Singula is a first-of-its-kind Learning Mental Health System (LMHS) using technology and big data to diagnose and treat anxiety and depression using a biopsychosocial approach. We are challenging the status quo in healthcare by building a direct avenue from clinical research to clinical care using a multi-level integration of disciplines and approaches.
Singula Institute™ provides Singula Medical, PLLC with healthcare management service organization (MSO) services, providing practice organization, management, and administrative support services.
Our LMHS includes a Clinic that adapts to the patient’s dynamic and individualized needs, bridging gaps in clinical care and a Social Impact Community that fosters Societal Resilience; Through learning from and educating diverse communities, we demystify and destigmatize mental health, empowering a more inclusive and democratized culture of care.
Our clinical care is delivered with empathy, compassion, and openness to an individual’s unique set of biological, psychological, and social characteristics. By utilizing comprehensive clinical evaluations, we can track progress through directed interventions and provide superior mental health care leading to the best possible outcome for every patient.
Social stigmas often prevent people from accepting the need for treatment. Our community programs and events are developed and created around making a positive impact on how society views and engages with mental health treatment. To learn more about upcoming Social Impact Community events, please join Singula in getting involved by donating or joining our newsletter.
Our Learning Mental Health System (LMHS) proposes a multi-level collaboration among patients, providers, researchers, and health policymakers within a coordinated and integrated data flow to improve care and deliver individualized treatment for each patient.
Singula’s multi-faceted expert team tackles the societal problem of anxiety and depression head-on through a multi-pronged approach. We put our patients first, delivering precision medicine through a biological, psychological, and social (biopsychosocial) approach. By using technology and machine learning methods we can integrate multiple mental health disciplines and target the patient’s issues more efficiently and effectively. The data acquisition is initiated through multiple patient-clinician interactions providing longitudinal biopsychosocial data to the main clinical research data frame. Patient data is gathered by advanced technology, which is processed in an integrated data inter-frame through multiple encounters by a research team. An evidence repository will provide a continuous flow of information to optimize decision-making on all levels of the LMHS.
Meanwhile, our Social Impact Community uses data-driven educational programs to build societal resilience, reduce the stigma surrounding mental health and mental illness, increase engagement in mental health care, and promoting mental wellness.
Singula transforms the lives of people suffering from anxiety and depression by individualizing diagnostics and treatments. We deliver precision medicine through an innovative learning health system that leverages clinical research and cutting-edge technology.
Through our Learning Health System, clinical care and research, and social impact community, the Singula team is committed to the individualization of diagnosis and treatment for anxiety and depression. Our foundation strives to integrate multiple mental health disciplines for the better delivery of patient care. In turn, this will reduce the stigma surrounding mental health and mental illness – the cultivation of a mentally healthy society.
Funding mental health research and clinical care now is crucial to ensure the success of future scientific breakthroughs. Donors are stepping up to support the efforts of the scientific and medical communities as they develop new treatments, cures and methods to treat mental illness.
We envision a world in which no individual endures needless suffering due to anxiety and depression