The HealthKit Revolution, Part 2: Piloting Health Apps

During the past few years, providers have found it challenging to engage patients in their own care plans. Ironically, one of the primary hindrances to greater patient involvement is technology. Engagement beyond the office setting requires the willingness and ability of patients to transmit health information back and forth with their providers through some electronic medium.

For these interactions to be successful, however, technology tools need to be familiar, user-friendly, and convenient. And organizations need a mechanism for receiving that information and integrating it with their EHR platforms to ensure that the data has meaning and applicability.

Personal health-monitoring apps stand at the intersection of these patient and provider needs. Apple’s HealthKit, for example, offers patients a familiar name and ease of use, with technology embedded in devices (e.g., phones or watches) that patients may already be using to manage their health.  As mentioned in a previous article, HealthKit has already been piloted at several industry-leading healthcare organizations with major EHR vendors.

What should we be doing now?

For most health systems or physician practices, funneling resources into managing the integration between their EHR and apps such as HealthKit may be premature.  The availability of the data itself doesn’t automatically ensure improved patient outcomes, especially without the knowledge and/or processes in place to synthesize and translate this information into optimal patient care plans. Before sifting through the potential benefits and complexities of collecting so much health information, organizational leadership likely have a few important questions.

1. How can we use this data to better care for our patients? Personal medical data (e.g., vital signs, exercise habits, dietary patterns) could be accessible autonomously through personal health-monitoring apps, giving providers a more complete picture of their patients’ health. This is especially important for the management of chronic diseases – as of 2012, over half of all adults struggle with at least one chronic disease, and 7 of the top 10 causes of death were due to chronic disease, meaning improvements to treatment regimens have the potential to make a big impact.

2. How can this data save us money? Roughly 78% of private insurance and 80% of government-sponsored insurance dollars are spent managing chronic conditions, with that number expected to increase in the coming years. As many organizations shift toward value-based care, they can reap significant savings by implementing focused and proactive efforts using personal health maintenance data to better manage these conditions.

3. What data do we need for the programs we are already participating in? Meaningful Use participants, Patient-Centered Medical Homes, and Accountable Care Organizations all rely on solid data and patient engagement.  Integrating with personal health-monitoring apps could (and/or should) already be a part of your “big data” strategy based on current program participation.

Proactively managing treatments based on personal health information gathered remotely is poised to change how providers think about interacting with patients. In the case of HealthKit, initial reports look promising. Pilot programs have been expanded into additional areas, and Apple recently unveiled a clinical research-focused addition, ResearchKit. If these initiatives continue to yield positive results, other organizations and vendors will surely look for opportunities to engage with patients through personal devices.

This entry was posted in Data Analysis, EHR, EHR/EMR, EMR, Healthcare IT, Information Systems & Technology, Patient Engagement and tagged , , , , , , by Jennifer Bendfeldt. Bookmark the permalink.

About Jennifer Bendfeldt

Jennifer works in ECG’s Healthcare IT practice. With over 7 years of experience in the healthcare industry, she helps clients address operational, technical, and strategic issues associated with the implementation, utilization, and optimization of EHRs. Her expertise in-cludes team and project management, as well as needs assessments; work flow redesign; EHR incentive programs; and IT-driven improvements in clinic operations, the revenue cycle, and the quality of patient care. Prior to joining ECG, Jennifer started out her career working as a Nutritionist at the Nebraska Heart Institute in Lincoln, Nebraska, before taking on a healthcare administration internship and later becoming an EHR Analyst at Tufts Medical Center in Boston, Massachusetts. Jennifer has a bachelor of science degree in nutrition science/dietetics, with a minor in psychology, from the University of Nebraska-Lincoln and a master of healthcare administration degree from the Sawyer Business School at Suffolk University.

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