Data and Research in Health and Social Care

This part of the Health and Social Care Blog focuses on data and research: how evidence is gathered, interpreted and used to improve care. In health and social care, decisions should not be based on guesswork or “we’ve always done it this way”. Data and research help services understand what works, what needs improving, and how to keep people safe.

Data can include many things: incident reports, safeguarding concerns, falls records, pressure ulcer audits, medication errors, staff training completion, waiting times, and feedback from people who use services. Research includes studies, evaluations, clinical guidance and reviews that explore outcomes and best practice. Some data is collected nationally. Some is collected within a service. Either way, the aim is to learn and improve.

Across the posts linked on this page, you will explore the difference between qualitative information (people’s experiences and views) and quantitative information (numbers and measures). Both matter. A service might have strong audit results but poor feedback about dignity. Or the opposite: good feedback but rising falls. Looking at evidence from different angles gives a more accurate picture and helps teams avoid blind spots.

You’ll also consider how to read information critically. Not every study is high quality, and not every statistic tells the whole story. It helps to ask simple questions: Who was included? What was measured? Over what period? Could anything else explain the results? Good practice is about being evidence-informed, not blindly following whatever is most popular online.

Ethics and confidentiality are central when handling data. Personal information must be recorded accurately, stored securely, and shared only when appropriate. People should understand why information is being collected and how it will be used. In many settings, data is anonymised for audits and improvement work. Where information is identifiable, staff must follow policy and legal requirements. Good record-keeping protects people and protects services.

You will probably recognise the importance of data when patterns start to show: repeated falls in the same corridor, medication errors at the same time of day, or complaints linked to the same part of a process. Data turns “a feeling” into something a team can act on. It also helps services check whether changes are actually improving outcomes.

Practice example: a domiciliary care provider notices an increase in missed calls on weekends. By reviewing rota data, travel times and visit lengths, the manager identifies that schedules are unrealistic. Adjusting visit planning and staffing levels reduces missed calls and improves continuity for people receiving care. The improvement is measurable and meaningful.

Another practice example: in a care home, audit data shows pressure ulcer risk assessments are completed on time, but incidents still occur. A deeper review might look at repositioning records, equipment availability, nutrition, hydration and staff confidence. This can lead to practical actions such as refresher training, better handover prompts, and clearer escalation routes.

Research also supports reflective practice. When staff understand the evidence behind guidelines—such as infection control, moving and handling, or dementia care—they are more likely to apply it consistently and confidently. It also supports professional conversations: you can explain why a change is needed using evidence, not opinion.

Use the links on this page to explore how data is collected, how research informs practice, and how quality improvement works in real services. When evidence is used well, it strengthens safety, improves experiences, and supports better outcomes for the people who rely on care.