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PhysioNow – A digital musculoskeletal patient self-assessment application, transforming access to MSK physiotherapy services
Physiotherapy (United Kingdom) ; 114:e102-e103, 2022.
Article in English | EMBASE | ID: covidwho-1701791
ABSTRACT
Keywords Digital;Transformation;Quality

Purpose:

PhysioNow is a digital self-assessment application that was collaboratively developed by Connect Health and EQL. The main aims of introducing this technology were to (1) Improve patient access pathways (2) Utilise digital triage to stratify patients, allowing urgent clinical conditions to be picked up rapidly and directed to appropriate care (3) Work towards recommendations of the TOPOL report and the NHS five-year forward view around digital healthcare (4) Reduce administrative processing time (5) Provide information to improve the quality and focus of clinical consultations

Methods:

PhysioNow was co-produced by digital and clinical colleagues as informed by an EIA through an innovative service improvement programme. An AGILE approach was adopted within implementation, working in sprints to ensure all components were met. Process design was applied to use robotic process automation (RPA) in both registration of patients and handling of patients in the clinical system following PhysioNow completion, additionally the linking of our data warehouse to the registration portal and web application via an Application Programming Interface (API) allowed seamless patient transition and information flow. Time was invested developing the clinical decision tree algorithms to ensure patients were asked appropriate questions and stratified safely, in line with normal volumes of red flags/urgent cases. Decision tree changes involved clinician feedback and clinical audit of all patients’ outcomes to continually improve the decision tree. Patient focus groups were employed to look at specific questions and all patients that used PhysioNow were involved in service user feedback.

Results:

Between July 2020 and the 14th of April 2021 PhysioNow was transitioned in a phased approach to 15 NHS physiotherapy services. To date, 22,422 patients were eligible to use PhysioNow and 96% were offered the opportunity to complete it. 15,366 patients have subsequently completed, with an uptake of 73%. 11,219 patients have been stratified to routine care, 3393 patients were stratified to an urgent physiotherapy assessment, 487 patients were advised to seek advice of NHS 111. Benefits achieved are an accessible platform for patients available 24/7;patient access and improved patient journey, clinicians effectively using PhysioNow outputs to target and inform clinical assessment;improved waiting times;reduction in volume of admin registrations via RPA has led to financial savings. Conclusion(s) This programme of work has enabled Connect Health to deliver a safe, effective, cost neutral solution to stratification of patients referred to Community MSK Physiotherapy services. We have demonstrated high levels of patient uptake by adopting an AGILE delivery cycle and identified barriers to clinical effectiveness and user accessibility/digital literacy via Continuous Improvement. Plans include further stratification of clinical conditions, enabling direct referral from PhysioNow into a supported self-management environment along with using AI and machine learning, to enhance the decision tree and pathways. Impact This project has been implemented into routine practice across Connect Health, providing patients with a new accessible way of accessing MSK physiotherapy services. PhysioNow has been trialled with Welsh Health Boards to support Covid Recovery successful and demonstrates enhanced patient care pathways, clinician interactions and effectively detects clinically urgent conditions that needed urgent care. Funding acknowledgements This work was funded by Connect Health and EQL as the Healthcare provider and the technology develop respectively.
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Full text: Available Collection: Databases of international organizations Database: EMBASE Language: English Journal: Physiotherapy (United Kingdom) Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: EMBASE Language: English Journal: Physiotherapy (United Kingdom) Year: 2022 Document Type: Article