From Data to Decision: A Practical Guide for Collaborative Healthcare Analytics

The course covers various aspects of healthcare data, including measuring and documenting data quality, collaborating with clinicians and administrators, improving record-keeping, and understanding the root cause of data quality issues. It also includes opportunities for collaboration with data scientists, statisticians, data engineers, and other technical professionals. The course concludes with a live session where participants apply the concepts learned to a case study and their own practice.

This pathway is aligned with the National Competency Framework for Data Professionals in Health and Care and is aimed at early-career analysts working at Competency Associate Practitioner (L1) and Competency Practitioner (L2) levels. It is ideal for those in roles such as Assistant Analyst, Data Assistant, Junior Analyst (Band 3/4), and Data Analyst, Information Officer (Band 5/6). The course focuses on building skills in communication, teamwork, and aligning analytical work with clinical and organisational goals. Participants will learn effective communication techniques to bridge the gap between technical analysis and clinical decision-making, fostering impactful contributions to healthcare projects.

• DAC1 L2: You can reverse-engineer existing analyses and replicate the method and results.

• DAC2 L1: You recognise basic issues of data quality and can take action with guidance to prevent or counteract them.

• DAC2 L2: You can identify a broad range of data quality issues and perform data cleansing and consistency checks.

• DAC3 L1: You understand the appropriate media to communicate findings and you shape communications relevant to the audience and their needs.