ISAI, LLC
About ISAI
ISAI is a privately held company dedicated to providing state of the art technology for the capture and integration of high-quality, longitudinal patient data. The primary goal of the company is to invert the current focus of the healthcare industry from billing/revenue-centric to patient-centric by eliminating fragmentation in healthcare data and providing best-practices with respect to high-quality health data management.
Over the past several years, ISAI has been developing one of the world’s most sophisticated healthcare data integration platforms - HealthML. HealthML takes disparate healthcare data and processes it into high-quality, integrated, ‘clean’ data for use in both clinical decision support and research analytics. The platform has multiple ‘data connectors’ for ingesting data from a variety of external sources and integrating that data into comprehensive longitudinal patient records.
The ISAI platform directly addresses this issue with a data ingestion engine that is capable of pulling in data from multiple clinics and data sources. The following diagrams show how the ISAI Healthcare Data Refinery would be used to support the Digital Health Network vision.
Our Mission
The Fragmentation of Healthcare
Systemic fragmentation permeates all aspects of the US healthcare system and nowhere can this fragmentation be seen more prevalently then in the fragmentation of healthcare data and systems.
In the US, there is no single comprehensive source of a patient’s medical history. Patient data is fragmented and siloed into Electronic Healthcare Record systems (EHRs) in over six thousand EHR implementations at clinics and hospitals across the country. Over the course of a patient’s life, they may visit multiple care centers and specialists with separate electronic medical recording keeping systems (EHRs). Furthermore, lab tests and genomic tests often come back to the physician’s office in a form that is not machine readable. (Many of us have repeatedly experienced this fragmentation whenever we visit a new clinic and are asked to fill out 12-15 pages of medical history.)
As a result, none of the stakeholders in the healthcare system (patients, physicians, hospitals, research institutions, payers) have a single integrated view of a patient’s medical history. The impact on the quality of healthcare is significant both with respect to clinical practice and medical research in several ways.
First, fragmentation directly impacts quality of care in any patient-physician interaction. It is estimated that over a million deaths in the US are due to medical errors with a resulting toll in terms of both human suffering and malpractice costs. This is especially true with the growing trend in telemedicine where a provider may only have the patient’s recollection of the medical history and little or no supporting historical data. It is estimated that medical costs for medical errors account for 29B in the US. Some estimates put medical errors as the third leading cause of death in the US just behind heart disease and cancer (Although other studies show different results). https://healthjournalism.org/blog/2023/07/medical-errors-are-the-third-leading-cause-of-death-and-other-statistics-you-should-question/
Second, existing EHR systems are plagued with useability difficulties (systems fragmentation) causing undue administrative burden on clinicians and care-givers at the point of patient care. Physician burnout has become such a critical problem in healthcare that 60% of physicians do not recommend their profession as a career. https://www.healthleadersmedia.com/strategy/60-docs-wouldnt-recommend-their-profession-career
Third, the needs of the research community are severely hampered by a lack of comprehensive patient records. The pharmaceutical industry requires complete and accurate deidentified patient data for the early phases of drug development and identified data for the later phases of drug development (i.e. clinical trials). The way in which patient data is collected for clinical studies is carefully regulated by the FDA and requires sophisticated data collection systems that fall beyond the technical capabilities and budgets of any one research group, clinic, hospital network, or advocacy group. Large contract research organizations (CROs) and pharmaceutical companies do have the resources to build and maintain such data collection systems.
A report in the National Library of Medicine states ‘Generating accurate and sufficient results to determine whether or not there is merit in continuing is important at each stage in the clinical trial process. The investments of resources, time, and funding grow with successive stages, from pre-clinical through phase 3. Thus, the cost of a failed phase 3 trial is not just the cost associated with the trial itself but the cost of all prior trials as well as the cost of lost time pursuing a potentially viable alternative.’ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6092479/
However, the data gathered during a clinical trial oftentimes is not published should the trial fail. This is a yet another form of waste analogous to discarding valuable drugs that retain their efficacy, only here we are discarding valuable data.
These issues are compounded by rising healthcare costs due to ineffective or wasteful treatments. A 2017 article in Scientific American states ‘Experts estimate the U.S. health care system wastes $765 billion annually—about a quarter of all the money that’s spent. Of that, an estimated $210 billion goes to unnecessary or needlessly expensive care, according to a 2012 report by the National Academy of Medicine. ProPublica has been documenting the ways waste is baked into the system. Hospitals throw away new supplies and nursing homes discard still-potent medication. Drugmakers combine cheap ingredients to create expensive specialty pills and arbitrary drug expiration dates force hospitals and pharmacies to toss valuable drugs.’
There are other aspects of fragmentation in healthcare. A recent posting of The American Association of Medical Colleges (AAMC) describes the ‘representation gap’ between men and women in clinical trials why we know so little about women's health stating ‘Before 1993, women were rarely included in clinical trials. Today, the medical field still doesn’t know how well many drugs and devices work for women.’ The posting goes on to say ‘doctors have considered women’s bodies atypical and men’s bodies the “norm,” despite women accounting for nearly half the global population and outnumbering men in the United States since 1946… Though policy and social changes in the 1990s have helped turn the tide, women remain underrepresented in research, sometimes grossly so.’
This underrepresentation has led to a large imbalance of high-quality clinical data about women necessary to support clinical studies in every major disease category including, but not limited to: cardiovascular disease, cancer, metabolic disease, reproductive issues, menopausal studies, and endometriosis.
Today, there are many advocacy groups in women’s health representing a broad spectrum of health concerns such as the ones listed above. The same is true for advocacy groups in the rare disease community. All of these groups have been essential in driving awareness for their constituent patient communities and, in some instances, have been able to drive research dollars towards investigational and interventional studies in their areas of focus. However, all these efforts remain fragmented and the resulting impact on the patient population is limited.
The above cases in women’s health and advocacy are examples of institutional fragmentation.
While the solution for several of the issues cited above have a legislative component, a large part of the problem lies in the lack of integration of healthcare systems and data.
The Solution
ISAI is building and deploying HealthML, our data integration platform to be used as a foundational data repository for integrated healthcare records. We are calling this initiative The Digital Healthcare Network (DHN). The DHN would provide a single integrated view of patient data available to all stakeholders in healthcare, including the patient.
The intention of the DHN is to eliminate fragmentation in healthcare and to accelerate research by providing a single-source integration platform that can be used by patients, clinicians, advocacy groups, research institutions, and biotech/pharma to further investigational studies across any health area of concern.