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Research Studies is a monthly compilation of research articles funded by AHRQ or authored by AHRQ researchers and recently published in journals or newsletters.
Results
1 to 5 of 5 Research Studies Displayed
Soares WE, Knee A, Gemme SR
SC, et al. A prospective evaluation of Clinical HEART score agreement, accuracy, and adherence in emergency department chest pain patients.
The HEART score is a risk stratification aid that may safely reduce chest pain admissions for emergency department patients. However, differences in interpretation of subjective components potentially alters the performance of the score. In this study, the investigators compared agreement between HEART scores determined during clinical practice with research-generated scores and estimated their accuracy in predicting 30-day major adverse cardiac events.
AHRQ-funded; HS024815.
Citation:
Soares WE, Knee A, Gemme SR .
SC, et al. A prospective evaluation of Clinical HEART score agreement, accuracy, and adherence in emergency department chest pain patients.
Ann Emerg Med 2021 Aug;78(2):231-41. doi: 10.1016/j.annemergmed.2021.03.024..
Keywords:
Heart Disease and Health, Cardiovascular Conditions, Emergency Department, Diagnostic Safety and Quality, Clinical Decision Support (CDS), Health Information Technology (HIT)
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
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
Panahiazar M, Taslimitehrani V, Pereira NL
Using EHRs for heart failure therapy recommendation using multidimensional patient similarity analytics.
The authors developed a multidimensional patient similarity assessment technique that leverages multiple types of information from the electronic health records and predicts a medication plan for each new patient based on prior knowledge and data from similar patients.Their findings suggest that it is feasible to harness population-based information for an individual patient-specific assessment.
AHRQ-funded; HS023077.
Citation:
Panahiazar M, Taslimitehrani V, Pereira NL .
Using EHRs for heart failure therapy recommendation using multidimensional patient similarity analytics.
Stud Health Technol Inform 2015;210:369-73.
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Keywords:
Clinical Decision Support (CDS), Data, Electronic Health Records (EHRs), Heart Disease and Health, Patient-Centered Healthcare
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
