Preventive

Health monitoring

 

Health monitoring and risk monitoring are two distinct topics in this blog. Risk monitoring is much more related to molecular diagnostics (another topic) as it uses these technologies to assess genetic or acquired risks factors of people. Health monitoring is a more general term and much of it is happening outside of clinical environments.

 

Health monitoring is very often part of the active role of participants/patients. Therefore, it is intimately linked to heath education, which will be the next topic of this blog. Confronting people with measurable consequences of their lifestyle has a great educational effect and is a great reinforcement to turn good intentions into lasting actions. We all have the tendency to attribute insufficient attention to health issues to the work load and the many social and personal obligations modern life imposes on us. Health monitoring by any method works as a constant reminder that taking care of our health is not a task we can postpone as convenient in our current situation. It is like sports: If I belong to a sports club and/or have a trainer breathing down my neck I will stick much more to any training regimen that doing things entirely on my own. Being part of a group or team raises the importance of such events (almost) to the level of professional activities, for which we always find time. 

 

Of course, this only works if the heath monitoring can be integrated into our daily lives. Visits to a MD’s surgery twice a week is hardly a sustainable model for heath monitoring, except for the most dedicated hypochondriacs. Basically, the idea of health monitoring by a suitable device is rather old. A Health monitoring system has already been described in a US Patent (number 5778882) dating back to 1995.

 

The ideal form of health monitoring is non-invasive, based on easy-to get, best automatically collected data and an immediate (ideally positive) feedback to the person. Health monitoring including minimal invasive measures of blood sugar levels is the most widespread monitoring forms for diabetes patients. Integration of data originating from sensor-based systems and electronic health records combined with smart data analytics methods and powerful user centered approaches enable the shift toward preventive, predictive, personalized, and participatory diabetes care (Zarkogianni et al., 2015).

 

But it does not stop there. Obesity, often a prelude to diabetes, is one of the biggest drivers of preventable chronic diseases and healthcare costs in Worldwide. Monitoring of the daily energy expenditure (EE) could be be used to personalize diets and programming physical activity. Physical inactivity is one of the most important public health problems. However, physical activity can be promoted only by increasing citizens' empowerment on taking care of their health, and it passes from the improving of individual information. The assessment of the energy expenditure critically relies on physiological data acquisition. Sensors connected with mobile devices could be important tools for disease prevention and interventions affecting health behaviors (Tagliente et al 2016).

 

A already mention, requirements form health monitoring devices goes well beyond the development of technical solutions. Crucial innovations in making and deploying usable empowering end-user services are needed. They need to be trusted and user-acceptable. Only then large-scale information and communication technology-supported adoption of healthier lifestyles can become a reality. Such innovations require multidomain, multilevel, transdisciplinary work, grounded in theory but driven by citizens’ and health care professionals’ needs, expectations, and capabilities and matched by business ability to bring innovation to the market (Spanakis et al 2016). 

 

User-acceptability can only be tested and proven by us, the users and will require us to articulate our concerns or approval of devices. Just because some smart watch sells like hotcake due to its coolness factor does not automatically make it the best choice for health monitoring if it lacks critical features.

 

Preventing disease is beating monitoring disease

 

Not every disease or risk factor can be avoided, especially if there is a genetic basis to it. However, being at risk for a disease or actually developing clinical symptoms is not the same. A person can have an inevitable genetic risk for a particular disease and still prevent, delay or ameliorate the outbreak. A nice example for such a situation is hemophilia. Patients have a genetic variation that impairs their blood clotting system to some degree.This may cause uncontrolled bleeding upon even small injuries, which can be life-threatening without treatment. In this case, prophylaxis is considered optimal care for hemophilia patients to prevent bleeding and to preserve joint function thereby improving quality of life. 

 

Hemophilia prophylaxis can be further individualized by taking into account the bleeding phenotype, physical activity/lifestyle, joint status, and pharmacokinetic handling of specific clotting factor concentrates, all of which vary among individuals. Here, several determinants have to be considered in context to achieve optimal prophylaxis for individual patients. These include factor dose/ dosing frequency, cost/affordability, bleeding triggers (physical activity/lifestyle, chronic arthropathy and synovitis), and bleeding rates. Altering one determinant inevitably results in adjustment of the other two. Fully personalized medicine in every respect. And here is where things become inseparable: Clinics with comprehensive care are central to the success of prophylaxis. This necessitates professional expertise, support, and counseling, patient and family education (Poon & Lee, 2016).

 

Behavior heath monitoring by phones, watches & co.

 

Naturally, health monitoring is taking advantage of the literally omnipresent smart phones and other smart devices. Consumer-grade smart watches have penetrated the health research space rapidly since 2014. However, this has become pervasive only a few years ago. Therefore, smart watch technical function, acceptability, and effectiveness in supporting health must be validated in larger field studies that enroll actual participants living with the conditions these devices target (Reeder et al 2016).

 

A rather important part of our behavior regards what, when and how much we eat and drink, in one word our nutrition. The efficacy of behavioral nutrition interventions using e-health technologies to decrease fat intake and increase fruit and vegetable intake was demonstrated in studies conducted from 2005 to 2009, with approximately 75% of trials showing positive effects. By 2010, an increasing number of behavioral nutrition interventions were focusing on body weight, fighting obesity (see above). The emphasis shifted more and more to personalized electronic interventions that included weight and behavioral self-monitoring as key features. This is where monitoring and education meet again. More diverse target audiences began to participate, and mobile components were added to interventions. However, most regimes still rely on self-reported measures of dietary behavior rather than objective measurements. Changing the design and use of the many electronic devices that are now available in the marketplace for nutrition monitoring and behavioral change will require joint efforts between nutritionists and the industry producing such devices (Olsen 2016).

 

Asthma and Chronic Obstructive Pulmonary Disease (COPD)

 

Nevertheless, there are several fields of health monitoring where smart devices are already applied successfully.  Asthma and COPD are common chronic obstructive lung disorders in the US that affect over 49 million people, unfortunately without a real cure. The best that can be done is controlling symptoms, which is successful in most patients that adhere to their personal treatment plan. Smart monitoring devices are pivotal in that respect and are mainstream tools to assist patients in self-monitoring and decision-making. In the long run, this should result in a shift toward a care model increasingly centered on personal adoption and use of digital and web-based tools, personalized healthcare. Online communities for asthma and COPD patients are very attractive as they spare the trip to the MD. Patients are supported online, and patient-centered research efforts become feasible (Himes & Weizmann, 2016).

 

Many Asthma patients have to rely on inhalers to treat or prevent asthma attacks. Therefore, the inhalers themselves are perfect for integrating monitoring technologies. Inhaler-based monitoring devices were already introduced in the beginning of the 1980s. Initially their main purpose was the assessment of medication adherence. In the meantime technological progress and novel sensing components allowed the enhancement of inhalers with a wider range of monitoring capabilities. This should help to optimize asthma self-management (Kikidis et al, 2016). 

 

Epigenetic health monitoring

 

Environmental Epigenomics studies the epigenetic effect (changes to chromosomes without changes to the DNA sequence) on human health from exposure to environmental factors. This is often brought about by chemicals detected primarily in pharmaceutical drugs, personal care products, food additives, and food containers. There is hardly anybody in the modern world not affected by at least some of these incredients, called endocrine-disrupting chemicals. They were found to be associated with a high incidence and prevalence of many endocrine-related disorders in humans. The assessment of such chemical and their epigenetic effects is changing with new analytical technology, including DNA methylation analysis as a viable method for assessing the effects of endocrine disruptors (Tapia-Orozco et al, 2017).

 

A common theme for all the examples mentioned above is that patients/citizens, in short everybody has to agree on participating in such monitoring, be it personal or a part of a larger study. Generalized insights can only be derived from health monitoring if a sufficient number of participants is achieved. Given the social, educational, and financial heterogeneity of modern societies, this is not always an easily achieved condition.

 

However, there is one part of modern societies where this is no an issue because people are simply ordered to participate. The military is ideal in terms of adherence to strict regimes, availability and follow up of its members. The biggest disadvantage is the non-representative composition of the group necessarily lacking juveniles and the old age group. Also the representation of women is far lower than in the general population. Setting these sampling issue aside, the military is an ideal test ground to evaluate what can be achieved by high coverage of a group. Bradburne et al (2015) have nicely summarized what kind of technologies (omics), tools, and equipment are considered by military medicine to be compatible with downstream processing and analysis for each class of molecule measured. They consider genomics, epigenomics, transcriptomics, metabolomics, proteo- mics, lipidomics, and efforts to combine their use. The usual suspects in personalized medicine. It will be very interesting to see, what results are borne out in this special environment and to which extent this will be relevant and applicable for general public and personal health monitoring. 

 

References

 

16    Reeder, B. & David, A. Health at hand: A systematic review of smart watch uses for health and wellness. J

        Biomed Inform 63, 269-276, doi:10.1016/j.jbi.2016.09.001 (2016).

17    Zarkogianni, K. et al. A Review of Emerging Technologies for the Management of Diabetes Mellitus. IEEE Trans

        Biomed Eng 62, 2735-2749, doi:10.1109/TBME.2015.2470521 (2015).

18    Tagliente, I. et al. Which indicators for measuring the daily physical activity? An overview on the challenges and

        technology limits for Telehealth applications. Technol Health Care 24, 665-672, doi:10.3233/THC-161216 (2016).

19    Tapia-Orozco, N. et al. Environmental epigenomics: Current approaches to assess epigenetic effects of 

        endocrine disrupting compounds (EDC's) on human health. Environ Toxicol Pharmacol, 

        doi:10.1016/j.etap.2017.02.004 (2017).

20    Spanakis, E. G. et al. Technology-Based Innovations to Foster Personalized Healthy Lifestyles and Well-Being: 

         A Targeted Review. J Med Internet Res 18, e128, doi:10.2196/jmir.4863 (2016).

21    Olson, C. M. Behavioral Nutrition Interventions Using e- and m-Health Communication Technologies: A 

        Narrative Review. Annu Rev Nutr 36, 647-664, doi:10.1146/annurev-nutr-071715-050815 (2016).

22    Himes, B. E. & Weitzman, E. R. Innovations in health information technologies for chronic pulmonary diseases. 

         Respir Res 17, 38, doi:10.1186/s12931-016-0354-3 (2016).

23    Kikidis, D., Konstantinos, V., Tzovaras, D. & Usmani, O. S. The Digital Asthma Patient: The History and Future of 

         Inhaler Based Health Monitoring Devices. J Aerosol Med Pulm Drug Deliv 29, 219-232,    

        doi:10.1089/jamp.2015.1267 (2016).

24    Poon, M. C. & Lee, A. Individualized prophylaxis for optimizing hemophilia care: can we apply this to both 

         developed and developing nations? Thromb J 14, 32, doi:10.1186/s12959-016-0096-y (2016).

25  Bradburne, C. et al. Overview of 'Omics Technologies for Military Occupational Health Surveillance and 

       Medicine. Mil Med 180, 34-48, doi:10.7205/MILMED-D-15-00050 (2015).

 

What’s coming up next?

 

Next week I will expand into the field of Education as an important aspect of personalized medicine. Only people with some basic knowledge are competent partners and motivated to maximize modern medicine - the slogan of our association.

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