National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Blood Pressure (1)
- Chronic Conditions (3)
- Community-Based Practice (1)
- Comparative Effectiveness (1)
- (-) Diabetes (5)
- Diagnostic Safety and Quality (1)
- Education: Patient and Caregiver (1)
- Electronic Health Records (EHRs) (2)
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- (-) Health Information Technology (HIT) (5)
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- Telehealth (2)
- Women (1)
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 5 of 5 Research Studies DisplayedPresley C, Agne A, Shelton T
Mobile-enhanced peer support for African Americans with Type 2 diabetes: a randomized controlled trial.
This study compared the effectiveness of a community-based diabetes self-management education (DSME) plus mobile health (mHealth)-enhanced peer support intervention to community-based DSME alone for African American adults with poorly controlled type 2 diabetes. This randomized controlled trial took place in Jefferson County, Alabama within a safety-net healthcare system with a group diagnosed with type 2 diabetes and hemoglobin A1C ≥ 7.5%. The intervention group reviewed community-based DSME plus 6 months of mHealth-enhanced peer support, including 12 weekly phone calls, then 3 monthly calls from community health workers. The control group received community based DSME only. Primary outcomes were lower A1C and secondary outcomes were lower diabetes distress, depressive symptoms, self-efficacy or confidence in their ability to manage diabetes, and social support. Of 120 participants selected, 97 completed the study. Both groups experienced clinical meaning reduction in A1C. Participants in the intervention group experienced a significantly larger reduction in diabetes distress compared to the control group.
AHRQ-funded; HS019465.
Citation: Presley C, Agne A, Shelton T .
Mobile-enhanced peer support for African Americans with Type 2 diabetes: a randomized controlled trial.
J Gen Intern Med 2020 Oct;35(10):2889-96. doi: 10.1007/s11606-020-06011-w..
Keywords: Telehealth, Health Information Technology (HIT), Patient Self-Management, Diabetes, Chronic Conditions, Racial and Ethnic Minorities, Community-Based Practice, Comparative Effectiveness, Patient-Centered Outcomes Research, Evidence-Based Practice, Outcomes, Education: Patient and Caregiver
Tassone C, Keshavjee K, Paglialonga A
Evaluation of mobile apps for treatment of patients at risk of developing gestational diabetes.
This study evaluated mobile apps using a theory-based evaluation framework to discover their applicability for patients at risk of gestational diabetes. It assessed how well the existing mobile apps on the market met the information and tracking needs of patients with gestational diabetes and evaluated the feasibility of how to integrate these apps into patient care.
AHRQ-funded; HS021495; HS24869.
Citation: Tassone C, Keshavjee K, Paglialonga A .
Evaluation of mobile apps for treatment of patients at risk of developing gestational diabetes.
Health Informatics J 2020 Sep;26(3):1983-94. doi: 10.1177/1460458219896639..
Keywords: Diabetes, Risk, Health Information Technology (HIT), Women
Aguilera A, Figueroa CA, Hernandez-Ramos R
mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE study.
In this randomized controlled trial, the researchers’ goal is to examine the effect of a text-messaging smartphone application to encourage physical activity in low-income ethnic minority patients with comorbid diabetes and depression. They will compare passively collected daily step counts, self-reported PHQ-8 and most recent hemoglobin A1c from medical records at baseline and at intervention completion at 6-month follow-up. They plan to submit manuscripts describing their user-designed methods and testing of the adaptive learning algorithm and will submit the results of the trial for publication in peer-reviewed journals and presentations at scientific meetings.
AHRQ-funded; HS025429.
Citation: Aguilera A, Figueroa CA, Hernandez-Ramos R .
mHealth app using machine learning to increase physical activity in diabetes and depression: clinical trial protocol for the DIAMANTE study.
BMJ Open 2020 Aug 20;10(8):e034723. doi: 10.1136/bmjopen-2019-034723..
Keywords: Telehealth, Health Information Technology (HIT), Diabetes, Chronic Conditions, Racial and Ethnic Minorities, Low-Income, Health Promotion
Misra-Hebert AD, Milinovich A, Zajichek A
Natural language processing improves detection of nonsevere hypoglycemia in medical records versus coding alone in patients with type 2 diabetes but does not improve prediction of severe hypoglycemia events: an analysis using the electronic medical record
The purpose of this study was to determine if natural language processing (NLP) improves detection of non-severe hypoglycemia (NSH) in patients with type 2 diabetes and no NSH documentation by diagnosis codes and to measure if NLP detection improves the prediction of future severe hypoglycemia (SH). The authors identified NSH events by diagnosis codes and NLP 2005 to 2017 and built an SH prediction model. Their findings showed that detection of NSH improved with NLP in patients with type 2 diabetes without improving SH prediction.
AHRQ-funded; HS024128.
Citation: Misra-Hebert AD, Milinovich A, Zajichek A .
Natural language processing improves detection of nonsevere hypoglycemia in medical records versus coding alone in patients with type 2 diabetes but does not improve prediction of severe hypoglycemia events: an analysis using the electronic medical record
Diabetes Care 2020 Aug;43(8):1937-40. doi: 10.2337/dc19-1791..
Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Diagnostic Safety and Quality
Huguet N, Kaufmann J, O'Malley J
Using electronic health records in longitudinal studies: estimating patient attrition.
This study’s objective was to estimate overall and among adults with diabetes or hypertension: 1) patient attrition over a 3-year period at community health centers; and 2) the likelihood that patients with Medicaid switched their primary care source. Data was collected from the retrospective cohort study of 2012-2017 claims data Accelerating Data Value Across a National Community Health Center Network (ADVANCE) Clinical Data Research Network of community health centers. This study focused on Oregon Medicaid enrollees with a total of 232,891 patients aged 19-64 with a gap of 6 months or more following a claim for a visit billed to a primary care source. The authors theorized the reason was due to patients with Medicaid permanently changing their primary care source. They found that attrition over 3 years averaged 33.5% but patients with diabetes or hypertension was lower (25% or less). Among Medicaid patients the attrition rate 12% for community health center patients compared with 39% for single-provider practice patients.
AHRQ-funded; HS025962.
Citation: Huguet N, Kaufmann J, O'Malley J .
Using electronic health records in longitudinal studies: estimating patient attrition.
Med Care 2020 Jun;58(Suppl 1):S46-S52. doi: 10.1097/mlr.0000000000001298...
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Diabetes, Blood Pressure, Chronic Conditions, Primary Care, Medicaid