This path to more significant health instrumentation has been led by consumer applications that provide immediate insights into specific conditions (e.g., high blood pressure, blood sugar, arrhythmia, or fitness level). Downstream use of this data for machine learning is typically limited to device makers or large consumer personal health platform vendors like Apple, Google, Garmin, or Amazon.
These types of digital technology and data are making their way into provider-delivered healthcare. Within the recent wave of digital health startups, many seek to use instrumentation (e.g., wearables or motion capture via consumer devices) to improve the provision of care to patients. Though the pace of change has been slow, more traditional health providers are also beginning to embrace the expanded use of patient instrumentation and data analysis technologies.
The bottom line is that instrumentation, data collection, and machine learning represent tremendous opportunities for providers to improve their care delivery and their businesses. This use case for digital technology will ultimately find its way into every aspect of healthcare practice. One of the areas to see the early focus is a category of needs we refer to as “Movement Health.”
The term Movement Health captures a broad set of health concerns relevant to many different perspectives, including medical practice, physical therapy, sport & exercise, and occupational health & wellness. Example concerns that fit into this category include:
- Musculoskeletal (MSK) injury prevention and recovery
- Balance and mobility improvement
- Athletic performance optimization
- MSK pain management
- Traumatic brain injury diagnosis and recovery management
- Neurodegenerative disorder diagnosis & treatment
The limited availability of objective assessment data is a critical challenge to movement health practice. The situation fits the familiar “you can’t manage what you can’t measure” axiom. Indeed, diagnostic tools have been applied to movement health issues (e.g., x-rays, MRI, ECG, EEG, range-of-motion tests, and “functional tests”). However, the ability of these tools to address needs has been limited in two primary ways:
- Granularity of measurement: What aspects of movement health are being assessed, and how precisely can differences between individuals be measured? Many current assessments focus only on a narrow element of movement health and only supply coarse-grained bad/not-obviously-bad distinctions.
- Scale and reach of measurement: How many people can be assessed feasibly at high frequency? Apparatus, expertise, cost, & complexity limit the scaling of legacy assessment approaches.
What if providers had high-quality movement health metrics and associated analysis throughout the course of each patient’s care? The potential benefits are manifold:
- Better patient screening & care assignment
- Better recovery progress tracking & care adjustment
- Better care effectiveness & quality control
Movement Health Intelligence Platforms
To take advantage of this opportunity, health providers need technology platforms and applications beyond the current scheduling, billing, and EHR-focused systems they have deployed. These needs are analogous to those that drove the deployment of data-centric operational capabilities into other domains such as manufacturing, eCommerce, and finance – one key difference being that those were far less limited by a lack of instrumentation.
Consumer-driven investments in fitness-related technologies have resulted in radically improved instrumentation for movement health-related issues. Several instrumentation technologies are particularly well-suited to movement health assessment needs, notably:
- Force plates: Tests performed on force plates can provide rich and reliable data for movement health assessment. Various test protocols are available (e.g., balance and jump variations) to serve the needs of different populations and conditions of interest. Force plates can also be pragmatically deployed in a manner similar to weight scales and used with minimal training.
- Wearables: Wristband or ring-based wearables are exceptionally convenient for passively collecting activity data (e.g., exercise output, general movement, sleep) over extended periods. From wearable devices, providers can get information about what transpires between visits or checkpoints in therapy.
- Video motion capture: Video systems can capture complex movement patterns and reduce them to usable data. High-precision systems have significant setup/apparatus needs, but some basic capabilities are available via cameras on consumer phones.
This instrumentation capability, combined with available low-cost, scalable data collection, storage, and analysis technologies, provides the foundation for health intelligence platforms to be a standard tool for nearly every provider – not limited to research laboratories or the Apples and Googles of the world.