National Healthcare Quality and Disparities Report
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Topics
- Blood Pressure (2)
- Blood Thinners (1)
- (-) Cardiovascular Conditions (17)
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- Diagnostic Safety and Quality (2)
- (-) Electronic Health Records (EHRs) (17)
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- Health Information Technology (HIT) (16)
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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 17 of 17 Research Studies DisplayedFuery MA, Kadhim B, Samsky MD
Electronic health record embedded strategies for improving care of patients with heart failure.
This article reviews recent findings from randomized clinical trials examining the impact of electronic health record (HER) alerts (called nudges) on quality of care for heart failure patients. These clinical trials demonstrated that some EHR alerts can improve care for heart failure patients. The trials described utilized default options, involved clinicians in the alert design process, provided actionable recommendations, and aimed to minimize disruptions to typical workflow.
AHRQ-funded; HS027626.
Citation: Fuery MA, Kadhim B, Samsky MD .
Electronic health record embedded strategies for improving care of patients with heart failure.
Curr Heart Fail Rep 2023 Aug; 20(4):280-86. doi: 10.1007/s11897-023-00614-0..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Heart Disease and Health, Cardiovascular Conditions, Chronic Conditions
Chu CD, Lenoir KM, Rai NK
Concordance between clinical outcomes in the systolic blood pressure intervention trial and in the electronic health record.
This study examined the role that electronic health records (EHRs) can play in follow-up for concordance with trial-ascertained outcomes. The authors linked EHR and trial data for participants in the Systolic Blood Pressure Intervention Trial (SPRINT), a randomized trial comparing intensive and standard blood pressure targets. Among participants with available EHR data concurrent to trial-ascertained outcomes, they calculated sensitivity, specificity, positive predictive value, and negative predictive value for EHR-recorded cardiovascular disease (CVD) events, using the gold standard of SPRINT-adjudicated outcomes (myocardial infarction (MI)/acute coronary syndrome (ACS), heart failure, stroke, and composite CVD events). They additionally compared the incidence of non-CVD adverse events (hyponatremia, hypernatremia, hypokalemia, hyperkalemia, bradycardia, and hypotension) in trial versus EHR data. Of the 2468 SPRINT participants included, EHR data demonstrated ≥80% sensitivity and specificity, and ≥99% negative predictive value for MI/ACS, heart failure, stroke, and composite CVD events. Positive predictive value ranged from 26% for heart failure to 52% for MI/ACS. Conclusions were that EHR data uniformly identified more non-CVD adverse events and higher incidence rates compared with trial ascertainment.
AHRQ-funded; HS026383.
Citation: Chu CD, Lenoir KM, Rai NK .
Concordance between clinical outcomes in the systolic blood pressure intervention trial and in the electronic health record.
Contemp Clin Trials 2023 May; 128:107172. doi: 10.1016/j.cct.2023.107172..
Keywords: Blood Pressure, Electronic Health Records (EHRs), Health Information Technology (HIT), Cardiovascular Conditions
Villa Zapata L, Boyce RD, Chou E
QTc prolongation with the use of hydroxychloroquine and concomitant arrhythmogenic medications: a retrospective study using electronic health records data.
The purpose of this AHRQ-funded retrospective study of electronic health records was to assess changes in the QTc interval in patients taking hydroxychloroquine (with or without concomitant QT-prolonging medications.) Patients were placed into one of 6 cohorts, depending upon their monotherapy with one of 3 different medications: hydroxychloroquine, methotrexate, or sulfasalazine, or, based on their exposure to any combination of those drugs with any other drug known to increase the QT interval. The study concluded that compared to sulfasalazine or methotrexate, hydroxychloroquine was related with an increase in the QTc interval.
AHRQ-funded; HS025984.
Citation: Villa Zapata L, Boyce RD, Chou E .
QTc prolongation with the use of hydroxychloroquine and concomitant arrhythmogenic medications: a retrospective study using electronic health records data.
Drugs Real World Outcomes 2022 Jun 5:1-9. doi: 10.1007/s40801-022-00307-5..
Keywords: Medication, Cardiovascular Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT)
Bobo WV, Ryu E, Petterson TM
Bi-directional association between depression and HF: an electronic health records-based cohort study.
This study examined whether heart failure (HF) patients were more likely to be diagnosed with depression, or patients with depression were more likely to be diagnosed with HF. This retrospective cohort study utilized electronic health records (EHRs) from a large healthcare system in 2006 for adults who received primary care services. The EHR identified 10,649 people with depression, and 5,911 people with HF between 2006 to 2018. In the depression cohort there were 2,024 newly diagnosed occurrences of HF, and 944 occurrences of newly diagnosed depression in the HF cohort over 4-6 years of follow-up. There was a significantly higher risk of developing HF in the depression cohort than vice versa.
AHRQ-funded; HS023077.
Citation: Bobo WV, Ryu E, Petterson TM .
Bi-directional association between depression and HF: an electronic health records-based cohort study.
J Comorb 2020 Jan-Dec;10:2235042x20984059. doi: 10.1177/2235042x20984059..
Keywords: Heart Disease and Health, Cardiovascular Conditions, Depression, Electronic Health Records (EHRs), Health Information Technology (HIT), Chronic Conditions
Byrd TF, Ahmad FS, Liebovitz DM
Defragmenting heart failure care: medical records integration.
This article discusses the need to improve interoperability of software systems so that so that providers and patients can access clinical information needed to help coordinate care of heart failure patients. New data standards currently being proposed in legislation would make it possible to guide clinical decision-making.
AHRQ-funded; HS026385.
Citation: Byrd TF, Ahmad FS, Liebovitz DM .
Defragmenting heart failure care: medical records integration.
Heart Fail Clin 2020 Oct;16(4):467-77. doi: 10.1016/j.hfc.2020.06.007..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Heart Disease and Health, Cardiovascular Conditions, Data
Shah RU, Mutharasan RK, Ahmad FS
Development of a portable tool to identify patients with atrial fibrillation using clinical notes from the electronic medical record.
The electronic medical record contains a wealth of information buried in free text. In this study, the investigators created a natural language processing algorithm to identify patients with atrial fibrillation (AF) using text alone. The authors concluded that this approach allowed better use of the clinical narrative and created an opportunity for precise, high-throughput cohort identification.
AHRQ-funded; HS026385.
Citation: Shah RU, Mutharasan RK, Ahmad FS .
Development of a portable tool to identify patients with atrial fibrillation using clinical notes from the electronic medical record.
Circ Cardiovasc Qual Outcomes 2020 Oct;13(10):e006516. doi: 10.1161/circoutcomes.120.006516..
Keywords: Heart Disease and Health, Cardiovascular Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT), Diagnostic Safety and Quality
Koopman RJ, Canfield SM, Belden JL
Home blood pressure data visualization for the management of hypertension: designing for patient and physician information needs.
This study examined whether using home blood pressure visualization tools helps management of hypertension for both patients and physicians. A multidisciplinary team used iterative user-centered design to create a blood pressure visualization EHR prototype that included patient-generated blood pressure data. The study included an attitude and behavior survey and 10 focus groups with 16 patients and 24 physicians. Most patients measured their blood pressure at home, but only half shared data with their physician. Data visualization helped patients and physicians have a fuller understanding of the blood pressure “story” and helped with patient-physician interactions to better control hypertension.
AHRQ-funded; HS023328.
Citation: Koopman RJ, Canfield SM, Belden JL .
Home blood pressure data visualization for the management of hypertension: designing for patient and physician information needs.
BMC Med Inform Decis Mak 2020 Aug 18;20(1):195. doi: 10.1186/s12911-020-01194-y..
Keywords: Blood Pressure, Electronic Health Records (EHRs), Health Information Technology (HIT), Chronic Conditions, Cardiovascular Conditions
Homco J, Carabin H, Nagykaldi Z
Validity of medical record abstraction and electronic health record-generated reports to assess performance on cardiovascular quality measures in primary care.
The purpose of this study was to compare observed performance scores measured using 2 imperfect reference standard data sources with misclassification-adjusted performance scores obtained using bayesian latent class analysis. Using aspirin, blood pressure, and smoking performance data from the Healthy Hearts for Oklahoma Project, researchers found that extracting information for the same individuals using different data sources generated different performance score estimates. Recommendations included further research to identify the sources of these differences.
AHRQ-funded; HS023919.
Citation: Homco J, Carabin H, Nagykaldi Z .
Validity of medical record abstraction and electronic health record-generated reports to assess performance on cardiovascular quality measures in primary care.
JAMA Netw Open 2020 Jul;3(7):e209411. doi: 10.1001/jamanetworkopen.2020.9411..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Cardiovascular Conditions, Quality Measures, Quality of Care, Primary Care, Provider Performance, Evidence-Based Practice
Wang SV, Rogers JR, Jin Y
Stepped-wedge randomised trial to evaluate population health intervention designed to increase appropriate anticoagulation in patients with atrial fibrillation.
Clinical guidelines recommend anticoagulation for patients with atrial fibrillation (AF) at high risk of stroke; however, studies report 40% of this population is not anticoagulated. The purpose of this study was to evaluate a population health intervention to increase anticoagulation use in high-risk patients with AF. The investigators concluded that algorithms to identify underuse of anticoagulation among patients with AF in healthcare databases may not capture clinical subtleties or patient preferences and may overestimate the extent of undertreatment.
AHRQ-funded; HS022193.
Citation: Wang SV, Rogers JR, Jin Y .
Stepped-wedge randomised trial to evaluate population health intervention designed to increase appropriate anticoagulation in patients with atrial fibrillation.
BMJ Qual Saf 2019 Oct;28(10):835-42. doi: 10.1136/bmjqs-2019-009367..
Keywords: Blood Thinners, Heart Disease and Health, Cardiovascular Conditions, Medication, Health Information Technology (HIT), Shared Decision Making, Electronic Health Records (EHRs), Practice Patterns, Healthcare Utilization
Knierim KE, Hall TL, Dickinson LM
Primary care practices' ability to report electronic clinical quality measures in the EvidenceNOW Southwest Initiative to Improve Heart Health.
The objective of this study was to determine how quickly primary care practices can report electronic clinical quality measures (eCQMs) and to identify the practice characteristics associated with faster reporting. Examining the EvidenceNOW Southwest initiative, the researchers’ results showed that the time to report eCQMs varied by measure and practice type, with very few practices reporting quickly. Additional support for practices to succeed in new programs that require eCQM reporting was recommended.
AHRQ-funded; HS023904.
Citation: Knierim KE, Hall TL, Dickinson LM .
Primary care practices' ability to report electronic clinical quality measures in the EvidenceNOW Southwest Initiative to Improve Heart Health.
JAMA Netw Open 2019 Aug 2;2(8):e198569. doi: 10.1001/jamanetworkopen.2019.8569..
Keywords: Primary Care, Quality Indicators (QIs), Quality Measures, Quality Improvement, Quality of Care, Heart Disease and Health, Cardiovascular Conditions, Patient-Centered Outcomes Research, Evidence-Based Practice, Electronic Health Records (EHRs), Health Information Technology (HIT)
Hannan EL, Barrett SC, Samadashvili Z
Retooling of paper-based outcome measures to electronic format: comparison of the NY State public risk model and EHR-derived risk models for CABG mortality.
This study assessed the feasibility of retooling the paper-based New York State coronary artery bypass graft (CABG) surgery statistical model for mortality and readmission into a model for electronic health records (EHRs). Researchers found that only 6 data elements could be extracted from the EHR, and outlier hospitals differed for readmission but was usable for mortality. They concluded that the EHR model was inferior to the NYS model, and that simplifying the EHR risk model couldn’t capture most of the risk factors in the NYS model.
AHRQ-funded; HS022647.
Citation: Hannan EL, Barrett SC, Samadashvili Z .
Retooling of paper-based outcome measures to electronic format: comparison of the NY State public risk model and EHR-derived risk models for CABG mortality.
Med Care 2019 May;57(5):377-84. doi: 10.1097/mlr.0000000000001104..
Keywords: Surgery, Electronic Health Records (EHRs), Health Information Technology (HIT), Mortality, Outcomes, Risk, Cardiovascular Conditions
Cykert S, DeWalt DA, Weiner BJ
A population approach using cholesterol imputation to identify adults with high cardiovascular risk: a report from AHRQ's EvidenceNow initiative.
Investigators estimated cholesterol scores for patients between the ages of 40 and 79 in large practice electronic health networks who did not have that in their electronic health record (EHR). This data was used to calculate 10-year Assessment of Cardiovascular Disease Risk (ASCVD) risk scores for patients in 219 practices. They estimated the scores using both “good value’ estimation methodology and formal imputation. The “good value” estimation methodology resulted in less patients with risk scores than imputation but it had higher specificity and a lower false positive rate.
AHRQ-funded; HS023912.
Citation: Cykert S, DeWalt DA, Weiner BJ .
A population approach using cholesterol imputation to identify adults with high cardiovascular risk: a report from AHRQ's EvidenceNow initiative.
J Am Med Inform Assoc 2019 Feb;26(2):155-58. doi: 10.1093/jamia/ocy151..
Keywords: Cardiovascular Conditions, Electronic Health Records (EHRs), Heart Disease and Health, Evidence-Based Practice, Health Information Technology (HIT), Patient-Centered Outcomes Research, Quality Improvement
Blecker S, Sontag D, Horwitz LI
Early identification of patients with acute decompensated heart failure.
The purpose of this study was to develop and test accuracies of various approaches to identify patients with acute decompensated heart failure (ADHF) with the use of data derived from the electronic health record. The authors concluded that machine learning algorithms with unstructured notes had the best performance for identification of ADHF and can improve provider efficiency for delivery of quality improvement interventions.
AHRQ-funded; HS023683.
Citation: Blecker S, Sontag D, Horwitz LI .
Early identification of patients with acute decompensated heart failure.
J Card Fail 2018 Jun;24(6):357-62. doi: 10.1016/j.cardfail.2017.08.458..
Keywords: Cardiovascular Conditions, Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT), Heart Disease and Health
Wang SV, Rogers JR, Jin Y
Use of electronic healthcare records to identify complex patients with atrial fibrillation for targeted intervention.
The researchers tested algorithms for identifying atrial fibrillation (AF) patients who also have known risk factors for stroke and major bleeding using electronic healthcare records (EHRs) data. The performance of candidate algorithms in 1000 bootstrap resamples was compared to a gold standard of manual chart review by experienced resident physicians of 480 patient charts. For 11 conditions, the median positive predictive value of the EHR-derived algorithms was greater than 0.90.
AHRQ-funded; HS022193.
Citation: Wang SV, Rogers JR, Jin Y .
Use of electronic healthcare records to identify complex patients with atrial fibrillation for targeted intervention.
J Am Med Inform Assoc 2017 Mar 1;24(2):339-44. doi: 10.1093/jamia/ocw082.
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Keywords: Heart Disease and Health, Cardiovascular Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT), Risk
Woollen J, Prey J, Wilcox L
Patient experiences using an inpatient personal health record.
Researchers investigated post-operative cardiac surgical patients' experience using an inpatient personal health record (PHR) on a tablet computer to increase engagement in their hospital care. They found that patients reported high satisfaction with being able to view their hospital medications and access educational materials related to their medical conditions. Patients also reported a desire to view daily progress reports about their hospital stay.
AHRQ-funded; HS021816.
Citation: Woollen J, Prey J, Wilcox L .
Patient experiences using an inpatient personal health record.
Appl Clin Inform 2016 Jun 1;7(2):446-60. doi: 10.4338/aci-2015-10-ra-0130.
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Keywords: Cardiovascular Conditions, Electronic Health Records (EHRs), Hospitalization, Patient Experience, Patient Experience
Wolfson J, Bandyopadhyay S, Elidrisi M
A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data.
This paper proposed an adaptation of the well-known Naive Bayes machine learning approach to time-to-event outcomes subject to censoring. It compared the predictive performance of that method with the Cox proportional hazards model which is commonly used for risk prediction in healthcare populations, and illustrated its application to prediction of cardiovascular risk using an electronic health record dataset from a large Midwest integrated healthcare system.
AHRQ-funded; HS017622.
Citation: Wolfson J, Bandyopadhyay S, Elidrisi M .
A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data.
Stat Med 2015 Sep 20;34(21):2941-57. doi: 10.1002/sim.6526..
Keywords: Risk, Electronic Health Records (EHRs), Health Information Technology (HIT), Cardiovascular Conditions
Hess R, Fischer GS, Sullivan SM
Patterns of response to patient-centered decision support through a personal health record.
The investigators evaluated patients' patterns of responses to notifications regarding guideline-recommended services delivered through a personalized health record (PHR). They found that approximately 61% of participants accessed the PHR or received the care that triggered the message after the first message and 73% after the first two messages. They concluded that, in this low-intensity intervention, participants accessed the PHR and received recommended care.
AHRQ-funded; HS018167.
Citation: Hess R, Fischer GS, Sullivan SM .
Patterns of response to patient-centered decision support through a personal health record.
Telemed J E Health 2014 Nov;20(11):984-9. doi: 10.1089/tmj.2013.0332.
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Keywords: Cardiovascular Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient-Centered Healthcare, Clinician-Patient Communication