Product Case Study: WellSaid, health messaging tool

WellSaid is a health communication tool, designed to collect Patient Reported Experience/Outcome Measures (PREMs/PROMs) for healthcare services looking to drive continuous improvement models.

94% of UK adults, own or use a mobile phone capable of receiving SMS messages (Ofcom 2017) and 75% or patients believe that mobile health solutions can convey significant health benefits to them (GSMA, 2012). Further to this SMS based questionnaires are shown to have comparable accuracy to pen and paper, but with higher response rates (Christie et al., 2014).

Developed in partnership with NHS Wales, WellSaid uses “chatbots” to engage patients, at distance across multiple messaging platforms (SMS, FB messenger, Email). This allows the healthcare team to:

• Gather Patient Consent — WellSaid puts your patients in charge of consent at every step of engagement. Promoting trust through consistent and clear permissions. Ensuring your service meets UK legislation.
• Engage Groups Automatically — Build customised conversations and trigger them based on time or patient response. Then monitor your interactions, with a simple to learn dashboard and control panel.
• Improve Service Outcomes — Automatically analyse quantitative data and usage analytics. Export qualitative responses for further analysis and produce reports for management meetings.

The platform was built with minimal resources using a lean, agile approach. The specifciation was driven by:

• The patient group—catering for low technology access, low literacy and low self-efficacy groups
• The healthcare system — high levels of information governance and legacy hardware/OS with strict firewalls

The user experience of the system was key, but had to be shaped entirely by the spec. Given the minimal resources we could spend open source frameworks work our go to for building on:

• Botman — a open source multi channel messaging framework, which connects to Nexmo, a GDPR compliant SMS gateway
• Larvel — to build the automated/scheduled messaging (conversations) covering various formats and triggers
• Charts.js — to build the automated analytics, with a potentially complex data visualisation
• Bootstrap UI — for the front end CSS, which met accessibility standards but provided a fast/cheap way to build the system

The platform is now live with the NHS. In trials with NHS Wales, WellSaid achieved an average response rate of 77% in two interventions over 12 weeks with 70% of patients providing feedback for continuous improvement of the service. This far exceeds existing solutions in both efficiency and cost. To date, three research papers have been written on the impact of the system and data presented at several scientific conferences.