The opportunity to join up health and social care at all levels in the system, create better outcomes and a less fragmented experience for people, is a core reason why integrated care systems (ICS) were created. Key to the vision statement set out by NHS England and Improvement is how ICSs must use patient experience, engagement and insights to tackle the widening gap of variation in services across the country. Yet, the incumbent methods of collecting this data are limited and insights are difficult to codify.
Patient experience, as defined by the Beryl Institute, is ‘the sum of all interactions, shaped by an organisation’s culture, that influence patient perceptions across the continuum of care’. This experience is not just about the service someone received or whether that person was seen on time, it also covers whether they felt treated with dignity and respect, and whether they felt that the doctor told them about their diagnosis in a sensitive way.
We are now rapidly moving towards ICSs becoming statutory. This period of change is a great opportunity to leverage data at scale to transform the quality and experiences patients have at a system level.
Legacy models for gathering patient experience are not fit for purpose in ICSs
Currently in the health sector, the most common method of collecting patient experience is through traditional surveys, such as NHS England’s ‘Patient Experience Survey’ (PES), the Friends and Family Test or similar. Although they serve some purpose in collecting the feedback of patients along critical points in the patient pathway at specific locations, their ability to generate insight and real improvement are limited. In fact, they often achieve low very response rates and suffer from key limitations such as timeliness of results and accurate patient representation. There are also significant delays between patient experience collection, manual analysis and the sharing of outcomes which mean that the opportunities for real-time, actionable quality improvement are often missed. Surveys can be inflexible and are often designed from the perspective of the healthcare professional and management point of view, with limited patient input.
Finally, the richest patient experience insights are found in the text feedback. However, the free text comments are also the most difficult to codify because they are messy and unstructured. New machine learning domains, such as natural language processing (NLP), are an excellent opportunity for progress in patient experience. Using trained NLP algorithms, based on real patient comments, we can unlock the insight from the high volume of online comments to derive accurate, actionable insight from the text, not only at an organisational level, but across patient pathways and disease conditions.
The restructuring of the health and social care system into ICSs provides a unique and necessary opportunity to modernise and improve the way we gather, analysis and generate insight from patient experience data.
Online feedback as a complementary model of generating patient experience insight
Online patient feedback from social media generates more than a million comments a month in England across all NHS trusts and is a growing platform for the patient voice. The majority (60%) of these comments are positive, and importantly patients are posting unpromoted about the concerns and observations that matter most to them, across the entire pathway of care.
In fact, online feedback presents a unique opportunity to generate a timely, representative and actionable set of insights on patient experience that could be used to supplement the incumbent survey models. This feedback can be collected across the care pathway – from community services through to primary care, secondary care and back again. It can then be automatically scored and themed to generate actionable real time insight – positioning patients as the architect of quality improvement.
Improving patient experience at an ICS level is about improving all of the interactions that influence patient perceptions of the care they receive. The exchanges people have with healthcare providers are not in isolation with other parts of the system – be it housing, primary care or secondary care. What we need to do is start to think about patient experience in pathways across the whole system, rather than in single organisations. Doing this in conjunction with direct surveys and online feedback, will provide us with the opportunity to do this.
How data plays a key role in the collection of patient experience
Data and machine learning enable us to generate innovative solutions to the current challenges in patient experience and quality improvement.
By listening to patients at scale we can use the ‘wisdom of the crowd’ and harness their collective knowledge. This data can then be used to benchmark departments, providers, regions, and national trends, as well as the variation in critical points along the patient pathway. This links back to NHS England and Improvement’s vision of tackling unwarranted variation in service quality, access and performance. A more modernised approach to patient feedback collection, analysis and reporting could also empower stakeholders to provide a safer, better patient experience by helping to prioritise resources and improve services.
Now is the time to start asking ourselves what we can do to ensure the way patient experience is captured at an ICS level drives improvement.
The future of patient experience
The status quo of patient experience isn’t providing value for patients, or the organisations tasked improving it.
By analysing patient comments in real-time we will be able to better make changes at a local level, place based level and national level. Continuously listening to patients ensures quality improvement initiatives therefore have noticeable effect. And through gathering richer insights from a wider sample of patients, we can ultimately democratise the patient voice.
By Dr Meghan Leaver/PEP Health
