Cogitativo Introduces ‘Visión’, A Machine Learning Tool Built to Tackle the Growing Deferred Care Crisis

Cogitativo is a data science enterprise based in Berkeley to develop and implement creative, scalable solutions to the healthcare system’s most complicated challenges. Cogitativo uses machine learning, proprietary data sets, and expertise from individuals with decades of experience working with public health institutions to provide relevant insights and save lives.

Cogitativo recently announced the release of Visión, a first-of-its-kind machine learning platform that may help people with chronic diseases forecast and prevent acute medical occurrences, as well as track disease progression for those at high risk.

Visión combines cutting-edge machine learning techniques with clinical treatment recommendations information to discover and expose gaps in individual patient care that may lead to adverse outcomes. As a result, it can help create focused clinical interventions that enhance outcomes for vulnerable persons, such as those who delayed seeking medical help during the pandemic.

Millions of Americans have gone 18 months without critical screenings and treatment, resulting in a deferred care crisis requiring immediate and proven solutions to assist those in need. Cogitativo’s CEO believes that Visión will play a crucial role in averting acute medical occurrences for vulnerable people and enabling health care organizations to overcome many of the obstacles they encounter.

Healthcare payors and providers are reporting an increase in medical demands among those who were unable to receive care during the pandemic, particularly those with chronic diseases such as chronic kidney disease, cardiovascular disease, diabetes, HIV, and mental health issues. In addition, many doctors are dealing with an increase in inpatient visits. Individuals are returning to medical facilities for appointments, testing, and treatment as the virus continues to spread.

To anticipate higher risk for an acute clinical event, Visión examines patient’s health records through the perspective of peer-reviewed research on disease progression, social determinants of health, climate change, and other relevant data sources. These time-based projections will allow healthcare payors and providers to identify members and patients who are most likely to need more medical attention in the coming months. This information will enable healthcare payors and providers to perform proactive outreach and deliver preventative treatment to at-risk beneficiaries and make tailored preventive care recommendations.

Cogitativo’s new machine learning tool can assist physicians across the country in identifying their most at-risk patients and conduct proactive outreach, ensuring that these patients receive the critical care and attention they require while also avoiding unpredictable waves of patient visits that cause capacity issues.


Sanskriti is currently pursuing her bachelor’s in Journalism, Psychology, and English and is enthusiastic about getting to know new people, uncovering their stories, and engaging with the atmosphere. She has an inclination towards news affairs, writing and teaching.

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