Using AI to identify the best healthcare provider for injured workers
In workers’ compensation cases, selecting the right doctor — particularly in a complex claim such as a back injury or head trauma — can have a significant impact on the successful treatment of injured employees as well as on claims costs.
Because of these differences in quality, insurance companies usually determine the eligible physicians for patients. Until recently, this selection process had to rely on a traditional statistical approach. These models tended to require a significant number of claims per doctor as well as a thorough manual review of mountains of paperwork to yield any meaningful assessment.
Cross-referencing physicians with insurance claims data
The San Francisco-based company Grand Rounds is a pioneer service provider in this field, operating successfully at the crossroads of the technology and health insurance industry. They specialise in using AI, machine learning and big data to help users find physicians who will give them accurate diagnoses the first time around, and to pair patients with experts who are qualified to offer a second opinion, if that’s what is required.
Using AI, Grand Rounds can scan a database of over 700,000 physicians – equivalent to 96 per cent of the U.S. total – and cross-reference it with insurance claims data and biographical information to rank doctors based on the quality of their work.
Doctors’ performance is measured in hundreds of different categories, including mortality data, re-admission, complication rates, claims duration, medical expenses, and return-to-work rates. The algorithm also takes into account where the physicians did their training, which other experts they trained with and how often they perform tests and procedures. This data is compiled and used to assist in ranking medical providers into different tiers.
Identifying risk: Why do rankings work?
In general, the best doctors tend to take a more complete approach to medical care. They consider all aspects of an injured worker’s health that might affect current performance and recovery. They’ll usually delve deeper into a patient’s medical history to ascertain whether there can be any contributing factors – such as high blood pressure, obesity or diabetes – that might impede recovery. They understand that an employee being able to return to work — even in a modified capacity — can play a crucial role in their long-term recovery process as well as in the patient’s general happiness.
In contrast, the worst doctors are often responsible for driving up the number of medical appointments, tests, and referrals. They are quicker to prescribe painkillers or other, potentially addictive, medication.
An algorithm can detect these underlying trends and find signs that there might be a risk of over-treatment rather than a focus on getting injured employees on the road to recovery. It can also identify when an injured employee’s health is deteriorating, so that medical intervention can take place before they may need to be hospitalised.
Avoiding unnecessary procedures
Similar to Grand Rounds, New-Jersey-based Hindsait uses AI and machine learning to analyse and interpret vast datasets of past and real-time medical information, including unstructured clinical notes and all kinds of medical records. It detects underlying patterns and presents that information to doctors on a self-developed software-as-a-service platform. This helps physicians streamline their workflows and to make more informed prognoses about which procedures are best for a patient. Doctors can spend more time with their patients instead of their paperwork.
AI solutions like this can ensure that insurance companies do not pay for unnecessary tests, patients can avoid the potentially painful and costly effects of unneeded procedures, and providers save time while achieving better results.
Overall, the road to recovery for many injured employees will remain a long and arduous one. However, when it comes to getting sick or injured employees the care they need, the introduction of AI is a huge leap in the right direction.