User:Feldman.lynn/sandbox

SimulConsult’s main product is diagnostic decision support software (DDSS) to help clinicians diagnose rare diseases. Studies have shown that using it can reduce diagnostic errors by up to 75% and reduce the average time for a clinician to reach a genetic diagnosis by 55%, from 234 to 129 minutes.

Founded in 2008, SimulConsult was the outgrowth of work by Michael M. Segal, MD PhD dating back to his residency in pediatric neurology. Dr. Segal felt that there were too many known diseases to remember well. He modeled the first DDSS version on the diagnostic thinking of Columbia clinical geneticist Kwame Anyane-Yeboa, MD at Columbia.

Over the past decade, the software's development and testing have been supported by over $5 million in Small Business Innovation Research (SBIR) grants from the NIH, as well as grants from PCORI and Mass Ventures, which included many clinical trials.

During early development, the DDSS software (delivered as software-as-a-service or SaaS) was made available to clinicians free of charge. SBIR grants, however, come with the expectation that the recipient will become a revenue-producing business. Accordingly, with the release of its v3.0 software platform in April 2019, SimulConsult transitioned to paid subscriptions. SimulConsult has users at top US academic medical centers as well as in many countries around the world. There are ~70 authors and editors who have built the core database of diseases and related findings. SimulConsult's senior leadership team includes Lynn Feldman, MBA, CEO; Michael M. Segal MD PhD, Founder and CSO; Richard Berenson, JD MBA, CFO; and Mark Zbikowski, MS, CTO.

A series of papers reporting on clinical trials have been published; all show the accuracy of the DDSS. . Additional work shows the usefulness of the automated reports.

The company is in the process of developing its first enterprise product. This new product is designed to integrate with the electronic health record. The DDSS uses natural language processing techniques combined with vocabulary from the DDSS curated database to identify findings in the patient record and flag them in the user interface of the DDSS. In addition, in the enterprise version automated reports can be digitally signed and added to the patient's chart in the electronic health record. In the prototype, use of the software saved an additional 61% of time, reducing the non-patient facing clinician time to 79 minutes.

As of March 2021, the DDSS includes: (1) a database of >7,500 diseases and >196,000 relationships of findings to diseases that are updated many times per month; (2) all Mendelian disorders with known molecular basis, all well-accepted chromosomal syndromes, and the non-genetic conditions (aka phenocopies) in the differential diagnosis of genetic conditions; (3) an algorithm that prioritizes the Usefulness of suggested findings (including tests) to refine the initial differential diagnosis; (4) "Core Lists" of findings within particular specialties that enable efficient capture of patient findings; and (5) clinical correlation with Next Generation Sequencing (NGS) results to reach a definitive diagnosis and return results.