National Healthcare Quality and Disparities Report
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Search All Research Studies
AHRQ Research Studies Date
Topics
- Adverse Drug Events (ADE) (2)
- Adverse Events (3)
- Catheter-Associated Urinary Tract Infection (CAUTI) (1)
- Children/Adolescents (3)
- (-) Clinical Decision Support (CDS) (16)
- Decision Making (6)
- Diagnostic Safety and Quality (1)
- Disabilities (1)
- Electronic Health Records (EHRs) (4)
- Electronic Prescribing (E-Prescribing) (1)
- Genetics (1)
- Healthcare-Associated Infections (HAIs) (1)
- Health Information Exchange (HIE) (1)
- Health Information Technology (HIT) (10)
- Heart Disease and Health (1)
- Human Immunodeficiency Virus (HIV) (1)
- Long-Term Care (1)
- Medical Errors (2)
- Medication (3)
- Newborns/Infants (1)
- Nursing Homes (2)
- Nutrition (1)
- Patient-Centered Outcomes Research (1)
- Patient Adherence/Compliance (1)
- Patient Safety (3)
- Practice Patterns (1)
- Pressure Ulcers (1)
- Prevention (2)
- Primary Care (4)
- Quality Measures (1)
- Quality of Care (1)
- Urinary Tract Infection (UTI) (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 16 of 16 Research Studies DisplayedMcCullagh LJ, Sofianou A, Kannry J
User centered clinical decision support tools: adoption across clinician training level.
This study examined the differences in adoption of CDS tools across providers’ training level. It found that the completion rates of the CDS calculator and medication order sets were higher among first year residents compared to all other training levels. Attending physicians were the less likely to accept the initial step of the CDS tool (29.3 percent) or complete the medication order sets (22.4 percent) that guided their prescription decisions.
AHRQ-funded; HS018491.
Citation: McCullagh LJ, Sofianou A, Kannry J .
User centered clinical decision support tools: adoption across clinician training level.
Appl Clin Inform 2014 Dec 17;5(4):1015-25. doi: 10.4338/aci-2014-05-ra-0048.
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Keywords: Clinical Decision Support (CDS), Decision Making, Practice Patterns
Einbinder J, Hebel E, Wright A
The number needed to remind: a measure for assessing CDS effectiveness.
The purpose of this paper is to provide a better understanding of population based clinical decision support (CDS) performance measurement, to identify best practices for designing and implementing CDS, and to introduce two new quality measures, titled Reminder Performance (RP) and the Number Needed to Remind (NNR) for evaluating the effectiveness of clinical reminders in the context of the CDS Dashboards.
AHRQ-funded; 290200810010.
Citation: Einbinder J, Hebel E, Wright A .
The number needed to remind: a measure for assessing CDS effectiveness.
AMIA Annu Symp Proc 2014 Nov 14;2014:506-15..
Keywords: Decision Making, Clinical Decision Support (CDS), Quality Measures, Quality of Care
Boyce RD, Perera S, Nace DA
A survey of nursing home physicians to determine laboratory monitoring adverse drug event alert preferences.
The researchers conducted a survey to learn about the laboratory value thresholds that clinical event monitors should use to generate alerts about potential adverse drug events (ADEs). They found that the majority of physicians surveyed prefer alerting thresholds that would generally lead to fewer alerts than if widely accepted standardized laboratory ranges were used.
AHRQ-funded; HS019461; HS018721.
Citation: Boyce RD, Perera S, Nace DA .
A survey of nursing home physicians to determine laboratory monitoring adverse drug event alert preferences.
Appl Clin Inform 2014 Oct 29;5(4):895-906. doi: 10.4338/aci-2014-06-ra-0053..
Keywords: Nursing Homes, Clinical Decision Support (CDS), Adverse Events
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), 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
Islam R, Weir C, Del Fiol G
Heuristics in managing complex clinical decision tasks in experts' decision making.
The authors sought to understand how clinicians manage complexity while dealing with complex clinical decision tasks. They found that experts cope with complexity in a variety of ways, including using efficient and fast decision strategies to simplify complex decision tasks, mentally simulating outcomes, and focusing on only the most relevant information.
AHRQ-funded; HS023349.
Citation: Islam R, Weir C, Del Fiol G .
Heuristics in managing complex clinical decision tasks in experts' decision making.
IEEE Int Conf Healthc Inform 2014 Sep;2014:186-93. doi: 10.1109/ichi.2014.32.
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Keywords: Clinical Decision Support (CDS), Decision Making, 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
Crane HM, Heckbert SR, Drozd DR
Lessons learned from the design and implementation of myocardial infarction adjudication tailored for HIV clinical cohorts.
In this study, a team of researchers developed, implemented, and evaluated a myocardial infarction (MI) adjudication protocol for cohort research of human immunodeficiency virus. They found that central adjudication is crucial and that clinical diagnoses alone are insufficient for ascertainment of MI. Over half the events ultimately determined to be MIs were not identified by clinical diagnoses.
AHRQ-funded; HS019515
Citation: Crane HM, Heckbert SR, Drozd DR .
Lessons learned from the design and implementation of myocardial infarction adjudication tailored for HIV clinical cohorts.
Am J Epidemiol. 2014 Apr 15;179(8):996-1005. doi: 10.1093/aje/kwu010..
Keywords: Human Immunodeficiency Virus (HIV), Heart Disease and Health, Clinical Decision Support (CDS), Diagnostic Safety and Quality
Olsho LE, Spector WD, Williams CS
AHRQ Author: Spector WD
Evaluation of AHRQ's on-time pressure ulcer prevention program: a facilitator-assisted clinical decision support intervention for nursing homes.
The researchers evaluated the effectiveness of the On-Time Quality Improvement for Long Term Care (On-Time) program in reducing the rate of in-house-acquired pressure ulcers among nursing home residents. They found that On-Time implementation is associated with sizable reductions in pressure ulcer incidence.
AHRQ-authored; AHRQ-funded; 290200600011I.
Citation: Olsho LE, Spector WD, Williams CS .
Evaluation of AHRQ's on-time pressure ulcer prevention program: a facilitator-assisted clinical decision support intervention for nursing homes.
Med Care 2014 Mar;52(3):258-66. doi: 10.1097/mlr.0000000000000080.
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Keywords: Clinical Decision Support (CDS), Long-Term Care, Nursing Homes, Pressure Ulcers, Prevention
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), 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), Decision Making, Electronic Health Records (EHRs), Health Information Technology (HIT), Primary Care