The SingHealth Duke-NUS Health Services Research Institute (HSRI) collaborates with SingHealth Health Services Research Centre (HSRC) to deliver ongoing and relevant education opportunities. Other key partners in this are the Office for Service Transformation and the Singhealth Academy.
Health care professionals require the skills and confidence to prosecute health services research. Clinical staff and managers face healthcare challenges every day.
They must respond to population growth, aging population, increasing prevalence of chronic disease, which are costly to manage under current configuration of services, and they have to abide by measures to reduce waste and inefficiency.
Duke-NUS Programme in Health Services and System Research (HSSR) is partnering with SingHealth to deliver an academic programme that is relevant, practical and tailored for the needs of the modern health care professional.
The Graduate Certificate in Health Services Innovation is launched by HSRI on 2 January 2021 and has four academic modules. These will be stackable to a Master's degree and will be taught with the needs of busy health care professionals in mind.
Module 1: Implementation Science for Health Services
This module is designed to introduce health care professionals to the principles of translating evidence for better services into a clinical setting.
Participants will learn processes and factors associated with successful integration of evidence-based interventions within a particular setting, assess whether the core components of the original intervention were faithfully transported to the real-world setting and gain new knowledge about the adaptation of the implemented intervention to the local context.
On successful completion of this module, students will be able to:
• Design interventions based on community, patient, clinician and organizational inputs to translate findings into clinical practice, policy and public health• Design evaluations of interventions that translate evidence into practice• Develop better proposals• Develop a design for a research implementation and/or a dissemination and evaluation project
Module 2: Research Methods for Health Services
This is about the current practice of health services research. It will include a discussion of the reproducibility crisis. The sources of data that are commonly used to address research questions are reviewed and critiqued. Different approaches to assess causality and associations are taught. An introduction to qualitative research methods is provided and participants are taught about systematic reviews and meta analyses.
Upon completion of the module, students should be able to:
• Describe the reproducibility crisis and debate contemporary issues relevant to the conduct of health services research.• Understand the requirements for good survey design, the importance of patient reported outcome measures. The advantages and disadvantages of using disease registries and other routinely collected data. • Apply the methods of qualitative research and understand the value of these approaches to Health Services Research. • Design and conduct a systematic review and simple meta analyses.
Module 3: Health Technology Assessment, Cost-Effectiveness and Decision-making
Health technology assessment is a well-established tool used when decisions need to be made quickly. Often there is no time for new data collection or a dedicated research effort. It is an exercise in synthesizing current evidence and responding appropriately. Economic evaluation has its foundations in welfare economics and offers a theory based approach to informing choice and trade-offs given resources are scarce. Often, new data are required or a more formal research approach is used. Various modelling approaches are used to complete economic evaluations.
• Complete their own health technology assessment project and understand the rationale and methods for doing one. • Understand the principles of welfare economics, market failures and how they apply to the supply of health care services. • Be able to read and interpret a published cost-effectiveness study, able to collaborate with a health economist for a new study. • Understand the scientific paradigms of decision making and how they come into conflict with traditional scientific dogma. • Have awareness of other approaches for decision making such as dynamic system modelling and multi criterion approaches.
Module 4: Data Science + Healthcare
This module exposes students to the foundation concepts, case studies and applications, some mathematics behind data science models and algorithms. There will also be practical sessions for model development, training, validation and tests. Students will acquire new knowledge of data science techniques. The new knowledge from this course will enable predictions to be made about likely diagnoses, prognoses of health conditions and risks of adverse events.
There will also be a mini-project and healthcare case studies to demonstrate the applicability of data science as a key enabler for improving the delivery of health services.
Upon completion, students should be able to:
• Understand the value and application of data science for the future of health services• Develop the ability to independently conduct health data science projects