Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, NC, United Stated of America.
Duke Clinical Research Institute, Duke University, Durham, NC, United Stated of America.
PLoS One. 2021 May 28;16(5):e0251336. doi: 10.1371/journal.pone.0251336. eCollection 2021.
Chronic pain affects 50 million Americans and is often treated with non-pharmacologic approaches like physical therapy. Developing a no-show prediction model for individuals seeking physical therapy care for musculoskeletal conditions has several benefits including enhancement of workforce efficiency without growing the existing provider pool, delivering guideline adherent care, and identifying those that may benefit from telehealth. The objective of this paper was to quantify the national prevalence of no-shows for patients seeking physical therapy care and to identify individual and organizational factors predicting whether a patient will be a no-show when seeking physical therapy care.
Retrospective cohort study.
Commercial provider of physical therapy within the United States with 828 clinics across 26 states.
Adolescent and adult patients (age cutoffs: 14-117 years) seeking non-pharmacological treatment for musculoskeletal conditions from January 1, 2016, to December 31, 2017 (n = 542,685). Exclusion criteria were a primary complaint not considered an MSK condition or improbable values for height, weight, or body mass index values. The study included 444,995 individuals.
Prevalence of no-shows for musculoskeletal conditions and predictors of patient no-show.
In our population, 73% missed at least 1 appointment for a given physical therapy care episode. Our model had moderate discrimination for no-shows (c-statistic:0.72, all appointments; 0.73, first 7 appointments) and was well calibrated, with predicted and observed no-shows in good agreement. Variables predicting higher no-show rates included insurance type; smoking-status; higher BMI; and more prior cancellations, time between visit and scheduling date, and between current and previous visit.
The high prevalence of no-shows when seeking care for musculoskeletal conditions from physical therapists highlights an inefficiency that, unaddressed, could limit delivery of guideline-adherent care that advocates for earlier use of non-pharmacological treatments for musculoskeletal conditions and result in missed opportunities for using telehealth to deliver physical therapy.
慢性疼痛影响了 5000 万美国人,通常采用物理治疗等非药物方法进行治疗。为接受肌肉骨骼疾病物理治疗的个人开发一个预未到诊模型有几个好处,包括在不增加现有提供者数量的情况下提高劳动力效率、提供符合指南的护理以及识别可能从远程医疗中受益的人员。本文的目的是量化全国范围内因接受肌肉骨骼疾病物理治疗而未到诊的患者比例,并确定个人和组织因素,预测患者在寻求物理治疗时是否会未到诊。
回顾性队列研究。
美国一家提供物理治疗的商业机构,在 26 个州拥有 828 家诊所。
2016 年 1 月 1 日至 2017 年 12 月 31 日期间因肌肉骨骼疾病寻求非药物治疗的青少年和成年患者(年龄截止点:14-117 岁)(n=542685)。排除标准为主要投诉不被认为是肌肉骨骼疾病或身高、体重或体重指数值不切实际。本研究包括 444995 人。
肌肉骨骼疾病未到诊的发生率和患者未到诊的预测因素。
在我们的人群中,73%的人在给定的物理治疗护理过程中至少错过 1 次预约。我们的模型对未到诊有中等程度的预测能力(c 统计量:所有预约为 0.72,前 7 次预约为 0.73),且校准良好,预测和观察到的未到诊率吻合较好。预测更高未到诊率的变量包括保险类型;吸烟状况;更高的 BMI;以及更多的既往取消预约次数、就诊日期和预约日期之间的时间、以及当前就诊和上次就诊之间的时间。
在接受物理治疗治疗肌肉骨骼疾病时,未到诊的比例很高,这表明存在效率低下的问题,如果不加以解决,可能会限制符合指南的护理的提供,这种护理提倡更早地使用非药物治疗肌肉骨骼疾病,并导致错过使用远程医疗提供物理治疗的机会。