Kinship between FinTech & HealthTech : Leverage innovations for a Value-Based HealthCare Society

Some ideas for FinTech & Health Tech startups in addressing critical consumer needs

Disclaimers: Opinions expressed in this article are solely mine not of my current or previous employers

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Being in the Payments & FinTech space, I have started to wonder where else can some of the innovations from the recent advancements could be applied. I realized that one early adopter would be HealthTech segment under gargantuan Life Sciences industry.

I have set out a few broad categories where Payment industry (largely from FinTech & Financial Services breakthroughs) can help leapfrog, and have few suggestions for HealthTech - largely towards creating a value-based healthcare model.

Identity

"All payments originated by a Payer (either consumer or individual or corporate) needs to be properly Authenticated and Authorized. Establishing Identities of all players is an important first step in FinTech/Payments/Financial Services industry"

Authentication & Authorization is a service/capability that Payments industry (FinTechs, Financial Services and Banks) has spent zillions of dollars in innovating better ways to do. Authentication mechanisms available are a large spectrum - basic passwords, step up authentications using 3DS, device bound tokens, soft tokens like OTP, bio-metric (including finger prints, retina scans), and even more advanced methods that are behavioral or contextual based (AI, Deep Learning, Machine Learning models). These services are used as part of KYC (Know Your Customer). FinTech & Payment industry had to delve deep into this problem space largely due to Legal & Compliance mandates that exist for the purpose of protecting a Consumer. Besides regulatory requirements that are payment specific like AML (which may not be the focus here) which come up if the payment scenarios includes cross border.

In HealthTech industry (technology aspects of Life Sciences), Health Insurance Portability And Accountability Act (HIPAA) in the US, and General Data Protection Regulations (GDPR) in EU or California Consumer Privacy Act (CCPA) going effective Jan 2020, provides stringent guidelines around accountability related to health data integrity, confidentiality (read PII - Personally Identifiable Information in Payments lingo - like Name, Gender, SSN, or any identities that can traced to an individual, and in future these could include DNA, biometric data, etc), and availability. Many healthcare services providers such as clinics, insurance cos, emergency medical response system, medical device manufactures for monitoring/diagnostics, as well as consumer electronic providers like Apple, FitBit and Samsung have access to lot of user data. With proliferation of devices and services providers, using advanced authentication mechanisms similarly used in FinTech will become imminent to protect a patient's identity. It would be a good idea for FinTech's to offer identity innovations through "services or APIs" for Health Care and Life Sciences industry in general for robust Authentication & Authorization needs. Startups focused on Health Tech (Digital Health) could leapfrog innovations by leveraging services offered by FinTech & Financial Services industry.

Use Case #1: Imagine you are a Medical service provider and you have to attend to a patient and want to verify identity - this scenario is similar to an online merchant or retailer had to go through when a consumer interacts for a purchase transaction. A practical and easy solution would be to leverage some of KYC (Know Your Customer) mechanisms that Financial Service providers routinely have to do for all customer interactions. A simple second factor authentication through the patient's payment Card or Bank Account could help authenticate patient's identity. This service could become critical during emergency response (ER) when patient is not very interactive with the ER personnel, and the team needs a second factor identity check. Any form of step up authentication through a Payment Instrument (like a Credit Card) that the consumer carrying or biometric scan could help. Companies like Visa have various identify verification services that are available for certified partners (check these out here). For eg, doing a "zero dollar" Auth or AVS check with a special MCC code over the card network rails could be an option. Embedding such services as part of the Digital Health platform could make these services more robust when handling a consumer. Visa also offers ALIAS service that could help retrieve a Consumer's information through their phone number.

Health care Platform services (eg. eVariant, CareCloud, ChangeHealthCare, Pivotal, Phillips HealthSuite, etc) are already offering comprehensive suite of services from Patient Onboarding, record keeping, Analytics, Payments, etc. Augmenting this layer with a comprehensive AuthN, AuthZ, Alias/Resolve services would take the patient identity verification to the next level. Accurate identification mechanisms are essential to reduce the margin of error.

Fast forward to future: A person's unique biological marker are represented in SNP (single nucleotide polymorphisms, "snips") in their DNA sequence. These SNPs or in some extreme cases like disease causing mutations, influence traits such as appearance, disease susceptibility or mental/behavioral preferences in a human. These traits are what determine an individual's identity. Key question is: Can SNPs provide a genetic fingerprint for use in identity verification? Can these be used for second factor authentication? Can a biomarker scan detect an SNP in near real time, and thereby accurately identify a Consumer and provide access to a secure financial/payment vault like a Google Wallet or Apple Wallet or PayTM wallet?

Open architectures for information dissemination

BlockChain had its roots to develop BitCoin, a non-fiat crypto currency. Over the last few years, BlockChain spun off from FinTech roots and is developing its own sense of purpose by going after distributed information sharing opportunities like Gaming, licensing, Supply Chain manufacturing, food & agriculture product distribution from farm-to-table, and even Government. BlockChain protocols are getting implemented in both - Private & Public (see here for a comprehensive comparison - talks about Private & Public in an Open/Closed context)

Needless to say, with HIPAA and other regulations like CCPA, how information is shared amongst various entities is highly regulated - for Life Science work, a Private BlockChain network makes most sense.

Use Case #2: A special needs student/individual has various service providers in the daily life - dozens of Therapists, Regional Center, School District, Psychiatrist, Psychologist, Insurance Companies, Pharmacies, Drug Manufacturers, private research institutions (like Stanford, MIND/UC Davis, and Govt Departments like DOR (Department of Rehabilitation), Social Security, Emergency responders, and Medical agencies like MediCaid, and MediCal. Add to this, these students/kids would need their information to be shared with State agencies like State Parks, and even transportation providers like Airlines on an adhoc basis. Creating a "private blockchain" could greatly help the system to become more efficient. Records become available immediately to all care givers, the family & therapists becomes more efficient - instead of searching for documents that are scattered all over. Some of the Identity services can be deployed in the Private BlockChain for HealthCare industry participants. Most importantly, Insurance industry could benefit as they would have good visibility on the patient's care. In the era of value-based healthcare, where outcomes are more important than outputs, building efficiencies in processes is an essential building block.

Advanced Analytics including Machine Learning/Deep Learning

Machine Learning and Deep Learning are applicable when there is sufficient data around an incident and its precursors - data capturing a sequence of steps. In the case of Payments & Financial services industry, fraud detection models kick-in through using learning algorithms. Data driven decision making looks for these patterns (series of data points) like how fraudsters gain access to a consumer's financial identity and perpetuate fraud. ML/DL algorithms predict if a particular transaction was actually done by the consumer or a fraudster, all based on actual consumer's "persona" and behavioral pattern, applicable within a specific context. With Bayesian models, the focus is being shifted to "WHY" thereby establishing a cause/effect pattern than pure regression/correlation. Check my notes on this.

AI/ML in HealthCare so far largely focusing on preventative medicine, drug discovery & testing, diagnosis in chronic medical situations - check this article by Forbes. Recently Google Cloud's recent foray into HealthCare to create an ability to store and retrieve data, or the news item recently when a ML algorithm was able to scan a scatter plot of EEG and was able to predict a tumor buildup more accurately than a seasoned surgeon. In the second instance, past data was used by the DL Algorithm to detect patterns in a really fast manner - sort of seconds - to detect tumor buildup. Habits such as eating patterns, food preferences, stress, bio markers like blood tests etc provide ample data around an individual's future stat - something for a ML/DL system to predict.

The similarities between these two industries is that, a set of sequence of events in a temporal manner that need to be analyzed to detect an outcome, and often there is a time sensitivity involved for a decision to be made. Most often, in payment industry, a decision to approve/decline an authorization request is done within 200-300 milliseconds. Entire global ecosystem is built to scale this processing speed. Such infrastructure is needed to provide quality healthcare in the future, especially during natural catastrophe like an epidemic outbreak, or attending to an isolated individual who needs urgent care in a rural/remote setting. Ability to host these DL/ML models in the cloud, and securely delivering to a patient who is remote, demand the same infrastructure needs like that of a payment transaction.

Closing comments - Towards a Value Based HealthCare Society

If you are in FinTech/Payments & Financial Services industry, this could be a great opportunity to start looking some problems areas in Life Sciences industry and plugin. Entire HealthCare industry is trying very hard to move to Value-based delivery model. In this model, HealthCare providers will be compensated based on patient health outcomes. With this emphasis, focus shifts to helping patients improve their health and reduce costs through efficient means. More on this topic is here. Key is measurement of health outcomes against the cost of delivering the outcomes. More importantly, reducing costs for providing service becomes a primary factor. Providers need to become more efficient in providing healthcare and performing diagnostics. The margin for error diminishes, as outcomes become more important than output. Innovations from Payments/FinTech could become a catalyst towards creating a society that is value-based.

Comments & thoughts are welcome. thanks for reading this far