.
AHRQ-funded; HS026379; HS024532.
Citation: Ingraham NE, Jones EK, King S .
Re-aiming equity evaluation in clinical decision support: a scoping review of equity assessments in surgical decision support systems.
Ann Surg 2023 Mar; 277(3):359-64. doi: 10.1097/sla.0000000000005661..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Disparities, Surgery
Cochran A, Rayo MF
Toward joint activity design: augmenting user-centered design with heuristics for supporting joint activity.
This paper discusses the development of a clinical decision support application for preventing hospital-acquired infection called GeoHAI, which has yielded positive results in early usability testing and is expected to test positively in supporting joint activity, which will be measured through the novel implementation of Joint Activity Monitoring. The design and implementation of this application will help to unify the work of Human-Centered Design and Cognitive Systems Engineering through demonstration of the possibilities and necessities. The authors are calling this unified process Joint Activity Design, which supports designing for machines to be good team players.
AHRQ-funded; HS027200.
Citation: Cochran A, Rayo MF .
Toward joint activity design: augmenting user-centered design with heuristics for supporting joint activity.
Proc Int Symp Hum Factors Ergon Healthc 2023 Mar; 12(1):19-23. doi: 10.1177/2327857923121006..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Orthopedics
Shear K, Rice H, Garabedian PM
Usability testing of an interoperable computerized clinical decision support tool for fall risk management in primary care.
The purpose of this study was to conduct usability testing of the ASPIRE fall risk management tool for use in divergent primary care clinics. Participants recruited from two sites with different electronic health records and clinical organizations used ASPIRE across two clinical scenarios; they rated ASPIRE usability as above average, based on usability benchmarks. Time spent on tasks decreased significantly between the first and second scenarios, indicating ease of learnability. The authors conclude that ASPIRE could be integrated into diverse organizations, since it allows a tailored implementation without the need to build a new system for each organization. ASPIRE is therefore well positioned to impact the challenge of falls at scale.
AHRQ-funded; HS027557.
Citation: Shear K, Rice H, Garabedian PM .
Usability testing of an interoperable computerized clinical decision support tool for fall risk management in primary care.
Appl Clin Inform 2023 Mar;14(2):212-26. doi: 10.1055/a-2006-4936.
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Health Information Technology (HIT), Falls, Primary Care, Risk, Prevention
Djulbegovic B, Hozo I, Lizarraga D
Evaluation of a fast-and-frugal clinical decision algorithm ('pathways') on clinical outcomes in hospitalised patients with COVID-19 treated with anticoagulants.
The objective of this study was to assess if delivery of anticoagulant prophylaxis according to an algorithm improved clinical outcomes in patients hospitalized with COVID-19 in comparison with anticoagulant treatment given at individual practitioners' discretion. Findings indicated that the algorithm did not reduce death, venous thromboembolism, nor major bleeding, but helped avoid longer hospital stay and admission to an intensive-care unit.
AHRQ-funded; HS024917.
Citation: Djulbegovic B, Hozo I, Lizarraga D .
Evaluation of a fast-and-frugal clinical decision algorithm ('pathways') on clinical outcomes in hospitalised patients with COVID-19 treated with anticoagulants.
J Eval Clin Pract 2023 Feb; 29(1):3-12. doi: 10.1111/jep.13780..
Keywords: COVID-19, Clinical Decision Support (CDS), Blood Thinners, Medication, Evidence-Based Practice, Health Information Technology (HIT)
Gephart SM, Tolentino DA, Quinn MC
Neonatal intensive care workflow analysis informing NEC-Zero clinical decision support design.
The aim of this qualitative descriptive study was to explore the current clinical workflow and sociotechnical processes of clinicians for necrotizing enterocolitis risk awareness, timely discovery of symptoms, and treatment to guide decision support design. The researchers conducted 11 focus groups in two neonatal ICUs. The study found that workflow processes were different for nurses (who observe the signs of necrotizing enterocolitis and inform providers to order diagnostic tests and treatments) and providers (who receive notification of necrotizing enterocolitis concern and then decide what actions to take). The researchers reported that clinicians wanted a necrotizing enterocolitis-relevant dashboard with: 1) nutrition tracking and recognition of necrotizing enterocolitis; 2) features to support decision-making; 3) breast milk tracking and feeding clinical decision support; 4) tools for necrotizing enterocolitis surveillance and quality reporting; and 5) general electronic health records improvements to enhance user experience.
AHRQ-funded; HS022908.
Citation: Gephart SM, Tolentino DA, Quinn MC .
Neonatal intensive care workflow analysis informing NEC-Zero clinical decision support design.
Comput Inform Nurs 2023 Feb; 41(2):94-101. doi: 10.1097/cin.0000000000000929..
Keywords: Newborns/Infants, Clinical Decision Support (CDS), Intensive Care Unit (ICU), Workflow, Health Information Technology (HIT)
Rizk S, Kaelin VC, Sim JGC
Implementing an electronic patient-reported outcome and decision support tool in early intervention.
The study’s aim was to identify and prioritize early intervention (EI) stakeholders' perspectives of supports and barriers to implementing the Young Children's Participation and Environment Measure (YC-PEM), an electronic patient-reported outcome (e-PRO) tool, for scaling its implementation across multiple local and state EI programs. A mixed-methods study was conducted with EI families (n = 6), service coordinators (n = 9), and program leadership (n = 7). Semi-structured interviews and focus groups were conducted and used to share quantitative trial results. All three stakeholder groups identified thematic supports and barriers across multiple constructs within each of four Consolidated Framework for Implementation Research (CFIR) domains: (1) Six themes for "intervention characteristics," (2) Six themes for "process," (3) Three themes for "inner setting," and (4) Four themes for "outer setting." Priorities from stakeholders included prioritized reaching families with diverse linguistic preferences and user navigation needs, further tailoring its interface with automated data capture and exchange processes ("process"); and fostering a positive implementation climate ("inner setting"). Improving EI access (“outer setting”) using YC-PEM e-PRO results was also articulated by service coordinators and program leadership.
AHRQ-funded; HS027583.
Citation: Rizk S, Kaelin VC, Sim JGC .
Implementing an electronic patient-reported outcome and decision support tool in early intervention.
Appl Clin Inform 2023 Jan; 14(1):91-107. doi: 10.1055/s-0042-1760631..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Children/Adolescents, Evidence-Based Practice, Patient-Centered Outcomes Research, Implementation