National Healthcare Quality and Disparities Report
Latest available findings on quality of and access to health care
Data
- Data Infographics
- Data Visualizations
- Data Tools
- Data Innovations
- All-Payer Claims Database
- Healthcare Cost and Utilization Project (HCUP)
- Medical Expenditure Panel Survey (MEPS)
- AHRQ Quality Indicator Tools for Data Analytics
- State Snapshots
- United States Health Information Knowledgebase (USHIK)
- Data Sources Available from AHRQ
Search All Research Studies
AHRQ Research Studies
Sign up: AHRQ Research Studies Email updates
Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 6 of 6 Research Studies DisplayedByrd 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
Liang Q, Ward S, Pagani FD
Linkage of Medicare records to the interagency registry of mechanically assisted circulatory support.
This study merged Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) records with CMS Medicare claims regarding adults receiving durable FDA-approved mechanical circulatory support devices (MCSDs) in order to investigate the uncertainty of penetrance of Medicare beneficiaries within INTERMACS. The results indicated that there was an annual increase in CMS and INTERMACS centers performing durable MCSD implants among adults from 2008 to 2013, but the CMS centers outnumbered the INTERMAC centers throughout this period. Representation within INTERMACS of MCSDs implanted in Medicare beneficiaries more than doubled in 2013. The authors conclude that ‘the vast majority’ of Medicare beneficiaries receiving MCSDs are increasingly captured in INTERMACS, and that contemporary studies in INTERMACS are therefore relevant and generalizable to the Medicare population.
AHRQ-funded; HS022535.
Citation: Liang Q, Ward S, Pagani FD .
Linkage of Medicare records to the interagency registry of mechanically assisted circulatory support.
Ann Thorac Surg 2018 May;105(5):1397-402. doi: 10.1016/j.athoracsur.2017.11.044..
Keywords: Cardiovascular Conditions, Heart Disease and Health, Data, Medicare, Registries
Liang Q, Ward S, Pagani FD
Linkage of Medicare records to the interagency registry of mechanically assisted circulatory support.
This study merged Interagency Registry for Mechanically Assisted Circulatory Support (INTERMACS) records with CMS Medicare claims regarding adults receiving durable FDA-approved mechanical circulatory support devices (MCSDs) in order to investigate the uncertainty of penetrance of Medicare beneficiaries within INTERMACS. The results indicated that there was an annual increase in CMS and INTERMACS centers performing durable MCSD implants among adults from 2008 to 2013, but the CMS centers outnumbered the INTERMAC centers throughout this period. Representation within INTERMACS of MCSDs implanted in Medicare beneficiaries more than doubled in 2013. The authors conclude that ‘the vast majority’ of Medicare beneficiaries receiving MCSDs are increasingly captured in INTERMACS, and that contemporary studies in INTERMACS are therefore relevant and generalizable to the Medicare population.
AHRQ-funded; HS022535.
Citation: Liang Q, Ward S, Pagani FD .
Linkage of Medicare records to the interagency registry of mechanically assisted circulatory support.
Ann Thorac Surg 2018 May;105(5):1397-402. doi: 10.1016/j.athoracsur.2017.11.044..
Keywords: Cardiovascular Conditions, Heart Disease and Health, Data, Medicare, Registries
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.
.
.
Keywords: Clinical Decision Support (CDS), Data, Electronic Health Records (EHRs), Heart Disease and Health, Patient-Centered Healthcare
Lim E, Cheng Y, Reuschel C
Risk-adjusted in-hospital mortality models for congestive heart failure and acute myocardial infarction: Value of clinical laboratory data and race/ethnicity.
This study examined the impact of key laboratory and race/ethnicity data on the prediction of in-hospital mortality for congestive heart failure (CHF) and acute myocardial infarction (AMI). It found that adding a simple three-level summary measure based on the number of abnormal laboratory data observed to hospital administrative claims data significantly improved the model prediction for inpatient mortality.
AHRQ-funded; HS019990.
Citation: Lim E, Cheng Y, Reuschel C .
Risk-adjusted in-hospital mortality models for congestive heart failure and acute myocardial infarction: Value of clinical laboratory data and race/ethnicity.
Health Serv Res 2015 Aug;50 Suppl 1:1351-71. doi: 10.1111/1475-6773.12325..
Keywords: Heart Disease and Health, Mortality, Data, Inpatient Care
Panahiazar M, Taslimitehrani V, Pereira N
Using EHRs and machine learning for heart failure survival analysis.
This study assessed the performance of the Seattle Heart Failure Model using EHRs at Mayo Clinic, and sought to develop a risk prediction model using machine learning techniques that applied routine clinical care data. Its results showed the models which were built using EHR data are more accurate (11 percent improvement in AUC) with the convenience of being more readily applicable in routine clinical care.
AHRQ-funded; HS023077.
Citation: Panahiazar M, Taslimitehrani V, Pereira N .
Using EHRs and machine learning for heart failure survival analysis.
Stud Health Technol Inform 2015;216:40-4..
Keywords: Electronic Health Records (EHRs), Heart Disease and Health, Risk, Data