Number Of Scheduled Appointments Research Articles

Impact of COVID-19 on access to cancer care in Rwanda: a retrospective time-series study using electronic medical records data

IntroductionThe COVID-19 pandemic has caused disruptions in access to routine healthcare services worldwide, with a particularly high impact on chronic care patients and low and middle-income countries. In this study,...

Predicting Patient Wait Times by Using Highly Deidentified Data in Mental Health Care: Enhanced Machine Learning Approach.

BackgroundWait times impact patient satisfaction, treatment effectiveness, and the efficiency of care that the patients receive. Wait time prediction in mental health is a complex task and is affected by the difficulty in predicting the required number of treatment sessions for outpatients, high no-show rates, and the possibility of using group treatment sessions. The task of wait time analysis becomes even more challenging if the input data has low utility, which happens when the data is highly deidentified by removing both direct and quasi identifiers.ObjectiveThe first aim of this study was to develop machine learning models to predict the wait time from referral to the first appointment for psychiatric outpatients by using real-time data. The second aim was to enhance the performance of these predictive models by utilizing the system’s knowledge while the input data were highly deidentified. The third aim was to identify the factors that drove long wait times, and the fourth aim was to build these models such that they were practical and easy-to-implement (and therefore, attractive to care providers).MethodsWe analyzed retrospective highly deidentified administrative data from 8 outpatient clinics at Ontario Shores Centre for Mental Health Sciences in Canada by using 6 machine learning methods to predict the first appointment wait time for new outpatients. We used the system’s knowledge to mitigate the low utility of our data. The data included 4187 patients who received care through 30,342 appointments.ResultsThe average wait time varied widely between different types of mental health clinics. For more than half of the clinics, the average wait time was longer than 3 months. The number of scheduled appointments and the rate of no-shows varied widely among clinics. Despite these variations, the random forest method provided the minimum root mean square error values for 4 of the 8 clinics, and the second minimum root mean square error for the other 4 clinics. Utilizing the system’s knowledge increased the utility of our highly deidentified data and improved the predictive power of the models.ConclusionsThe random forest method, enhanced with the system’s knowledge, provided reliable wait time predictions for new outpatients, regardless of low utility of the highly deidentified input data and the high variation in wait times across different clinics and patient types. The priority system was identified as a factor that contributed to long wait times, and a fast-track system was suggested as a potential solution.

Comparative assessment of customized (insignia) and non-customized bracket systems (Damon Q) for clinical effectiveness and efficiency-A clinical study

The study's goal was to compare and contrast the effectiveness and efficiency of customized and non-customized orthodontic brackets. 10 patients (Group A) were treated with a Customized section System (Insignia USA) and 10 patients (Group B) were treated with a Non-customized Bracket system (Damon).Gathering this data, the clinical effectiveness and efficiency was measured by estimating Initial Peer Assessment Rating (PAR) and Final PAR scores, assessing the complete therapy time, number of scheduled appointments, number of examination visits, number of loose brackets and pain rating during the treatment which was recorded with a numerical rating scale. The Insignia group outperformed the Damon group in terms of clinical efficiency, but there was no difference in PAR score reduction so overall clinical effectiveness of the Insignia and Damon groups was identical. Orthodontists would be able to give high-quality treatment in less time with fewer appointments and less chair time if they use the optimum bracket system.

The Impact of the COVID-19 Pandemic on Israeli Orthodontic Practice: A Clinic’s Activity and Patients’ Attitudes

The current study aimed to characterize the activity in orthodontic clinics during the COVID-19-induced lockdown and the inter-lockdown periods, as well as to evaluate patients’ perspectives with respect to their fears, their extent of cooperation with treatment, and their emergency needs during the lockdown. The data were gathered from 11 private orthodontic clinics from 1 January 2020 to 8 March 2021, which included three lockdowns and inter-lockdowns. Information specifying the number of admissions, missed appointments, and emergency visits was gathered. Four hundred and twenty-nine orthodontic patients treated in those clinics agreed to complete a questionnaire that evaluated their concerns and expectations, the treatment emergency issues, implementation of the orthodontist’s instructions, and contact with the clinical staff during lockdowns. There was a significant increase in the number of scheduled appointments during the inter-lockdown periods, compared with the pre-pandemic period (p = 0.001). No difference in the number of missed/canceled or emergency appointments was found between the different periods (p > 0.420). The majority (89.6%) of the emergency visits involved issues with appliances; 68.7% of the subjects were advised to present themselves at clinics. During the peaks of the waves of the COVID-19 pandemic, a sharp rise in the number of missed and urgent appointments was not found. Reducing the number of orthodontic emergencies may assist in reducing patient fears.

COVID-19 pandemic impact on Primary Health Care Accessibility in Portugal

The COVID-19 pandemic disrupted health systems worldwide, mobilizing most of its resources to COVID-19 care. In Portugal, since mid-March 2020, the scheduled assistance activity of the primary health care services has been altered or interrupted, to respond to the needs of users with suspected or diagnosed SARS-CoV-2 infection. This study intends aims to assess the impact of the COVID-19 pandemic in terms of access to primary health care during 2020 in Portugal. Primary Health Care accessibility data were extracted from the national data transparency portal. Data were aggregated by the 5 health regions and compared to homologous periods for years 2019 and 2020. In Portugal, in 2020 the number of primary health care consultations decreased in the regions of Alentejo (-5%), Algarve (-1%) and Centre (-1%) but increased in both North (+6%) and Lisbon and the Tagus Valley regions (+7%). The number of scheduled appointments decreased in the 5 regions (-16%), increasing the unscheduled appointments (+24%). Those differences were higher during the first lockdown (-42% schedule appointments vs + 13% unscheduled appointments). Presential consultations decreased by 38%, non-presential increased by 101%, and domiciliary consultations were reduced by 37%. Changes to regular activity of primary health care units compromised the access to presential health care by the non-COVID-19 population. After the first pandemic wave, the resumption of scheduled activity changed from face-to-face to non-presential consultation. The adoption of new technologies and telemedicine increased the total of registered consultations, compared to previous year. However, not all non-presential consultation is in fact patient-facing teleconsultation, with some of them being just for prescription renewal or to prescribe complementary exams. Predominantly urban regions were less affected by the suspension of presential activity, maintaining their assistance by non-presential provision of care and telework.Key messages Amidst the COVID-19 pandemic, the Portuguese primary health care services ensured the assistance to their population by non-presential provision of care.Predominantly rural regions were most affected by the suspension of presential consultation.

The Financial Cost of Interprofessional Ambulatory Training: What's the Bottom Line?

Team-based care is recommended as a building block of high-performing primary care but has not been widely adapted in training sites. Cost may be one barrier to a team-based approach. We quantified incremental annual faculty and staff costs as well as potential cost savings associated with an interprofessional (IP) ambulatory training program compared to a traditional residency clinic at the same site. Cost calculations for the 2017-2018 academic year were made using US Department of Labor median salaries by profession and divided by the number of residents trained per year. Cost implications of lower no-show rates were calculated by multiplying the difference in no-show rate by the number of scheduled appointments, and then by the weighted average of the reimbursement rate. A total of 1572 arrived appointments were seen by the 10 residents in the IP program compared with 8689 arrived appointments seen by 57 residents in the traditional clinic. The no-show rate was 11.5% (265 of 2311) in the IP program and 19.2% (2532 of 13 154) in the traditional clinic (P < .001). Total cost to the health system through higher staffing needs was $113,897, or $11,390 per trained resident. Total costs of the IP model due to higher faculty and staff to resident ratios totaled $11,390 per resident per year. Understanding the faculty and staff costs and potential cost-saving opportunities associated with transformation to an IP model may assist in sustainability.

Patient navigation to improve diabetes outpatient care at a safety-net hospital: a retrospective cohort study

BackgroundRecent emphasis on value based care and population management, such as Accountable Care Organizations in the United States, promote patient navigation to improve the quality of care and reduce costs. Evidence supporting the efficacy of patient navigation for chronic disease care is limited. The objective of this study was to evaluate the effect of a patient navigation program on medical and administrative outcomes among patients with diabetes in an urban, safety-net hospital clinic setting.MethodsA retrospective cohort study with pre- and post-intervention periods was conducted. Eligible patients were those with A1C ≥ 8.5% and at least one appointment no-show in the previous 12 months. The intervention and reference groups were balanced on observed characteristics and baseline outcome levels using propensity score matching. The effect of patient navigation was isolated using the difference-in-differences approach. Primary outcomes were A1C, low-density lipoprotein cholesterol, triglycerides, random urine microalbumin, the number of scheduled appointments, clinic visits, emergency visits, and inpatient stays, and the percentage of arrivals, cancellations, and no-shows to scheduled appointments.ResultsOf 797 eligible patients, 328 entered the navigation program. Matching reduced the sample size to 392 individuals (196 in each group). Patient navigation resulted in improved A1C (−1.1 percentage points; p < .001), more scheduled appointments (+ 5.3 per year; p < .001), more clinic visits (+6.4 per year; p < .001), more arrivals to scheduled appointments (+7.4 percentage points; p = .009) and fewer no-shows (−9.8 percentage points; p < .001).ConclusionsNavigation was associated with improved glycemic control and better clinic engagement among patients with diabetes. Further research is important to identify what features of navigation in diabetes care are critical to achieving success and to understand navigators’ role in other settings.

Walk-In Triage Systems in University Counseling Centers

ABSTRACTTo meet the complex mental health needs of students, some university counseling centers (UCCs) have implemented walk-in triage intake systems, which have not yet been empirically investigated. This study compared client and clinician differences (N = 5564) between a traditional scheduled intake system (Year 1) and a walk-in triage system (Year 2) at a large, southeastern UCC. Results showed a significant increase in clients’ attendance rates and clinicians’ caseloads, a significant decrease in no-show rates, and no change in students’ symptom severity at intake between Years 1 and 2. Clinicians’ number of scheduled appointments were unchanged, indicating that clinicians were already at maximum capacity for appointments in Year 1. Results are discussed in terms of the benefits and challenges that walk-in triage systems present to students, universities, and UCCs.

Appointment Scheduling Under Patient Preference and No-Show Behavior

Motivated by the rising popularity of electronic appointment booking systems, we develop appointment scheduling models that take into account the patient preferences regarding when they would like to be seen. The service provider dynamically decides which appointment days to make available for the patients. Patients arriving with appointment requests may choose one of the days offered to them or leave without an appointment. Patients with scheduled appointments may cancel or not show up for the service. The service provider collects a “revenue” from each patient who shows up and incurs a “service cost” that depends on the number of scheduled appointments. The objective is to maximize the expected net “profit” per day. We begin by developing a static model that does not consider the current state of the scheduled appointments. We give a characterization of the optimal policy under the static model and bound its optimality gap. Building on the static model, we develop a dynamic model that considers the current state of the scheduled appointments, and we propose a heuristic solution procedure. In our computational experiments, we test the performance of our models under the patient preferences estimated through a discrete choice experiment that we conduct in a large community health center. Our computational experiments reveal that the policies we propose perform well under a variety of conditions.

Intervention program to reduce waiting time of a dermatological visit: Managed overbooking and service centralization as effective management tools

Long waiting times are an impediment of dermatological patient care world-wide, resulting in significant disruption of clinical care and frustration among carers and patients. To reduce waiting times for dermatological appointments. A focus group including dermatologists and management personnel reviewed the scheduling process, mapped potential problems and proposed a comprehensive intervention program. The two major approaches taken in the intervention program were revision of the scheduling process by managed overbooking of patient appointments and centralization of the dermatological service into a centralized dermatological clinic. Following the intervention program, the average waiting time for dermatological appointments decreased from 29.3 to 6.8 days. The number of scheduled appointments per 6 months rose from 17,007 to 20,433. Non-attendance proportion (no-show) decreased from 33% to 28%. Dermatologist work-hours were without significant change. Waiting lists for dermatological consultations were substantially shortened by managed overbooking of patient appointments and centralization of the service.

The variable anchorage straight wire technique compared with the straight wire technique in deep overbite correction

The aim of this retrospective study was to compare the treatment results and the number of required treatment appointments between the variable anchorage straight wire technique (VAST) and the straight wire (SW) technique. The subjects were 53 Caucasian patients of both sexes (25 males and 28 females, mean age 13.5 years at the start of treatment), with an overjet > or = 4 mm and an overbite > or = 3 mm. The patients were divided into four groups, VAST (n = 31) or SW (n = 22), extraction or non-extraction, and were treated by the same orthodontist. Variables from two lateral cephalograms obtained before and at the completion of active treatment, and the number of scheduled appointments were compared between the two techniques. The main difference between the two techniques was the bracket design. With the VAST, the bracket allowed both tipping and parallel movements with the possibility to combine double archwires. Due to the influence of the Begg technique, no extra-oral traction was needed in the VAST groups and Class II elastics were used at the start of treatment. Both techniques seemed to produce equal treatment results. However, in this study, it was shown that in deep overbite correction, the VAST required fewer scheduled appointments than the SW technique.

Compliance with prenatal care visits in substance abusers

Objective: We sought to determine whether pregnant, inner-city substance abusers, cared for in a multidisciplinary setting, had comparable numbers of missed appointments and similar outcomes in comparisonwith a low-risk patient population.Methods: A retrospective review was conducted on a sample of 97 patients with uncomplicated prenatal care over a 7-year period (1994-2001). They were comparedto a sample of 88 substance abusers cared for and delivered at Bellevue Hospital over the same period. Demographic information was recorded, as well as frequency of prenatal visits, number of missed appointments,birth weight, and gestational age at delivery.Results: In our population, substance abusers were found to be significantly older (28.9 vs. 25.6 years, p < 0.0001), had had more pregnancies(4.3 vs. 2.4, p < 0.0001) and had had more children (2.0 vs. 0.7, p < 0.0001) than controls. Both substance abusers and control patients had a similar number of scheduled appointments (11.4 in eachgroup, p = 0.99), but substance abusers missed more appointments (1.6 vs. 0.7, p < 0.0005).Conclusions: When cared for in a multidisciplinary setting, substance abusers will attend an adequatenumber of prenatal visits. However, they are still more likely than non-substance abusers to miss visits, although the difference may not be clinically significant.