Healthcare Analytics

Postgraduate Certificate

Course Details

Course Code	GA_SHCAC_S09
Level	9
Duration	1 year
Credits	30
Method of Delivery	Online
Campus Locations	Mayo
Mode of Delivery	Part Time

Apply Now How to Apply

Apply Now How to Apply

Course Overview

The eHealth project has made significant progress in terms of the roll-out and integration of ICT systems across Irish healthcare services. The project objectives, inter alia, are identified as: improved population wellbeing; placing the patient at the centre of the healthcare delivery system; improved health service provider efficiencies; and the provision of an Electronic Health Record (EHR). Additionally, the project objectives align with the overall healthcare reform agenda which signals the move to a more sustainable model of healthcare, (the concept of the right care in the right place at the right time) including new models of care, technological innovation and healthcare insights derived from data.

Achievement of these objectives can only be realised through unlocking the ‘meaningful use’ of the vast amounts of healthcare data which these systems continue to capture and generate. In the business world, where successful analytics adoption (including big data analytics) has supported business value creation, the approach has been to strategically manage the diffusion of an analytics culture throughout the organisation, recognising that analytics is an amalgam of technology, process, and human capital.

This programme aims to equip students in the use of data analytics to influence healthcare delivery by raising their level of healthcare analytics awareness and skills for application & will equip graduates to use analytics in local decision-making and collaborate with the centralised business intelligence units.

Data analytics capacity and capability will be increasingly required with the volume of data generated by digital healthcare. The ability to understand, use and manipulate data through analytics skills and competency will enable graduates of this programme to champion healthcare analytics as a driver of quality within speciality areas of discipline or interest.

Why Study this course?

Concepts: Explore the concepts important in data analysis and statistics with an introduction to statistical and analytical techniques which underpin healthcare analytics.

Data and Technology: Use data and technology effectively, with an understanding of the context of application in the evolving digital health landscape of eHealth, mHealth, connected health and AI.

Drive Quality: Understand, use, and manipulate data through analytics skills & champion healthcare analytics as a driver of quality within speciality areas of discipline or interest.

Course Details

Year 1

Semester	Module Details	Credits	Mandatory / Elective
1	Statistics for Healthcare Analytics The rapid digitalisation of healthcare systems and records means that the healthcare industry and healthcare professions can now deliver clinical care, policy and planning on sound evidence. Part of this evidence is derived from the evaluation of available data sets and the application of appropriate statistics. To realise the potential that 'Big Data' can offer healthcare practice and planning, it is essential that healthcare professionals and those working in the healthcare industry are comfortable working with data and deriving and interpreting basic statistics. There exists disparity across the healthcare professions on the extent to which statistics are taught. The module is practical in nature and will focus on introducing students to the concepts important in data analysis and statistics. The module is aimed at students with no previous statistical analysis experience. It will provide the student with an introduction to statistical and analytical techniques which underpin healthcare analytics. Learning Outcomes 1. Analysetheoretical concepts fundamental to data analysis 2. Apply appropriate statistical tests to data in the healthcare context. 3. Analyse and interpretdescriptive and inferrential statistics on healthcare data. 4. Synthesiseand present healthcare data graphically. 5. Critically evaluate the threats to validity and reliability of results	10	Mandatory
2	Health Care Analytics: Tools and Practices This module introduces students to the general concepts of data analytics and practices in terms of how data sources and data sets are captured, transformed and modelled and how analytics is applied within health care settings. Using business intelligence and analytics tools the module investigates descriptive, predictive and prescriptive analytics concepts as they apply to health care data. Learning Outcomes 1. Differentiate between unstructured, semi-structuredand structured data 2. Critically evaluate a range ofkey healthcare data sources in terms of content, quality,data mining and data warehousing implications 3. Import a variety of datasources into Business Intelligencesoftware and apply data transformation techniques to meet user requirements 4. Analyse the principles of star schema and snowflake relational data modelling 5. Construct and analyse Data Models,Measures, Key PerformanceIndicators,Visualisations and Dashboards to Guide Healthcare Improvement Activities 6. Critically appraise predictive and prescriptive analytical techniques usedin data driven decision-making and applythem withinExcel	10	Mandatory
Year	Connected Health Implementing digital health is more than just deploying new technologies or devices. The rapid advancement of technology in healthcare also requires a specialised workforce who understand and the significance of the sociotechnical dimensions in digital health implementations and have the capability to part of the digital transformation agenda. Connected Health is a field in healthcare that seeks to use technology and health information to improve patient outcomes. Digital health solutions to improve integrated care, community care and home-based care can be seen as connected health solutions. These solutions will record and gather data and health information (such as exercise, diet, vital signs, wellbeing data etc) about an individual from data gathered by applications, sensors and new or proposed other healthcare technology devices (smartphones etc). This vast array of health information can be valuable for making decisions about individual care, but also for managing the future of health services more broadly. Health services, researchers and companies are all keen to have access to this information. Important elements of connected health are healthcare ICT, Interoperability, healthcare Infrastructure; Processes; Solutions and Applications and health data and information standards. Connected Health is a paradigm shift looking after the individual in a process that speaks to the health journey of the person, through the entire lifespan, leveraging a variety of technologies, data, and information to do so. This module is intended to balance the enhancement of student's ability to use data and technology effectively, with an understanding of the context of application in the evolving digital health landscape. Learning Outcomes 1. Analyse how populations and individuals currently usehealth-related devices and apps to inform their health behaviour choices through the use of information & data 2. Critically appraise health information standards & common representations of health data & information (including ICD, SNOMED, ICNP) 3. Analyse electronic healthcare system/healthcare application interoperability levels, policies;perspectives;approaches, models and standards 4. Applyethical considerations and approval processesrelated to dataset privacy when adopting a P5 Model of Healthcare for connected health. 5. Assess the impact of Artificial Intelligence (AI) and the integration of this technologyinto processes andproducts used in connected health 6. Interpret open innovation (OI) perspectives and how adoption can accelerate improvements in the quality of healthcare innovation & delivery.	10	Mandatory

Recommended Study Hours per week

It is recommended that students should try to allow for 5-7 hours per week per 5 credit module to their studies. This might be broken down to allow for up to 2 hours per week for online lectures and tutorials and 4-5 hours of self guided study hours.

Examination and Assessment

100% continuous assessment.

On-Campus Attendance Requirement

No attendance required.

Download a prospectus

Postgraduate Prospectus Online, Flexible & Professional Development Prospectus

Entry Requirements

Candidates applying directly to the ATU will have to meet the entry requirements as indicated in ATU/GMIT’s Academic Code of Practice No. 4 (Access, Transfer and Progression), at any given time.
The minimum entry requirement is a Level 8 degree with a H2.2 classification or equivalent and, at least 1 year experience working in or providing solutions into a healthcare environment.
There is no cognate award requirement for entry and eligible candidates may be from any domain of activity of the health services sector, including inter alia health care and social care professionals, administrative, technical support staff and solutions development providers.
Applicants not having the minimum formal qualification can be considered through the Recognition of Prior Learning (RPL) process to establish equivalence. Members of the programme team will be actively involved in processing applications through RPL.
Applications will be welcomed from international candidates who meet the minimum entry requirements. Where required, the Department of Nursing, Health Science and Integrated Care will engage with the ATU International Office to map progression from partner colleges abroad.
Applicants whose first language is not English are required to provide evidence of English language proficiency based on the International English Language Testing System (IELTS) or equivalent. These requirements are available from ATU/GMIT’s Admission’s office

Additional Requirements

For admission onto the programme, eligible candidates will be required to confirm that they have access to the following:

Windows 10 Operating System
Internet Explorer 11
CPU Intel Core i5 or better
4 GB RAM
Display 1440 x 900
Administrative rights on a computing device (PC, Laptop, Tablet etc.) to download Microsoft Power BI (64-bit version) and Excel add-ins within the package

Fees

Total Fees EU: €3000

*Subject to Governing Body approval.

Further information on fees

Careers

This programme will provide contextual skills and competencies to build, promote and manage data and information and to understand analytics in digital healthcare.

Graduates will be able to identify areas within the healthcare environment where healthcare analytics can be applied.

eHealth workers/digital champions are required across the full spectrum of healthcare job roles, spanning clinical, social care, informatics, and administration.

There is a recognised consistent requirement for new roles in the HSE for staff in business intelligence units, informatics departments, the new National Children’s Hospital, health data mining, and health information roles.

Potential job roles:

ICT Project Manager roles
Business Intelligence & Reporting roles
eHealth and Disruptive Technologies Projects
Technical Analyst (Health Services)
IT Integration Projects Officer
Data Manager
Integration Analyst
Health Data and Information Services Roles
eHealth systems Integration Projects

Further Information

Who Should Apply?

This programme will provide contextual skills and competencies to build, promote and manage data and information and to understand analytics in digital healthcare. Graduates will be able to identify areas within the healthcare environment where healthcare analytics can be applied – eHealth workers/digital champions are required across the full spectrum of healthcare job roles, spanning clinical, social care, informatics, and administration.