INTEGRATED CASE AND CARE MANAGEMENT
Remove biases, eliminate human error, and work purely with hard data and algorithmic analysis to help healthcare payer companies develop more accurate, positive outcomes.
Offer personalized preventative measures depending on each patient. Combine lab visits, specialist visits, and physician notes with claims data to recognize early diagnosis patterns.
More accurate prognoses and diagnoses
Offer personalized preventative measures depending on each patient
Combine lab visits, specialist visits, and physician notes with claims data to recognize patterns for early diagnoses.
Predict chronic illnesses, such as diabetes.
Work within CT scans and genome sequencing
Our solution can help detect complicated illness patterns and help identify or even prevent rare and undiagnosed diseases. It does this by combining claims data with various medical information sources. Sometimes, the treatment for an illness is not as helpful as we would like, and can, in fact, be harmful to some patients. Our technology allows earlier detection of harmful effects through human trials that might otherwise get missed. Pattern recognition, combined with extensive claims data, helps predict and detect adverse drug reactions.
IntelliPayer can assist in:
- Improving on service monitoring
- Readmission to hospital
- On-site disease contraction
- Machine learning analysis
- Demographics, medical histories, and admission times to predict on-site risk.
As people, we are biased whether we like it or not, no matter how much we try. IntelliPayer has the potential to mitigate or even eradicate some of the more grievous biases!
Factors that play in doctor bias :
- The types of drugs they will prescribe
- Diagnoses they will make in their limited time
- Limited samples, press, or patient history
- Self-reinforcing experience
- Cognitive biases like risk aversion
- Over-confidence due to past success
We help you combat all of this by relying solely on hard facts and algorithmic analysis and it returns entirely unbiased information. Another kind of bias is omitted variable bias when it comes to specific treatments. Our solution is able to analyze every variable; even those a researcher might otherwise overlook.
In short, using IntelliPayer serves to improve patient and client experience, as well as the experience of insurance companies.
By erasing biases, removing human error, and working purely with hard data and algorithmic analysis, we can help usher the world of healthcare insurance into a more accurate, more positive age for all.