Differences in usage of a patient portal across socio-demographic groups: observational study of the NHS App in England
File(s)
Published version
Author(s)
Type
Journal Article
Abstract
Background:
The adoption of patient portals, such as the National Health Service (NHS) App in England, may improve patient engagement in health care. However, concerns remain regarding differences across sociodemographic groups in the uptake and use of various patient portal features, which have not been fully explored. Understanding the use of various functions across diverse populations is essential to ensure any benefits are equally distributed across the population.
Objective:
This study aims to explore differences in the use of NHS App features across age, sex, deprivation, ethnicity, long-term health care needs, and general practice (GP) size categories.
Methods:
We used weekly NHS App use data from the NHS App dashboard for 6386 GPs in England from March 2020 to June 2022. Negative binomial regression models explored variations in weekly rates of NHS App features used (registrations, log-ins, prescriptions ordered, medical record views, and appointments booked). Outcomes were measured as weekly rates per 1000 GP-registered patients, and we conducted separate models for each outcome. Regression models included all covariates mentioned above and produced incident rate ratios, which we present here as relative percentages for ease of interpretation. GP-level covariate data on sociodemographic variables were used as categorical variables in 5 groups for deprivation (Q1=least deprived practices and Q5=most deprived practices) and 4 groups for all other variables (Q1=least deprived practices and Q4=most deprived practices).
Results:
We found variations in the use of different features overall and across sociodemographic categories. Fully adjusted regression models found lower use of features overall in more deprived practices (eg, Q5 vs Q1: registrations=–34%, log-ins=–34.9%, appointments booked=–39.7%, medical record views=–32.3%, and prescriptions ordered=–9.9%; P<.001). Practices with greater proportions of male patients also had lower levels of NHS App use (eg, Q4 vs Q1: registration=–7.1%, log-in=–10.4%, and appointments booked=–36.4%; P<.001). Larger practices had an overall higher use of some NHS App features (eg, Q4 vs Q1: registration=3.2%, log-ins=11.7%, appointments booked=73.4%, medical record views=23.9%, and prescriptions ordered=20.7%; P<.001), as well as those with greater proportions of White patients (eg, Q4 vs Q1: registration=1.9%, log-ins=9.1%, appointments booked=14.1%, medical record views=28.7%, and prescriptions ordered=130.4%; P<.001). Use patterns varied for practices with greater proportions of patients with long-term health care needs (eg, Q4 vs Q1: registrations=–3.6%, appointments booked=–20%, and medical record views=6%; P≤.001).
Conclusions:
This study highlights that the use of the NHS App features varied across sociodemographic groups. In particular, it is used less by people living in more deprived areas. Tailored interventions and patient support are required to ensure that any benefits from the NHS App are spread equally throughout the population.
J Med Internet Res 2024;26:e56320
The adoption of patient portals, such as the National Health Service (NHS) App in England, may improve patient engagement in health care. However, concerns remain regarding differences across sociodemographic groups in the uptake and use of various patient portal features, which have not been fully explored. Understanding the use of various functions across diverse populations is essential to ensure any benefits are equally distributed across the population.
Objective:
This study aims to explore differences in the use of NHS App features across age, sex, deprivation, ethnicity, long-term health care needs, and general practice (GP) size categories.
Methods:
We used weekly NHS App use data from the NHS App dashboard for 6386 GPs in England from March 2020 to June 2022. Negative binomial regression models explored variations in weekly rates of NHS App features used (registrations, log-ins, prescriptions ordered, medical record views, and appointments booked). Outcomes were measured as weekly rates per 1000 GP-registered patients, and we conducted separate models for each outcome. Regression models included all covariates mentioned above and produced incident rate ratios, which we present here as relative percentages for ease of interpretation. GP-level covariate data on sociodemographic variables were used as categorical variables in 5 groups for deprivation (Q1=least deprived practices and Q5=most deprived practices) and 4 groups for all other variables (Q1=least deprived practices and Q4=most deprived practices).
Results:
We found variations in the use of different features overall and across sociodemographic categories. Fully adjusted regression models found lower use of features overall in more deprived practices (eg, Q5 vs Q1: registrations=–34%, log-ins=–34.9%, appointments booked=–39.7%, medical record views=–32.3%, and prescriptions ordered=–9.9%; P<.001). Practices with greater proportions of male patients also had lower levels of NHS App use (eg, Q4 vs Q1: registration=–7.1%, log-in=–10.4%, and appointments booked=–36.4%; P<.001). Larger practices had an overall higher use of some NHS App features (eg, Q4 vs Q1: registration=3.2%, log-ins=11.7%, appointments booked=73.4%, medical record views=23.9%, and prescriptions ordered=20.7%; P<.001), as well as those with greater proportions of White patients (eg, Q4 vs Q1: registration=1.9%, log-ins=9.1%, appointments booked=14.1%, medical record views=28.7%, and prescriptions ordered=130.4%; P<.001). Use patterns varied for practices with greater proportions of patients with long-term health care needs (eg, Q4 vs Q1: registrations=–3.6%, appointments booked=–20%, and medical record views=6%; P≤.001).
Conclusions:
This study highlights that the use of the NHS App features varied across sociodemographic groups. In particular, it is used less by people living in more deprived areas. Tailored interventions and patient support are required to ensure that any benefits from the NHS App are spread equally throughout the population.
J Med Internet Res 2024;26:e56320
Date Issued
2024-11-13
Date Acceptance
2024-08-01
Citation
Journal of Medical Internet Research, 2024, 26
ISSN
1438-8871
Publisher
JMIR Publications
Journal / Book Title
Journal of Medical Internet Research
Volume
26
Copyright Statement
© Sukriti KC, Chrysanthi Papoutsi, Claire Reidy, Bernard Gudgin, John Powell, Azeem Majeed, Felix Greaves, Anthony A Laverty. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 13.11.2024. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/39536310
PII: v26i1e56320
Subjects
Science & Technology
Life Sciences & Biomedicine
Health Care Sciences & Services
Medical Informatics
digital health
patient portals
technological health divide
eHealth
inequality
observational
ecological
England
app
patient portal
disparities
deprivation
demographics
long-term health care
negative binomial regression model
intervention
patient support
general practice
digital technology
patient
youth
HEALTH
DISPARITIES
Publication Status
Published
Coverage Spatial
Canada
Article Number
e56320
Date Publish Online
2024-11-13