There is a common fallacy that every new technology that skitters across the healthcare plain will have an earth-shattering, and short-term, positive impact on the healthcare system writ large.

June 10, 2019

When attending the Health Information Management Systems Society’s (HIMSS) annual meeting, you see a vast and growing number of service providers addressing some healthcare-technology need, whether far-reaching, niche, real, or imagined, in the healthcare space. From artificial intelligence (AI) to machine learning to blockchain to care management, the healthcare horizon is rife with new technologies.

But these solutions seldom deliver immediate applications or success. Look at IBM Watson’s highly publicized venture into the delivery of cancer-care services. Internal IBM documents showed “multiple examples of unsafe and incorrect treatment recommendations” from the Watson for Oncology system.[1] Additionally, The Wall Street Journal pointed out that “more than a dozen IBM partners and clients have halted or shrunk” Watson’s oncology-related projects.[2] In a blog post titled “Setting the Record Straight,” IBM responded to some of this media coverage by saying that it is inaccurate to suggest Watson “has not made ‘enough’ progress on bringing the benefits of AI to healthcare."[3]

Is that to say that AI, machine learning, and blockchain will not play a role in the future of healthcare? Certainly not. But it seems reasonable to expect some missteps in the short term. These and other cutting-edge technologies are needed to advance the delivery and coordination of care, squeeze costs out of “the system,” and help ensure repeatable quality-care outcomes. But few technologies are perfect.

Blockchain

Here, I do not address the obstacles to blockchain deployment in healthcare (or any other space); those can be many. However, let’s level set blockchain technology for a moment. For the purpose of this article, blockchain (utilized and actualized in the exchange of e-currencies such as Bitcoin) is a computing technology that ensures the real-time accuracy of a dataset of information. The data are stored on a series of “blocks” that are “chained” together and shared among users. The record does not require an external authority to validate the data. Instead, it uses an identified key to decrypt and then alter the database. The database is then updated, and all the users are able to see the items being managed in the dataset, such as e-currency, inventory, etc., in real time (see Figure 1 below). Without getting into the granular details of the functionality of blockchain, the important feature of this technology, as it applies to this article, is the use of a shared (or agreed upon) dataset that all constituents can see in real time.

Figure 1.

Block Chain Figure 1

With this facile definition underpinning this article, it begs a discussion of what areas in healthcare can be managed where a standard dataset exists, and multiple constituents can update the data in real time. This is a distributed ledger meaning, essentially, that all parties who need access to the same data with access to the blockchain share the same value in the chain. For instance, if there is one widget in the block, that data is shared throughout the chain, so all constituents understand that there is one widget in the block. If someone removes one widget, the ledger is updated immediately.

The hobgoblin with the application of blockchain (and other technologies) in healthcare is the massive disparity and disaggregation of data throughout the healthcare system. For far too long, the healthcare industry has been fragmented and has hobbled along with all of its gangly incongruence. For instance, different electronic medical records systems, different insurance company expectations, etc. Fast forward to today, this fragmentation of data has bred inefficiency and expense.

So, applying blockchain in a meaningful way will be a challenge in the short term. However, companies are now pouring money into blockchain technology, which may flatten the curve in terms of adoption and deployment.

Much has been made about blockchain technology and its ability to harness single-source data and adjust the master database so that other users can share a common dataset. As with many things in healthcare, we are quick to latch on to the newest and greatest and its potential applications. You cannot open a healthcare webpage without some mention of AI or blockchain. While blockchain technology may positively impact healthcare delivery, the reality is that this fix will not occur overnight.

Since blockchain requires a central repository for data that can be adjusted in near real time, its long-term applications may be vast but in the short term the massive disparity and siloed nature of the healthcare-delivery system will create more short-term impediment than rapid advance.

While the (future) potential seems boundless, top-of-mind areas for the application of blockchain in healthcare may include (and not be limited to):

  • Care delivery and coordination/electronic medical records (EMR) – Establishment of a single record for a patient that is shared (and updated in real time) among treating providers. If deployed, this could lead to a reduction in unnecessary testing, a clear and updated picture of the patient’s care, the prospect of better care management (especially in the era of “volume to value”), and a reduction in administrative inefficiency.
  • Credentialing – A single dataset of provider credentials among insurance companies so that when something changes in a doctor’s background, all constituents are updated. Quicker, more accurate, and more timely credentialing breeds efficiency in the process, expedites the addition of doctors to insurance plans, and can improve payments.
  • Supply chain – Utilizing a single data source for supply chain management would reduce errors, allow for better supply management (e.g. just in time) and inventory control, and improve accuracy. This may also apply to the prescription and management of drugs such as opioids.
  • Revenue cycle management (RCM) – Instead of being reactive (e.g., working denials, submitting appeals, etc.), a single dataset in the RCM space would (theoretically) assist in patient eligibility, quicker claims adjudication, and more efficient collections from patients (since payer and plan status eligibilities are updated in real time). RCM deployment might assist in the communication of real-time information to patients, the accuracy of claims, better management of accounts receivable, and efficiencies throughout the RCM process (e.g., claim refiling, calls to insurance companies, etc.). This application may even offer improved price transparency for consumers.
  • Health Information Exchange (HIE) – Around 2008, we heard a great deal about HIEs and how they would marry disparate EMR data into one location that could then be accessed by different groups facilitating an exchange of patient data and delivering more efficient care. Although the development of HIEs were thought to be able to share data and care through the delivery mechanics, there were issues with proprietary data, interoperability, and overall data security. What happened? As with many things in healthcare, a great deal of money was thrown at HIEs with little return. However, an HIE using EMRs and a single medical record could theoretically use blockchain to create efficiencies in the delivery of care and provide secure sharing of patient data.

I am decidedly no expert in blockchain. But after nearly 30 years in the healthcare space, I have a strong sense of how blockchain can apply to healthcare and the risks associated with premature adoption.

Am I claiming that blockchain has no place in healthcare? It should be obvious that I am not. However, all new technologies, especially apropos of healthcare, require thoughtful deployment and managed expectations. The adage “under promise, over deliver” seems appropriate. While research into applications of blockchain, AI, and other technologies should continue, these bold visions should be tempered by the practical realities of the U.S. healthcare behemoth.

This article originally appeared on Forbes.com.


  1. Healthcare IT News, August 14, 2018
  2. Daniela Hernandez and Ted Greenwald, "IBM Has a Watson Dilemma," The Wall Street Journal, August 11, 2018. 
  3. John E. Kelly III, "Watson Health: Setting the Record Straight," IBM Watson Health Perspectives, August 11, 2018. 

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