In April 2022, ExamOne and Sikka.ai introduced a collaboration to supply oral healthcare info via HealthPiQture. Sikka just lately printed a whitepaper on the usage of Sikka Well being Indicators™ to determine well being dangers amongst insurance coverage candidates.
Sikka Well being Indicators whitepaper
Determine pre-existing well being situations from dental scientific notes
Sikka.ai is the main API Platform within the retail healthcare business 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 functions on its platform.
Sikka has over 41,000 opt-in dental practices put in within the US and Canada via 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 situations or habits with outsized influence on underwriting. These indicators are based mostly on precise scientific notes from the licensed suppliers within the practices or affected person reported situations on well being historical past types. Sikka’s oral healthcare indicators may help decide the suitable danger class or adjustment based mostly on the applicant’s well being danger indicators. This may help be sure that “much less dangerous” life insurance coverage policyholders don’t find yourself subsidizing “dangerous” ones, no matter whether or not or not situations are mischaracterized by chance or deliberately.
10 Sikka Well being Indicators
Textual content Classification Mannequin
From Sikka’s huge database, sufferers with scientific notes that include particular key phrases are recognized for every well being indicator. These scientific notes had been preprocessed utilizing numerous NLP preprocessing strategies. The Word2vec algorithm was used to generate a distributed illustration of phrases from scientific 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 info and, not like conventional classification algorithms, LSTM can use a a number of phrase string to seek 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 information has been validated in research carried out by 3 main reinsurance corporations, 3 main information 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 vital numbers of “smoking non-disclosers” that price carriers as a lot as $23,0001 per conventional time period policyholder in misplaced premiums attributable to misclassification, based mostly on the evaluation of 1 of the information suppliers3. Individually Sikka Indicators are actually in manufacturing with a number of carriers and have been useful at figuring out lacking underlying situations that affect underwriting. Research of Sikka’s Tobacco indicators have been accomplished to determine gross protecting worth of virtually 10x the associated 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 could be informative about total well being. Munich Re recommends every provider carry out a retrospective examine to finest assess the worth and utility of the Sikka Tobacco Rating on its company-specific insured inhabitants.3
Be a part of Sikka and ExamOne for a captivating and well timed webinar dialogue with high business panelists on the best way to leverage oral healthcare information 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 Value 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