National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Ambulatory Care and Surgery (1)
- Behavioral Health (1)
- Blood Pressure (3)
- Care Management (3)
- Children/Adolescents (1)
- Chronic Conditions (10)
- Clinical Decision Support (CDS) (1)
- Communication (1)
- (-) Diabetes (24)
- Diagnostic Safety and Quality (2)
- Education: Patient and Caregiver (1)
- (-) Electronic Health Records (EHRs) (24)
- Healthcare Delivery (1)
- (-) Health Information Technology (HIT) (24)
- Health Insurance (1)
- Health Services Research (HSR) (1)
- Lifestyle Changes (4)
- Medicaid (1)
- Medication (3)
- Outcomes (1)
- Patient-Centered Outcomes Research (2)
- Patient Adherence/Compliance (1)
- Patient and Family Engagement (2)
- Patient Safety (1)
- Patient Self-Management (2)
- Payment (1)
- Practice Patterns (1)
- Pregnancy (1)
- Primary Care (5)
- Quality Measures (1)
- Quality of Care (3)
- Racial and Ethnic Minorities (1)
- Risk (1)
- Shared Decision Making (1)
- Social Determinants of Health (2)
- Vulnerable Populations (1)
- 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 24 of 24 Research Studies DisplayedMehta S, Lyles CR, Rubinsky AD
Social determinants of health documentation in structured and unstructured clinical data of patients with diabetes: comparative analysis.
It is not clear how accurately Electronic health records (HER) data reflect patients' lived experience of social determinants of health (SDOH). The process of manually reviewing clinical notes to retrieve SDOH information is not feasible. The purpose of this study was to apply two tools, PatientExploreR and Electronic Medical Record Search Engine (EMERSE), to identify SDOH mappings for structured and unstructured patient data. The researchers included 4,283 adult patients receiving primary care for diabetes at UCSF. The study results revealed that SDOH may be more significant in the lives of patients with diabetes than is evident from structured data recorded on EHRs. When researchers applied EMERSE NLP rules, additional information was uncovered from patient clinical notes on problems related to social connections isolation, employment, financial insecurity, housing insecurity, food insecurity, education, and stress.
AHRQ-funded; HS026383.
Citation: Mehta S, Lyles CR, Rubinsky AD .
Social determinants of health documentation in structured and unstructured clinical data of patients with diabetes: comparative analysis.
JMIR Med Inform 2023 Aug 22; 11:e46159. doi: 10.2196/46159..
Keywords: Social Determinants of Health, Diabetes, Chronic Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT)
Narindrarangkura P, Alafaireet PE, Khan U
Predicting suicide attempts among people with diabetes using a large multicenter electronic health records dataset.
This study’s goal was to determine the risk factors for suicidal behaviors of people with diabetes as they have a higher risk than the general population. The authors investigated risk factors and predicted suicide attempts in people with diabetes using the Least Absolute Shrinkage and Selection Operator (LASSO) regression. They used data from Cerner Real-World Data™ and included over 3 million diabetes patients in the study. They analyzed gender-, diabetes-type, and depression-specific LASSO regression models. The study included 7764 subjects diagnosed with suicide attempts with an average age of 45. They found risk factors for suicide attempts in diabetes patients, such as being an American Indian or Alaska Native, atypical agents, benzodiazepines, and antihistamines. Amyotrophy had a negative coefficient for suicide attempts with males with diabetes but had a positive coefficient for females. Using MAOI had a negative coefficient for suicide attempts in T1DM patients. Patients less than 20 years of age had a positive coefficient for suicide in depressed and non-depressed patients with diabetes.
AHRQ-funded; HS028032.
Citation: Narindrarangkura P, Alafaireet PE, Khan U .
Predicting suicide attempts among people with diabetes using a large multicenter electronic health records dataset.
Int J Psychiatry Med 2023 Jul; 58(4):302-24. doi: 10.1177/00912174231162477..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Behavioral Health, Diabetes, Chronic Conditions
Fuji KT, Abbott AA, Galt KA
A mixed-methods evaluation of standalone personal health record use by patients with type 2 diabetes.
The purpose of this study was to compare use of a standalone personal health records (PHRs) by patients with Type 2 diabetes to usual care through assessment of self-care behaviors, and short-term impact on social cognitive outcomes and hemoglobin A1c (HbA1c). Five themes emerged from the qualitative analysis describing participants' experiences with the PHR and identifying reasons for lack of engagement. Study findings revealed low PHR uptake and minimal impact on study outcomes, including lack of communication and information-sharing between patients and providers.
AHRQ-funded; HS018625.
Citation: Fuji KT, Abbott AA, Galt KA .
A mixed-methods evaluation of standalone personal health record use by patients with type 2 diabetes.
Perspect Health Inf Manag 2021 Fall;18(4):1e..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Diabetes, Patient Self-Management, Chronic Conditions, Patient and Family Engagement
Cemballi AG, Karter AJ, Schillinger D
Descriptive examination of secure messaging in a longitudinal cohort of diabetes patients in the ECLIPPSE study.
This longitudinal study looked at trends in secure messaging (SM) use in health care system patient portals using a diverse cohort of diabetes patients enrolled in the ECLIPPSE study from 2006 to 2015. The authors found a 10-fold increase in overall messaging volume during that time period. A majority of patients were using SM by 2015, including those with lower income or with self-reported limited health literacy. At the beginning of the survey period more physicians than nurses were using SM, but that changed over time as well.
AHRQ-funded; HS026383.
Citation: Cemballi AG, Karter AJ, Schillinger D .
Descriptive examination of secure messaging in a longitudinal cohort of diabetes patients in the ECLIPPSE study.
J Am Med Inform Assoc 2021 Jun 12;28(6):1252-58. doi: 10.1093/jamia/ocaa281..
Keywords: Diabetes, Chronic Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT)
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
Althoff KN, Wong C, Hogan B
Mind the gap: observation windows to define periods of event ascertainment as a quality control method for longitudinal electronic health record data.
Under the hypothesis that use of electronic health records in health research may lead to false assumptions of complete event ascertainment, the authors of this article estimated "observation windows" (OWs) as a quality-control approach to reduce the likelihood of false assumption. The impact of OWs on estimating rates of type II diabetes mellitus from HIV clinical cohorts are demonstrated. Data from 16 HIV clinical cohorts to the NA-ACCORD were used to identify and evaluate OWs for an operationalized definition of diabetes occurrence. The authors conclude that OWs have utility as a quality-control approach to complete event ascertainment and help to improve the accuracy of estimates.
AHRQ-funded; 90047713.
Citation: Althoff KN, Wong C, Hogan B .
Mind the gap: observation windows to define periods of event ascertainment as a quality control method for longitudinal electronic health record data.
Ann Epidemiol 2019 May;33:54-63. doi: 10.1016/j.annepidem.2019.01.015..
Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Health Services Research (HSR), Quality of Care
Wu SS, Chan KS, Bae J
Electronic clinical reminder and quality of primary diabetes care.
The goal of this retrospective cohort study was to examine the association of EMR's clinical reminder use with a comprehensive set of diabetes quality metrics in office-based physicians and within solo- versus multi-physician practices. Data on visits made by adults with diabetes were identified from the National Ambulatory Medical Care Survey and a multiple logistic regression was used to test for associations between clinical reminder use and recommended services by the American Diabetes Association. The researchers found no statistically significant relationship that suggests clinical reminder use improves diabetes process guidelines for solo practices, and they conclude that other resource efforts are needed to reduce gaps in primary diabetes care.
AHRQ-funded; HS000029.
Citation: Wu SS, Chan KS, Bae J .
Electronic clinical reminder and quality of primary diabetes care.
Prim Care Diabetes 2019 Apr;13(2):150-57. doi: 10.1016/j.pcd.2018.08.007..
Keywords: Care Management, Chronic Conditions, Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Primary Care, Quality of Care
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), Shared 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
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
Ratanawongsa N, Chan LL, Fouts MM
The challenges of electronic health records and diabetes electronic prescribing: implications for safety net care for diverse populations.
This review highlights how the EHR electronic prescribing transformation has affected diabetes care for vulnerable patients and offers recommendations for improving patient safety through EHR electronic prescribing design, implementation, policy, and research. Specifically, it presents evidence for the adoption of RxNorm and standardized naming and picklist options for high alert medications such as insulin.
AHRQ-funded; HS022561; HS023558.
Citation: Ratanawongsa N, Chan LL, Fouts MM .
The challenges of electronic health records and diabetes electronic prescribing: implications for safety net care for diverse populations.
J Diabetes Res 2017;2017:8983237. doi: 10.1155/2017/8983237.
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Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Vulnerable Populations, Diabetes, Patient Safety, Chronic Conditions
Brown SD, Grijalva CS, Ferrara A
Leveraging EHRs for patient engagement: perspectives on tailored program outreach.
Electronic health records (EHRs) present healthcare delivery systems with scalable, cost-effective opportunities to promote lifestyle programs among patients at high risk for type 2 diabetes, yet little consensus exists on strategies to enhance patient engagement. In this study, the investigators explored patient perspectives on program outreach messages containing content tailored to EHR-derived diabetes risk factors--a theory-driven strategy to increase the persuasiveness of health communications.
AHRQ-funded; HS019367.
Citation: Brown SD, Grijalva CS, Ferrara A .
Leveraging EHRs for patient engagement: perspectives on tailored program outreach.
Am J of Manag Care 2017 Jul;23(7):e223-e30..
Keywords: Diabetes, Communication, Education: Patient and Caregiver, Electronic Health Records (EHRs), Health Information Technology (HIT), Healthcare Delivery, Lifestyle Changes, Patient and Family Engagement
Chung S, Zhao B, Lauderdale D
Initiation of treatment for incident diabetes: evidence from the electronic health records in an ambulatory care setting.
The researchers examined patterns and predictors of initiation of treatment for incident diabetes in an ambulatory care setting in the US. They found that only half of patients were treated during the first year following diabetes incidence, and only 20% of patients received both medication prescription and lifestyle modification interventions.
AHRQ-funded; HS019815.
Citation: Chung S, Zhao B, Lauderdale D .
Initiation of treatment for incident diabetes: evidence from the electronic health records in an ambulatory care setting.
Prim Care Diabetes 2015 Feb;9(1):23-30. doi: 10.1016/j.pcd.2014.04.005..
Keywords: Ambulatory Care and Surgery, Care Management, Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Primary Care, Practice Patterns
Hosomura N, Goldberg SI, Shubina M
Electronic documentation of lifestyle counseling and glycemic control in patients with diabetes.
The aim of this study was to establish quantitative characteristics of documentation of lifestyle counseling that are associated with improved glycemic control in patients with diabetes, using a previously validated natural language processing system that enables abstraction of lifestyle counseling documentation from narrative electronic provider notes. It identified novel quantitative characteristics of electronic documentation of lifestyle counseling that are associated with improved glycemic control in patients with diabetes.
AHRQ-funded; HS017030.
Citation: Hosomura N, Goldberg SI, Shubina M .
Electronic documentation of lifestyle counseling and glycemic control in patients with diabetes.
Diabetes Care 2015 Jul;38(7):1326-32. doi: 10.2337/dc14-2016..
Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Lifestyle Changes
Herrin J, da Graca B, Aponte P
Impact of an EHR-based diabetes management form on quality and outcomes of diabetes care in primary care practices.
The researchers assessed the impact of a diabetes management form (DMF) accessible within an electronic health record on the quality and outcomes of diabetes care. They found that although tests (microalbumin, eye and foot exams) increased more for DMF-exposed patients, these patients had less improvement in achieving outcomes.
AHRQ-funded; HS020696
Citation: Herrin J, da Graca B, Aponte P .
Impact of an EHR-based diabetes management form on quality and outcomes of diabetes care in primary care practices.
Am J Med Qual. 2015 Jan-Feb;30(1):14-22. doi: 10.1177/1062860613516991..
Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Primary Care, Chronic Conditions
Benkert R, Dennehy P, White J
Diabetes and hypertension quality measurement in four safety-net sites: lessons learned after implementation of the same commercial electronic health record.
The authors described what implementation of a commercially available EHR with built-in quality query algorithms showed us about our care for diabetes and hypertension populations in four safety net clinics. They found that utilizing a shared EHR, a Regional Extension Center-like partnership model, and similar quality query algorithms allowed safety-net clinics to benchmark and improve the quality of care across differing patient populations and health care delivery models.
AHRQ-funded; HS017191.
Citation: Benkert R, Dennehy P, White J .
Diabetes and hypertension quality measurement in four safety-net sites: lessons learned after implementation of the same commercial electronic health record.
Appl Clin Inform 2014 Aug 20;5(3):757-72. doi: 10.4338/aci-2014-03-ra-0019.
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Keywords: Diabetes, Blood Pressure, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality of Care, Chronic Conditions
Hirsch AG, Scheck McAlearney A
Measuring diabetes care performance using electronic health record data: the impact of diabetes definitions on performance measure outcomes.
The authors examined the use of electronic health record (EHR) data for diabetes performance measurement. They found that diabetes performance measures are influenced by the data elements used to identify patients. They recommended that as EHR data are used increasingly to measure performance, continuing to improve our understanding of how EHR data are collected and used will be critical.
AHRQ-funded; HS020165.
Citation: Hirsch AG, Scheck McAlearney A .
Measuring diabetes care performance using electronic health record data: the impact of diabetes definitions on performance measure outcomes.
Am J Med Qual 2014 Jul-Aug;29(4):292-9. doi: 10.1177/1062860613500808.
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Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Measures
Schmittdiel JA, Raebel MA, Dyer W
Prescription medication burden in patients with newly diagnosed diabetes: a SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) study.
The purpose of this study is to use electronic health records to examine how many classes of drugs are used by newly diagnosed patients with diabetes immediately before and after the diagnosis of diabetes. Before diagnosis, these patients are using an average of 5 drug classes, and afterwards, use rises to an average of 6.6. Between 2005 and 2009, the average number of drug classes used after diagnosis decreased slightly.
AHRQ-funded; HS01985
Citation: Schmittdiel JA, Raebel MA, Dyer W .
Prescription medication burden in patients with newly diagnosed diabetes: a SUrveillance, PREvention, and ManagEment of Diabetes Mellitus (SUPREME-DM) study.
J Am Pharm Assoc 2014 Jul-Aug;54(4):374-82. doi: 10.1331/JAPhA.2014.13195..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Diabetes, Medication
Fuji KT, Abbott AA, Galt KA
Personal health record design: qualitative exploration of issues inhibiting optimal use.
Few studies have examined the barriers to personal health record (PHR) use resulting from design issues identified by actual users. The researchers conducted interviews with 59 patients who had received training in using Microsoft Health Vault for PHRs to manage their diabetes-related health information. Three barriers to use (difficulty of use, lack of value, life got in the way) could be traced back to PHR design considerations.
AHRQ-funded; HS018625.
Citation: Fuji KT, Abbott AA, Galt KA .
Personal health record design: qualitative exploration of issues inhibiting optimal use.
Diabetes Care 2014;37(1):e13-4. doi: 10.2337/dc13-1630..
Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Self-Management
Lawrence JM, Black MH, Zhang JL
Validation of pediatric diabetes case identification approaches for diagnosed cases by using information in the electronic health records of a large integrated managed health care organization.
The researchers explored the utility of different algorithms for diabetes case identification by using electronic health records. They found that case identification accuracy was highest in 75% of bootstrapped samples for those who had 1 or more outpatient diabetes diagnoses or 1 or more insulin prescriptions and in 25% of samples for those who had 2 or more outpatient diabetes diagnoses and 1 or more antidiabetic medications.
AHRQ-funded; HS019859.
Citation: Lawrence JM, Black MH, Zhang JL .
Validation of pediatric diabetes case identification approaches for diagnosed cases by using information in the electronic health records of a large integrated managed health care organization.
Am J Epidemiol 2014 Jan;179(1):27-38. doi: 10.1093/aje/kwt230..
Keywords: Children/Adolescents, Diabetes, Chronic Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT), Diagnostic Safety and Quality
Zhang M, Shubina M, Morrison F
Following the money: copy-paste of lifestyle counseling documentation and provider billing.
To find out whether copied documentation of lifestyle counseling was used to justify higher evaluation and management (E&M) charges, researchers investigated 12,527 patient encounters in which lifestyle counseling was documented. When time spent on counseling was recorded, copied lifestyle counseling was associated with a decrease of 70.5% in the odds of higher E&M charges.
AHRQ-funded; HS017030
Citation: Zhang M, Shubina M, Morrison F .
Following the money: copy-paste of lifestyle counseling documentation and provider billing.
BMC Health Serv Res. 2013 Oct 2;13:377. doi: 10.1186/1472-6963-13-377..
Keywords: Diabetes, Electronic Health Records (EHRs), Health Information Technology (HIT), Health Insurance, Lifestyle Changes, Payment