This page Accelerator’s Data use workstream shares information from the Accelerator’s work to follow studies and projects that offer insight into data and data infrastructures for social care during the covid-19 pandemic.
For studies relating to public engagement and covid-19 see the Accelerator’s public engagement tracker here.
This tracker and its format were inspired by the Ada Lovelace Institute Public attitudes to COVID-19, technology and inequality tracker.
Please get in touch if you are aware of any updates or additions we should include. Let us know by contacting Cian O’Donovan via c.o’firstname.lastname@example.org.
The report shows a large increase from 2019 in the use of video meeting platforms. However, only small increases in the uptake of other digital software or systems were observed and attributed to covid-19. The report frames this as ‘digital maturity’ and ‘digital readiness’ within the social care sector.
Adult social care and COVID-19 after the first wave: assessing the policy response in England
Analysis of the national government policy response for social care between June 2020 and March 2021. A lack of publicly available data means that we only know so much about the impacts of the pandemic on social care, and the success of policies to support the sector. Data on care provided outside care homes are limited and hard to interpret. The authors say this is concerning, given the sustained increase in mortality reported among people receiving care at home.
This summary outlines 10 key lessons for the implementation, adoption, and spread of digital innovations in health and social care services.
Poses 10 questions for policy, including on data: how can better and more frequent data for use by local authorities, national bodies and providers themselves be collected to help better understand and shape the market without overburdening providers?
This dialogue convened more than 100 members of the public to discuss how to make sure that health and care data is used in ways that benefit people and society. It found that transparency around the purpose and aim of data use, as well as how data is used is key to ensuring public benefit is realised.
Summary of 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.
This survey was part of the Ada Lovelace Institute’s project in partnership with the Health Foundation, exploring how the accelerated adoption of data-driven technologies and systems during the pandemic may have affected inequalities. The survey found a ‘data divide’ that could affect health inequalities according to people’s digital literacy, access to health-related technologies and other socio-economic factors.
A survey on the use of AI and data-driven technology in the UK’s COVID-19 response. The results suggest significant public support for the use of data-driven technology to help combat the immediate public health crisis, and to mitigate the wider effects of lockdown. However, many respondents also felt that the potential of data-driven technology was not being fully realised. They find that trust in the rules and regulations governing technology is the single biggest predictor of whether someone believes that digital technology has a role to play in the COVID-19 response.
This polling data looks at the public’s attitudes towards the impact of coronavirus and Government’s handling of the pandemic. The data shows a number of changes in the public’s perceptions on these issues since July and May 2020 , when two earlier rounds of this polling were carried out.
UK care home residents are invisible in national datasets. The COVID-19 pandemic has exposed data failings that have hindered service development and research for years. Fundamental gaps, in terms of population and service demographics coupled with difficulties identifying the population in routine data are a significant limitation. The authors suggest changes that could address this data gap: (1) Reliable identification of care home residents and their tenure; (2) Common identifiers to facilitate linkage between data sources from different sectors; (3) Individual-level, anonymised data inclusive of mortality irrespective of where death occurs; (4) Investment in capacity for large-scale, anonymised linked data analysis within social care working in partnership with academics; (5) Recognition of the need for collaborative working to use novel data sources, working to understand their meaning and ensure correct interpretation; (6) Better integration of information governance, enabling safe access for legitimate analyses from all relevant sectors; (7) A core national dataset for care homes developed in collaboration with key stakeholders to support integrated care delivery, service planning, commissioning, policy and research to provide timely and responsive policy decisions to support care homes.
This report explores the extent to which this opportunity was realised in practice by summarising how the LNNs responded to the pandemic and where they were positioned within the city-wide response. It draws on the findings of a ‘Real Time Evaluation’ (RTE) of the LNNs during the COVID-19 pandemic. These activities are an example of community practices not evident in existing data infrastructures.
Evolution and impact of COVID-19 outbreaks in care homes: population analysis in 189 care homes in one geographic region
National data are aggregated, which means our understanding of variation between care homes is limited. Robust national data for the care home population are scarce and data sources are fragmented, meaning our understanding of the needs and outcomes of residents is poor. Despite this the study describes the evolution of outbreaks of COVID-19 in all care homes in one health region in Scotland, specifically the timing of outbreaks, number of confirmed cases in residents, care home characteristics associated with the presence of an outbreak, and deaths of residents in both care homes and hospitals.
Over 30 workshop participants identified profound structural and cultural challenges that impact how data is collected, shared and used. The participants also described ways that misaligned incentives and misunderstandings – rooted in different perspectives and language – are undermining efforts to build consensus and make collaborative progress.
Long-standing structural issues have exacerbated the crisis in social care and hindered the response to the pandemic. The report calls for immediate action to prevent further harm including by filling the gaps in data, particularly for those receiving domiciliary care. The authors say new data strategy is needed for social care that first and foremost enables the provision of better care.
Analysis of the national government policy response during the first phase of the pandemic. Long-standing issues within the system – including underfunding, workforce shortages, system fragmentation, and lack of quality data – shaped the ability of the sector to respond.
Aims: To establish what data need to be in place to support research, service development and uptake of innovation in care homes. To synthesise existing evidence and data sources with care home generated resident data to deliver a minimum data set (MDS) that is usable and authoritative for different user groups (residents, relatives, business, practitioners, academics, regulators and commissioners).
This is a platform for moderated discussion about how data analytics can be used to improve social care in the UK. Features input from analysts and policy experts on data in social care