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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 6 of 6 Research Studies DisplayedSchnipper 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
McLoone M, McNamara M, Jennings MA
Observing sources of system resilience using in situ alarm simulations.
The authors conducted in situ simulations of a hypoxemic-event alarm in medical/surgical and intensive care units at a tertiary care pediatric hospital to identify sources of resilience in alarm systems. They collected data on response timing, made observations of the environment, and conducted postsimulation debrief interviews. Four primary means of successful alarm responses were mapped to domains of the Systems Engineering Initiative for Patient Safety framework to guide future alarm system design and improvement.
AHRQ-funded; HS026620; HS028682.
Citation: McLoone M, McNamara M, Jennings MA .
Observing sources of system resilience using in situ alarm simulations.
J Hosp Med 2023 Nov; 18(11):994-98. doi: 10.1002/jhm.13217..
Keywords: Patient Safety, Hospitals
Chen VW, Chidi AP, Dong Y
Risk-adjusted cumulative sum for early detection of hospitals with excess perioperative mortality.
This study’s goal was to compare the risk-adjusted cumulative sum (CUSUM) with episodic evaluation for early detection of hospitals with excess perioperative mortality. The study cohort included 697,566 patients treated at 104 Veterans’ Affairs hospitals across 24 quarters with a mean age of 60.9 years and 91.4% male. These patients underwent a noncardiac operation at a Veterans Affairs hospital, had a record in the Veterans Affairs Surgical Quality Improvement Program (January 1, 2011, through December 31, 2016), and were aged 18 years or older. For each hospital, the median number of quarters detected with observed to expected ratios, at least 1 CUSUM signal, and more than 1 CUSUM signal was 2 quarters (IQR, 1-4 quarters), 8 quarters (IQR, 4-11 quarters), and 3 quarters (IQR, 1-4 quarters). Outlier hospitals were identified 33.3% of the time (830 quarters) with at least 1 CUSUM signal within a quarter, 12.5% (311 quarters) with more than 1 CUSUM signal, and 11.0% (274 quarters) with observed to expected ratios at the end of the quarter. The CUSUM detection occurred a median of 49 days (IQR, 25-63 days) before observed to expected ratio reporting (1 signal, 35 days [IQR, 17-54 days]; 2 signals, 49 days [IQR, 26-61 days]; 3 signals, 58 days [IQR, 44-69 days]; ≥4 signals, 49 days [IQR, 42-69 days]. Of 274 hospital quarters detected with observed to expected ratios, 72.6% were concurrently detected by at least 1 CUSUM signal vs 42.7% by more than 1 CUSUM signal. There was a dose-response relationship between the number of CUSUM signals in a quarter and the median observed to expected ratio (0 signals, 0.63; 1 signal, 1.28; 2 signals, 1.58; 3 signals, 2.08; ≥4 signals, 2.49).
AHRQ-funded; HS013853.
Citation: Chen VW, Chidi AP, Dong Y .
Risk-adjusted cumulative sum for early detection of hospitals with excess perioperative mortality.
JAMA Surg 2023 Nov; 158(11):1176-83. doi: 10.1001/jamasurg.2023.3673..
Keywords: Quality Improvement, Surgery, Hospitals, Patient Safety, Mortality, Quality of Care
Thom KA, Rock C, Robinson GL
Direct gloving vs hand hygiene before donning gloves in adherence to hospital infection control practices: a cluster randomized clinical trial.
The purpose of this study was to assess the effectiveness of a direct-gloving policy on adherence to infection prevention control practices in a hospital setting. In this study, hospital units were randomly assigned to either the intervention (hand hygiene not required before putting on gloves) or to usual care (hand hygiene required prior to before putting on nonsterile gloves). The primary study outcome was adherence to the expected practice upon room entry and room exit. Thirteen hospital units participated in the trial, and 3,790 health care personnel (HCP) were observed. The study found that adherence to expected practice was higher in the 6 units with the direct-gloving intervention than in the 7 usual care units even when controlling for baseline hand hygiene rates, unit type, and universal gloving policies. The intervention had no effect on hand hygiene adherence measured at entry to non-contact precautions rooms or at room exit. The intervention was related with increased total bacteria colony counts and increased detection of pathogenic bacteria on gloves in the ED and reduced colony counts in pediatrics units, with no change in either total colony count for adult intensive care unit or presence of pathogenic bacteria for adult intensive care unit.
AHRQ-funded; HS024108.
Citation: Thom KA, Rock C, Robinson GL .
Direct gloving vs hand hygiene before donning gloves in adherence to hospital infection control practices: a cluster randomized clinical trial.
JAMA Netw Open 2023 Oct 2; 6(10):e2336758. doi: 10.1001/jamanetworkopen.2023.36758..
Keywords: Hospitals, Patient Safety, Guidelines, Healthcare-Associated Infections (HAIs)
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
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