An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge
Published in Genome Biology on March 25, 2014 by Brownstein CA et al.
The article describes the CLARITY genome interpretation contest, and how SimulConsult had by far the fastest analysis times.
SimulConsult receives SBIR II from the National Library of Medicine of the NIH beginning September 2013 with Michael M. Segal MD PhD as Primary Investigator
This project uses the power of diagnostic decision support software to provide advanced capabilities to multiple electronic health records, including complex test selection, superior clinical reporting, payor integration and learning from patient results, using as research areas radiology and genetics, in the diagnosis of neurological diseases. The aims are to use the deep knowledge of such a tool to improve accuracy and cost-effectiveness of medical care. More generally, the goal is to advance the vision of “best of breed” knowledge tools making medical care better and more affordable.
SimulConsult and the Geisinger Genomic Medicine Institute won the Bio-IT World Best Practices Award in Informatics
SimulConsult and the Geisinger Genomic Medicine Institute won the Bio-IT World Best Practices Award in Informatics for their use of SimulConsult’s Genome-Phenome Analyzer to analyze genomes accurately and quickly.
SimulConsult receives SBIR I from the National Human Genome Research Institute (NHGRI) of the NIH beginning March 27 2013 with Michael M. Segal MD PhD as Primary Investigator
With the declining cost of whole genome sequencing, the main cost of such testing is becoming the cost of interpreting the huge amount of data that is generated. This project combines the power of using diagnostic software to examine all known diagnoses (the “phenome”) with the power of whole exome sequencing to examine the genome. In automating the genome-phenome analysis, this project brings the power of genome analysis to clinical practice – lowering costs while increasing accuracy.
Presented on March 22, 2013 by Segal MM, Wiliams MS, Tromp G and Gleeson JG at the American College of Medical Genetics 2013 annual Meeting.
SimulConsult receives SBIR I from the National Institute of Arthritis and Musculoskeletal and Skin Diseases of the NIH beginning September 2013 with Michael M Segal MD PhD as Primary Investigator
This project responds to a critical shortage of pediatric rheumatologists by enlisting top rheumatologists to encapsulate the diagnostic information in their field in the most advanced decision support software tool for diagnosis. The project tests workability of integration into a tool used in other areas of medicine and assesses the benefits of such rheumatology assistance for both rheumatologists and general clinicians. By doing so, it tests whether this decision support approach can be used more widely to improve accuracy and cost effectiveness in medicine.
Published in Genome Web on May 18, 2012 by Uduak Grace Thomas
SimulConsult, a bioinformatics company based in Chestnut Hill, Mass., is marketing a new software tool called the Genome-Phenome Analyzer, which lets clinicians and research labs combine whole-genome and whole-exome sequencing data with clinical findings and phenotype information
Published in Neurology on May 15, 2012 by Segal MM and Schiffmann R.
The editorial discusses the role for diagnostic decision support in facilitating an evidence-based discussion between clinicians and payers.
Published in “Pediatric Neurology: Principles and Practice”, Swaiman KF et al., editors, 5th edition, Saunders, Chapter 108 by Segal M and Lever S
Published in MIT’s Technology Review on September 21, 2011.
The article discusses IBM’s Watson, Isabel and SimulConsult in the context of medical decision support.
SimulConsult receives contract from the National Library of Medicine of the NIH beginning September 27, 2010 with Michael M. Segal MD PhD as Primary Investigator
The project is designed to assess the feasibility of a computational approach to diagnostic decision support based on an open, comprehensive database encompassing many diseases, using a Bayesian model with an evidence-based authoring process in which it is possible to update one disease in isolation, without commenting on other diseases, and do so with detailed temporally-sensitive information.
Published in Brain on July 12, 2010 by Peter Garrard John Stephenson Vijeya Ganesan Timothy Peters
The authors used SimulConsult to analyze a historical diagnosis.
Published as a book in September 2009 by King MD and Stephenson BP, Mac Keith Press
In the book the authors discuss SimulConsult, beginning on page 1 with “With the explosion of electronic information such as found on PubMed and the availability of freely accessible diagnostic software such as SimulConsult one might ask what possible use is there for a handbook like this.
In an interview with Hugh Hewitt, Clayton Christensen comments on how SimulConsult will disrupt aspects of the health system.
Published in the Health Business Group Blog on March 6, 2009.
In The Computer Will See You Now, Dr. Anne Armstrong-Coben highlights the depersonalization and mindless checkboxes of electronic health records. She identifies Tablet PCs as the way to deal with the depersonalization, but is silent on what to do about the mindless checkboxes:
Published on December 4, 2008 by Clayton Christensen et al
A book by Clayton Christensen and colleagues discusses SimulConsult as an example of a “disruptive innovation” that helps generalist and specialist doctors make diagnoses at the level of specialists and sub-specialists.
Published in Acta Pediatric in November 12, 2007 by Michael M Segal, MD PhD
Textbooks teach about diagnosis by describing diseases and the collection of findings in each disease. However, patients show up with findings, not diseases, and we must invert our knowledge to take the patient’s collection of findings and figure out the correct diagnosis. It is not so simple to do this, particularly in pediatrics. The Office of Rare Diseases at the National Institutes of Health estimates that 8% of people have one of the 7000 diseases listed as ‘rare’, and most of these diseases have onset in the pediatric years.
This is a lot of information to consider, and as a result diagnosis is wrong an estimated 15% of the time.
MD NetGuide article “Top Ten Physician Inventors” (on page 7) cites as #2 Michael Segal MD PhD: “Was responsible for the development of SimulConsult, a decision-support software that combines clinical and laboratory findings to help physicians come to a simultaneous diagnosis on a disease.”
Published in Neurology Today on February 6, 2007 by Orly Avitzur MD.
A sophisticated neurology wiki that helps doctors make clinical decisions is exactly what child neurologist Michael M. Segal, MD, PhD, had in mind when he created SimulConsult. SimulConsult users input data into software that helps them arrive at a differential diagnosis of neurological syndromes.
David J. Michelson, MD, assistant professor of neurology at Loma Linda University School of Medicine, said he has been amazed by SimulConsult’s ability to generate perfect matches to single conditions.
“The software is very user-friendly and intuitive,” he said. “It is designed to highlight metabolic and genetic syndromes which often only differ by certain specific findings.” … a 7-year-old boy with a neurodegenerative disorder with dementia, cerebellar atrophy, and spastic quadriplegia – despite EMG and muscle biopsy results suggesting denervation – was a perfect match for neuroaxonal dystrophy. He quipped, “Steven Ashwal made that diagnosis within five seconds of hearing me describe the child, which just proves that I need the program a lot more than he does.”
The tool has matured and increased in accuracy through a collaborative effort of many neurologists. In contrast to Wikipedia, all submissions to the SimulConsult database are reviewed by doctors following the existing norms for medical journals. Dr. Segal contends that wikis are more descriptive, providing details about findings in diseases, than prescriptive, providing rules tailored for particular clinical situations. The descriptive information available through wikis is a good way to aggregate evidence-based medicine, Dr. Segal added.
“Our software addresses 1,400 inherited and congenital neurological diseases, and uses over 24,000 data points,” said Dr. Segal. “Since there are no clinical rules, adding new material is straightforward and can be done merely by changing individual data points.”
SimulConsult also created a blog format for clinical cases in which medical terms from a case narrative are hyperlinked into the diagnostic software (simulconsult.com/cases/). Physicians can click into the software with all patient findings already entered. The cases blog format is being developed together with the Child Neurology Society for residents and other doctors in practice who want to keep their skills sharp and up-to-date with the latest advances in diagnostic knowledge.
The ability to click into information tools from narratives about patients has the potential for much wider application. “In essence, a medical chart is a privacy-protected blog,” Dr. Segal pointed out. If data such as labs, tests, history and physical exam findings can be filtered into software, physicians can be easily assisted in medical decision-making.”
“The cases blog illustrates the potential of a neurology wiki,” Dr. Segal continued. “As similar tools become an integral part of practice, opportunities for collecting the wisdom of the neurology community in these ways will increase.”
Published in Journal of Child Neurology in April 21, 2006 by Michael M Segal MD PhD
Medical practice will be improved by the use of software that not only assists with diagnosis but can do so at the bedside, where the doctor can act immediately upon suggestions such as useful findings to check. Medical education will shift away from a focus on details of unusual diseases and toward a focus on skills of physical examination and using compertized tools. Medical publishing, in contrast, will shift toward greater detail: it will be increasingly important to quantitate the frequency of findings in diseases and their time course since such information can have a major impact clinically when added to decision support software.