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 Date
Topics
- Blood Thinners (1)
- Cardiovascular Conditions (1)
- Children/Adolescents (1)
- Chronic Conditions (1)
- Clinical Decision Support (CDS) (1)
- Dementia (1)
- Elderly (1)
- Electronic Health Records (EHRs) (3)
- Emergency Department (3)
- Healthcare Delivery (1)
- (-) Healthcare Utilization (7)
- (-) Health Information Technology (HIT) (7)
- Heart Disease and Health (1)
- Hospitals (1)
- Medication (1)
- Neurological Disorders (2)
- Practice Patterns (1)
- Primary Care (1)
- Shared Decision Making (2)
- Social Determinants of Health (1)
- Surgery (1)
- Telehealth (3)
- Trauma (1)
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 7 of 7 Research Studies DisplayedShah W, Villaflores CW, Chuong LH
Association between in-person vs telehealth follow-up and rates of repeated hospital visits among patients seen in the emergency department.
This study investigated whether the rates of emergency department (ED) return visits and hospitalization differ between patients who obtain in-person versus telehealth encounters for post-ED follow-up care. This retrospective cohort study included adult patients who came to either of 2 in-system EDs of a single urban integrated academic system from April 2020 to September 2021, were discharged home, and obtained a follow-up appointment with a primary care physician within 14 days of their index ED visit. Overall, the study recorded 12,848 patients with 16,987 ED encounters (mean age 53 years; 57% women, 12% Black or African American; 22% Hispanic or Latinx; and 58% White) included. Overall, 17% of initial ED encounters led to returns to the ED, and 4% subsequent hospitalizations. Telehealth vs in-person follow-up visits were associated with increased rates of ED returns (28.3 more ED returns per 1000 encounters) and hospitalizations (10.6 more hospitalizations per 1000 encounters).
AHRQ-funded; HS026372.
Citation: Shah W, Villaflores CW, Chuong LH .
Association between in-person vs telehealth follow-up and rates of repeated hospital visits among patients seen in the emergency department.
JAMA Netw Open 2022 Oct;5(10):e2237783. doi: 10.1001/jamanetworkopen.2022.37783..
Keywords: Telehealth, Health Information Technology (HIT), Emergency Department, Healthcare Utilization, Hospitals
Dixit RA, Ratwani RM, Bishop JA
The impact of expanded telehealth availability on primary care utilization.
This study examined the impact of telehealth availability due to the COVID-19 pandemic and whether it may result in an unnecessary increase in utilization. The authors analyzed 4,114,651 primary care encounters from three healthcare systems between 2019 and 2021 and found little change in telehealth utilization as it became widely available.
AHRQ-funded; HS028255.
Citation: Dixit RA, Ratwani RM, Bishop JA .
The impact of expanded telehealth availability on primary care utilization.
NPJ Digit Med 2022 Sep 9;5(1):141. doi: 10.1038/s41746-022-00685-8..
Keywords: Telehealth, Health Information Technology (HIT), Primary Care, Healthcare Utilization
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
Wissel BD, Greiner HM, Glauser TA
Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.
Racial disparities in the utilization of epilepsy surgery are well documented, but it is unknown whether a natural language processing (NLP) algorithm trained on physician notes would produce biased recommendations for epilepsy presurgical evaluations. To assess this, an NLP algorithm was trained to identify potential surgical candidates using 1097 notes from 175 epilepsy patients with a history of resective epilepsy surgery and 268 patients who achieved seizure freedom without surgery (total N = 443 patients).
AHRQ-funded; HS024977.
Citation: Wissel BD, Greiner HM, Glauser TA .
Investigation of bias in an epilepsy machine learning algorithm trained on physician notes.
Epilepsia 2019 Sep;60(9):e93-e98. doi: 10.1111/epi.16320..
Keywords: Neurological Disorders, Surgery, Clinical Decision Support (CDS), Healthcare Utilization, Health Information Technology (HIT), Shared Decision Making
Gillespie SM, Wasserman EB, Wood NE
High-intensity telemedicine reduces emergency department use by older adults with dementia in senior living communities.
Individuals with dementia have high rates of emergency department (ED) use for acute illnesses. In this study, the investigators evaluated the effect of a high-intensity telemedicine program that delivered care for acute illnesses on ED use rates for individuals with dementia residing in senior living communities (SLCs; independent and assisted living).
AHRQ-funded; HS018047.
Citation: Gillespie SM, Wasserman EB, Wood NE .
High-intensity telemedicine reduces emergency department use by older adults with dementia in senior living communities.
J Am Med Dir Assoc 2019 Aug;20(8):942-46. doi: 10.1016/j.jamda.2019.03.024..
Keywords: Elderly, Telehealth, Health Information Technology (HIT), Dementia, Neurological Disorders, Healthcare Delivery, Chronic Conditions, Emergency Department, Healthcare Utilization
Durojaiye AB, Levin S, Toerper M
Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data.
This study electronic health record (EHR) data to compare usage patterns from pediatric trauma patients with minor injuries at a Level I pediatric trauma center. The data was used to compare demographics, clinical and network characteristics, and emergency department (ED) length of stay (LOS). Three distinct groups were compared: fully connected, partially connected, and disconnected. The fully connected group had a decreased ED LOS compared with the partially connected group.
AHRQ-funded; HS023837.
Citation: Durojaiye AB, Levin S, Toerper M .
Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data.
J Am Med Inform Assoc 2019 Jun;26(6):506-15. doi: 10.1093/jamia/ocy184..
Keywords: Children/Adolescents, Trauma, Electronic Health Records (EHRs), Health Information Technology (HIT), Emergency Department, Healthcare Utilization
Bucher BT, Shi J, Pettit RJ
Determination of marital status of patients from structured and unstructured electronic healthcare data.
This paper describes a robust method to determine the marital status of patients, which is included as a Social Determinant of Health and considered a key driver of health care utilization. A robust method to determine marital status using structured and unstructured electronic healthcare data was developed using data from a single US academic institution. A natural language processing (NLP) pipeline was developed and validated. Performance was compared against two baseline methods: a machine learning n-gram model and structured data from the electronic health record. Overall the NLP engine had excellent to superior performance compared with the other models.
AHRQ-funded; HS025776.
Citation: Bucher BT, Shi J, Pettit RJ .
Determination of marital status of patients from structured and unstructured electronic healthcare data.
AMIA Annu Symp Proc 2020 Mar 4;2019:267-74..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Social Determinants of Health, Healthcare Utilization