Democratising the Patient Experience
Using PEP Health insights to support the investigation of Health Inequalities
COVID-19 pandemic has exacerbated inequalities in healthcare
PEP Health insights reveal patients are well placed to report acts of discrimination
Patient Experience data should be considered in the development of health inequalities policy and improvement programs
The impact of the COVID-19 pandemic has replicated existing health inequalities and, in some cases, has increased them. PEP Health is a data source agnostic platform that gathers and analyses patient comments from a multitude of publicly available sources such as Facebook, Twitter, NHS.UK, SMS, digital webforms and more. Text based patient comments are where the richest insights are found and may be especially effective to capture the voices of marginalized patient populations, helping to reveal what is particularly salient to them.
PEP Health gathers more than 1 million data points a month from patients across publicly available platforms and internal datasets such as the Friends and Family Test (FFT). The comments are intelligently scored and themed and tagged to location and service using novel Natural Language Processing. The use of machine learning enables automated, unfiltered and real time access to what patients really think about the care they receive.
Our data reveals that patients are well placed to observe and report episodes of discrimination, racism, ageism, and sexism that they experience. Below, are two comments taken from the public domain that illustrate how patients talk about discrimination in the care they receive.
Attitude of staff to older patients - In both [names of providers redacted] I am a reasonably intelligent and well educated woman of 78 and still have my marbles! Remarks made in a friendly and intelligent way to members of staff are sometimes slapped down by a condescending and patronising response like bless you. I am pleased to see the rainbow outside the hospital as well as all the work to combat racism, and any lack of respect towards disabled people, but it seems that it is considered acceptable to treat older people in a patronising way. I feel that this is ageism and I suggest that training should include forbidding certain words and phrases as responses to a patient's questions or remarks.
During my stay at [name of provider redacted] I noticed how the midwife assigned to my ward showed preferential treatment to the white patients on the ward. I was treated very differently compared to them and the midwives were trying to encourage me to go home despite showing signs that I was in labour. Due to the lack of care I nearly gave birth in the hospital bath tub I was refused entry to the birthing center despite the fact that this was part of my birth plan and I was r...ushed to the delivery suite only 14 minutes before my baby was born. I gave birth alone without my birthing partner without pain killers for a large majority of my labour I was told to go into a bath tub and 'flick water' on myself to alleviate the pain despite stating that I wanted to use gas and air and pethidine in my birth plan. I gave birth alone not because of the pandemic but because of the racist attitude of the initial midwife that I had at my ward. She evidently shared her views with the midwife who took over and as a result my signs of labour were ignored. No woman should experience what I experienced and the statistics that Black and Asian Women are more likely to lose their babies or even die during child birth is no longer surprising.
Patients are well placed to observe discrimination in their care experience. Capturing these experiences is an important step in the process towards quality improvement and the development of health inequalities policy. Traditional methods such as non-standardised surveys such as the Friends & Family Test, are typically slow to analyse and have a response rate of less than 20%. Low response rates and skewed representation create a bias in the data that is collected for patient experience and access to more channels of communication, online, provide a unique way to cast a wider net. Patients who have experienced an episode of discrimination have access to multiple online platforms and channels, which improves access and representation in the patient experience feedback that is used to inform improvement strategies and policy. Unlike traditional surveys or other one-off feedback methods, organic unprompted comments posted by a patient at the time of their care gives richer insights into a wider spectrum of opinions.
We need to ensure that the health inequalities agenda and associated policies and actions are informed by real-time, comprehensive, and patient-centred data, supporting the measurement and evaluation of the impact of interventions. PEP Health offers access to a wider perspective on patient experience and should be considered in the current development of the NHS’s data driven strategy to tackle the complex and changing landscape of health inequalities.