Single-Use Health Data: A Byproduct of a Fragmented Ecosystem

Single-Use Health Data: A Byproduct of a Fragmented Ecosystem

In the complex landscape of American healthcare, a silent crisis is unfolding that demands a new term to describe it. I propose the term "single-use health data" to describe the health measurements and metrics that individuals generate constantly—daily, hourly, or even by the minute—that serve only one immediate purpose before being discarded. This widespread practice isn't just a missed opportunity; it represents a fundamental flaw in how we manage health information. By failing to properly utilize this data, we're overlooking its potential to improve both individual care and public health outcomes.

Defining Single-Use Health Data

Single-use health data refers to discrete health-related data points generated by consumers through various digital platforms, wearable devices, and applications that:

  1. Are collected for a specific, limited purpose
  2. Serve only a singular function in isolation from other health metrics
  3. Lack integration into comprehensive health records or longitudinal analysis
  4. Become effectively inaccessible or unutilized by a consumer after their initial purpose is fulfilled
  5. Represent potentially valuable health insights that remain underutilized in the broader healthcare ecosystem

This phenomenon creates a "digital health shadow" where consumers continuously generate health-related information that, despite its potential aggregate value, exists in fragmented silos and fails to contribute to a holistic understanding of individual or population health.

The Fragmentation Problem

The U.S. healthcare system operates as a fragmented network of private providers, insurance companies, pharmaceutical firms, digital health startups, and government agencies. Each entity collects, stores, and utilizes health data in isolated systems. This fragmentation creates information silos where valuable health insights become trapped, inaccessible to other stakeholders who could benefit from them.

The impact of this fragmentation is substantial. According to a 2021 McKinsey study, 50 to 75 percent of healthcare waste could be eliminated through better utilization of data. This represents $500 billion to $750 billion in potential cost reductions for the U.S. healthcare system alone.

Consider a typical patient journey: blood pressure readings at a primary care office, medication history at a pharmacy, insurance claims with one company, fitness data on a wearable device, and nutrition information in a meal-tracking app. Despite all representing aspects of the same person's health, these data points rarely converge to create a comprehensive health picture.

Undermining Comprehensive Health Records

The concept behind Electronic Health Records (EHRs) and Personal Health Records (PHRs) was revolutionary—creating comprehensive, longitudinal views of an individual's health across their lifetime. This vision promised improved care coordination, reduced medical errors, enhanced preventive care, and more empowered patients.

However, the reality has fallen short of this promise. EHRs have largely become digital file cabinets within individual health systems rather than interconnected repositories of patient information. The proliferation of single-use health data points directly undermines this foundational goal by perpetuating fragmentation rather than integration.

The Quiz Conundrum: A Case Study in Waste

The ubiquitous online health quiz perfectly illustrates the wastefulness of single-use health data. Across the internet, these questionnaires collect detailed health information—sleep patterns, stress levels, dietary habits, symptom histories—ostensibly to help consumers find personalized products or services.

With 58.5% of U.S. adults using the internet for health information, the scale of this data generation is significant. Yet after serving its immediate purpose of generating a recommendation, this valuable health information rarely benefits the individual again. While companies extract value through analytics and marketing optimization, this represents a one-sided exchange. The consumer's health profile—potentially valuable for clinical care—remains isolated in a proprietary database, inaccessible to both the individual who provided it and healthcare providers who could use it to deliver better care.

This pattern repeats across countless digital health touchpoints, from symptom checkers to wellness apps. Each creates isolated fragments of health information that remain stranded in digital islands, with most consumer health apps falling outside HIPAA regulations, further blocking integration with clinical systems.

The Cost of Digital Waste

The consequences of this data fragmentation extend far beyond inefficiency and are well-documented in healthcare research:

  1. Incomplete care and redundant testing: Physicians make treatment recommendations without access to the full spectrum of patient health information, leading to preventable hospitalizations and medical errors.
  2. Missed patterns and patient burden: Important health trends that might be apparent when viewing aggregated data remain invisible when information is scattered. Individuals must repeatedly provide the same information across different healthcare settings, creating frustration and increasing the risk of inconsistent reporting. A 2012 study found that missing or fragmented health data can bias clinical algorithms and research, leading to suboptimal care.
  3. Unrealized AI potential: Perhaps the most significant opportunity cost is the inability to leverage artificial intelligence and machine learning tools to their full potential. These technologies thrive on comprehensive, longitudinal datasets that allow them to identify subtle patterns and predict health outcomes. With data trapped in disconnected silos, AI applications are limited to narrow use cases rather than transformative insights across the full patient journey. The fragmentation of health data means that even the most sophisticated AI tools can only see partial pictures of patient health, severely limiting their ability to generate meaningful, personalized recommendations or identify population-level trends that could revolutionize preventive care and treatment protocols.

Toward a More Integrated Future

Addressing the single-use health data problem requires systemic changes to how we collect, store, and share health information:

  • Interoperability standards and governance: Strengthening technical standards that enable secure health information exchange. The 21st Century Cures Act mandates improved interoperability, while FHIR (Fast Healthcare Interoperability Resources) provides a technical foundation, though adoption remains inconsistent. Key initiatives like TEFCA (Trusted Exchange Framework and Common Agreement) offer hope as a nationwide governance approach for secure health information exchange. If fully implemented, TEFCA could provide the infrastructure needed to unlock health data from siloed environments and enable true interoperability at scale.
  • Patient ownership and value-based incentives: Empowering individuals with greater control over their health data while realigning payment models to reward care coordination and data sharing. Current fee-for-service models often discourage collaboration, making financial incentives a critical lever for change. Emerging personal health record systems are beginning to address ownership challenges, though technical complexity remains a barrier.
  • Privacy frameworks and consumer awareness: Developing data protection approaches that balance security with information exchange benefits, while educating the public about their health data's value. As breach incidents rise, more sophisticated consent and governance approaches are needed, alongside consumer education about the benefits of greater data connectivity.


The wasteful cycle of single-use health data represents a significant missed opportunity in American healthcare. By addressing the fragmentation that creates and perpetuates this problem, we can move closer to the original vision of truly comprehensive, longitudinal health records that improve outcomes and patient experiences while reducing unnecessary costs and inefficiencies.

As healthcare data continues its exponential grow, the imperative to address fragmentation becomes even more urgent. Each isolated data point represents not just technical waste but potentially meaningful health insights that could improve individual care and advance population health.

Only by evolving beyond our current fragmented ecosystem can we transform the scattered fragments of health information into a cohesive mosaic that accurately reflects the complex reality of human health and fulfills the promise of data-driven healthcare.


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