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.

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.

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.

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.

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.

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.

The Random Effects Warfarin Days' Supply (REWarDS) Model: Development and Validation of a Novel Method for Estimating Exposure to Warfarin Using Administrative Data.

Warfarin's complex dosing is a significant barrier to measurement of its exposure in observational studies using population databases. Using population-based administrative data (1996-2019) from British Columbia, Canada, we developed a method based on statistical modeling (Random Effects Warfarin Days' Supply (REWarDS)) that involves fitting a random-effects linear regression model to patients' cumulative dosage over time for estimation of warfarin exposure. Model parameters included a minimal universally available set of variables from prescription records for estimation of patients' individualized average daily doses of warfarin. REWarDS estimates were validated against a reference standard (manual calculation of the daily dose using the free-text administration instructions entered by the dispensing pharmacist) and compared with alternative methods (fixed window, fixed tablet, defined daily dose, and reverse wait time distribution) using Pearson's correlation coefficient (r), the intraclass correlation coefficient, and the root mean squared error. REWarDS-estimated days' supply showed strong correlation and agreement with the reference standard (r = 0.90 (95% confidence interval (CI): 0.90, 0.90); intraclass correlation coefficient = 0.95 (95% CI: 0.94, 0.95); root mean squared error = 8.24 days) and performed better than all of the alternative methods. REWarDS-estimated days' supply was valid and more accurate than estimates from all other available methods. REWarDS is expected to confer optimal precision in studies measuring warfarin exposure using administrative data.

Transplantation of Patients With Long Dialysis Vintage in the Current Deceased Donor Kidney Allocation System (KAS).

RATIONALE & OBJECTIVE: In 2014 the wait-time calculation for deceased donor kidney transplantation in the United States was changed from the date of first waitlisting to the date of first maintenance dialysis treatment with the aim of minimizing disparities in access to transplantation. This study examined the impact of this policy on access to transplantation, patient survival, and transplant outcomes among patients treated with maintenance dialysis for a prolonged duration before waitlisting. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: Patients identified in the US Renal Data System between 2008 and 2018 aged 18-70 years and in the 95th percentile of dialysis treatment duration (≥6.5 years) before waitlisting. EXPOSURE: Waitlisting for transplantation before versus after implementation of the policy. OUTCOME: Time from date of waitlisting to deceased donor transplantation and death, and from date of transplantation to all cause graft loss. ANALYTICAL APPROACH: Univariate and multivariable time to event analyses. RESULTS: Patients waitlisted after the policy change had a higher likelihood of deceased donor transplantation (HR, 3.12 [95% CI, 2.90-3.37]) and lower risk of death (HR, 0.74 [95% CI, 0.63-0.87]). The risk of graft loss was lower in the post-kidney allocation system (KAS) cohort (HR, 0.66 [95% CI, 0.55-0.80]). The proportion of adult patients treated with dialysis ≥6.5 years who were never waitlisted for transplantation remained high (73%) and did not decrease after the policy implementation. LIMITATIONS: Cannot determine causality in this observational study. CONCLUSIONS: The policy change was associated with an increase in deceased donor transplantation and marked improvement in patient survival for patients waitlisted after long periods of dialysis treatment without decreasing the utility of available deceased donor kidney supply. The policy was not associated with increased waitlisting of this disadvantaged population.

The impact of waiting time for orthopaedic consultation on pain levels in individuals with osteoarthritis: a systematic review and meta-analysis.

OBJECTIVE: Time spent waiting for access to orthopaedic specialist health services has been suggested to result in increased pain in individuals with osteoarthritis (OA). We assessed whether time spent on an orthopaedic waiting list resulted in a detrimental effect on pain levels in patients with knee or hip OA. METHODS: We searched Ovid MEDLINE, EMBASE and EBSCOhost databases from inception until September 2021. Eligible articles included individuals with OA on an orthopaedic waitlist and not receiving active treatment, and reported pain measures at two or more time points. Random-effects meta-analysis was used to estimate the pooled effect of waiting time on pain levels. Meta-regression was used to determine predictors of effect size. RESULTS: Thirty-three articles were included (n = 2,490 participants, 67 ± 3 years and 62% female). The range of waiting time was 2 weeks to 2 years (20.8 ± 18.8 weeks). There was no significant change in pain over time (effect size = 0.082, 95% CI = -0.009, 0.172), nor was the length of time associated with longitudinal changes in pain over time (ß = 0.004, 95% CI = -0.005, 0.012). Body mass index was a significant predictor of pain (ß = -0.043, 95% CI = -0.079, 0.006), whereas age and sex were not. CONCLUSIONS: Pain remained stable for up to 1 year in patients with OA on an orthopaedic waitlist. Future research is required to understand whether pain increases in patients waiting longer than 1 year.

Delay in adjuvant chemotherapy administration for patients with FIGO stage I epithelial ovarian carcinoma is associated with worse survival; an analysis of the National Cancer Database.

OBJECTIVE: The administration of adjuvant chemotherapy within 42 days from surgery is one of the proposed quality measures for patients with epithelial ovarian cancer (EOC). The aim of the present study was to evaluate the impact of chemotherapy delay in the survival of patients with stage I EOC. METHODS: The National Cancer Database was accessed, and patients diagnosed between 2004 and 2015 with FIGO stage I EOC who received multi-agent chemotherapy were identified. Overall survival (OS) was compared between patients who received chemotherapy <6 weeks and 6-12 weeks from surgery with the log-rank test following generation of Kaplan-Meier curves. Cox model was constructed to control for a priori selected confounders. RESULTS: A total of 8549 patients who received adjuvant chemotherapy at a median 35 days from surgery (interquartile range 19) were identified; 67.7% received adjuvant chemotherapy <6 weeks from surgery while 32.3% experienced a delay. Patients who experienced a delay were more likely to have comorbidities (18.4% vs 14.9%, p < 0.001), and be managed in non-academic facilities (57.1% vs 53.2%, p = 0.001). Patients who experienced a delay had worse OS compared to those who did not, p < 0.001; 5-year OS rates 85.7% and 89.7%, respectively. For patients with high-grade serous tumors, those who experienced a delay had a 5-yr OS of 81.9% compared to 88.6% for those who did not, p < 0.001. After controlling for age, race, presence of comorbidities, insurance status, tumor histology and grade, performance of lymphadenectomy and substage, chemotherapy delay was associated with worse survival (HR: 1.25, 95% CI: 1.10, 1.42). CONCLUSIONS: For patients with early stage EOC administration of adjuvant chemotherapy within 6 weeks from surgery was associated with better overall survival, especially for those with stage IC disease.

Value of Reducing Wait Times for Chimeric Antigen Receptor T-Cell Treatment: Evidence From Randomized Controlled Trial Data on Tisagenlecleucel for Diffuse Large B-Cell Lymphoma.

OBJECTIVES: This study aimed to quantify the value of reducing chimeric antigen receptor T-cell (CAR-T) treatment wait times on patients with refractory and relapsed aggressive blood cancer who can newly gain access to treatment or access treatment earlier in their disease course. METHODS: Using data from the JULIET clinical trial, we first identified the number of additional patients with diffuse large B-cell lymphoma that would have been treated with tisagenlecleucel CAR-T therapy if wait times were shortened. For these patients, we estimated mortality benefits using literature estimates of CAR-T effectiveness. Next, among patients who already received CAR-T, we estimated tumor burden progression over time using a linear probability regression model. The primary outcome variable was an indicator for having above-normal lactate dehydrogenase, and we controlled for time, use of bridging therapy, and time-invariant patient characteristics. The regression results, along with literature estimates relating lactate dehydrogenase to CAR-T effectiveness, were used to compute the survival benefits of earlier CAR-T treatment. RESULTS: Reducing wait times by 2 months increased the number of eligible patients receiving CAR-T by at least 10.7%. For patients already receiving tisagenlecleucel CAR-T, a 2-month reduction in wait times generated a 3.3% increase in survival gains per treated patient. Thus, among patients seeking treatment, the combined treatment efficacy increased by 14%, with approximately one-quarter of survival benefits accruing to existing patients receiving faster treatment. CONCLUSIONS: Delays affected not only access to CAR-T treatments but also treatment effectiveness. Our results highlight the survival benefits of expediting treatment access and may help explain some observed differences in CAR-T effectiveness across countries.

The wait time to primary surgery in endometrial cancer - impact on survival and predictive factors: a population-based SweGCG study.

BACKGROUND: Poor survival rates in different cancer types are sometimes blamed on diagnostic and treatment delays, and it has been suggested that such delays might be related to sociodemographic factors such as education and ethnicity. We examined associations of the wait time from diagnosis to surgery and survival in endometrial cancer (EC) and explored patient and tumour factors influencing the wait time. MATERIAL AND METHODS: In this historical population-based cohort study, The Swedish Quality Registry for Gynaecologic Cancer (SQRGC) was used to identify EC patients who underwent primary surgery between 2010 and 2018. Factors associated with a wait time > 32 d were analysed with logistic regression. The 32-d time point was defined in accordance with the Swedish Standardisation Cancer Care programme. Adjusted Poisson regression analyses were used to analyse excess mortality rate ratio (EMRR). RESULTS: Out of 7366 women, 5535 waited > 32 d for surgery and 1098 > 70 d. The overall median wait time was 44 d. The factors most strongly associated with a wait time > 32 d were surgery at a university hospital (adjusted odds ratio [OR] 1.34, 95% confidence interval [CI] 1.08-1.66) followed by country of birth (OR 1.31, 95% CI 1.10-1.55) and year of diagnosis. There were no associations between wait time and histology or age. A wait time < 15 d was associated with higher mortality (adjusted EMRR 2.29,95% CI 1.36-3.84) whereas no negative survival impact was seen with a wait time of 70 d. Age, tumour stage, histology and risk group were highly associated with survival, whereas education, country of origin and hospital level did not have any impact on survival. CONCLUSIONS: Surgery within the first two weeks after EC diagnosis was associated with worsened survival. A prolonged wait time did not seem to have any significant adverse effect on prognosis.HighlightsSurgery within the first two weeks after diagnosis of endometrial cancer (EC) was associated with poorer survival.A prolonged wait time to surgery did not worsen prognosis.Delay in time to surgery was associated with sociodemographic factors.

Provider supply and access to primary care.

Resource-constrained delivery systems often have access issues, causing patients to wait a long time to see a provider. We develop theoretical and empirical models of wait times and apply them to primary care delivery by the U.S. Veterans Health Administration (VHA). Using instrumental variables to handle simultaneity issues, we estimate the effect of clinician supply on new patient wait times. We find that it has a sizable impact. A 10% increase in capacity reduces wait times by 2.1%. Wait times are also associated with clinician productivity, scheduling protocols, and patient access to alternative sources of care. The VHA has adopted our models to identify underserved areas as specified by the MISSION Act of 2018.

A single-entry model and wait time for hip and knee replacement in eastern health region of Newfoundland and Labrador 2011-2019.

BACKGROUND: A single-entry model in healthcare consolidates waiting lists through a central intake and allows patients to see the next available health care provider based on the prioritization. This study aimed to examine whether and to what extent the prioritization reduced wait times for hip and knee replacement surgeries. METHOD: The survival regression method was used to estimate the effects of priority levels on wait times for consultation and surgery for hip and knee replacements. The sample data included patients who were referred to the Orthopedic Central Intake clinic at the Eastern Health region of Newfoundland and Labrador and had surgery of hip and knee replacements between 2011 and 2019. RESULT: After adjusting for covariates, the hazard of having consultation booked was greater in patients with priority 1 and 2 than those in priority 3 when and at 90 days after the referral was made for both hip and knee replacements. Regarding wait time for surgery after the decision for surgery was made, while the hazard of having surgery was lower in priority 2 than in priority 3 when and indifferent at 182 days after the decision was made, it was not significantly different between priority 1 and priority 3 among hip replacement patients. Priority levels were not significantly related to the hazard of having surgery for a knee replacement after the decision for surgery was made. Overall, the hazard of having surgery after the referral was made by a primary care physician was greater for patients in high priority than those in low priority. Preferring a specific surgeon indicated at referral was found to delay consultation and it was not significantly related to the total wait time for surgery. Incomplete referral forms prolonged wait time for consultation and patients under age 65 had a longer total wait time than those aged 65 or above. CONCLUSION: Patients with high priority could have a consultation booked earlier than those with low priority and prioritization in a single entrance model shortens the total wait time for surgery. However, the association between priority levels and wait for surgery after the decision for surgery was made has not well-established.

"It feels like an endless fight": a qualitative study exploring healthcare utilization of persons with rheumatic conditions waiting for pain clinic admission.

BACKGROUND: Individuals living with a rheumatic pain condition can face delays in accessing pain clinics, which prevents them from receiving timely treatment. Little is known regarding their specific healthcare utilization in order to alleviate pain while waiting to obtain services in pain clinics. Hence, the aim of this study was to explore the perceptions and experiences of persons living with rheumatic conditions regarding healthcare utilization while waiting to access a pain clinic. METHODS: In this qualitative descriptive study, semi-structured interviews were conducted with adults living with a painful rheumatic condition that reported either being waiting for admission in a pain clinic, having been referred but then denied pain clinic services, or having received services during the previous six months, in the province of Quebec, Canada. The interviews were transcribed verbatim, and an inductive thematic analysis was performed. RESULTS: Twenty-six individuals were interviewed (22 women and 4 men; mean age 54 ± 10 years). Three themes were identified: 1) lacking guidance in identifying solutions to their complex and multidimensional needs, 2) struggling to obtain and maintain services due to systemic access barriers, and 3) displaying resilience through a search for accessible and sustainable self-management strategies. CONCLUSIONS: The current approaches and structures of health services fail to adequately answer the service needs of individuals experiencing painful rheumatic conditions. Important shifts are required in pain education, in increasing access to multidisciplinary approaches at the primary care level and in breaking down barriers individuals with chronic pain face to receive appropriate and timely care.

Audit of waiting time-to-treatment of atypical endometrial hyperplasia.

BACKGROUND: Atypical endometrial hyperplasia (AEH) is the precursor lesion in endometrial carcinoma, the most common gynaecological malignancy in New Zealand, with inequities in disease burden and outcome for Maori and Pacific women. AIMS: In women diagnosed with AEH at two hospitals, to audit five standards of care for surgical management and time-to-treatment, and identify variation in care by ethnicity and other factors. MATERIALS AND METHODS: Demographic, referral, diagnostic and treatment characteristics were collected for women with a new AEH diagnosis between 1/1/2019 and 31/12/2020. Surgical management and time-to-treatment were audited against Royal College of Obstetricians and Gynaecologists and New Zealand Ministry of Health Faster Cancer Treatment recommendations. RESULTS: Of 124 participants, 60% were Pacific, 86% premenopausal, and 80% had obesity. For 55 women managed surgically, surgical standards of care were met. There were delays between referral, diagnosis and treatment - only 18% and 56% of women met the 62-day (referral to treatment) and 31-day (decision-to-treat to treatment) targets, respectively. Wait times were prolonged for women who had dilation and curettage (vs pipelle), magnetic resonance imaging (MRI) (vs no MRI), and surgery (vs medical management). Ethnic disparities were not identified for any standard. DISCUSSION: Delays to treatment were found throughout women's journeys. Hospital services can streamline their clinical pathways for women referred for abnormal uterine bleeding, flagging obesity as a high suspicion for cancer indicator, increasing access to endometrial sampling in primary care and establishing 'one-stop-shop' outpatient assessment with empiric initiation of intrauterine progestogen.

Measuring Telehealth Visit Length and Schedule Adherence Using Videoconferencing Data.

Background: The ability to measure clinical visit length is critical for operational efficiency, patient experience, and accurate billing. Despite the unprecedented surge in telehealth use in 2020, studies on visit length and schedule adherence in the telehealth setting are nonexistent in the literature. This article aims to demonstrate the use of videoconferencing data to measure telehealth visit length and schedule adherence. Materials and Methods: We used data from telehealth video visits at four clinical specialties at Nationwide Children's Hospital, including behavioral health (BH), speech pathology (SP), physical therapy/occupational therapy (PT/OT), and primary care (PC). We combined videoconferencing timestamp data with visit scheduling data to calculate the total visit length, examination length, and patient wait times. We also assessed schedule adherence, including patient on-time performance, examination on-time performance, provider schedule deviations, and schedule length deviations. Results: The analyses included a total of 175,876 telehealth video visits. On average, children with BH appointments spent a total of 57.2 min for each visit, followed by PT/OT (50.8 min), SP (42.1 min), and PC (25.0 min). The average patient wait times were 4.1 min (BH), 2.7 min (PT/OT), 2.8 min (SP), and 3.1 min (PC). The average examination lengths were 48.8 min (BH), 44.5 min (PT/OT), 34.9 min (SP), and 16.6 min (PC). Regardless of clinical specialty, actual examination lengths of most visits were shorter than the scheduled lengths, except that appointments scheduled for 15 min tended to run overtime. Conclusions: Videoconferencing data provide a low-cost, accurate, and readily available resource for measuring telehealth visit length and schedule adherence.

Care Barriers for Patients With Nonsyndromic Orofacial Clefts in Saudi Arabia: A Cross-Sectional Study.

OBJECTIVE: To evaluate the barriers faced by patients with nonsyndromic orofacial clefts (NSOFC) throughout their treatment course in Saudi Arabia. DESIGN: A cross-sectional study. SETTING: Eleven different governmental health care centers across Saudi Arabia. Patients: Records of pediatric patients with NSOFC. INTERVENTIONS: A questionnaire with multiple validation stages was designed to assess the barriers in care of these patients through telephonic interviews with the parents or guardians of patients with NSOFC. MAIN OUTCOME MEASURES: We identified 3 care-barrier-related factors: (1) geographic accessibility, (2) appointment availability and accessibility, and (3) scheduling-related barriers. RESULTS: Overall, 240 participants of both sexes, with orofacial cleft of various types and with various demographic characteristics (residence, family monthly income, and caregiver level of education) were included. The highest mean score of care barriers was reported for scheduling-related barriers. Overall, 186 individuals reported sometimes/often not receiving the required medical care for the following reasons: scheduling difficulties (89%; 37.1%), prolonged waiting room time (40%; 16.7%), and transportation difficulties (36%; 15.0%). A linear regression showed that parents cited late appointments as the main reason for patients with NSOFC not receiving adequate medical care. Care-barrier factors were significantly related to gender (P = .035), patient age (P < .001), place of residency (P < .001), and caregiver's level of education (P = .015). CONCLUSIONS: Gaps in the health care system directly related to common care barriers need to be addressed to ensure adequate care for patients with NSOFC.

A Simulation Modelling Study of Referral Distribution Policies in a Centralized Intake System for Surgical Consultation.

Delays beyond recommended wait times, especially for specialist services, are associated with adverse health outcomes. The Alberta Surgical Initiative aims to improve the referral wait time-the time between a referral is received at the central intake to the time a specialist sees the patient. Using the discrete event simulation modelling approach, we evaluated and compared the impact of four referral distribution policies in a central intake system on three system performance measures (number of consultations, referral wait time and surgeon utilization). The model was co-designed with clinicians and clinic staff to represent the flow of patients through the system. We used data from the Facilitated Access to Surgical Treatment (FAST) centralized intake referral program for General Surgery to parameterize the model. Four distribution policies were evaluated - next-available-surgeon, sequential, "blackjack," and "kanban." A sequential distribution of referrals for surgical consultation among the surgeons resulted in the worst performance in terms of the number of consultations, referral wait time and surgeon utilization. The three other distribution policies are comparable in performance. The "next available surgeon" model provided the most efficient and robust model, with approximately 1,000 more consultations, 100 days shorter referral time and a 14% increase in surgeon utilization. Discrete event simulation (DES) modelling can be an effective tool to illustrate and communicate the impact of the referral distribution policy on system performance in terms of the number of consultations, referral wait time and surgeon utilization.

Association between definitive chemoradiotherapy wait-time and survival in locally-advanced cervical cancer: Implications during the coronavirus pandemic.

OBJECTIVE: The current coronavirus pandemic caused a significant decrease in cancer-related encounters resulting in a delay in treatment of cancer patients. The objective of this study was to examine the survival effect of delay in starting concurrent chemo-radiotherapy (CCRT) in women with locally-advanced cervical cancer. METHODS: This is a retrospective observational study querying the National Cancer Database from 2004 to 2016. Women with stage IB2-IVA squamous cell carcinoma, adenocarcinoma, or adenosquamous carcinoma of the uterine cervix who received definitive CCRT with known wait-time for CCRT initiation after cancer diagnosis were eligible (N=13,617). Cox proportional hazard regression model with restricted cubic spline transformation was fitted to assess the association between CCRT wait-time and all-cause mortality in multivariable analysis. RESULTS: The median wait-time to start CCRT was 6 (IQR 4-8) weeks. In a multivariable analysis, older age, non-Hispanic black and Hispanic ethnicity, recent year of diagnosis, Medicaid and uninsured status, medical comorbidities, and absence of nodal metastasis were associated with longer CCRT wait-time (P<.05). Women with aggressive tumor factors (poorer differentiation, large tumor size, nodal metastasis, and higher cancer stage) were more likely to have a short CCRT wait-time (P<.05). After controlling for the measured covariates, CCRT wait-time of 6.1-9.8 weeks was not associated with increased risk of all-cause mortality compared to a wait-time of 6 weeks. Similar association was observed when the cohort was stratified by histology, cancer stage, tumor size, or brachytherapy use. CONCLUSION: An implication of this study for the current coronavirus pandemic is that in the absence of aggressive tumor factors, a short period of wait-time to start definitive CCRT may not be associated with increased risk of mortality in women with locally-advanced cervical cancer.