National Healthcare Quality and Disparities Report
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AHRQ Research Studies Date
Topics
- Adverse Drug Events (ADE) (2)
- Adverse Events (3)
- Cancer (1)
- Cardiovascular Conditions (1)
- Children/Adolescents (1)
- Chronic Conditions (2)
- Clinical Decision Support (CDS) (1)
- Clinician-Patient Communication (1)
- Communication (2)
- Dementia (1)
- Diabetes (2)
- (-) Diagnostic Safety and Quality (16)
- (-) Electronic Health Records (EHRs) (16)
- Healthcare Delivery (1)
- Health Information Technology (HIT) (16)
- Heart Disease and Health (1)
- Imaging (5)
- Kidney Disease and Health (1)
- Medical Errors (2)
- Medication (1)
- Medication: Safety (1)
- Neurological Disorders (1)
- Patient Safety (5)
- Primary Care (1)
- Quality Improvement (2)
- Quality of Care (2)
- Shared Decision Making (2)
- Surgery (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 DisplayedSalmasian H, Blanchfield BB, Joyce K
Association of display of patient photographs in the electronic health record with wrong-patient order entry errors.
Wrong-patient order entry (WPOE) errors have a high potential for harm; these errors are particularly frequent wherever workflows are complex and multitasking and interruptions are common, such as in the emergency department (ED). The purpose of this study was to evaluate whether the use of noninterruptive display of patient photographs in the banner of the electronic health record (EHR) is associated with a decreased rate of WPOE errors.
AHRQ-funded; HS024713.
Citation: Salmasian H, Blanchfield BB, Joyce K .
Association of display of patient photographs in the electronic health record with wrong-patient order entry errors.
AMA Netw Open 2020 Nov 2;3(11):e2019652. doi: 10.1001/jamanetworkopen.2020.19652..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Medical Errors, Adverse Drug Events (ADE), Adverse Events, Medication, Medication: Safety, Patient Safety, Diagnostic Safety and Quality
Rogith D, Satterly T, Singh H
Application of human factors methods to understand missed follow-up of abnormal test results.
This study demonstrated application of human factors methods for understanding causes for lack of timely follow-up of abnormal test results ("missed results") in outpatient settings. The investigators identified 30 cases of missed test results by querying electronic health record data, developed a critical decision method based interview guide to understand decision-making processes, and interviewed physicians who ordered these tests. They analyzed transcribed responses, developed a CI-based flow model, and conducted a fault tree analysis to identify hierarchical relationships between factors that delayed action.
AHRQ-funded; HS022087; HS022901.
Citation: Rogith D, Satterly T, Singh H .
Application of human factors methods to understand missed follow-up of abnormal test results.
Appl Clin Inform 2020 Oct;11(5):692-98. doi: 10.1055/s-0040-1716537..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Shared Decision Making, Diagnostic Safety and Quality, Communication, Clinician-Patient Communication
Shah RU, Mutharasan RK, Ahmad FS
Development of a portable tool to identify patients with atrial fibrillation using clinical notes from the electronic medical record.
The electronic medical record contains a wealth of information buried in free text. In this study, the investigators created a natural language processing algorithm to identify patients with atrial fibrillation (AF) using text alone. The authors concluded that this approach allowed better use of the clinical narrative and created an opportunity for precise, high-throughput cohort identification.
AHRQ-funded; HS026385.
Citation: Shah RU, Mutharasan RK, Ahmad FS .
Development of a portable tool to identify patients with atrial fibrillation using clinical notes from the electronic medical record.
Circ Cardiovasc Qual Outcomes 2020 Oct;13(10):e006516. doi: 10.1161/circoutcomes.120.006516..
Keywords: Heart Disease and Health, Cardiovascular Conditions, Electronic Health Records (EHRs), Health Information Technology (HIT), Diagnostic Safety and Quality
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
Bronsert M, Singh AB, Henderson WG
Identification of postoperative complications using electronic health record data and machine learning.
Investigators developed a machine learning algorithm for identifying patients with one or more complications using data from the electronic health record (EHR). They concluded that using machine learning on EHR postoperative data linked to American College of Surgeons National Surgical Quality Improvement Program outcomes data, a model with 163 predictors from the EHR identified complications well at their institution.
AHRQ-funded; HS026019.
Citation: Bronsert M, Singh AB, Henderson WG .
Identification of postoperative complications using electronic health record data and machine learning.
Am J Surg 2020 Jul;220(1):114-19. doi: 10.1016/j.amjsurg.2019.10.009..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Surgery, Quality Improvement, Quality of Care, Diagnostic Safety and Quality
Lacson R, Healey MJ, Cochon LR
Unscheduled radiologic examination orders in the electronic health record: a novel resource for targeting ambulatory diagnostic errors in radiology.
The purpose of this study was to assess the prevalence of unscheduled radiologic examination orders in an electronic health record and to assess the proportion of unscheduled orders that are clinically necessary. Unscheduled radiologic examination orders were retrieved for seven modalities: computed tomography, magnetic resonance imaging, ultrasound, obstetric ultrasound, bone densitometry, mammography, and fluoroscopy. Findings showed that large numbers of radiologic examination orders remain unscheduled in the electronic health record. Identifying and performing clinically necessary unscheduled radiologic examination orders may help reduce diagnostic errors related to diagnosis and treatment delays and enhance patient safety.
AHRQ-funded; HS024722.
Citation: Lacson R, Healey MJ, Cochon LR .
Unscheduled radiologic examination orders in the electronic health record: a novel resource for targeting ambulatory diagnostic errors in radiology.
J Am Coll Radiol 2020 Jun;17(6):765-72. doi: 10.1016/j.jacr.2019.12.021..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Diagnostic Safety and Quality, Imaging, Patient Safety
Zhou Y, Abel GA, Hamilton W
Imaging activity possibly signalling missed diagnostic opportunities in bladder and kidney cancer: a longitudinal data-linkage study using primary care electronic health records.
Sub-optimal use or interpretation of imaging investigations prior to diagnosis of certain cancers may be associated with less timely diagnosis, but pre-diagnostic imaging activity for urological cancer is unknown. In this study, the investigators analysed linked data derived from primary and secondary care records and cancer registration to evaluate the use of clinically relevant imaging tests pre-diagnosis, in patients with bladder and kidney cancer diagnosed in 2012-15 in England.
AHRQ-funded; HS022087.
Citation: Zhou Y, Abel GA, Hamilton W .
Imaging activity possibly signalling missed diagnostic opportunities in bladder and kidney cancer: a longitudinal data-linkage study using primary care electronic health records.
Cancer Epidemiol 2020 Jun;66:101703. doi: 10.1016/j.canep.2020.101703..
Keywords: Cancer, Diagnostic Safety and Quality, Imaging, Primary Care, Electronic Health Records (EHRs), Health Information Technology (HIT)
Soleimani J, Pinevich Y, Barwise AK
Feasibility and reliability testing of manual electronic health record reviews as a tool for timely identification of diagnostic error in patients at risk.
Although diagnostic error (DE) is a significant problem, it remains challenging for clinicians to identify it reliably and to recognize its contribution to the clinical trajectory of their patients. The purpose of this work was to evaluate the reliability of real-time electronic health record (EHR) reviews using a search strategy for the identification of DE as a contributor to the rapid response team (RRT) activation. Early and accurate recognition of critical illness is of paramount importance.
AHRQ-funded; HS026609.
Citation: Soleimani J, Pinevich Y, Barwise AK .
Feasibility and reliability testing of manual electronic health record reviews as a tool for timely identification of diagnostic error in patients at risk.
Appl Clin Inform 2020 May;11(3):474-82. doi: 10.1055/s-0040-1713750..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Diagnostic Safety and Quality, Medical Errors, Adverse Events, Patient Safety
Barnes DE, Zhou J, Walker RL
Development and validation of eRADAR: a tool using EHR Data to detect unrecognized dementia.
The goal of this retrospective cohort study was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia. The tool was named EHR Risk of Alzheimer’s and Dementia Assessment Rule (eRADAR). This study was conducted at Kaiser Permanente Washington (KPWA) using participants in the Adult Changes in Thought (ACT) study who undergo comprehensive testing every 2 years to detect and diagnose dementia and have linked KPWA EHR data. Overall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 49% were previously unrecognized in the EHR. The final 31-predictor model included markers of dementia-related symptoms, healthcare utilization patterns, and dementia risk factors. The study showed good discrimination in the development interval and validation samples.
AHRQ-funded; HS022982.
Citation: Barnes DE, Zhou J, Walker RL .
Development and validation of eRADAR: a tool using EHR Data to detect unrecognized dementia.
J Am Geriatr Soc 2020 Jan;68(1):103-11. doi: 10.1111/jgs.16182..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Dementia, Neurological Disorders, Diagnostic Safety and Quality, Clinical Decision Support (CDS), Shared Decision Making
Lacson R, Gujrathi I, Healey M
Closing the loop on unscheduled diagnostic imaging orders: a systems-based approach.
This study looked at the impact of implementing a tool called SCORE (System for Coordinating Orders for Radiology Exams), whose objective is to manage unscheduled orders for outpatient diagnostic imaging in an electronic health record (EHR) with embedded computerized physician order entry. The rate of unscheduled imaging orders was compared before SCORE (October 2017 to September 2018) and after (October 2018 to June 2019). There was a 49% reduction in unscheduled orders after SCORE implementation at a large academic institution.
AHRQ-funded; HS024722.
Citation: Lacson R, Gujrathi I, Healey M .
Closing the loop on unscheduled diagnostic imaging orders: a systems-based approach.
J Am Coll Radiol 2021 Jan;18(1 Pt A):60-67. doi: 10.1016/j.jacr.2020.09.031..
Keywords: Imaging, Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Safety
Danforth KN, Hahn EE, Slezak JM
Follow-up of abnormal estimated GFR results within a large integrated health care delivery system: a mixed-methods study.
This study examined the rates of follow-up with patients after abnormal estimated glomular filtration rate (eGFR) laboratory results, which may indicate chronic kidney disease. A large integrated health system was used with a total of 244,540 patients aged 21 or older with abnormal eGFRs were included from January 2010 through December 2015. Timely follow-up was defined as repeat eGFR testing within 60 to 150 days, follow-up testing before 60 days that indicated normal kidney function, or diagnosis before 60 days of chronic kidney disease or kidney cancer. Follow-up was found to be poor, with 58% of patients lacking timely follow-up. Fifteen physicians were also interviewed and it was found that both system-level and provider-level factors influenced follow-up rates.
AHRQ-funded; HS024437.
Citation: Danforth KN, Hahn EE, Slezak JM .
Follow-up of abnormal estimated GFR results within a large integrated health care delivery system: a mixed-methods study.
Am J Kidney Dis 2019 Nov;74(5):589-600. doi: 10.1053/j.ajkd.2019.05.003..
Keywords: Healthcare Delivery, Diagnostic Safety and Quality, Kidney Disease and Health, Electronic Health Records (EHRs), Health Information Technology (HIT), Chronic Conditions
Kang SK, Garry K, Chung R
Natural language processing for identification of incidental pulmonary nodules in radiology reports.
The authors developed natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations using the electronic health records for patients who underwent chest CT before and after implementation of a department-wide dictation macro of the Fleischner Society recommendations. They concluded that NLP reliably automates identification of ILNs in unstructured reports, pertinent to quality improvement efforts for ILN management.
AHRQ-funded; HS024376.
Citation: Kang SK, Garry K, Chung R .
Natural language processing for identification of incidental pulmonary nodules in radiology reports.
J Am Coll Radiol 2019 Nov;16(11):1587-94. doi: 10.1016/j.jacr.2019.04.026..
Keywords: Imaging, Diagnostic Safety and Quality, Health Information Technology (HIT), Electronic Health Records (EHRs), Quality Improvement, Quality of Care
Quinn M, Forman J, Harrod M
Electronic health records, communication, and data sharing: challenges and opportunities for improving the diagnostic process.
Diagnosis requires that clinicians communicate and share patient information in an efficient manner. Advances in electronic health records (EHRs) and health information technologies have created challenges and opportunities for such communication. In this multi-method, focused ethnographic study of physicians on general medicine inpatient units in two teaching hospitals, the investigators found that existing communication technologies and EHR-based data sharing processes were perceived as barriers to diagnosis. In particular, reliance on paging systems and lack of face-to-face communication among clinicians created obstacles to sustained thinking and discussion of diagnostic decision-making.
AHRQ-funded; HS022835; HS024385.
Citation: Quinn M, Forman J, Harrod M .
Electronic health records, communication, and data sharing: challenges and opportunities for improving the diagnostic process.
Diagnosis 2019 Aug 27;6(3):241-48. doi: 10.1515/dx-2018-0036.
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Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Diagnostic Safety and Quality, Communication
Deng F, Li MD, Wong A
Quality of documentation of contrast agent allergies in electronic health records.
The purpose of this study was to describe and appraise contrast agent allergy documentation in the electronic health record (EHR). The investigators concluded that contrast allergy records in EHRs were diverse and commonly low quality. They suggest that continued EHR enhancements and training are needed to support contrast allergy documentation to facilitate improved patient care and medical research.
AHRQ-funded; HS025375.
Citation: Deng F, Li MD, Wong A .
Quality of documentation of contrast agent allergies in electronic health records.
J Am Coll Radiol 2019 Aug;16(8):1027-35. doi: 10.1016/j.jacr.2019.01.027..
Keywords: Adverse Drug Events (ADE), Adverse Events, Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT), Imaging
Murphy DR, Meyer AN, Sittig DF
Application of electronic trigger tools to identify targets for improving diagnostic safety.
This article discusses the use of electronic trigger tools to reduce diagnostic errors and improve patient safety. The authors present a framework called Safer Dx Trigger Tools Framework that will enable health systems to develop and implement e-trigger tools. It identifies and measures diagnostic errors using comprehensive electronic health record (EHR) data. The application of the algorithms used will require a diverse team of specialists to implement. Future research is also outlined.
AHRQ-funded; HS022901; HS022087; HS017820.
Citation: Murphy DR, Meyer AN, Sittig DF .
Application of electronic trigger tools to identify targets for improving diagnostic safety.
BMJ Qual Saf 2019 Feb;28(2):151-59. doi: 10.1136/bmjqs-2018-008086..
Keywords: Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Safety
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