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Digital Health is NOT Dead, maybe

Digital Health By Mark Jamilkowski

I am both excited and alarmed by the articles and case studies on emerging healthcare related technology and related investments which highlight new healthcare apps, data management tools, or enhanced analytic software suites. There is tremendous potential to be incredibly impactful to the experience we have in managing our health, to the processes we encounter in the delivery of care, and to the quality of care being delivered.

I have been in the industry coming up on 30 years now, in a variety of roles. Trained as a health actuary, I believe I have a unique appreciation for the data collected from the consumer engagement aspect of digital health, and see this interface as critical to capture social determinant based information, as well as health and fitness status, across the entire community (and not just patients). The application of this information is widespread, impacting not only the delivery of care, and alignment of care professionals in the case management/pop health space, but also in the financial management and product development part of the health-based value chain. I have watched many clients struggle with digital solutions intended to "fix" things, but have failed because of lack of understanding and vision associated with the wide-spread and ripple-like effect digital health solutions can (and should) have.

In reviewing the materials, I see four main areas of influence. The four areas are community health data collection and engagement, patient based care delivery and clinical services, operational support and data management services and in the financing and insurance aspect of the ecosystem. Below I discuss the first two:

Community Based

Community based data collection and related apps target consumer engagement. These apps and technologies are typified by personalized wellness programs, gamification, automated tracking of social determinants, and directed chronic care support and decision support to behavioral/mental health patients, seniors, diabetics, heart failure/CHF patients, asthmatics, and cancer patients, in particular. Tele-health platforms are another popular venture, forming a bridge between these broader wellness and care management initiatives and directed care delivery. This may also coincide with employer sponsored programs that offer employees assistance in health-related lifestyle changes. Participation incentives however varies considerably, so interaction is not consistent so measurement is difficult. In my opinion, these programs need strong insurance product support and collaboration to reach their potential. Not recognizing and addressing this interdependence will greatly limit the value and impact of these technologies.

Care Delivery and Clinical Services

The appeal for technology that addresses care delivery pains and operational gaps is well documented. There are opportunities for revenue and cash-flow improvement (sustainability) as well as improvement in efficiency and effectiveness. The results promised include beating prognosis, improving satisfaction scores, increasing quality and STARs ratings, and so on. The risks associated with technology developed on the care delivery side include new technologies and tools that overlap existing (internal) capabilities, versus augment / supplement. Also, the actual impact of these investments greatly depends on the overall maturity of the organization in terms of data management and analytics, as well as in terms of clinical process and alignment. If the cultural alignment and competencies of the staff are out of sync with the purchased technology, the results are likely in my experience to be sub-optimal and result in backlash, delays, frustrations, and deterioration in relationships.

Some technologies in this space are tactical, focused on patient engagement, including care and pain management, appointment scheduling and billing. Most of the focus appears aimed at applying varying levels of reasoning and cognitive analytics in decision support, to suggest appropriate, potentially alternative, care delivery methods. The support may also extend to care professional alignment and care coordination needs. Some technologies are purported to identify clinical workflow configurations around automated evidence based standards / clinical pathways. Here is an excellent example of exciting and concerning. It is exciting to note that the analytics are addressing the complex math associated with modeling, monitoring and tracking variations in clinical pathways, and trying to create faster decisions around care delivery process optimization. The use of petri nets and multi-objective optimization techniques is a direct reflection of the maturing sophistication of data availability and application of more advanced analytic sciences (and not just bio-pharma sciences) to healthcare issues.

However, while all very promising and exciting, it is concerning that little mention is given the actuarial elements that identify and quantify risk within these applications. Data organizing tools should be understood for their risk adjustment capabilities. This includes how statistical concepts such as credibility and singularity are applied in data sets, and how poly-chronic cohorts and their inherent clinical and population based variances are optimized. Reflecting actuarial risk in these algorithms may also include how case-mix indexes or other clinical-risk based metrics are incorporated, or to what extent probabilistic (density) functions are used to illustrate a range of issues, outcomes, or pathways, within which professional clinical judgment can be informed. Judgment will be needed, so I prefer “informed” results as opposed to requirements to conform.


It occurs to me that these data and population health related initiatives can create data overload, exacerbate system inter-operability challenges, and threaten to destabilize if done in a patchwork or ad-hoc manner, as compared to in accordance with an overall strategy and detailed but practical implementation plan. There is a risk that a lot of money will be spent chasing technology that in the end disrupts and destroys value and quality, versus supporting and augmenting it.

You may have seen the article about the "Death of Digital Health" – I am not sure it is “dead” but rather I think it is a time for focus and diligence from a total system perspective. I’d like to hear your thoughts on the potential risks and distractions that these emerging technologies and analytic support tools can create. I will be posting some follow up articles to continue the dialog and explain my point of view further as well.

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