Published in The Journal for Electronic Health Data and Methods on December 6, 2017 by Michael M. Segal, Alanna K. Rahm, Nathan C. Hulse, Grant Wood, Janet L. Williams, Lynn Feldman, Gregory J. Moore, David Gehrum, Michelle Yefko, Steven Mayernick, Roger Gildersleeve, Margie C. Sunderland, Steven B. Bleyl, Peter Haug, Marc S. Williams
The article describes the result of an NIH-sponsored study of integrating SimulConsult’s diagnostic decision support system with Electronic Health Record systems.
Published in the Journal of Genetic Counselors in April 2018 (open access) by Williams JL, Rahm AK, Zallen DT, Stuckey H, Fultz K, Fan AL, Bonhag M, Feldman L, Segal MM, Williams MS.
The article describes the result of a PCORI-sponsored study of providing information about genetic testing to patients, including a display driven by the highly granular onset information in SimulConsult’s diagnostic decision support system.
Published by the Journal of Pediatric Rheumatology Online on December 13, 2016 (open access) by Michael M. Segal, Balu Athreya, Mary Beth F. Son, Irit Tirosh, Jonathan S. Hausmann, Elizabeth Y. N. Ang, David Zurakowski, Lynn K. Feldman, and Robert P. Sundel
The article describes the result of an NIH-sponsored study of adding rheumatology information to the SimulConsult diagnostic decision support system. The 26 clinicians demonstrated a significant reduction in diagnostic errors following introduction of the software, from 28% errors while unaided to 15% using decision support (p < 0.0001). Improvement was greatest for emergency medicine physicians (p = 0.013) and clinicians in practice for less than 10 years (p = 0.012). This error reduction occurred despite the fact that testers employed an “open book” approach to generate their initial lists of potential diagnoses, spending an average of 8.6 min using printed and electronic sources of medical information before using the diagnostic software.
Published in the American Journal of Medical Genetics in May 2016 (open access) by Williams JL, Rahm AK, Stuckey H, Green J, Feldman L, Zallen DT, Bonhag M, Segal MM, Fan AL, Williams MS.
The article describes the responses by clinicians to SimulConsult’s prognosis table, as used in genomic reports. One sample: “I love it—no clicks, detailed, comprehensive enough that I didn’t feel I needed another source—everything a pediatrician would think about.”
Published in Applied Translational Genomics, in July 22, 2015 by Michael M. Segal.
In a brain MRI report, the following words often appear: “clinical correlation is recommended”. These words signify that inadequate clinical information was provided, or that an unexpected finding on the MRI should be assessed clinically. “Clinical correlation is recommended” is less common in a report about a single gene or simple gene panel. This is because the very act of ordering the test conveys much of what is important about the clinical situation, and only rarely is further information needed.
Genetics labs are moving into new territory as they adopt next-generation genomic sequencing. When moving beyond single gene tests and simple panels, more clinical correlation is needed. The complexity of interpretation becomes similar to a brain MRI, only more so.
In an exome, thousands of variants are found. Even after comparing to other family members, and using estimates of variant pathogenicity, many genes must be considered. Sometimes clinical correlation can be as simple as using the key clinical finding, assuming that you know which finding is key. But sometimes the situation is more complicated: variants are found in a gene that hadn’t been considered clinically, or two genes are needed to explain the clinical picture, and more clinical correlation is needed.
Published in the Journal of Child Neurology in June of 2015 by Michael M. Segal, MD, PhD, Mostafa Abdellateef, Ayman W. El-Hattab, MD, Brian S. Hilbush, PhD, Francisco M. De La Vega, PhD, Gerard Tromp, PhD, Marc S. Williams, MD, Rebecca A. Betensky, PhD, and Joseph Gleeson, MD
We describe an “integrated genome-phenome analysis” that combines both genomic sequence data and clinical information for genomic diagnosis. It is novel in that it uses robust diagnostic decision support and combines the clinical differential diagnosis and the genomic variants using a “pertinence” metric. This allows the analysis to be hypothesis-independent, not requiring assumptions about mode of inheritance, number of genes involved, or which clinical findings are most relevant. Using 20 genomic trios with neurologic disease, we find that pertinence scores averaging 99.9% identify the causative variant under conditions in which a genomic trio is analyzed and family-aware variant calling is done. The analysis takes seconds, and pertinence scores can be improved by clinicians adding more findings. The core conclusion is that automated genome-phenome analysis can be accurate, rapid, and efficient. We also conclude that an automated process offers a methodology for quality improvement of many components of genomic 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
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.
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.
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.
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 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.
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.
Neuronline review of SimulConsult by G. Fuller
Imagine the scene: you have just seen a patient with what seems likely to be an inherited or congenital syndrome who has a combination of symptoms and signs you do not recognise and in whom standard investigations have provided no clues. What do you do? Looking in the books is very time consuming and depends on how well the books are indexed; searching PubMed or online inheritance in man (OMIM) is often difficult using just symptoms and signs. Wouldn’t it be useful if you could put the clinical information into a database to narrow down the differential diagnosis? This is the idea that drives www.simulconsult.com, which describes itself as a “medical decision support software” that “allows doctors and other medical professionals to combine clinical and laboratory findings” and get a “simultaneous consult about diagnosis”. Registration is straightforward and this leads you to an introductory video and the opportunity to search the site. The searching is reasonably intuitive. You enter the age and sex, and then can add clinical feature and test results, either having searched for them or from an alphabetical or category based pick list.