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Healthcare Data “Golden Record” Becoming Reality

  • Impact of technology and data disruption to healthcare continues to grow and expand

  • Delays in adopting innovation are both cultural and related to challenges in managing data

  • Health data is siloed across multiple sources e.g. EHR, wearable, digital and other sources; a central record is needed to create effective action and change

  • Case Study: The patient-centered data set, or “golden record”, is becoming a reality

Evolve, or Disrupt, Either Way Healthcare is Changing

There are essentially four ways I see healthcare either evolving or being disrupted by technology and data. These are personalized wellness and access interactions, clinical education and enhancement through artificial intelligence, biologic advancements, and automation.

  1. Personal Wellness and Access – Tracking and informing on healthier behaviors, encouraging health through mobile health and digital health applications, that also provide health monitoring and information, encouragement/coaching, and convenient access (e.g. telehealth)

  2. Clinical Education and Efficiency – Broader awareness of evidence-based medicine, supported by machine Learning / artificial intelligence based algorithms that accelerate clinical decision making, and establish quality of delivery benchmarks. These algorithms are also being applied to improve predictive staffing loads/resources needed with targeted workflows and teaming recommendations that optimize use of resources, support care coordination efforts and track fraud, waste (over-utilized services), and abuse.

  3. Scientific Innovations – Clinical / bio-scientific innovations such as virtual reality, which provides location-agnostic therapy (pain, psychological, stress, stress management, physical activity), 3D printing emerging as cost-effective organ replacement, robotic DME in surgical care, and genetics-based personalized medicine/pharmacological solutions.

  4. Administrative Automation – Reducing costs through automating and reforming certain administrative and procurement processes, such as predictive modeling assistance with target pending on medical equipment, or automating complex processes such as revenue cycle/invoicing or credentialing.

Seems we are talking a lot about how these advancements will impact the industry, but progress seems very slow. Maybe its impatience, but what is taking so long for change that everyone appears to desire?

What’s Taking So Long

There are many issues that slow the realization of the healthcare future state, and these have not changed much over the past decade. The three challenges, among the many others, that dominate physician and hospital leadership concerns, appear to be:

  1. Cultural support for change, i.e. not in a dictated manner, but fundamentally led by an aligned physician community

  2. Having the technology and associated competencies to support the change

  3. Data, in all matters related to it, including collection, standardization, validation/reconciliation, analysis, and reporting actionable insights.

Changing culture in health-related entities is notoriously difficult, given historical biases and working relationships of the various stakeholders. The changes being attempted, such as shifting to patient centric care, is hard to envision and communicate. Many processes, roles and responsibilities change in the shift from a healthcare paradigm that is hospital-centric and disease state oriented to a community based, personalized basis. This impacts care delivery, insurance plan design, as well as public policy.

The shift implies patient-based episode care delivery is not the only focus, but that a more empathetic, holistic approach is used that incorporates information about the person, and the community at large. This redefines “healthcare” to imply the “health” of the community and the “care” it needs, whether better access to food, remediated mold from leaky pipes, or coordinated clinical approaches that reduce complications and readmissions for poly-chronic patients. Hospitals and physicians are starting to coordinate with others, breaking down traditional communication and information-sharing silos. Changes in regulations to facilitate information sharing are also emerging.

While changing culture, there is a need to determine an overall strategy related to use of capital and human resources to build or implement technology-based solutions. Setting these priorities though largely hinges on the availability of data to act on, creating an ROI of sorts that supports and justifies the expense associated with the investment in people and tools.

The technology issue has evolved post-Meaningful Use digitizing of the basic building blocks of care delivery, i.e. electronic medical records(EMR/EHR) and clinical data registries. The goal now is to augment these platforms with data collected from mobile health and digital health technologies to create population health based care management programs and interoperability that facilitates better care decision making. We are now collecting data such as steps taken, calories consumed, our mood, our commuting distances, heart rates, blood sugar levels...basically moving from an environment of paper and fax machines, and data measured in terabytes annually, to a world where the data pipeline we need to manage and monitor contains exabytes daily.

I have previously discussed the need for a comprehensive data and health IT strategy (Is Your Vision for Innovation in Health Technology A Reality or Pixie Dust, ). Developing the data strategy is critical, as recently discussed in the article “Developing Quality Measures to Succeed in Valuebased Care” on ( It is critical to have physician buy-in regarding the data to be collected and used for outcomes measurement, for care delivery, for patient engagement, etc. Collecting the agreed-upon data and structuring it though must be done with an eye toward creating meaningful and actionable insights, to avoid both drowning in a data tidal wave as well as over-analysis or “alert fatigue” that Dr. John Lee, CMIO at Edward Hospital discussed in the Provider Symposium at the Health 2.0 conference. A recent survey published by SCIO Analytics pointed out that Integrating financial and clinical data, incorporating external and/or unstructured data, and data accuracy were top data related concerns among healthcare executives they polled.

Case Study – Achieving the “Golden Record” in Health Data

One of the vendors in this space, Faichi, has been helping clients in the US and England solve this data issue, from data collection and migration as well as data structure for business intelligence and support of analytics. Recently, the Faichi team has been assisting a mid-size hospital ranked in the “Top 100 Best Hospitals” in Becker’s Hospital Review to address what management saw as a major challenge to their ability to continue delivering clinical excellence in the future; their data is insufficient.

The hospital system’s data challenges stemmed from numerous acquisitions of smaller hospitals over the past several years, none of which with a similar EHR implementations. This was a baseline challenge to create a technology platform that would not only have consolidated information but also enable digital health and population health care management strategies in the future. Management recognized that the healthcare system they initially were planning for has evolved and new data systems were needed given the disruption implied by advances in digital health and mobile-health. They envision a future state where patients are enabled to create and manage their own health “data lake.” Being able to incorporate and respond to patients that bring their own data and develop effective and value-based care programs that improve on outcomes and patient care would be impossible given their existing patch-quilt of data infrastructure.

Hospital executive leadership identified a need for new technology (versus a build-it approach) that could address their data-related concerns. The approach has been to establish proof-of-concept with an initial, small-scale use case and then gradually scale the solution system-wide. The benefits of the phased roll-out included avoiding sticker-shock without understanding the ROI of the investment, and then being able to gain acceptance by generating results that illustrated the value of the investment that also had minimal internal infrastructure and resource involvement.

With Faichi, management was able to implement a flexible and scalable solution that consolidated their data from disparate sources, and also established capability to manage and merge “white space” data that came from other sources with minimal internal IT efforts. These other data sources include disparate sources like personal wellness and/or clinical data from devices, claims data, other third party tools, and unstructured social media data. Faichi has termed this collected data “the golden record,” illustrated below.

Fig1: Technology schematic illustrating access to information considered essential to drive personalized care and population health initiatives

Tejas Deshmukh of Faichi says, “The solution has the ability to ingest data supporting multiple formats, and consolidate this data into usable business information. In a true sense it is a digital-enablement platform.”

The technology is designed around suspect matching, duplicate record identification, and normalizing data. Hospital management is looking to use the resulting normalized data set to support data sharing and data analysis (especially predictive and deep learning techniques) to accelerate clinical teaming within Population Health Management and other patient-focused initiatives. They are also leveraging the consolidated data platform to establish data sharing and analysis supporting Clinical decision support systems across their enterprise, and establish baseline capabilities and data analysis associated with performance tracking and reporting under Value Based Care programs.

Management was also very concerned with the security protocols associated with this data aggregation. Says Mr. Deshmukh, “We have addressed the security issue by leveraging REST API’s for all data exchange, which are encrypted and decrypted at the source. And while the Faichi solution is cloud enabled and uses AWS, it can be also hosted on the clients’ IT environment for in-premise types of implementation.”


The technology and data related innovations sweeping across the healthcare industry are driving significant efforts that both evolve as well as disrupt the way care is considered as well as delivered. The changes are substantial, both in terms of how we interact with the healthcare system as well as in terms of how we define “health” and “care.” We are all being impacted by these innovations and disruptions, from how aware we are of and manage our personal wellness, to how effective the clinical services we receive are given emerging technology and research. The example of the Midwest hospital taking on the fundamental issue of data infrastructure is an indication of both the willingness to change as well as acknowledgement of the cultural and financial challenges that change implies. I feel we are making strides, despite the challenges, and are moving in the right direction. The winners among care givers and vendors alike will be those that purposefully address both the cultural and the data issues.

I want your reaction and perspectives. On twitter @ShiftHealthcare or send me an email here.

About Faichi:

Faichi Solutions is an IT Services Company specialized in healthcare product development. Operating out of Sunnyvale CA, Faichi has worked on 40+ products and 70+ mobile + web applications, working with ISVs across their product roadmap (ideation to sustenance). Shoot your IT related questions to

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