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
Topics
- Behavioral Health (1)
- Cardiovascular Conditions (1)
- Clinical Decision Support (CDS) (1)
- Electronic Health Records (EHRs) (2)
- Evidence-Based Practice (2)
- Healthcare Delivery (1)
- (-) Health Information Technology (HIT) (6)
- Hospitalization (1)
- Low-Income (1)
- Outcomes (1)
- Patient-Centered Outcomes Research (1)
- Prevention (1)
- Primary Care (2)
- (-) Tobacco Use (6)
- Tobacco Use: Smoking Cessation (3)
- Young Adults (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 6 of 6 Research Studies DisplayedRoberts MM, Marino M, Wells R
Differences in use of clinical decision support tools and implementation of aspirin, blood pressure control, cholesterol management, and smoking cessation quality metrics in small practices by race and sex.
The objective of this cross-sectional study was to evaluate the association between population-based clinical decision support (CDS) tools and racial and sex disparities in the aspirin use, blood pressure control, cholesterol management, and smoking cessation (ABCS) care quality metrics among smaller primary care practices. Researchers used practice-level data from the EvidenceNOW initiative, from practices that submitted both survey data and electronic health record (EHR)-derived ABCS data stratified by race and sex. Their findings suggested that practices using CDS tools had small disparities but were not statistically significant; however, CDS tools were not associated with reductions in disparities. They concluded that more research was needed on effective practice-level interventions to mitigate disparities.
AHRQ-funded; HS023940.
Citation: Roberts MM, Marino M, Wells R .
Differences in use of clinical decision support tools and implementation of aspirin, blood pressure control, cholesterol management, and smoking cessation quality metrics in small practices by race and sex.
JAMA Netw Open 2023 Aug; 6(8):e2326905. doi: 10.1001/jamanetworkopen.2023.26905..
Keywords: Clinical Decision Support (CDS), Health Information Technology (HIT), Cardiovascular Conditions, Tobacco Use, Tobacco Use: Smoking Cessation, Primary Care, Evidence-Based Practice, Prevention
Hitsman B, Matthews PA, Papandonatos GD B, Matthews PA, Papandonatos GD
An EHR-automated and theory-based population health management intervention for smoking cessation in diverse low-income patients of safety-net health centers: a pilot randomized controlled trial.
The purpose of this study was to test the initial effectiveness of an electronic health record (EHR)-automated population health management (PHM) intervention for smoking cessation among adult patients. The researchers included 190 participants from a federally qualified health center in Chicago who self-identified as smokers as documented in the electronic health records and who completed a longitudinal "needs assessment of health behaviors to strengthen health programs and services” baseline survey. Participants were then randomly assigned to the PHM intervention (N=97) or the enhanced usual care (EUC) group (N=93). Primary outcomes were treatment engagement, utilization, and self-reported smoking cessation. In the PHM group, 25.8% of participants engaged in treatment, 21.6% used treatment, and 16.3% were abstinent at 28 weeks. There was no engagement of the quitline among EUC participants, and an abstinence rate of 6.4%. The researchers concluded that a PHM approach that can address unique barriers for low-income individuals may be an important addition to clinic-based care.
AHRQ-funded; HS021141.
Citation: Hitsman B, Matthews PA, Papandonatos GD B, Matthews PA, Papandonatos GD .
An EHR-automated and theory-based population health management intervention for smoking cessation in diverse low-income patients of safety-net health centers: a pilot randomized controlled trial.
Transl Behav Med 2022 Oct 7;12(9):892-99. doi: 10.1093/tbm/ibac026..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Tobacco Use, Tobacco Use: Smoking Cessation, Low-Income
Chu KH, Matheny SJ, Escobar-Viera CG
Smartphone health apps for tobacco cessation: a systematic review.
The objective of this systematic review was to identify and evaluate the types of studies that use smartphone apps for interventions in tobacco cessation. Findings showed that the majority of studies identified that use tobacco cessation apps as an intervention delivery modality were mostly at the pilot/feasibility stage. The growing field has resulted in studies that varied in methodologies, study design, and inclusion criteria. Recommendations included more consistency in intervention components and larger randomized controlled trials for tobacco cessation smartphone apps.
AHRQ-funded; HS022989.
Citation: Chu KH, Matheny SJ, Escobar-Viera CG .
Smartphone health apps for tobacco cessation: a systematic review.
Addict Behav 2021 Jan;112:106616. doi: 10.1016/j.addbeh.2020.106616..
Keywords: Health Information Technology (HIT), Tobacco Use: Smoking Cessation, Tobacco Use, Evidence-Based Practice
Chu KH, Escobar-Viera CG, Matheny SJ
Tobacco cessation mobile app intervention (Just Kwit! study): protocol for a pilot randomized controlled pragmatic trial.
The aims of this pilot study were to assess the impact on tobacco cessation of using a smartphone app compared with usual care and to generate feasibility data to inform a future fully powered clinical trial. The authors suggest that data generated by this study can be used for larger fully powered trials such as comparative effectiveness studies against apps developed by academics or health scientists based on behavioral theories, or cost-effectiveness analyses of mobile interventions.
AHRQ-funded; HS022989.
Citation: Chu KH, Escobar-Viera CG, Matheny SJ .
Tobacco cessation mobile app intervention (Just Kwit! study): protocol for a pilot randomized controlled pragmatic trial.
Trials 2019 Feb 26;20(1):147. doi: 10.1186/s13063-019-3246-2..
Keywords: Health Information Technology (HIT), Patient-Centered Outcomes Research, Tobacco Use, Young Adults
Nahhas GJ, Wilson D, Talbot V
Feasibility of implementing a hospital-based "opt-out" tobacco-cessation service.
This study assessed the feasibility and outcomes of implementing a hospital-based "opt-out" tobacco-cessation service. The service consisted of a bedside consult and phone follow-up 3, 14, and 30 days after hospital discharge using interactive-voice-response. Findings from this study suggest that an inpatient smoking-cessation service with an "opt-out" approach can positively impact short-term cessation outcomes.
AHRQ-funded; HS023863.
Citation: Nahhas GJ, Wilson D, Talbot V .
Feasibility of implementing a hospital-based "opt-out" tobacco-cessation service.
Nicotine Tob Res 2017 Aug;19(8):937-43. doi: 10.1093/ntr/ntw312.
.
.
Keywords: Health Information Technology (HIT), Hospitalization, Tobacco Use, Outcomes
Bailey SR, Heintzman JD, Marino M
Smoking-cessation assistance: before and after stage 1 meaningful use implementation.
This study examined whether smoking status assessment, cessation assistance, and odds of being a current smoker changed after Stage 1 Meaningful Use (MU) implementation. Its findings suggest that incentives for MU of electronic health records increase the odds of smoking assessment and cessation assistance, which could lead to decreased smoking rates among vulnerable populations.
AHRQ-funded; HS021522.
Citation: Bailey SR, Heintzman JD, Marino M .
Smoking-cessation assistance: before and after stage 1 meaningful use implementation.
Am J Prev Med 2017 Aug;53(2):192-200. doi: 10.1016/j.amepre.2017.02.006.
.
.
Keywords: Behavioral Health, Electronic Health Records (EHRs), Health Information Technology (HIT), Healthcare Delivery, Primary Care, Tobacco Use