Postoperative and postdischarge nausea and vomiting following ambulatory eye, head, and neck surgeries: a retrospective cohort study comparing incidence and associated factors.

BACKGROUND: Ambulatory surgery is often followed by the development of nausea and/or vomiting (N/V). Although risk factors for postoperative nausea and vomiting (PONV) are frequently discussed, the distinction between PONV and postdischarge nausea and vomiting (PDNV) is unclear. This is especially troublesome given the potential consequences of postdischarge nausea and vomiting (PDNV), which include major discomfort and hospital readmission. METHODS: In this retrospective cohort study, data from 10,231 adult patients undergoing ambulatory ophthalmology or otolaryngology procedures with general anesthesia were collected and analyzed. Binary and multinomial logistic regression was used to assess the association between patient and anesthetic characteristics (including age, body mass index (BMI), American Society of Anesthesiologists Physical Status (ASA P/S) classification, current smoker status, and intra- and postoperative opioid usage) and the odds ratios of experiencing only PDNV, only PONV, or both PONV and PDNV, as compared to not experiencing N/V at all. RESULTS: We found that 17.8% of all patients developed N/V (PONV and/or PDNV). Patients who experienced PONV had a 2.79 (95% confidence interval 2.24-3.46) times greater risk of reporting PDNV. Binary logistic regression found that younger age, opioid use, and female sex were associated with an increased likelihood of experiencing any N/V. Increased use of nitrous oxide and a higher ASA P/S class was associated with elevated likelihood of PONV, but not PDNV or PONV plus PDNV. CONCLUSIONS: Patients experiencing N/V in the PACU are observed to develop PDNV disproportionately by a factor of 2.79. The patients have distinct predictors, indicating important opportunities for care improvements beyond current guidelines.

What Went Right? A Mixed-Methods Study of Positive Feedback Data in a Hospital-Wide Mortality Review Survey.

BACKGROUND: Toxic work culture contributes to healthcare worker burnout and attrition, but little is known about how healthcare organizations can systematically create and promote a culture of civility and collegiality. OBJECTIVE: To analyze peer-to-peer positive feedback collected as part of a systematized mortality review survey to identify themes and recognition dynamics that can inform positive organizational culture change. DESIGN: Convergent mixed-methods study design. PARTICIPANTS: A total of 388 physicians, 212 registered nurses, 64 advanced practice providers, and 1 respiratory therapist at four non-profit hospitals (2 academic and 2 community). INTERVENTION: Providing optional positive feedback in the mortality review survey. MAIN MEASURES: Key themes and subthemes that emerged from positive feedback data, associations between key themes and positive feedback respondent characteristics, and recognition dynamics between positive feedback respondents and recipients. KEY RESULTS: Approximately 20% of healthcare workers provided positive feedback. Three key themes emerged among responses with free text comments: (1) providing extraordinary patient and family-centered care; (2) demonstrating self-possession and mastery; and (3) exhibiting empathic peer support and effective team collaboration. Compared to other specialties, most positive feedback from medicine (70.2%), neurology (65.2%), hospice and palliative medicine (64.3%), and surgery (58.8%) focused on providing extraordinary patient and family-centered care (p = 0.02), whereas emergency medicine (59.1%) comments predominantly focused on demonstrating self-possession and mastery (p = 0.06). Registered nurses (40.2%) provided multidirectional positive feedback more often than other clinician types in the hospital hierarchy (p < 0.001). CONCLUSIONS: Analysis of positive feedback from a mortality review survey provided meaningful insights into a health system's culture of teamwork and values related to civility and collegiality when providing end-of-life care. Systematic collection and sharing of positive feedback is feasible and has the potential to promote positive culture change and improve healthcare worker well-being.

Financial Impact of a Radiology Safety Net Program for Resolution of Clinically Necessary Follow-up Imaging Recommendations.

OBJECTIVE: Health care safety net (SN) programs can potentially improve patient safety and decrease risk associated with missed or delayed follow-up care, although they require financial resources. This study aimed to assess whether the revenue generated from completion of clinically necessary recommendations for additional imaging (RAI) made possible by an IT-enabled SN program could fund the required additional labor resources. METHODS: Clinically necessary RAI generated October 21, 2019, to September 24, 2021, were tracked to resolution as of April 13, 2023. A new radiology SN team worked with existing schedulers and care coordinators, performing chart review and patient and provider outreach to ensure RAI resolution. We applied relevant Current Procedural Terminology, version 4 codes of the completed imaging examinations to estimate total revenue. Coprimary outcomes included revenue generated by total performed examinations and estimated revenue attributed to SN involvement. We used Student's t test to compare the secondary outcome, RAI time interval, for higher versus lower revenue-generating modalities. RESULTS: In all, 24% (3,243) of eligible follow-up recommendations (13,670) required SN involvement. Total estimated revenue generated by performed recommended examinations was $6,116,871, with $980,628 attributed to SN. Net SN-generated revenue per 1.0 full-time equivalent was an estimated $349,768. Greatest proportion of performed examinations were cross-sectional modalities (CT, MRI, PET/CT), which were higher revenue-generating than non-cross-sectional modalities (x-ray, ultrasound, mammography), and had shorter recommendation time frames (153 versus 180 days, P < .001). DISCUSSION: The revenue generated from completion of RAI facilitated by an IT-enabled quality and safety program supplemented by an SN team can fund the required additional labor resources to improve patient safety. Realizing early revenue may require 5 to 6 months postimplementation.

Impact of an Automated Closed-Loop Communication and Tracking Tool on the Rate of Recommendations for Additional Imaging in Thoracic Radiology Reports.

OBJECTIVE: Assess the effects of feedback reports and implementing a closed-loop communication system on rates of recommendations for additional imaging (RAIs) in thoracic radiology reports. METHODS: In this retrospective, institutional review board-approved study at an academic quaternary care hospital, we analyzed 176,498 thoracic radiology reports during a pre-intervention (baseline) period from April 1, 2018, to November 30, 2018; a feedback report only period from December 1, 2018, to September 30, 2019; and a closed-loop communication system plus feedback report (IT intervention) period from October 1, 2019, to December 31, 2020, promoting explicit documentation of rationale, time frame, and imaging modality for RAI, defined as complete RAI. A previously validated natural language processing tool was used to classify reports with an RAI. Primary outcome of rate of RAI was compared using a control chart. Multivariable logistic regression determined factors associated with likelihood of RAI. We also estimated the completeness of RAI in reports comparing IT intervention to baseline using χ2 statistic. RESULTS: The natural language processing tool classified 3.2% (5,682 of 176,498) reports as having an RAI; 3.5% (1,783 of 51,323) during the pre-intervention period, 3.8% (2,147 of 56,722) during the feedback report only period (odds ratio: 1.1, P = .03), and 2.6% (1,752 of 68,453) during the IT intervention period (odds ratio: 0.60, P < .001). In subanalysis, the proportion of incomplete RAI decreased from 84.0% (79 of 94) during the pre-intervention period to 48.5% (47 of 97) during the IT intervention period (P < .001). DISCUSSION: Feedback reports alone increased RAI rates, and an IT intervention promoting documentation of complete RAI in addition to feedback reports led to significant reductions in RAI rate, incomplete RAI, and improved overall completeness of the radiology recommendations.

Development and External Validation of an Artificial Intelligence Model for Identifying Radiology Reports Containing Recommendations for Additional Imaging.

BACKGROUND. Reported rates of recommendations for additional imaging (RAIs) in radiology reports are low. Bidirectional encoder representations from transformers (BERT), a deep learning model pretrained to understand language context and ambiguity, has potential for identifying RAIs and thereby assisting large-scale quality improvement efforts. OBJECTIVE. The purpose of this study was to develop and externally validate an artificial intelligence (AI)-based model for identifying radiology reports containing RAIs. METHODS. This retrospective study was performed at a multisite health center. A total of 6300 radiology reports generated at one site from January 1, 2015, to June 30, 2021, were randomly selected and split by 4:1 ratio to create training (n = 5040) and test (n = 1260) sets. A total of 1260 reports generated at the center's other sites (including academic and community hospitals) from April 1 to April 30, 2022, were randomly selected as an external validation group. Referring practitioners and radiologists of varying sub-specialties manually reviewed report impressions for presence of RAIs. A BERT-based technique for identifying RAIs was developed by use of the training set. Performance of the BERT-based model and a previously developed traditional machine learning (TML) model was assessed in the test set. Finally, performance was assessed in the external validation set. The code for the BERT-based RAI model is publicly available. RESULTS. Among a total of 7419 unique patients (4133 women, 3286 men; mean age, 58.8 years), 10.0% of 7560 reports contained RAI. In the test set, the BERT-based model had 94.4% precision, 98.5% recall, and an F1 score of 96.4%. In the test set, the TML model had 69.0% precision, 65.4% recall, and an F1 score of 67.2%. In the test set, accuracy was greater for the BERT-based than for the TML model (99.2% vs 93.1%, p < .001). In the external validation set, the BERT-based model had 99.2% precision, 91.6% recall, an F1 score of 95.2%, and 99.0% accuracy. CONCLUSION. The BERT-based AI model accurately identified reports with RAIs, outperforming the TML model. High performance in the external validation set suggests the potential for other health systems to adapt the model without requiring institution-specific training. CLINICAL IMPACT. The model could potentially be used for real-time EHR monitoring for RAIs and other improvement initiatives to help ensure timely performance of clinically necessary recommended follow-up.

Development and Assessment of an Information Technology Intervention to Improve the Clarity of Radiologist Follow-up Recommendations.

Importance: It is challenging to ensure timely performance of radiologist-recommended additional imaging when radiologist recommendation language is incomplete or ambiguous. Objective: To evaluate whether voluntary use of an information technology tool with forced structured entry of recommendation attributes was associated with improved completeness of recommendations for additional imaging over time. Design, Setting, and Participants: This cohort study of imaging report data was performed at an academic quaternary care center in Boston, Massachusetts, and included consecutive adults with radiology examinations performed from September 12 to 13, 2019 (taxonomy validation), October 14 to 17, 2019 (before intervention), April 5 to 7, 2021 (1 week after intervention), and April 4 to 7, 2022 (1 year after intervention), with reports containing recommendations for additional imaging. A radiologist scored the 3 groups (preintervention group, 1-week postintervention group, and 1-year postintervention group) of 336 consecutive radiology reports (n = 1008) with recommendations for additional imaging. Intervention: Final implementation on March 27, 2021, of a voluntary closed-loop communication tool embedded in radiologist clinical workflow that required structured entry of recommendation attributes. Main Outcomes and Measures: The a priori primary outcome was completeness of recommendations for additional imaging, defined in a taxonomy created by a multidisciplinary expert panel. To validate the taxonomy, 2 radiologists independently reviewed and scored language attributes as present or absent in 247 consecutive radiology reports containing recommendations for additional imaging. Agreement was assessed with Cohen κ. Recommendation completeness over time was compared with with 1-sided Fisher exact tests and significance set at P < .05. Results: Radiology-related information for consecutive radiology reports from the 4 time periods was collected from the radiology department data warehouse, which does not include data on patient demographic characteristics or other nonimaging patient medical information. The panel defined 5 recommendation language attributes: complete (contains imaging modality, time frame, and rationale), ambiguous (equivocal, vague language), conditional (qualifying language), multiplicity (multiple options), and alternate (language favoring a different examination to that ordered). Two radiologists had more than 90% agreement (κ > 0.8) for these attributes. Completeness with use of the tool increased more than 3-fold, from 14% (46 of 336) before the intervention to 46% (153 of 336) (P < .001) 1 year after intervention; completeness in the corresponding free-text report language increased from 14% (46 of 336) before the intervention to 25% (85 of 336) (P < .001) 1 year after the intervention. Conclusions and Relevance: This study suggests that supplementing free-text dictation with voluntary use of a structured entry tool was associated with improved completeness of radiologist recommendations for additional imaging as assessed by an internally validated taxonomy. Future research is needed to assess the association with timely performance of clinically necessary recommendations and diagnostic errors. The taxonomy can be used to evaluate and build interventions to modify radiologist reporting behaviors.

Predictors of Completion of Clinically Necessary Radiologist-Recommended Follow-Up Imaging: Assessment Using an Automated Closed-Loop Communication and Tracking Tool.

BACKGROUND. Patients with adverse social determinants of health may be at increased risk of not completing clinically necessary follow-up imaging. OBJECTIVE. The purpose of this study was to use an automated closed-loop communication and tracking tool to identify patient-, referrer-, and imaging-related factors associated with lack of completion of radiologist-recommended follow-up imaging. METHODS. This retrospective study was performed at a single academic health system. A tool for automated communication and tracking of radiologist-recommended follow-up imaging was embedded in the PACS and electronic health record. The tool prompted referrers to record whether they deemed recommendations to be clinically necessary and assessed whether clinically necessary follow-up imaging was pursued. If imaging was not performed within 1 month after the intended completion date, the tool prompted a safety net team to conduct further patient and referrer follow-up. The study included patients for whom a follow-up imaging recommendation deemed clinically necessary by the referrer was entered with the tool from October 21, 2019, through June 30, 2021. The electronic health record was reviewed for documentation of eventual completion of the recommended imaging at the study institution or an outside institution. Multivariable logistic regression analysis was performed to identify factors associated with completion of follow-up imaging. RESULTS. Of 5856 recommendations entered during the study period, the referrer agreed with 4881 recommendations in 4599 patients (2929 women, 1670 men; mean age, 61.3 ± 15.6 years), who formed the study sample. Follow-up was completed for 74.8% (3651/4881) of recommendations. Independent predictors of lower likelihood of completing follow-up imaging included living in a socioeconomically disadvantaged neighborhood according to the area deprivation index (odds ratio [OR], 0.67 [95% CI, 0.54-0.84]), inpatient (OR, 0.25 [95% CI, 0.20-0.32]) or emergency department (OR, 0.09 [95% CI, 0.05-0.15]) care setting, and referrer surgical specialty (OR, 0.70 [95% CI, 0.58-0.84]). Patient age, race and ethnicity, primary language, and insurance status were not independent predictors of completing follow-up (p > .05). CONCLUSION. Socioeconomically disadvantaged patients are at increased risk of not completing recommended follow-up imaging that referrers deem clinically necessary. CLINICAL IMPACT. Initiatives for ensuring completion of follow-up imaging should be aimed at the identified patient groups to reduce disparities in missed and delayed diagnoses.

A Prospective Intervention to Reduce Burnout Among Academic Radiologists.

RATIONALE AND OBJECTIVES: Few studies have examined what constitutes effective interventions to reduce burnout among radiologists. We compared self-reported burnout among academic medical center radiologists before and after a series of departmental initiatives intended to increase wellbeing and professional satisfaction. MATERIALS AND METHODS: This Institutional Review Board-approved, prospective study took place 2017-2019 in a tertiary academic medical center. In pre- (2017) and post-intervention (2019) periods, we administered the previously-validated Stanford Physician Wellness Survey to faculty in our 11-division radiology department. Faculty rated their burnout level across 8 domains (professional fulfillment, emotional exhaustion, interpersonal disengagement, sleep difficulties, self-compassion, negative work impact on personal relations, organizational/personal values alignment, perceived quality of supervisory leadership). Between the two surveys, departmental initiatives focusing on culture, team building, work-life balance, and personal well-being were implemented (e.g., electronic medical record training, shorter work hours). Pre- and post-survey results were compared, using Whitney-Mann U test to calculate Z scores. RESULTS: Faculty members rated lower professional fulfillment (Z-3.04, p=0.002), higher emotional exhaustion (Z=2.52, p=0.012), increased sleep-related impairment (Z=2.38, p=0.012), and reduced organizational/personal values alignment (Z=-4.10, p<0.0001) between the two surveys. No significant differences were identified associated with interpersonal disengagement (Z=1.82, p=0.069), self-compassion (Z=1.39, p=0.164), negative impact of work on personal relationship (Z=0.89, p=0.372) and perceived supervisory leadership quality (Z=0.07, p=0.942). CONCLUSION: Despite numerous departmental initiatives intended to improve culture, workplace efficiency, work-life balance, and personal wellness, self-reported burnout was unchanged or worsened over time.Physician and employee wellness embedded into institutional culture maybe more effective than departmental improvement initiatives.

Patient Experience Scores for Radiologists: Comparison With Nonradiologist Physicians and Changes After Public Posting in an Institutional Online Provider Directory.

BACKGROUND. Patients are increasingly using online information regarding patient experiences to guide care decisions. OBJECTIVE. The purpose of our study was to compare patient experience scores between radiologists and nonradiologist physicians and to assess changes in scores after their public posting in an online physician directory. METHODS. This retrospective study included data collected from May 1, 2017, to November 30, 2018, at a single large academic medical center. After all institutional outpatient visits, patients were e-mailed the Press Ganey Medical Practice Survey, which included 10 questions (answered using a Likert scale and converted to 100-point range) relating to the patient's experience with the specific provider for the encounter. Surveys were distributed to patients after radiology encounters if involving an image-guided invasive procedure. Mean scores for each question and the mean weighted overall score were displayed on each physician's publicly available profile on the hospital's online physician directory and were updated monthly. Scores were compared between radiologists and nonradiologist physicians; temporal changes were assessed. RESULTS. The response rate was 18.0% (96,057/533,983). After exclusions (23,989 surveys completed without provider ratings; 183 surveys evaluating physician assistants), 71,885 physician surveys were evaluated: 2703 surveys for 65 radiologists, 49,403 surveys for 916 physicians in 17 nonsurgical specialties, and 19,779 surveys for 262 physicians in 13 surgical specialties. Over the study period, the mean overall score was 95.6 for radiologists and 95.9 for nonradiologists (94.6 for surgical specialties, 96.4 for nonsurgical specialties). For the 10 individual questions, scores ranged for radiologists from 94.6 (time spent with patient) to 96.8 (friendliness/courtesy) and for nonradiologists from 94.6 (time spent with patient) to 97.0 (friendliness/courtesy). The mean overall score increased from the first month to the final month for radiologists from 94.2 to 97.1 and for nonradiologists from 95.7 to 96.3. For radiologists, the largest improvement was for instructions regarding postprocedure follow-up care (increased from 91.4 to 97.4). CONCLUSION. Radiologists received high scores on patient experience surveys when evaluated on encounters involving invasive procedures, achieving scores similar to those for other physicians. Scores improved over time, possibly related to online posting of survey results. CLINICAL IMPACT. The findings support the utility of implementing patient experience surveys in radiology.

Collaborative Case Review: A Systems-Based Approach to Patient Safety Event Investigation and Analysis.

OBJECTIVES: The aims of the 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. METHODS: A fully integrated CCR process, co-led by radiology and an institutional patient safety program, was implemented on November 1, 2017, at our large academic medical center for evaluating adverse events involving radiology. Quality and safety teams performed reviews for events identified with other departments who maintained their existing processes. This institutional review board-approved study describes the program, including percentage of CCR from an institutional Electronic Safety Reporting System, percentage of CCR per specialty, and action item completion rates and strength (e.g., stronger) based on a Veterans Administration-designed hierarchy. χ2 analysis assessed impact of clinical specialty on strength of action prescribed. RESULTS: Seventy-three CCR in 2018 generated 260 action items from 10 specialties. Seventy percent (51/73) were adverse events identified through Electronic Safety Reporting System. The specialty most frequently associated with CCR was radiology (16/73, 22%). Most action items (204/260, 78%) were completed in 1 year; stronger action items were completed in 71 (27%) of 260. Radiology was responsible for 61 action items; 25 (41%) of 61 were strong versus all other specialties with strong action items in 46 (23%) of 199 (P < 0.01). CONCLUSIONS: 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. Active engagement in CCR can provide insights into addressing adverse events and promote patient safety.

Coronavirus disease 2019 (COVID-19) screening system utilizing daily symptom attestation helps identify hospital employees who should be tested to protect patients and coworkers.

OBJECTIVE: To investigate the effectiveness of a daily attestation system used by employees of a multi-institutional academic medical center, which comprised of symptom-screening, self-referrals to the Occupational Health Services team, and/or a severe acute respiratory coronavirus virus 2 (SARS-CoV-2) test. DESIGN: We conducted a retrospective cohort study of all employee attestations and SARS-CoV-2 tests performed between March and June 2020. SETTING: A large multi-institutional academic medical center, including both inpatient and ambulatory settings. PARTICIPANTS: All employees who worked at the study site. METHODS: Data were combined from the attestation system (COVIDPass), the employee database, and the electronic health records and were analyzed using descriptive statistics including χ2, Wilcoxon, and Kruskal-Wallis tests. We investigated whether an association existed between symptomatic attestations by the employees and the employee testing positive for SARS-CoV-2. RESULTS: After data linkage and cleaning, there were 2,117,298 attestations submitted by 65,422 employees between March and June 2020. Most attestations were asymptomatic (99.9%). The most commonly reported symptoms were sore throat (n = 910), runny nose (n = 637), and cough (n = 570). Among the 2,026 employees who ever attested that they were symptomatic, 905 employees were tested within 14 days of a symptomatic attestation, and 114 (13%) of these tests were positive. The most common symptoms associated with a positive SARS-CoV-2 test were anosmia (23% vs 4%) and fever (46% vs 19%). CONCLUSIONS: Daily symptom attestations among healthcare workers identified a handful of employees with COVID-19. Although the number of positive tests was low, attestations may help keep unwell employees off campus to prevent transmissions.

Exacerbation of Inequities in Use of Diagnostic Radiology During the Early Stages of Reopening After COVID-19.

OBJECTIVE: Assess diagnostic radiology examination utilization and associated social determinants of health during the early stages of reopening after state-mandated shutdown of nonurgent services because of coronavirus disease 2019 (COVID-19). METHODS: This institutional review board-approved, retrospective study assessed all patients with diagnostic radiology examinations performed at an academic medical center with eight affiliated outpatient facilities before (January 1, 2020, to March 8, 2020) and after (June 7, 2020, to July 15, 2020) the COVID-19 shutdown. Examinations during the shut down (March 9, 2020, to June 6, 2020) were excluded. Patient-specific factors (eg, race, ethnicity), imaging modalities, and care settings were extracted from the Research Data Warehouse. Primary outcome was the number of diagnostic radiology examinations per day compared pre- and post-COVID-19 shutdown. Univariate analysis and multivariable logistic regression determined features associated with completing an examination. RESULTS: Despite resumption of nonurgent services, marked decrease in radiology examination utilization persisted in all care settings post-COVID-19 shutdown (869 examinations per day preshutdown [59,080 examinations in 68 days] versus 502 examinations per day postshutdown [19,594 examinations in 39 days]), with more significantly decreased odds ratios for having examinations in inpatient and outpatient settings versus in the emergency department. Inequities worsened, with patients from communities with high rates of poverty, unemployment, and chronic disease having significantly lower odds of undergoing radiology examinations post-COVID-19 shutdown. Patients of Asian race and Hispanic ethnicity had significantly lower odds ratios for having examinations post-COVID-19 shutdown compared with White and non-Hispanic patients, respectively. DISCUSSION: The COVID-19 pandemic has exacerbated known pre-existing inequities in diagnostic radiology utilization. Resources should be allocated to address subgroups of patients who may be less likely to receive necessary diagnostic radiology examinations, potentially leading to compromised patient safety and quality of care.

Closing the Loop on Unscheduled Diagnostic Imaging Orders: A Systems-Based Approach.

PURPOSE: The aims of this study were to (1) describe the System for Coordinating Orders for Radiology Exams (SCORE), the objective of which is to manage unscheduled orders for outpatient diagnostic imaging in an electronic health record (EHR) with embedded computerized physician order entry; (2) assess the impact of SCORE and other related factors (eg, demographics) on the rate of unscheduled orders; and (3) assess the clinical necessity of orders canceled, expired, scheduled, and performed. METHODS: This institutional review board-approved retrospective study was conducted at a large academic institution between October 1, 2017, and July 1, 2019. The design and implementation of SCORE are described, including people (eg, competencies), processes (eg, standardized procedures), and tools (eg, EHR interfaces, dashboard). The rate of unscheduled imaging orders was compared before SCORE (October 1, 2017, to September 30, 2018) and after SCORE (October 1, 2018, to Jun 30, 2019) using χ2 analysis. For 447 randomly selected orders, mode of resolution was obtained from the EHR, and factors related to order resolution were assessed using multivariate analysis. Finally, clinical necessity was manually assessed by two physicians. RESULTS: Before SCORE, 52,204 of 607,020 examination orders (8.6%) were unscheduled, compared with 20,900 of 475,000 examination orders (4.4%) after SCORE (P < .00001, χ2 test), a 49% reduction in unscheduled orders. Among 447 randomly selected orders, orders were addressed via cancellation (57%), expiration (21%), scheduling (1%), and performance (11%). Order resolution was not significantly associated with other factors. About 32% of cancellations and 27.7% of expired orders remained clinically necessary, which was attributed to scheduling and patient-related factors. CONCLUSIONS: SCORE significantly reduced unscheduled diagnostic imaging orders. This patient safety initiative may help reduce errors resulting from diagnostic delays due to unscheduled examination orders.

Addressing the caste system in U.S. healthcare in the era of COVID-19.

In healthcare, we find an industry that typifies the unique blend of racism, classism, and other forms of structural discrimination that comprise the U.S. caste system-the artificially-constructed and legally-reinforced social hierarchy for assigning worth and determining opportunity for individuals based on race, class, and other factors. Despite myths of meritocracy, healthcare is actually a casteocracy; and conversations about racism in healthcare largely occupy an echo chamber among the privileged upper caste of hospital professionals. To address racism in healthcare, we must consider the history that brought us here and understand how we effectively perpetuate an employee caste system within our own walls.

Reducing Medication Waste While Improving Access to Sugammadex: A Quality Improvement Project in Medication Stewardship.

The relatively high cost of sugammadex compared to neostigmine limits its widespread use to reverse neuromuscular blockade, despite its faster onset and more complete clinical effect. While ensuring timely access to sugammadex is important in improving perioperative safety, it is also vital to control unnecessary spending. We describe a quality improvement initiative to reduce excess spending on sugammadex while improving access for anesthesia providers. Monthly spending on sugammadex decreased by 52% ($70,777 vs $33,821), while medication access increased via automated medication dispensers in each operating room. Clinical usage decreased by one-third, with presumed increased adherence to dosing guidelines.

Unscheduled Radiologic Examination Orders in the Electronic Health Record: A Novel Resource for Targeting Ambulatory Diagnostic Errors in Radiology.

PURPOSE: The aim of this study was to assess the prevalence of unscheduled radiologic examination orders in an electronic health record, and the proportion of unscheduled orders that are clinically necessary, by modality. METHODS: This retrospective study was conducted from January to October 2016 at an academic institution. All unscheduled radiologic examination orders were retrieved for seven modalities (CT, MR, ultrasound, obstetric ultrasound, bone densitometry, mammography, and fluoroscopy). After excluding duplicates, 100 randomly selected orders from each modality were assigned to two physician reviewers who classified their clinical necessity, with 10% overlap. Interannotator agreement was assessed using κ statistics, the percentage of clinically necessary unscheduled orders was compared, and χ2 analysis was used to assess differences by modality. RESULTS: A total 494,503 radiologic examination orders were placed during the study period. After exclusions, 33,546 unscheduled orders were identified, 7% of all radiologic examination orders. Among 700 reviewed unscheduled orders, agreement was substantial (κ = 0.63). Eighty-seven percent of bone densitometric examinations and sixty-five percent of mammographic studies were considered clinically necessary, primarily for follow-up management. The majority of orders in each modality were clinically necessary, except for CT, obstetric ultrasound, and fluoroscopy (P < .0001). CONCLUSIONS: Large numbers of radiologic examination orders remain unscheduled in the electronic health record. A substantial portion are clinically necessary, representing potential delays in executing documented provider care plans. Clinically unnecessary unscheduled orders may inadvertently be scheduled and performed. Identifying and performing clinically necessary unscheduled radiologic examination orders may help reduce diagnostic errors related to diagnosis and treatment delays and enhance patient safety, while eliminating clinically unnecessary unscheduled orders will help avoid unneeded testing.

Factors Associated With Optimal Follow-up in Women With BI-RADS 3 Breast Findings.

OBJECTIVE: Assess rate of and factors associated with optimal follow-up in patients with BI-RADS 3 breast findings. METHODS: This Institutional Review Board-approved, retrospective cohort study, performed at an academic medical center, included all women undergoing breast imaging (ultrasound and mammography) in 2016. Index reports for unique patients with an assessment of BI-RADS 3 (retrieved via natural language processing) comprised the study population. Patient-specific and provider-related features were extracted from the Research Data Warehouse. The Institutional Cancer Registry identified patients diagnosed with breast cancer. Optimal follow-up rate was calculated as patients with follow-up imaging on the same breast 3 to 9 months from the index examination among patients with BI-RADS 3 assessments. Univariate analysis and multivariable logistic regression determined features associated with optimal follow-up. Malignancy rate and time to malignancy detection were recorded. RESULTS: Among 93,685 breast imaging examinations, 64,771 were from unique patients of which 2,967 had BI-RADS 3 findings (4.6%). Excluding patients with off-site index examinations and those with another breast examination <3 months from the index, 1,125 of 1,511 patients (74%) had optimal follow-up. In univariate and multivariable analysis, prior breast cancer was associated with optimal follow-up; younger age, Hispanic ethnicity, divorced status, and lack of insurance were associated with not having optimal follow-up. Malignancy rate was 0.86%, and mean time to detection was 330 days. DISCUSSION: Follow-up of BI-RADS 3 breast imaging findings is optimal in only 74% of women. Further interventions to promote follow-up should target younger, unmarried women, those with Hispanic ethnicity, and women without history of breast cancer and without insurance coverage.