VIDEO | Blue Cross Blue Shield of Massachusetts CDAO: AI is Still Developing in Health Care

(US and Canada) Himanshu Arora, Chief Data and Analytics Officer, Blue Cross Blue Shield of Massachusetts, speaks with Jake Dreier, HiLabs Growth and Marketing Strategy VP, in a video interview about leveraging incremental data and analytics changes that impact member experience and other concepts to consider while implementing AI, ML, and similarly advanced technologies.

Arora lists a few data and analytics situations where the organization has leveraged incremental and immediate changes to boost member experience:

1. Predicting the cases through which members experience the cost or price by analyzing and modeling the data in advance.
2. Leveraging call center or survey data to understand the where and how of cost surprises members experience.
3. Using data for counseling, guiding, and educating members when they seek help scheduling care with a provider.
4. Understanding providers’ perspectives and working out problem areas with them.

According to Arora, the more complex the care an individual seeks, the more complexity there is in advocating for that care. He believes combining clinical data and members’ health care data to predict the best health care pathways for them will bring new opportunities.

Arora shares that external consumer behavior data increasingly yields more insights for the organization than clinical data, claims/financial data, membership, and product plan data. He says the organization is looking for an end-to-end member experience by creating a 360-degree member view. 

Next, Arora emphasizes specific mandatory approaches that organizations must keep in mind while implementing AI, ML, or other health care data solutions:

1. Stay up to date with the latest developments in the AI and ML space.
2. Humbly accept the idea that the advances in the underlying technology will come from outside the industry/company.

Arora states that his organization is working toward converting problem-solving methods from hardware to proof of concepts. He points out that AI is still developing in health care, which is OK because health care is still in its early phases with AI. He cautions that health care organizations must be careful about allowing black-box AI to be the answer to everything.

In conclusion, Arora states that the most forward use of AI will happen outside health care before health care adopts the techniques. He notes that the explainability aspect regarding the usage and reliability of black-box AI in health care needs attention.

CDO magazine thanks Himanshu Arora for sharing his data and analytic insights with our global community.

See more from Himanshu Arora

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