Reducing last-minute cancellations of elective urological surgery-effectiveness of specialist nurse preoperative assessment.

Last-minute cancellations in urological surgery are a global issue, resulting in the wastage of resources and delays to patient care. In addition to non-cessation of anticoagulants and inadequately treated medical comorbidities, untreated urinary tract infections are a significant cause of last-minute cancellations. This study aimed to ascertain whether the introduction of a specialist nurse clinic resulted in a reduction of last-minute cancellations of elective urological surgery as part of our elective recovery plan following the Coronavirus disease 2019, the contagious disease caused by severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 pandemic. A specialist urology nurse-led clinic was introduced to review urine culture results preoperatively. Specialist nurses contacted patients with positive urine cultures and their general practitioners by telephone and email to ensure a minimum of 2 days of 'lead-in' antibiotics were given prior to surgery. Patients unfit for surgery were postponed and optimized, and vacant slots were backfilled. A new guideline was created to improve the timing and structure of the generic preassessment. Between 1 January 2021 and 30 June 2021, a mean of 40 cases was booked each month, with average cancellations rates of 9.57/40 (23.92%). After implementing changes on 1 July 2021, cancellations fell to 4/124 (3%) for the month. On re-audit, there was a sustained and statistically significant reduction in cancellation rates: between 1 July 2021 and 31 December 2021 cancellations averaged 4.2/97.5 (4.3%, P < .001). Two to nine (2%-16%) patients were started on antibiotics each month, while another zero to two (0%-2%) were contacted for other reasons. The implementation of a specialist urology nurse-led preassessment clinic resulted in a sustained reduction in cancellations of last-minute elective urological procedures.

Exploring potential barriers in equitable access to pediatric diagnostic imaging using machine learning.

In this work, we examine magnetic resonance imaging (MRI) and ultrasound (US) appointments at the Diagnostic Imaging (DI) department of a pediatric hospital to discover possible relationships between selected patient features and no-show or long waiting room time endpoints. The chosen features include age, sex, income, distance from the hospital, percentage of non-English speakers in a postal code, percentage of single caregivers in a postal code, appointment time slot (morning, afternoon, evening), and day of the week (Monday to Sunday). We trained univariate Logistic Regression (LR) models using the training sets and identified predictive (significant) features that remained significant in the test sets. We also implemented multivariate Random Forest (RF) models to predict the endpoints. We achieved Area Under the Receiver Operating Characteristic Curve (AUC) of 0.82 and 0.73 for predicting no-show and long waiting room time endpoints, respectively. The univariate LR analysis on DI appointments uncovered the effect of the time of appointment during the day/week, and patients' demographics such as income and the number of caregivers on the no-shows and long waiting room time endpoints. For predicting no-show, we found age, time slot, and percentage of single caregiver to be the most critical contributors. Age, distance, and percentage of non-English speakers were the most important features for our long waiting room time prediction models. We found no sex discrimination among the scheduled pediatric DI appointments. Nonetheless, inequities based on patient features such as low income and language barrier did exist.

Analysis of the Waiting Time in Clinic Registration of Patients with Appointments and Random Walk-Ins.

Healthcare institutions generally use an appointment system. However, patients often need to receive medical services unexpectedly. If they visit a clinic without an appointment, they may have to wait for a long time, as their priority is low. In this study, we investigated whether the clinic registration system can be improved by separating the queues and resources for different types of patients. From our simulation results, we found that under a certain setup, the separation policy does not effectively reduce the walk-ins' waiting time, nor improve the service. The study gives valuable managerial insights into the factors affecting patients' waiting times. As the number of random walk-ins is relatively higher, the service times are longer, and the no-show rate of appointments is lower, separation may reduce the waiting time of walk-in patients.

Patient Satisfaction With Telehealth Visits for New Patient Appointments for Pelvic Floor Disorders: A Randomized Trial of Telehealth Versus Standard In-Person Office Visits.

IMPORTANCE: The acceptability and safety of telehealth have been reported in urogynecology for preoperative and postoperative care but not new patient consultation. OBJECTIVES: This study aimed to determine if new patient telehealth encounters are noninferior to in-person encounters for women presenting to a urogynecology clinic using a satisfaction questionnaire. Secondary objectives were to describe patient experiences and follow-up. STUDY DESIGN: A randomized controlled trial of telehealth versus in-person consults for new patients with any urogynecologic condition was conducted. Patients completed the validated Patient Satisfaction Questionnaire 18 (PSQ-18) after the visit. The primary outcome was composite PSQ-18 score. Using a noninferiority margin of 5 points on the PSQ-18, 25 patients per arm were required with a power of 80% and an α of 0.05. RESULTS: From March to September 2021, 133 patients were screened, 71 were randomized, and 58 were included in the final analysis (30 telehealth and 28 in-person). Demographic characteristics were similar between groups. Patient Satisfaction Questionnaire 18 composite scores were high for both groups but higher for in-person versus telehealth visits (75.68 ± 8.55 vs 66.60 ± 11.80; P = 0.001; difference, 9.08); results were inconclusive with respect to noninferiority. Women in the telehealth group expressed uncertainty regarding the telehealth format. There were no differences in short-term follow-up, communication with the office, or treatment chosen between groups. CONCLUSIONS: Women seen by urogynecologic providers for a new consult both via in-person or telehealth visits demonstrated high satisfaction with their first visit. We were unable to determine if telehealth is noninferior to in-person visits. Our study adds to the literature that telehealth is safe, effective, and acceptable to patients.

Regulação do acesso ao tratamento do câncer de boca no estado do Rio de Janeiro / Study of the regulation system for access to oral cancer treatment in the state of Rio de Janeiro

Objetivos: Descrever o perfil das solicitações de vaga para tratamento do câncer de boca e analisar o tempo entre a solicitação e o agendamento. Métodos. Pesquisa com dados secundários do Sistema Estadual de Regulação do Estado do Rio de Janeiro, entre setembro de 2015 e junho de 2018. Incluiu-se as solicitações para "Oncologia Ambulatório de 1ª vez- Cirurgia de Cabeça e Pescoço" classificadas como câncer de boca e excluiu-se as com status "cancelada". Resultados. Foram exportados 5802 registros, sendo 1663 elegíveis. A idade média foi de 61 anos, com um desvio padrão de 12,3 anos. O tempo médio de espera foi de 19 dias com um desvio padrão de 16,6 dias. 19% dos agravos referiram-se as "Neoplasia maligna de outras partes e partes não especificadas da língua". Conclusão. O perfil dos pacientes corrobora o encontrado na literatura e o tempo de espera para o atendimento é considerado aceitável.

Objectives: To describe the profile of vacancy requests for treatment of oral cancer and to analyze the time between the request and the schedule. Methods. Research with secondary data from the State Regulation System of the State of Rio de Janeiro, between September 2015 and June 2018. Included were requests for "First-time Ambulatory Oncology - Head and Neck Surgery" classified as oral cancer and those with "canceled" status were excluded. Results. 5,802 records were exported, of which 1663 were eligible. The average age was 61 years, with a standard deviation of 12.3 years. The average waiting time was 19 days with a standard deviation of 16.6 days. 19% of the complaints referred to "Malignant neoplasm from other parts and unspecified parts of the tongue". Conclusion. The profile of patients corroborates that found in the literature and the waiting time for care is considered acceptable.

Propiedades psicométricas de la Escala de Planificación Contextualizada en la Educación Física / Propriedades Psicométricas da Escala de Planeamento Contextualizada em Educação Física / Psychometric properties of the Contextualized Planning Scale in Physical Education

La planificación del profesor debe responder al entorno en que se desarrolle el proceso de enseñanza-aprendizaje. En ese sentido, el objetivo de este estudio fue adaptar y validar al contexto mexicano el Cuestionario de Influencia en la Planificación en la Educación Física (CIPEF). Participaron 748 docentes de educación física de México (64.2% hombres), con una edad media de 38 años, quienes fueron divididos endos submuestras. Con la primera de ellas, se realizó un análisis factorial exploratorio, que presentó un valor KMO de .869 y una esfericidad de Barlett de: c2= 9433.705; gl= 703; p< .001, y donde los ítems se agruparon en 10 factores (dos de ellos, añadidos para este estudio). Con la segunda submuestra, se realizaron análisis factoriales confirmatorios al modelo de 10 factores (c2/gl= 4.49; NNFI = .98; CFI = .98; RMSEA = .042) y aun modelo de segundo orden (c2/gl = 2.86; NNFI = .90; CFI = .93; RMSEA = .05). Ambos modelos presentaron índices de bondad de ajuste adecuados. Tras realizar el análisis de test-retest en una muestra independiente de 68 profesores de la misma área geográfica, se concluyó que la Escala de Planificación Contextualizada en la Educación Física es un instrumento válido, fiable y estandarizado que permite medir el grado de influencia que ejercen diversos factores sobre la planificación del profesor en el contexto mexicano. (AU)

The teacher's planning should respond to the environment in which the teaching-learning process takes place. In this sense, the objective of this study was to adapt and validate the Physical Education Planning Influence Questionnaire to the Mexican context. A total of 748 physical education teachers from Mexico (64.2% men), with a mean age of 38 years, participated in the study and were divided into two subsamples. With the first one, an exploratory factor analysis was performed, which presented a KMO value of .869 and a Barlett's sphericity of: c2= 9433.705; df= 703; p< .001, and where the items were grouped into 10 factors (two of them, added for this study). With the second subsample, confirmatory factor analyses were performed on the 10-factor model (c2/df= 4.49; NNFI = .98; CFI = .98; RMSEA = .042) and on a second-order model (c2/df= 2.86; NNFI = .90; CFI = .93; RMSEA = .05). Both models presented adequate goodness-of-fit indices. After performing the test-retest analysis on an independent sample of 68 teachers from the same geographical area, it was concluded that the Contextualized Planning Scale in Physical Education is a valid, reliable and standardized instrument that allows measuring the degree of influence exerted by various factors on the teacher's planning in the Mexican context. (AU)

O planeamento do professor deve responder ao ambiente em que o processo de ensino-aprendizagem tem lugar. Neste sentido, o objectivo deste estudo era adaptar e validar o CIPEF (Cuestionario de Influencia en la Planificación en la Educación Física) ao contexto mexicano. Um total de 748 professores de educação física do México (64,2% do sexo masculino), com uma idade média de 38 anos, participaram no estudo e foram divididos em duas subamostras. Com o primeiro, foi realizada uma análise de factores exploratórios, que apresentou um valor KMO de .869 e uma esfericidade de Barlett de: c2= 9433.705; gl= 703; p< .001, e onde os itens foramagrupados em 10 factores (dois deles, adicionados para este estudo). Com a segunda subamostra, foram realizadas análises de factores de confirmação no modelo de 10 factores (c2/gl= 4,49; NNFI = .98; CFI = .98; RMSEA = .042) e num modelo de segunda ordem (c2/gl= 2,86; NNFI = .90; CFI = .93; RMSEA = .05). Ambos os modelos apresentavam índices adequados de goodness-of-fit. Após a realização da análise de teste-reteste numa amostra independente de 68 professores da mesma área geográfica, concluiu-se que a Escala de Planeamento Contextualizada em Educação Física é um instrumento válido, fiável e padronizado que permite medir o grau de influência exercida por vários factores sobre o planeamento do professor no contexto mexicano. (AU)

Liderazgo autoritario y flexible en la planificación y toma de decisiones de entrenadores de fútbol en España / Liderança autoritária e flexível no planejamento e tomada de decisões de Treinadores de futebol na Espanha / Authoritative and flexible leadership in the planning and decision making of football coaches in Spain

El objetivo de esta investigación fue analizar el proceso de planificación y toma de decisiones de los entrenadores españoles de fútbol en función variables sociodemográficas, de formación y del contexto del equipo. A través de un diseño descriptivo, comparativo y transversal, se administraron los cuestionarios de estilos de decisión y planificación en el deporte a una muestra de 315 de entrenadores de fútbol en activo. Se analizó la validez y fiabilidad de las escalas empleadas y se realizó un análisis correlacional entre los factores de cada escala. Los resultados indican que los entrenadores puntúan más alto la toma de decisiones democráticas (M= 3,77 ±,74) y la planificación flexible (M= 4,04 ±,69). De igual modo, se encontraron correlaciones entre la toma de decisiones y planificación siendo los pares: democrática-flexible y autoritaria-rígida. También se encontraron diferencias significativas en relación a la edad, características del equipo, formación universitaria y deportiva. (AU)

The objective of this research is to analyse the planning and decision-making process of Spanish football coaches according to socio-demographic, educational and team context variables. Using a descriptive, comparative and cross-sectional design, the questionnaires on decision-making and planning styles in sport were administered to a sample of 315 active football coaches. The validity and reliability of the scales used were analysed and a correlational analysis was carried out between the factors of each scale. The results indicate that coaches scored democratic decision-making (M= 3.77 ±.74) and flexible planning (M= 4.04 ±.69) higher. Similarly, correlations were found between decision-making and planning with the pairs being democratic-flexible and authoritarian-rigid. Significant differences were also found in relation to age, team characteristics, university and sports training. (AU)

O objectivo desta investigação era analisar o processo de planeamento e tomada de decisões dos treinadores espanhóis de futebol de acordo com variáveis sociodemográficas, educacionais e de contexto de equipa. Através de um desenho descritivo, comparativo e transversal, os questionários de estilos de decisão e planeamento no desporto foram administrados a uma amostra de 315 treinadores de futebol activos. A validade e fiabilidade das escalas utilizadas foram analisadas e foi efectuada uma análise correlacional entre os factores de cada escala. Os resultados indicam que os treinadores pontuaram a tomada de decisão democrática (M= 3,77 ±,74) e o planeamento flexível (M= 4,04 ±,69) mais alto. Do mesmo modo, foram encontradas correlações entre a tomada de decisões e o planeamento, sendo os pares democrático-flexível e autoritário-rígido. Foram também encontradas diferenças significativas em relação à idade, características da equipa, formação universitária e desportiva. (AU)

Appointment attendance behaviors in multiple sclerosis: Understanding the factors that differ between no shows, short notice cancellations, and attended appointments.

BACKGROUND: There has yet to be an examination of how appointment attendance behaviors in multiple sclerosis (MS) are related to scheduling metrics and certain demographic, clinical, and behavioral factors such as cognitive functioning and personality traits. This study aimed to examine the factors that differ between no shows (NS), short notice cancellations (SNC), and attended appointments. METHODS: Participants (n = 110) were persons with MS who were enrolled in a larger cross-sectional study, during which they completed a battery of neuropsychological measures. Data about their appointments in three MS-related clinics the year prior to their study evaluation were extracted from the medical record. Bivariate analyses were done, with post-hoc tests conducted with Bonferroni corrections if there was an overall group difference. RESULTS: A higher number of SNC were noted during the winter, with 22.4% being due to the weather. SNC were also more common on Thursdays, but less frequent during the early morning time slots (7am to 9am). In contrast, NS were associated with lower annual income, weaker healthcare provider relationships, lower self-efficacy, higher levels of neuroticism, depressive symptom severity, and health distress, and greater cognitive difficulties, particularly with prospective memory. CONCLUSIONS: While SNC are related to clinic structure and situational factors like the weather, NS may be more influenced by behavioral issues, such as difficulty remembering an appointment and high levels of distress. These findings highlight potential targets for reducing the number of missed appointments in the clinic, providing opportunities for improved healthcare efficiency and most importantly health.

An operations research approach to automated patient scheduling for eye care using a multi-criteria decision support tool.

Inefficient management of resources and waiting lists for high-risk ophthalmology patients can contribute to sight loss. The aim was to develop a decision support tool which determines an optimal patient schedule for ophthalmology patients. Our approach considers available booking slots as well as patient-specific factors. Using standard software (Microsoft Excel and OpenSolver), an operations research approach was used to formulate a mathematical model. Given a set of patients and clinic capacities, the model objective was to schedule patients efficiently depending on eyecare measure risk factors, referral-to-treatment times and targets, patient locations and slot availabilities over a pre-defined planning horizon. Our decision support tool can feedback whether or not a patient is scheduled. If a patient is scheduled, the tool determines the optimal date and location to book the patients' appointments, with a score provided to show the associated value of the decisions made. Our dataset from 519 patients showed optimal prioritization based on location, risk of serious vision loss/damage and the referral-to-treatment time. Given the constraints of available slots, managers can input hospital-specific parameters such as demand and capacity into our model. The model can be applied and implemented immediately, without the need for additional software, to generate an optimized patient schedule.

Medical appointments and provision of medical care during the COVID-19 pandemic in Mainz, Germany.

Previous evidence suggested that non-COVID-19-related medical care was reduced during the first wave of the COVID-19 pandemic, but it remained unclear whether or to which extent this effect lasted beyond the first wave, or existed in a longer time frame. Here, we consider questionnaire data of the Gutenberg-COVID-19 study together with pre-pandemic baseline data of the Gutenberg Health Study concerning the region around Mainz, Germany, to study the effects of the pandemic on the provision of medical care until April 2021. We observed that the proportion of cancelled medical appointments was low and that the fraction of participants with a medical appointment as an indicator for the number of appointments being made was in line with pre-pandemic levels. Appointments were more likely cancelled by the patient (rather than the provider), and more likely cancelled by medical specialists such as dentists or ophthalmologists (rather than GPs). In conclusion, we found some evidence that, at least with regard to realized appointments, the medical system and the provision of medical care were not harmed by the COVID-19 pandemic on a longer time scale.

Experiences with small and large numbers of protesters at abortion clinics in North Carolina.

OBJECTIVES: To analyze the association between number of antiabortion protesters and patients' and their companions' experiences accessing abortion clinics in North Carolina. STUDY DESIGN: In this concurrent mixed-methods study conducted in 2018-2019 at two independent abortion clinics in North Carolina, the author triangulated the methods of participant observation, descriptive statistical analysis of survey data, and thematic content analysis of open-ended responses to compare experiences of respondents who observed larger (>10) versus smaller (1-10) numbers of protesters at their clinic visit. The analytic sample contained experiences of patients and companions who saw protesters during the study period. RESULTS: Of 1530 people approached for the survey, 886 (58%) completed the questionnaire. Overall, 655 respondents were included in the analysis. Most respondents (n = 546, 83%) saw 1 to 10 protesters, versus those who saw >10 protesters (n = 109, 17%). Respondents who saw 1 to 10 protesters had their cars stopped at higher rates (53%) than those who saw >10 protesters (40%) but reported being physically approached at similar rates (22% vs. 23%). Respondents who saw >10 protesters indicated that it was more dangerous to drive into the clinic (44% vs. 23%) and more difficult to access the clinic (65% vs. 39%), when compared with people who saw 1 to 10 protesters. Respondents who saw >10 protesters also reported that they thought about leaving more frequently (21% vs. 12%), that the protesters made them feel unsafe (44% vs. 23%), made their visit more stressful (71% vs. 59%), and protesters negatively impacted their clinic experience at higher rates (47% vs. 31%). CONCLUSIONS: Respondents experienced logistical barriers to clinic access regardless of the number of protesters, though these worsened with larger numbers of protesters. Respondents perceived larger numbers of protesters as more intimidating and felt less safe navigating into the clinic. While all respondents made it to their appointments, these perceptions about larger numbers show how clinic protesting is an intimidating force that interferes with clinic access. IMPLICATIONS: Showing the ways that the number of protesters relates to logistical and emotional barriers can help clinics in planning mitigation measures to address issues of clinic access for their patients and their companions.

Early pregnancy confirmation availability at crisis pregnancy centers and abortion facilities in the United States.

OBJECTIVES: Crisis pregnancy centers (CPCs) seek to dissuade people from having abortions. Twenty-five states have policies supporting CPCs. We aimed: (1) to characterize access to early pregnancy confirmation at CPCs compared to abortion facilities nationwide and (2) to understand the role of state CPC policy in service access. STUDY DESIGN: We conducted a national mystery caller study of 445 CPCs and geographically paired abortion facilities, posing as patients seeking pregnancy confirmation. Facility type (CPC vs abortion facility) was the primary exposure in Aim 1. Wait time to first available early pregnancy appointment was the primary outcome. In Aim 2, state-level CPC policy designation (supportive vs not supportive of CPCs) was the primary exposure. Difference in wait time ≥7 days to first available appointment between CPCs and paired abortion facilities was the primary outcome. RESULTS: CPCs were more likely than abortion facilities to provide same-day appointments (68.5% vs 37.2%, p < 0.0001), and free pregnancy testing (98.0% vs 16.6%, p < 0.0001). The median wait to first available appointment at a CPC was 0 days (IQR 0,1), compared to 1 day at abortion facilities (IQR 0, 5), p < 0.0001. In states with supportive CPC policy environments, abortion facilities were less likely to have wait times exceeding their paired CPC by a week or more, compared to paired facilities in states with non-supportive CPC policy environments (p = 0.033). This remained true after adjusting for state abortion policy environment (p = 0.011). CONCLUSIONS: Pregnancy confirmation is more accessible at CPCs compared to abortion facilities. Factors other than state-level CPC policies likely influence service accessibility. There is a need for improved access to pregnancy confirmation in medical settings. IMPLICATIONS: Our findings demonstrating that pregnancy confirmation is more accessible at crisis pregnancy centers than at abortion facilities are predicted to be exacerbated in the wake of abortion clinic closures following the Dobbs v Jackson Women's Health Organization Supreme Court decision. This highlights the need for improved funding and support for pregnancy confirmation service delivery in medical settings, including abortion facilities.

Improving Hospital Outpatient Clinics Appointment Schedules by Prediction Models.

Patient no-shows and suboptimal patient appointment length scheduling reduce clinical efficiency and impair the clinic's quality of service. The main objective of this study is to improve appointment scheduling in hospital outpatient clinics. We developed generic supervised machine learning models to predict patient no-shows and patient's length of appointment (LOA). We performed a retrospective study using more than 100,000 records of patient appointments in a hospital outpatient clinic. Several machine learning algorithms were used for the development of our prediction models. We trained our models on a dataset that contained patients', physicians', and appointments' characteristics. Our feature set combines both unstudied features and features adopted from previous studies. In addition, we identified the influential features for predicting LOA and no-show. Our LOA model's performance was 6.92 in terms of MAE, and our no-show model's performance was 92.1% in terms of F-score. We compared our models' performance to the performance of previous research models by applying their methods to our dataset; our models demonstrated better performance. We show that the major effector of such differences is the use of our novel features. To evaluate the effect of our prediction results on the quality of schedules produced by appointment systems (AS), we developed an interface layer between our prediction models and the AS, where prediction results comprise the AS input. Using our prediction models, there was an 80% improvement in the daily cumulative patient waiting time and a 33% reduction in the daily cumulative physician idle time.