National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Blood Pressure (2)
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- Decision Making (1)
- (-) Diabetes (8)
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- (-) Electronic Health Records (EHRs) (8)
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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 8 of 8 Research Studies DisplayedMisra-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
Panattoni L, Chan A, Yang Y
Nudging physicians and patients with autopend clinical decision support to improve diabetes management.
This study’s objective was to determine the impact on routine glycalated hemoglobin (A1C) laboratory test completion of incorporating an autopend laboratory order functionality into clinical decision support. The clinical decision support includes 1) routing provider alerts to a separate electronic folder, 2) automatically populating preauthorization forms, and 3) linking the timing and content of electronic patient health maintenance topic (HMT) reminders to the provider authorization. The likelihood of A1C laboratory test completion increased after autopend by between 21% to 33.9%.
AHRQ-funded; HS019167.
Citation: Panattoni L, Chan A, Yang Y .
Nudging physicians and patients with autopend clinical decision support to improve diabetes management.
Am J Manag Care 2018 Oct;24(10):479-83..
Keywords: Clinical Decision Support (CDS), Decision Making, Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT)
Ramirez M, Maranon R, Fu J
Primary care provider adherence to an alert for intensification of diabetes blood pressure medications before and after the addition of a "chart closure" hard stop.
The purpose of this study was to evaluate provider responses to a narrowly targeted Best Practice Advisory (BPA) alert regarding the intensification of blood pressure medications for persons with diabetes before and after implementation of a ‘chart closure’ hard stop. Researchers designed a BPA that sent alerts via an electronic health record system during outpatient encounters when patients with diabetes had elevated blood pressures and were not on angiotensin receptor blocking medications. These alerts were implemented in eight primary care practices within UCLA Health. Data on provider responses to the alerts was compared before and after implementing a ‘chart closure’ hard stop. Providers responded to alerts more often after the ‘chart closure’ hard stop was implemented. The researchers conclude that targeting specific omitted medication classes can produce specific alerts that may reduce alert fatigue, and that using a ‘chart closure’ hard stop may prompt providers to take action without major disruptions to their workflow.
AHRQ-funded; HS000046.
Citation: Ramirez M, Maranon R, Fu J .
Primary care provider adherence to an alert for intensification of diabetes blood pressure medications before and after the addition of a "chart closure" hard stop.
J Am Med Inform Assoc 2018 Sep;25(9):1167-74. doi: 10.1093/jamia/ocy073..
Keywords: Blood Pressure, Diabetes, Primary Care, Electronic Health Records (EHRs), Health Information Technology (HIT), Medication, Care Management
Flory JH, Keating SJ, Siscovick D
Identifying prevalence and risk factors for metformin non-persistence: a retrospective cohort study using an electronic health record.
Non-persistence may be a significant barrier to the use of metformin. The objective of this study was to assess reasons for metformin non-persistence, and whether initial metformin dosing or use of extended release (ER) formulations affect persistence to metformin therapy. The investigators concluded that their data supported the routine prescribing of low starting doses of metformin as a tool to improve persistence.
AHRQ-funded; HS023898.
Citation: Flory JH, Keating SJ, Siscovick D .
Identifying prevalence and risk factors for metformin non-persistence: a retrospective cohort study using an electronic health record.
BMJ Open 2018 Jul 23;8(7):e021505. doi: 10.1136/bmjopen-2018-021505..
Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Medication, Patient Adherence/Compliance, Outcomes, Patient-Centered Outcomes Research, Risk
Hedderson MM, Brown SD, Ehrlich SF
A tailored letter based on electronic health record data improves gestational weight gain among women with gestational diabetes mellitus: the Gestational Diabetes' Effects on Moms (GEM) cluster-randomized controlled trial.
The purpose of this study was to evaluate whether a tailored letter improved gestational weight gain (GWG) and whether GWG mediated a multicomponent intervention's effect on postpartum weight retention among women with gestational diabetes mellitus (GDM). The authors concluded that a tailored electronic health record-based letter improved GWG, which mediated the effect of a multicomponent intervention in reducing postpartum weight retention.
AHRQ-funded; HS019367.
Citation: Hedderson MM, Brown SD, Ehrlich SF .
A tailored letter based on electronic health record data improves gestational weight gain among women with gestational diabetes mellitus: the Gestational Diabetes' Effects on Moms (GEM) cluster-randomized controlled trial.
Diabetes Care 2018 Jul;41(7):1370-77. doi: 10.2337/dc17-1133..
Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Lifestyle Changes, Patient-Centered Outcomes Research, Pregnancy, Women
DuGoff EH, Walden E, Ronk K
Can claims data algorithms identify the physician of record?
This study sought to determine the agreement of the primary care physician (PCP) identified by claims algorithms with the PCP of record in electronic health record data. It concluded that researchers may be more likely to identify a patient's PCP when focusing on primary care visits only; however, these algorithms perform less well among vulnerable populations and those experiencing fragmented care.
AHRQ-funded; HS021899.
Citation: DuGoff EH, Walden E, Ronk K .
Can claims data algorithms identify the physician of record?
Med Care 2018 Mar;56(3):e16-e20. doi: 10.1097/mlr.0000000000000709.
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Keywords: Diabetes, Elderly, Electronic Health Records (EHRs), Primary Care
Graetz I, Huang J, Brand RJ
Bridging the digital divide: mobile access to personal health records among patients with diabetes.
The authors examined personal health record (PHR) use through a computer-based Web browser or mobile device. They found that mobile-ready PHRs may increase access among patients facing a digital divide in computer use, disproportionately reaching racial/ethnic minorities and lower socioeconomic status patients. They recommend continued efforts to increase equitable access to PHRs among patients with chronic conditions.
AHRQ-funded; HS015280.
Citation: Graetz I, Huang J, Brand RJ .
Bridging the digital divide: mobile access to personal health records among patients with diabetes.
Am J Manag Care 2018 Jan;24(1):43-48..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Diabetes, Racial and Ethnic Minorities, Social Determinants of Health