National Healthcare Quality and Disparities Report
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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
76 to 100 of 199 Research Studies DisplayedCurran RL, Kukhareva PV, Taft T
Integrated displays to improve chronic disease management in ambulatory care: a SMART on FHIR application informed by mixed-methods user testing.
This study’s objective was to evaluate a novel electronic health record (EHR) add-on application for chronic disease management that uses an integrated display to decrease user cognitive load, improve efficiency, and support clinical decision making. The authors designed an application using the technology framework known as SMART on FHIR (Substitutable Medical Applications and Reusable Technologies on Fast Healthcare Interoperability Resources). They used mixed methods to obtain user feedback on a prototype to support ambulatory providers managing chronic obstructive pulmonary disease. Two patient scenarios were presented to the participants using the regular EHR with and without access to their prototype. Results measured was the percentage of expert-recommended ideal care tasks completed. Timing, keyboard and mouse use, and participant surveys were also collected. The 13 participants complete more recommended care using the prototype (81% vs 48%) and recommended tasks per minute over long sessions. Keystrokes per task were also lower with the prototype (6 vs 18). While there was a learning curve for this application, it will increase efficiency and patient care with practice.
AHRQ-funded; HS026198.
Citation: Curran RL, Kukhareva PV, Taft T .
Integrated displays to improve chronic disease management in ambulatory care: a SMART on FHIR application informed by mixed-methods user testing.
J Am Med Inform Assoc 2020 Aug;27(8):1225-34. doi: 10.1093/jamia/ocaa099..
Keywords: Chronic Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT), Care Management, Ambulatory Care and Surgery, Clinical Decision Support (CDS), Decision Making
Co Z, Holmgren AJ, Classen DC
The tradeoffs between safety and alert fatigue: data from a national evaluation of hospital medication-related clinical decision support.
This study evaluated the overall performance of hospitals that used the Computerized Physician Order Entry Evaluation Tool in 2017 and 2018 and compared performances for fatal orders and nuisance orders each year. The authors evaluated 1599 hospitals that took the test by using their overall percentage scores along with the percentage of fatal orders appropriately alerted on and the percentage of nuisance orders incorrectly alerted on. Overall hospital scores improved from 58.1% in 2017 to 66.2% in 2018. Fatal order performance improved slightly from 78.8% to 83.0%, but there no very little change in nuisance order performance (89.0% to 89.7%). Conclusions were that perhaps hospitals are not targeting the deadliest orders first and some hospitals may be achieving higher scores by over-alerting. This has the potential to cause clinician burnout and even worsen patient safety.
AHRQ-funded; HS023696.
Citation: Co Z, Holmgren AJ, Classen DC .
The tradeoffs between safety and alert fatigue: data from a national evaluation of hospital medication-related clinical decision support.
J Am Med Inform Assoc 2020 Aug;27(8):1252-58. doi: 10.1093/jamia/ocaa098..
Keywords: Medication: Safety, Medication, Patient Safety, Clinical Decision Support (CDS), Decision Making, Burnout, Hospitals, Health Information Technology (HIT), Quality of Care
Panattoni L, Stults CD, Chan AS
The human resource costs of implementing autopend clinical decision support to improve health maintenance.
This study estimated the costs of developing and implementing the Sutter Health autopend functionality within an existing electronic health maintenance (HM) reminder system. Findings showed that developing and implementing autopend took more than 3 years, involved 6 managers and 3 Epic programmers, and cost $201,500 and 2670 total hours, excluding the costs of implementing the initial HM reminder system. The autopend clinical decision support might be similarly costly for other organizations to implement if their managers need to complete comparable activities. However, electronic health record vendors could include autopend as a standard package to reduce development costs and improve the uptake of this promising clinical decision support tool.
AHRQ-funded; HS022631.
Citation: Panattoni L, Stults CD, Chan AS .
The human resource costs of implementing autopend clinical decision support to improve health maintenance.
Am J Manag Care 2020 Jul;26(7):e232-e36. doi: 10.37765/ajmc.2020.43766..
Keywords: Clinical Decision Support (CDS), Decision Making, Implementation
Wang L, Blackley SV, Blumenthal KG
A dynamic reaction picklist for improving allergy reaction documentation in the electronic health record.
Incomplete and static reaction picklists in the allergy module led to free-text and missing entries that inhibit the clinical decision support intended to prevent adverse drug reactions. In this study, the investigators developed a novel, data-driven, "dynamic" reaction picklist to improve allergy documentation in the electronic health record (EHR). The investigators concluded that their dynamic reaction picklist was superior to the static picklist and suggested proper reactions for allergy documentation.
AHRQ-funded; HS025375.
Citation: Wang L, Blackley SV, Blumenthal KG .
A dynamic reaction picklist for improving allergy reaction documentation in the electronic health record.
J Am Med Inform Assoc 2020 Jun;27(6):917-23. doi: 10.1093/jamia/ocaa042..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Clinical Decision Support (CDS)
Westafer LM, Kunz A, Bugajska P
Provider perspectives on the use of evidence-based risk stratification tools in the evaluation of pulmonary embolism: a qualitative study.
Providers often pursue imaging in patients at low risk of pulmonary embolism (PE), resulting in imaging yields <10% and false-positive imaging rates of 10% to 25%. Attempts to curb overtesting have had only modest success and no interventions have used implementation science frameworks. The objective of this study was to identify barriers and facilitators to the adoption of evidence-based diagnostic testing for PE.
AHRQ-funded; HS025701.
Citation: Westafer LM, Kunz A, Bugajska P .
Provider perspectives on the use of evidence-based risk stratification tools in the evaluation of pulmonary embolism: a qualitative study.
Acad Emerg Med 2020 Jun;27(6):447-56. doi: 10.1111/acem.13908..
Keywords: Respiratory Conditions, Evidence-Based Practice, Diagnostic Safety and Quality, Imaging, Decision Making, Clinical Decision Support (CDS), Practice Patterns, Provider: Physician, Provider: Clinician, Provider
Trubiano JA, Vogrin S, Chua KYL
Development and validation of a penicillin allergy clinical decision rule.
Penicillin allergy is a significant public health issue for patients, antimicrobial stewardship programs, and health services. Validated clinical decision rules are urgently needed to identify low-risk penicillin allergies that potentially do not require penicillin skin testing by a specialist. The objective of this study was to develop and validate a penicillin allergy clinical decision rule that enables point-of-care risk assessment of patient-reported penicillin allergies.
AHRQ-funded; HS026395.
Citation: Trubiano JA, Vogrin S, Chua KYL .
Development and validation of a penicillin allergy clinical decision rule.
JAMA Intern Med 2020 May;180(5):745-52. doi: 10.1001/jamainternmed.2020.0403..
Keywords: Antimicrobial Stewardship, Antibiotics, Medication, Clinical Decision Support (CDS), Risk
Classen DC, Holmgren AJ, Co Z
National trends in the safety performance of electronic health record systems from 2009 to 2018.
This study examined trends in the safety performance of electronic health records (EHRs) in hospitals from 2009 to 2018. The Leapfrog Health IT Safety Measure test was administered by the Leapfrog Group from July 2018 to December 1, 2019. Overall mean performance scores increased from 53.9% in 2009 to 65.6% in 2018. Mean hospital scores for categories representing basic clinical decision support increased from 69.8% in 2009 to 85.6% in 2018. Advanced decision clinical support also increased from 29.5% in 2009 to 46.1%. These results showed great improvement, but there is still substantial safety risk in current hospital EHR systems.
AHRQ-funded; HS023696.
Citation: Classen DC, Holmgren AJ, Co Z .
National trends in the safety performance of electronic health record systems from 2009 to 2018.
JAMA Netw Open 2020 May;3(5):e205547. doi: 10.1001/jamanetworkopen.2020.5547..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Hospitals, Patient Safety, Quality Measures, Clinical Decision Support (CDS), Quality Indicators (QIs)
Ramirez M, Chen K, Follett RW
Impact of a "chart closure" hard stop alert on prescribing for elevated blood pressures among patients with diabetes: quasi-experimental study.
The aim of the study was to evaluate whether the implementation of the Best Practice Advisory (BPA) was associated with changes in angiotensin-converting enzyme inhibitor (ACEI) and angiotensin-receptor blocker (ARB) prescribing during primary care encounters for patients with diabetes. The investigators concluded that a BPA with a "chart closure" hard stop is a promising tool for the treatment of patients with comorbid diabetes and hypertension with an ACEI or ARB, especially when implemented within the context of team-based care, wherein clinical pharmacists support the work of primary care providers.
AHRQ-funded; HS00046.
Citation: Ramirez M, Chen K, Follett RW .
Impact of a "chart closure" hard stop alert on prescribing for elevated blood pressures among patients with diabetes: quasi-experimental study.
JMIR Med Inform 2020 Apr 17;8(4):e16421. doi: 10.2196/16421..
Keywords: Blood Pressure, Medication, Diabetes, Clinical Decision Support (CDS), Decision Making, Chronic Conditions
Carayon P, Hoonakker P, Hundt AS
Application of human factors to improve usability of clinical decision support for diagnostic decision-making: a scenario-based simulation study.
This study used a scenario-based simulation to compare a human factor (HF)-based clinician decision support (CDS) with a web-based CDS (MDCalc) for clinicians to diagnose pulmonary embolism (PE) in the emergency department. A total of 32 emergency physicians participated using both CDS types. Emergency physicians made more appropriate diagnoses decisions with the PE-Dx CDS (94%) than with the web-based CDS (84%). Experimental tasks were also performed faster (average 96 seconds per scenario versus 117 seconds). They also reported lower workload and higher satisfaction with the HF-based CDS.
AHRQ-funded; HS024342; HS024558; HS022086.
Citation: Carayon P, Hoonakker P, Hundt AS .
Application of human factors to improve usability of clinical decision support for diagnostic decision-making: a scenario-based simulation study.
BMJ Qual Saf 2020 Apr;29(4):329-40. doi: 10.1136/bmjqs-2019-009857..
Keywords: Clinical Decision Support (CDS), Decision Making, Health Information Technology (HIT), Diagnostic Safety and Quality, Emergency Department
Richardson JE, Middleton B, Platt JE
Building and maintaining trust in clinical decision support: recommendations from the Patient-Centered CDS Learning Network.
Knowledge artifacts in digital repositories for clinical decision support (CDS) can promote the use of CDS in clinical practice. However, stakeholders will benefit from knowing which they can trust before adopting artifacts from knowledge repositories. In this paper, the investigators discuss their investigation into trust for knowledge artifacts and repositories by the Patient-Centered CDS Learning Network's Trust Framework Working Group (TFWG).
AHRQ-funded; HS024849.
Citation: Richardson JE, Middleton B, Platt JE .
Building and maintaining trust in clinical decision support: recommendations from the Patient-Centered CDS Learning Network.
Learn Health Syst 2020 Apr;4(2):e10208. doi: 10.1002/lrh2.10208.
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Keywords: Clinical Decision Support (CDS), Decision Making, Patient-Centered Healthcare, Patient-Centered Outcomes Research
Richardson S, Cohen S, Khan S
Higher imaging yield when clinical decision support is used.
Increased utilization of CT pulmonary angiography (CTPA) for the evaluation of pulmonary embolism has been associated with decreasing diagnostic yields and rising concerns about the harms of unnecessary testing. The objective of this study was to determine whether clinical decision support (CDS) use would be associated with increased imaging yields after controlling for selection bias.
AHRQ-funded; HS022061.
Citation: Richardson S, Cohen S, Khan S .
Higher imaging yield when clinical decision support is used.
J Am Coll Radiol 2020 Apr;17(4):496-503. doi: 10.1016/j.jacr.2019.11.021.
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Keywords: Clinical Decision Support (CDS), Imaging, Diagnostic Safety and Quality, Decision Making, Blood Clots
Marcial LH, Blumenfeld B, Harle C
Barriers, facilitators, and potential solutions to advancing interoperable clinical decision support: multi-stakeholder consensus recommendations for the opioid use case.
These proceedings report on the AHRQ-sponsored Patient-Centered CDS Learning Network (PCCDS LN) Technical Framework Working Group (TechFWG), which was convened to identify barriers, facilitators, and potential solutions for interoperable clinical decision support, with a specific focus on addressing the opioid epidemic. The key insights were extrapolated to CDS-facilitated care improvement outside of the specific opioid use case. If applied broadly, the recommendations should help advance the availability and impact of interoperable CDS delivered at scale.
AHRQ-funded; HS024849.
Citation: Marcial LH, Blumenfeld B, Harle C .
Barriers, facilitators, and potential solutions to advancing interoperable clinical decision support: multi-stakeholder consensus recommendations for the opioid use case.
AMIA Annu Symp Proc 2020 Mar 4;2019:637-46..
Keywords: Clinical Decision Support (CDS), Decision Making, Opioids, Medication, Pain, Patient-Centered Healthcare, Patient-Centered Outcomes Research
Meyer AND, Giardina TD, Spitzmueller C
Patient perspectives on the usefulness of an artificial intelligence-assisted symptom checker: cross-sectional survey study.
This study examined patients’ experiences using an artificial intelligence (AI)-assisted online symptom checker and their doctors’ reactions to that use. From March 2 through March 15, 2018 an online survey was conducted of US users of the Isabel Symptom Checker within 6 months of their use. The majority of users were women, white, and had a mean age of 48. Overall, patients had a positive experience with the symptom checker and felt they would use it again (91.4%). About 48% discussed the findings with their physician and felt about 40% of their physicians were interested. Patients who had previously experienced diagnostic errors were more likely to use the symptom checker to determine if they should seek care.
AHRQ-funded; HS025474; HS027363.
Citation: Meyer AND, Giardina TD, Spitzmueller C .
Patient perspectives on the usefulness of an artificial intelligence-assisted symptom checker: cross-sectional survey study.
J Med Internet Res 2020 Jan 30;22(1):e14679. doi: 10.2196/14679..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Diagnostic Safety and Quality, Patient Safety
Holmgren AJ, Co Z, Newmark L
Assessing the safety of electronic health records: a national longitudinal study of medication-related decision support.
The authors tested how well EHRs prevented medication errors with the potential for patient harm. Data from a national, longitudinal sample of 1527 hospitals in the US from 2009-16 who took a safety performance assessment test using simulated medication orders was used. The authors found that hospital medication order safety performance improved over time. They conclude that intentional quality improvement efforts appear to be a critical part of high safety performance and may indicate the importance of a culture of safety.
AHRQ-funded; HS023696.
Citation: Holmgren AJ, Co Z, Newmark L .
Assessing the safety of electronic health records: a national longitudinal study of medication-related decision support.
BMJ Qual Saf 2020 Jan;29(1):52-59. doi: 10.1136/bmjqs-2019-009609..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Safety, Medication, Electronic Prescribing (E-Prescribing), Medication: Safety, Clinical Decision Support (CDS), Decision Making
Barnes DE, Zhou J, Walker RL
Development and validation of eRADAR: a tool using EHR Data to detect unrecognized dementia.
The goal of this retrospective cohort study was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia. The tool was named EHR Risk of Alzheimer’s and Dementia Assessment Rule (eRADAR). This study was conducted at Kaiser Permanente Washington (KPWA) using participants in the Adult Changes in Thought (ACT) study who undergo comprehensive testing every 2 years to detect and diagnose dementia and have linked KPWA EHR data. Overall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 49% were previously unrecognized in the EHR. The final 31-predictor model included markers of dementia-related symptoms, healthcare utilization patterns, and dementia risk factors. The study showed good discrimination in the development interval and validation samples.
AHRQ-funded; HS022982.
Citation: Barnes DE, Zhou J, Walker RL .
Development and validation of eRADAR: a tool using EHR Data to detect unrecognized dementia.
J Am Geriatr Soc 2020 Jan;68(1):103-11. doi: 10.1111/jgs.16182..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Dementia, Neurological Disorders, Diagnostic Safety and Quality, Clinical Decision Support (CDS), Decision Making
Wissel BD, Greiner TA, Holland-Bouley KD
Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery.
Delay to resective epilepsy surgery results in avoidable disease burden and increased risk of mortality. The objective of this study was to prospectively validate a natural language processing (NLP) application that uses provider notes to assign epilepsy surgery candidacy scores. The authors suggest that an electronic health record-integrated NLP application can accurately assign surgical candidacy scores to patients in a clinical setting.
AHRQ-funded; HS024977.
Citation: Wissel BD, Greiner TA, Holland-Bouley KD .
Prospective validation of a machine learning model that uses provider notes to identify candidates for resective epilepsy surgery.
Epilepsia 2020 Jan;61(1):39-48. doi: 10.1111/epi.16398..
Keywords: Neurological Disorders, Surgery, Health Information Technology (HIT), Clinical Decision Support (CDS), Decision Making
Lomotan EA, Meadows G, Michaels M
AHRQ Author: Lomotan EA
To share is human! Advancing evidence into practice through a national repository of interoperable clinical decision support.
The purpose of this study was to describe how a national repository of clinical decision support (CDS) can serve as a public resource for healthcare systems, academic researchers, and informaticists seeking to share and reuse CDS knowledge resources. AHRQ’s CDS Connect has provided a functional platform where CDS developers are actively sharing their work. CDS sharing may lead to improved implementation efficiency through numerous pathways, and further research is ongoing to quantify efficiencies gained.
AHRQ-authored; AHRQ-funded; 290201600001U; 233201500022I.
Citation: Lomotan EA, Meadows G, Michaels M .
To share is human! Advancing evidence into practice through a national repository of interoperable clinical decision support.
Appl Clin Inform 2020 Jan;11(1):112-21. doi: 10.1055/s-0040-1701253..
Keywords: Clinical Decision Support (CDS), Decision Making, Patient-Centered Outcomes Research, Evidence-Based Practice, Registries, Health Information Technology (HIT)
Downs SM, Bauer NS, Saha C
Effect of a computer-based decision support intervention on autism spectrum disorder screening in pediatric primary care clinics: a cluster randomized clinical trial.
This study examined outcomes for implementation of a decision support system called CHICA (Child Health Improvement Through Computer Automation) to improve screening rates for autism in children aged 18 to 24 months. A random sample of 274 children in four urban clinics was used. Two clinics participated in the intervention, and two served as controls. Because participating clinics requested intervention be discontinued for children aged 18 months, only results for those aged 24 months was analyzed. Of the 263 children with reviewed results, 92% were enrolled in Medicaid, 52.5% were African American, and 36.5% were Hispanic. Screening rates increased from 0% at baseline to 100% in 24 months during the study period of November 2010 to November 2012. Screening results were positive for 265 of 980 children screened by CHICA in the time period, with 2 children from the intervention group positively diagnosed in the time frame of the study.
AHRQ-funded; HS018453.
Citation: Downs SM, Bauer NS, Saha C .
Effect of a computer-based decision support intervention on autism spectrum disorder screening in pediatric primary care clinics: a cluster randomized clinical trial.
JAMA Netw Open 2019 Dec 2;2(12):e1917676. doi: 10.1001/jamanetworkopen.2019.17676..
Keywords: Autism, Clinical Decision Support (CDS), Decision Making, Health Information Technology (HIT), Primary Care, Children/Adolescents, Screening
Levy AE, Shah NR, Matheny ME
Determining post-test risk in a national sample of stress nuclear myocardial perfusion imaging reports: implications for natural language processing tools.
The authors investigated whether Natural Language Processing (NLP) tools could potentially help estimate myocardial perfusion imaging (MPI) risk. Subjects were VA patients who underwent stress MPI and coronary angiography 2009-11; stress test reports were randomly selected for analysis. The authors found that post-test ischemic risk was determinable but rarely reported in this sample of stress MPI reports. They conclude that this supports the potential use of NLP to help clarify risk and recommend further study of NLP in this context.
AHRQ-funded; HS022998.
Citation: Levy AE, Shah NR, Matheny ME .
Determining post-test risk in a national sample of stress nuclear myocardial perfusion imaging reports: implications for natural language processing tools.
J Nucl Cardiol 2019 Dec;26(6):1878-85. doi: 10.1007/s12350-018-1275-y..
Keywords: Imaging, Risk, Clinical Decision Support (CDS), Health Information Technology (HIT), Diagnostic Safety and Quality, Cardiovascular Conditions, Heart Disease and Health
Lambert BL, Galanter W, Liu KL
Automated detection of wrong-drug prescribing errors.
Investigators assessed the specificity of an algorithm designed to detect look-alike/sound-alike (LASA) medication prescribing errors in electronic health record (EHR) data. They found that automated detection of LASA medication errors is feasible and can reveal errors not currently detected by other means. Additionally, real-time error detection is not possible with the current system. They suggested that further development should replicate their analysis in other health systems and on a larger set of medications and should decrease clinician time spent reviewing false-positive triggers by increasing specificity.
AHRQ-funded; HS021093.
Citation: Lambert BL, Galanter W, Liu KL .
Automated detection of wrong-drug prescribing errors.
BMJ Qual Saf 2019 Nov;28(11):908-15. doi: 10.1136/bmjqs-2019-009420..
Keywords: Adverse Drug Events (ADE), Adverse Events, Clinical Decision Support (CDS), Electronic Health Records (EHRs), Health Information Technology (HIT), Medical Errors, Medication, Patient Safety
Blecker S, Austrian JS, Horwitz LI
Interrupting providers with clinical decision support to improve care for heart failure.
The goal of this study was to develop a clinical decision support (CDS) system to recommend an angiotenson converting enzyme (ACE) inhibitor during hospitalization so it could be promoted for continuation at discharge. Patients who were hospitalized with reduced ejection fraction were pseudo-randomized to deliver interruptive or non-interruptive CDS alerts to providers based on the patients’ even or odd medical record number. The utilization rate was higher for interruptive alert versus non-interruptive alert hospitalizations for a sample of 958. This resulted in improved quality of care for heart failure patients.
AHRQ-funded; HS023683.
Citation: Blecker S, Austrian JS, Horwitz LI .
Interrupting providers with clinical decision support to improve care for heart failure.
Int J Med Inform 2019 Nov;131:103956. doi: 10.1016/j.ijmedinf.2019.103956..
Keywords: Clinical Decision Support (CDS), Decision Making, Heart Disease and Health, Cardiovascular Conditions, Medication, Medication: Safety, Patient Safety, Quality Improvement, Quality of Care
Cochran AL, Rathouz PJ, Kocher KE
A latent variable approach to potential outcomes for emergency department admission decisions.
The authors sought to provide a general framework to evaluate admission decisions from electronic healthcare records. They estimated that while admitting a patient with higher latent needs reduced the 30-day risk of revisiting the emergency department or later being admitted through the emergency department by over 79%, admitting a patient with lower latent needs actually increased these 30-day risks by 3.0% and 7.6%, respectively.
AHRQ-funded; HS024160.
Citation: Cochran AL, Rathouz PJ, Kocher KE .
A latent variable approach to potential outcomes for emergency department admission decisions.
Stat Med 2019 Sep 10;38(20):3911-35. doi: 10.1002/sim.8210..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Emergency Department, Clinical Decision Support (CDS), Decision Making, Hospitalization
Wissel BD, Greiner HM, Glauser TA
Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.
Racial disparities in the utilization of epilepsy surgery are well documented, but it is unknown whether a natural language processing (NLP) algorithm trained on physician notes would produce biased recommendations for epilepsy presurgical evaluations. To assess this, an NLP algorithm was trained to identify potential surgical candidates using 1097 notes from 175 epilepsy patients with a history of resective epilepsy surgery and 268 patients who achieved seizure freedom without surgery (total N = 443 patients).
AHRQ-funded; HS024977.
Citation: Wissel BD, Greiner HM, Glauser TA .
Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.
Epilepsia 2019 Sep;60(9):e93-e98. doi: 10.1111/epi.16320..
Keywords: Neurological Disorders, Surgery, Clinical Decision Support (CDS), Healthcare Utilization, Health Information Technology (HIT), Decision Making
Gance-Cleveland B, Leiferman J, Aldrich H
Using the technology acceptance model to develop startsmart: mHealth for screening, brief intervention, and referral for risk and protective factors in pregnancy.
The purpose of this study was to develop StartSmart, a mobile health (mHealth) intervention to support evidence-based prenatal screening, brief intervention, and referral to treatment for risk and protective factors in pregnancy. Expert clinicians provided guidance on the screening instruments, resources, and practice guidelines. Clinicians suggested identifying specific prenatal visits for the screening. Patients reported that the tablet-based screening was useful to promote adherence to guidelines and provided suggestions for improvement.
AHRQ-funded; HS024738.
Citation: Gance-Cleveland B, Leiferman J, Aldrich H .
Using the technology acceptance model to develop startsmart: mHealth for screening, brief intervention, and referral for risk and protective factors in pregnancy.
J Midwifery Womens Health 2019 Sep;64(5):630-40. doi: 10.1111/jmwh.13009..
Keywords: Health Information Technology (HIT), Domestic Violence, Clinical Decision Support (CDS), Decision Making, Pregnancy, Women, Evidence-Based Practice, Screening, Prevention
Nguyen BP, Reese T, Decker S
Implementation of clinical decision support services to detect potential drug-drug interaction using clinical quality language.
The authors report on the implementation and evaluation of CDS Services which represent potential drug-drug interactions knowledge with Clinical Quality Language (CQL). Their suggested solution is based on emerging standards including CDS Hooks, FHIR, and CQL. They selected two use cases, implemented them with CQL rules, and tested them.
AHRQ-funded; HS023826; HS025984.
Citation: Nguyen BP, Reese T, Decker S .
Implementation of clinical decision support services to detect potential drug-drug interaction using clinical quality language.
Stud Health Technol Inform 2019 Aug 21;264:724-28. doi: 10.3233/shti190318..
Keywords: Clinical Decision Support (CDS), Adverse Drug Events (ADE), Medication, Adverse Events, Patient Safety, Health Information Technology (HIT)