‘One of the greatest opportunities of the 21st century is the potential to safely harness the power of the technology revolution, which has transformed our society, to meet the challenges of improving health and providing better, safer, sustainable care for all.’National Information Board

The ability to exploit advances in digital technology in support of better health and better health care is a priority for health care services. The NHS Long Term Plan, published in January 2019, envisages a central role for technology, forecasting that technology will empower people, support health and care professionals to deliver better care, improve clinical efficiency and safety and improve population health overall. Alongside service innovations such as digital-first primary care and the NHS App, there are plans to create better digital infrastructure and build a digital-ready workforce that can make effective use of technologies as they are developed. This approach to digital infrastructure largely consists of the adoption of technology standards, to ensure that data are accessible and that it is possible for different systems to exchange information, and an expansion of the number of acute, mental health and ambulance trusts working with the NHS Global Digital Exemplars on information technology (IT) projects.

All these initiatives involve data, which the NHS has in abundance. A digital footprint is generated almost every time a person comes into contact with a service (Box 1). The volume of data will continue to grow as the NHS spends billions of pounds on its information systems. However, it is failing to make the most of the benefits that can flow from these systems, because there are not enough people with the right skills to use the information that is being collected.

Box 1: The volume of electronic information in NHS health care systems is growing

  • It has been estimated that as much as 30% of the entire world’s stored data is generated in health care systems. A single patient can typically generate close to 80MB of data each year in imaging and electronic medical record data.
  • NHS services see 1 million patients every 36 hours. Almost all interactions generate some form of electronic record or footprint. There are 200 different data collection systems across health care systems.
  • A typical hospital stay requires the collection of several hundred individual data items.
  • A GP holds electronic records of every consultation, in coded form, stretching back decades.
  • 20 million pieces of patient feedback have been received through the Friends and Family Test alone.
  • Increasingly, individuals themselves are generating data about their own health, using apps and websites.

Strategies aimed at exploiting the promise of data typically cover:

  • innovation and investment in new technologies
  • managing and accessing new data streams in new ways
  • investing in the analytical workforce, which can use the data to provide actionable insight.

The third aspect tends to get the least attention – it is less glamorous and solutions are often challenging and long term. But it is an essential requirement if we are to exploit the advantages that new technologies offer.

This report explores some of the ways in which good data analytics can support decision-makers. It also identifies some missed opportunities that flow from our limited ability to make sense of information relevant to health and health care. It is based on the Health Foundation’s experience of promoting innovative data analytics in health and social care. One of our projects in this area is the Advancing Applied Analytics programme, which is now supporting 23 teams to improve analytical capability in health and care services.

Better use of patient data can improve the quality and operational efficiency of health care in various ways (Table 1). However, as we discovered in previous work, health and care organisations often have problems accessing analytical skills when needed. For that work, we interviewed people across health and care systems in the UK, and many highlighted the problem of not having the right people to interpret the data and provide useful analysis to clinicians and managers (Box 2). This problem is not new or unique to health services. But it is a serious challenge if we want to make the most of the information collected and realise the benefits of investment in digital technology. Part of the answer is making sure that health care services have in place the systems designers, training and infrastructure necessary for new technology. It also means having people and teams who can help make sense of the growing mountains of data.

Table 1: Information and intelligence provided by data analysts – who it is for and how it is applied



General population

  • Identifying information sources that might be useful to patients.
  • Testing the effects of different presentation styles aimed at patients and the general population.
  • Looking at the effects of new information systems.

All users of health and care services

  • Designing and testing the effects of new approaches to sharing information with service users.

Clinical teams

  • Developing decision aids/tools that use data to help diagnose or manage diseases (eg risk scores and algorithms).
  • Informing the design of improvement initiatives.
  • Monitoring the quality of care delivered over time.

Service managers

  • Identifying service objectives and monitoring tools (performance indicators).
  • Tracking new care initiatives and providing the information required to improve them.
  • Devising and adapting mathematical modelling tools (eg to improve scheduling or patient flow).
  • Synthesising and summarising the literature on the effectiveness of new interventions and service models.
  • Supporting data collection and analysis of clinical audits.

Commissioners and planners

  • Assessing needs and priorities.
  • Reviewing evidence of effectiveness and efficiency of service delivery.
  • Assessing need and demand and forecasting for populations.
  • Modelling capacity requirements and business planning.
  • Agreeing evaluation frameworks and monitoring effects of service models.
  • Monitoring the quality of services.

Those running organisations

  • Performance analysis.
  • Assessment of the economic impacts of changes (eg new technology).
  • Quality monitoring.
  • Assessing probable effects of changes before they are made (eg closure of A&E departments).
  • Forecasting demand for services (eg ahead of winter).
  • Business and strategic planning.

System- and national-level decision-makers

  • Monitoring against strategic priorities.
  • Developing and applying mathematical models to inform policy (eg vaccination or urgent care).
  • Regulation of efficiency and quality.
  • Resource allocation.
  • Programme evaluation so that the NHS can learn from experience and improve.

This report has been written at a critical moment for the NHS workforce, with over 100,000 vacancies reported by trusts and problems attracting, retaining and motivating staff. Overcoming these wider problems is crucial to building analytical capability in the NHS. But it is equally important to recognise that analytical capability requires its own strategy, one that articulates clear roles for analytical teams in the health care system, as well as leadership models and approaches to supporting collaboration between analysts, clinicians and managers.

Box 2: Issues limiting analytical capability in health care organisations

Analyst numbers and priorities

  • In some areas, there are not enough analysts.
  • However, the existing workforce is not always used to its full potential.

Analyst skills

  • Some analytical teams cannot easily access people with skills in more academic disciplines, such as statistics and economics.
  • Analysts need good communication skills and the ability to explain complex ideas to senior managers clearly and concisely.

Access to data and tools

  • Lack of the right data can hamper the analysis.
  • Better software tools can free up analysts’ time from mundane tasks.
  • Obtaining data at the right level that satisfies information governance requirements can be challenging.

Professional and personal development

  • Analysts often lack opportunities to progress their career to a senior level while still being an analyst.

Fragmentation and isolation

  • The ability to share experiences and learn new methods and techniques is essential, but health care analysts can become isolated, working as individuals or in small teams across several organisations.

Senior management recognition

  • Senior managers might not always see the need for or value of analytics.

Analytical leadership

  • Good leaders – people who understand the supply side of the issues and can also engage with managers at the highest levels – are important.

Adapted from Understanding analytical capability in health care: Do we have more data than insight?

* For further details, see

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