Transforming Population Health Management Systems with AI & ML

Transforming Population Health Management Systems with AI & ML

Chronic illnesses account for a shocking 75% of the $2.2 trillion spent on health care each year in the U.S. With 6 out of every 10 Americans living with a chronic condition, and 1.7 million Americans losing their lives to them annually, it is more essential now to stay ahead of chronic condition diagnoses and exacerbation. Existing population health management systems follow established practice, use ruled-based systems, assume rich patient histories and provide workflow systems for users.  But taking it to the next level would require adding the intelligent layer of Artificial Intelligence and Machine Learning.

Patients with regular interactions with the healthcare system have a rich history on which to run existing population health models.  But what about those who have a sparse history because they don’t go to regular check-ups or don’t have the financial means for regular care?  Imagine being able to identify the early-onset of diabetes with ease and intervening before a patient has damage. Another common scenario is a patient being rushed to the ER and being diagnosed with a chronic condition such as COPD and the physician finding existing and irreversible damage.  Earlier intervention is possible without adding armies of care managers to sift through data.  Instead, they can be presented with the highest risk patients based on an overall risk score or for specific condition intervention programs.

Felix Diagnose AI™ is an ensemble of the latest and most sophisticated artificial intelligence technologies, designed to carefully analyze patient history, clinical pathways and gather hidden patterns at both the patient and group levels.  By providing key recommendations related to the problem at hand, we can then help clinicians better understand their population and identify patients who need intervention and not create additional alert fatigue. Our Diagnose AI tool provides the necessary insights and enables physicians to intervene at an early stage and change the trajectory of patients’ health by preventing conditions from turning into lifelong illnesses.

Felix Diagnose AI™ Tool allows clinicians to predict, prevent, and delay the onset of chronic conditions such as COPD, early-onset diabetes, congestive HF, coronary artery disease, and more.   Once the engine has been given the necessary data, it can provide these insights in as little as 5 days, which is faster than any other population health management analytics provider.

Armed with a list of at-risk patients and the associated timeline,  proactive intervention programs are crafted and patients are monitored closely to prevent chronic diseases. The engine monitors all kinds of data, from clinical to external, that can affect the underlying condition. Felix Diagnose AI™ tool can also work with sparse data to make accurate predictions, unlike similar systems in the market. Furthermore, with the engine providing insights, it frees up the time of the doctors considerably and allows them to spend their time more productively engaging in inpatient care.

When it comes to the industry standard, Felix Diagnose AI™ outperformed Johns Hopkins’ models by identifying patients who are infrequent visitors to their healthcare providers. Compared to the industry standard, here is how Felix’s Diagnose AI stacks up:

As the old idiom goes, prevention is always better than cure. By looking at the astounding statistics concerning chronic diseases in America, we can comprehend the urgency of the issue at hand. By 2025, it is estimated that 164 million Americans – nearly half (49%) of the population, will suffer from chronic illnesses.

Intervening earlier for patients across the financial spectrum and reducing exacerbations that require hospitalization are critical to better utilize healthcare spending.  For more information of Felix Diagnose AI, please write to us at