Event Summary | Digital Health Speaker Series: Data in Healthcare Panel
Edited by Aditya Raj
On Thursday, October 29th, ViTAL hosted its third event in the Digital Health Speaker Series through ZOOM on the topic of Data in Healthcare, particularly regarding its role and significance in the rapidly expanding Digital Health industry.
Many of us are aware of the diverse changes technology has brought to healthcare, from the way care is delivered, the emergence of remote patient care systems, to AI-powered predictive diagnostics, and to more efficient ways of allocating the resources within the healthcare systems utilizing mobile applications. One of the essential groundwork of these breakthroughs is “Big Data.” According to HIMSS, “Big Data” refers to datasets with an exceptionally large volume in size or complexity that is hard for traditional databases or data processing application software to capture, manage, and process with low-latency. Despite its complexity, analytics of big data may reveal patterns, trends, and associations, especially relating to human behaviors and interactions.
We were very excited to have Dr. Trishan Panch, Dr. Nicole Billings, and Jessica Davis join us, each representing a unique field within the Digital Health realm to share their expertise working with various types of healthcare data for their innovative products and research focuses. Dr. Trishan Panch is the Co-founder and Chief Innovation Officer of Wellframe. Wellframe focuses on developing digital health management platforms to enable health plans and healthcare providers to amplify existing care resources to improve patient engagement and better manage care. Along with his hands-on work in Digital Health at Wellframe, Panch is also an instructor at the Harvard T.H. Chan School of Public Health where he teaches Masters and Ph.D. courses in Health Sciences. Dr. Nicole Billings is the Director of Lab Services at Day Zero Diagnostics. Day Zero Diagnostics aims to revolutionize the traditional ways of approaching infectious disease diagnostics by leveraging whole-genome sequencing of infectious agents and use machine learning algorithms to work towards solving the global healthcare crisis of antibiotic resistance. Jessica Davis is a Ph.D. student at the Network Science Institute and the Modeling of Biological + Socio-technical Systems Lab at Northeastern University, where she focuses on the ongoing COVID-19 research both internationally and in the Northeastern Community.
Three main questions framed our discussion:
- What is Big Data’s role and significance in healthcare?
Dr. Panch kicked off the discussion by assessing the value of big data from patients and clinicians’ point of views. He affirms that data has enabled a considerable amount of growth in technology in the past decade. He explains that the approach Wellframe chooses is to improve the patient-clinician care management process. He points out that healthcare professionals are particularly interested in “creating knowledge that benefits the patients.” As more and more healthcare data becomes available and our increasing ability to sense, capture, aggregate, and make inferences from it increases, Dr. Panch believes that the potential for creating value and knowledge using data is present, as well as using innovations to increase the quality of care and its fair distribution. However, there are still many more social and economic factors that need to be addressed given the complex nature of the healthcare system and variations in the quality of care.
Dr. Billings then took the perspective from the data that Day Zero Diagnostics leverages for the development of their innovative tools. In comparison to Wellframe’s platform-based software application that patients engage directly, Day Zero’s technology serves to inform clinicians and its downstream patient care. As a microbiologist, Big Data that Dr. Billings' encounters have always been in the realm of genomics and proteomics, where there is a massive amount of computational work on standardizing the data for further processing. To Dr. Billings, the value of big data in healthcare is to develop tools and pipelines that benefit the clinicians for diagnosis of diseases by appropriately managing and analyzing the data.
Jessica then speaks about her experience working with large volumes of data as a researcher. At Northeastern, Jessica works with terabytes of possible epidemic outcome data. She points out that processing the data mathematically, learning from the mathematical calculations, and transforming them into something visually interpretable is very important for the public to learn stories behind data and for policymakers to make critical decisions.
2. Does the current health data processing help to reduce the complexity (or ease the burden) of the health care system in the United States?
To begin, Dr. Panch addresses the question from the public health system point of view whereas Dr. Billings and Jessica speak about their experience processing the data. As mentioned above, due to variations in health standards and access to care, Dr. Panch states that with the existing technology, aggregating to a system-level of change is challenging because many drivers of different health outcomes are outside of the broadly defined “health system.” However, some differences can be made in specific areas. Dr. Panch emphasizes, even though changing elements of the system through technical innovations would address some issues within, we need to keep in mind that factors that are outside the health systems and have impacts on certain health outcomes still need to be addressed as well.
Dr. Billings agreed with what Dr. Panch pointed out that the healthcare system is very broad, and touched upon the current ways to process data in her area of expertise. For instance, in her experience working with institutions across the country, data management systems across institutions are not as integrated as the public would expect. Procedures such as data sharing among institutions are done frequently, with each lab having its own protocol and platforms. Similarly, every different hospital has its ways to manage data. Dr. Billings points out that the current ways to work with healthcare data need to take into account the complex nature of the healthcare field. Many processes are time-consuming and burdensome for healthcare professionals to work with. She hopes that in the future healthcare data and the ways to process it could become more standardized and streamlined to ease the workload.
Despite the challenges in the current approaches to working with healthcare data, Jessica spoke on some improvements she has experienced in her recent work with the COVID-19 research. Jessica agrees that flexible data sharing among researchers and platforms in previous pandemics were not as common as Dr. Billings described. However, in the COVID-19 pandemic, Twitter exploded with data scientists who would share data in multiple languages and convert them into a readable format that allowed effective research across the world. Although some data should be kept confidential, in the light of the pandemic, this emergence of “collective science” definitely propels both the research and the development of a cure for the virus.
3. How do you put patients’ level of trust and confidence in sharing their own data in designing and building your innovations/products?
Dr. Panch speaks for Wellframe in that they are very protective of patients’ data and only use the data internally for the development of their products that go into the care of the patients. In general, Wellframe strongly supports local evidence-based medicine approaches. Similarly, local approaches to data analysis can be more useful because of the variations in patient populations. Wellframe believes that the best way of creating algorithms and algorithmic products is to focus on problems with the people that know about the data-generating process and building something to alter it. Dr. Billings then added another perspective from Day Zero Diagnostics’ standpoint. She states that the data Day Zero Diagnostics collects is proprietary to them internally. Day Zero Diagnostics does not distribute or sell the data they own. She acknowledges the hesitation and reservation from the patients’ side when it comes to having personal genomic information collected, shared, or utilized for research. For clinical studies, Day Zero Diagnostics states clear of their goal and usage of the data and try their best to de-identify patients’ specific genomic information to help protect patient data. Similarly, Jessica agrees with the other two speakers that some healthcare datasets are sensitive to patients and should not be shared. However, some such as the COVID-19 datasets should be shared effectively and protectively for more biological discoveries that benefit the public.
The key takeaway from this discussion is that data and technology enable us to bridge the gap of health inequities in specific areas within the healthcare system. However, given the complex nature of our system, it is more realistic to look at technology as an assisting tool. Under the influence of the COVID-19 pandemic, we recognize the benefits of computational tools and algorithms such as data sharing and machine learning. We are excited about the advancement of technologies such as digital care management system platforms and digital therapeutic and telemedicine tools. As we are optimistic about the breakthroughs and the potentials of leveraging big data, we need to keep in mind that factors outside the scope of the health system also need to be addressed to better navigate the resources we have and adapt technology into healthcare.
Thank you to our attendees for tuning in, and a very special thanks to Trishan Panch, Nicole Billings, and Jessica Davis for such an insightful event!
The event recording is available here.
