Effects of waiting for outpatient physiotherapy services in persons with musculoskeletal disorders: a systematic review

Abstract

Background In response to issues with timely access for musculoskeletal physiotherapy, telephone assessment and advice services have been evaluated in primary care settings. It is unclear whether this service model can reduce wait times and non-attendance rates for Emergency Department (ED) physiotherapy, compared to usual care. A secondary aim was to evaluate service user acceptability. Methods This was a single-site cohort study that compares data on non-attendance rates, wait time to rst physiotherapy contact and participant satisfaction between patients that opted for a service based on initial telephone assessment and advice, versus routine face-to-face appointments. 116 patients were referred for ED physiotherapy over the 3-month pilot at the ED and outpatient physiotherapy department, X, Ireland. 91 patients (78%) opted for the telephone assessment and advice service, with 40% (n=36) contacting the service. 25 patients (22%) opted for the face-to-face service. Data on non-attendance rates and wait time was gathered using the hospital data reporting system. Satisfaction data was collected on discharge using a satisfaction survey adapted from the General Practice Assessment Questionnaire. Independent-samples t-test or Mann Whitney U Test was utilised depending on the distribution of the data. For categorical data, Chi-Square tests were performed. A level of signi cance of p ≤ 0.05 was set for this study. Results Those that contacted the telephone assessment and advice service had a signi cantly reduced wait time (median 6 days; 3-8 days) compared to those that opted for usual care (median 35 days; 19-39 days) (p ≤ 0.05). There was no signi cant between-group differences for non-attendance rates or satisfaction. Conclusion Given the faster access to ED physiotherapy, without compromising on service user satisfaction, this telephone assessment and advice service, which can be introduced rapidly, could be helpful in triaging referrals and minimising face-to-face consultations in line with COVID-19 recommendations. However, a large scale study is warranted to con rm these ndings.

Waiting Time as an Indicator for Health Services Under Strain: A Narrative Review

“…Despite a reduction over time, SES had a statistically significant effect on waiting time in every year of analysis ( Table 2). 58 There are multiple review papers that describe the interaction between waiting time for allied health services and clinical outcomes; [74][75][76][77] however, there is little evidence available on whether these times are affected by SES. We identified 4 studies that describe waiting-time inequality in the allied health sector.…”

“…Among respondents who reported their clinic time during the 24-hour assessment period, a median (95% CI) of 86 [83][84][85][86][87][88] minutes was spent in-clinic. 63 Those in the lowest income quartile reported a mean [95% CI] clinic time of 91 [87][88][89][90][91][92][93][94][95] minutes compared with those in the highest income quartile, who reported a mean clinic time of 72 [65][66][67][68][69][70][71][72][73][74][75][76][77][78] minutes. 63 Disproportionate ill health in lower SES patients has consistently been rejected as an explanation for this gradient.…”

A Multi-Faceted Strategy for Evidence Translation Reduces Healthcare Waiting Time: A Mixed Methods Study Using the RE-AIM Framework

“…Services provided in community and outpatient settings include allied health services, rehabilitation, chronic disease management programs and a broad variety of healthcare services provided through community health services. Delays in access to these services have consequences, including lower levels of engagement, missed opportunities for treatment, and worse health outcomes (2)(3)(4). Furthermore, long waiting lists contribute to service inefficiencies, as resources are redirected from frontline care to managing the waiting list (5).…”

A classification-based approach to low back pain in primary care – protocol for a benchmarking controlled trial

“…In addition to patient-related factors and management, professional and health care system-related factors also affect the outcomes of patients with LBP. Such factors include imaging policy, patient education, the attitudes and beliefs of health care professionals, and the timing of rehabilitation [2,13,14].…”