Wearing Your Data: A Global Perspective
By Xcenda
The global market for wearable technologies is rapidly expanding as mature economies look at ways to more effectively provide healthcare and reduce costs. This article provides a global perspective of wearable technology, describes how the digital streams (“big data”) may be utilized, and contextualizes the wearable technology big data revolution in terms of current health technology assessment (HTA) processes.
HTA QUARTERLY | FALL 2018
Wearing Your Data: A Global Perspective
By Tom Walters, PharmD, MBA, MS; Cynthiya Ruban, PhD, MS; Kimberly Gittings, PharmD, MS;
Marcus Healey, PhD, MBA, MS
Technological advances within healthcare have resulted in substantially improved access to a wealth of data that can be used to better understand patient behaviors and improve care. Wearable technologies, devices that can be worn or integrated with human skin to continuously and closely monitor an individual’s activities, such as heart rate, step count, and sleeping patterns, have been a driving factor in personalized data collection. The global market for wearable technologies is rapidly expanding as mature economies look at ways to more effectively provide healthcare and reduce costs. This article provides a global perspective of wearable technology, describes how the digital streams (“big data”) may be utilized, and contextualizes the wearable technology big data revolution in terms of current health technology assessment (HTA) processes.
Unique features of wearable technologies
Wearable technologies have different types of sensors that collect and transmit patient-level data, which offer several unique features related to data collection and utilization: 1) real-time monitoring of patients; 2) the ability to share data with caregivers and providers; and 3) the capacity to collect continuous data from a patient over a long period of time. In aggregate, these technologies produce large amounts of real-time data that can be uploaded to a “cloud” database where patterns can be uncovered and insights derived.
Real-Time Monitoring
Wearable technologies often “sync” to individuals’ mobile phones and other wireless technologies used in medical care, with the term “mobile health” (mHealth) used for medicine and public health supported by mobile devices and wearables. The generation, aggregation, and dissemination of health information via mHealth allows for sharing of information and real-time monitoring between patients, caregivers, and providers. Real-time monitoring of patients gives providers an ability to better understand a patient’s health condition and allows providers to relay helpful information to the patient or their caregiver.
Big Data
Many stakeholders (ie, healthcare providers, insurance companies, etc) are interested in the “big data” generated by wearable technology to identify previously undetectable patterns through the convergence of multiple streams and different types of data. These patterns can be utilized to support a wide range of healthcare functions including disease surveillance, clinical decision support systems, and individual healthcare management.
Proven Value
The value of remote monitoring systems in chronic diseases has been demonstrated through improved patient quality of life, better symptom control, improved wound healing rates, reduced lower limb amputations, decreased emergency room visits and unplanned hospitalizations, fewer bed days of care, decreased nursing home admissions in the elderly, and decreased overall costs to the health system. Additionally, big data generated through wearables can offer insights enabling reductions in healthcare cost at a population level, improvements in quality and efficiency through analysis of healthcare data from wearable technology, and identification of new patterns in behavior, care management, or interventions that can lead to improved patient outcomes, improved quality of care, and reduced healthcare utilization.
Payers and HTA agencies’ perspective
While there is a great deal of interest surrounding wearable technologies, many HTA agencies and payers do not explicitly state how, if at all, they are managing wearable technologies and the real-world evidence (RWE) that will be generated. RWE is routinely used in Europe for safety monitoring and drug utilization of marketed products. However, there is increasing interest in the use of RWE for ascertaining treatment efficacy, improving population-level health outcomes that can be useful for HTAs, and for rapid cycle evaluation of medicines and medical devices. A recently conducted review of economic evaluation guidelines noted that many guidelines state that RWE will be considered. In some cases, preferences for RWE are made explicit for certain pieces of evidence and in other cases, guidelines are unclear.
Big data has many implications for HTAs, including improved data collection both within research and clinical practice settings. Additionally, big data can help researchers and clinicians analyze trends in order to stratify patients based on risk for adverse outcomes, ultimately providing the medical community with information to help modify practice patterns and personalize care for their patients. In fact, many clinical trials are being conducted utilizing wearable technologies in order to better monitor patient activities and analyze findings.
Despite this uptake of wearable technologies in clinical trials, the Institute for Quality and Efficiency in Healthcare (IQWiG) in Germany, for example, has released limited information regarding how, they plan to evaluate the benefit of wearable technologies in the future. A proven benefit/value would probably be a requirement for a not yet planned regular reimbursement by statutory health insurance. Similarly, the National Institute for Health and Care Excellence (NICE) in the UK provides information on how they appraise technologies such as medical devices and health promotion activities, but finding information surrounding covered technologies has proven to be challenging. From an HTA perspective, there is currently a gap that exists between the potential of wearable technologies to impact care and the body of scientific evidence needed to demonstrate real-world effectiveness in different disease states. As such, it appears that many HTA agencies have not yet determined reimbursement structures for these technologies.
Big data has many implications for HTAs, including improved data collection both within research and clinical practice settings. Additionally, big data can help researchers and clinicians analyze trends in order to stratify patients based on risk for adverse outcomes, ultimately providing the medical community with information to help modify practice patterns and personalize care for their patients. In fact, many clinical trials are being conducted utilizing wearable technologies in order to better monitor patient activities and analyze findings.
Despite this uptake of wearable technologies in clinical trials, the Institute for Quality and Efficiency in Healthcare (IQWiG) in Germany, for example, has released limited information regarding how, they plan to evaluate the benefit of wearable technologies in the future. A proven benefit/value would probably be a requirement for a not yet planned regular reimbursement by statutory health insurance. Similarly, the National Institute for Health and Care Excellence (NICE) in the UK provides information on how they appraise technologies such as medical devices and health promotion activities, but finding information surrounding covered technologies has proven to be challenging. From an HTA perspective, there is currently a gap that exists between the potential of wearable technologies to impact care and the body of scientific evidence needed to demonstrate real-world effectiveness in different disease states. As such, it appears that many HTA agencies have not yet determined reimbursement structures for these technologies.
Challenges for implementation of wearable technology and wearable devices
The integration of wearable technology, and the big data that it produces, is in its infancy and faces major challenges associated with reimbursement by HTAs and implementation by decision makers, including regulatory and reimbursement approval in multi-payer and single-payer HTAs across the globe (Figure 1).
Figure 1. Challenges for Implementation of Wearable Technology and Wearable Devices
Conclusion
There is a need for additional evidence generation, from both clinical trials and real-world settings, to demonstrate clinical and economic outcomes associated with wearable technologies. Advancement in the analytics of wearable technology data will further demonstrate value and generate opportunities for wearable technologies. This will create a shift from disease treatment to prevention, increased personalization of medical treatment versus a one-size-fits-all approach, and the genesis and maturation of software and hardware companies that may challenge current healthcare industry dynamics.
As the use of wearable technologies continues to grow and gain influence, it is crucial that developers of innovative wearable technologies and the HTA/payer community understand the opportunities (and limitations) for RWE to inform price negotiations and coverage/reimbursement decisions. Furthermore, manufacturers and payers need to collaborate in the generation, interpretation, and application of RWE to determine the place of these technologies and the data they generate within patient care pathways and health policy decisions.
The article should be referenced as follows:
Walters T, Ruban C, Gittings K, Healey M. Wearing your data: a global perspective. HTA Quarterly. Fall 2018. Nov. 13, 2018.
Sources
- Beck RW, Riddlesworth T, Ruedy K, et al. Effect of continuous glucose monitoring on glycemic control in adults with type 1 diabetes using insulin injections: the diamond randomized clinical trial. JAMA. 2017;317(4):371-378. doi:10.1001/jama.2016.19975.
- Brucher L, Moujahid S. The Internet-of-Things. A revolutionary digital tool for the healthcare industry. https://www2.deloitte.com/content/dam/Deloitte/lu/Documents/life-sciences-health-care/lu_digital-tool-healthcare-industry_062017.pdf. 2017. Accessed on June 27, 2018.
- Byrom B, Watson C, Doll H, et al. Selection of and evidentiary considerations for wearable devices and their measurements for use in Rregulatory decision making: recommendations from the ePRO Consortium. Value in Health. 2018;21:631-639.
- EUnetHTA. Wearable Cardioverter-Defbrillator (WCD) Therapy in Primary and Secondary Prevention of Sudden Cardiac Arrest in Patients at Risk https://www.eunethta.eu/wp-content/uploads/2018/01/Assessment_WCD_final.pdf. Published November 30, 2016. Accessed July 28, 2018.
- European Medical Association (EMA). Update on Real World Evidence Data Collection. Accessed at https://ec.europa.eu/health/sites/health/files/files/committee/stamp/2016-03_stamp4/4_real_world_evidence_ema_presentation.pdf. Published March 10, 2018. Accessed July 16, 2018.
- Haghi M, Thurow K, Habil I, et al. Wearable devices in medical Internet of Things: scientific research and commercially available devices. Healthcare Informatics Research. 2017;23(1):4-15.
- Institute of Health Economics. Real World Evidence – What role can it play in real world decision-making? https://www.ihe.ca/download/real_world_evidence_what_role_can_it_play_in_real_world_decision_making_.pdf. 2017. Accessed July 16, 2018.
- Kite-Powell J. Are medical grade devices the next generation of wearables? https://www.forbes.com/sites/jenniferhicks/2016/04/30/are-medical-grade-devices-the-next-generation-of-wearables/#2bbe6f1062bb. Published April 30, 2016. Accessed July 15, 2018.
- Lamkin P. Wearable tech market to be worth $34 Billion by 2020. https://www.forbes.com/sites/paullamkin/2016/02/17/wearable-tech-market-to-be-worth-34-billion-by-2020/#56ac711f3cb5. Published February 17, 2016. Accessed June 27, 2018.
- Mechael P, Kaonga N, Batavia H, et al. mHealth: new horizons for health through mobile technologies. World Health Organization. http://www.who.int/goe/publications/goe_mhealth_web.pdf. 2011. Accessed August 28, 2018.
- Morton N, Blackman D. The growing availability of wearable devices: a perspective on current applications in clinical trials. Applied Clinical Trials. http://www.appliedclinicaltrialsonline.com/print/314756?page=full. 2016. Accessed June 26, 2018.
- NICE. Technology appraisal guidance. https://www.nice.org.uk/about/what-we-do/our-programmes/nice-guidance/nice-technology-appraisal-guidance. Accessed July 15, 2018.
- PWC. The Wearable Life 2.0 Connected living in a wearable world. https://www.pwc.se/sv/pdf-reports/the-wearable-life-2-0.pdf. April 30, 2016. Accessed July 28 2018.
- Schüll ND. Data for life: Wearable technology and the design of self-care. BioSocieties. 2016;11(3):317-333.
Soren Research. How smart wearables disrupt the healthcare sector. http://www.soreonresearch.com/wp-content/uploads/2014/09/Extract-Soreon-Research-Report-The-Wearable-Health-Revolution.pdf. Published October 2014. Accessed August 29, 2018. - United Healthcare. United Healthcare Motion. https://www.uhc.com/employer/programs-tools/for-employees/unitedhealthcare-motion. Accessed July 15, 2018.
- Wang S, Goring SM, Lozano-Ortega G. Inclusion of real-world evidence in submission packages to health technology assessment bodies: What do current guidelines indicate? Value in Health. 2016;19(3):A287. EUnetHTA. Wearable cardioverter-defibrillator (WCD) therapy in primary and secondary prevention of sudden cardiac arrest in patients at risk. https://www.eunethta.eu/wp-content/uploads/2018/01/Assessment_WCD_final.pdf. November 30, 2016. Accessed on: July 28, 2018.
- Wright, R, Keith L. Wearable technology: if the tech fits, wear it. Journal of Electronic Resources in Medical Libraries. 2014;11(4):204-216.
Wu J, Li H, Cheng S, Lin, Z. . The promising future of healthcare services: when big data analytics meets wearable technology. Information & Management. 2016;53(8):1020-1033.
