Introduction to Health Data Science

IIDS67681 Introduction to Health Data Science 15 Semester 1 Postgraduate Taught Level 6 Sabine Van der Veer Unit coordinator Glen Martin Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 ' European Credit Transfer & Accumulation System Rating : 7.5 The role of the health data scientist is to turn health data into insights into past and current healthcare delivery, and to help use these insights for informing decisions about healthcare delivery in the future. To be able to do this, it is critical to understand: (i) the different types of health information systems and technologies and how they are used for care delivery; (ii) how health data is created, collected, stored, and retrieved; (iii) the different data sources available to support decision-making, and how to determine which ones are appropriate to use; (iv) how to handle patient data in a confidential and secure manner to ethical and quality standards that are appropriate for a modern health service; (v) which techniques and methodologies are most appropriate to investigate data; (vi) how to elicit requirements of health professionals and other stakeholders, in line with their objectives and processes; and (vii) how to communicate and visualise results for various stakeholders, so that it provides them with meaningful insights from the data. The role of the health data scientist is to turn health data into insights into past and current healthcare delivery, and to help use these insights for informing decisions about healthcare delivery in the future. To be able to do this, it is critical to understand: (i) the different types of health information systems and technologies and how they are used for care delivery; (ii) how health data is created, collected, stored, and retrieved; (iii) the different data sources available to support decision-making, and how to determine which ones are appropriate to use; (iv) how to handle patient data in a confidential and secure manner to ethical and quality standards that are appropriate for a modern health service; (v) which techniques and methodologies are most appropriate to investigate data; (vi) how to elicit requirements of health professionals and other stakeholders, in line with their objectives and processes; and (vii) how to communicate and visualise results for various stakeholders, so that it provides them with meaningful insights from the data. In this unit, you will learn about socio-technical and methodological approaches for going from health data to insights for informing decisions about healthcare delivery. You will apply these approaches to uses of data and systems in healthcare, illustrated with real-world case-studies drawn from projects and research done in clinical practice settings. You will do this by covering three main areas:<ol> <li style="text-align:justify">Health Information Systems and the Health Data Landscape </li> <li style="text-align:justify">Handling and Investigating Health Data </li> <li style="text-align:justify">Health Data Visualisation to Support Stakeholders’ Decision Making  </li></ol>  <ul> <li>Health data landscape, data models/ architecture, data storage and retrieval technologies and data linkage methodologies/principles</li> <li>Information governance and security</li> <li>Health Information Systems and Technologies (e.g., social and mobile health technologies, architectures, networks, internet, cloud)</li> <li>System design cycle and methodologies</li> <li>Stakeholder requirements gathering</li> <li>Principles of data visualisation/ communicating data to stakeholders</li> <li>Application of system design cycle to create a data visualisation/dashboard</li> <li>Communication/presentation styles</li></ul> <ul> <li>Discuss the health data landscape and the pathway from data collection, interpretation, analysis, visualization and decision-making</li> <li>Understand the different approaches to system development, including how to turn user/stakeholder requirements into development processes</li> <li>Discuss the range of technologies available to produce, store and retrieve data</li> <li>Evaluate the technical, ethical and legal problems associated with the use of health data</li> <li>Discuss and understand concepts in data modelling</li></ul> <ul> <li>Critically review a system/technology or data modelling plan and make suggestions for improvement</li> <li>Explore, capture and communicate system requirements related to stakeholder needs </li> <li>Apply systems methodologies to a healthcare problem</li> <li>Produce visual and textual documentation to communicate the design of a system in a formal and structured way</li> <li>Identify and appraise data sources used to support healthcare decision making</li></ul> <ul> <li>Elicit information from various stakeholders of a systems requirements gathering exercise, and communicate the results</li> <li>Use systems methodologies to design a technological solution to a healthcare problem, or a data visualisation/dashboard</li></ul> <ul> <li>Communicate effectively both in written and verbal format to both non-technical and technical audiences (including in public) </li> <li>Be able to plan a project, including appreciation of resource allocation </li> <li>Work though the problem-solving cycle   </li></ul> Group/team working Work collaboratively within a team Project management Understand about resource allocation and project planning Problem solving Work through the problem solving cycle This unit will be delivered in a blended format: e-Learning preparation material will impart basic and core knowledge whilst the face-to-face (F2F) workshops will formalise the content and encourage attendees to draw upon their own reading and experience. Specifically, the F2F workshops will be delivered as workshops, where each block will cover a key section of the module/ learning material. The F2F sessions will consist of lecture/structured discussion, group problem-based activities, and real-world case studies (drawn from University of Manchester research-driven projects and current NHS projects).Throughout the module, students will be placed in groups. They will work in these groups for problem-based activities (formative assessment), as well as allowing the students to actively participate in the different stages of systems design of a ‘informatics’ solution (data visualisation) to a specific healthcare delivery problem (COPD/asthma). At the end of the unit, students are asked to present this in a ‘dragons den’ (contributing 30% of the overall assessment mark).  In addition, at regular times in the F2F workshops students will present back to other students and tutors to show and share thinking.Following each F2F session, students will be asked to reflect upon their learning using the online space (e.g. forums), and reflect on the material. 7 Oral assessment/presentation 70% 8 Practical skills assessment 30% Formative assessment and feedback to students is a key fature of the on-line learning materials for this unit.  Students will be required to engage in a wide range of interactive exercises to enhance their learning and test their developing knowledge and skills.  In addition, there will be a series of supervised pratical hands-on exericses that will allow for verbal feedback. NONE MSc Health Data Science PT MSc Health Data Science PGDT Taught Component Mandatory PG Dip Health Data Science PT PG Diploma Health Data Science PGDT Taught Component Mandatory PG Cert Health Data Science PT PGCert Health Data Sci (18) PGDT Taught Component Mandatory Health Data Science - CPD Health Data Science - CPD PGDT Taught Component Optional MSc Health Data Science FT MSc Health Data Science FT PGDT Taught Component Mandatory PG Dip Health Data Science FT PG Dip Health Data Science FT PGDT Taught Component Mandatory PG Cert Health Data Science FT PG Cert Health Data Science FT PGDT Taught Component Mandatory N Davies, A, Mueller, J, Developing Medical Apps and mHealth Interventions: A guide for researchers, physicians and informaticians. Springer Lectures 18 Tutorials 24 Work based learning 30 0 78