Evaluation of a Natural Language Processing Approach to Identify Diagnostic Errors and Analysis of Safety Learning System Case Review Data: Retrospective Cohort Study.

BACKGROUND: Diagnostic errors are an underappreciated cause of preventable mortality in hospitals and pose a risk for severe patient harm and increase hospital length of stay. OBJECTIVE: This study aims to explore the potential of machine learning and natural language processing techniques in improving diagnostic safety surveillance. We conducted a rigorous evaluation of the feasibility and potential to use electronic health records clinical notes and existing case review data. METHODS: Safety Learning System case review data from 1 large health system composed of 10 hospitals in the mid-Atlantic region of the United States from February 2016 to September 2021 were analyzed. The case review outcome included opportunities for improvement including diagnostic opportunities for improvement. To supplement case review data, electronic health record clinical notes were extracted and analyzed. A simple logistic regression model along with 3 forms of logistic regression models (ie, Least Absolute Shrinkage and Selection Operator, Ridge, and Elastic Net) with regularization functions was trained on this data to compare classification performances in classifying patients who experienced diagnostic errors during hospitalization. Further, statistical tests were conducted to find significant differences between female and male patients who experienced diagnostic errors. RESULTS: In total, 126 (7.4%) patients (of 1704) had been identified by case reviewers as having experienced at least 1 diagnostic error. Patients who had experienced diagnostic error were grouped by sex: 59 (7.1%) of the 830 women and 67 (7.7%) of the 874 men. Among the patients who experienced a diagnostic error, female patients were older (median 72, IQR 66-80 vs median 67, IQR 57-76; P=.02), had higher rates of being admitted through general or internal medicine (69.5% vs 47.8%; P=.01), lower rates of cardiovascular-related admitted diagnosis (11.9% vs 28.4%; P=.02), and lower rates of being admitted through neurology department (2.3% vs 13.4%; P=.04). The Ridge model achieved the highest area under the receiver operating characteristic curve (0.885), specificity (0.797), positive predictive value (PPV; 0.24), and F1-score (0.369) in classifying patients who were at higher risk of diagnostic errors among hospitalized patients. CONCLUSIONS: Our findings demonstrate that natural language processing can be a potential solution to more effectively identifying and selecting potential diagnostic error cases for review and therefore reducing the case review burden.

Accounting for taste: preferences mediate the relationship between documentation time and ambulatory physician burnout.

OBJECTIVES: Physician burnout in the US has reached crisis levels, with one source identified as extensive after-hours documentation work in the electronic health record (EHR). Evidence has illustrated that physician preferences for after-hours work vary, such that after-hours work may not be universally burdensome. Our objectives were to analyze variation in preferences for after-hours documentation and assess if preferences mediate the relationship between after-hours documentation time and burnout. MATERIALS AND METHODS: We combined EHR active use data capturing physicians' hourly documentation work with survey data capturing documentation preferences and burnout. Our sample included 318 ambulatory physicians at MedStar Health. We conducted a mediation analysis to estimate if and how preferences mediated the relationship between after-hours documentation time and burnout. Our primary outcome was physician-reported burnout. We measured preferences for after-hours documentation work via a novel survey instrument (Burden Scenarios Assessment). We measured after-hours documentation time in the EHR as the total active time respondents spent documenting between 7 pm and 3 am. RESULTS: Physician preferences varied, with completing clinical documentation after clinic hours while at home the scenario rated most burdensome (52.8% of physicians), followed by dealing with prior authorization (49.5% of physicians). In mediation analyses, preferences partially mediated the relationship between after-hours documentation time and burnout. DISCUSSION: Physician preferences regarding EHR-based work play an important role in the relationship between after-hours documentation time and burnout. CONCLUSION: Studies of EHR work and burnout should incorporate preferences, and operational leaders should assess preferences to better target interventions aimed at EHR-based contributors to burnout.

Diagnostic Excellence in the Context of Climate Change: A Review.

Climate change is leading to a rise in heat-related illnesses, vector-borne diseases, and numerous negative impacts on patients' physical and mental health outcomes. Concurrently, healthcare contributes about 4.6% of global greenhouse gas emissions. Low-value care, such as overtesting and overdiagnosis, contributes to unnecessary emissions. In this review, we describe diagnostic excellence in the context of climate change and focus on two topics. First, climate change is affecting health, leading to the emergence of certain diseases, some of which are new, while others are increasing in prevalence and/or becoming more widespread. These conditions will require timely and accurate diagnosis by clinicians who may not be used to diagnosing them. Second, diagnostic quality issues, such as overtesting and overdiagnosis, contribute to climate change through unnecessary emissions and waste and should be targeted for interventions. We also highlight implications for clinical practice, research, and policy. Our findings call for efforts to engage healthcare professionals and policymakers in understanding the urgent implications for diagnosis in the context of climate change and reducing global greenhouse gas emissions to enhance both patient and planetary outcomes.

Does nurse use of a standardized flowsheet to document communication with advanced providers provide a mechanism to detect pulse oximetry failures? A retrospective study of electronic health record data.

BACKGROUND: Pulse oximetry guides clinical decisions, yet does not uniformly identify hypoxemia. We hypothesized that nursing documentation of notifying providers, facilitated by a standardized flowsheet for documenting communication to providers (physicians, nurse practitioners, and physician assistants), may increase when hypoxemia is present, but undetected by the pulse oximeter, in events termed "occult hypoxemia." OBJECTIVE: To compare nurse documentation of provider notification in the 4 h preceding cases of occult hypoxemia, normal oxygenation, and evident hypoxemia confirmed by an arterial blood gas reading. METHODS: We conducted a retrospective study using electronic health record data from patients with COVID-19 at five hospitals in a healthcare system with paired SpO2 and SaO2 readings (measurements within 10 min of oxygen saturation levels in arterial blood, SaO2, and by pulse oximetry, SpO2). We applied multivariate logistic regression to assess if having any nursing documentation of provider notification in the 4 h prior to a paired reading confirming occult hypoxemia was more likely compared to a paired reading confirming normal oxygen status, adjusting for characteristics significantly associated with nursing documentation. We applied conditional logistic regression to assess if having any nursing documentation of provider notification was more likely in the 4-hour window preceding a paired reading compared to the 4-hour window 24 h earlier separately for occult hypoxemia, visible hypoxemia, and normal oxygenation. RESULTS: There were data from 1910 patients hospitalized with COVID-19 who had 44,972 paired readings and an average of 26.5 (34.5) nursing documentation of provider notification events. The mean age was 63.4 (16.2). Almost half (866/1910, 45.3 %) were White, 701 (36.7 %) were Black, and 239 (12.5 %) were Hispanic. Having any nursing documentation of provider notification was 46 % more common in the 4 h before an occult hypoxemia paired reading compared to a normal oxygen status paired reading (OR 1.46, 95 % CI: 1.28-1.67). Comparing the 4 h immediately before the reading to the 4 h one day preceding the paired reading, there was a higher likelihood of having any nursing documentation of provider notification for both evident (OR 1.45, 95 % CI 1.24-1.68) and occult paired readings (OR 1.26, 95 % CI 1.04-1.53). CONCLUSION: This study finds that nursing documentation of provider notification significantly increases prior to confirmed occult hypoxemia, which has potential in proactively identifying occult hypoxemia and other clinical issues. There is potential value to encouraging standardized documentation of nurse concern, including communication to providers, to facilitate its inclusion in clinical decision-making.

New insights on a recurring theme: A secondary analysis of nurse turnover using the National Sample Survey of Registered Nurses.

BACKGROUND: Registered nurse (RN) turnover is a recurring phenomenon that accelerated during COVID-19 and heightened concerns about contributing factors. PURPOSE: Provide baseline RN turnover data to which pandemic and future RN workforce turnover behaviors can be compared. METHODS: A cross-sectional, secondary analysis of RN turnover using U.S. National Sample Survey of Registered Nurses 2018 data. Responses from 41,428 RNs (weighted N = 3,092,991) across the United States were analyzed. Sociodemographic, professional, employment, and economic data and weighting techniques were used to model prepandemic RN turnover behaviors. DISCUSSION: About 17% of the sample reported a job turnover, with 6.2% reporting internal and 10.8% reporting external turnover. The factors common across both internal and external turnover experiences included education, employment settings, and years of nursing experience. CONCLUSIONS: Baseline RN turnover data can help employers and policymakers understand new and recurring nursing workforce trends and develop targeted actions to reduce nurse turnover.

Where are the critical care nurses? A statewide analysis of actively practicing nurses' transitions out of the clinical area.

BACKGROUND: Critical care nurse shortages and burnout have spurred interest in the adequacy of nursing supply in the United States. Nurses can move between clinical areas without  additional education or licensure. PURPOSE: To identify transitions that critical care nurses make into non-critical care areas, and examine the prevalence and characteristics associated with those transitions. METHODS: Secondary analysis of state licensure data from 2001-2013. DISCUSSION: More than 75% of nurses (n = 8,408) left critical care in the state, with 44% making clinical area transitions within 5 years. Critical care nurses transitioned into emergency, peri-operative, and cardiology areas. Those observed in recession years were less likely to make transitions; female and nurses with masters/doctorate degrees were more likely. CONCLUSION: This study used state workforce data to examine transitions out of critical care nursing. Findings can inform policies to retain and recruit nurses back into critical care, especially during public health crises.

Outpatient nurse staffing relationship with organizational, nurse and patient outcomes: A scoping review.

Background: Nurses are an integral part of outpatient healthcare settings and are needed to provide effective patient care. Ample research and reviews have been done on nurse staffing in inpatient settings relationship with a variety of organizational, nurse and patient outcomes, however there is no review of outpatient nurse staffing relationship with organizational, nurse and patient outcomes. Objectives: The purpose of this paper is to present a scoping review that evaluates the state of the literature on relationships among nurse staffing and organizational, nurse and patient outcomes in the outpatient setting. Methods: The review used PRISMA guidelines for scoping reviews. The search focused on nurse staffing and organizational outcome in outpatient settings and synonyms for those terms. PubMed, Ebscohost CINAHL, and Ebscohost Global Health were searched. Articles were included if they measured nurse staffing relationship with any organizational, nurse and patient outcome in an outpatient setting. Extraction was completed in a matrix first then charted into synthesis tables. Results: Thirty-seven studies were included in the review. Nurse staffing was measured in the literature by perceived staffing adequacy, types of healthcare workers staffed, full-time equivalents, nurse vacancies, proportion of nurses to total staff, agency or float nurse use, presence of nurse on the healthcare team and nurse to patient ratios. Nurse staffing of a variety of measures was associated with better patient outcomes, lower costs, and lower nurse turnover. Only one study of the 37 included did not show a positive outcome of better nurse staffing, which showed that increased nurse staffing was associated with less patient engagement in psychotherapy. Conclusions: Outpatient care setting stakeholders and policy makers should consider improving nurse staffing, as stronger nurse staffing is associated with better patient outcomes lower costs and less nurse turnover. In addition, better staffing helps improve nurses' attitudes towards their job and increase job satisfaction. Most of the studies included in this review only focused on the staffing measure of perceived staffing adequacy. While perceived staffing adequacy is a useful measure of nurse staffing able to capture nurses' perception, it should not be used in isolation and more researchers should focus on gaps in outpatient nurse staffing with more objective measures such as fulltime equivalents. Tweetable abstract: A 37 article scoping review on nurse staffing in outpatient care found that stronger staffing was linked with better patient outcomes, lower costs, and less turnover.

Supporting the Dynamic Careers of Licensed Practical Nurses: A Strategy to Bolster the Long-Term Care Nurse Workforce.

As the U.S. population ages and the demand for long-term care increases, an insufficient number of licensed practical nurses (LPNs) is expected in the nursing workforce. Understanding the characteristics of LPN participation in the workforce is essential to address this challenge. Drawing on the theory of boundaryless careers, the authors examined longitudinal employment data from LPNs in North Carolina and described patterns in LPN licensure and career transitions. Two career patterns were identified: (a) the continuous career, in which LPNs were licensed in 75% or more of the years they were eligible to be licensed and (b) the intermittent career, in which lapses in licensure occurred. Findings indicated that LPNs who made job transitions were more likely to demonstrate continuous careers, as were Black LPNs. These findings suggest the importance of organizational support for LPN career transitions and support for diversity in the LPN workforce.