Monthly Archives: December 2015

Expanding Your Population Health Data Foundation to Claims and Beyond


Post by Niranjan Sharma


Director of Engineering for Healthcare Analytics Platform & Applications, Caradigm

Healthcare is traditionally thought of as the care of patients by healthcare providers. Clinical data is generated during that care, and payers reimburse providers for the services rendered based on submitted claims. For providers engaging in population health, working solely with clinical data only tells part of the population health story. Most healthcare organizations are striving to derive more value and population insight by including claims and other types of data so that they can better stratify their populations, drive other analytics efforts, and improve care coordination among many activities. 

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Siloed Data Challenges

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The challenge is that it is complicated to ingest, normalize and model different types of healthcare data. Healthcare organizations often have many disparate information systems, and many work with partners who in turn also have many disparate systems. Most providers are still working towards harmonizing all of their data so they can view a single picture of their populations and make the best use of it in a timely manner to meet their clinical and financial goals.

 

Harmonize Data, Analyze & Compute

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One of Caradigm’s hallmarks as an enterprise population health company is that we are experts in healthcare data management infrastructure and processes. We help our customers remove the complexity and manual processes associated with data management through the Caradigm Intelligence Platform (CIP), an enterprise data warehouse designed specifically for healthcare. CIP enables organizations to harmonize their data, and then perform a rich array of analysis (e.g. predictive risk stratification, utilization), as well as computations on data (e.g. quality compliance, gaps in care, display last glucose results, display last PCP visit for a patient, etc.).

 

Modeling Claims Data Using Entities

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Caradigm has a proprietary methodology that structures data as specific healthcare entities. On the outer ring in the diagram above are examples of core payer entities that we can introduce with our customers. Seeing payer data organized in this fashion is often eye opening because it provides a harmonious view of the care delivered to patients. What is even more exciting is when payer data is combined with clinical and other data to show a complete picture that can then feed other integrated applications.

 

Lighting Up Applications With Payer Data

  • Risk Management Analytics
  • Accountable Care Organization compliance
  • Gaps in Care
  • Gaps in Billing
  • Network Utilization Analytics
  • LOS Analytics
  • Post-Acute Care Analytics
  • PMPM Analytics
  • In-Patient Analytics
  • ED Visit Analytics
  • Ambulatory Visit Analytics
  • Drug Utilization Analytics
  • Conditions Analytics
  • Bundled Payments Analytics
  • EMR Only Analytics
  • Claims Only Analytics
  • Harmonized Data Analytics

The beauty of a complete and reusable data asset is that it can light up all kinds of analytics applications. You can forecast clinical and financial risk, identify gaps in care, and analyze utilization or network steerage in order to uncover opportunities for financial improvement.

The amount of data available in our industry is growing exponentially. It is time for healthcare organizations to augment their ability to harness all of that data and realize more value. If you would like to discuss how your organization can harmonize its data and better leverage claims data as part of population health efforts, then please send us a note here.

FHIR Up Population Health


Post by Neal Singh


Chief Executive Officer, Caradigm

It’s a fantastic sign for the healthcare industry that the Fast Healthcare Interoperability Resources (FHIR) standard is garnering a lot of recent attention. I’ve had conversations with several CIOs who are hearing that FHIR could be the next-generation standards framework that can help innovate data sharing at their organizations. I can understand why they’re excited. EMRs have been closed systems for a long time, which creates major challenges for organizations wanting to share data between disparate systems. The challenge is even greater for organizations engaging in population health initiatives because the open sharing of data between different systems and providers is a must. Provider organizations want to learn more about FHIR because it has the potential to help overcome these interoperability challenges.

Let’s explore FHIR a little deeper. There are a few important details to know in order to understand its potential to help:

FHIR is an evolving standard

Up until September 2015, there were two active versions – DSTU1 & DSTU2. DSTU2 is the new version, but some technology vendors are still using DSTU1. HL7, the creator of FHIR, is still working on a final standard expected to be released in 2017. Once the final standard is in place, it will likely take a few years for broader adoption.

Vendor approaches vary

Solution vendors are in the early stages of developing FHIR strategies. Some EMR vendors are prototyping the use of FHIR APIs to enable read access of certain resources from patient charts. Others are working on the ability to read and write data back into systems. The types of data models that can be accessed using FHIR APIs also vary. For example, one vendor may support Patient, Allergy and Medication data models, but may not support Family History, Immunization, CareTeam or PlanofCare data models. Vendors can also vary whether they enable just read or read and write for each of the data models.

The use case is discrete data sharing

FHIR was designed for discrete data sharing, i.e., sharing of small batches of patient data. If you need to share one or two or ten bits of data, then FHIR can help. It is not intended for high volume data ingestion required for large scale aggregation.

FHIR is not the only game in town

Web services with REST-based APIs can already accomplish what FHIR seeks to achieve. Our customers don’t have to wait for FHIR, they can solve their data sharing challenges today using our rich and open web services data connectors that include role-based security controls and auditability. Caradigm has built unique applications like Knowledge Hub that can share real-time data and information from third-party applications directly within clinician workflows in their EMR. In the UK population health market, we have built mobile applications using REST-based APIs that can share patient data pulled from multiple sources to a mobile application at the point-of-care.

Caradigm fundamentally believes in open standards, data sharing, and in democratizing information to drive innovation in healthcare. That’s why we support an extensive number of data models, and have always been on the cutting edge of supporting emerging models such as NLP, unstructured models and now FHIR. We are able to engage services for FHIR API integrations, and will continue to build access to entities in the Caradigm Intelligence Platform including deeper integrations with specific EMRs. Caradigm also collaborates with other industry leaders on emerging standards by participating annually in events such as the IHE North American Connectathon Week (see this post about last year’s event). We look forward to participating in the next Connectathon in January.

Ultimately, there are many ways to approach population health, and Caradigm partners closely with our customers to understand their goals and challenges in order to help them develop strategies. We’re excited at the prospect of FHIR being part of the solution for our customers. If you’d like to discuss FHIR more and how it fits into your population health strategies, then please reach out to us here.

Go Big or Go Home: The Importance of Scale in Population Health


Post by Scott McLeod


Director of Product Marketing, Caradigm

In a recent article, “Why Dartmouth Ditched the Pioneer ACO Program”, Rene Letourneau for HealthLeaders Media described Dartmouth-Hitchcock Health System’s exit from the Pioneer ACO program. While the article notes Dartmouth’s defection was “unsurprisingly” prompted by financial concerns related to the CMS targets, it also revealed an often-overlooked factor in success or failure of accountable care initiatives—the size of the population served.

Robert A. Greene, MD, executive vice president and chief population health management officer for Dartmouth-Hitchcock, touched on this concern. “We would have to go it alone if we stayed in the program, which means our population would have been smaller, said Greene, “If we stayed in for 2015, we would have expected to owe another $3 million to $4 million.” Estimates place the size of Dartmouth-Hitchcock’s at-risk population at 23,500 lives in 2013.

As healthcare delivery organizations seek sustainability under risk contracts, they should look to the experienced health plans and insurance companies. Health payers range in size from local plans with ten thousand covered lives to national carriers covering millions. Many of those at the lower end of this scale struggle financially, and as a result, also with attaining the clinical outcomes desired for their members.

While smaller size can create a number of challenges, I will call out two—the cost of variability and critical mass for programs.

Utilization and costs of healthcare services vary from year to year. In a larger population, the overall variation is less noticeable because there is typically enough patients with lower utilization to balance those that incur higher costs. In a smaller population, a relatively small set of patients can have a negative impact on the average utilization and per capita spend. This is why insurers are concerned about adverse selection, resulting in a larger-than-desired proportion of higher-risk individuals among its members.

Population health initiatives need a certain number of patients to be sustainable. For example, focusing on preventive care targeted at high-risk diabetics requires a sufficient number of members that qualify and enroll in a program for it to be successful at the population level. Smaller payers often do not have the necessary membership. Adding to this, on the other side of the equation, is the fact that lower revenues makes it difficult to allocate resources for these programs.

In my experience working with payer organizations, the minimum size for long-term sustainability is 80,000 – 100,000 covered lives. It will be some time before a significant portion of ACOs and other at-risk organizations achieve that size. Until then, in addition to some success stories, I expect we will see more developments like those occurring at Dartmouth-Hitchcock.