The recently renamed QuintilesIMS Institute (previously IMS Institute for Healthcare Informatics) is a global research platform that strives to shape and drive tomorrow’s healthcare industry. Its strategy is based on information and data-driven solutions, where the productive use of big data lies at the heart. Recently, more focus has been given to decision modelling - the process of simulating real-world scenarios to assess the potential impact and consequences of decisions, before allocating resources to the live situations. This is the QuintilesIMS Institute’s latest tool set up to maximize the desired outcome from decisions every step of the way, being powerful enough to integrate complex variables and immense amounts of data.
From the Duke-NUS Stroke Model for example, we observe an alarming increase in the prevalence and growth of stroke in Malaysia, South Korea and the Philippines, all part of the fast-paced and rapidly-transitioning Asia Pacific region. Other observations will show that healthcare costs in Asia are rising, yet its peaking development is leaving unsteady infrastructures and uneven access to quality medical treatment for its populations. If we couple these studies with the fact that Asia is facing general demographic and epidemiological challenges – then the need for a serious do-over of the healthcare strategy in Asia becomes apparent.
A report titled “Advancing Value-Based Healthcare in Asia” published by the QuintilesIMS Institute details the usefulness of decision modelling and relates some of its findings in Asia. This supports the Institute’s fervent drive to implement Value-Based Healthcare (VBH) in order to maximize patient outcomes in a cost-effective manner. With the help of decision modelling and health informatics, their studies have shown the ineffectiveness of a system that capitalises on immediate results. It urges all stakeholders to work towards improving the standards of care and avoid costs in the long-run due to long-term disease complications, for example. This patient-centric approach has indeed proven to be in the best interest of all stakeholders, and with the launch of their new Asian branch, the QuintilesIMS Institute of Healthcare Informatics’ new mission is to bring healthcare actors together to work towards this revised value-based approach of the health industry.
Dr. Xavier Xuanhao Chan is the director for this newly-launched QuintilesIMS Institute for Healthcare Informatics in Asia, and was kind enough to answer a few questions we had, in order to articulate the new trends and concepts that are to be put in place in Asia.
Xavier Xuanhao Chan, PHD Xavier Chan is responsible for developing public health capabilities across IMS Health business units and providing Real-World Evidence (RWE) solutions for clients in China and the Southeast Asia region. He has over 12 years of experience in the healthcare and pharmaceutical policy arena in Europe and Asia with experience on market access, public health and pharmaceutical policy, government relations, real world evidence solutions, and emerging markets.
Prior to joining IMS Health, he was Deputy Country Director for the Clinton Health Access Initiative (CHAI) in Myanmar, where he provided policy and technical assistance to senior officials in Ministry of Health to scale up MDR-TB and HIV treatment programs; accelerate efforts to eliminate malaria; improve effective vaccine management and strengthen supply chain management. Prior to CHAI, he worked as a consultant in various roles for World Self-Medication Industry, International Pharmaceutical Federation and World Health Organisation from2005 to2011. Xavier holds a PhD in Public Health & Policy from the London School of Hygiene and Tropical Medicines, UK and a Master of Science in Geographic Information Systems from Vrije Universiteit, The Netherlands and a Bachelor of Science in Pharmacy from the National University of Singapore.
Interview with Dr. Xavier Xuanhao Chan
From the report “Advancing Value-Based Healthcare (VBH) in Asia” published by QuintilesIMS Institute for Healthcare Informatics in Asia, how will decision modelling benefit patients with different diseases?
Dision modelling is the process of creating and testing various real-world scenarios to assess the potential impact of decisions in these situations. Data-driven insights gathered from modelling such scenarios can inform decision making processes to maximise the value passed on to patients – by allowing them to quickly receive the treatments they need most to recover faster.
Currently, the Institute is carrying out decision modelling for diseases like diabetes and stroke to simulate different treatment choices and its respective health and economic outcomes. This real-world data-driven modelling process can be similarly applied to other diseases as long as there is sufficient data available for analysis.
How can the value-based approaches be used to optimise the healthcare sector in Asia? Could you elaborate on the challenges and opportunities for VBH in Asia?
Value-based healthcare will optimise outcomes both through preventative health initiatives or strategies to improve care provided. It can also mitigate the most significant cost drivers such as acute events and repeat hospitalisations. This will ultimately result in a high quality healthcare system that will enable patients to quickly receive the treatments they need most.
A value-based healthcare approach in Asia creates opportunities for healthcare systems to effectively track outcomes and actual cost of care for each patient to understand what is working, what isn’t, and how to minimise waste. For patients, this means they can expect treatment and disease intervention that is tailored to their needs, introduced at the right time and focused on improving their quality of life.
Of course, such an approach does not come without challenges. Value-based healthcare is a collaborative effort across multiple stakeholders and each one comes with differing priorities and ability to implement change. Also, emerging market health systems often lack technology and regulatory framework to access and share real world data. To maximise the benefits value-based health models can provide in Asia, all stakeholders, including hospitals, government institutions, academia, clinicians, insurance agencies, payers and manufacturers need to revise their focus from the volume and profitability of services provided (i.e. physician visits, hospitalisations, procedures, and tests) to tailored services (i.e. health-related social services) that optimise patient outcomes.
How can QuintilesIMS ensure the delivery of timely and accurate data to leaders or policymakers to make informed decisions?
The QuintilesIMS Institute in Asia invests in building and strengthening specialist physician networks to enable data sharing and collaborative research. Through our networks and collaborative partners, we aim to galvanise resources to improve clinical and academic capacity to collect and analyse longitudinal patient data, which can ultimately be shared with leaders and policymakers to aid in decision making.
The effectiveness of any health information management system depends heavily on the level of engagement and commitment of all relevant stakeholders in the healthcare ecosystem. As a neutral platform for these stakeholders – both public and private – to collaborate, the QuintilesIMS Institute is laying the foundations for the sharing of data and best practice from previously disconnected sources, which is often the case in emerging markets such as Indonesia, Vietnam, Philippines and Thailand.
What is the recent focus of healthcare in China? How does it differ from the rest of Southeast Asia? Could you share some examples of Real-World Evidence (RWE) solutions provided to clients in China?
Real-World Evidence (RWE) solutions use innovative study designs to address payers’ and physicians' increasing needs for evidence. Like most countries, China’s healthcare system remains budget-constrained, with policies favoring essential medicines and services. However, the inefficient use of existing healthcare resources can prevent systems’ sustainability and investments in innovation.
For example, to better understand how insurance coverage can raise efficiency and contribute to being a priority in decision makers' agenda in China, local RWE data were collected to evaluate the impact of insurance coverage of certain drugs with the Patients Assistance Program (PAP) as well as regular laboratory tests.
The project demonstrates short term and long term clinical and health economic outcomes which can be achieved. It successfully addresses stakeholders’ evidence needs, strengthens payers’ belief on key contributors to patient outcomes, therefore greatly supporting further market access and insurance negotiations in China.
In summary, RWE solutions can build trusted partnerships between pharma, physicians, and payers, allowing stakeholders to explore better healthcare solutions for disease treatment. RWE practice has created a model of cross-functional collaboration among strategy, Health Economics and Outcomes Research (HEOR), market access, marketing, and medical teams. This model can be expanded and applied to other products for our clients.
In layman’s terms, how would you define Big Data? What kind of roles do Big Data play in healthcare or medical industry?
Big data is a large pool of information gathered and analysed to reveal patterns and produce insights to aid in decision making. In disease modelling, this can include information relating to epidemiology (e.g. incidence, prevalence and mortality data), activity and patterns of care (e.g. rates of receiving specific interventions) and costs (e.g. costs of tests and medications). Data may be sourced from clinical information systems including electronic health records and patient registries, as well as administrative systems used by payers to manage claims, patient surveys, public records, research studies and clinical trials.
Currently, the Institute taps on big data to carry out decision modelling for diseases like diabetes and stroke to simulate different treatment choices and their respective health and economic outcomes. Insights gathered from modelling such scenarios can inform decision making processes to maximise the value passed on to patients.
It is worth noting that there has been growing importance of real-world health data and analytics to improving healthcare, as stakeholders recognise the progress made in identifying best treatments, improving patient outcomes, and optimising resource allocation.
For example, the Institute’s work with Duke-NUS on the Singapore Stroke Model uncovered a synergistic aspect to stroke intervention strategies. It was found that a suite of interventions (e.g. public awareness campaigns, use of thrombolysis or endovascular therapy, etc.) was much more effective when undertaken together than in isolated instances. Incorporating all stroke practice improvement strategies led to a gain of 14,330 quality-adjusted life years (QALYs) versus only 166 QALYs gained by implementing only a public awareness campaign for the full Singapore population.