The ‘Ghost in the Shell’ of NHS Patient Data Policies: News Media on care.data's Haunting of the General Practice Data for Planning and Research

This study examines the controversy surrounding NHS England's suspended 'General Practice Data for Planning and Research' (GPDPR) programme, which aimed to automatically extract personally identifiable coded health data into a central data repository. Drawing on the concept of 'hauntology', I analyse UK news media coverage to explore how the legacy of the earlier, abandoned care.data programme shaped stakeholder opposition and policy debates around GPDPR's data governance. Findings suggest that this programme was often seen as a 'déjà vu' of care.data. Key policy challenges that undermined trust and acceptability included concerns over access to patient data by commercial companies, cumbersome opt-out processes and the absence of shared governance procedures and meaningful ownership arrangements. Comparatively, care.data faced greater political resistance despite lower perceived intrusiveness, highlighting the complex interplay between public engagement, political context and programme design. This study advances understanding of how historical policy failures linger in societal memory, affecting the receptivity and acceptability of subsequent data initiatives. It offers actionable insights for policymakers designing comparable public health data programmes that balance health system improvements, economic growth and public trust.

Authors

Institutions

Publication Details

Journal
Sociology of Health & Illness
Published
2026-08-17
DOI
https://doi.org/10.1111/1467-9566.70251
Primary Topic
Data Analysis and Archiving
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The ‘Ghost in the Shell’ of NHS Patient Data Policies: News Media on care.data's Haunting of the General Practice Data for Planning and Research

Paraskevas Vezyridis
Sociology of Health & Illness
Data Analysis and Archiving
article

The ‘Ghost in the Shell’ of NHS Patient Data Policies: News Media on care.data's Haunting of the General Practice Data for Planning and Research

Paraskevas Vezyridis
article en

Abstract

This study examines the controversy surrounding NHS England's suspended 'General Practice Data for Planning and Research' (GPDPR) programme, which aimed to automatically extract personally identifiable coded health data into a central data repository. Drawing on the concept of 'hauntology', I analyse UK news media coverage to explore how the legacy of the earlier, abandoned care.data programme shaped stakeholder opposition and policy debates around GPDPR's data governance. Findings suggest that this programme was often seen as a 'déjà vu' of care.data. Key policy challenges that undermined trust and acceptability included concerns over access to patient data by commercial companies, cumbersome opt-out processes and the absence of shared governance procedures and meaningful ownership arrangements. Comparatively, care.data faced greater political resistance despite lower perceived intrusiveness, highlighting the complex interplay between public engagement, political context and programme design. This study advances understanding of how historical policy failures linger in societal memory, affecting the receptivity and acceptability of subsequent data initiatives. It offers actionable insights for policymakers designing comparable public health data programmes that balance health system improvements, economic growth and public trust.

Sociology of Health & IllnessVol. 48(7)
University of Nottingham (GB)
Openalex Percentile: Top 4%
Data Analysis and Archiving
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.