Inequalities and usage of a patient portal: observational study of the NHS App in England. (Preprint)

Author:

KC Sukriti,Papoutsi ChrysanthiORCID,Reidy ClaireORCID,Gudgin Bernard,Powell John,Majeed AzeemORCID,Greaves Felix,Laverty Anthony A

Abstract

BACKGROUND

The adoption of patient portals, supported by initiatives such as the national rollout of the NHS App in England, may improve patient engagement in healthcare. However, concerns remain regarding disparities in the uptake and utilisation of various patient portal features, which have not been fully explored for the NHS App. Understanding patterns of use of the various app functions across diverse populations is essential to address potential inequality trends and to ensure equitable implementation practices.

OBJECTIVE

We explored population factors related to deprivation, age, sex, ethnicity, and long-term healthcare needs associated with uptake of the NHS App features using data from 6,386 General Practices (GP)s in England.

METHODS

Negative binomial regression models were used to explore variations in weekly rates of NHS App features used (registrations, logins, prescriptions ordered, medical record views and appointments booked) based on GP level patient sociodemographic variables split into quantiles (for deprivation, Q5= least deprived practices and for all other variables, Q4= practices with the highest population percentage for the given variable).

RESULTS

We found variations in patient engagement with the different features and among the different demographic categories. There was lower use of features overall in deprived areas (e.g. Q5 vs Q1= -34.0% for registrations, -34.9% for logins, -39.7% for appointment booked, -32.3% for medical record views and -9.9% for prescriptions; P<.001) and in practices with more male patients (e.g. Q4 vs Q1= -7.1% for registration, -10.4% for login, -36.4% for appointments booked, -12.0% for medical record views, -14.4% for prescriptions; P<.001). Larger practices had an overall higher use of different features (e.g. Q4 vs Q1= 3.2% for registration, 11.7% for logins, 73.4% for appointments booked, 23.9% for medical record views and 20.7% for prescriptions; P<.001), as well as those with more white patients (e.g. Q4 vs Q1= 1.9% for registration, 9.1% for logins, 14.1% for appointments booked, 28.7% for medical record views, 130.4% for prescriptions ordered; P<.001). Whereas, usage patterns varied for practices with more younger population (e.g. Q4 vs Q1= 3.1% for registration, 5.6% for logins, 46.5% for appointments booked, -14.8% for prescriptions; P<.001 and 1.7% for medical record views, P=0.003) and in those practices with more patients with long-term healthcare needs (e.g. Q4 vs Q1= -3.6% for registrations, -20.0% for appointments booked, 6.0% for medical record views, 18.3% for prescriptions; P<.001 and -1.7% for logins; P=0.001).

CONCLUSIONS

This study highlights inequalities in the use of the NHS App features, revealing a deprivation gradient and variations across the different demographic categories. Recognising and dealing with these patterns is crucial for addressing inequities in digital health engagement. Tailored interventions and patient support are required to ensure equitable access and utilisation among diverse patient groups.

CLINICALTRIAL

N/A

Publisher

JMIR Publications Inc.

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