In April 2022, ExamOne and Sikka.ai introduced a collaboration to offer oral healthcare data by HealthPiQture. Sikka just lately revealed a whitepaper on the usage of Sikka Well being Indicators™ to establish well being dangers amongst insurance coverage candidates.

Sikka Well being Indicators whitepaper

Establish pre-existing well being circumstances from dental medical notes

Sikka.ai is the main API Platform within the retail healthcare trade that features opt-in dentistry, veterinary, audiology, optometry, chiropractic, orthodontics, oral surgical procedure, and different medical practices. Sikka.ai API Platform seamlessly connects to 96% of the retail healthcare market all through the US and is processing billions of transactions a day. Sikka.ai API Platform supplies the platform to assist practices optimize their enterprise, profitability, affected person communication, income cycle administration, affected person satisfaction, and affected person medical historical past evaluation, by enabling over 50 market purposes on its platform.

Sikka has over 41,000 opt-in dental practices put in within the US and Canada by its market-leading API integration platform. Sikka leverages this wealthy dataset to find out if life insurance coverage candidates have 1or extra of 10 pre-existing circumstances or habits with outsized influence on underwriting.  These indicators are primarily based on precise medical notes from the licensed suppliers within the practices or affected person reported circumstances on well being historical past varieties.  Sikka’s oral healthcare indicators may also help decide the suitable threat class or adjustment primarily based on the applicant’s well being threat indicators. This may also help make sure that “much less dangerous” life insurance coverage policyholders don’t find yourself subsidizing “dangerous” ones, no matter whether or not or not circumstances are mischaracterized by accident or deliberately.

10 Sikka Well being Indicators

Textual content Classification Mannequin

From Sikka’s huge database, sufferers with medical notes that include particular key phrases are recognized for every well being indicator. These medical notes had been preprocessed utilizing numerous NLP preprocessing methods. The Word2vec algorithm was used to generate a distributed illustration of phrases from medical notes as numerical vectors, capturing the semantics and relationships between phrases.

The embedded phrase was fed into the Lengthy Brief Time period Reminiscence (LSTM) mannequin Determine 2, which is a kind of recurrent neural community able to studying order dependence in sequence prediction issues. The LSTM mannequin is efficient in memorizing essential data and, not like conventional classification algorithms, LSTM can use a a number of phrase string to search out out the category to which it belongs. The LSTM mannequin was educated on a 400,000 balanced dataset with an accuracy of 99%.

As a part of enhancing the textual content categorization, a guidelines engine was developed to include any incorrect classifications discovered within the retrospective research.

Retrospective Research and Hit price

Sikka’s knowledge has been validated in research carried out by 3 main reinsurance corporations, 3 main knowledge suppliers, a number of carriers and MGAs in each the US and Canada, and a number one life settlement firm. These research vary from a choose 2,500 to an expansive 8,000,000 data and have match charges of as much as 54%. The tobacco indicator has recognized important numbers of “smoking non-disclosers” that value carriers as a lot as $23,000¹ per conventional time period policyholder in misplaced premiums as a consequence of misclassification, primarily based on the evaluation of 1 of the info suppliers³. Individually Sikka Indicators are actually in manufacturing with a number of carriers and have been useful at figuring out lacking underlying circumstances that affect underwriting.  Research of Sikka’s Tobacco indicators have been accomplished to establish gross protecting worth of virtually 10x the fee.² In 2019, Munich Re carried out a validation of Sikka’s Tobacco Rating utilizing insured data. Analysis confirms that details about dental well being will be informative about general well being. Munich Re recommends every service carry out a retrospective research to finest assess the worth and software of the Sikka Tobacco Rating on its company-specific insured inhabitants.³

Upcoming webinar

Be part of Sikka and ExamOne for a captivating and well timed webinar dialogue with prime trade panelists on the best way to leverage oral healthcare knowledge successfully for all times underwriting.

Register for our upcoming webinar on March 23, 2023.

1 https://www.verisk.com/siteassets/toprisks/how-audio-analytics-can-detect-undisclosed-tobacco-use-verisk-whitepaper.pdf

2 ExamOne Price Profit Evaluation, June, 2021, Brian Lanzrath

3 https://www.munichre.com/us-life/en/views/alternatives-for-stratifying-mortality-risk/oral-health-mortality-and-smoker-detection.html