Why I chose Johnson
I chose Johnson at Cornell Tech because it’s the only program that provides the skeleton structure for a career centered on creativity and innovation. No industry is riper for technological breakthroughs than healthcare. The Johnson Cornell Tech MBA gives me both the mindset and toolkit to spearhead the charge.
October 22 2014
The health sector is arguably one of the most “closed” systems in every sense imaginable. Historically, the relationship between the vulnerable patient and entrusted physician has been predicated on a sacred, unbreakable bond that has survived through generations of doctors. This bond survives today in the Hippocratic Oath that all newcomers to the field must vow before commencing studies. Outside the inherently closed nature of the doctor-patient relationship, the state of affairs in the American healthcare system is as complex as ever despite attempted shifts towards centralization. The ability for physicians, patients, and third parties to navigate this lumbering behemoth of a system is covered with endless red tape.
The idea of introducing an “open” infrastructure, or a publicly modifiable software platform, to healthcare is greeted with cautious optimism. In addition to the obvious concerns of privacy with personal health information, adding an additional nuance to the overwhelming system runs the risk of increasing sensory overload providers face everyday. However, if that information is freely accessible, unadulterated, and appropriately contextualized it has the potential to draw meaningful and accurate conclusions. By leveling the playing field, these conclusions drawn via natural mechanisms of competition have the potential to reduce time, money, and complexity within healthcare. Innovation becomes a habit. Approaches are no longer siloed. Naturally, given the sensitive nature of the medical content and sluggishness to transition to taking full advantage of an open architecture is understandable. This is not to say that significant strides in this sector have not been made. Given the breadth of open architecture (open data, open API, open source), the approach in analyzing its permeation within the health sector is through careful analysis of gains and roadblocks in open data adoption as a pertinent sample.
Open data is a practice that particular data sets should be freely available to the public without restriction. The role of open data has been used to introduce transparency in realms such as government (see www.data.gov), but in the health sector it assumes a greater role in the context of scientific discovery. Not only does the opportunity to allow all minds to be privy to the same data set allow for maximal analysis, it fosters collaboration and innovation for more perspectives and higher-level conclusions. New York University (NYU) researchers collaborated with the United Kingdom’s National Health Service to produce an 81-page guide on how to use government open health data entitled, “The Open Data Era in Health and Social Care” in which the notion of mutual accountability is strongly espoused. One of the best examples of the use of open data in this sector is the recent advent of www.healthdata.gov, a federal website managed by the United States Department of Health and Human Services that allows easily downloadable data by third parties. The concept of open data, however, is not a novel one. Given that the International Council of Science first recognized the importance of open data in 1957 to “prevent the loss of data and maximize its accessibility,” only recently have the Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) freely offered comprehensive data sets.
In today’s health sector most advancement is made through academic research and publication. Almost every data set being used in health-related academic publications are restricted to the authors and rely on the honor code in arriving at the results from described methods. As a result, broad conclusions that have the potential of affecting many patients are drawn from data sets only a limited number of investigators are privy to. Furthermore, data extraction and analysis is often left to the most junior investigators. Only in rare cases does a publisher ask to review the data, leaving most of the scientific literature without verification. Moreover, investigators in competing groups will repeat an exhaustive process to collect data rather than asking the original investigator for the dataset. The need for greater collaboration and resource utilization has since resulted in a culture shift as exemplified by the success of the Multi-Center Orthopaedic Outcome Network (MOON). MOON is a consortium of surgeons from academic centers including the Hospital for Special Surgery, Cleveland Clinic, Ohio State University, University of Colorado, University of Iowa, Vanderbilt University, and Washington University in St. Louis that have won multiple Neer Awards in orthopaedics research as a single unit for its clinical insights in ACL reconstruction and rotator cuff treatment.
Just as MOON is collaborative but still closed, the notion of open data has benefits but remains not widely adopted. For example, in 2013 the New England Journal of Medicine published an editorial by Dr. Jeffrey Drazen recapitulating the debate on openness clinical trials data. On one hand, availability of the data can be useful for physicians of late-stage cancer patients seeking Hail Mary treatments, while on the other hand, those who painstakingly gathered the data deserve “dibs” on the data for publication. As a result, the concept of creating a moratorium period before other investigators can access clinical trial data has been proposed but remains short of the open paradigm.
An aforementioned complaint among healthcare professionals, particularly physicians, is sensory overload. When open data comes to fruition, data will become a free-flowing commodity without context. The majority of a new physician’s time has been shown to average just 8 minutes of patient face time. Instead of counseling patients, physicians are forced to perform ancillary tasks indirectly related to patient care (i.e. navigating the electronic health record for pertinent information). Professionals in the field are not unwelcoming to increased data but rather seek a more palatable and contextualized means of accessing and viewing this information. Recognizing this crisis, companies like Palantir and Open mHealth were born to make clinical sense of the data.
Despite the health sector’s inherently closed nature, there exists both a need and a push towards “opening” the infrastructure. As seen with the open data example, there was easy adoption from the CDC and WHO but resistance from groups less than eager to part with hard-earned clinical trial data. The resistance and slow-adoption rate can be pinpointed to the historically and culturally closed nature of healthcare. In healthcare, closed should not be mistaken for inflexibility. There exists aspects in healthcare that may need to remain closed when it comes to personal identifying data, but there also exists tremendous upside to an open architecture that may alleviate fundamental problems that plague the industry (i.e. soaring costs, underwhelming outcomes). Open is a powerful and viable tool at our disposal that crowdsources innovation to resolve fundamental problems. Given the myriad of well-documented problems facing the American healthcare system, remaining closed is no longer an option. Opening healthcare represents a paradigmatic shift that may be the best solution available.