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Healthcare trails all American industries except hospitality, construction, and agriculture in its adoption of digital technologies, according to McKinsey. Yet healthcare organizations are among the most complex enterprises in the world. That digital disparity leaves hospitals, health systems, and physician practices accountable to make high-risk decisions with untimely, incomplete, and inaccurate data. Patients, for their part, are mostly left out of a data ecosystem that could help them be more accountable and engaged in their own care. Hospital margins are shrinking, clinicians are overworked and over-measured, and healthcare systems need more and more data sources to manage risk and population health initiatives.
Traditional data warehousing, which solved some of these problems, is no longer good enough. As Gartner recently reported, traditional data warehousing will be outdated and replaced by new architectures by the end of 2018. And current applications are no longer sufficient to manage these burgeoning healthcare issues. The technology is now available to change the digital trajectory of healthcare.
A New Response to the Data-Centric Future of Healthcare
DOS is Health Catalyst’s response to a simple truth: The future of healthcare will be centered around the broad and more effective use of data.
From population health management to value-based care, healthcare providers face a quagmire of reimbursement schemes and quality initiatives, each requiring precise analysis of clinical, financial and patient data. Yet to get there, they must unravel a Gordian knot of diverse information systems that cannot communicate with each other and that separately lack the data needed to succeed. The explosion of information from wearables, mobile phones, genomics, and other sources outside the traditional healthcare sphere is exacerbating these problems while also enabling personalized healthcare and management as never before, assuming organizations can manage the transformation.
The Data Operating System: Changing The Digital Trajectory Of Healthcare
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DOS delivers significant benefits to healthcare organizations:
- Orders of magnitude faster software application development will enable applications that are tailored to specific needs, not generic requirements.
- Physicians will have more intelligent software applications that can be tuned to their preferences and optimized to their disciplines, and patients will benefit from the same data and applications with more personalized care.
- Generic, impersonal healthcare workflow and patient care will no longer be the norm.
- A new level of personalized care for both physicians and patients will finally be possible.
Clinical and financial decision support at the point of care is almost nonexistent in healthcare, restricted to a few pioneering organizations that can afford the engineering and informatics staff to implement and maintain it. With DOS, this kind of decision support is affordable and effective, raising the value of existing electronic health records and making new software applications possible.
DOS might sound ambitious, but it’s a common-sense step forward. The technology, tools, and experience already exist to make it happen, thanks in large part to Google, Facebook, Amazon, Microsoft, and Twitter. Like the Late-Binding™ technology in data warehousing, vendors are encouraged to borrow DOS™ ideas and concepts to be competitive and practical.
Six Big and Common Headaches Relieved
DOS has the power to solve extremely common problems for healthcare organizations, with a solution that:
- Enables and simplifies the upcoming tsunami of data requirements for population health and risk-based payment models. Only 8 percent of the data required for precision medicine and population health resides in today’s EHRs.
- Improves physician and care provider satisfaction by providing the right data, at the right time, in the right modality.
- Leverages legacy data warehouses without the need to replace them.
- Accelerates the benefits of mergers, acquisitions, and partnerships through rapid and granular data integration of the new organization.
- Enables Personal Health Records (PHR) for patients in an unprecedented way, including portability of the data from one care delivery system to another.
- Provides an orders-of-magnitude less expensive strategic option to “rip and replace” for integrating disparate EHRs with a single vendor solution.
Groundbreaking Attributes of the Healthcare Data Operating System
DOS is made possible not only by the enabling technologies and engineering patterns of Silicon Valley, but also by Health Catalyst’s proven success in managing healthcare data. Understanding the ins and outs of healthcare data requires years of operational experience that can only come of being deeply embedded within complex organizations. No other company in healthcare has more experience and skill in this area than Health Catalyst, whose customers care for nearly one fourth of all Americans.
The Health Catalyst analytics architecture can ingest data from over 150 different vendors of source data systems at a granular level, including claims, clinical, financial, administrative, wearables, genomic, and socio-economic data domains. Health Catalyst has a library of over 200 reusable data bindings—algorithms, value sets and metrics—and 24 healthcare-specific machine learning models, and these are expanding every day.
The seven attributes of the Data Operating System are:
- Reusable clinical and business logic: Registries, value sets, and other data logic lies on top of the raw data and can be accessed, reused, and updated through open APIs, enabling third-party application development.
- Streaming data: Near or real-time data streaming from the source all the way to the expression of that data through the DOS, supporting both transaction-level exchange of data and analytic processing.
- Integrates structured and unstructured data: Integrates text and structured data in the same environment. Eventually, incorporates images, too.
- EHR Integration (closed loop capability): The methods for expressing the knowledge in the DOS include the ability to deliver that knowledge at the point of decision-making, including back into the workflow of source systems, such as an EHR.
- Microservices architecture: In addition to abstracted data logic, open microservices APIs exist for DOS operations such as authorization, identity management, data pipeline management, and software application telemetry. These microservices are built specifically to enable third-party applications to be built on the DOS.
- Machine Learning: The DOS natively runs machine learning models and enables rapid development and utilization of these models, embedded in all applications.
- Agnostic data lake: Some or all of the DOS can be deployed over the top of any healthcare data lake. The reusable forms of logic must support different computation engines (e.g., SQL, Spark SQL, SQL on Hadoop, et al.).
The Data Operating System Is a Product of Culture
The seven attributes listed above should be used to evaluate all vendors and solutions in the healthcare data space. Every vendor should offer its technology and professional services as if selling them to family, friends, and colleagues. Health Catalyst is proud to do this with DOS and the new generation of products that utilize DOS, combined with analytic services expertise tailored specifically to each client.
Deep Learning, Artificial Intelligence and Natural Language Processing will add a layer of transformative utility to all of the aforementioned tools.
"DOS is Health Catalyst’s response to a simple truth: The future of healthcare will be centered around the broad and more effective use of data."
ReplyDeleteWell, no. At least, I certainly hope not. As patient, caregiver, and physician I hope the future of healthcare is centered around the needs of patients.
Let me add to the comment on the proper role of data. Last year, I wrote an article for The BMJ on going beyond patient-centered care to collaborative health. My assertion was that to maintain the ethical and effective doctor-patient relationship in the kind of data environment described above, the health care system AND patients needed to commit to shared information (full transparency from all sources); shared engagement (with all the new stakeholders, online and off); and shared accountability. Happy to comment more and share details.
ReplyDelete