Why Healthtech Companies Are Shifting Focus to Comprehensive Patient Profiles
Washington, Wednesday, 22 July 2026.
With over eleven million Americans in coordinated care, healthtech firms are shifting from simple data exchange to comprehensive patient profiles to deliver advanced, value-based healthcare intelligence.
From Interoperability to Healthcare Intelligence
Historically, digital transformation in healthcare focused heavily on overcoming information exchange barriers. Using HL7 and FHIR standards, the industry successfully connected electronic health records (EHRs), laboratories, pharmacies, imaging centers, and payer networks [1]. However, as of July 22, 2026, the sector has largely achieved this initial phase of basic connectivity and is shifting its focus to ‘Healthcare Intelligence’ [1]. Industry experts, including those at South Plainfield, New Jersey-based Equipo Health, argue that the next competitive advantage in healthcare will not be defined by the sheer number of connected systems, but by the ability to transform those connections into meaningful, actionable insights [1].
To address this need, healthtech companies are prioritizing longitudinal patient profiles that synthesize clinical records, claims, pharmacy data, imaging, referrals, and remote monitoring into a single continuous narrative [1]. On July 21, 2026, Equipo Health announced its strategic focus on evolving from basic data interoperability to advanced longitudinal patient intelligence to support value-based care [1]. By preserving clinical context across diverse care settings, such platforms enable healthcare providers to optimize population health management, automate workflows, and monitor quality performance more effectively than traditional, siloed EHR systems allow [1].
The Economic Drivers of Accountable Care
This technological transition is accelerated by federal value-based care initiatives. The Centers for Medicare & Medicaid Services (CMS) reports that accountable care programs, such as the Medicare Shared Savings Program (MSSP), currently support coordinated care for over 11 million people across the United States [1]. For healthcare organizations and insurers managing these large populations, longitudinal data is crucial for risk management and risk adjustment optimization [1]. As clinical systems shift toward value-based outcomes, having a complete history of patient interactions becomes a financial necessity rather than a technological luxury [1].
The financial scale of this shift is reflected in the rapid expansion of the broader digital health market. The global digital health market is projected to grow from approximately $199.14 billion in 2025 to $573.53 billion by 2030 [2], representing an increase of 188.003% over the five-year period. However, as capital pours into telehealth, mobile apps, and artificial intelligence diagnostics, industry experts warn of a fundamental data quality gap [2]. Mathematically, the value of AI in healthcare is defined as the product of data quality, clinical context, and longitudinal meaning [2]. If the underlying biological data is shallow, the resulting clinical intelligence remains shallow [2].
Integrating Physiology into Longitudinal Profiles
To build truly robust healthcare intelligence, some healthtech platforms are looking beyond standard administrative and EHR data. Dr. Marcos Leal Brioschi, CEO of InfraREDMed, points out that many digital health businesses rely too heavily on basic vitals, claims, questionnaires, and medication histories, which fail to capture deep physiological dysfunction [2]. The human body expresses underlying issues through physiological signals like microcirculation, autonomic tone, thermal asymmetry, and tissue stress [2]. Incorporating medical thermography as a visual, physician-interpreted physiological data layer offers an opportunity for preventive health platforms to track inflammation, recovery, and metabolic changes over time, ultimately enriching the longitudinal record for superior clinical outcomes [1][2].