Health System Reveals Wearable Integration Hurdles
One Brooklyn Health is successfully using wearables for remote patient monitoring (RPM) for chronic conditions like diabetes and hypertension, in a partnership with Kane Health and CyberMed Health. However, a recent podcast revealed that RPM data is still monitored manually in external systems and not integrated into the hospital's Epic EHR. Care managers must proactively monitor alerts without automated messaging, though plans are in place to integrate the data via HL7 and FHIR APIs.
- The One Brooklyn Health RPM program, launched in September of the previous year, is provided at no out-of-pocket cost to patients and aims to reduce emergency room visits and hospital readmissions. - The integration of wearable data into EHRs like Epic often relies on the HL7 FHIR (Fast Healthcare Interoperability Resources) standard, which defines data structures for clinical information like observations and allows for exchange via modern web APIs. This approach is designed to be more flexible than older standards like HL7 v2, treating data as modular, queryable resources. - Consumer health apps that are used independently by consumers to track their own health information generally fall outside the scope of HIPAA regulations. However, if the app shares data with a healthcare provider (a "covered entity"), it may be considered a "business associate" and must comply with HIPAA's security and privacy rules. - Successful consumer health apps often use a "freemium" model to lower the barrier to entry, attracting users with free features before guiding them toward a paid subscription for more personalized experiences. Headspace, for example, focused its email marketing and engagement efforts on retention of paying customers rather than acquisition of free users. - Women's health app Flo, which has over 62 million monthly active users, achieved significant user growth by implementing social logins, which increased new-user sign-ups from 6% to 75% and reduced churn during onboarding. The company reached a valuation of over $1 billion, making it the first purely digital consumer women's health app to achieve unicorn status. - AI and machine learning are increasingly used to provide personalized health insights in consumer apps. For example, AI can analyze data from wearables and patient records to offer tailored treatment suggestions and lifestyle modifications for managing chronic conditions like diabetes. - Building trust with health-conscious consumers is critical and often centers on transparency and evidence-backed claims. Strategies include providing clear information on ingredient sourcing, citing scientific studies to substantiate claims, and creating educational content that empowers users to make informed decisions. - Early-stage funding in the digital health sector remains strong, with AI-driven companies attracting significant investment. Longevity-focused startups are also securing substantial funding, with notable rounds for companies focused on epigenetic reprogramming and AI-enabled drug discovery to extend healthy lifespans.
