National Healthcare Quality and Disparities Report
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Search All Research Studies
Topics
- Adverse Drug Events (ADE) (1)
- Adverse Events (1)
- Alcohol Use (1)
- Anxiety (1)
- (-) Behavioral Health (16)
- Children/Adolescents (1)
- Chronic Conditions (2)
- Community-Based Practice (1)
- Depression (3)
- Diabetes (1)
- (-) Electronic Health Records (EHRs) (16)
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- Health Information Technology (HIT) (14)
- Health Services Research (HSR) (1)
- Medication (1)
- Outcomes (1)
- Patient-Centered Outcomes Research (1)
- Patient and Family Engagement (1)
- Patient Experience (1)
- Patient Safety (1)
- Pregnancy (1)
- Prevention (1)
- Primary Care (4)
- Screening (1)
- Stress (1)
- Substance Abuse (2)
- Tobacco Use (1)
- Women (1)
- Young Adults (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 16 of 16 Research Studies DisplayedFrimpong JA, Liu X, Liu L
AHRQ Author: Liu L
Adoption of electronic health record among substance use disorder treatment programs: nationwide cross-sectional survey study.
The purpose of this study was to explore the adoption of electronic health record (EHR) systems in substance use disorder (SUD) programs, with an emphasis on changes in adoption from 2014 to 2017, and identify organizational-level variables related with EHR adoption. The researchers utilized data from the 2014 and 2017 National Drug Abuse Treatment System Surveys, and analyzed 1,027 SUD programs. The study found the adoption of EHR increased significantly from 57.6% in 2014 to 69.2% in 2017. Nearly one-third of SUD programs had not yet adopted an EHR system by 2017. The researchers identified a significant increase in technology use and ownership by a parent company and a decrease in the percentage of uninsured patients in 2017 compared to 2014. Further analysis revealed significant differences by adoption status for three main barriers to adoption: 1. Costs of start-up, 2. Ongoing financial costs, and 3. Privacy or security concerns. Programs that used computerized scheduling and billing systems had a greater likelihood of adopting EHR. Ownership type, such as private nonprofit and public, or interest in taking part in a patient-centered medical home were related with a greater likelihood to adopt EHR. Overall, SUD programs were more likely to adopt an EHR system in 2017 compared to 2014.
AHRQ-authored.
Citation: Frimpong JA, Liu X, Liu L .
Adoption of electronic health record among substance use disorder treatment programs: nationwide cross-sectional survey study.
J Med Internet Res 2023 Dec 14; 25:e45238. doi: 10.2196/45238..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Substance Abuse, Behavioral Health
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
Huffstetler AN, Epling J, Krist AH
The need for electronic health records to support delivery of behavioral health preventive services.
In this article the authors discuss adaptations to electronic health records to improve behavioral health preventive services. They recommend a refocus in digital health away from best business practices that help EHR vendors and toward best health-related practice in order to improve patient care and make work easier for clinicians.
AHRQ-funded; HS027077.
Citation: Huffstetler AN, Epling J, Krist AH .
The need for electronic health records to support delivery of behavioral health preventive services.
JAMA 2022 Aug 23;328(8):707-08. doi: 10.1001/jama.2022.13391..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Behavioral Health, Prevention, Healthcare Delivery
Lin Y, Sharma B, Thompson HM
External validation of a machine learning classifier to identify unhealthy alcohol use in hospitalized patients.
This study’s objective was to validate a machine learning approach to alcohol screening using a natural language processing (NLP) classifier developed at an independent medical center. This retrospective cohort study took place at a midwestern US tertiary-care, urban medical center that has an inpatient structured universal screening model for unhealthy substance use and an active addiction consult service. The cohort included 57,605 unplanned admissions of adult patients between October 23, 2017 and December 31, 2019 with electronic health record (EHR) documentation of manual alcohol screening. The authors examined error in manual screening and reviewed discordance between the NLP classifier and AUDIT-derived reference. The classifier demonstrated adequate sensitivity and specificity for routine clinical use as an automated screening tool for identifying at-risk patients.
AHRQ-funded; HS026385.
Citation: Lin Y, Sharma B, Thompson HM .
External validation of a machine learning classifier to identify unhealthy alcohol use in hospitalized patients.
Addiction 2022 Apr;117(4):925-33. doi: 10.1111/add.15730..
Keywords: Alcohol Use, Behavioral Health, Screening, Electronic Health Records (EHRs), Health Information Technology (HIT)
Tang LA, Jeffery AD, Leech AA
A comparison of methods to identify antenatal substance use within electronic health records.
This study described the development of a natural-language-processing-based algorithm for detecting antenatal substance use among individuals receiving perinatal care. Findings showed that the accuracy of antenatal substance use detection was improved with more stringent case definitions; however, the overall proportion of true cases confirmed by manual chart review decreased.
AHRQ-funded; HS026395.
Citation: Tang LA, Jeffery AD, Leech AA .
A comparison of methods to identify antenatal substance use within electronic health records.
Am J Obstet Gynecol MFM 2022 Mar;4(2):100535. doi: 10.1016/j.ajogmf.2021.100535..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Substance Abuse, Pregnancy, Women, Behavioral Health
Turvey CL, Fuhrmeister LA, Klein DM
Patient and provider experience of electronic patient portals and secure messaging in mental health treatment.
This study explored patient and provider experience of patient electronic access to the mental health treatment record and the use of secure messaging. Participants received online surveys with questions about their experiences. Researchers concluded that the implementation of electronic access to mental health notes requires a transition from viewing the medical record as the exclusive tool of providers to that of a collaborative tool for patients and providers to achieve treatment goals.
AHRQ-funded; HS025785.
Citation: Turvey CL, Fuhrmeister LA, Klein DM .
Patient and provider experience of electronic patient portals and secure messaging in mental health treatment.
Telemed J E Health 2022 Feb;28(2):189-98. doi: 10.1089/tmj.2020.0395..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Experience, Behavioral Health, Patient and Family Engagement
Coley RY, Boggs JM, Beck A
Predicting outcomes of psychotherapy for depression with electronic health record data.
This study evaluated models for predicting outcomes of psychotherapy for depression in a clinical practice setting. Findings showed that prediction models did not accurately predict depression treatment outcomes despite using rich electronic health record data and advanced analytic techniques. Recommendations included caution when considering prediction models for psychiatric outcomes using baseline intake information and transparent research to evaluate performance of any model intended for clinical use.
AHRQ-funded; HS026369.
Citation: Coley RY, Boggs JM, Beck A .
Predicting outcomes of psychotherapy for depression with electronic health record data.
J Affect Disord Rep 2021 Dec;6:100198. doi: 10.1016/j.jadr.2021.100198..
Keywords: Depression, Behavioral Health, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient-Centered Outcomes Research, Outcomes
Blumenthal KG, Li Y, Acker WW
Multiple drug intolerance syndrome and multiple drug allergy syndrome: epidemiology and associations with anxiety and depression.
In this study, the authors used electronic health record (EHR) data to describe prevalences of MDIS and MDAS and to examine associations with anxiety and depression. The investigators concluded that: 1.) while 6% of patients had MDIS, only 1% had MDAS; 2.) MDIS was associated with both anxiety and depression; 3.) patients with both anxiety and depression had an almost twofold increased odds of MDIS; 4.) MDAS was associated with a 40% increased odds of depression, but there was no significant association with anxiety.
AHRQ-funded; HS022728.
Citation: Blumenthal KG, Li Y, Acker WW .
Multiple drug intolerance syndrome and multiple drug allergy syndrome: epidemiology and associations with anxiety and depression.
Allergy 2018 Oct;73(10):2012-23. doi: 10.1111/all.13440..
Keywords: Adverse Drug Events (ADE), Adverse Events, Anxiety, Depression, Electronic Health Records (EHRs), Health Information Technology (HIT), Medication, Behavioral Health, Patient Safety
Ratwani R
Electronic health records and improved patient care: opportunities for applied psychology.
There have been numerous challenges that have been largely centered on the technology not meeting the cognitive needs of the clinical end-users. There is a significant opportunity for applied psychologists to address many of these challenges. The author highlights three key areas: studying and modeling clinician needs, applying theoretically grounded design principles, and developing technology to support teamwork and communication.
AHRQ-funded; HS023701.
Citation: Ratwani R .
Electronic health records and improved patient care: opportunities for applied psychology.
Curr Dir Psychol Sci 2017 Aug;26(4):359-65. doi: 10.1177/0963721417700691.
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Keywords: Electronic Health Records (EHRs), Behavioral Health, Health Services Research (HSR)
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.
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Keywords: Behavioral Health, Electronic Health Records (EHRs), Health Information Technology (HIT), Healthcare Delivery, Primary Care, Tobacco Use
Kelley C, Lee B, Wilcox L
Self-tracking for mental wellness: understanding expert perspectives and student experiences.
Recent studies with college student populations have examined the feasibility of collecting everyday mood, activity, and social data. However, these studies do not account for students' experiences and challenges adopting self-tracking technologies to support mental wellness goals. In this paper, the authors present two studies conducted to better understand self-tracking for stress management and mental wellness in student populations.
AHRQ-funded; HS021393.
Citation: Kelley C, Lee B, Wilcox L .
Self-tracking for mental wellness: understanding expert perspectives and student experiences.
Proc SIGCHI Conf Hum Factor Comput Syst 2017 May 2;2017:629-41. doi: 10.1145/3025453.3025750..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Behavioral Health, Stress, Young Adults
Daley MF, Newton DA, DeBar L
Accuracy of electronic health record-derived data for the identification of incident ADHD.
The purpose of this study was to assess the accuracy of electronic health record (EHR)-derived diagnoses in identifying children with incident (i.e., newly diagnosed) ADHD. The authors describe their study and suggest that studies predicated on the identification of incident ADHD cases need to carefully consider study designs that minimize the likelihood of case misclassification.
AHRQ-funded; HS019912.
Citation: Daley MF, Newton DA, DeBar L .
Accuracy of electronic health record-derived data for the identification of incident ADHD.
J Atten Disord 2017 Mar;21(5):416-25. doi: 10.1177/1087054713520616..
Keywords: Children/Adolescents, Electronic Health Records (EHRs), Health Information Technology (HIT), Behavioral Health
Fulford D, Tuot DS, Mangurian C
Electronic psychiatric consultation in primary care in the safety net.
The authors examined the feasibility and acceptability of implementing a psychiatric eReferral program in a publicly funded, community-based primary care clinic in San Francisco staffed by eight primary care practitioners (PCPs). They found feasibility and acceptability of implementing an integrated electronic psychiatry consultation and referral service in a community-based primary care clinic and recommended future trials designed to examine the impact of this type of service on the delivery of high-quality mental health care and its cost-effectiveness in a safety-net health care system.
AHRQ-funded; HS021700.
Citation: Fulford D, Tuot DS, Mangurian C .
Electronic psychiatric consultation in primary care in the safety net.
Psychiatr Serv 2016 Oct;67(10):1160-61. doi: 10.1176/appi.ps.671003.
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Keywords: Community-Based Practice, Electronic Health Records (EHRs), Behavioral Health, Primary Care, Health Information Technology (HIT)
Cifuentes M, Davis M, Fernald D
Electronic health record challenges, workarounds, and solutions observed in practices integrating behavioral health and primary care.
This article describes the electronic health record (EHR)-related experiences of practices striving to integrate behavioral health and primary care using tailored, evidenced-based strategies from 2012 to 2014; and the challenges, workarounds and initial health information technology (HIT) solutions that emerged during implementation. The researchers found that as practices gained experience with integration, they began to move beyond workarounds to more permanent HIT solutions.
AHRQ-funded; HS022981.
Citation: Cifuentes M, Davis M, Fernald D .
Electronic health record challenges, workarounds, and solutions observed in practices integrating behavioral health and primary care.
J Am Board Fam Med 2015 Sep-Oct;28(Suppl 1):S63-72. doi: 10.3122/jabfm.2015.S1.150133..
Keywords: Behavioral Health, Primary Care, Electronic Health Records (EHRs), Evidence-Based Practice
Anderson HD, Pace WD, Brandt E
Monitoring suicidal patients in primary care using electronic health records.
The objective of this study was to estimate the use of diagnostic codes in EHRs to document suicidal ideation and attempt among patients seen in primary care. It found that few cases of suicidal ideation and suicide attempt as documented in a primary care setting using a clinician’s notes field or a patient-reported PHQ-9 were also documented in the patient’s EHR using diagnostic codes.
AHRQ-funded; HS019464.
Citation: Anderson HD, Pace WD, Brandt E .
Monitoring suicidal patients in primary care using electronic health records.
J Am Board Fam Med 2015 Jan-Feb;28(1):65-71. doi: 10.3122/jabfm.2015.01.140181..
Keywords: Behavioral Health, Primary Care, Electronic Health Records (EHRs), Health Information Technology (HIT)
Yoon S, Taha B, Bakken S
Using a data mining approach to discover behavior correlates of chronic disease: a case study of depression.
The purposes of this methodological paper are: 1) to describe data mining methods for building a classification model for a chronic disease using a U.S. behavior risk factor data set, and 2) to illustrate application of the methods using a case study of depressive disorder. Its application of data mining strategies identified childhood experience living with mentally ill and sexual abuse, and limited usual activity as the strongest correlates of depression among hundreds of variables.
AHRQ-funded; HS019853; HS022961.
Citation: Yoon S, Taha B, Bakken S .
Using a data mining approach to discover behavior correlates of chronic disease: a case study of depression.
Stud Health Technol Inform 2014;201:71-8..
Keywords: Chronic Conditions, Behavioral Health, Depression, Health Information Technology (HIT), Electronic Health Records (EHRs)