Evidence summary: The use of Information and Communications Technology and Data Sharing in Long-Term Care settings

William Byrd, Sian Smith, Maximilian Salcher-Konrad and Adelina Comas-Herrera (Care Policy and Evaluation Centre, London School of Economics and Political Science)

This evidence summary covers emerging evidence on the use of information and communications technology (ICT) and data sharing in long-term care settings (both in facilities and in the community) in response to the COVID-19 pandemic.

This summary was developed as part of the Social Care COVID Recovery and Resilience Research project, which has conducted a mapping of 137 studies describing interventions in long-term care (LTC) settings in response to the COVID-19 pandemic. More information on the methods used to generate this summary are available upon request. Briefly, we applied a pragmatic approach to searching academic databases throughout 2020 and mapped studies describing all interventions in LTC facilities (LTCFs) in response to the COVID-19 pandemic. 

Here, we briefly summarise evidence from 21 studies on how ICT and data sharing interventions were used in LTC settings, distinguishing between interventions to provide or maintain care, monitor COVID-19 patients remotely, provide training and guidance to informal and professional carers, combat isolation, track COVID-19 exposure, as well as other applications. 

  • Providing/maintaining health care
    • In Barcelona, Spain, (Benaque et al., 2020) and Hong Kong (Lai et al., 2020), contingency plans were created for home-based care users who receive dementia care, replacing face-to-face consultations with telemedicine. This allowed providing appropriate service levels to users. In Hong Kong, those who received video calls had improved resilience and wellbeing when compared to those who received phone calls. 
    • In Rome, Italy, a care home with 19 residents switched from in-person psychological counselling to nurse-assisted phone and video call consultations. Video calls proved useful for those with hearing disabilities. Timings were unchanged to maintain routine for patients (Renzi et al., 2020).
  • Monitoring COVID-19 patients remotely 
    • In Spain, the use of electronic health records allowed real-time identification and monitoring of the progression of infection in facilities in Catalonia (Echeverría et al., 2020) and Seville (Bernabeu-Wittel et al., 2020). In Catalonia, this enabled remote treatment of mild cases of COVID-19. In Seville, this enabled the prescription of drugs as if residents were in hospital, which reduced referrals to hospital and increased the survival of residents. 
  • Providing training and guidance, both to informal and professional carers
    • In the United Kingdom, a care home used WhatsApp to connect staff and enable them to share tips for the care of patients with dementia. This online communication helped to boost wellbeing and morale and fostered a positive atmosphere amongst staff and residents (Britton, 2020).
    • In the United States, training via video conferencing was used to share best practices from academic medical experts in Chicago (Gleason et al., 2020), Massachusetts (Lipsitz et al., 2020), and Charlottesville (Harris et al., 2020). In Chicago, training sessions had new and relevant information and helped staff to feel more in control. In Massachusetts, weekly webinars targeted infection control procedures and resulted in improved adherence and declines in weekly infection and mortality rates. In Charlottesville, this enabled the clinical status of patients to be discussed with experts, which resulted in lower-than-average mortality and hospitalisation rates. 
  • Combatting isolation
    • In the United States (Rhode Island (Gallo Marin et al., 2020) and New Brunswick (McArthur et al., 2021)), and France (Sacco et al., 2020), electronic devices enabled residents to connect with their families and helped mitigate against negative mental health outcomes associated with lockdown. In Rhode Island, this allowed staff to simultaneously provide updates to families. In Angers, France, although higher satisfaction levels were associated with video calls, residents were able to complete phone calls more independently, and consequently tended to use this medium more frequently. 
    • In Connecticut (van Dyck et al., 2020) and across the United States (Sacco et al., 2020), telephone outreach programmes were initiated for adults living in LTCFs and the community who were at risk of social isolation. The wellbeing of residents improved, and the initiatives also helped the volunteers address other problems related to quality of care. 
    • In Alberta, Canada, a study surveyed 10 care homes who, following changes to visitation policies, concluded that technologies that are adaptable to specific needs are required to ensure accessibility, complemented by robust technological infrastructure (Ickert et al., 2020).  
    • In Malaga, Spain, an existing technology system called AssistDem was adapted to provide cognitive stimulation for those with cognitive impairment, as well as basic care information, social connectedness functionality, and information on physical activity (Goodman-Casanova et al., 2020).
  • Tracking COVID-19 status and exposure among long-term care recipients and staff
    • In England, some local authorities used National Early Warning Scores for disease surveillance, measuring vital signs, such as body temperature and respiration rate, to detect disease before the onset of symptoms (Stow et al., 2020).
    • In Ohio, the United States, a group of community assisted living facilities (5,000 residents) created a cloud-based application to record cases and potential exposures in the first 100 days of an outbreak. They used a symptom screening app for staff, encouraging isolation and testing (Mills et al., 2020).
  • Other applications
    • In Israel, heat maps presented real-time data on institutional and domiciliary facilities, which included diagnosed COVID-19 cases and trajectories of outbreaks within facilities. These were deemed useful for understanding the causes of outbreaks and tailoring mitigation steps (Caspi et al., 2020).
    • In the United States, a machine learning model trained on COVID-19 outcomes in 1,146 nursing homes generated a risk index of the likelihood of infections within these institutions. This model demonstrated moderate predictive power and a strong association with nursing home outcomes (Sun et al., 2020).
    • In South Korea, a machine learning model used sociodemographic characteristics and medical history to predict the prognosis of 10, 237 COVID-19 patients after diagnosis. Study authors presented their model as potentially useful tool for the quick triage of patients without having to wait for the additional results of tests (An et al., 2020).
    • In the United States, a GIS-based[1] spatial model was used to determine the link between nursing home-level metrics and county-level place-based variables in 13,709 nursing homes with COVID-19 cases, revealing that county-level COVID-19 and per-capita income were the most significant predictors of outbreaks (Sugg et al., 2021).


The use of information and communications technology and data sharing in LTC settings has been deployed during the pandemic for several purposes. This includes those focused on the continuation of care, such as using technology to monitor patients, replace face-to-face consultations, and enable contact with families. Additionally, technology has been used for data sharing purposes, to provide training and guidance, to model outbreaks, and predict outcomes for patients. 

However, these interventions have generally only been described in case studies and other descriptive reports. Robust empirical evaluations of information and communications technology and data sharing during the COVID-19 pandemic in LTC facilities remains largely missing.

[1] A geographic information system (GIS) is a computer system for capturing, storing, checking, and displaying data related to positions on Earth’s surface. This can help individuals and organizations better understand spatial patterns and relationships. (https://www.who.int/topics/geographic_information_systems/en/)

To cite this summary:

Byrd W, Smith S, Salcher-Konrad M and Comas-Herrera (2021) Evidence summary: The use of Information and Communications Technology and Data Sharing in Long-Term Care settings. LTCcovid.org, International Long-Term Care Policy Network, CPEC-LSE, 12 April 2021.

Research carried out as part of the Social Care COVID Recovery and Resilience Project (funded by the National Institute for Health Research (NIHR) Policy Research Programme (NIHR202333). The views expressed in this summary are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care).


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Benaque, A., Gurruchaga, M. J., Abdelnour, C., Hernández, I., Cañabate, P., Alegret, M., Rodríguez, I., Rosende-Roca, M., Tartari, J. P., Esteban, E., López, R., Gil, S., Vargas, L., Mauleón, A., Espinosa, A., Ortega, G., Sanabria, A., Pérez, A., Alarcón, E., … Boada, M. (2020). Dementia Care in Times of COVID-19: Experience at Fundació ACE in Barcelona, Spain. Journal of Alzheimer’s Disease76(1), 33–40. https://doi.org/10.3233/JAD-200547

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Britton, B. (2020). Case study: WhatsApp support through the COVID-19 pandemic. Nursing & Residential Care22(7), 1–2. https://doi.org/10.12968/nrec.2020.22.7.8

Caspi, G., Chen, J., Liverant-Taub, S., Shina, A., & Caspi, O. (2020). Heat maps for surveillance and prevention of COVID-19 spread in nursing homes and assisted living facilities. Journal of the American Medical Directors Association. https://doi.org/10.1016/j.jamda.2020.05.048

Echeverría, P., Mas Bergas, M. A., Puig, J., Isnard, M., Massot, M., Vedia, C., Peiró, R., Ordorica, Y., Pablo, S., Ulldemolins, M., Iruela, M., Balart, D., Ruiz, J. M., Herms, J., Clotet Sala, B., & Negredo, E. (2020). COVIDApp as an Innovative Strategy for the Management and Follow-Up of COVID-19 Cases in Long-Term Care Facilities in Catalonia: Implementation Study. JMIR Public Health and Surveillance6(3), e21163. https://doi.org/10.2196/21163

Gallo Marin, B., Wasserman, P., Cotoia, J., Singh, M., Tarnavska, V., Gershon, L., Lester, I., & Merritt, R. (2020). Experiences of Rhode Island Assisted Living Facilities in Connecting Residents with  Families through Technology During the COVID-19 Pandemic. Rhode Island Medical Journal (2013)103(8), 59–61.

Gleason, L. J., Beiting, K. J., Walker, J., Shervani, S., Graupner, J., Mittal, K., Lee, K. K., Schrantz, S., Johnson, D., Levine, S., & Thompson, K. (2020). Using Telementoring to Share Best Practices on COVID-19 in Post-Acute and Long-Term Care Facilities. Journal of the American Geriatrics Society. https://doi.org/10.1111/jgs.16840

Goodman-Casanova, J. M., Durá-Pérez, E., Guzmán-Parra, J., Cuesta-Vargas, A., & Mayoral-Cleries, F. (2020). Telehealth home support during COVID-19 confinement: Survey study among community-dwelling older adults with mild cognitive impairment or mild dementia (Preprint). Journal of Medical Internet Research22(5), e19434. https://doi.org/10.2196/19434

Harris, D. A., Archbald-Pannone, L., Kaur, J., Cattell-Gordon, D., Rheuban, K. S., Ombres, R. L., Albero, K., Steele, R., Bell, T. D., & Mutter, J. B. (2020). Rapid Telehealth-Centered Response to COVID-19 Outbreaks in Postacute and Long-Term Care Facilities. Telemedicine and E-Health, tmj.2020.0236. https://doi.org/10.1089/tmj.2020.0236

Ickert, C., Rozak, H., Masek, J., Eigner, K., & Schaefer, S. (2020). Maintaining Resident Social Connections During COVID-19: Considerations for  Long-Term Care. Gerontology & Geriatric Medicine6, 2333721420962669. https://doi.org/10.1177/2333721420962669

Lai, F. H.-Y., Yan, E. W.-H., Yu, K. K.-Y., Tsui, W.-S., Chan, D. T.-H., & Yee, B. K. (2020). The Protective Impact of Telemedicine on Persons With Dementia and Their Caregivers During the COVID-19 Pandemic. The American Journal of Geriatric Psychiatry. https://doi.org/10.1016/j.jagp.2020.07.019

Lipsitz, L. A., Lujan, A. M., Dufour, A., Abrahams, G., Magliozzi, H., Herndon, L., & Dar, M. (2020). Stemming the Tide of COVID-19 Infections in Massachusetts Nursing Homes. Journal of the American Geriatrics Society. https://doi.org/10.1111/jgs.16832

McArthur, C., Saari, M., Heckman, G. A., Wellens, N., Weir, J., Hebert, P., Turcotte, L., Jbilou, J., & Hirdes, J. P. (2021). Evaluating the Effect of COVID-19 Pandemic Lockdown on Long-Term Care Residents’ Mental Health: A Data-Driven Approach in New Brunswick. Journal of the American Medical Directors Association22(1), 187–192. https://doi.org/10.1016/j.jamda.2020.10.028

Mills, W. R., Buccola, J. M., Sender, S., Lichtefeld, J., Romano, N., Reynolds, K., Price, M., Phipps, J., White, L., & Howard, S. (2020). Home-Based Primary Care Led-Outbreak Mitigation in Assisted Living Facilities in the  First 100 Days of Coronavirus Disease 2019. Journal of the American Medical Directors Association21(7), 951–953. https://doi.org/10.1016/j.jamda.2020.06.014

Renzi, A., Verrusio, W., Messina, M., & Gaj, F. (2020). Psychological intervention with elderly people during the COVID-19 pandemic: the experience of a nursing home in Italy. Psychogeriatrics?: The Official Journal of the Japanese Psychogeriatric Society. https://doi.org/10.1111/psyg.12594

Sacco, G., Lléonart, S., Simon, R., Noublanche, F., & Annweiler, C. (2020). Communication Technology Preferences of Hospitalized and Institutionalized Frail  Older Adults During COVID-19 Confinement: Cross-Sectional Survey Study. JMIR MHealth and UHealth8(9), e21845. https://doi.org/10.2196/21845

Stow, D., Barker, R. O., Matthews, F. E., & Hanratty, B. (2020). National Early Warning Scores (NEWS / NEWS2) and COVID-19 deaths in care homes: a longitudinal ecological study. Public and Global Health. http://medrxiv.org/lookup/doi/10.1101/2020.06.15.20131516

Sugg, M. M., Spaulding, T. J., Lane, S. J., Runkle, J. D., Harden, S. R., Hege, A., & Iyer, L. S. (2021). Mapping community-level determinants of COVID-19 transmission in nursing homes: A  multi-scale approach. The Science of the Total Environment752, 141946. https://doi.org/10.1016/j.scitotenv.2020.141946

Sun, C. L. F., Zuccarelli, E., Zerhouni, E. G. A., Lee, J., Muller, J., Scott, K. M., Lujan, A. M., & Levi, R. (2020). Predicting Coronavirus Disease 2019 Infection Risk and Related Risk Drivers in  Nursing Homes: A Machine Learning Approach. Journal of the American Medical Directors Association21(11), 1533-1538.e6. https://doi.org/10.1016/j.jamda.2020.08.030

van Dyck, L. I., Wilkins, K. M., Ouellet, J., Ouellet, G. M., & Conroy, M. L. (2020). Combating Heightened Social Isolation of Nursing Home Elders: The Telephone Outreach in the COVID-19 Outbreak Program. The American Journal of Geriatric Psychiatry. https://doi.org/10.1016/j.jagp.2020.05.026

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