Vaporware, Lack of Scale, Blown Budgets, Services Contracts, Custom Software and Point Solutions.
Written by: Trent Gavazzi
Since the HITECH Act became law in 2009, the ability to provide every American with a complete lifetime patient record (LPR)—accessible whenever and wherever they need care—has been the holy grail of healthcare. Despite the billions of dollars spent to promote the adoption of electronic health records and the surge of patient data coming from many disparate sources such as clinical research, claims, EHR, and wearables, most stakeholders still struggle to create a 360-degree view of a patient’s health with data they can trust, in a usable format.
Curating a comprehensive, longitudinal view of every patient’s healthcare journey has enormous potential to improve the quality of care, increase the efficiency of our healthcare system, and tackle skyrocketing healthcare costs. As a valuable tool for all stakeholders across the healthcare ecosystem, a trusted LPR can also enhance the patient’s journey and has wide applications across risk adjustment, care management, care coordination, population health management, data analytics, clinical trials, and medical research.
Healthcare data interoperability and data curation roadblocks persist
Interoperability is the ability of different patient data sources and applications to communicate and exchange data accurately and consistently. Many “healthcare interoperability” solutions have emerged over the last decade amidst increasing regulation to prevent information blocking and promote information exchange, such as the Cures Act and TEFCA to name a couple. Unfortunately, their focus has been only data liberation. Data liquidity and truly effective software solutions that make data usable and create an LPR have lagged. This has left the industry somewhat complacent with low quality and inconsistent patient data which has increased the total cost of ownership, hindered innovation, and has failed at decreasing the cost of care.
A few of the biggest roadblocks to making relevant patient health data accessible and usable across the healthcare ecosystem are:
- Single use case data exchange: At the heart of the problem is disparate buyers for specific use cases creating digital siloes and solutions built for those specific use cases that are unable to support a cohesive patient data strategy to support the needs of the entire organization. The most digitally advanced area for a healthcare stakeholder is largely related to some form of payment or revenue model. Unfortunately this has stunted a comprehensive vision for data across most solutions.
- Lack of internal expertise: Most healthcare organizations do not have the deep expertise or budget to efficiently or effectively ingest and organize patient data into a consumable medium for the variety of users that may need it. This results in a high total cost of ownership and a “frankenstack” architecture of home grown and vended solutions that miss expectations or fail completely.
- Data liquidity explosion: Data is being exchanged more frequently, but the quality and the usability of the data has not improved, leaving a garbage in, garbage out problem. Business units with unique needs have yet to work across departments or organizations to share in scalable solutions that can plug analytical-ready patient data into a variety of use cases.
- Data silos: Patient data lives within a vast array of sources such as labs, pharmacies, healthcare providers, health plans, patient monitoring systems, wearables, and paper files, and is not accessible by outside departments or organizations. Consequently, those who need that data to make informed decisions do not have a complete picture of the patient.
- Varying formats: Unstructured data fields, multiple coding languages, and constantly evolving formats create a situation where data cannot adequately link to other relevant pieces of information. This problem further inhibits the exchange and usefulness of patient data.
- Data quality: Patient data throughout the ecosystem remains inaccurate, out of date, inconsistent, and often not matched to the correct patient. Duplicate, conflicting, or outdated patient data from different sources can lead to poor medical decisions, missed opportunities for improving health promptly, and unnecessary care delivery.
Software-driven interoperability and data curation: 3 successful use cases
Software that delivers healthcare data interoperability by combining all aspects of each patient’s care into a comprehensive, complete patient profile will drive better medical decision-making and reduce costs. Much like the technology that makes wastewater drinkable, a scaleable modular technology platform can transform a massive lake or a handheld pitcher of patient data into useful, drinkable information. Below are 3 use cases of how modular technology can be leveraged by a spectrum of stakeholders and their unique needs:
- Use Case #1: Payvider
Concerned about the time and resources needed to ingest and aggregate direct clinical feeds from multiple sources, a large payvider (payer-provider partnership) deployed CareEvolution’s APIs and Orchestrate data persistence technology to ingest, aggregate, and enrich patient data from various sources to produce a comprehensive, up-to-date patient record.
Providers and members now have ‘real-time’ access to lab and imaging reports, medication details, claims, and clinical encounter information in their workflow. Analytically ready data streamlines performance improvement efforts and reporting. The platform also facilitates real-time acute and post-acute care tracking, generating FHIR notifications to alert the care management team upon admission or discharge to drive more efficient care coordination.
- Use Case #2: Health plan
A well-known national health plan adopted CareEvolution’s Orchestrate technology stack, which includes the Terminology and Identity APIs to create LPRs for its 46+ million members, connecting over 2,800 providers, 240 data sources, including wearable data, and 7.5 billion claims. The organization successfully leverages the platform for AI, machine learning, risk adjustment, quality program development, care management, member engagement, collaboration across benefit offerings, and clinical trials.
- Use Case #3: Patient data aggregator
Built to serve multiple patient data use cases across operational departments, this health technology company focuses solely on creating a rich network of patient data for multiple purposes across numerous markets. They needed a partner with a highly scalable API that could take multiple patient records, harmonize them, normalize code sets and medications, and make them available in multiple output formats from FHIR, CDA, to OMOP. It was also critical that their partner offer modern “software” SaaS pricing vs high historical costs associated with manual processes. They sought to eliminate costs rather than shift them to enable mass adoption of harmonized, cleansed patient data.
Building a 360 degree lifetime patient record with software at scale
Today, technological capabilities exist for healthcare organizations to achieve the level of data interoperability needed to build comprehensive, accessible, and trusted LPRs for every patient that includes claims, clinical, wearable, device, and any other important patient data.
Here are three steps to building a trusted LPR:
- Leverage existing ingestion interfaces or adopt a single, real-time data ingestion interface with prebuilt drivers to intake real-world patient data (claims, clinical, wearable, devices, SDoH, PDFs, Flat files, standard, non-standard, etc.) from different healthcare data silos to establish high quality patient matching without false positives and proven at scale.
- Implement software capable of aggregating, normalizing, and synchronizing healthcare data to support the creation of a lifetime patient record for any number of patients in real-time.
- Deploy technology that is able to produce real-time, analytics-ready patient data to the data lake and format of your choice.
CareEvolution’s Orchestrate technology stack unlocks the ability to create a LPR at scale. Orchestrate is a cloud-native full-stack platform that ingests, aggregates, cleans and organizes raw data, and it features modular self-service APIs such as:
- Terminology API to standardize and classify healthcare codes and concepts
- Convert API to transform input data from one standardized format to another
- Insight API to compute hierarchical condition category (HCC) risk scores
- Identity API to enable privacy-preserving record linking across data sources and use cases
They can be evaluated in our sandbox at rosetta.careevolution.com/register