Ophthalmic epidemiology · 2024
Weather Patterns, Patient, and Appointment Characteristics Associated with Cancellations and No-Shows in a Glaucoma Clinic.
СтатьяНаблюдательное исследованиеПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Ojalvo Israel, Mehran Nikki, Sharpe James, Zhang Qiang, Myers Jonathan S, Razeghinejad Reza, Lee Daniel, Kolomeyer Natasha Nayak
Аннотация
PURPOSE: To identify factors that are associated with no-shows and cancellations in a glaucoma clinic.
METHODS: Retrospective observational study of patients seen at a glaucoma clinic over a two-year period (6/2017-5/2019). Demographics and clinic information were recorded from the electronic medical record. A total of 36,810 visits from 7,383 patients were studied. Weather data was collected from the National Centers for Environmental Information. Distance analysis was calculated utilizing Bing Maps application programming interface (API) on Microsoft Excel. Visits were divided into three groups based on appointment status: kept, cancelled, and no-show.
RESULTS: Bivariate analysis found a statistically significant difference in various factors amongst patients based on appointment status. Patients <15 miles from clinic had a higher rate of no-show, but a lower rate of cancellations compared to those farther (p < 0.0001) Using multivariable logistic regression, the following factors were associated with the likelihood of patient cancellation: average snowfall (Odds Ratio = 1.37); presence of storm event (OR = 1.12), new visit (OR = 1.82), follow-up appointments (OR = 1.90), and travel distance > 15 miles (OR = 1.11). The following factors were associated with patient no-show: resident clinic (OR = 1.79), new visit (OR = 2.24), follow-up appointments (OR = 2.18), age (OR = 0.99), average snowfall (OR = 1.27), presence of storm event (OR = 1.41), average windspeed (OR = 0.98), and travel distance > 15 miles (OR = 0.67).
CONCLUSION: Patient age, gender, travel distance, appointment type, and weather were all significantly associated with rates of patient cancellations and no-shows. These risk factors could lead to interventions to improve appointment adherence and patient retention. Weather is an under-analyzed factor in patient follow-up rates that warrants further investigation.
METHODS: Retrospective observational study of patients seen at a glaucoma clinic over a two-year period (6/2017-5/2019). Demographics and clinic information were recorded from the electronic medical record. A total of 36,810 visits from 7,383 patients were studied. Weather data was collected from the National Centers for Environmental Information. Distance analysis was calculated utilizing Bing Maps application programming interface (API) on Microsoft Excel. Visits were divided into three groups based on appointment status: kept, cancelled, and no-show.
RESULTS: Bivariate analysis found a statistically significant difference in various factors amongst patients based on appointment status. Patients <15 miles from clinic had a higher rate of no-show, but a lower rate of cancellations compared to those farther (p < 0.0001) Using multivariable logistic regression, the following factors were associated with the likelihood of patient cancellation: average snowfall (Odds Ratio = 1.37); presence of storm event (OR = 1.12), new visit (OR = 1.82), follow-up appointments (OR = 1.90), and travel distance > 15 miles (OR = 1.11). The following factors were associated with patient no-show: resident clinic (OR = 1.79), new visit (OR = 2.24), follow-up appointments (OR = 2.18), age (OR = 0.99), average snowfall (OR = 1.27), presence of storm event (OR = 1.41), average windspeed (OR = 0.98), and travel distance > 15 miles (OR = 0.67).
CONCLUSION: Patient age, gender, travel distance, appointment type, and weather were all significantly associated with rates of patient cancellations and no-shows. These risk factors could lead to interventions to improve appointment adherence and patient retention. Weather is an under-analyzed factor in patient follow-up rates that warrants further investigation.