Effect of telehealth on use of secondary care and mortality: findings from the Whole System Demonstrator cluster randomised trial
Open accessAbstract
OBJECTIVE: To assess the effect of home based telehealth interventions on the use of secondary healthcare and mortality. DESIGN: Pragmatic, multisite, cluster randomised trial comparing telehealth with usual care, using data from routine administrative datasets. General practice was the unit of randomisation. We allocated practices using a minimisation algorithm, and did analyses by intention to treat. SETTING: 179 general practices in three areas in England. PARTICIPANTS: 3230 people with diabetes, chronic obstructive pulmonary disease, or heart failure recruited from practices between May 2008 and November 2009. INTERVENTIONS: Telehealth involved remote exchange of data between patients and healthcare professionals as part of patients' diagnosis and management. Usual care reflected the range of services available in the trial sites, excluding telehealth. MAIN OUTCOME MEASURE: Proportion of patients admitted to hospital during 12 month trial period. RESULTS: Patient characteristics were similar at baseline. Compared with controls, the intervention group had a lower admission proportion within 12 month follow-up (odds ratio 0.82, 95% confidence interval 0.70 to 0.97, P = 0.017). Mortality at 12 months was also lower for intervention patients than for controls (4.6% v 8.3%; odds ratio 0.54, 0.39 to 0.75, P < 0.001). These differences in admissions and mortality remained significant after adjustment. The mean number of emergency admissions per head also differed between groups (crude rates, intervention 0.54 v control 0.68); these changes were significant in unadjusted comparisons (incidence rate ratio 0.81, 0.65 to 1.00, P = 0.046) and after adjusting for a predictive risk score, but not after adjusting for baseline characteristics. Length of hospital stay was shorter for intervention patients than for controls (mean bed days per head 4.87 v 5.68; geometric mean difference -0.64 days, -1.14 to -0.10, P = 0.023, which remained significant after adjustment). Observed differences in other forms of hospital use, including notional costs, were not significant in general. Differences in emergency admissions were greatest at the beginning of the trial, during which we observed a particularly large increase for the control group. CONCLUSIONS: Telehealth is associated with lower mortality and emergency admission rates. The reasons for the short term increases in admissions for the control group are not clear, but the trial recruitment processes could have had an effect. TRIAL REGISTRATION NUMBER: International Standard Randomised Controlled Trial Number Register ISRCTN43002091.
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- Authors
- Steventon, A., Bardsley, M., Billings, J., Dixon, J., Doll, H., Hirani, S., Cartwright, M., Rixon, L., Knapp, M., Henderson, C., Rogers, A., Fitzpatrick, R., Hendy, J., Newman, S., & for the Whole System Demonstrator Evaluation Team
- Affiliations
- Nuffield Trust (GB)
- Wagner College (US)
- University of East Anglia (GB)
- City, University of London (GB)
- King's College London (GB)
- London School of Economics and Political Science (GB)
- University of Manchester (GB)
- University of Oxford (GB)
- University of Surrey (GB)
- Corresponding author
- Steventon, A.
- ORCID
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2012-06-21
- Volume
- 344
- Issue
- jun21 3
- Pages
- e3874-e3874
- ISSN
- 1756-1833 (ISSN-L)
- PMC
- PMC3381047
- OpenAlex
- W1970039259
- Cited by
- 583
- References
- 50
- Citations by year
- 2026: 8 · 2025: 12 · 2024: 20 · 2023: 20 · 2022: 19 · 2021: 38 · 2020: 32 · 2019: 32 · 2018: 42 · 2017: 47 · 2016: 61 · 2015: 74 · 2014: 75 · 2013: 83 · 2012: 20
- FWCI
- 77.82
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- BMJ (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- City Research Online (City University London) (acceptedVersion)
- London School of Economics and Political Science Research Online (London School of Economics and Political Science) (acceptedVersion)
- ePrints Soton (University of Southampton) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- London School of Economics and Political Science Theses Online (London School of Economics and Political Science) (submittedVersion)
- Funders
- National Institute for Health and Care Research
- University College London
- Engineering and Physical Sciences Research Council (EP/I029788/1)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Telemedicine and Telehealth Implementation
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Demography › Technology Use by Older Adults
- Keywords
- telemedicine, hospitalization, mortality, diabetes mellitus, chronic obstructive pulmonary disease, heart failure, remote patient monitoring, emergency admissions, length of hospital stay, general practice, health care costs, predictive risk score, intention-to-treat analysis, primary care intervention, health disparities
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Emergency Service, Hospital, England, Female, Hospitalization, Humans, Length of Stay, Male, Middle Aged, Mortality, Cluster Analysis, Logistic Models, Telemedicine, Young Adult, General Practice
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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