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Masters Degrees in Health Informatics, London, United Kingdom

We have 9 Masters Degrees in Health Informatics, London, United Kingdom

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Who is it for?. This course will help you become part of the newest and fastest growing specialty in healthcare by understanding how to apply informatics solutions to develop high-quality and sustainable healthcare. Read more

Who is it for?

This course will help you become part of the newest and fastest growing specialty in healthcare by understanding how to apply informatics solutions to develop high-quality and sustainable healthcare.

It has been designed for health professionals who wish to enhance their careers with an informatics qualification. It will also appeal to computer scientists, engineers and others with relevant technical or professional qualifications who wish to move into a successful career involving the application of informatics in the health service.

Objectives

The Health Informatics MSc at City, University of London aims to develop future leaders in the field who will transform healthcare with sustainable, informatics-led approaches, and is the only MSc in the UK to be accredited by the British Computer Science Society.

High-quality teaching combines both theory and practice, with a strong focus on real-world applications including electronic health records, clinical data management and analytics, mobile technology and telehealth. Teaching is supported by guest lectures from medicine and industry. Furthermore, you will be part of a multi-professional and strongly international cohort bringing together many points of view on national and international computerised healthcare initiatives.

Accreditation

Accredited by BCS, The Chartered Institute for IT for the purposes of partially meeting the academic requirement for registration as a Chartered IT Professional.

Internships

As a postgraduate student on a Computing and Information Systems course, you will have the opportunity to complete up to six months of professional experience as part of your degree.

Our longstanding internship scheme gives you the chance to apply the knowledge and skills gained from your taught modules within a real business environment. An internship also provides you with professional development opportunities that enhance your technical skills and business knowledge.

Internships delivered by City, University of London offer an exceptional opportunity to help you stand out in the competitive IT industry job market. The structure of the course extends the period for dissertation submission to January, allowing you to work full-time for up to six months. You will be supported by our outstanding Professional Liaison Unit (PLU) should you wish to consider undertaking this route.

Teaching and learning

High-quality teaching is delivered by research-active academics from City, University of London. Specialist industry professionals also participate in teaching and learning, ensuring that students learn the knowledge and skills most valued by industry.

Teaching combines both theory and practice, with a strong focus on real-world applications including electronic health records, clinical data management and analytics, mobile technology and telehealth. You will also undertake an independent research project.

All taught modules are delivered through a combination of lectures, interactive workshops, tutorials and activities supported by the University's online learning environment.

Taught modules are generally assessed through a combination of coursework and examination, although some modules are 100% coursework based (e.g. Data Analysis with Healthcare Application, Information Architecture and Project Management). Examinations focus on applying health informatics theories to realistic clinical scenarios. Coursework assignments centre on analysing real world problems, developing computational models and systems to solve these problems and producing written reports and documentation.

The taught component of the MSc is worth 66.67% and the independent research project is worth 33.33%. The independent research project allows students to conduct original research on a health informatics topic of their choice

Upon successful completion of eight modules and the independent research project, you will be awarded a master’s level qualification. Alternatively, if you do not complete the dissertation but have successfully completed the taught component you will be awarded a postgraduate diploma. Successful completion of four modules will lead to the award of a postgraduate certificate.

Modules

The MSc comprises of 180 credits.

You will study six core modules and two elective modules. You will also undertake an independent research project.

A full-time student is expected to commit 35 hours a week, which includes attendance at lectures, tutorials and workshops, and independent study on coursework, the individual research project and preparation for examinations.

Taught Core Modules

Core modules are mandatory and provide a detailed insight into key areas of health informatics. The modules are designed to complement each other and incrementally build specialist knowledge in the area. For example, the Electronic Health Records module focuses on important standards and techniques for securely capturing, storing and exchanging clinical data. Data Analysis with Healthcare demonstrates how to undertake statistical analyses of clinical data and report the results. In the Modelling Healthcare Decisions and Knowledge Management in Healthcare modules students learn about machine learning techniques that can be applied to clinical data and used to develop intelligent systems to support clinical decision making, including the cost effectiveness of those decisions in a variety of healthcare settings. The Telehealth and Mobile Applicationsmodules examines the emerging role of telehealth with a focus on new technologies and devices such as mobile apps, sensors and cloud computing that can be used to capture clinical data and deliver health services in environments such as patients’ homes. The Research, Methods and Professional Issues module develops students' research skills and helps with planning and carrying out original research in their independent research project.

  • Electronic Health Records (15 credits)
  • Data Analysis with Healthcare Application (15 credits)
  • Modelling Healthcare Decisions (15 credits)
  • Knowledge Management in Healthcare (15 credits)
  • Telehealth and Mobile Applications (15 credits)
  • Research, Methods and Professional Issues (15 credits)

Career prospects

Graduates from the Health Informatics MSc pursue successful careers in health services (both state and private sectors in the UK and overseas), and in related healthcare industries such as Electronic Health Record providers. There are a wide variety of roles and opportunities in health informatics as outlined the NHS Careers in Health Informatics including:

  • Health records designers and developers
  • Health data scientists
  • Data managers
  • Taxonomy managers
  • System and application analysts
  • Information analysts
  • IT project managers
  • Digital transformation leads
  • PACS and RIS managers
  • Education and training.


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Today's society faces the challenge of providing high-quality, patient-centred, sustainable and affordable healthcare, in an environment of increased demand and scarce resources. Read more

Today's society faces the challenge of providing high-quality, patient-centred, sustainable and affordable healthcare, in an environment of increased demand and scarce resources. The Health Informatics MSc at UCL aims to form future leaders who will address this challenge, transforming healthcare delivery through the use of information and communication technologies.

About this degree

Our graduates are professionals able to effectively engage with clinicians, managers, patients and policymakers, with the necessary skills and tools to harness healthcare information for improving clinical practice and service delivery. They possess the knowledge about healthcare problems, the concepts used to analyse them and the principles that govern the successful engineering, application and evaluation of solutions.

Students undertake modules to the value of 180 credits.

The programme consists of one core module (15 credits), seven optional modules (105 credits) and a research project (60 credits).

A Postgraduate Diploma (120 credits, flexible study 2-5 years) is offered.

A Postgraduate Certificate (60 credits, flexible study over a period of two years) is offered.

Core modules

  • Principles of Health Informatics

Optional modules

  • Research Methods in Healthcare
  • Information Systems in Healthcare
  • Electronic Health Records
  • Patient Safety and Clinical Risk
  • Clinical Decision Support Systems
  • eHealth: Patients and the Internet
  • Information Law and Governance in Clinical Practice
  • Learning Health Systems
  • Principles of Health Data Analytics
  • Principles of Health Data Science*
  • Data Methods for Health Research*
  • Machine Learning in Healthcare & Biomedicine*

*Full-time MSc students have option to share Data Science for Research in Health & Biomedicine modules

Dissertation/report

All MSc students undertake an independent research project, normally based at their place of work, which culminates in a piece of work written in the style of a journal article.

Teaching and learning

The programme is taught by 'blended learning', and therefore includes interactive online teaching and face-to-face lectures, seminars and workshops including substantial use of examples of real clinical systems. Assessment is through examination, critical evaluations, technical tasks, coursework and project reports, compulsory programming and database assignments, and the dissertation.

Further information on modules and degree structure is available on the department website: Health Informatics MSc

Careers

Health informatics is a subject of growing importance, with exciting career development prospects for clinicians, managers, administrators and technologists. The main areas where our graduates find employment are business intelligence, information management, project and programme management, informatics analysts and directors, quality and service improvement management.

Recent career destinations for this degree

  • Business & Performance Manager, Camden & Islington NHS FT
  • Business Intelligence Analyst, Hinchingbrooke Hospital (NHS)
  • Commissioning Manager, NHS South Tees Clinical Commissioning Group
  • Programme Manager, NHS Wakefield Clinical Commissioning Group (CCG)
  • Project Manager, Cambridge University Hospitals NHS Foundation Trust

Careers data is taken from the ‘Destinations of Leavers from Higher Education’ survey undertaken by HESA looking at the destinations of UK and EU students in the 2013–2015 graduating cohorts six months after graduation.

Why study this degree at UCL?

The MSc in Health Informatics at UCL is taught by a team of specialists within the UCL Institute of Health Informatics, and understanding how information technologies can be harnessed for improving the delivery of care is central to their academic mission. UCL is at the centre of a vast network of clinical collaborators and houses probably the largest concentration of health informatics expertise in the UK.

The institute conducts world-leading research and our teaching, which is research based, focuses on areas such as electronic healthcare records, decision support systems, consumer health informatics, and clinical and applied bioinformatics.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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This course is ideal for graduates who love to work in a role that connects computing and biology, medicine, or healthcare, and have an analytical and inquisitive mind. Read more

This course is ideal for graduates who love to work in a role that connects computing and biology, medicine, or healthcare, and have an analytical and inquisitive mind.

Our school of School of Computing and Engineering has developed partnerships, such as Amazon allowing our students to gain vital industry skills in:

• integration with big data

• cloud computing

• cyber-security.

This course has been structured with the modern healthcare sector in mind, providing you with the opportunity to gain comprehensive ICT skills required by the sector.

Course detail

We aim to develop future leaders through increasing your knowledge and skills in:

• how to manage and analyse large scale, individual and personalised health data

• ethics and governance issues around health data

• big Data (statistical and machine-learning) methods

• the healthcare context, processes and environment

• clinical and biological problems

• healthcare system integration (HL7 messages)

• informatics project management/change management

• exposing you to a range of health information systems and technologies

Modules

  • Research Methods 
  • Supervised Research Project
  • Information Systems in Healthcare 
  • Knowledge Management 
  • Data Architecture 

Option modules

  • Leadership and Management Competence in Healthcare 
  • Information Systems in Healthcare 
  • HCI for Information Systems 
  • Data Management in Healthcare 
  • Programming Support 
  • Dissertation in Health Informatics 
  • Public Health Perspectives 
  • Measuring Public Health and Wellbeing 
  • Knowledge Management 

Career and study progression

This course will thoroughly prepare you for a wide range of careers as a health informatics or Bioinformatics practitioner in the public and private sectors, including:

• clinical informatics

• personalised Medicine

• clinical bioinformatics

• education and training

• health records and patient administrators

• information and communication technology

• information management

• libraries and knowledge management

• project and programme management.

On successful completion of this course you can pursue further study at MPhil and PhD level.

How to apply

Click the following link for information on how to apply to this course.

Scholarships and bursaries

Information about scholarships and bursaries can be found here.



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The UCL programme in Data Science for Research in Health and Biomedicine covers computational and statistical methods as applied to problems in data-intensive medical research. Read more

The UCL programme in Data Science for Research in Health and Biomedicine covers computational and statistical methods as applied to problems in data-intensive medical research. Students learn techniques that are transforming medical research and creating exciting new commercial opportunities. Our recent graduates, many of whom begin paid internships while completing the MSc, have moved on to roles in industry and academia.

About this degree

Students learn how to link and analyse large complex datasets. They design and carry out complex and innovative clinical research studies that take advantage of the increasing amount of available data about the health, behaviour and genetic make-up of small and large populations. The content is drawn from epidemiology, computer science, statistics and other fields, including genetics.

Students undertake modules to the value of 180 credits.

The programme consists of five core modules (75 credits), three optional modules (45 credits) and a dissertation/report (60 credits).

A Postgraduate Diploma (120 credits) is offered.

A Postgraduate Certificate (60 credits) is offered.

Core modules

  • Principles of Epidemiology Applied to Electronic Health Records Research
  • Data Management for Health Research
  • Statistics for Epidemiology and Public Health
  • Statistical Methods in Epidemiology
  • Topics in Health Data Science

Optional modules

  • Advanced Statistics for Records Research
  • Database Systems
  • Information Retrieval and Data Mining
  • Principles of Health Informatics
  • Machine Learning in Healthcare and Biomedicine
  • Statistics for Interpreting Genetic Data
  • Electronic Health Records
  • Clinical Decision Support Systems

Dissertation/report

All students undertake an independent research project which culminates in a dissertation. Project Proposal 20% (2,000 words); Journal Article 80% (6,000 words).

Teaching and learning

The programme is delivered by clinicians, statisticians and computer scientists from UCL, including leading figures in data science. We use a combination of lectures, practical classes and seminars. A mixture of assessment methods is used including examinations and coursework.

Further information on modules and degree structure is available on the department website: Data Science for Research in Health and Biomedicine MSc

Careers

Students on this programme will be passionate about research and know that, in the 21st century, some of the most exciting, stimulating and productive research is carried out using large collections of data acquired in big collaborative endeavours or major public or private initiatives. We hope that graduates will build on that passion and, together with the experience gained on the programme, will go one to develop careers as entrepreneurs, scientists and managers, working in industry, academia and healthcare.

Employability

The programme is designed to meet a need, identified by the funders of health research and by a number of industrial organisations and healthcare agencies, for training in the creation, management and analysis of large datasets. This programme is practical, cross-disciplinary and closely linked to cutting-edge research and practice at UCL and UCL’s partner organisations. Data science is arguably the most rapidly growing field of employment at the moment and employers recruiting in health data science include government agencies, technology companies, consulting and research firms as well as scientific organisations. A number of employers are supporting the programme in different ways, including providing paid internships to selected students.

Why study this degree at UCL?

Data science is an exciting area with a dynamic job market, including in healthcare. Our graduates have gone on to work for a range of companies, including large research organisations and small start-ups, while others are working in health care or pursuing their interests in universities.

The lecturers on this programme are international experts in health data science and students will learn about cutting-edge research projects. The collaboration is part of the Farr Institute, a network of centres of excellence created to enhance the UK’s strength in data-intensive research. This MSc will draw on that collaboration, giving students access to the most advanced research in the field.

We work closely with a range of employing organisations to ensure that our graduates have the best possible preparation for a career in data science. This includes offering industry-sponsored dissertations for selected students.

Research Excellence Framework (REF)

The Research Excellence Framework, or REF, is the system for assessing the quality of research in UK higher education institutions. The 2014 REF was carried out by the UK's higher education funding bodies, and the results used to allocate research funding from 2015/16.

Learn more about the scope of UCL's research, and browse case studies, on our Research Impact website.



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Overview. This course is still accepting applications for September 2018 entry. According to UN forecasts, by 2030 urban areas are projected to house 5 billion people globally (60 per cent of total population) and 662 cities will have at least 1 million residents. Read more

Overview

This course is still accepting applications for September 2018 entry

According to UN forecasts, by 2030 urban areas are projected to house 5 billion people globally (60 per cent of total population) and 662 cities will have at least 1 million residents.

Our Urban Informatics MSc is designed for students who want to play a part in influencing the future of these growing cities and the wellbeing of their citizens. It will equip students to capture and use the rich behavioural data increasingly available from cities and citizens themselves.

Using London as a lab, it will use detailed case studies to equip students with the technical skills required to conduct effective urban data analysis, and then to communicate results to effect change.

This course is suitable for students with a computation or statistical background, or geography with a computational component.

Features

  • Draws from both natural and social science areas to provide a rounded degree that combines the technical and social aspects of urban informatics.
  • Based in the Centre for Urban Science and Progress London (CUSP London), with connections to New York University and CUSP New York.
  • Located in central London, with opportunities to interact with government agencies and for grounded case studies using London as a lab to drive effective learning.
  • Friendly and supportive learning environment, with students from across the globe.
  • Based in the Faculty of Natural and Mathematical Sciences, with links to both Health and Social Science and Public Policy and world-leading teaching and research.

Course details

The first term provides foundation modules in core data science techniques, the theories underlying the study of cities, and ways to communicate analyses so as to affect policy-making. The second term focuses on data analysis for cities, providing insight into both spatial and network analysis as well as providing more depth on data mining techniques.

In term two you will also take a specialised module exploring one aspect of city life, such as air pollution or mental health, in real depth and detail. This provides a testbed for the analysis techniques learnt, enabling students to develop confidence and experience with handling urban data. In the summer term you will also engage in a substantive individual project – connected to our research interests – tackling one of a range of urban informatics topics.

Sign up for more information. Email now

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Healthcare professionals wishing to extend their understanding of issues relating to quality, information and safety are encouraged to apply for this specialised pathway. Read more
Healthcare professionals wishing to extend their understanding of issues relating to quality, information and safety are encouraged to apply for this specialised pathway. Teaching is delivered by specialists in their field and a student advisor supports students in selecting modules and in reviewing their personal development plan and career goals.

Degree information

Students explore various facets of healthcare quality with an emphasis on the role of information evidence, regulation and safe practice. They develop insights into the challenges of managing high-quality service delivery change, and confidence to tackle the complex job of improving patient care. Implicit in the selection of modules is the acquisition of skills and knowledge relevant to a student’s day-to-day professional life.

Students undertake modules to the value of 60 credits.

The programme consists of one core module (15 credits), and three optional modules (45 credits).

Core modules
-Healthcare Quality and Evidence Based Practice

Optional modules - choose three from the following:
-Healthcare Associated Infection Prevention, Control and Organisational Aspects
-Information Law and Governance
-Leadership and Professional Development
-Legal and Regulatory Aspects of Healthcare Associated Infection Control
-Litigation, Complaints and Concerns: Raising Clinical Standards
-Patient Safety and Clinical Risk
-Quality Improvement in Healthcare
-Research Methods in Healthcare

Teaching and learning
Some modules are taught by full distance learnnig. Other modules are delivered through blended learning, combining formal contact time with academic staff, research fellows and guest speakers, and interactive online study using the virtual learning environment. The amount and timing of campous attendance varies between modules - see module library for details. Assessment varies according to the modules selected but is primarily via coursework.

Careers

The programme offers practitioners a focused education and training, which chimes with the NHS's commitment to incorporate elements of clinical governance, quality assurance, health informatics, and change management into continuing professional development curricula for both clinicians and managers.

Employability
Increasingly employers are advertising posts with job titles which include the terms 'patient safety', 'risk', 'quality' and 'clinical governance'. This award is aimed at clinical professionals who have taken on a new role in their organisation with a remit for safety and quality or who are seeking to shift their career in this direction. The skills and knowledge acquired from this certificate will assist students in furthering their career in this expanding field.

Why study this degree at UCL?

This new specialised Health and Medical Sciences pathway focuses on key topics relating to quality, information and safety, and equips students with the professional skills needed in modern healthcare settings.

The programme offers the opportunity to study at a time and place convenient to your own circumstances making it feasible to combine study and full-time work.

It provides access to a range of modules relating to quality, governance, information and safety, as well as opportunities to interact with a range of senior academics and professional experts drawn from across UCL and beyond.

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Imperial College London Medicine
Distance from London: 0 miles
Our Cancer Biology stream provides broad training in research and prepares you for a research career in the fight against cancer. Read more

Our Cancer Biology stream provides broad training in research and prepares you for a research career in the fight against cancer.

The course embraces cutting-edge developments in the field: you will experience some of the most technologically advanced approaches currently being applied to the broad field of cancer research in a teaching programme that comprises both theoretical and practical elements.

We offer two streams:

  • Cancer Biology
  • Cancer Informatics

Your choice of stream will inform the modules you study and your choice of research projects. The structure of the course and assessment methods are similar for both streams.

Careers

This MRes is designed for aspiring researchers – many of our students go on to study for a PhD.

Those in employment have entered into roles such as Research Scientist, Research Assistant, and Scientific Officer.

Further information

For full information on this course, including how to apply, see: http://www.imperial.ac.uk/study/pg/medicine/cancer-biology/ ;

If you have any enquiries you can contact our team at:



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Imperial College London Computing
Distance from London: 0 miles
This specialism focuses on the study of vision, graphics, intelligent behaviour and biomedical image computing. This taught postgraduate course is aimed at students who may not have studied computing exclusively but who have studied a considerable amount of computing already. Read more

This specialism focuses on the study of vision, graphics, intelligent behaviour and biomedical image computing.

This taught postgraduate course is aimed at students who may not have studied computing exclusively but who have studied a considerable amount of computing already.

If you want to become a specialist in a particular area of computing, this course will provide a first crucial step towards that goal.

Further information

For full information on this course, including how to apply, see: http://www.imperial.ac.uk/study/pg/computing/visual-computing-robotics/

If you have any enquiries you can contact our team at:



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Imperial College London Medicine
Distance from London: 0 miles
The. MSc in Health Data Analytics and Machine Learning. at Imperial College London is a one-year full-time course aimed at building a solid and common background in analysing health data. Read more

The MSc in Health Data Analytics and Machine Learning at Imperial College London is a one-year full-time course aimed at building a solid and common background in analysing health data.

Your main objective is to develop skills in using appropriate cutting edge quantitative methods to fully exploit complex and high dimensional data.

The course is delivered by the School of Public Health in collaboration with the Data Science Institute, with teaching from both the School and Institute undertaken by international experts with strong methodological background and expertise in the application of these approaches to large-scale medical and clinical data.

Each module and the six-month research project includes project-based work. Projects are based on real data and will address real scientific questions from research staff within School of Public Health, Data Science Institute and industrial partners.

The programme is a full-time 12 month taught Master’s course, which runs from October-September.

The course is divided between six core taught modules and one six-month research project.

In term one, you share your first two modules with MSc Epidemiology and Master of Public Health students, ensuring a common foundation in epidemiology. The third core module is specific to this course.

You will also set and agree a research project focus in your first term.

In term two, you turn your focus to statistical methods in the three remaining core modules, as well as continuing in-depth planning for your research project.

Your third term is predominantly made up of the research project.

Graduates of this course will have acquired the strong methodological background needed to perform in-depth analysis of medical and epidemiological high throughput datasets.

You will graduate prepared to pursue further study at doctoral level, become an expert analyst in industry, and join large data companies.



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