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Topics
- Behavioral Health (1)
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- (-) Health Information Technology (HIT) (12)
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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
1 to 12 of 12 Research Studies DisplayedYang Y, Bass EJ, Sockolow PS
Knowledge elicitation of homecare admission decision making processes via focus group, member checking and data visualization.
Researchers elicit knowledge related to expert decision-making processes to inform information technology design and related interventions. In this study, the investigators examine knowledge elicitation of homecare admission decision making processes via focus group, member checking and data visualization. The investigators concluded that the data collection and validation methodology showed promise for knowledge elicitation in time-constrained situations.
AHRQ-funded; HS024537.
Citation: Yang Y, Bass EJ, Sockolow PS .
Knowledge elicitation of homecare admission decision making processes via focus group, member checking and data visualization.
AMIA Annu Symp Proc 2018 Dec 5;2018:1127-36..
Keywords: Home Healthcare, Shared Decision Making, Health Information Technology (HIT), Data
Quintana Y, Crotty B, Fahy D
Information sharing across generations and environments (InfoSAGE): study design and methodology protocol.
This open prospective cohort study aimed to assess a novel, Internet based, family-centric communication and collaboration platform created to address the information needs of elders and their informal caregivers in a community setting. It used a mixed methods approach, utilizing qualitative survey data along with website usage analytic data.
AHRQ-funded; HS021495.
Citation: Quintana Y, Crotty B, Fahy D .
Information sharing across generations and environments (InfoSAGE): study design and methodology protocol.
BMC Med Inform Decis Mak 2018 Nov 20;18(1):105. doi: 10.1186/s12911-018-0697-4.
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BMC Med Inform Decis Mak 2018 Nov 20;18(1):105. doi: 10.1186/s12911-018-0697-4.
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Keywords: Caregiving, Communication, Shared Decision Making, Elderly, Health Information Technology (HIT), Patient-Centered Healthcare, Clinician-Patient Communication, Web-Based
Gianfrancesco MA, Tamang S, Yazdany J
Potential biases in machine learning algorithms using electronic health record data.
This Special Communication outlines the potential biases that may be introduced into machine learning-based clinical decision support tools that use electronic health record data and proposes potential solutions to the problems of overreliance on automation, algorithms based on biased data, and algorithms that do not provide information that is clinically meaningful.
AHRQ-funded; HS024412.
Citation: Gianfrancesco MA, Tamang S, Yazdany J .
Potential biases in machine learning algorithms using electronic health record data.
JAMA Intern Med 2018 Nov;178(11):1544-47. doi: 10.1001/jamainternmed.2018.3763..
Keywords: Electronic Health Records (EHRs), Clinical Decision Support (CDS), Health Information Technology (HIT), Shared Decision Making
Panattoni L, Chan A, Yang Y
Nudging physicians and patients with autopend clinical decision support to improve diabetes management.
This study’s objective was to determine the impact on routine glycalated hemoglobin (A1C) laboratory test completion of incorporating an autopend laboratory order functionality into clinical decision support. The clinical decision support includes 1) routing provider alerts to a separate electronic folder, 2) automatically populating preauthorization forms, and 3) linking the timing and content of electronic patient health maintenance topic (HMT) reminders to the provider authorization. The likelihood of A1C laboratory test completion increased after autopend by between 21% to 33.9%.
AHRQ-funded; HS019167.
Citation: Panattoni L, Chan A, Yang Y .
Nudging physicians and patients with autopend clinical decision support to improve diabetes management.
Am J Manag Care 2018 Oct;24(10):479-83..
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT)
Meyer AND, Thompson PJ, Khanna A
Evaluating a mobile application for improving clinical laboratory test ordering and diagnosis.
This study evaluated if a mobile application improved generalist physicians' appropriate laboratory test ordering and diagnosis decisions and assessed if physicians perceive it as useful for learning. The study concluded that a mobile app, PTT (partial thromboplastin times) Advisor, may contribute to better test ordering and diagnosis, serve as a learning tool for diagnostic evaluation of certain clinical disorders, and improve patient outcomes.
AHRQ-funded; HS022087; HS023602.
Citation: Meyer AND, Thompson PJ, Khanna A .
Evaluating a mobile application for improving clinical laboratory test ordering and diagnosis.
J Am Med Inform Assoc 2018 Jul;25(7):841-47. doi: 10.1093/jamia/ocy026..
Keywords: Shared Decision Making, Diagnostic Safety and Quality, Health Information Technology (HIT)
Mistry B, Stewart De Ramirez S, Kelen G
Accuracy and reliability of emergency department triage using the emergency severity index: an international multicenter assessment.
This study assessed the accuracy and variability of triage score assignment by emergency department (ED) nurses using the Emergency Severity Index (ESI) in 3 countries. It found that the concordance of nurse-assigned ESI score with reference standard was universally poor and variability was high. Although the ESI is the most popular ED triage tool in the United States and is increasingly used worldwide, its findings point to a need for more reliable ED triage tools.
AHRQ-funded; HS023641.
Citation: Mistry B, Stewart De Ramirez S, Kelen G .
Accuracy and reliability of emergency department triage using the emergency severity index: an international multicenter assessment.
Ann Emerg Med 2018 May;71(5):581-87.e3. doi: 10.1016/j.annemergmed.2017.09.036.
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Keywords: Shared Decision Making, Emergency Department, Emergency Medical Services (EMS), Health Information Technology (HIT), Nursing
Levin S, Toerper M, Hamrock E
Machine-learning-based electronic triage more accurately differentiates patients with respect to clinical outcomes compared with the emergency severity index.
This study seeks to evaluate an electronic triage system (e-triage) based on machine learning that predicts likelihood of acute outcomes enabling improved patient differentiation. It concluded that E-triage more accurately classifies emergency severity index (ESI) level 3 patients and highlights opportunities to use predictive analytics to support triage decisionmaking.
AHRQ-funded; HS023641.
Citation: Levin S, Toerper M, Hamrock E .
Machine-learning-based electronic triage more accurately differentiates patients with respect to clinical outcomes compared with the emergency severity index.
Ann Emerg Med 2018 May;71(5):565-74.e2. doi: 10.1016/j.annemergmed.2017.08.005.
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Keywords: Shared Decision Making, Health Information Technology (HIT), Health Information Technology (HIT), Outcomes
Nanji KC, Seger DL, Slight SP
Medication-related clinical decision support alert overrides in inpatients.
This study examined the use of medical-related clinical decision support alert overrides by clinicians in hospital inpatient settings. Overall, almost three-quarters of alerts were overridden, with 40% of them not being appropriate. The majority of overrides dealing with duplicate drug, patient allergy or formulary substitution alerts were appropriate but very few for renal- or age-based were. The authors concluded that research should be done to optimize alert types and frequencies to reduce alarm fatigue.
AHRQ-funded; HS024764.
Citation: Nanji KC, Seger DL, Slight SP .
Medication-related clinical decision support alert overrides in inpatients.
J Am Med Inform Assoc 2018 May;25(5):476-81. doi: 10.1093/jamia/ocx115..
Keywords: Clinical Decision Support (CDS), Shared Decision Making, Health Information Technology (HIT), Inpatient Care, Medication
Wilbanks J
Design issues in e-consent.
Informed consent has not been implemented as a relationship, but instead as a single-point transaction that must be completed in order to enroll participants. This paper discusses e-consent and notes that it is an opportunity to: truly inform research participants about clinical protocols; provide a meaningful choice architecture to support a potential participant’s decision making about whether or not to enroll; and serve as the beginning of an ongoing ethical relationship with study participants.
AHRQ-funded; HS022789.
Citation: Wilbanks J .
Design issues in e-consent.
J Law Med Ethics 2018 Mar;46(1):110-18. doi: 10.1177/1073110518766025..
Keywords: Shared Decision Making, Health Information Technology (HIT), Patient-Centered Outcomes Research, Research Methodologies
Aalsma MC, Zerr AM, Etter DJ
Physician intervention to positive depression screens among adolescents in primary care.
The objective of this study was to determine the effectiveness of computer-based screening and physician feedback to guide adolescent depression management within primary care. The investigators found that when a computer-based decision support system algorithm focused on adolescent depression and was implemented in two primary care clinics, a majority of physicians utilized screening results to guide clinical care.
AHRQ-funded; HS022681.
Citation: Aalsma MC, Zerr AM, Etter DJ .
Physician intervention to positive depression screens among adolescents in primary care.
J Adolesc Health 2018 Feb;62(2):212-18. doi: 10.1016/j.jadohealth.2017.08.023..
Keywords: Care Management, Children/Adolescents, Shared Decision Making, Depression, Health Information Technology (HIT), Behavioral Health, Primary Care, Primary Care: Models of Care, Screening
Dowding D, Merrill JA, Onorato N
The impact of home care nurses' numeracy and graph literacy on comprehension of visual display information: implications for dashboard design.
This study explored home care nurses' numeracy and graph literacy and their relationship to comprehension of visualized data. Results suggest that nurses' comprehension of visualized information is influenced by their numeracy, graph literacy, and the display format of the data. Individual differences in numeracy and graph literacy skills need to be taken into account when designing dashboard technology.
AHRQ-funded; HS023855.
Citation: Dowding D, Merrill JA, Onorato N .
The impact of home care nurses' numeracy and graph literacy on comprehension of visual display information: implications for dashboard design.
J Am Med Inform Assoc 2018 Feb;25(2):175-82. doi: 10.1093/jamia/ocx042.
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Keywords: Shared Decision Making, Health Information Technology (HIT), Health Literacy, Health Information Technology (HIT), Nursing
Ye S, Leppin AL, Chan AY
An informatics approach to implement support for shared decision making for primary prevention statin therapy.
The study authors designed an informatics decision-support tool to facilitate use of the Mayo Clinic Statin Choice decision aid at the point-of-care and evaluated its impact. The investigators found that implementation of a point-of-care decision-support tool increased the usage of decision aids for primary prevention statin therapy. This effect does not appear to be mediated by any concomitant changes in physician attitude toward shared decision making.
AHRQ-funded; HS025198.
Citation: Ye S, Leppin AL, Chan AY .
An informatics approach to implement support for shared decision making for primary prevention statin therapy.
MDM Policy Pract 2018 Jan-Jun;3(1):2381468318777752. doi: 10.1177/2381468318777752..
Keywords: Shared Decision Making, Health Information Technology (HIT), Medication, Prevention, Tools & Toolkits