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- (-) Adverse Events (11)
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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 11 of 11 Research Studies DisplayedAuerbach AD, Lee TM, Hubbard CC
Diagnostic errors in hospitalized adults who died or were transferred to intensive care.
The objective of this retrospective cohort study was to determine the prevalence, underlying causes, and harms of diagnostic errors in hospitalized adults who were transferred to an intensive care unit or who died. Data was taken from 29 academic medical centers in the U.S. in a random sample of adults hospitalized with general medical conditions. Errors were found to have contributed to temporary harm, permanent harm, or death in nearly 18% of patients; among patients who died, diagnostic error was judged to have contributed to death in 6.6% of cases. The researchers noted that problems with choosing and interpreting tests and the processes involved with clinician assessment were a high priority for improvement efforts.
AHRQ-funded; HS027369.
Citation: Auerbach AD, Lee TM, Hubbard CC .
Diagnostic errors in hospitalized adults who died or were transferred to intensive care.
JAMA Intern Med 2024 Feb; 184(2):164-73. doi: 10.1001/jamainternmed.2023.7347..
Keywords: Diagnostic Safety and Quality, Medical Errors, Hospitals, Inpatient Care, Quality of Care, Patient Safety, Adverse Events
Dalal AK, Schnipper JL, Raffel K
Identifying and classifying diagnostic errors in acute care across hospitals: early lessons from the Utility of Predictive Systems in Diagnostic Errors (UPSIDE) study.
This paper describes the Utility of Predictive Systems in Diagnostic Errors (UPSIDE) study, whose aim was to define the prevalence and underlying causes of diagnostic errors (DEs) in patients who die in the hospital or are transferred to the intensive care unit (ICU) after the first 48 hours. This study was conducted at 31 hospitals with more than 2500 cases reviewed using electronic health records. The authors identified some insights into key requirements into building a robust DE surveillance program by developing these steps: 1) Develop a shared understanding of what constitutes a diagnostic error; 2) Use validated tools to identify diagnostic errors and classify process failures, but respect your context; 3) Develop a standard approach to using electronic health records for case reviews; 4) Ensure reliability and consistency of the case review process; and 5) Link diagnostic error case reviews to institutional safety programs. They also developed steps to establish a diagnosis error review process at the hospital level with six processes.
AHRQ-funded; HS027369; HS026613.
Citation: Dalal AK, Schnipper JL, Raffel K .
Identifying and classifying diagnostic errors in acute care across hospitals: early lessons from the Utility of Predictive Systems in Diagnostic Errors (UPSIDE) study.
J Hosp Med 2024 Feb; 19(2):140-45. doi: 10.1002/jhm.13136..
Keywords: Diagnostic Safety and Quality, Medical Errors, Adverse Events, Patient Safety, Quality of Care, Hospitals
Newman-Toker DE, Nassery N, Schaffer AC
Burden of serious harms from diagnostic error in the USA.
Americans who experience serious harm from misdiagnosis annually. Serious harm is defined as permanent morbidity or morality. This cross-sectional analysis used nationally representative observational data. The authors estimated annual incident vascular events and infections from 21.5 million (M) sampled US hospital discharges (2012-2014). US-based cancer registries were used to find annual new cancers. They derived diagnostic errors and serious harms by multiplying by literature-based rates for disease-specific incidences for 15 major vascular events, infections and cancers ('Big Three' categories). Extrapolating to all diseases (including non-'Big Three' dangerous disease categories), they estimated total serious harms annually in the USA to be 795,000 (plausible range 598,000-1,023,000). Using more conservative assumptions they estimated 549,000 serious harms. These results were compatible with setting-specific serious harm estimates from inpatient, emergency department and ambulatory care. Fifteen dangerous diseases accounted for 50.7% of total serious harms and the top 5 (stroke, sepsis, pneumonia, venous thromboembolism and lung cancer) accounted for 38.7%.
AHRQ-funded; HS027614; HS029350.
Citation: Newman-Toker DE, Nassery N, Schaffer AC .
Burden of serious harms from diagnostic error in the USA.
BMJ Qual Saf 2024 Jan 19; 33(2):109-20. doi: 10.1136/bmjqs-2021-014130..
Keywords: Healthcare Cost and Utilization Project (HCUP), Diagnostic Safety and Quality, Medical Errors, Patient Safety, Quality of Care, Adverse Events
Giardina TD, Hunte H, Hill MA
Defining diagnostic error: a scoping review to assess the impact of the National Academies' report improving diagnosis in Health Care.
This study looked at peer-reviewed published literature to explore how researchers operationalize the National Academies of Science, Engineering, and Medicine’s (NASEM) definition of diagnostic error that was defined in their 2015 publication “Improving Diagnosis in Health Care”. Published literature was identified from October 2015 to February 2021. The authors also conducted subject matter expert interviews. Of the 34 studies identified, 16 were analyzed and abstracted to determine how diagnostic error was operationalized and measured. Studies were grouped by four themes: epidemiology, patient focus, measurement/surveillance, and clinician focus. Nine studies identified used the NASM definition. Five of those studies also operationalized with existing definitions proposed before the NASEM report, four operationalized the components of the NASEM definition, and three studies operationalized error using existing definitions only. Subject matter experts concluded that the NASEM definition functions as a foundation for researchers to conceptualize diagnostic error.
AHRQ-funded; 233201500022I; HS027280; HS025474; HS027363.
Citation: Giardina TD, Hunte H, Hill MA .
Defining diagnostic error: a scoping review to assess the impact of the National Academies' report improving diagnosis in Health Care.
J Patient Saf 2022 Dec 1;18(8):770-78. doi: 10.1097/pts.0000000000000999..
Keywords: Diagnostic Safety and Quality, Quality of Care, Medical Errors, Adverse Events, Healthcare Delivery
Zhu Y, Simon GJ, Wick EC
Applying machine learning across sites: external validation of a surgical site infection detection algorithm.
Surgical complications have tremendous consequences and costs. Complication detection is important for quality improvement, but traditional manual chart review is burdensome. Automated mechanisms are needed to make this more efficient. The purpose of the study was to understand the generalizability of a machine learning algorithm between sites; automated surgical site infection (SSI) detection algorithms developed at one center were tested at another distinct center.
AHRQ-funded; HS024532.
Citation: Zhu Y, Simon GJ, Wick EC .
Applying machine learning across sites: external validation of a surgical site infection detection algorithm.
J Am Coll Surg 2021 Jun;232(6):963-71.e1. doi: 10.1016/j.jamcollsurg.2021.03.026..
Keywords: Healthcare-Associated Infections (HAIs), Surgery, Adverse Events, Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality Improvement, Quality of Care
Marshall TL, Ipsaro AJ, Le M
Increasing physician reporting of diagnostic learning opportunities.
This study investigated methods to improve physician reporting of diagnostic errors at the pediatric division of a hospital. In that pediatric hospital medicine (PHM) division only 1 diagnostic-related safety event was reported in the preceding 4 years. The authors aimed to improve attending physician reporting of suspected diagnostic errors from 0 to 2 per 100 PHM patient admissions within 6 months. The improvement team used the Model for Improvement and used the term diagnostic learning opportunity (DLO) with clinicians as opposed to diagnostic error to lessen the stigma. They developed an electronic reporting form and encouraged its use through reminders, scheduled reflection time, and monthly progress reports. Over the course of 13 weeks, there was an increase from 0 to 1.6 per patient admission reports files. Most events (66%) were true diagnostic errors.
AHRQ-funded; HS023827.
Citation: Marshall TL, Ipsaro AJ, Le M .
Increasing physician reporting of diagnostic learning opportunities.
Pediatrics 2021 Jan;147(1). doi: 10.1542/peds.2019-2400..
Keywords: Children/Adolescents, Diagnostic Safety and Quality, Medical Errors, Adverse Events, Patient Safety, Hospitals, Quality Improvement, Quality of Care
Dadlez NM, Adelman J, Bundy DG
Contributing factors for pediatric ambulatory diagnostic process errors: Project RedDE.
This study examined root causes of three common pediatric diagnostic errors by having 31 practices enrolled in a national QI collaborative perform monthly “mini-RCAs” (mini root cause analyses). The diagnoses errors studied were missed adolescent depression, missed elevated blood pressure, and missed actionable laboratory values. Twenty-eight practices submitted 184 mini-RCAs with the most common causes being patient volume (adolescent depression and elevated BP), inadequate staffing (adolescent depression), clinic milieu (elevated BP), written communication and provider knowledge (actionable laboratory values), and electronic health records (EHRs) – (elevated BP and actionable laboratory values). The median number of mini-RCAs submitted was 6.
AHRQ-funded; HS024538; HS024713; HS026121.
Citation: Dadlez NM, Adelman J, Bundy DG .
Contributing factors for pediatric ambulatory diagnostic process errors: Project RedDE.
Pediatr Qual Saf 2020 May-Jun;5(3):e299. doi: 10.1097/pq9.0000000000000299..
Keywords: Children/Adolescents, Diagnostic Safety and Quality, Quality Improvement, Quality of Care, Medical Errors, Adverse Events, Patient Safety
Sheehan SE, Safdar N, Singh H
Detection and remediation of misidentification errors in radiology examination ordering.
In this study, the investigators described the pilot testing of a quality improvement methodology using electronic trigger tools and preimaging checklists to detect "wrong-side" misidentification errors in radiology examination ordering, and to measure staff adherence to departmental policy in error remediation. The investigators concluded that their trigger tool enabled the detection of substantially more imaging ordering misidentification errors than preimaging safety checklists alone, with a high positive predictive value.
AHRQ-funded; HS022087; HS017820.
Citation: Sheehan SE, Safdar N, Singh H .
Detection and remediation of misidentification errors in radiology examination ordering.
Appl Clin Inform 2020 Jan;11(1):79-87. doi: 10.1055/s-0039-3402730..
Keywords: Medical Errors, Adverse Events, Diagnostic Safety and Quality, Patient Safety, Imaging, Quality Improvement, Quality of Care
Singh H, Graber ML, Hofer TP
Measures to improve diagnostic safety in clinical practice.
In this paper, the investigators discuss how the need to develop measures to improve diagnostic performance could move forward at a time when the scientific foundation needed to inform measurement is still evolving. They highlight challenges and opportunities for developing potential measures of "diagnostic safety" related to clinical diagnostic errors and associated preventable diagnostic harm. In doing so, they propose a starter set of measurement concepts for initial consideration that seem reasonably related to diagnostic safety and call for these to be studied and further refined.
AHRQ-funded; HS022087.
Citation: Singh H, Graber ML, Hofer TP .
Measures to improve diagnostic safety in clinical practice.
J Patient Saf 2019 Dec;15(4):311-16. doi: 10.1097/pts.0000000000000338.
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Keywords: Patient Safety, Diagnostic Safety and Quality, Healthcare Delivery, Quality Improvement, Quality of Care, Medical Errors, Adverse Events
Bundy DG, Singh H, Stein RE
The design and conduct of Project RedDE: a cluster-randomized trial to reduce diagnostic errors in pediatric primary care.
This paper discusses the results of Project RedDE, which was a virtual collaborative quality improvement study to reduce diagnostic errors in pediatric primary care practices. Forty-three practices were initially recruited, with a total of 31 practices left at the end due to practice dropout and two participating practices merging. This study was a randomized controlled trial targeting three common diagnostic errors (missed diagnoses of adolescent depression, abnormal blood pressure, and lack of followup for abnormal laboratory results). Contamination across study groups was a recurring problem, but risk mitigations were used. Electronic health records contributed to teams’ success.
AHRQ-funded; HS203608.
Citation: Bundy DG, Singh H, Stein RE .
The design and conduct of Project RedDE: a cluster-randomized trial to reduce diagnostic errors in pediatric primary care.
Clin Trials 2019 Apr;16(2):154-64. doi: 10.1177/1740774518820522..
Keywords: Adverse Events, Children/Adolescents, Diagnostic Safety and Quality, Medical Errors, Prevention, Primary Care, Quality of Care, Quality Improvement
Muldoon MF, Kronish IM, Shimbo D
Of signal and noise: overcoming challenges in blood pressure measurement to optimize hypertension care.
This paper reviews the manifestations and consequences of BP mismeasurement and misinterpretation in clinical practice and draw on recent research to propose a set of solutions that leverage available technologies to optimize hypertension care.
AHRQ-funded; HS024262.
Citation: Muldoon MF, Kronish IM, Shimbo D .
Of signal and noise: overcoming challenges in blood pressure measurement to optimize hypertension care.
Circ Cardiovasc Qual Outcomes 2018 May;11(5):e004543. doi: 10.1161/circoutcomes.117.004543..
Keywords: Blood Pressure, Diagnostic Safety and Quality, Adverse Events, Medical Errors, Electronic Health Records (EHRs), Health Information Technology (HIT), Quality of Care