The Tangle on FHIR

The full article was originally published by Sebastian Fuhrhop on Medium. Read the full article here.

Developing an open source DLT layer for healthcare data exchange

Introduction

“It’s 2040. I’m 80 years old and fully able to manage my own health. We finally have the secure information infrastructure that allows us to collect, analyze and compare our health and behavioral data ourselves.” [1]

Unfortunately, the reality of today is that there are still significant barriers in exchanging healthcare information between different sources (hospitals, insurance, wearables devices, etc.), which may delay providers’ decision-making ability, prevent patients from having a more engaged role in their health and leading to higher costs.

In the USA, a 2017 study showed that c. 60% of the assessed hospitals were not able to find, send, receive and integrate electronic patient information from outside care providers [2]. Additionally, in almost 40% of the cases where information was exchanged, it was a challenge to match or identify the correct patient between systems [3]. The situation is not much different in Europe, where only a limited number of citizens were shown to have online access to their healthcare records, and the percentage of hospitals exchanging healthcare records electronically was shown to be stubbornly low (e.g. only 39% of hospitals exchange information electronically within the same country, and only 4% of hospitals exchange information with hospitals in other countries) [3].

The purpose of this article is, therefore, to introduce a new approach for healthcare data exchange, by making use of the decentralized and therefore always available nature of DLT.

Benefits of achieving this interoperable healthcare data exchange [3] include:

  • Strengthened care coordination — by having real-time access to patient data, providers, patients and caregivers can collaborate and make joint care decisions
  • Improved safety and quality — interoperable patient data helps to avoid duplicate tests and conflicting medications, which ultimately translates into better and safer care
  • Increased efficiency and reduced costs — information sharing saves clinical and administrative time as well as reduces repeated exams, which ultimately reduces costs for patients, providers, and insurers
  • Robust public health registries and research data — anonymized aggregated patient health information will allow for faster monitoring of public disease threats and to support in advanced research

Why DLT?

One could argue that the described problem could be addressed with a centralized database architecture. Several initiatives such as healthcare information exchanges (HIEs), middleware providers and patient portals, have shown that that is true.

However, for certain use cases, the DLT approach presents advantages over the centralized approach due to:

  1. by nature, it enables patients to own and manage access to their data (as only they are in control of encryption keys)
  2. it removes the need to trust a single authority with one’s data, by inverting data ownership dependencies
  3. it opens the room for innovation and for a broader spectrum of healthcare applications to be deployed since the consequence of 1 and 2 is the removal of data silos, potentially making healthcare more patient-centric

Why IOTA?

One of the most well-known advantages of IOTA is its feeless nature. In combination with MAM (a second layer protocol for IOTA), this allows for free data exchange.

The feeless nature of IOTA is particular useful in those cases requiring continuous/high volume data exchange. In healthcare, this would be represented by the Internet of Medical Things (IoMT) space, where millions of devices (e.g., wearables, mhealth apps, etc.) currently generate continuous data streams. Since providers do not have the time to analyze this raw data, analytics tools need to be developed that develop digestible insights. Advancements in this data analytics space is therefore highly dependent on the fluidity and exchange of device generated data.

FHIR — A healthcare standard

In healthcare, one key requirement for the adoption of new technologies is interoperability with older systems in place. For this reason, we have chosen Fast Healthcare Interoperability Resources (FHIR) as the underlying exchange protocol for healthcare data.

This allows integration into existing systems by facilitating the JSON or XML API functionalities that are specified within the FHIR spectrum.

Besides interoperability, FHIR has other benefits that let it stand out as a healthcare standard, such as versioning (different versions of FHIR can co-exist in a system) or the strict usage of web standards [4].

Pact FHIR

As part of our Untangle Care project [5] our goal is to build a solution that enables for patient-generated health data to be exchanged fluidly and freely with the rest of the healthcare ecosystem (doctors, insurance, caregivers, etc.), while still keeping patients in control of its ownership and access. We are therefore developing a FHIR compliant system [6], which allows data-generating applications (e.g. connected devices, mHealth apps, etc.) to work with FHIR resources, exchanged on the Tangle via MAM.

This system is divided in three parts, which we explain further in the following passages.

Core Layer

The core layer [7] reflects most of the FHIR API level interactions as specified in the FHIR documentation [8].

It implements interactions as use cases and defines an interface for the FHIR data source (decoupled from IOTA). Implementing the interface allows us to work with different data sources, thus making the system more flexible and integrable with existing FHIR data sources.

Iota Implementation Layer

The IOTA layer [9] comes with an implementation of the FHIR data source interface. Internally it uses MAM to manage FHIR resources and defines interfaces that need to be implemented in order to work in a stateful environment.

Read the full Article

The full article was originally published by Sebastian Fuhrhop on Medium, where people are continuing the conversation by highlighting and responding to this story.

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