Socioeconomic factors influence surgical wait times for non-emergent gynecologic surgical procedures: a retrospective analysis.

BACKGROUND: In various disciplines, an association between surgical wait times and patient outcomes has been identified. This study is among the first to investigate whether practice setting influences wait times for elective surgeries in benign gynecology. METHODS: This retrospective study of patients at three New York hospitals from 10/2019-2/2020 compared surgical wait times among patients seen in federally-qualified health centers (FQHC's) and private practice settings. Emergent surgeries, oncology cases, abortions, urogynecology procedures, and cases concurrently booked with another specialty were excluded. Surgical wait time was defined as the time (days) from the decision to operate to the day of the procedure. A multivariable mixed model was used to model surgical wait time by setting of care, adjusting for age, BMI, race, ethnicity, insurance, need for medical clearance, and scheduled block time. A univariable analysis was then utilized to assess surgical wait times by clinical setting for each insurance type. RESULTS: Five hundred forty patients were identified with a median age of 45.6 years (range 16-87). Average surgical wait time was 27 days (range 1-288 days). In multivariable analysis, longer surgical wait times were associated with being seen preoperatively in a FQHC compared to the private practice setting (102% longer, 59.5 days vs. 22 days, p < 0.0001), and with needing medical clearance (56.4% longer, 45 days vs. 22 days. p = 0.0001). CONCLUSIONS: These results suggest that in benign gynecology, surgical wait times are significantly influenced by the practice setting in which a patient gets care, with notable delays in care among patients who are seen in a federally qualified health center preoperatively.

Access to child developmental assessment services in culturally and linguistically diverse metropolitan Sydney: a retrospective cohort analysis.

BACKGROUND: Despite the increasing prevalence of neurodevelopmental disorders (NDD), data regarding access to child development services have remained limited globally. Long wait times are a major barrier to developmental assessments, impacting on care and outcomes. The aim is to retrospectively analyse the demographic profile and prioritisation of patients seen at a child developmental assessment service (CDAS) in a vulnerable region of Sydney, and explore factors affecting wait times. METHODS: Data was collated and analysed for 2354 patients from 2018 to 2022. Socio-Economic Indexes for Areas (SEIFA) were collated from the Australian Bureau of Statistics. Descriptive statistics were used for demographic data and various statistical methods were used to analyse the relationships and impact of factors likely to affect wait lists. RESULTS: The median age was 51 months (IQR41-61) and males comprised 73.7% of the cohort. 64% of children were from culturally and linguistically diverse backgrounds (CALD) and 47% lived in the most disadvantaged suburbs. The median wait time was 302.5 days (IQR175-379) and 70% of children were seen within 12 months. CALD patients and children over 5-years had shorter wait times. Most children with Global Developmental Delay (GDD) were from the lowest four SEIFA deciles and waited longer for an appointment. 42.6% were seen within the priority allocated time or sooner. Children with ASD and/or severe GDD were prioritised to be seen earlier. Overall, the study could not demonstrate any difference in the wait times according to the prioritisation groups. CONCLUSION: This study provides insights into the profile, prioritisation processes and wait lists of children seen by CDAS in South Western Sydney with high rates of social vulnerability and presents an argument to discuss benchmarking targets with service providers. It identifies the need to prioritise children living in suburbs with socioeconomic disadvantage and refine prioritisation and data collection processes to improve wait times.

Health-related quality of life does not deteriorate while waiting for anterior cruciate reconstruction.

PURPOSE: The aim of this study was to determine how preoperative health-related quality of life (HRQoL) is affected by the duration of the wait time (WT) for anterior cruciate ligament reconstruction (ACLR) once a decision is made to proceed with surgery. METHODS: This was a multi-centre prospective cohort study. One hundred and twenty-two patients 14 years of age and above waiting for ACLR completed the International Knee Documentation Committee (IKDC) demographic, current health assessment and subjective knee evaluation (SKF) forms on the day of decision to operate and the day of surgery. Changes in scores were analyzed for the entire cohort, adjusted for WTs and a subset was compared for patients with isolated anterior cruciate ligament (ACL) tears and ACL tears with concurrent meniscal involvement. Changes in HRQoL scores from the day of the decision to operate to the 9-month postoperative appointments were also assessed. RESULTS: Energy/Fatigue (p < 0.05), Pain (p < 0.05), General Health (p < 0.05) and the IKDC-SKF Score (p < 0.05) significantly increased between the day of the decision to operate and the day of surgery. Only the change in IKDC-SKF score remained significantly higher after adjusting for WT. Baseline HRQoL scores significantly improved by the 9-month postoperative appointment. CONCLUSION: The length of time waiting for ACLR did not adversely influence HRQoL in this study. However, low preoperative HRQoL and the significant improvement in HRQoL of patients followed postoperatively suggest that timely surgery is beneficial for this patient population. LEVEL OF EVIDENCE: Level II.

A National Survey of Obstetrics and Gynecology Resident Perspectives on Their Preparedness to Provide Care for Underserved Patients with Gynecologic Malignancies.

Obstetrics and Gynecology (Ob/Gyn) residents will encounter, screen for, and diagnose gynecologic malignancies. This survey assessed residents' confidence in providing NCCN Guidelines-based care to Gynecologic Oncology patients of differing racial/ethnic backgrounds and insurance statuses while accounting for residents' backgrounds. An anonymous, novel Qualtrics survey was disseminated to current US Ob/Gyn residents, with multiple-choice questions about subject demographics and Likert scale questions about their readiness to care for diverse patients. Differences in responses between racial groups were analyzed using the Kruskal-Wallis Rank Sum test. Differences in responses between ethnic groups were evaluated using the Wilcoxon Rank Sum test. Regardless of their backgrounds, residents feel "somewhat prepared" to care for diverse patients. There was no statistical between ethnic groups regarding confidence in caring for racial minorities or insurance types. Similarly, there was no statistical difference between racial groups regarding caring for racial minorities, but a difference did exist for insurance types (p = 0.027). No significant racial/ethnic differences were found in opinions on trial enrollment or chemotherapy delays, though most residents agreed that racial/ethnic minorities face delays in chemotherapy. Finally, resident ethnicity and race both impacted resident perceptions of difficulties for Medicaid and minority patients in obtaining non-operative gynecologic care (p = 0.044; p = 0.017) and scheduling outpatient appointments (p = 0.016; p = 0.032). Ob/Gyn residents feel prepared to provide NCCN Guidelines-based care to socioeconomically diverse patients with gynecologic malignancies, though differences exist when accounting for residents' racial/ethnic backgrounds. These results reflect the importance of emphasizing on culturally competent care in residency, particularly for patients with cancer.

Effect of a National VHA Medical Scribe Pilot on Provider Productivity, Wait Times, and Patient Satisfaction in Cardiology and Orthopedics.

BACKGROUND: Section 507 of the VA MISSION Act of 2018 mandated a 2-year pilot study of medical scribes in the Veterans Health Administration (VHA), with 12 VA Medical Centers randomly selected to receive scribes in their emergency departments or high wait time specialty clinics (cardiology and orthopedics). The pilot began on June 30, 2020, and ended on July 1, 2022. OBJECTIVE: Our objective was to evaluate the impact of medical scribes on provider productivity, wait times, and patient satisfaction in cardiology and orthopedics, as mandated by the MISSION Act. DESIGN: Cluster randomized trial, with intent-to-treat analysis using difference-in-differences regression. PATIENTS: Veterans using 18 included VA Medical Centers (12 intervention and 6 comparison sites). INTERVENTION: Randomization into MISSION 507 medical scribe pilot. MAIN MEASURES: Provider productivity, wait times, and patient satisfaction per clinic-pay period. KEY RESULTS: Randomization into the scribe pilot was associated with increases of 25.2 relative value units (RVUs) per full-time equivalent (FTE) (p < 0.001) and 8.5 visits per FTE (p = 0.002) in cardiology and increases of 17.3 RVUs per FTE (p = 0.001) and 12.5 visits per FTE (p = 0.001) in orthopedics. We found that the scribe pilot was associated with a decrease of 8.5 days in request to appointment day wait times (p < 0.001) in orthopedics, driven by a 5.7-day decrease in appointment made to appointment day wait times (p < 0.001), and observed no change in wait times in cardiology. We also observed no declines in patient satisfaction with randomization into the scribe pilot. CONCLUSIONS: Given the potential improvements in productivity and wait times with no change in patient satisfaction, our results suggest that scribes may be a useful tool to improve access to VHA care. However, participation in the pilot by sites and providers was voluntary, which could have implications for scalability and what effects could be expected if scribes were introduced to the care process without buy-in. Cost was not considered in this analysis but is an important factor for future implementation. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04154462.

Medicaid coverage and access to obstetrics and gynecology subspecialists: findings from a national mystery caller study in the United States.

BACKGROUND: Previous research suggests that access to healthcare may influence the diagnosis and treatment of obstetrical and gynecologic pathologies. Audit studies, a single-blinded and patient-centered design, have been employed to measure access to care for health services. To date, no study has assessed the dimensions of access to obstetrics and gynecologic subspecialty care based on insurance type (Medicaid vs commercial). OBJECTIVE: This study aimed to evaluate the mean appointment wait time for a new patient visit to female pelvic medicine and reconstructive surgery, gynecologic oncology, maternal-fetal medicine, and reproductive endocrinology and infertility when presenting with Medicaid vs commercial insurance. STUDY DESIGN: Each subspecialty medical society has a patient-facing physician directory of physicians across the United States. Of note, 800 unique physicians were randomly selected from the directories (200 per subspecialty). Of the 800 physicians, each physician was called twice. The caller presented with Medicaid or, in a separate call, with Blue Cross Blue Shield. The order in which the calls were placed was randomized. The caller asked for the soonest appointment available for respective medical conditions based on subspecialty: stress urinary incontinence, new-onset pelvic mass, preconceptual counseling after an autologous kidney transplant, and primary infertility. RESULTS: From 800 physicians initially contacted, 477 responded to at least 1 call in 49 states plus the District of Columbia. The mean appointment wait time was 20.3 business days (standard deviation, ±18.6). A significant difference was found in new patient appointment wait times by type of insurance, with 44% longer wait time for Medicaid (ratio, 1.44; 95% confidence interval, 1.34-1.54; P<.001). When the interaction between insurance type and subspecialty was added to the model, it was also highly significant (P<.01). More specifically, Medicaid patients in female pelvic medicine and reconstructive surgery had a longer wait time than commercially insured patients. Patients seeking care in maternal-fetal medicine had the least difference, but Medicaid-insured patient wait times were still longer than commercial-insured patient wait times. CONCLUSION: Typically, a patient can expect to wait 20.3 days for a new patient appointment with a board-certified obstetrics and gynecology subspecialist. Callers presenting with Medicaid insurance experienced significantly longer new patient appointment wait times than callers with commercial insurance.

Variation and clinical consequences of wait-times for atrial fibrillation ablation: population level study in Ontario, Canada.

AIMS: Atrial fibrillation (AF) is the most common cardiac rhythm disorder. Emerging evidence supporting the efficacy of catheter ablation in managing AF has led to increased demand for this therapy, potentially outpacing the capacity to perform this procedure. Mismatch between demand and capacity for AF ablation results in wait-times which have not been comprehensively evaluated at a population level. Additionally, the consequences of such delays in AF ablation, namely the risk of hospitalization or adverse events, have not been studied. METHODS AND RESULTS: This observational cohort study included adults referred for catheter ablation to treat AF in Ontario, Canada, between 1 April 2016 and 31 March 2020. Wait-time was defined from referral to the earliest of ablation, death, off-list, or the study endpoint of 31 March 2022. The outcomes of interest included a composite of death, hospitalization for AF/heart failure, and emergency department visit for AF/heart failure. Our study cohort included 6253 patients referred for de novo AF ablation. The median wait-time for patients who received and who did not receive ablation was 218 days (IQR: 112-363) and 520 days (IQR: 270-763), respectively. Wait-time increased consistently for patients referred between October 2017 and March 2020. Mortality was rare, but significant morbidity was observed, affecting 19.2% of patients on the waitlist for AF ablation. Paroxysmal AF was associated with a statistically significant greater risk for adverse outcomes on the waitlist (HR 1.51, 95% CI 1.18-1.93). CONCLUSION: Wait-times for AF ablation are increasing and are associated with significant morbidity.

Racial variation in baseline characteristics and wait times among patients undergoing bariatric surgery.

BACKGROUND: Although bariatric surgery is the most effective treatment for obesity and weight-related comorbid diseases, utilization rates are disproportionately low among non-white patients. We sought to understand if variation in baseline characteristics or access to care exists between white and non-white patients. METHODS: Using a statewide bariatric-specific data registry, we evaluated all patients who underwent bariatric surgery between 2006 and 2020 and completed a preoperative baseline questionnaire, which included a question about self-identification of race. Patient characteristics, co-morbidities, and time from initial preoperative clinic evaluation to date of surgery were compared among racial groups. RESULTS: A total of 73,141 patients met inclusion criteria with 18,741 (25.5%) self-identified as non-white. These included Black/African American (n = 11,904), Hispanic (n = 3448), Asian (n = 121), Native Hawaiian/Pacific Islander (n = 41), Middle Eastern (n = 164), Multiple (n = 2047) and other (n = 608). Non-white males were the least represented group, accounting for only 4% of all bariatric cases performed. Non-white patients were more likely to be younger (43.0 years vs. 46.6 years, p < 0.0001), disabled (16% vs. 11.4%, p < 0.0001) and have Medicaid (8.4% vs. 3.8%, p < 0.0001) when compared to white patients, despite having higher rates of college education (78.0% vs. 76.6, p < 0.0001). In addition, median time from initial evaluation to surgery was also longer among non-white patients (157 days vs. 127 days, p < 0.0001), despite having higher rates of patients with a body mass index above 50 kg/m2 (39.0% vs. 33.2%, p < 0.0001). CONCLUSIONS: Non-white patients undergoing bariatric surgery represent an extremely diverse group of patients with more socioeconomic disadvantages and longer wait times when compared to white patients despite presenting with higher rates of severe obesity. Current guidelines and referral patterns for bariatric surgery may not be equitable and need further examination when considering the management of obesity within diverse populations to reduce disparities in care-of which non-white males are particularly at risk.

Variations in wait times for imaging services: a register-based study of self-reported wait times for specific examinations in Norway.

BACKGROUND: While the number of medical images has increased substantially, the demand has outpaced access, resulting in long wait times in many countries. Long wait times are a key problem for patient safety and quality of care as they can result in prolonged suffering, delayed diagnosis and treatment, as well as poorer prognosis and loss of lives. Surprisingly, little is known about wait times for imaging services. OBJECTIVE: Investigate wait times for specific imaging services in Norway and to compare wait times with the total number of examinations and their development over time. METHODS: Data from the wait time registry at the Norwegian Directorate of Health from 2018 to 2021 as well as data on outpatient imaging provided by the Norwegian Health Economics Administration (HELFO) and in-patient data afforded by fourteen hospital trusts and hospitals in Norway were analysed. Data include the total number of imaging examinations according to the Norwegian Classification of Radiological Procedures (NCRP). Analyses were performed with descriptive statistics. RESULTS: Wait times vary through the months of the year. Conventional X-ray (XR) had the shortest wait times (3.0-4.4 weeks), and Magnetic Resonance Imaging (MRI) and ultrasound (US) had the lengthiest (8.7-12.0 and 7.9-11.4 weeks respectively). The wait times were lengthiest during the summer and winter holidays. Variations in wait times were also found for specific examination types between Norway's four public health regions. In addition, there was variation over time within the health regions. The wait times with the private health providers were substantially lower than with the public health providers. From 2018 to 2021, the wait time for MRIs increased by 6.6%, while the number of examinations (per 10,000) increased by 8.6%. Those regions with the highest number of examinations per 1,000 inhabitants per year had the lowest wait times. CONCLUSION: Wait times for diagnostic imaging procedures varied with time, region, and modality in Norway from 2018 to 2021. Long wait times may entail many negative consequences for patients, professionals, and the healthcare system. Reducing long wait times is an obvious way to improve the quality, safety, and efficiency of care.

Reducing Wait Times for Radiology Exams Around Holiday Periods: A Monte Carlo Simulation.

Reducing patient wait times is a key operational goal and impacts patient outcomes. The purpose of this study is to explore the effects of different radiology scheduling strategies on exam wait times before and after holiday periods at an outpatient imaging facility using computer simulation. An idealized Monte Carlo simulation of exam scheduling at an outpatient imaging facility was developed based on the actual distribution of scheduled exams at outpatient radiology sites at a tertiary care medical center. Using this simulation, we examined three scheduling strategies: (1) no scheduling modifications, (2) increase imaging capacity before or after the holiday (i.e. increase facility hours), and (3) use a novel rolling release scheduling paradigm. In the third scenario, a fraction of exam slots are blocked to long-term follow-up exams and made available only closer to the exam date, thereby preventing long-term follow-up exams from filling the schedule and ensuring slots are available for non-follow-up exams. We examined the effect of these three scenarios on utilization and wait times, which we defined as the time from order placement to exam completion, during and after the holiday period. The baseline mean wait time for non-follow-up exams was 5.4 days in our simulation. When no scheduling modifications were made, there was a significant increase in wait times in the week preceding the holiday when compared to baseline (10.0 days vs 5.4 days, p < 0.01). Wait times remained elevated for 4 weeks following the holiday. Increasing imaging capacity during the holiday and post-holiday period by 20% reduced wait times by only 6.2% (9.38 days vs 10.0 days, p < 0.01). Increasing capacity by 50% resulted in a 7.1% reduction in wait times (9.28 days, p < 0.01), and increasing capacity by 100% resulted in a 13% reduction in wait times (8.75 days, p < 0.01). In comparison, using a rolling release model produced a reduction in peak wait times equivalent to doubling capacity (8.76 days, p < 0.01) when 45% of slots were reserved. Improvements in wait times persisted even when rolling release was limited to the 3 weeks preceding or 1 week following the holiday period. Releasing slots on a rolling basis did not significantly decrease utilization or increase wait times for long-term follow-up exams except in extreme scenarios where 80% or more of slots were reserved for non-follow-up exams. A rolling release scheduling paradigm can significantly reduce wait time fluctuations around holiday periods without requiring additional capacity or impacting utilization.

Preoperative echocardiogram does not increase time to surgery in hip fracture patients with prior percutaneous coronary intervention.

BACKGROUND: The purpose of this study was to (1) assess the effect of preoperative echocardiogram on time to surgery and (2) assess the outcomes of patients with a previous percutaneous coronary intervention (PCI). METHODS: Demographic, clinical, quality and cost data were obtained and a validated risk predictive tool (STTGMA) was calculated for each of a consecutive series of hip fracture patients. Comparative analyses of patients who had an echocardiogram prior to surgery or a PCI prior to hospitalization were performed. RESULTS: Between 2014 and 2020, 2625 patients presented to our institution with a hip fracture. From this cohort 471 patients underwent a preoperative transthoracic echocardiogram (TTE), 30 who had a history of a PCI, and an additional 26 who had a history of PCI but did not undergo a preoperative TTE. Those undergoing a preoperative TTE had similar time (days) to surgery (1.73 vs 1.77, p = 0.86) and 30-day mortality (4% vs 7%, p = 0.545) regardless of PCI history. PCI patients who underwent a preoperative TTE experienced increased rates of 1-year mortality (27% vs 10%, p = 0.007) and major complications (23% vs 12%, p = 0.08) compared to those without a PCI history. PCI patients undergoing a preoperative TTE had a similar time (days) to surgery (1.77 vs 1.48, .p = 0.397) compared to PCI patients without a preoperative TTE. Patients who underwent a preoperative TTE had higher rates of 90-day readmission (31.0% vs 8.0%, p = 0.047) and 1-year mortality (26.7% vs 3.8%, p = 0.029). CONCLUSIONS: Having a preoperative TTE does not affect surgical wait times in hip fracture patients regardless of PCI history, but it may not improve mortality outcomes or reduce postoperative complications in patients with a history of a PCI.

Improvements in Severe Acute Respiratory Syndrome Coronavirus 2 Testing Cascade in the United States: Data From Serial Cross-sectional Assessments.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing is critical for monitoring case counts, early detection and containment of infection, clinical management, and surveillance of variants. However, community-based data on the access, uptake, and barriers to testing have been lacking. METHODS: We conducted serial cross-sectional online surveys covering demographics, coronavirus disease 2019 symptoms, and experiences around SARS-CoV-2 diagnostic testing to characterize the SARS-CoV-2 testing cascade and associated barriers across 10 US states (California, Florida, Illinois, Maryland, Massachusetts, Nebraska, North Dakota, South Dakota, Texas, and Wisconsin), from July 2020 to February 2021. RESULTS: In February 2021, across 10 US states, 895 respondents (11%) reported wanting a diagnostic test in the prior 2 weeks, 63% of whom were tested, with limited variability across states. Almost all (97%) who were tested received their results; 56% received their results within 2 days. In Maryland, Florida, and Illinois, where serial data were available at 4 time points, 56% were tested the same day they wanted or needed a test in February 2021, compared with 28% in July 2020, and 45% received results the same day, compared with 17% in July 2020. Wanting a test was significantly more common among younger, nonwhite respondents and participants with a history of symptoms or exposure. Logistical challenges, including not knowing where to go, were the most frequently cited barriers. CONCLUSIONS: There were significant improvements in access and turnaround times across US states, yet barriers to testing remained consistent across states, underscoring the importance of a continued focus on testing, even amidst mass vaccination campaigns.

The impact of preoperative imaging on wait times, surgical approach and overall survival in endometrioid endometrial cancers.

OBJECTIVES: Routine preoperative axial imaging studies (CT/MRI) are not recommended for endometrioid endometrial cancer as they are unlikely to change management and may delay surgery. This study evaluated the association of receiving preoperative imaging on various outcomes. METHODS: A population-based cohort of Endometrioid Endometrial Cancer cases from 2006 to 2016 were identified from the Cancer Registry in Ontario, Canada. Wait time to surgery, type of surgery and overall survival were evaluated in patients with and without preoperative imaging. Predictive factors for wait time > 56 days and aggressive surgery (radical hysterectomy / lymphadenectomy) were determined using multivariable regression analysis. RESULTS: 13,050 cases were included. 22.6% of patients received preoperative imaging, mainly CT scans. Most patients (95.9%) received no neoadjuvant treatment. Patients with preoperative imaging were more likely to have neoadjuvant treatment (11.7% vs. 1.8%) and less likely to have surgery at 180 days post diagnosis (87.9% vs 94.6%). Patients with preoperative imaging had median wait time to surgery of 64 days (47-87), compared to 53 days (36-74) than those without imaging (p < 0.001). Multivariable modeling showed preoperative imaging was associated with decreased odds of having surgery within 56 days (OR = 0.68, 95% CI = 0.62-0.75), and increased odds (OR = 1.73, 95% CI = 1.53-1.95) of having aggressive surgery. The 5-year overall survival for patients with imaging was 84.8% versus 91.1% for patients without preoperative imaging. CONCLUSIONS: Preoperative imaging was associated with longer wait times to surgery, more aggressive surgery, surgery with a gynecologic oncologist and increased use of neoadjuvant and adjuvant treatment. In early-stage disease there was no observed improvement in overall survival for patients with preoperative imaging. Further research on potential benefits of preoperative imaging in higher risk patients is required.

Pre-operative wait times in high-grade non-endometrioid endometrial cancer: Do surgical delays impact patient survival?

OBJECTIVE: Practice guidelines advocating for regionalization of endometrial cancer surgery to gynecologic oncologists practicing in designated gynecologic oncology centres were published in Ontario in June 2013. Our objectives were to determine whether this policy affected surgical wait times, and whether longer wait time to surgery is a predictor of survival in high grade endometrial cancer patients. METHODS: This was a population-based retrospective cohort study, which included patients diagnosed with high-grade non-endometrioid endometrial cancer who had a hysterectomy between 2003 and 2017. Multivariable Cox proportional hazards regression with a spline function was used to model the relationship between surgical wait time and overall survival (OS). RESULTS: We identified 3518 patients who underwent hysterectomy for high-grade non-endometrioid endometrial cancer. Patients who had surgery with a gynecologic oncologist had a median surgical wait time from diagnosis to hysterectomy of 53 days compared to 57 days pre-regionalization (p = 0.0007), and from first gynecologic oncology consultation to hysterectomy of 29 days compared to 32 days pre-regionalization (p = 0.0006). Survival was inferior for patients who had surgery within 14 days of diagnosis (HR death 2.7 for 1-7 days, 95% CI 1.61-4.51, and HR death 1.96 for 8-14 days, 95% CI 1.50-2.57), reflective of disease severity. Decreased survival occurred with surgical wait times of more than 45 days from the patient's first gynecologic oncology appointment (HR death 1.19 for 46-60 days, 95% CI 1.04-1.36, and HR death 1.42 for 61-75 days, 95% CI 1.11-1.83). CONCLUSIONS: Regionalization of surgery for high-grade endometrial cancer has not had an impact on surgical wait times. Patients who have surgery more than 45 days after surgical consultation have reduced survival.

Do racial disparities exist at various time points during an emergency department visit for chest pain.

INTRODUCTION: It is well documented that disparities in patient care based on race and ethnicity are prevalent in the emergency medical care setting. In most cases these evaluations are patient focused and outcome based. The timeliness of patient treatment in the emergency department (ED) is correlated with patient outcomes. In this study, we sought to evaluate whether the timeliness of care for patients with chest pain across stages of care was impacted by patient race. METHODS: This was a retrospective evaluation of ED throughput times including adults who presented to one of seventeen EDs in a large healthcare system from January 1, 2019 to December 31, 2019 and met criteria for inclusion. The effect of race on different intervals of care were assessed. Generalized Linear Models were used to estimate the effect of race on different intervals of care while controlling for Charlson Comorbidity index, age, gender, insurance, ED facility type and emergency severity index acuity level. RESULTS: A total of 28,705 patients were included, with a mean age of 54 ± 18 years. The majority of patients were White (63%), female (56%) and had Medicare or Medicaid (56%). Black patients experienced significantly increased wait times for resident physician examination, advanced practice provider examination, attending physician examination, and ED disposition. There was no difference in time to triage between Black patients and White patients. CONCLUSION: Black patients have longer wait times for resident physician evaluation, advanced practice provider evaluation, attending physician evaluation, and ED disposition when presenting to the ED with chest pain.

Exploring wait time variations in a prostate cancer patient pathway-A qualitative study.

Norwegian health authorities emphasise that all citizens should have equal access to healthcare and implement cancer patient pathways (CPPs) to ensure medical care for all patients within the same time frame and to avoid unwanted variation. Statistics regarding prostate cancer indicate longer wait times for patients from a local hospital compared to patients from a university hospital. This study describes which health system-related factors influence variations in wait times. Eighteen healthcare workers participated in qualitative individual interviews conducted using a semi-structured interview guide. Transcripts were analysed by systematic text condensation, which is a cross-case method for the thematic analysis of qualitative data. The analysis unveiled four categories describing possible health system-related factors causing variation in times spent on diagnostics for patients in the local hospital and in university hospital, respectively: (a) capacity and competence, (b) logistics and efficiency, (c) need for highly specialised investigations, and (d) need for extra consultations. Centralisation of surgical treatment necessitated the transfer of patients, with extra steps indicated in the CPP for patients transferring from the local hospital to the university hospital for surgery. The local hospital seemed to lack capacity more frequently than the university hospital. Possible factors explaining variations in wait time between the two hospitals concern both internal conditions at the hospitals in organising CPPs and the implications of transferring patients between hospitals. Differences in hospitals' capacity can cause variations in wait time. The extra steps involved in transferring patients between hospitals can lead to additional time spent in CPP.

Wait No Longer: Reducing Medication Wait-Times for Individuals with Co-Occurring Disorders.

Objective: Community addiction treatment agencies have utilized Network for the Improvement of Addiction Treatment (NIATx), a proven implementation strategy, to reduce appointment wait-times. However, its effectiveness at reducing medication access wait-times has not been explored. Thus, we conducted an exploratory analysis to evaluate the impact of the NIATx implementation strategies on reduced wait-times to addiction, psychotropic or both medications for individuals with co-occurring disorders (COD). Methods: In a cluster-randomized waitlist control group design, community addiction treatment agencies (n = 49) were randomized to receive the NIATx strategy (Cohort 1, n = 25) or to a Waitlist control (Cohort 2, n = 24). All agencies had a 12-month active intervention period. The primary outcome was the medication encounter wait-time. A univariate general linear model analysis utilizing a logarithmic (log10) transformation examined medication wait-times improvements. Results: The intent-to-treat analysis for psychotropic medications and both medications (reflecting integrated treatment) showed significant main effects for intervention and time, especially comparing Baseline and Year 1 to Year 2. Conversely, only the main effect for time was significant for addiction medications. Wait-time reductions in Cohort 1 agencies was delayed and occurred in the sustainment phase. Wait-times to a psychotropic, addiction, or both medications encounter declined by 3 days, 4.9 days, and 6.8 days, respectively. For Cohort 2 agencies, reduced wait-times were seen for psychotropic (3.4 days), addiction (6 days), and both medications (4.9 days) during their active implementation period. Same- or next-day medication access also improved. Conclusions: NIATx implementation strategies reduced medication encounter wait-times but timing of agency improvements varied. Despite a significant improvement, a three-week wait-time to receive integrated pharmacological interventions is clinically suboptimal for individuals with a COD in need of immediate intervention. Community addiction treatment agencies should identify barriers and implement changes to improve medication access so that their patients "wait no longer" to receive integrated treatment and medications for their COD.

Canadian demand and access to corneal transplantation: a provincial comparison.

To gather information from stakeholders involved in corneal donation and transplantation to inform discussion at the "National Consensus Forum on Improving Cornea Donation and Transplantation Access in Canada" held in February 2020, survey questions were posed to eye banks, transplanting ophthalmologists and organ donation organizations across Canada to learn more about demand, wait times, and access to tissue for transplant. The survey response rate was one hundred percent (100%) for eye banks and organ donation organizations while 64 percent (64%) of transplant ophthalmologists provided feedback. A number of opportunities for improvement were identified including: demand forecasting; infrastructure and strategies to align supply with demand; data collection and benchmarking of wait times for assessment and transplant to support consistency, equitability and transparency in access; and national collaboration in the development of a data strategy to accurately measure demand and access to cornea transplants in a consistent manner across all provinces to facilitate equity in access nationally.

Impact of surgical wait times during summer months on the oncological outcomes following robotic-assisted radical prostatectomy: 10 years' experience from a large Canadian academic center.

PURPOSE: Most Canadian hospitals face significant reductions in operating room access during the summer. We sought to assess the impact of longer wait times on the oncological outcomes of localized prostate cancer patients following robotic-assisted radical prostatectomy (RARP). METHODS: We conducted a retrospective review of a prospectively maintained RARP database in two high-volume academic centers, between 2010 and 2019. Assessed outcomes included the difference between post-biopsy UCSF-CAPRA and post-surgical CAPRA-S scores, Gleason score upgrade and biochemical recurrence rates (BCR). Multivariable regression analyses (MVA) were used to evaluate the effect of wait times. RESULTS: A total of 1057 men were included for analysis. Consistent over a 10 year period, summer months had the lowest surgical volumes despite above average booking volumes. The lowest surgical volume occurred during the month of July (7.1 cases on average), which was 35% less than the cohort average. The longest average wait times occurred for patients booked in June (93 ± 69 days, p < 0.001). On MVA, patients booked in June had significantly more chance of having an increase in CAPRA score [HR (95% CI) 1.64 (1.02-2.63); p = 0.04] and in CAPRA risk group [HR (95% CI) 1.82 (1.04-3.19); p = 0.03]. Cohort analysis showed fair correlation between CAPRA-score difference and wait time (Pearson correlation: r = - 0.062; p = 0.044). CONCLUSION: Our cohort results demonstrate that conventional RARP wait times are significantly and consistently prolonged during summer months over the past 10 years, with worse post-RARP oncological outcomes in terms of CAPRA scores. Other compensatory mechanisms to sustain consistent yearly operative output should be considered.

Leveraging advanced preparation of oncology medications: Decreasing turnaround-times in an outpatient infusion center.

INTRODUCTION: Many oncology infusions are provided in hospital-based infusion centers. With hospital-based infusion centers seeing increased volumes, patient wait times continue to be a priority. Extended wait times for oncology infusions have been shown to lead to patient dissatisfaction. METHODS: Advanced Preparation of oncology infusion medications allows pharmacy to verify and prepare specific medications the day before a patient's infusion appointment. Our study targeted lower cost, commonly used medications to prepare in advance. Data analyzed included turnaround time (TAT), medication waste, and oncology infusion preparation volumes. Implementation took place in two phases to allow time for the healthcare team to adjust to the new workflow. Phase I medications include a small amount of medications prepared manually by pharmacy technicians. Phase II medications included all phase I medications plus additional medications that were compounded in the intravenous (IV) robotic compounding system. RESULTS: Our study demonstrated significant decrease in median TAT for medications prepared in advance. 537 infusions were prepared using the Advanced Preparation module with a median TAT of 24.2 minutes (IQR, 18.0-34.0). The pre-implementation median TAT was 45.0 minutes (IQR, 36.0-56.0), which represents a decrease of 20.8 minutes (46.2%) following implementation of the program, (p<0.001). There were a total of 149 advanced preparation doses that were wasted (21.7% of doses). CONCLUSION: We have seen a statistically significant reduction in TAT for Advanced Preparation medications. Low volume of Advanced Preparation medications compared to total infusion volume limited impact on overall TAT.