Enhancing genomic laboratory reports from the patients’ view: A qualitative analysis
Published by the American Journal of Medical Genetics (open access) on June 18, 2015 by Heather Stuckey, Janet L. Williams, Audrey L. Fan, Alanna Kulchak Rahm, Jamie Green, Lynn Feldman, Michele Bonhag, Doris T. Zallen, Michael M. Segal, Marc S. Williams
The article describes the responses by families to SimulConsult’s Prognosis Table, as used in genomic reports. Some samples:
– Gives idea of what to look for in the future
– Timeframes very helpful
– Would use as baseline for reference
– Everything on it is necessary
– Can use with provider for discussion
Extending Genome-Phenome Analysis
SimulConsult receives SBIR II 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 exome and 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 diagnostic software that examines all known diagnoses (the “phenome”) with the power of whole exome sequencing to examine the genome, and uses advanced capabilities such as compatibility with all family structures and the ability to take into account DNA deletions and duplications. In automating the genome-phenome analysis, this project brings the power of genome analysis to clinical practice – lowering costs while increasing accuracy.
SimulConsult has commercial contracts with a number of laboratories for its Genome-Phenome Analyzer to analyze exome data. These contracts make use of the ongoing research and product development from this grant, including the addition of the ability to analyze copy number variations from genomic data or a traditional microarray and families with samples from family members other than a trio.
Evidence-Based Decision Support for Neurological Diagnosis Reduces Errors and Unnecessary Workup
Published in the Journal of Child Neurology in April 2014 by Segal MM, Williams MS, Gropman AL, Torres AR, Forsyth R, Connolly AM, El-Hattab AW, Perlman SJ, Samanta D, Parikh S, Pavlakis SG, Feldman LK, Betensky RA, Gospe SM Jr.
Using vignettes of real cases and the SimulConsult diagnostic decision support software, neurologists listed a differential diagnosis and workup before and after using the decision support. Using the software, there was a significant reduction in error, up to 75% for diagnosis and 56% for workup. This error reduction occurred despite the baseline being one in which testers were allowed to use narrative resources and Web searching. A key factor that improved performance was taking enough time (>2 minutes) to enter clinical findings into the software accurately. Under these conditions and for instances in which the diagnoses changed based on using the software, diagnostic accuracy improved in 96% of instances. There was a 6% decrease in the number of workup items accompanied by a 34% increase in relevance. The authors conclude that decision support for a neurological diagnosis can reduce errors and save on unnecessary testing.
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.
Interoperable decision support to improve diagnostic workflow across multiple EHR
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.
Automated genome-phenome analysis
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.
Genome-Phenome Analysis for Diagnosis and Gene Discovery
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.
Empowering Physicians with Evidence-Based Decision Support for Pediatric Rheumatologic Diagnoses
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.
SimulConsult Launches Software to Link Genomic, Clinical, and Phenotypic Data
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
Decision support for diagnosis: co-evolution of tools and resources
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.
The Impact of Computer Resources on Child Neurology
Published in “Pediatric Neurology: Principles and Practice”, Swaiman KF et al., editors, 5th edition, Saunders, Chapter 108 by Segal M and Lever S
MIT Technology Review on medical decision support
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.
An Evidence-Based, Open-Database Approach to Diagnostic 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.
Attenuated variants of Lesch–Nyhan disease: the case of King James VI/I
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.
A Handbook of Neurological Investigations in Children
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.
Professor Clayton Christensen on health care reform and disruptive innovation
In an interview with Hugh Hewitt, Clayton Christensen comments on how SimulConsult will disrupt aspects of the health system.
Doctor calls for SimulConsult without realizing it
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:
The Innovator’s Prescription: A Disruptive Solution for Health Care
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.
How doctors think, and how software can help avoid cognitive errors in diagnosis
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.