National Healthcare Quality and Disparities Report
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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 25 of 81 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
Schnipper JL, Raffel KE, Keniston A
Achieving diagnostic excellence through prevention and teamwork (ADEPT) study protocol: a multicenter, prospective quality and safety program to improve diagnostic processes in medical inpatients.
This paper describes the protocol for a study that will build surveillance for hospital diagnostic errors into usual care, benchmark diagnostic performance across sites, pilot test interventions, and evaluate the program's impact on diagnostic error rates. The authors will test achieving diagnostic excellence through prevention and teamwork (ADEPT), a multicenter, real-world quality and safety program utilizing interrupted time-series techniques to evaluate outcomes. They will use a randomly sampled population of medical patients hospitalized at 16 US hospitals who died, were transferred to intensive care, or had a rapid response during the hospitalization. There will be surveillance for diagnostic errors on 10 events per month per site using a previously established two-person adjudication process. With guidance from national experts in quality and safety, study sites will report and benchmark diagnostic error rates, share lessons regarding underlying causes, and design, implement, and pilot test interventions using both Safety I and Safety II approaches aimed at patients, providers, and health systems. The primary outcome sought after will be the number of diagnostic errors per patient, using segmented multivariable regression to evaluate change in y-intercept and change in slope after initiation of the program.
AHRQ-funded; HS029366.
Citation: Schnipper JL, Raffel KE, Keniston A .
Achieving diagnostic excellence through prevention and teamwork (ADEPT) study protocol: a multicenter, prospective quality and safety program to improve diagnostic processes in medical inpatients.
J Hosp Med 2023 Dec; 18(12):1072-81. doi: 10.1002/jhm.13230..
Keywords: Diagnostic Safety and Quality, Patient Safety, Quality of Care, Hospitals, Inpatient Care
Cifra CL, Custer JW, Smith CM
Prevalence and characteristics of diagnostic error in pediatric critical care: a multicenter study.
This study’s objective was to determine the prevalence and characteristics of diagnostic errors and identify factors associated with error in patients admitted to the PICU. This multicenter cohort study used structured medical record review by trained clinicians using the Revised Safer Dx instrument to identify diagnostic error (defined as missed opportunities in diagnosis). The cohort included 882 randomly selected patients 0-18 years old who were nonelectively admitted to participating PICUs. Of these admissions, 13 (1.5%) had a diagnostic error up to 7 days after PICU admission, with infections (46%) and respiratory conditions (23%) being the most missed diagnoses. One diagnostic error caused a prolonged hospital stay. Common missed diagnostic opportunities included failure to consider the diagnosis despite a suggestive history and failure to broaden diagnostic testing, both at 69%. Unadjusted analysis identified more diagnostic errors in patients with atypical presentations (23.1% vs 3.6%), neurologic chief complaints (46.2% vs 18.8%), admitting intensivists greater than or equal to 45 years old (92.3% vs 65.1%), admitting intensivists with more service weeks/year (mean 12.8 vs 10.9 weeks), and diagnostic uncertainty on admission (77% vs 25.1%). Generalized linear mixed models determined that atypical presentation (odds ratio [OR] 4.58) and diagnostic uncertainty on admission (OR 9.67) were significantly associated with diagnostic error.
AHRQ-funded; HS026965.
Citation: Cifra CL, Custer JW, Smith CM .
Prevalence and characteristics of diagnostic error in pediatric critical care: a multicenter study.
Crit Care Med 2023 Nov; 51(11):1492-501. doi: 10.1097/ccm.0000000000005942..
Keywords: Children/Adolescents, Diagnostic Safety and Quality, Critical Care, Intensive Care Unit (ICU), Medical Errors, Patient Safety
Gupta AB, Greene MT, Fowler KE
Associations between hospitalist shift busyness, diagnostic confidence, and resource utilization: a pilot study.
Hospitalists are frequently attending to multiple tasks when overseeing patient care, and patients are at risk for diagnostic errors. The purpose of this single-center, prospective, pilot observational study was to measure hospitalist workload and examine its influences on diagnostic performance in a real-world clinical setting. The researchers had hospitalists admitting new patients to the hospital complete an abbreviated Mindful Attention Awareness Tool and a survey on diagnostic confidence upon shift completion. Complete data were available for 37 unique hospitalists who admitted 160 unique patients. The study found that increases in admissions and pages were related with higher odds of hospitalists reporting it was "difficult to focus on what is happening in the present." Increased pages was associated with a decrease in the number of differential diagnoses listed.
AHRQ-funded; HS024385; HS025891.
Citation: Gupta AB, Greene MT, Fowler KE .
Associations between hospitalist shift busyness, diagnostic confidence, and resource utilization: a pilot study.
J Patient Saf 2023 Oct 1; 19(7):447-52. doi: 10.1097/pts.0000000000001157..
Keywords: Hospitals, Diagnostic Safety and Quality, Patient Safety
Bourgeois FC, Hart NJ, Dong Z
Partnering with patients and families to improve diagnostic safety through the OurDX tool: effects of race, ethnicity, and language preference.
This study’s objective was to explore differences in race, ethnicity, and language preference associated with patient and family contributions and concerns using an electronic previsit tool designed to engage pediatric patients and their families in the diagnostic process (DxP). This cross-sectional study included 5,731 patients and families presenting to three subspecialty clinics at an urban pediatric hospital May to December 2021 who completed a previsit tool, which was codeveloped and tested with patients and families. Patients/families were invited to share visit priorities, recent histories, and potential diagnostic concerns prior to each visit. The authors conducted chart review on a random subset of visits to review concerns and determine whether patient/family contributions were included in the visit note. Compared with patients self-identifying as White, those self-identifying as Black (odds ratio [OR]: 1.70) or "other" race (OR: 1.48) were more likely to report a diagnostic concern. Participants who preferred a language other than English were more likely to report a diagnostic concern than English-preferring patients (OR: 2.53). No significant differences were found in physician-verified diagnostic concerns or in integration of patient contributions into the note based on race, ethnicity, or language preference.
AHRQ-funded; HS027367.
Citation: Bourgeois FC, Hart NJ, Dong Z .
Partnering with patients and families to improve diagnostic safety through the OurDX tool: effects of race, ethnicity, and language preference.
Appl Clin Inform 2023 Oct; 14(5):903-12. doi: 10.1055/s-0043-1776055..
Keywords: Diagnostic Safety and Quality, Patient Safety, Racial and Ethnic Minorities
Zhu Y, Wang Z, Newman-Toker D
Misdiagnosis-related harm quantification through mixture models and harm measures.
Investigating and monitoring misdiagnosis-related harm utilizing the traditional chart review process is labor intensive, potentially unstable, and not conducive to scaling. Researchers propose to leverage the association between symptoms and diseases based on electronic health records or claim data. Specifically, the increased risk of disease after a false-negative diagnosis can be utilized as an indicator of potential harm. The researcher report that the problem with off-the-shelf statistical methods to assess these dynamics is that they do not fully accommodate the data structure of a well-hypothesized risk pattern and thus fail to sufficiently address the unique challenges. The purpose of this study was to explore a mixture regression model and its associated goodness-of-fit testing to address the existing gaps seen in usual statistical analysis methods. The researchers additionally proposed harm measures and profiling analysis procedures to quantify, assess, and compare misdiagnosis-related harm across institutes with potentially differing patient population compositions. Simulation studies were utilized to study the performance of the proposed methods. Researchers then applied and demonstrated the methods through data analyses on stroke occurrence data from the Taiwan Longitudinal Health Insurance Database. From those analyses risk factors for being harmed due to misdiagnosis were assessed, which revealed insights for health care quality research. Finally, researchers compared general and special care hospitals in Taiwan and observed better diagnostic performance in special care hospitals utilizing a variety of new assessment measures.
AHRQ-funded; HS027614.
Citation: Zhu Y, Wang Z, Newman-Toker D .
Misdiagnosis-related harm quantification through mixture models and harm measures.
Biometrics 2023 Sep; 79(3):2633-48. doi: 10.1111/biom.13759..
Keywords: Diagnostic Safety and Quality, Patient Safety, Hospitals
Liberman AL, Wang Z, Zhu Y
Optimizing measurement of misdiagnosis-related harms using Symptom-Disease Pair Analysis of Diagnostic Error (SPADE): comparison groups to maximize SPADE validity.
The purpose of this paper was to clarify features of the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) approach to accurately measure diagnostic errors to assure that researchers utilize this method to yield valid results, as well as improve the validity of SPADE and related approaches to quantify diagnostic error in medicine. The researchers describe four types of comparators (intra-group and inter-group), detailing the reason for selecting one over the other and conclusions that can be drawn from these comparative analyses.
AHRQ-funded; HS027614.
Citation: Liberman AL, Wang Z, Zhu Y .
Optimizing measurement of misdiagnosis-related harms using Symptom-Disease Pair Analysis of Diagnostic Error (SPADE): comparison groups to maximize SPADE validity.
Diagnosis 2023 Aug 1; 10(3):225-34. doi: 10.1515/dx-2022-0130..
Keywords: Diagnostic Safety and Quality, Medical Errors, Adverse Events, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Safety
Garber A, Garabedian P, Wu L
Developing, pilot testing, and refining requirements for 3 EHR-integrated interventions to improve diagnostic safety in acute care: a user-centered approach.
This study’s objective was to describe a user-centered approach to develop, pilot test, and refine requirements for 3 electronic health record (EHR)-integrated interventions that target key diagnostic process failures in hospitalized patients. The interventions to be developed were a Diagnostic Safety Column (DSC) within an EHR-integrated dashboard to identify at-risk patients; a Diagnostic Time-Out (DTO) for clinicians to reassess the working diagnosis; and a Patient Diagnosis Questionnaire (PDQ) to gather patient concerns about the diagnostic process. After initial refinement from an analysis, final requirements were created for 10 test cases predicted by the DSC, 18 clinician DTO participants, and 39 PDQ responses including the following: DSC configurable parameters (variables, weights) to adjust baseline risk estimates in real-time based on new clinical data collected during hospitalization; more concise DTO wording and flexibility for clinicians to conduct the DTO with or without the patient present; and integration of PDQ responses into the DSC to ensure closed-looped communication with clinicians. An analysis of focus groups confirmed that tight integration of the interventions with the EHR would be necessary to prompt clinicians to reconsider the working diagnosis in cases with elevated diagnostic error (DE) risk or uncertainty. Potential implementation barriers identified included alert fatigue and distrust of the risk algorithm (DSC); time constraints, redundancies, and concerns about disclosing uncertainty to patients (DTO); and patient disagreement with the care team's diagnosis (PDQ).
AHRQ-funded; HS026613.
Citation: Garber A, Garabedian P, Wu L .
Developing, pilot testing, and refining requirements for 3 EHR-integrated interventions to improve diagnostic safety in acute care: a user-centered approach.
JAMIA Open 2023 Jul; 6(2):ooad031. doi: 10.1093/jamiaopen/ooad031..
Keywords: Electronic Health Records (EHRs), Health Information Technology (HIT), Diagnostic Safety and Quality, Patient Safety
Bradford A, Goeschel C, Shofer M
AHRQ Author: Shofer M
Five new ways to advance diagnostic safety in your clinical practice.
This AHRQ-authored article describes new resources that clinicians can use to advance diagnostic safety and prevent errors. The new AHRQ-funded resources include Calibrate Dx, Measure Dx, Safer Dx Checklist, TeamSTEPPS for Diagnostic Improvements, and the Toolkit for Engaging Patients to Improve Diagnostic Safety. A table is provided which describes the resource, gives an example or strategy or practice change, and describes the audience for the resource. Recommendations are also given to help clinicians reduce barriers to diagnostic safety including: 1) Start small and focused; 2) Align with other high-priority initiatives; 3) Start with the resources you have; and 4) Consider how diagnostic safety work can enhance missions other than clinical care.
AHRQ-authored.
Citation: Bradford A, Goeschel C, Shofer M .
Five new ways to advance diagnostic safety in your clinical practice.
Am Fam Physician 2023 Jul; 108(1):14-16..
Keywords: Diagnostic Safety and Quality, Patient Safety
Petragallo R, Bertram P, Halvorsen P
Development and multi-institutional validation of a convolutional neural network to detect vertebral body mis-alignments in 2D x-ray setup images.
In image-guided radiotherapy (IGRT), lack of correct alignment to the vertebral body continues to be a rare but serious risk to patient safety. The researchers propose that an automated image-review algorithm be included in the IGRT process as an interlock to detect off-by-one vertebral body errors. The purpose of this study was to describe the development and validation of a convolutional neural network (CNN)-based approach for an automated image-review algorithm using patient image data from a planar stereoscopic x-ray IGRT system. The researchers collected X-rays and digitally reconstructed radiographs (DRRs) from 429 spine radiotherapy patients treated using a stereoscopic x-ray image guidance system. True-negative, "no-error" cases were established using clinically-applied, physician approved alignments. "Off-by-one vertebral body" errors were simulated by translating DRRs along the spinal column using a semi-automated method. A leave-one-institution-out method was utilized to estimate the accuracy of the model on data from unseen institutions as follows: every image from five of the institutions was used to train a CNN model from scratch. The size of the resulting training set ranged from 5700 to 9372 images, and was dependent on which five institutions had contributed data. The training set was randomized and split using a 75/25 split into the final training/ validation sets. X-ray/ DRR image pairs and the related labels of "no-error" or "shift" were used as the model input. Accuracy of the model was assessed utilizing images from the sixth institution, which was omitted from the training phase. This test set ranged from 180 to 3852 images, again depending on which institution had been left out of the training phase. The trained model was utilized to categorize the images from the test set as either "no-error" or "shifted", and the model predictions were compared to the ground truth labels to evaluate model accuracy. This process was repeated until the images of each institution had been utilized as the testing dataset. The study found that when the six models were utilized to categorize unseen image pairs from the institution omitted during training, the resulting receiver operating characteristic area under the curve values ranged from 0.976 to 0.998.
AHRQ-funded; HS026486.
Citation: Petragallo R, Bertram P, Halvorsen P .
Development and multi-institutional validation of a convolutional neural network to detect vertebral body mis-alignments in 2D x-ray setup images.
Med Phys 2023 May; 50(5):2662-71. doi: 10.1002/mp.16359..
Keywords: Imaging, Patient Safety, Diagnostic Safety and Quality
Bell SK, Bourgeois F, Dong J
Patient identification of diagnostic safety blindspots and participation in "good catches" through shared visit notes.
The goal of this study was to investigate whether sharing clinical notes with patients supported identification of potential breakdowns in the diagnostic process that might be difficult for clinical staff to observe -- "diagnostic safety blindspots." Researchers analyzed patient-reported ambulatory documentation errors among patients at 3 U.S. healthcare centers. Older, female, unemployed, disabled, or sicker patients, or patients who worked in healthcare, were more likely to identify blindspots; patients who self-identified as Black, Asian, multiple races and those with less formal education as well as those who deferred decision-making to their providers were less likely to report blindspots. The researchers concluded that patients who read notes have unique insight about potential errors in their medical records and that organizations should encourage patient review of notes and create systems to track patient-reported blindspots.
AHRQ-funded; HS027367.
Citation: Bell SK, Bourgeois F, Dong J .
Patient identification of diagnostic safety blindspots and participation in "good catches" through shared visit notes.
Milbank Q 2022 Dec; 100(4):1121-65. doi: 10.1111/1468-0009.12593..
Keywords: Diagnostic Safety and Quality, Patient Safety, Electronic Health Records (EHRs), Health Information Technology (HIT)
Luximon DC, Ritter T, Fields E
Development and interinstitutional validation of an automatic vertebral-body misalignment error detector for cone-beam CT-guided radiotherapy.
The purpose of this study was to develop an automatic error detection algorithm that uses a three-branch convolutional neural network error detection model (EDM) to detect off-by-one vertebral-body misalignments using planning computed tomography (CT) images and setup CBCT images. The researchers collected algorithm training and test data from 480 patients undergoing radiotherapy treatment at two radiotherapy clinics. One model (EDM(1) ) was trained solely on data from institution 1. EDM(1) was further trained on a dataset from institution 2 to produce a fine-tuned model, EDM(2) . Another model, EDM(3), was trained using a training dataset composed of data from both institutions. The study found that when applied to the combined test set, EDM(1) , EDM(2) , and EDM(3) resulted in an area under curve of 99.5%, 99.4%, and 99.5%, respectively. EDM(1) achieved a sensitivity of 96% and 88% on Institution 1 and Institution 2 test set, respectively. EDM(2) obtained a sensitivity of 95% on each institution's test set. EDM(3) achieved a sensitivity of 95% and 88% on Institution 1 and Institution 2 test set, respectively. The researchers concluded that in CBCT-guided radiotherapy, the proposed algorithm demonstrated accuracy in identifying off-by-one vertebral-body misalignments that was sufficiently high enough to justify implementation in practice.
AHRQ-funded; HS026486.
Citation: Luximon DC, Ritter T, Fields E .
Development and interinstitutional validation of an automatic vertebral-body misalignment error detector for cone-beam CT-guided radiotherapy.
Med Phys 2022 Oct;49(10):6410-23. doi: 10.1002/mp.15927..
Keywords: Imaging, Diagnostic Safety and Quality, Medical Errors, Patient Safety
Shafer GJ, Singh H, Thomas EJ
Frequency of diagnostic errors in the neonatal intensive care unit: a retrospective cohort study.
The objective of this study was to determine the frequency and etiology of diagnostic errors during the first 7 days of admission for inborn neonatal intensive care unit (NICU) patients. The "Safer Dx NICU Instrument" was used to review electronic health records. The reviewers discovered that the frequency of diagnostic error in inborn NICU patients during the first 7 days of admission was 6.2%.
AHRQ-funded; HS027363.
Citation: Shafer GJ, Singh H, Thomas EJ .
Frequency of diagnostic errors in the neonatal intensive care unit: a retrospective cohort study.
J Perinatol 2022 Oct;42(10):1312-18. doi: 10.1038/s41372-022-01359-9..
Keywords: Newborns/Infants, Intensive Care Unit (ICU), Critical Care, Diagnostic Safety and Quality, Medical Errors, Adverse Events, Patient Safety, Electronic Health Records (EHRs), Health Information Technology (HIT)
Bradford A, Shofer M, Singh H
AHRQ Author: Shofer M, Singh H
Measure Dx: implementing pathways to discover and learn from diagnostic errors.
This paper discusses Measure Dx, a new AHRQ resource that translates knowledge from diagnostic measurement research into actionable recommendations. This resource guides healthcare organizations to detect, analyze, and learn from diagnostic safety events as part of a continuous learning and feedback cycle. The goal of Measure Dx is to advance new frontiers in reducing preventable diagnostic harm to patients.
AHRQ-authored; AHRQ-funded; 233201500022I; HS027363.
Citation: Bradford A, Shofer M, Singh H .
Measure Dx: implementing pathways to discover and learn from diagnostic errors.
Int J Qual Health Care 2022 Sep 10;34(3). doi: 10.1093/intqhc/mzac068..
Keywords: Diagnostic Safety and Quality, Patient Safety, Quality Improvement, Quality of Care, Electronic Health Records (EHRs), Health Information Technology (HIT), Health Systems, Learning Health Systems
Bradford A, Shahid U, Schiff GD
AHRQ Author: DiStabile P, Timashenka A, Jalal H, and Brady PJ
Development and usability testing of the Agency for Healthcare Research and Quality common formats to capture diagnostic safety events.
The purpose of this study was to conduct a usability assessment of the Agency for Healthcare Research and Quality (AHRQ) Common Formats for Event Reporting for Diagnostic Safety Events (CFER-DS) to assist in informing future revisions and implementation. The researchers recruited quality and safety personnel from 8 U.S. healthcare organizations and invited them to use the CFER-DS to simulate reporting and then provide written and verbal qualitative feedback. The study found that feedback about item clarity and content coverage was generally positive, but that reporter burden was a potential concern. Participants also identified opportunities to improve the CFER-DS, including clarifying several conceptual definitions, improving applicability across different care settings, and creating guidance to operationalize use of the tool.
AHRQ-authored; AHRQ-funded; HS027363, 233201500022I.
Citation: Bradford A, Shahid U, Schiff GD .
Development and usability testing of the Agency for Healthcare Research and Quality common formats to capture diagnostic safety events.
J Patient Saf 2022 Sep 1;18(6):521-25. doi: 10.1097/pts.0000000000001006..
Keywords: Diagnostic Safety and Quality, Patient Safety, Health Information Technology (HIT), Adverse Events
Giardina TD, Choi DT, Upadhyay DK
Inviting patients to identify diagnostic concerns through structured evaluation of their online visit notes.
This study’s objective was to test if patients can identify concerns about their diagnosis through structured evaluation of their online visit notes in an electronic health record (EHR) system. Patients aged 18-85 years in a large integrated health system who actively used the patient portal were invited to respond to an online questionnaire if an EHR algorithm detected any recent visit following an initial primary care consultation. The authors developed and tested an instrument (Safer Dx Patient Instrument) to help patients identify concerns related to the diagnostic process based on notes review and recall of recent “at-risk” visits. The algorithm identified 1282 eligible patients, of whom 486 responded. Of the 418 patients included in the analysis, 51 patients (12.2%) identified a diagnostic concern. Patients were more likely to report a concern if they disagreed with statements "The care plan the provider developed for me addressed all my medical concerns", "I trust the provider that I saw during my visit" and agreed with the statement "I did not have a good feeling about my visit".
AHRQ-funded; HS027363; HS025474.
Citation: Giardina TD, Choi DT, Upadhyay DK .
Inviting patients to identify diagnostic concerns through structured evaluation of their online visit notes.
J Am Med Inform Assoc 2022 May 11;29(6):1091-100. doi: 10.1093/jamia/ocac036..
Keywords: Diagnostic Safety and Quality, Electronic Health Records (EHRs), Health Information Technology (HIT), Patient Experience, Patient Safety
Lacson R, Khorasani R, Fiumara K
Collaborative case review: a systems-based approach to patient safety event investigation and analysis.
The objectives of this study were to assess a system-based approach to event investigation and analysis--collaborative case reviews (CCRs)--and to measure impact of clinical specialty on strength of action items prescribed. The institutional review board-approved study describes the program, including a percentage of CCR from an institutional Electronic Safety Reporting System. Findings showed that an integrated multispecialty CCR co-led by the radiology department and an institutional patient safety program was associated with a higher proportion of CCR, stronger action items, and higher action item completion rate versus other hospital departments.
AHRQ-funded; HS024722.
Citation: Lacson R, Khorasani R, Fiumara K .
Collaborative case review: a systems-based approach to patient safety event investigation and analysis.
J Patient Saf 2022 Mar 1;18(2):e522-e27. doi: 10.1097/pts.0000000000000857..
Keywords: Patient Safety, Adverse Events, Diagnostic Safety and Quality, Imaging
Marshall TL, Rinke ML, Olson APJ
Diagnostic error in pediatrics: a narrative review.
This narrative review focuses on the relative paucity of large, high-quality studies of diagnostic errors and what is known at present about the incident and epidemiology as well as the established research for identifying, evaluating, and reducing diagnostic errors. The authors propose several key research questions aimed at addressing persistent gaps in the pediatric diagnostic error literature. The authors state that additional research is needed to better establish the epidemiology of diagnostic errors in pediatrics, including identifying high-risk clinical scenarios, patient populations, and groups of diagnoses.
AHRQ-funded; HS023827; HS026644.
Citation: Marshall TL, Rinke ML, Olson APJ .
Diagnostic error in pediatrics: a narrative review.
Pediatrics 2022 Mar;149(Suppl 3). doi: 10.1542/peds.2020-045948D..
Keywords: Children/Adolescents, Diagnostic Safety and Quality, Patient Safety, Medical Errors
Zimolzak AJ, Shahid U, Giardina TD
Why test results are still getting "lost" to follow-up: a qualitative study of implementation gaps.
Lack of timely follow-up of abnormal test results is common and has been implicated in missed or delayed diagnosis, resulting in potential for patient harm. As part of a larger project to implement change strategies to improve follow-up of diagnostic test results, this study sought to identify specifically where implementation gaps exist, as well as possible solutions identified by front-line staff.
AHRQ-funded; HS27363.
Citation: Zimolzak AJ, Shahid U, Giardina TD .
Why test results are still getting "lost" to follow-up: a qualitative study of implementation gaps.
J Gen Intern Med 2022 Jan;37(1):137-44. doi: 10.1007/s11606-021-06772-y..
Keywords: Diagnostic Safety and Quality, Patient Safety, Quality Improvement, Quality of Care
Giardina TD, Korukonda S, Shahid U
Use of patient complaints to identify diagnosis-related safety concerns: a mixed-method evaluation.
This retrospective cohort study evaluated the use of patient complaint data to identify patient safety concerns related to diagnosis as an initial step to using this information to facilitate learning and improvement. Patient complaints submitted to the Geisinger healthcare system were reviewed with 2 cohorts from August to December 2017 (cohort 1) and January to June 2018 (cohort 2). The authors selected complaints more likely to be associated with diagnostic concerns in Geisinger’s existing complaint taxonomy. In cohort 1, 1865 complaint summaries were reviewed and 177 (9.5%) were identified as concerning. The review identified 39 diagnostic errors. In cohort 2, 2423 patient complaints were reviewed and 310 (12.8%) concerning reports were identified. A 10% sample contained give diagnostic errors. Most errors were categorized as “Clinical Care” issues.
AHRQ-funded; HS025474; HS027363.
Citation: Giardina TD, Korukonda S, Shahid U .
Use of patient complaints to identify diagnosis-related safety concerns: a mixed-method evaluation.
BMJ Qual Saf 2021 Dec;30(12):996-1001. doi: 10.1136/bmjqs-2020-011593..
Keywords: Diagnostic Safety and Quality, Patient Safety, Medical Errors, Adverse Events
Nehls N, Yap TS, Salant T
Systems engineering analysis of diagnostic referral closed-loop processes.
This systems engineering (SE) analysis of diagnostic referral closed-loop processes examines process logic, variation, reliability, and failures for completing diagnostic referrals originating in two primary care practices serving different demographics, using dermatology as an illustrating use case. Research has shown that there is a 65-73% failure rate in completing diagnostic referrals, which is a significant patient safety problem. An interdisciplinary team collaborated to understand processes of initiating and completing diagnostic referrals. Cross-functional process maps were developed through iterative group interviews with an urban community-based health center and a teaching practice within a large academic medical center. Results were used to conduct an engineering process analysis, assess variation between and within practices, and identify common failure modes and potential solutions.
AHRQ-funded; HS027282.
Citation: Nehls N, Yap TS, Salant T .
Systems engineering analysis of diagnostic referral closed-loop processes.
BMJ Open Qual 2021 Nov;10(4). doi: 10.1136/bmjoq-2021-001603..
Keywords: Diagnostic Safety and Quality, Primary Care, Patient Safety
Mahajan P, Pai CW, Cosby KS
Identifying trigger concepts to screen emergency department visits for diagnostic errors.
The diagnostic process is a vital component of safe and effective emergency department (ED) care. There are no standardized methods for identifying or reliably monitoring diagnostic errors in the ED, impeding efforts to enhance diagnostic safety. In this study, the investigators sought to identify trigger concepts to screen ED records for diagnostic errors and describe how they can be used as a measurement strategy to identify and reduce preventable diagnostic harm.
AHRQ-funded; HS024953; HS027363.
Citation: Mahajan P, Pai CW, Cosby KS .
Identifying trigger concepts to screen emergency department visits for diagnostic errors.
Diagnosis 2021 Aug 26;8(3):340-46. doi: 10.1515/dx-2020-0122..
Keywords: Emergency Department, Diagnostic Safety and Quality, Medical Errors, Adverse Events, Patient Safety
Cifra CL, Custer JW, Singh H
Diagnostic errors in pediatric critical care: a systematic review.
This study is a systematic review on the prevalence, impact, and contributing factors related to diagnostic errors in the PICU. A database search was done for literature up through December 2019. Using specific criteria, 396 abstracts were screened, and 17 studies were included. Fifteen of 17 studies had an observational research design. Autopsy studies showed a 10-23% rate of missed major diagnosis with 5-16% of the errors having a potential adverse impact on survival and would have changed care management. Retrospective record review studies reported varying rates of diagnostic error from 8% in a general PICU population to 12% among unexpected critical admissions. About a quarter of those patients were discussed at PICU morbidity and mortality conferences. Most misdiagnosed conditions were cardiovascular, infectious, congenital, or neurologic. System, cognitive, and both system and cognitive factors were associated with diagnostic error but there is limited information on the impact of misdiagnosis.
AHRQ-funded; HS026965.
Citation: Cifra CL, Custer JW, Singh H .
Diagnostic errors in pediatric critical care: a systematic review.
Pediatr Crit Care Med 2021 Aug;22(8):701-12. doi: 10.1097/pcc.0000000000002735..
Keywords: Children/Adolescents, Diagnostic Safety and Quality, Medical Errors, Adverse Events, Patient Safety, Intensive Care Unit (ICU), Critical Care