Too much time or not enough? An observational study of teacher wait time after questions in case-based seminars.

BACKGROUND: We define teacher wait time (TWT) as a pause between a teacher question and the following response given by a student. TWT is valuable because it gives students time to activate prior knowledge and reflect on possible answers to teacher questions. We seek to gain initial insights into the phenomenon of TWT in medical education and give commensurate recommendations to clinical teachers. METHODS: We observed n = 719 teacher questions followed by wait time. These were video-recorded in 29 case-based seminars in undergraduate medical education in the areas of surgery and internal medicine. The seminars were taught by 19 different clinical teachers. The videos were coded with satisfactory reliability. Time-to-event data analysis was used to explore TWT overall and independently of question types. RESULTS: In our sample of case-based seminars, about 10% of all teacher questions were followed by TWT. While the median duration of TWT was 4.41 s, we observed large variation between different teachers (median between 2.88 and 10.96 s). Based on our results, we recommend that clinical teachers wait for at least five, but not longer than 10-12 s after initial questions. For follow-up and reproduction questions, we recommend shorter wait times of 5-8 s. CONCLUSIONS: The present study provides insights into the frequency and duration of TWT and its dependence on prior questions in case-based seminars. Our results provide clinical teachers with guidance on how to use TWT as an easily accessible tool that gives students time to reflect on and respond to teacher questions.

Interventions to improve emergency department throughput and care delivery indicators: A systematic review and meta-analysis.

BACKGROUND: Emergency department (ED) crowding has repercussions on acute care, contributing to prolonged wait times, length of stay, and left without being seen (LWBS). These indicators are regarded as systemic shortcomings, reflecting a failure to provide equitable and accessible acute care. The objective was to evaluate the effectiveness of interventions aimed at improving ED care delivery indicators. METHODS: This was a systematic review and meta-analysis of randomized controlled trials (RCTs) assessing ED interventions aimed at reducing key metrics of time to provider (TTP), time to disposition (TTD), and LWBS. We excluded disease-specific trials (e.g., stroke). We used Cochrane's revised tool to assess the risk of bias and Grading of Recommendations, Assessment, Development, and Evaluations to rate the quality of evidence. The meta-analysis was performed using a random-effects model and Cochrane Q test for heterogeneity. Data were summarized as means (±SD) for continuous variables and risk ratios (RR) with 95% confidence intervals (CIs). RESULTS: We searched MEDLINE, EMBASE, and other major databases. A total of 1850 references were scanned and 20 RCTs were selected for inclusion. The trials reported at least one of the three outcomes of TTD, TTP, or LWBS. Most interventions focused on triage liaison physician and point-of-care (POC) testing. Others included upfront expedited workup (ordering tests before full evaluation by a provider), scribes, triage kiosks, and sending notifications to consultants or residents. POC testing decreased TTD by an average of 5-96 min (high heterogeneity) but slightly increased TTP by a mean difference of 2 min (95% CI 0.6-4 min). Utilizing a triage liaison physician reduced TTD by 28 min (95% CI 19-37 min; moderate-quality evidence) and was more effective in reducing LWBS than routine triage (RR 0.76, 95% CI 0.66-0.88; moderate quality). CONCLUSIONS: Operational strategies such as POC testing and triage liaison physicians could mitigate the impact of ED crowding and appear to be effective. The current evidence supports these strategies when tailored to the appropriate practice environment.

Phase-Based Care in Community Mental Health: A Cost-Effective Innovation Using Algorithms, Rating Scales and Treatment Teams for Depression Management.

This retrospective, observational report describes an innovative quality improvement process, Phase-based Care (PBC), that eliminated wait times and achieved positive clinical outcomes in a community mental health center's (CMHC) mood disorder clinic without adding staff. PBC accomplishes this by eliminating the ingrained cultural practice of routinely scheduling stable patients at rote intervals of 1-3 months, regardless of clinical need or medical necessity. Based on four organizational transformations and using mathematical algorithms developed for this process, PBC re-allocates therapy and medical resources away from routinely scheduled appointments and front-loads those resources to patients in an acute phase of illness. To maintain wellness for patients in recovery, lower frequency and intensity approaches are used. This report describes the development of the PBC methodology focusing on the Rapid Recovery Clinic (RRC) comprised of 182 patients with a primary diagnosis of a mood disorder, the largest of the 14 PBC clinics created. Over an 18-month period, wait times were reduced from several months to less than one week and recovery rates, meaning no longer in an acute phase, were 63% and 78% at weeks 6 and 12, respectively for patients who engaged in the program.

Association Between Emergency Department Operational Metrics and Substance Use Disorder Treatment Interest in Two Rhode Island Hospitals.

OBJECTIVE: This study examined if emergency department (ED) operational metrics, such as wait time or length of stay, are associated with interest in substance use disorder (SUD) treatment referral among patients at high risk of opioid overdose. METHODS: In this observational study, 648 ED patients at high risk of opioid overdose completed a baseline questionnaire. Operational metrics were summarized using electronic health record data. The association between operational metrics and treatment interest was estimated with multivariable logistic regression. RESULTS: Longer time to room (adjusted odds ratio [AOR]=1.12, 95% confidence interval [CI]=1.01-1.25) and length of stay (AOR=1.02, 95% CI=1.00-1.05) were associated with treatment referral interest. Time to provider and number of treating providers showed no significant association. CONCLUSION: Longer rooming wait times and longer ED visits were associated with increased SUD treatment referral interest. This suggests patients who wait for longer periods may be motivated for treatment and warrant further resource investment.

Speed, Spectrum, and Satisfaction: Assessment of an Infectious Diseases eConsult Program.

This report examines the implementation and early functioning of a new infectious diseases (ID) eConsult program. We recorded the reasons for placing ID eConsults, time to eConsult completion, in-person clinic wait times, and referring provider satisfaction following implementation of our outpatient eConsult program. Our data suggest that this ambulatory eConsult program led to improved access to ID subspecialty care, both via eConsults directly, and by reducing clinic wait times for patients who required an in-person evaluation.

Cost and non-cost factors associated with delays in receiving medical care in adults with atherosclerotic cardiovascular disease.

BACKGROUND: The study aims to compare cost and non-cost factors associated with delays in receiving medical care in adults with atherosclerotic cardiovascular disease (ASCVD). METHODS: Using 2014-2018 data from the Centers for Disease Control and Prevention (CDC) Behaviour Risk Factor Surveillance System (BRFSS) survey (N = 508,203), multivariate logistic regression models were developed to compute the adjusted odds ratio of reasons for delays in medical care in adults with ASCVD. RESULTS: Our study population of 61,227 adults with ASCVD (9.1%) had higher odds of any medical care delay (aOR 1.50, 95% CI 1.43-1.57), delay due to cost (aOR 1.55, 95% CI 1.45-1.65), long clinic wait times (aOR 1.21, 95% CI 1.04-1.39) and lack of transportation (aOR 1.64, 95% CI 1.47-1.84) than those without ASCVD. CONCLUSION: Novel public health and health policy approaches are urgently needed to reduce the cost- and non-cost-related barriers that adults with ASCVD encounter when accessing healthcare services.

Applications of Artificial Intelligence in Emergency Departments to Improve Wait Times: Protocol for an Integrative Living Review.

BACKGROUND: Long wait times in the emergency department (ED) are a major issue for health care systems all over the world. The application of artificial intelligence (AI) is a novel strategy to reduce ED wait times when compared to the interventions included in previous research endeavors. To date, comprehensive systematic reviews that include studies involving AI applications in the context of EDs have covered a wide range of AI implementation issues. However, the lack of an iterative update strategy limits the use of these reviews. Since the subject of AI development is cutting edge and is continuously changing, reviews in this area must be frequently updated to remain relevant. OBJECTIVE: This study aims to provide a summary of the evidence that is currently available regarding how AI can affect ED wait times; discuss the applications of AI in improving wait times; and periodically assess the depth, breadth, and quality of the evidence supporting the application of AI in reducing ED wait times. METHODS: We plan to conduct a living systematic review (LSR). Our strategy involves conducting continuous monitoring of evidence, with biannual search updates and annual review updates. Upon completing the initial round of the review, we will refine the search strategy and establish clear schedules for updating the LSR. An interpretive synthesis using Whittemore and Knafl's framework will be performed to compile and summarize the findings. The review will be carried out using an integrated knowledge translation strategy, and knowledge users will be involved at all stages of the review to guarantee applicability, usability, and clarity of purpose. RESULTS: The literature search was completed by September 22, 2023, and identified 17,569 articles. The title and abstract screening were completed by December 9, 2023. In total, 70 papers were eligible. The full-text screening is in progress. CONCLUSIONS: The review will summarize AI applications that improve ED wait time. The LSR enables researchers to maintain high methodological rigor while enhancing the timeliness, applicability, and value of the review. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/52612.

Relationship between wait times and post-atrial fibrillation ablation outcomes: A population-based study.

BACKGROUND: Rhythm control is a cornerstone of atrial fibrillation (AF) management. Shorter time between diagnosis of AF and receipt of catheter ablation is associated with greater rates of therapy success. Previous work considered diagnosis-to-ablation time as a binary or categorical variable and did not consider the unique risk profile of patients after a referral for ablation was made. OBJECTIVE: The purpose of this study was to comprehensively assess the impact of diagnosis-to-ablation and referral-to-ablation time on postprocedural outcomes at a population level. METHODS: This observational cohort study included patients who received catheter ablation to treat AF in Ontario, Canada. Patient demographics, medical comorbidities, AF diagnosis date, ablation referral date, and ablation date were collected. The primary outcomes of interest included a composite of death and hospitalization/emergency department visit for AF, heart failure, or ischemic stroke. Multivariable Cox models assessed the impact of diagnosis-to-ablation and referral-to-ablation times on the primary outcome. RESULTS: Our cohort included 7472 patients who received ablation for de novo AF between April 1, 2016, and March 31, 2022. Median [interquartile range] diagnosis-to-ablation time was 718 [399-1274] days and median referral-to-ablation time was 221 [117-363] days. Overall, 911 patients (12.2%) had the composite endpoint within 1 year of ablation. Increasing diagnosis-to-ablation time was associated with a greater incidence for the primary outcome (hazard ratio [HR]1.02; 95% confidence interval [CI] 1.01-1.02 per month). Increasing referral-to-ablation time did not impact the primary outcome (HR 1.00; 95% CI 0.98-1.01 per month). CONCLUSION: Delays between AF diagnosis and ablation referral may contribute to adverse postprocedural outcomes and provide an opportunity for health system quality improvements.

Racial differences in triage assessment at rural vs urban Maine emergency departments.

Data continue to accumulate demonstrating that those belonging to racialized groups face implicit bias in the emergency care delivery system across many indices, including triage assessment. The Emergency Severity Index (ESI) was developed and widely implemented across the US to improve the objectivity of triage assessment and prioritization of care delivery; however, research continues to support the presence of subjective bias in triage assessment. We sought to assess the relationship between perceived race and/or need for translator and assigned ESI score and whether this was impacted by hospital geography. We performed retrospective EMR-based review of patients presenting to urban and rural emergency departments of a health system in Maine with one of the top ten most common chief complaints (CC) across a 5-year period, excluding psychiatric CCs. We used multivariable regression to analyze the relationships between perceived race, need for translator, and gender with ESI score, wait time, and hallway bed assignments. We found that patients perceived as non-white were more likely to receive lower acuity ESI scores and have longer wait times as compared to patients perceived as white. Patients perceived as female were more likely to receive lower acuity scores and wait longer to be seen than patients perceived as male. The need for an interpreter was associated with increased wait times but not significantly associated with ESI score. After stratification by hospital geography, evidence of subjective bias was limited to urban emergency departments and was not evident in rural emergency departments. Further investigation of subjective bias in emergency departments in Maine, particularly in urban settings, is warranted.

The Role of Wait Time During the Questioning of Children: A Systematic Review.

The benefits of wait time in classroom discourses have been well documented in the field of education since the 1970s. While current forensic interview guidelines recognize the importance of pauses, whether there is sufficient empirical evidence to inform wait time guidelines in the legal context remains unanswered. This systematic review aimed to synthesize and provide a holistic update on the available research on the role of wait time when questioning children and recommended future direction to develop wait time guidelines specific to child forensic interviews. Systematic searches were conducted using four databases (PsycINFO, MedLine, ERIC, and Scopus). A total of 3,953 unique articles were returned, following a title and abstract screening, 68 full texts were reviewed, and 26 (including five additional studies identified through a hand search) were included. Inclusion criteria were the study sample included children under 18, published a measure of wait time in a questioning context, and in English. Overall, most knowledge of wait time remains in the field of education. Natural wait time is short, but with training, extended wait time yields significant benefits for both child and adult talk. Only one study examined the role of wait time in the forensic interviewing setting where a 10-s wait time appears to be more productive than shorter pauses. Extended wait time is a promising and simple interviewing practice with the potential to facilitate children's disclosure. The current review is a call for research in the area as it pertains to forensic interviewing of children and youth.

Wait Times for Scheduling Appointments for Prevention of Macrovascular and Microvascular Complications of Diabetes: Cross-Sectional Descriptive Study.

BACKGROUND: Diabetes is a chronic disease that requires lifelong management and care, affecting around 422 million people worldwide and roughly 37 million in the United States. Patients newly diagnosed with diabetes must work with health care providers to formulate a management plan, including lifestyle modifications and regular office visits, to improve metabolic control, prevent or delay complications, optimize quality of life, and promote well-being. OBJECTIVE: Our aim is to investigate one component of system-wide access to timely health care for people with diabetes in New York City (NYC), namely the length of time for someone with newly diagnosed diabetes to obtain an appointment with 3 diabetes care specialists: a cardiologist, an endocrinologist, and an ophthalmologist, respectively. METHODS: We contacted the offices of 3 different kinds of specialists: cardiologists, endocrinologists, and ophthalmologists, by telephone, for this descriptive cross-sectional study, to determine the number of days required to schedule an appointment for a new patient with diabetes. The sampling frame included all specialists affiliated with any private or public hospital in NYC. The number of days to obtain an appointment with each specialist was documented, along with "time on hold" when attempting to schedule an appointment and the presence of online booking capabilities. RESULTS: Of the 1639 unique physicians affiliated with (private and public) hospitals in the 3 subspecialties, 1032 (cardiologists, endocrinologists, and ophthalmologists) were in active practice and did not require a referral. The mean wait time for scheduling an appointment was 36 (SD 36.4; IQR 12-51.5) days for cardiologists; 82 (SD 47; IQR 56-101) days for endocrinologists; and 50.4 (SD 56; IQR 10-72) days for ophthalmologists. The median wait time was 27 days for cardiologists, 72 days for endocrinologists, and 30 days for ophthalmologists. The mean time on hold while attempting to schedule an appointment with these specialists was 2.6 (SD 5.5) minutes for cardiologists, 5.4 (SD 4.3) minutes for endocrinologists, and 3.2 (SD 4.8) minutes for ophthalmologists, respectively. Over 46% (158/341) of cardiologists enabled patients to schedule an appointment on the web, and over 55% (128/228) of endocrinologists enabled patients to schedule an appointment on the web. In contrast, only approximately 25% (117/463) of ophthalmologists offered web-based appointment scheduling options. CONCLUSIONS: The results indicate considerable variation in wait times between and within the 3 specialties examined for a new patient in NYC. Given the paucity of research on wait times for newly diagnosed people with diabetes to obtain an appointment with different specialists, this study provides preliminary estimates that can serve as an initial reference. Additional research is needed to document the extent to which wait times are associated with complications and the demographic and socio-economic characteristics of people served by different providers.

Effect of differentiated direct-to-pharmacy PrEP refill visits supported with client HIV self-testing on clinic visit time and early PrEP continuation.

INTRODUCTION: Delivery of oral pre-exposure prophylaxis (PrEP) is being scaled up in Africa, but clinic-level barriers including lengthy clinic visits may threaten client continuation on PrEP. METHODS: Between January 2020 and January 2022, we conducted a quasi-experimental evaluation of differentiated direct-to-pharmacy PrEP refill visits at four public health HIV clinics in Kenya. Two clinics implemented the intervention package, which included direct-to-pharmacy for PrEP refill, client HIV self-testing (HIVST), client navigator, and pharmacist-led rapid risk assessment and dispensing. Two other clinics with comparable size and client volume served as contemporaneous controls with the usual clinic flow. PrEP continuation was evaluated by visit attendance and pharmacy refill records, and time and motion studies were conducted to determine time spent in the clinics. Dried blood spots were collected to test for tenofovir-diphosphate (TFV-DP) at random visits. We used logistic regression to assess the intervention effect on PrEP continuation and the Wilcoxon rank sum test to assess the effect on clinic time. RESULTS: Overall, 746 clients were enrolled, 366 at control clinics (76 during pre-implementation and 290 during implementation phase), and 380 at direct-to-pharmacy clinics (116 during pre-implementation and 264 during implementation phase). Prior to implementation, the intervention and control clinics were comparable on client characteristics (female: 51% vs. 47%; median age: 33 vs. 33 years) and PrEP continuation (35% vs. 37% at 1 month, and 37% vs. 39% at 3 months). The intervention reduced total time spent at the clinic by 35% (median of 51 minutes at control vs. 33 minutes at intervention clinics; p<0.001), while time spent on HIV testing (20 vs. 20 minutes; p = 0.50) and pharmacy (8 vs. 8 minutes; p = 0.8) was unchanged. PrEP continuation was higher at intervention versus the control clinics: 45% versus 33% at month 1, 34% versus 25% at month 3 and 23% versus 16% at month 6. TFV-DP was detected in 85% (61/72) of samples, similar by the study group (83% vs. 85%). CONCLUSIONS: A client-centred PrEP delivery approach with direct-to-pharmacy PrEP refill visits plus client HIVST significantly reduced clinic visit time by more than one-third and improved PrEP continuation in public health HIV clinics in Kenya.

An examination of rectal prolapse surgery patients' quality of life and symptoms using patient-reported outcome instruments: A prospective cohort study.

BACKGROUND: We measured changes in self-reported health and symptoms attributable to rectal prolapse surgery using patient-reported outcome (PRO) measures. METHODS: A prospectively recruited cohort of patients scheduled for rectal prolapse repair in Vancouver, Canada between 2013 and 2021 were surveyed before and 6-months after surgery using seven PROs: the EuroQol Five-Dimension Instrument (EQ-5D-5L), Generalized Anxiety Disorder Scale (GAD-7), Pain Intensity, Interference with Enjoyment of Life and General Activity (PEG), Patient Health Questionnaire (PHQ-9), Fecal Incontinence Severity Index (FISI), Gastrointestinal Quality of Life Index (GIQLI), and the Fecal Incontinence Quality of Life Scale (FIQL). RESULTS: We included 46 participants who reported improvements in health status (EQ-5D-5L; p â€‹< â€‹0.01), pain interference (PEG; p â€‹< â€‹0.01), depressive symptoms (PHQ-9; p â€‹= â€‹0.01), fecal incontinence severity (FISI; p â€‹< â€‹0.01), gastrointestinal quality of life (GIQLI; p â€‹< â€‹0.01), and fecal incontinence quality of life (FIQL) related to lifestyle (p â€‹= â€‹0.02), coping and behaviour (p â€‹= â€‹0.02) and depression and self-perception (p â€‹= â€‹0.01). CONCLUSION: Surgical repair of rectal prolapse improved patients' quality of life with meaningful improvements in fecal incontinence severity and pain, and symptom interference with daily activities.

The majority of parents of children undergoing genetic testing report preference for earlier genetic counseling appointments.

In the Indiana University Health (IUH) Medical Genetics clinic, certified genetic counselors disclose genetic test results to patients by telephone. The wait-time between a result call-out and a follow-up appointment can vary from weeks to months depending on the medical geneticist's availability. Understanding the experiences that families face during these waiting periods can inform the field regarding what clinical improvements can be made to enhance patients' experiences. Our study explored three topics: the effects of wait-times on parents or patients between a result disclosure and medical genetics follow-up appointment, their anxiety levels during those wait-times, and suggestions for improving parents' and patients' experiences with genetics clinics. Patients or parents who were over 18 years old, who received an initial result call-out between May 2020 and September 2022 prior to a medical genetics follow-up appointment, and who had a diagnostic or a variant of uncertain significance (VUS) genetic test result were recruited for study participation. Individuals were surveyed on their diagnosis, wait-time following result disclosure, feelings during the wait-time, and preferences for result disclosures. The results showed that length of wait-time after a result call-out was not associated with increased anxiety; however, a background in genetics and support group involvement were associated with increased anxiety. The majority of respondents reported that if a genetic counseling-only appointment could occur closer to the time of results call-out, they would prefer to have a genetic counseling-only appointment with a second appointment for medical management with a geneticist later (58.1%). Based on these results, medical genetics clinics should consider implementing genetic counseling-only appointments to reduce wait-times for follow-up appointments.

Moderating Effects of Individual Traits on the Association Between Nature and Patient Wait Experiences.

OBJECTIVES: We empirically investigated to what extent plants in the emergency department (ED) waiting areas influence patient wait experiences (i.e., anxiety, perceived service quality, and perception of wait time) depending on individual differences in cognitive thinking styles and one's bonds with the natural world. BACKGROUND: Positive effects of nature on patient experiences in healthcare environments are well established by empirical research findings. However, evidence is scarce on the impact of nature on patient wait experiences and the roles of patient traits often related to their backgrounds. METHODS: A within-subjects study was conducted (N = 116) with two virtually built ED waiting rooms: with versus without indoor and outdoor plants. RESULTS: Findings confirmed that plants lower anxiety and improve perceptions of service quality and wait time. Cognitive thinking style significantly moderated how plants affected patient wait experiences. Although participants with higher connectedness to nature showed more positive responses to the nature condition, connectedness to nature did not significantly affect the association between nature and wait experiences. CONCLUSIONS: This study contributes to the existing body of knowledge on nature's effects in healthcare environments by examining the roles of individual differences in patients' and visitors' cognitive styles and connectedness to nature. Results highlighted the impact of these differences in patient experiences for effective implications of nature in waiting areas of healthcare facilities.

Predicting wait time for pediatric kidney transplant: a novel index.

BACKGROUND: Over one thousand pediatric kidney transplant candidates are added to the waitlist annually, yet the prospective time spent waiting is unknown for many. Our study fills this gap by identifying variables that impact waitlist time and by creating an index to predict the likelihood of a pediatric candidate receiving a transplant within 1 year of listing. This index could be used to guide patient management by giving clinicians a potential timeline for each candidate's listing based on a unique combination of risk factors. METHODS: A retrospective analysis of 3757 pediatric kidney transplant candidates from the 2014 to 2020 OPTN/UNOS database was performed. The data was randomly divided into a training set, comprising two-thirds of the data, and a testing set, comprising one-third of the data. From the training set, univariable and multivariable logistic regressions were used to identify significant predictive factors affecting wait times. A predictive index was created using variables significant in the multivariable analysis. The index's ability to predict likelihood of transplantation within 1 year of listing was validated using ROC analysis on the training set. Validation of the index using ROC analysis was repeated on the testing set. RESULTS: A total of 10 variables were found to be significant. The five most significant variables include the following: blood group, B (OR 0.65); dialysis status (OR 3.67); kidney disease etiology, SLE (OR 0.38); and OPTN region, 5 (OR 0.54) and 6 (OR 0.46). ROC analysis of the index on the training set yielded a c-statistic of 0.71. ROC analysis of the index on the testing set yielded a c-statistic of 0.68. CONCLUSIONS: This index is a modest prognostic model to assess time to pediatric kidney transplantation. It is intended as a supplementary tool to guide patient management by providing clinicians with an individualized prospective timeline for each candidate. Early identification of candidates with potential for prolonged waiting times may help encourage more living donation including paired donation chains.

Does waiting for surgery matter? How time from diagnostic MRI to resection affects outcomes in newly diagnosed glioblastoma.

OBJECTIVE: Maximal safe resection is the standard of care for patients presenting with lesions concerning for glioblastoma (GBM) on magnetic resonance imaging (MRI). Currently, there is no consensus on surgical urgency for patients with an excellent performance status, which complicates patient counseling and may increase patient anxiety. This study aims to assess the impact of time to surgery (TTS) on clinical and survival outcomes in patients with GBM. METHODS: This is a retrospective study of 145 consecutive patients with newly diagnosed IDH-wild-type GBM who underwent initial resection at the University of California, San Francisco, between 2014 and 2016. Patients were grouped according to the time from diagnostic MRI to surgery (i.e., TTS): ≤ 7, > 7-21, and > 21 days. Contrast-enhancing tumor volumes (CETVs) were measured using software. Initial CETV (CETV1) and preoperative CETV (CETV2) were used to evaluate tumor growth represented as percent change (ΔCETV) and specific growth rate (SPGR; % growth/day). Overall survival (OS) and progression-free survival (PFS) were measured from the date of resection and were analyzed using the Kaplan-Meier method and Cox regression analyses. RESULTS: Of the 145 patients (median TTS 10 days), 56 (39%), 53 (37%), and 36 (25%) underwent surgery ≤ 7, > 7-21, and > 21 days from initial imaging, respectively. Median OS and PFS among the study cohort were 15.5 and 10.3 months, respectively, and did not differ among the TTS groups (p = 0.81 and 0.17, respectively). Median CETV1 was 35.9, 15.7, and 10.2 cm3 across the TTS groups, respectively (p < 0.001). Preoperative biopsy and presenting to an outside hospital emergency department were associated with an average 12.79-day increase and 9.09-day decrease in TTS, respectively. Distance from the treating facility (median 57.19 miles) did not affect TTS. In the growth cohort, TTS was associated with an average 2.21% increase in ΔCETV per day; however, there was no effect of TTS on SPGR, Karnofsky Performance Status (KPS), postoperative deficits, survival, discharge location, or hospital length of stay. Subgroup analyses did not identify any high-risk groups for which a shorter TTS may be beneficial. CONCLUSIONS: An increased TTS for patients with imaging concerning for GBM did not impact clinical outcomes, and while there was a significant association with ΔCETV, SPGR remained unaffected. However, SPGR was associated with a worse preoperative KPS, which highlights the importance of tumor growth speed over TTS. Therefore, while it is ill advised to wait an unnecessarily long time after initial imaging studies, these patients do not require urgent/emergency surgery and can seek tertiary care opinions and/or arrange for additional preoperative support/resources. Future studies are needed to explore subgroups for whom TTS may impact clinical outcomes.

Racial and Ethnic Disparities in Emergency Department Wait Times for Headache.

Headache is a common complaint of individuals seeking treatment in the emergency department (ED). Because pain is subjective, medical evaluation is susceptible to implicit bias that can lead to disparities in wait times. The aim of this study was to determine whether there are racial and ethnic disparities in ED wait times for headache. Our study used the 2015-2018 National Hospital Ambulatory Care Surveys (NHAMCS), a nationally representative sample of ambulatory care visits to EDs. Our sample consisted of visits made by adults for headaches, which were identified using ICD-10 diagnosis codes and NHAMCS reason for visit codes. There were 12,301,655 ED visits for headache represented by our sample. The mean wait time for headache visits was 38.1 min (95%CI: 31.1, 45.0). The mean wait time for Non-Hispanic White patients, non-Hispanic Black patients, Hispanic patients, and the other race and ethnicity groups were 34.7 min (95%CI: 27.5, 42.0), 46.4 min (95%CI: 26.5, 66.4), 37.9 min (95%CI: 19.4, 56.3), and 21.0 min (95%CI: 6.3, 35.7) respectively. After controlling for patient- and hospital-level covariates, visits by non-Hispanic Black patients had 40% (95%CI: -0.01, 0.81, p = 0.056) longer wait times and visits by Hispanic patients had 39% (95%CI: -0.03, 0.80, p = 0.068) longer wait times than visits by non-Hispanic White patients. While our findings suggest that there may be longer wait times for visits by non-Hispanic Black and Hispanic patients compared to visits by non-Hispanic White patients, further research is needed to confirm these findings and determine causes of wait times disparities in the ED.

Intended and unintended consequences of strategies to meet performance benchmarks for rheumatologist referrals in a centralized intake system.

RATIONALE: Timely assessment of a chronic condition is critical to prevent long-term irreversible consequences. Patients with inflammatory arthritis (IA) symptoms require diagnosis by a rheumatologist and intervention initiation to minimize potential joint damage. With limited rheumatologist capacity, meeting urgency wait time benchmarks can be challenging. We investigate the impact of the maximum wait time guarantee (MWTG) policy and referral volume changes in a rheumatology central intake (CI) system on meeting this challenge. METHODS: We applied a system simulation approach to model a high-volume CI rheumatology clinic. Model parameters were based on the referral and triage data from the CI and clinic appointment data. We compare the wait time performance of the current distribution policy MWTG and when referral volumes change. RESULTS: The MWTG policy ensures 100% of new patients see a rheumatologist within their urgency wait time benchmark. However, the average wait time for new patients increased by 51% (178-269 days). A 10% decrease in referrals resulted in a 76% decrease on average wait times (178-43 days) for new patients and an increase in the number of patients seen by a rheumatologist within 1 year of the initial visit. CONCLUSION: An MWTG policy can result in intended and unintended consequences-ensuring that all patients meet the wait time benchmarks but increasing wait times overall. Relatively small changes in referral volume significantly impact wait times. These relationships can assist clinic managers and policymakers decide on the best approach to manage referrals for better system performance.

Use of Coordinator Role Improves Access to Rheumatologic Advanced Therapy.

OBJECTIVE: Delays in initiation of advanced therapies, which include biologics and targeted synthetic disease-modifying antirheumatic drugs, contribute to poor patient outcomes. The objective of this quality improvement project was to identify factors that lead to a delay in the initiation of advanced therapy and to perform plan-do-study-act cycles to decrease the time to start advanced therapy. METHODS: A retrospective chart review identified factors involved in delay to start advanced therapy. The primary outcome of the study was the number of days to advanced therapy start as measured by the date of rheumatologist recommendation to the date advanced therapy was initiated by the patient. An Advanced Therapy Coordinator role was created to standardize the workflow, optimize communication, and ensure a safety checklist was instituted. RESULTS: A total of 125 patients were reviewed for the study with 18 excluded. Preintervention median wait time was 82.0 (IQR 46.0-80.5) days. Median wait time during the intervention improved to 49.5 (IQR 34.0-69.5) days (April 2021 to January 2022), with nonrandom variation post intervention. Nonrandom variation was also noted in the latter baseline data (March 2020 to March 2021). CONCLUSION: This study demonstrates improved wait time to advanced therapy initiation through the role of an Advanced Therapy Coordinator to facilitate communication pathways.