Stigmatizing Language, Patient Demographics, and Errors in the Diagnostic Process.

This cohort study assesses the association between stigmatizing language, demographic characteristics, and errors in the diagnostic process among hospitalized adults.

Diagnostic Errors in Hospitalized Adults Who Died or Were Transferred to Intensive Care.

Importance: Diagnostic errors contribute to patient harm, though few data exist to describe their prevalence or underlying causes among medical inpatients. Objective: To determine the prevalence, underlying cause, and harms of diagnostic errors among hospitalized adults transferred to an intensive care unit (ICU) or who died. Design, Setting, and Participants: Retrospective cohort study conducted at 29 academic medical centers in the US in a random sample of adults hospitalized with general medical conditions and who were transferred to an ICU, died, or both from January 1 to December 31, 2019. Each record was reviewed by 2 trained clinicians to determine whether a diagnostic error occurred (ie, missed or delayed diagnosis), identify diagnostic process faults, and classify harms. Multivariable models estimated association between process faults and diagnostic error. Opportunity for diagnostic error reduction associated with each fault was estimated using the adjusted proportion attributable fraction (aPAF). Data analysis was performed from April through September 2023. Main Outcomes and Measures: Whether or not a diagnostic error took place, the frequency of underlying causes of errors, and harms associated with those errors. Results: Of 2428 patient records at 29 hospitals that underwent review (mean [SD] patient age, 63.9 [17.0] years; 1107 [45.6%] female and 1321 male individuals [54.4%]), 550 patients (23.0%; 95% CI, 20.9%-25.3%) had experienced a diagnostic error. Errors were judged to have contributed to temporary harm, permanent harm, or death in 436 patients (17.8%; 95% CI, 15.9%-19.8%); among the 1863 patients who died, diagnostic error was judged to have contributed to death in 121 (6.6%; 95% CI, 5.3%-8.2%). In multivariable models examining process faults associated with any diagnostic error, patient assessment problems (aPAF, 21.4%; 95% CI, 16.4%-26.4%) and problems with test ordering and interpretation (aPAF, 19.9%; 95% CI, 14.7%-25.1%) had the highest opportunity to reduce diagnostic errors; similar ranking was seen in multivariable models examining harmful diagnostic errors. Conclusions and Relevance: In this cohort study, diagnostic errors in hospitalized adults who died or were transferred to the ICU were common and associated with patient harm. Problems with choosing and interpreting tests and the processes involved with clinician assessment are high-priority areas for improvement efforts.

Prevalence and Causes of Diagnostic Errors in Hospitalized Patients Under Investigation for COVID-19.

BACKGROUND: The COVID-19 pandemic required clinicians to care for a disease with evolving characteristics while also adhering to care changes (e.g., physical distancing practices) that might lead to diagnostic errors (DEs). OBJECTIVE: To determine the frequency of DEs and their causes among patients hospitalized under investigation (PUI) for COVID-19. DESIGN: Retrospective cohort. SETTING: Eight medical centers affiliated with the Hospital Medicine ReEngineering Network (HOMERuN). TARGET POPULATION: Adults hospitalized under investigation (PUI) for COVID-19 infection between February and July 2020. MEASUREMENTS: We randomly selected up to 8 cases per site per month for review, with each case reviewed by two clinicians to determine whether a DE (defined as a missed or delayed diagnosis) occurred, and whether any diagnostic process faults took place. We used bivariable statistics to compare patients with and without DE and multivariable models to determine which process faults or patient factors were associated with DEs. RESULTS: Two hundred and fifty-seven patient charts underwent review, of which 36 (14%) had a diagnostic error. Patients with and without DE were statistically similar in terms of socioeconomic factors, comorbidities, risk factors for COVID-19, and COVID-19 test turnaround time and eventual positivity. Most common diagnostic process faults contributing to DE were problems with clinical assessment, testing choices, history taking, and physical examination (all p < 0.01). Diagnostic process faults associated with policies and procedures related to COVID-19 were not associated with DE risk. Fourteen patients (35.9% of patients with errors and 5.4% overall) suffered harm or death due to diagnostic error. LIMITATIONS: Results are limited by available documentation and do not capture communication between providers and patients. CONCLUSION: Among PUI patients, DEs were common and not associated with pandemic-related care changes, suggesting the importance of more general diagnostic process gaps in error propagation.

Characterizing patients hospitalized without an acute care indication: A retrospective cohort study.

BACKGROUND: Hospitalizations by patients who do not meet acute inpatient criteria are common and overburden healthcare systems. Studies have characterized these alternate levels of care (ALC) but have not delineated prolonged (pALC) versus short ALC (sALC) stays. OBJECTIVE: To descriptively compare pALC and sALC hospitalizations-groups we hypothesize have unique needs. DESIGNS, SETTINGS, AND PARTICIPANTS: A retrospective study of hospitalizations from March-April 2018 at an academic safety-net hospital. MAIN OUTCOME AND MEASURES: Levels of care for pALC (>3 days) and sALC (1-3 days) were determined using InterQual©, an industry standard utilization review tool for determining the clinical appropriateness of hospitalization. We examined sociodemographic and clinical characteristics. RESULTS: Of 2365 hospitalizations, 215 (9.1%) were pALC, 277 (11.7%) were sALC, and 1873 (79.2%) had no ALC days. There were 17,683 hospital days included, and 28.3% (n = 5006) were considered ALC. Compared to patients with sALC, those with pALC were older and more likely to be publicly insured, experience homelessness, and have substance use or psychiatric comorbidities. Patients with pALC were more likely to be admitted for care meeting inpatient criteria (89.3% vs. 66.8%, p < .001), had significantly more ALC days (median 8 vs. 1 day, p < .001), and were less likely to be discharged to the community (p < .001). CONCLUSIONS: Patients with prolonged ALC stays were more likely to be admitted for acute care, had greater psychosocial complexity, significantly longer lengths of stay, and unique discharge needs. Given the complexity and needs for hospitalizations with pALC days, intensive interdisciplinary coordination and resource mobilization are necessary.

Time to ACT: launching an Addiction Care Team (ACT) in an urban safety-net health system.

Across the USA, morbidity and mortality from substance use are rising as reflected by increases in acute care hospitalisations for substance use complications and substance-related deaths. Patients with substance use disorders (SUD) have long and costly hospitalisations and higher readmission rates compared to those without SUD. Hospitalisation presents an opportunity to diagnose and treat individuals with SUD and connect them to ongoing care. However, SUD care often remains unaddressed by hospital providers due to lack of a systems approach and addiction medicine knowledge, and is compounded by stigma. We present a blueprint to launching an interprofessional inpatient addiction care team embedded in the hospital medicine division of an urban, safety-net integrated health system. We describe key factors for successful implementation including: (1) demonstrating the scope and impact of SUD in our health system via a needs assessment; (2) aligning improvement areas with health system leadership priorities; (3) involving executive leadership to create goal and initiative alignment; and (4) obtaining seed funding for a pilot programme from our Medicaid health plan partner. We also present challenges and lessons learnt.

Prevalence and characterisation of diagnostic error among 7-day all-cause hospital medicine readmissions: a retrospective cohort study.

BACKGROUND: The prevalence and aetiology of diagnostic error among hospitalised adults is unknown, though likely contributes to patient morbidity and mortality. We aim to identify and characterise the prevalence and types of diagnostic error among patients readmitted within 7 days of hospital discharge. METHODS: Retrospective cohort study at a single urban academic hospital examining adult patients discharged from the medical service and readmitted to the same hospital within 7 days between January and December 2018. The primary outcome was diagnostic error presence, identified through two-physician adjudication using validated tools. Secondary outcomes included severity of error impact and characterisation of diagnostic process failures contributing to error. RESULTS: There were 391 cases of unplanned 7-day readmission (5.2% of 7507 discharges), of which 376 (96.2%) were reviewed. Twenty-one (5.6%) admissions were found to contain at least one diagnostic error during the index admission. The most common problem areas in the diagnostic process included failure to order needed test(s) (n=11, 52.4%), erroneous clinician interpretation of test(s) (n=10, 47.6%) and failure to consider the correct diagnosis (n=8, 38.1%). Nineteen (90.5%) of the diagnostic errors resulted in moderate clinical impact, primarily due to short-term morbidity or contribution to the readmission. CONCLUSION: The prevalence of diagnostic error among 7-day medical readmissions was 5.6%. The most common drivers of diagnostic error were related to clinician diagnostic reasoning. Efforts to reduce diagnostic error should include strategies to augment diagnostic reasoning and improve clinician decision-making around diagnostic studies.

Acute Care for Patients Who Are Incarcerated: A Review.

IMPORTANCE: The United States has the world's highest rate of incarceration. Clinicians practicing outside of correctional facilities receive little dedicated training in the care of patients who are incarcerated, are unaware of guidelines for the treatment of patients in custody, and practice in health care systems with varying policies toward these patients. This review considers legal precedents for care of individuals who are incarcerated, frequently encountered terminology, characteristics of hospitalized incarcerated patients, considerations for clinical management, and challenges during transitions of care. OBSERVATIONS: The Eighth Amendment of the US Constitution mandates basic health care for incarcerated individuals within or outside of dedicated correctional facilities. Incarcerated patients in the acute hospital setting are predominantly young men who have received trauma-related admitting diagnoses. Hospital practices pertaining to privacy, physical restraint, discharge counseling, and surrogate decision-making are affected by a patient's incarcerated status under state or federal law, institutional policy, and individual health care professional practice. Transitions of care necessitate consideration of the disparate medical resources of correctional facilities as well as awareness of transitions unique to incarcerated individuals, such as compassionate release. CONCLUSIONS AND RELEVANCE: Patients who are incarcerated have a protected right to health care but may experience exceptions to physical comfort, health privacy, and informed decision-making in the acute care setting. Research on the management of issues associated with hospitalized incarcerated patients is limited and primarily focuses on the care of pregnant women, a small portion of all hospitalized incarcerated individuals. Clinicians and health care facilities should work toward creating evidence-based and legally supported guidelines for the care of incarcerated individuals in the acute care setting that balance the rights of the patient, responsibilities of the clinician, and safety mandates of the institution and law enforcement.

Next-generation audit and feedback for inpatient quality improvement using electronic health record data: a cluster randomised controlled trial.

BACKGROUND: Audit and feedback improves clinical care by highlighting the gap between current and ideal practice. We combined best practices of audit and feedback with continuously generated electronic health record data to improve performance on quality metrics in an inpatient setting. METHODS: We conducted a cluster randomised control trial comparing intensive audit and feedback with usual audit and feedback from February 2016 to June 2016. The study subjects were internal medicine teams on the teaching service at an urban tertiary care hospital. Teams in the intensive feedback arm received access to a daily-updated team-based data dashboard as well as weekly inperson review of performance data ('STAT rounds'). The usual feedback arm received ongoing twice-monthly emails with graphical depictions of team performance on selected quality metrics. The primary outcome was performance on a composite discharge metric (Discharge Mix Index, 'DMI'). A washout period occurred at the end of the trial (from May through June 2016) during which STAT rounds were removed from the intensive feedback arm. RESULTS: A total of 40 medicine teams participated in the trial. During the intervention period, the primary outcome of completion of the DMI was achieved on 79.3% (426/537) of patients in the intervention group compared with 63.2% (326/516) in the control group (P<0.0001). During the washout period, there was no significant difference in performance between the intensive and usual feedback groups. CONCLUSION: Intensive audit and feedback using timely data and STAT rounds significantly increased performance on a composite discharge metric compared with usual feedback. With the cessation of STAT rounds, performance between the intensive and usual feedback groups did not differ significantly, highlighting the importance of feedback delivery on effecting change. CLINICAL TRIAL: The trial was registered with ClinicalTrials.gov (NCT02593253).

A Comparison of Laboratory Testing in Teaching vs Nonteaching Hospitals for 2 Common Medical Conditions.

Importance: Robust laboratory use data are lacking to support the general assumption that teaching hospitals with trainees routinely order more laboratory tests for inpatients than do nonteaching hospitals. Objective: To quantify differences in the use of laboratory tests between teaching and nonteaching hospitals. Design, Setting, and Participants: A cross-sectional study was performed using a statewide database to identify hospitalizations with a primary diagnosis of bacterial pneumonia or cellulitis from January 1, 2014, to June 30, 2015, at teaching and nonteaching hospitals with 100 or more hospitalizations of each condition. Patients included were adult inpatients with a primary diagnosis of bacterial pneumonia (n = 24 118) or cellulitis (n = 19 211); patients excluded were those with an intensive care unit stay, transfer from another hospital, or a length of stay that was 2 SDs or more of the condition's mean length of stay. Main Outcomes and Measures: Mean laboratory tests per day stratified by illness severity, as well as factors associated with laboratory use rates. Results: A total of 43 329 hospitalized patients (20493 women and 22836 men) had a principal diagnosis of bacterial pneumonia or cellulitis across 11 major teaching hospitals, 12 minor teaching hospitals, and 73 nonteaching hospitals in Texas. Mean number of laboratory tests per day varied significantly by hospital type and was highest for major teaching hospitals for both conditions (bacterial pneumonia: major teaching hospitals, 13.21; 95% CI, 12.91-13.51; nonteaching hospitals, 8.92; 95% CI, 8.84-9.00; P < .001; cellulitis: major teaching hospitals, 10.43; 95% CI, 10.16-10.70; nonteaching hospitals, 7.29; 95% CI, 7.22-7.36; P < .001). This association held for all levels of illness severity for both conditions, except for patients with cellulitis with the highest illness severity level. In generalized mixed linear regression models, controlling for additional patient and encounter covariates, there was a significant difference in the marginal effect of hospital teaching status on mean number of laboratory tests per day between major teaching and nonteaching hospitals (difference in marginal mean laboratory tests per day for bacterial pneumonia, 3.58; 95% CI, 2.61-4.55; P < .001; for cellulitis, 2.61; 95% CI, 1.76-3.47; P < .001). Conclusions and Relevance: Compared with nonteaching hospitals, patients in Texas admitted to major teaching hospitals with bacterial pneumonia or cellulitis received significantly more laboratory tests after controlling for illness severity, length of stay, and patient demographics. These results support the need to examine how the culture of training environments may contribute to increased use of laboratory tests.

What Happened to My Patient? An Educational Intervention to Facilitate Postdischarge Patient Follow-Up.

BACKGROUND: Following up on patients' clinical courses after hospital discharge may enhance physicians' learning and care of future patients. Barriers to this practice for residents include time constraints, discontinuous training environments, and difficulty accessing patient information. OBJECTIVE: We designed an educational intervention facilitating informed self-assessment and reflection through structured postdischarge follow-up of patients' longitudinal clinical courses. We then examined the experience of interns who received this intervention in a mixed methods study. METHODS: Internal medicine interns on a 4-week patient safety rotation received lists of hospitalized patients they had cared for earlier in the year. They selected patients for chart review and completed a guided reflection worksheet for each patient reviewed. Interns then discussed lessons learned in a faculty-led group debrief session. RESULTS: Of 62 eligible interns, 62 (100%) participated in this intervention and completed 293 reflection worksheets. We analyzed worksheets and transcripts from 6 debrief sessions. Interns reported that postdischarge patient follow-up was valuable for their professional development, and helped them understand the natural history of disease and patients' illness experiences. After reviewing their patients' clinical courses, interns stated that they would advocate for earlier end-of-life counseling, improve care transitions, and adjust their clinical decision-making for similar patients in the future. CONCLUSIONS: Our educational intervention created the time, space, and structure for postdischarge patient follow-up. It was well received by participants, and is an opportunity for experiential learning.

Using an online quiz-based reinforcement system to teach healthcare quality and patient safety and care transitions at the University of California.

QUALITY ISSUE: Implementing quality improvement (QI) education during clinical training is challenging due to time constraints and inadequate faculty development in these areas. INITIAL ASSESSMENT: Quiz-based reinforcement systems show promise in fostering active engagement, collaboration, healthy competition and real-time formative feedback, although further research on their effectiveness is required. CHOICE OF SOLUTION: An online quiz-based reinforcement system to increase resident and faculty knowledge in QI, patient safety and care transitions. IMPLEMENTATION: Experts in QI and educational assessment at the 5 University of California medical campuses developed a course comprised of 3 quizzes on Introduction to QI, Patient Safety and Care Transitions. Each quiz contained 20 questions and utilized an online educational quiz-based reinforcement system that leveraged spaced learning. EVALUATION: Approximately 500 learners completed the course (completion rate 66-86%). Knowledge acquisition scores for all quizzes increased after completion: Introduction to QI (35-73%), Patient Safety (58-95%), and Care Transitions (66-90%). Learners reported that the quiz-based system was an effective teaching modality and preferred this type of education to classroom-based lectures. Suggestions for improvement included reducing frequency of presentation of questions and utilizing more questions that test learners on application of knowledge instead of knowledge acquisition. LESSONS LEARNED: A multi-campus online quiz-based reinforcement system to train residents in QI, patient safety and care transitions was feasible, acceptable, and increased knowledge. The course may be best utilized to supplement classroom-based and experiential curricula, along with increased attention to optimizing frequency of presentation of questions and enhancing application skills.

Development of a Multi-Domain Assessment Tool for Quality Improvement Projects.

BACKGROUND: Improving the quality of health care and education has become a mandate at all levels within the medical profession. While several published quality improvement (QI) assessment tools exist, all have limitations in addressing the range of QI projects undertaken by learners in undergraduate medical education, graduate medical education, and continuing medical education. OBJECTIVE: We developed and validated a tool to assess QI projects with learner engagement across the educational continuum. METHODS: After reviewing existing tools, we interviewed local faculty who taught QI to understand how learners were engaged and what these faculty wanted in an ideal assessment tool. We then developed a list of competencies associated with QI, established items linked to these competencies, revised the items using an iterative process, and collected validity evidence for the tool. RESULTS: The resulting Multi-Domain Assessment of Quality Improvement Projects (MAQIP) rating tool contains 9 items, with criteria that may be completely fulfilled, partially fulfilled, or not fulfilled. Interrater reliability was 0.77. Untrained local faculty were able to use the tool with minimal guidance. CONCLUSIONS: The MAQIP is a 9-item, user-friendly tool that can be used to assess QI projects at various stages and to provide formative and summative feedback to learners at all levels.

Standardized Attending Rounds to Improve the Patient Experience: A Pragmatic Cluster Randomized Controlled Trial.

BACKGROUND: At academic medical centers, attending rounds (AR) serve to coordinate patient care and educate trainees, yet variably involve patients. OBJECTIVE: To determine the impact of standardized bedside AR on patient satisfaction with rounds. DESIGN: Cluster randomized controlled trial. SETTING: 500-bed urban, quaternary care hospital. PATIENTS: 1200 patients admitted to the medicine service. INTERVENTION: Teams in the intervention arm received training to adhere to 5 AR practices: 1) pre-rounds huddle; 2) bedside rounds; 3) nurse integration; 4) real-time order entry; 5) whiteboard updates. Control arm teams continued usual rounding practices. MEASUREMENTS: Trained observers audited rounds to assess adherence to recommended AR practices and surveyed patients following AR. The primary outcome was patient satisfaction with AR. Secondary outcomes were perceived and actual AR duration, and attending and trainee satisfaction. RESULTS: We observed 241 (70.1%) and 264 (76.7%) AR in the intervention and control arms, respectively, which included 1855 and 1903 patient rounding encounters. Using a 5-point Likert scale, patients in the intervention arm reported increased satisfaction with AR (4.49 vs 4.25; P = 0.01) and felt more cared for by their medicine team (4.54 vs 4.36; P = 0.03). Although the intervention shortened the duration of AR by 8 minutes on average (143 vs 151 minutes; P = 0.052), trainees perceived intervention AR as lasting longer and reported lower satisfaction with intervention AR. CONCLUSIONS: Medicine teams can adopt a standardized, patient-centered, time-saving rounding model that leads to increased patient satisfaction with AR and the perception that patients are more cared for by their medicine team. Journal of Hospital Medicine 2017;12:143-149.

Using the Electronic Health Record to Identify Educational Gaps for Internal Medicine Interns.

BACKGROUND: An important component of internal medicine residency is clinical immersion in core rotations to expose first-year residents to common diagnoses. OBJECTIVE: Quantify intern experience with common diagnoses through clinical documentation in an electronic health record. METHODS: We analyzed all clinical notes written by postgraduate year (PGY) 1, PGY-2, and PGY-3 residents on medicine service at an academic medical center July 1, 2012, through June 30, 2014. We quantified the number of notes written by PGY-1s at 1 of 3 hospitals where they rotate, by the number of notes written about patients with a specific principal billing diagnosis, which we defined as diagnosis-days. We used the International Classification of Diseases 9 (ICD-9) and the Clinical Classification Software (CCS) to group the diagnoses. RESULTS: We analyzed 53 066 clinical notes covering 10 022 hospitalizations with 1436 different ICD-9 diagnoses spanning 217 CCS diagnostic categories. The 10 most common ICD-9 diagnoses accounted for 23% of diagnosis-days, while the 10 most common CCS groupings accounted for more than 40% of the diagnosis-days. Of 122 PGY-1s, 107 (88%) spent at least 2 months on the service, and 3% were exposed to all of the top 10 ICD-9 diagnoses, while 31% had experience with fewer than 5 of the top 10 diagnoses. In addition, 17% of PGY-1s saw all top 10 CCS diagnoses, and 5% had exposure to fewer than 5 CCS diagnoses. CONCLUSIONS: Automated detection of clinical experience may help programs review inpatient clinical experiences of PGY-1s.

Exploring Physician Perspectives of Residency Holdover Handoffs: A Qualitative Study to Understand an Increasingly Important Type of Handoff.

BACKGROUND: The term "holdover admissions" refers to patients admitted by an overnight physician and whose care is then transferred to a new primary team the next morning. Descriptions of the holdover process in internal medicine are sparse. OBJECTIVE: To identify important factors affecting the quality of holdover handoffs at an internal medicine (IM) residency program and to compare them to previously identified factors for other handoffs. DESIGN: We undertook a qualitative study using structured focus groups and interviews. We analyzed data using qualitative content analysis. PARTICIPANTS: IM residents, IM program directors, and hospitalists at a large academic medical center. MAIN MEASURES: A nine-question open-ended interview guide. KEY RESULTS: We identified 13 factors describing holdover handoffs. Five factors-physical space, standardization, task accountability, closed-loop verification, and resilience-were similar to those described in prior handoff literature in other specialties. Eight factors were new concepts that may uniquely affect the quality of the holdover handoff in IM. These included electronic health record access, redundancy, unwritten thoughts, different clinician needs, diagnostic uncertainty, anchoring, teaching, and feedback. These factors were organized into five overarching themes: physical environment, information transfer, responsibility, clinical reasoning, and education. CONCLUSIONS: The holdover handoff in IM is complex and has unique considerations for achieving high quality. Further exploration of safe, efficient, and educational holdover handoff practices is necessary.