Healthcare informatics becomes personal informatics
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The document discusses the history and future of healthcare informatics and personal health data. It describes how healthcare in the 21st century has shifted from a focus on treatment to management of chronic conditions through lifestyle and behavioral changes. This represents an opportunity for prevention through monitoring personal health data. The future of healthcare informatics is predicted to become more personal and consumer-focused, with citizens playing a more proactive role in monitoring their own health data through devices and sharing data to receive personalized care and recommendations.
Healthcare informatics becomes personal informatics
- 1. 1 Healthcare informatics becomes personal informatics Ilkka Korhonen Professor, Information Technologies for Healthcare Tampere University of Technology, Finland WC 2012, 28.5.2012 WC2012 Ilkka Korhonen 03.08.12
- 2. 2 19th Century: the century of hygienics WC 2012 Ilkka Korhonen 03.08.12
- 3. 3 20th century: the century of medicine WC 2012 Ilkka Korhonen 03.08.12
- 4. 21st century: the century of behavioral change WC 2012 Ilkka Korhonen
- 5. The health challenge in 21st century: Chronic conditions Life style diseases Management rather than treatment Every day rather than occasionally
- 6. Determinants of health Quality/Efficacy of 10% Healthcare healthcare services delivery system Behavioural patterns- Lifestyle, exogenous 60% Nurture environmental factors, determinants socio-economic circumstances Genetic predispositions, endogenous 30% Nature determinants acquired genetic changes SA Schroeder: We Can Do Better - Improving the Health of the American People. N Engl J Med 2007; 357:1221-8, McGinnis et al., Health Affairs 21(2), 2002
- 7. Systems medicine Determinants of health organized as a “Systems Medicine” view. © Bousquet et al. Systems medicine and integrated care to combat chronic noncommunicable diseases. Genome Medicine 2011, 3:43
- 8. Prevention opportunity via behavioral change • Cardiovascular disease: 73-83% Nurses Health Study, NEJM 2000;343:16-22, NEJM 2001;345:790-97 • Diabetes type II: 58-91% Tuomilehto, 2001 NEJM 344(18): 1343-50 Nurses Health Study, NEJM 2000;343:16-22, NEJM 2001;345:790-97 • Cancer: 60-69% De Lorgeril, Arch Int Med 1998;158:1181-87 HALE Project. Knoops JAMA 2004;292:1433- 1439 WC 2012 Ilkka Korhonen 8
- 9. Innovation and Research in Life and Health Services These are also medicines Education Physical Nutrition Activity Education is Medicine Physical Activity is Medicine Nutrition is Medicine IF WE CAN DO • Anamnesis • Prescription • (Self-) Administration Needs Preferences • Monitoring of Compliance & Outcomes Behaviours • Vigilance on Adverse Effects Alberto Sanna, San Raffaele Scientific Institute: PREVE. Building the health eco-system @ Brussels, Nov. 15 th, 201 Engineering AwarenessTM
- 10. 03/08/12 10 A new role for citizens and patients ”People as co-producers of health and care” Proactive Individuals as Individuals as co-producers of co-producers of Health & Care Connected Health Health & Care choices Patients as Reactive passive objects Health & Care Citizen- Professionals Dependency Patient
- 11. Phases of ICT development PCs PCs connected to Internet MOBILE INTERNET Slow or no connections Fixed broadband Mobile took the lead with smart Business-driven Consumer- and business-driven phones, tablets, embedded SIMs “History suggests the mobile Internet has potential to create / One architecture: Client-Server Megatrend (OECD -centric) Location-awareness and gadget Office automation and processdestroy more wealth thanWeb computing cycles based on 10x One architecture: prior integration development user multiplierbusiness models New effect. Mobile broadband with capacity Regarding pace of change, more users will likely connect to the and quality issues Internet via mobile devices than desktop PCs within 5 years”. Cloud Connected Morgan Stanley (The Mobile Internet Report, 2009)Consumer- and utility-driven life Size bigger than in cycle #4 Main- In fact, theInternet 2.0 Connecting Gigatrend (global) sales of smart phones exceeded the sales of PCs in Mini PC world to the Three or four architectures: frame February 2011. Internet Intenet Emb, web, app, broadcast cache New ecosystem-centric business Connecting “The dominant design is the Internet and the future of mobility is the models people Nexec Oy) future of Internet” (Matti Mäkelin, Inflection 1970s- 1981- 1996- 2010 points (c) Matti Mäkelin, Nexec Oy, Finland
- 12. 12 History of personal computing “Before the introduction of the microprocessor in the early 1970s, computers were generally large, costly world starting on 70’s. Personal computers changed this systems owned by large corporations, universities, government agencies, and similar- sized institutions. End IT industry where individual users and Development of users generally did not directly interact with thenew innovative companiesprepare significant value with on machine, but instead would create tasks for the computer their personal computers off-line equipment, such as card punches. A number of assignments for the computer would be gathered up and processed in same would After the in medical informatics? What if batch mode. happen job had completed, users -Citizens In some cases it could take could collect the results. generating health data hours or days betweennew era of a job to information (PHR) and submitting health the computing center -Citizens and new receiving the output.” companies combining health data with Wikipedia health information and their non-health data new era of use of health information -Changing role of health professionals new era of health professionals WC 2012 Ilkka Korhonen 03.08.12
- 13. 13 Personal / Consumer Health Informatics Consumer Health Informatics (CHI) helps bridge the gap between patients and health resources. Consumer Health Informatics include technologies focused on patients as the primary users to health information. Giving patients tools to gather, manage, analyse and communicate their heath information between other patients and health professionals will change the way health care is practised. WC 2012 Ilkka Korhonen 03.08.12
- 14. Personal Health Systems = Personal Health Systems = Health and Wellness Technologies Health and Wellness Technologies Designed for the Consumer Designed for the Consumer Monitoring + Connectivity + Analysis + Feedback Monitoring + Connectivity + Analysis + Feedback
- 15. 15 Key issues in personal health informatics 1. Personal health monitoring 2. Personal data management (PHR) 3. Personal analysis and feedback – giving personal meaning to data and health information 4. Connectivity – to other patients, services, professionals, other application areas ”No man is an island” WC 2012 Ilkka Korhonen 3.8.2011
- 16. Benefits of self-monitoring • Daily weight monitoring helps in weigh loss and weight maintenance Next enable patients to: (Kayman et al., 1990; Linde et al., 2004; Wing et al., 2006) • •Self-monitor Regular diet and energy consumption monitoring supports •Interpret the feedback weight loss and may decrease food •Connect data meaning to intake (Baker & Kirschenbaum, 1993; Perri et al., 1989; Foreyt,things that really matter 2005) •Make real and concrete • Stepchanges in increases exercising monitoring their health and behaviors – baby steps and improved body composition blood pressure (Bravata et al., 2007; Clemes 2009) •Share and play - master • Self-monitoring is the most effieicnt And clinicians to support this Wing et al., 2006 method for getting rid of bad habits as coaches when needed (Quinn, 2010) WC 2012 Ilkka Korhonen
- 17. HRV monitoring combined with diary (=personal context = meaning) and intelligent analysis personally relevant discoveries! Physiological Stress (red) and recovery (green) Day 1 – Wed 4th of Apr, 2012 Sleep Telcos F2f mtg Running Delayed recovery Day 2 – Thu 5th of Apr, 2012 Nap Ice hockey game on TV (play-off) Ilkka Korhonen – Firstbeat stressipäivä 15.5.2012
- 18. Adding comparison to norms 18 adding more motivation and understanding ”should I do something?” Physiological recovery during sleep compared to population reference Day 1 – Wed 4th of Apr, 2012 HRV based recovery measured by RMSSD is 52ms. Population age-adjusted average is 34ms. Your sleep time was 7h 0min. Recommended sleep duration is min 7h Day 2 – Thu 5th of Apr, 2012 HRV based recovery measured by RMSSD is 79ms. Population age-adjusted average is 34ms. Your sleep time was 8h 15min. Recommended sleep duration isvaihdettava alatunnisteeseen *Oma nimi ja esityksen aihe min 7h 03.08.12
- 19. Identification of areas with most 19 improvement potential – seeing the big picture Life style health report based on HRV What next? Working time What next? How to translate understanding into action and concrete behaviors? Physical activity How to load Physical translate understanding into action and concrete Recovery behaviors? Leisure time Health coaching Nudging Health coaching Exercise Context design Nudging Exercise load Context design Recovery EE during exercise Sleep Total recovery Recovery quality Sleep time *Oma nimi ja esityksen aihe vaihdettava alatunnisteeseen 03.08.12
- 20. 20 Conclusions • The 21st century health challenge = life style related chronic diseases prevention and management possible only by empowering patients to do this themselves • Personal health informatics is informatics where patient is the primary user of health information • Personal health informatics enables similar revolution in health management as happened in personal computing • Risks are there... • ... but so are opportunities • Can we stop it?– or shall we rather use it? • Health is personal – so should also health informatics be WC2012 – Ilkka Korhonen 03.08.12
- 21. Thank you! Ilkka Korhonen Professor Dept Biomedical Engineering Tampere University of Technology ilkka.korhonen@tut.fi
Editor's Notes
- #5: First and Foremost…need a system designed to meet today’s health conditions… Our nation’s health has changed, but our current delivery model has remained what is essentially an acute, episodic care business model from the 19th century, a traditional fee-for-service model based on patients visiting hospitals and physicians’ offices only when they’re sick….. In the early 20 th century, infection was the leading cause of death in the United States. Acute in nature, infections were treated as they emerged. (STATS TO SUPPORT) As the century progressed, however, infection gave way to chronic disease as the leading cause of death and primary driver of health costs in the US. The shift is BIG – BIGGER than most folks realize when they think about the system. Complex, chronic disease in less than 10% of the population account for more than 80% of the annual costs. (can we find supporting evidence point?). Think about that for a minute and you recognize there are a bunch of implications of this: Re-engineering these care processes – but they typically cross org and economic boundaries, require behavior changes and more – The data we need to manage deal with these conditions goes way beyond what is collected/managed today The user experience for managing this care may be very different than the ‘chart’ today The need to think wholistically about prevention we need to move from the value being placed SOLELY on the activities focused on acute, episodic care to value being placed on real-time health management over the long-term (acute care vs. chronic care or wellness)
- #8: Determinants of health organized as a “Systems Medicine” view.
- #10: This leads me to our other research focus Behaviour Change Support using mHealth technologies. The driving idea here is an extension of the definition of usual medicines, i.e. pharmaceuticals, surgical and therapautic interventions. We propose to include also education, physical activity and nutrition into the realm of what is considered medicines. The challenge, however, is that we need to find efficient and effective ways to administer these new medicines and to monitor their effects. This is where theories and methodologies for behaviour change support and mHealth as a means of implementation are needed.