National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Adverse Drug Events (ADE) (4)
- Adverse Events (5)
- Autism (1)
- Behavioral Health (1)
- Cardiovascular Conditions (1)
- Care Management (1)
- Catheter-Associated Urinary Tract Infection (CAUTI) (1)
- Children/Adolescents (4)
- Chronic Conditions (1)
- (-) Clinical Decision Support (CDS) (22)
- Diagnostic Safety and Quality (1)
- Disabilities (1)
- Domestic Violence (1)
- Electronic Health Records (EHRs) (8)
- Electronic Prescribing (E-Prescribing) (1)
- Emergency Department (2)
- Evidence-Based Practice (1)
- Genetics (2)
- Healthcare-Associated Infections (HAIs) (1)
- Healthcare Delivery (2)
- Healthcare Utilization (1)
- Health Information Exchange (HIE) (1)
- (-) Health Information Technology (HIT) (22)
- Heart Disease and Health (1)
- Hospitalization (2)
- Imaging (1)
- Medical Errors (4)
- Medication (5)
- Neurological Disorders (1)
- Newborns/Infants (1)
- Nutrition (1)
- Pain (1)
- Patient-Centered Outcomes Research (1)
- Patient Adherence/Compliance (1)
- Patient Safety (6)
- Pregnancy (1)
- Prevention (2)
- Primary Care (5)
- Risk (1)
- Screening (2)
- Shared Decision Making (8)
- Surgery (1)
- Urinary Tract Infection (UTI) (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 22 of 22 Research Studies DisplayedDowns 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), Shared 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
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), Shared 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), Shared 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), Shared 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)
Liang C, Miao Q, Kang H
Leveraging patient safety research: efforts made fifteen years since To Err Is Human.
The present study sought to explore the associations between federal incentives of patient safety research and the outcomes from 1995 to 2014, in which two historical events - the release of To Err Is Human and the American Recovery and Reinvestment Act - were considered in the analysis. They concluded that their findings suggested a positive outcome in patient safety research.
AHRQ-funded; HS022895.
Citation: Liang C, Miao Q, Kang H .
Leveraging patient safety research: efforts made fifteen years since To Err Is Human.
Stud Health Technol Inform 2019 Aug 21;264:983-87. doi: 10.3233/shti190371..
Keywords: Patient Safety, Medical Errors, Adverse Events, Clinical Decision Support (CDS), Health Information Technology (HIT)
Harle CA, DiIulio J, Downs SM
Decision-centered design of patient information visualizations to support chronic pain care.
The objective of this study was to describe a decision-centered design process, and resultant interactive patient information displays, to support key clinical decision requirements in chronic noncancer pain care. Through critical decision method interviews and a half-day multidisciplinary design workshop, researchers designed an interactive prototype, the Chronic Pain Treatment Tracker. This prototype summarizes the current treatment plan, past treatment history, potential future treatments, and treatment options that require caution. The researchers concluded that the Chronic Pain Treatment Tracker presents clinicians with the information they need in a structure that promotes quick uptake, understanding, and action.
AHRQ-funded; HS023306.
Citation: Harle CA, DiIulio J, Downs SM .
Decision-centered design of patient information visualizations to support chronic pain care.
Appl Clin Inform 2019 Aug;10(4):719-28. doi: 10.1055/s-0039-1696668..
Keywords: Pain, Chronic Conditions, Shared Decision Making, Health Information Technology (HIT), Clinical Decision Support (CDS), Care Management, Healthcare Delivery
Ruaño G, Holford T, Seip RL
Pharmacogenetic clinical decision support for psychiatric hospitalization: design of the CYP-GUIDES randomized controlled trial.
The CYP-GUIDES (Cytochrome Psychotropic Genotyping Under Investigation for Decision Support) trial aims to establish evidence for clinical pharmacogenetics in psychotropic prescription in severely depressed inpatients. This article describes the design of a Randomized Controlled Trial (RCT) of CYP2D6 genotype-guided versus standard care psychotropic prescription. The CYP-GUIDES trial will assess whether clinical prescribing guided by CYP2D6 functional status can improve the treatment of psychiatric inpatients, shorten the length of hospitalization, and reduce readmission.
AHRQ-funded; HS022304.
Citation: Ruaño G, Holford T, Seip RL .
Pharmacogenetic clinical decision support for psychiatric hospitalization: design of the CYP-GUIDES randomized controlled trial.
Contemp Clin Trials 2019 Aug;83:27-36. doi: 10.1016/j.cct.2019.06.008..
Keywords: Behavioral Health, Hospitalization, Clinical Decision Support (CDS), Health Information Technology (HIT), Genetics
Patterson BW, Pulia MS, Ravi S
Scope and influence of electronic health record-integrated clinical decision support in the emergency department: a systematic review.
This systematic review examined the scope and influence of electronic health record-integrated clinical decision support (CDS) technologies implemented in hospital emergency departments. A literature search was conducted using 4 databases from the inception of these CDS systems through January 2018. Out of 2,558 potential studies identified, 42 met inclusion criteria. Common uses for CDS technologies included medication and radiology ordering practices, and more comprehensive systems supporting diagnosis and treatment for specific diseases. The majority of studies (83%) reported positive effects on outcomes, with most studies using a pre-post experimental design (76%). The authors concluded that although most studies show positive effects of CDS technologies, many of the studies were small and poorly controlled.
AHRQ-funded; HS024342; HS024558; HS022086.
Citation: Patterson BW, Pulia MS, Ravi S .
Scope and influence of electronic health record-integrated clinical decision support in the emergency department: a systematic review.
Ann Emerg Med 2019 Aug;74(2):285-96. doi: 10.1016/j.annemergmed.2018.10.034..
Keywords: Clinical Decision Support (CDS), Electronic Health Records (EHRs), Health Information Technology (HIT), Emergency Department
Powers EM, Shiffman RN, Melnick ER
Efficacy and unintended consequences of hard-stop alerts in electronic health record systems: a systematic review.
Clinical decision support (CDS) hard-stop alerts-those in which the user is either prevented from taking an action altogether or allowed to proceed only with the external override of a third party-are increasingly common but can be problematic. To understand their appropriate application, the investigators explored 3 key questions: (1) To what extent are hard-stop alerts effective in improving patient health and healthcare delivery outcomes? (2) What are the adverse events and unintended consequences of hard-stop alerts? (3) How do hard-stop alerts compare to soft-stop alerts?
AHRQ-funded; HS024332.
Citation: Powers EM, Shiffman RN, Melnick ER .
Efficacy and unintended consequences of hard-stop alerts in electronic health record systems: a systematic review.
J Am Med Inform Assoc 2018 Nov;25(11):1556-66. doi: 10.1093/jamia/ocy112..
Keywords: Clinical Decision Support (CDS), Electronic Health Records (EHRs), Health Information Technology (HIT), Healthcare Delivery, Patient Safety
Welch BM, Eilbeck K, Del Fiol G
Technical desiderata for the integration of genomic data with clinical decision support.
The objective of this study is to develop and validate a guiding set of technical desiderata for supporting the clinical use of the whole genome sequence (WGS) through clinical decision support (CDS). A panel of domain experts in genomics and CDS developed a proposed set of seven additional requirements. These additional desiderata provide important guiding principles for the technical development of CDS capabilities for the clinical use of WGS information.
AHRQ-funded; HS018352.
Citation: Welch BM, Eilbeck K, Del Fiol G .
Technical desiderata for the integration of genomic data with clinical decision support.
J Biomed Inform 2014 Oct;51:3-7. doi: 10.1016/j.jbi.2014.05.014..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Genetics, Electronic Health Records (EHRs), Shared Decision Making
Ranji SR, Rennke S, Wachter RM
Computerised provider order entry combined with clinical decision support systems to improve medication safety: a narrative review.
The authors searched AHRQ's Patient Safety Net to identify reviews of the effect of computerised provider order entry (CPOE) combined with clinical decision support systems (CDSS) on adverse drug event (ADE) rates in inpatient and outpatient settings. They found that CPOE+CDSS was consistently reported to reduce prescribing errors, but does not appear to prevent clinical ADEs in either the inpatient or outpatient setting. Implementation of CPOE+CDSS profoundly changes staff workflow, often leading to unintended consequences and new safety issues (such as alert fatigue) which limit the system's safety effects.
AHRQ-funded; 2902007100621.
Citation: Ranji SR, Rennke S, Wachter RM .
Computerised provider order entry combined with clinical decision support systems to improve medication safety: a narrative review.
BMJ Qual Saf 2014 Sep;23(9):773-80. doi: 10.1136/bmjqs-2013-002165.
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Keywords: Adverse Drug Events (ADE), Adverse Events, Medical Errors, Clinical Decision Support (CDS), Health Information Technology (HIT), Medication, Patient Safety
Baillie CA, Epps M, Hanish A
Usability and impact of a computerized clinical decision support intervention designed to reduce urinary catheter utilization and catheter-associated urinary tract infections.
The researchers evaluated the usability and effectiveness of a computerized clinical decision support (CDS) intervention aimed at reducing the duration of urinary tract catheterizations. They found that usability improved to 15% with the revised reminder. The catheter utilization ratio declined over the 3 time periods, as did CAUTIs per 1,000 patient-days. They concluded that the usability of the reminder was highly dependent on its user interface, with a homegrown version of the reminder resulting in higher impact than a stock reminder.
AHRQ-funded; HS016946.
Citation: Baillie CA, Epps M, Hanish A .
Usability and impact of a computerized clinical decision support intervention designed to reduce urinary catheter utilization and catheter-associated urinary tract infections.
Infect Control Hosp Epidemiol 2014 Sep;35(9):1147-55. doi: 10.1086/677630.
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Keywords: Catheter-Associated Urinary Tract Infection (CAUTI), Clinical Decision Support (CDS), Electronic Health Records (EHRs), Health Information Technology (HIT), Healthcare-Associated Infections (HAIs), Patient-Centered Outcomes Research, Urinary Tract Infection (UTI)
Carroll AE, Bauer NS, Dugan TM
Use of a computerized decision aid for developmental surveillance and screening: a randomized clinical trial.
A study to determine whether a computerized clinical decision support system is an effective approach to improve standardized developmental surveillance and screening (DSS) within primary care practices found that use of such a system significantly increased the number of children screened at 9, 18, and 30 months of age. It also increased the number of children who ultimately were diagnosed as having a developmental delay.
AHRQ-funded; HS017939
Citation: Carroll AE, Bauer NS, Dugan TM .
Use of a computerized decision aid for developmental surveillance and screening: a randomized clinical trial.
JAMA Pediatr. 2014 Sep;168(9):815-21. doi: 10.1001/jamapediatrics.2014.464..
Keywords: Health Information Technology (HIT), Clinical Decision Support (CDS), Primary Care, Children/Adolescents
Galanter WL, Bryson ML, Falck S
Indication alerts intercept drug name confusion errors during computerized entry of medication orders.
The authors measured whether indication alerts at the time of computerized physician order entry (CPOE) can intercept drug name confusion errors. They found that indication alerts intercepted 1.4 drug name confusion errors per 1000 alerts and recommended that institutions with CPOE consider using indication prompts to intercept drug name confusion errors.
AHRQ-funded; HS021093.
Citation: Galanter WL, Bryson ML, Falck S .
Indication alerts intercept drug name confusion errors during computerized entry of medication orders.
PLoS One 2014 Jul 15;9(7):e101977. doi: 10.1371/journal.pone.0101977.
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Keywords: Clinical Decision Support (CDS), Adverse Drug Events (ADE), Adverse Events, Medical Errors, Health Information Technology (HIT), Medication, Patient Safety
Bennett WE, Jr., Hendrix KS, Thompson-Fleming RT
Early cow's milk introduction is associated with failed personal-social milestones after 1 year of age.
The researchers used a novel computerized decision support system to gather data from multiple general pediatrics offices.They found an association between the introduction of cow's milk before 1 year of age and the rate of delayed developmental milestones after 1 year of age, adding strength to the recommendations from the AAP and IOM to delay cow's milk introduction until after 1 year of age.
AHRQ-funded; HS017939; HS018453; HS020640.
Citation: Bennett WE, Jr., Hendrix KS, Thompson-Fleming RT .
Early cow's milk introduction is associated with failed personal-social milestones after 1 year of age.
Eur J Pediatr 2014 Jul;173(7):887-92. doi: 10.1007/s00431-014-2265-y.
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Keywords: Clinical Decision Support (CDS), Disabilities, Health Information Technology (HIT), Newborns/Infants, Nutrition
Pevnick JM, Li N, Asch SM
Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence.
The researchers evaluated whether formulary decision support (FDS) could reduce patient medication costs, and thereby improve adherence. In the studied population, interruptive FDS shifted prescribing toward preferred tier medications, but these medications were only minimally less expensive for patients. Thus, FDS did not significantly increase adherence.
AHRQ-funded; HS016391.
Citation: Pevnick JM, Li N, Asch SM .
Effect of electronic prescribing with formulary decision support on medication tier, copayments, and adherence.
BMC Med Inform Decis Mak 2014;14:79. doi: 10.1186/1472-6947-14-79..
Keywords: Electronic Prescribing (E-Prescribing), Medication, Patient Adherence/Compliance, Clinical Decision Support (CDS), Health Information Technology (HIT)
Nagykaldi ZJ, Yeaman B, Jones M
HIE-i-health information exchange with intelligence.
This article reports on the development and pilot testing of an innovative approach to implement health information exchange with intelligence (HIE-i) in primary care settings. Records of 346 patients were studied in 6 primary care practices. The results suggest that coupling a geographically inclusive set of clinical data with HIE-based clinical decision support for prevention can considerably improve prospective care delivery.
AHRQ-funded; 290200710009I.
Citation: Nagykaldi ZJ, Yeaman B, Jones M .
HIE-i-health information exchange with intelligence.
J Ambul Care Manage 2014 Jan-Mar;37(1):20-31. doi: 10.1097/jac.0000000000000002..
Keywords: Clinical Decision Support (CDS), Health Information Exchange (HIE), Health Information Technology (HIT), Prevention, Primary Care
Bauer NS, Carroll AE, Downs SM
Understanding the acceptability of a computer decision support system in pediatric primary care.
In this study, the investigators examine the attitudes and opinions of pediatric users' toward the Child Health Improvement through Computer Automation (CHICA) system, a computer decision support system linked to an electronic health record in four community pediatric clinics. The investigators found that pediatric users appreciated the system's automation and enhancements that allowed relevant and meaningful clinical data to be accessible at point of care.
AHRQ-funded; HS018453; HS017939.
Citation: Bauer NS, Carroll AE, Downs SM .
Understanding the acceptability of a computer decision support system in pediatric primary care.
J Am Med Inform Assoc 2014 Jan-Feb;21(1):146-53. doi: 10.1136/amiajnl-2013-001851..
Keywords: Children/Adolescents, Clinical Decision Support (CDS), Shared Decision Making, Electronic Health Records (EHRs), Health Information Technology (HIT), Primary Care
Bauer NS, Carroll AE, Downs SM
Understanding the acceptability of a computer decision support system in pediatric primary care.
In this study, the investigators examine the attitudes and opinions of pediatric users' toward the Child Health Improvement through Computer Automation (CHICA) system, a computer decision support system linked to an electronic health record in four community pediatric clinics. The investigators found that pediatric users appreciated the system's automation and enhancements that allowed relevant and meaningful clinical data to be accessible at point of care.
AHRQ-funded; HS018453; HS017939.
Citation: Bauer NS, Carroll AE, Downs SM .
Understanding the acceptability of a computer decision support system in pediatric primary care.
J Am Med Inform Assoc 2014 Jan-Feb;21(1):146-53. doi: 10.1136/amiajnl-2013-001851..
Keywords: Children/Adolescents, Clinical Decision Support (CDS), Shared Decision Making, Electronic Health Records (EHRs), Health Information Technology (HIT), Primary Care