Emerging technologies and healthcare: quantum computing and blockchain
Quantum computing
First off, I am the furthest thing from a qualified quantum computing expert…but that’s why the internet is a fantastic place. After receiving my first intro to this topic in my Digital Literacy class at Columbia Business School, I’ve been curious about how quantum computing can disrupt the world of healthcare. Here’s a brief case study on the recent IBM / Cleveland Clinic partnership where IBM is installing its first private-sector, on premises quantum computing system in the US.
The partnership will focus on the research and clinical infrastructure to accelerate and enhance research capabilities across big data to advance patient care and improve population health. The quantum computer will be installed in the clinic’s Global Center for Pathogen and Human Health and will be intended to engage with universities, government, and industry, among other organizations.
According to IBM, potential opportunities within healthcare cover various aspects of the value chain, including diagnostic assistance, precision medicine, and pricing.
Diagnostic assistance
The timelier and more accurate a diagnosis, the lower the overall cost of care and better the outcomes. As imaging techniques like CT scans, MRIs, and X-rays remain the standard of care for diagnostics, there is opportunity to enhance these processes as many images are impacted by various factors like resolution and low replicability. Quantum computing — through the use of edge detection and image matching — can enhance the diagnostic analysis of these images.
Precision medicine
As recent studies suggest, medical care only has a 20% impact on patient outcomes vs more holistic factors (socioeconomic, environmental, etc) that carry the other 80%. With this data coming to light, there has been a significant push on moving care plan models away from this “one-size-fits-all” approach. Quantum-enhanced machine learning techniques can use large, comprehensive data sets to both predict the risk of future disease and the efficacy of potential treatments.
Pricing
While health plans have made considerable progress in determining insurance premiums, there still remains opportunity to create more accurate models in assessing complex factors like population health levels, interdependencies, and dynamic risk levels. Similar to how quantum computing can individually predict risk and treatment success for precision medicine, the same concept can be used on a population-level. Thus, payers would be able to improve their risk position and overall pricing models.
As quantum computing is currently a very exclusive capability within healthcare, the full extent of its disruptive impact in the near term is unknown, but as the technology becomes more ubiquitous and accessible, the disruptive use of big data sets can benefit stakeholders throughout the industry.
Blockchain and healthcare
A recent talk given from Amy Wu (FTX Ventures) in my class highlighted just how early society is in adopting blockchain technology, especially in less obvious sectors, such as healthcare. Her argument inspired me to dig a bit deeper into some of the most immediate and feasible solutions that have the potential to permeate the industry. Here are four tangible opportunities and examples:
Supply chain
According to WHO, 10% of available medicines around the world are counterfeit, with some developing countries having rates as high as 50%. And as counterfeiting technologies continue to advance — along with the complexity of pharmaceutical supply chains — so does the risk of being exploited by illegitimate wholesalers, distributors, and internet pharmacies.
Blockchain would enable stakeholders to verify the authenticity of medicine across the pharmaceutical supply chain. With a shared data platform that would record the transaction of drugs among legitimate stakeholders in the supply chain, blockchain would provide an opportunity to track and identify authentic medicines as they travel through the supply chain and to the patient.
Decentralized clinical trials
The clinical trial landscape is extraordinarily complex and has consistently been hindered by patient enrollment and data concerns that have limited improvement in transparency and efficiency.
A particularly compelling use case for blockchain is how it can be used to administer decentralized clinical trials, extending clinical trials’ reach to under-developed countries by eliminating data integrity concerns. In this model, patients and healthcare providers can record data directly onto the blockchain, which can be be viewed in real-time by clinicians across the world. There is significantly less distrust in the data as it is not being exchanged by several hands before reaching the sponsor.
Data interoperability
From trying to manage inconsistent data across multiple sources, to validating requests, and navigating archaic hospital data infrastructure, data interoperability is a nightmare. Despite these significant challenges, mastering interoperability would advance the healthcare system to new heights, improving quality of care and lowering unnecessary utilization.
For many of the already stated reasons, blockchain technology can be used to create a decentralized ledger of electronic health records. This secure aggregation of data would allow a patient, and every single provider they come in contact with, to have full access to their entire medical history.
While blockchain does present these exciting opportunities to progress the industry, it’s not without its fair share of headwinds. For example, the negative perception of blockchain from other industries can deter healthcare traction, a high level of technical expertise could be required to implement and manage these solutions, and much uncertainty remains regarding future regulatory complexities.
References:
· https://www.ibm.com/downloads/cas/8QDGKDZJ
· https://www.ajpmonline.org/article/S0749-3797(15)00514-0/fulltext
