Abstract:
A paradigm shift has taken place regarding innovation and learning in healthcare. In the past, one or several doctors, usually within the same institution, collaborated and developed new concepts or ideas and then tested them at their institution. Following the initial testing, the initial concept or prototype was modified, followed by incremental small improvements until the final product, concept, or procedure was ready for clinical testing. The traditional method of drug testing was the methodical transition from the test tube to phase 1 clinical testing, showing no harm to the human subjects, followed by phase 2 and phase 3—evaluating whether a new treatment works for a specific medical condition and then comparing the treatment against the previous standard of care for that condition or disease. The process of moving from the test tube or prototype to the marketplace takes many years and may require $1 billion of research and development for a new drug. Today, the entire process of innovation can be significantly shortened, with less expense, and a shorter timeline for development. This article discusses a new method of collaboration among multiple disciplines and even multiple institutions that will improve diagnosis, treatment, and management, and even enhance patient compliance and convenience regarding their medical care.
Many stakeholders often are included in moving an innovation from ground zero to the marketplace. In healthcare, these include physicians, patients, nurses, academic institutions, institutional review board oversight, engineers, IT personnel, software developers, human-centered designers, payers, coding experts—and let’s not forget the government! Corralling all of these stakeholders can seem almost insurmountable, much like herding cats. However, now there is a new method of harnessing all of the knowledge that is potentially available to accomplish an innovation project—or even come up with innovative solutions to common healthcare dilemmas.
The process of translating innovation into clinical care improvements is difficult, risky, expensive, and poorly understood. Many clinicians who identify healthcare problems do not have the time or expertise to solve the problems, and, on the other side of the coin, many academic researchers and technologists are unaware of the important gaps in clinical care to which their expertise may apply.1
Healthcare is at the intersection of disruptive innovation and the digital health experience. One of us (AK), a sinus surgeon at Harvard Medical School, firmly believes that disruptive innovation in healthcare requires collaboration, not competition. AK believes in a systems approach to fixing American healthcare. She has collaborated on an imaginative approach to redesign of our healthcare system that promotes “health” and works “systematically” for the patient. She is involved with the MIT Hacking Medicine group, which has been running the largest healthcare hackathons for several years.
Crowd Sourcing on Steroids
The term crowd sourcing was introduced by Jeff Howe and Mark Robinson in a Wired magazine article in June 2006. Crowd sourcing is defined as the act of a company or institution taking a function that once was performed only by employees and outsourcing it to a large network of people.2 For example, a medical practice identifies a task or problem that is performed or being discussed in-house and seeks outside help or assistance to do the task or solve the problem.
Research has found that a stable and supportive social network improves health outcomes for people with a wide range of conditions.
Crowd sourcing is powerful and has been in vogue in healthcare for many decades. Even before the Internet became widely available, there was evidence that social networks had a positive influence on patients’ health. In 1979, a large-scale California study showed that people with the lowest levels of social contact had mortality rates 2- to 4.5-times greater than those with strong social networks.3 Since then, research has found that a stable and supportive social network improves health outcomes for people with a wide range of conditions, from heart failure to postpartum depression.
Advantages of Crowd Sourcing
The advantage for a practice of outsourcing to a crowd rather than performing operations only in-house is that the practice can gain access to a very large community of potential workers who have a diverse range of skills and expertise and who are willing and able to complete necessary activities within a short period of time and often at a reduced cost.4 Crowd sourcing allows easier tasks, which would require time and staff, to be done outside of the office, often for a fraction of the HR cost and is building a robust shared economy. Crowd sourcing offers access to expertise that often is not readily available within the practice, and allows widespread sharing of best practices unlimited by geography and competitive landscape. Finally, crowd sourcing encourages the introduction of new ideas from a large pool of individuals with experiences and points of view that differ from those that exist within the practice. Transformational change often comes from collaboration across industries and disciplines. As a perfect example, the practice of anesthesia became immensely safer when safety checks and precautions used by the airline industry were applied to the mechanical setup of the machines.
Healthcare institutions are not in short supply of talent and people interested in improving the care that we provide our patients. However, putting stakeholders together and contending with all the egos and turf protection can be daunting for any innovator or entrepreneur. For the most part, healthcare providers and executives do not have all the skills and training to accomplish collaborative innovation. Also, there is less potential for funding for such projects.
One of the challenges that face the healthcare system is to identify problems, find effective solutions, and then move the project into the clinical environment. Speck et al.5 proposed a concept at research centers where ideas and scientific discoveries are incubated and then segued into clinical practice. This concept, which is in the embryonic stages, has attempted to improve access to resources supporting the acceleration from prototype to clinical use and to reduce academic career barriers to innovation and entrepreneurship.
Stanford Biodesign and the Johns Hopkins Bioengineering Innovation and Design programs are examples of academic programs that have created a curriculum that pulls together academia, industry, regulatory, and business strategy to overcome these obstacles. Despite these efforts, introductory training in rapid innovation techniques is not commonly accessible at academic medical and research centers. In-house incubation centers focus their limited resources on developing the skills of a small, select group of innovators or on supporting the development of ideas brought to them by industry and Pharma.5
Enter the Hackables
Now there is a novel approach developed at MIT referred to as the “Hacking Medicine” model— a scalable and practical approach to integrate interdisciplinary collaboration and training in rapid innovation techniques into the clinical innovation programs of academic medical centers.6 This MIT pilot model has tentacles in the Boston region, which can be readily introduced as a rapid innovation technique for academic medical and research centers.
A Systems Approach to Healthcare Innovation
A systems approach emphasizes the many distinct parts of a system and their interdependencies. In healthcare, this approach shifts the focus from the technical performance of a solution to the solution’s influence on a variety of individual stakeholders and their interactions. By understanding the complex incentive structures that drive adoption of new processes and technologies, nontechnical considerations such as design usability, workflow impact, and economic feasibility can be integrated into early prototypes, thereby addressing key challenges to translation into clinical practice.
According to Asch,7 a systems approach to healthcare innovation has four general stages: identification; description; alteration; and implementation. The identification and description stages create a multidimensional view of a compelling clinical need, following which the alteration and implementation stages build a framework in which to assess the viability of new products and new approaches to providing better care for our patients.
The process of translating academic biomedical advances into clinical care improvements is difficult, risky, expensive, and poorly understood.
This MIT model connects the clinicians who are on the front line with patients with academic researchers who might not be aware of what is involved in patient care. The key difference with this approach is to focus on the problem and keep iterating the dilemma to be solved, versus working toward the solution, which is what so many of us in healthcare focus on. The MIT model has been successful in bringing new ideas to the marketplace and to the clinical setting, where patients benefit from the new developments in patient care. One example in which a hackathon found a solution to the delivery of medication to patients is the PillPack, which was purchased by Amazon for $1 billion.
The process of translating academic biomedical advances into clinical care improvements is difficult, risky, expensive, and poorly understood. Many clinicians who identify healthcare problems do not have the time or expertise to solve the problems, and many academic researchers are unaware of important gaps in clinical care to which their expertise may apply.
The Yale Center for Biomedical Innovation and Technology (CBIT) was established in 2014 to educate healthcare innovators and enhance their impact. In four years, Yale CBIT has affected over 3000 people and established a healthcare innovation cycle as an efficient strategy to guide translational research. Yale CBIT has created or supported graduate and undergraduate courses, clinical immersion programs for industry partners, and large healthcare hackathon events. Over 200 projects have been submitted to CBIT for mentorship, and some of those projects have been commercialized and raised millions of dollars of follow-on funding. The authors present Yale CBIT as one model of accelerating the impact of academic medicine on clinical practice and outcomes. The project advising strategy is intended to be a template to maximize the efficiency of biomedical innovation and ultimately improve the outcomes and experiences of future patients.8
Systems Approach to Innovation: The MIT Hacking Medicine Model
Since early 2012, MIT Hacking Medicine has organized “healthcare hackathons” to bring together interdisciplinary teams to address healthcare challenges in a compressed time frame. These have worked with academic and corporate partners in a variety of settings. We tested this concept by redesigning the traditional “hackathon” competition model prevalent among software engineers.9 Hacking, in this case, refers to the original definition of the term, a “creative application of engineering ingenuity,” and a hackathon is a hacking marathon. The typical software hackathon is a two-day event, in which participants form teams around a product idea and create a prototype. In general, these events are considered educational and entertaining to engineers, and higher value is placed on technical novelty.
In a MIT Hacking Medicine event, we incorporate a traditional hackathon’s emphasis on rapid and intensive innovation but encourage teams to approach challenges in healthcare using the four stages of a systems approach as outlined earlier: identification; description; alteration; and implementation. The scope of the event typically is restricted to a single theme (e.g., rehabilitation medicine, EHRs, compliance, role of cannabidiol [CBD] in medical practice, oncology), which allows us to recruit domain-relevant mentorship and establish relevant criteria for evaluating teams during the event. Events begin with a proposal of unmet clinical needs that participants have identified or witnessed in their experiences as healthcare providers, patients, or researchers. Interdisciplinary teams composed of clinicians, data scientists, researchers, designers, developers, engineers, pharmacologists, PharmDs, IT experts, insurance companies, coders (remember, nothing will fly if the doctor doesn’t receive compensation), and business experts are formed around these clinical needs. Teams are then guided through a systems approach to their chosen clinical challenge.
Identification of the Problem
We ask teams to focus on understanding the context and stakeholder perspectives around the problem. At the start of this hackathon, no time limit is relegated to the solution. Teams identify the relevant stakeholders in the healthcare system (e.g., patients, clinicians, hospitals, pharmacies, healthcare insurance organizations) relevant to a specific clinical need. For example, this model may be an approach to treating orphan diseases or rare diseases. A rare disease is one that affects fewer than 200,000 people. Rare diseases become orphan diseases when drug companies are no longer interested in developing treatments against them because there is no return on the expensive investment required to perform the research and development required to develop treatments for such diseases or conditions. The hackable method can be used to harness the skills and expertise of stakeholders to better diagnose and treat these rare diseases.
This allows teams to understand the current existing barriers to implementing a solution. We encourage teams to closely scrutinize the incentives and preferences of the stakeholders, and to seek early feedback from these groups. At this time, the stakeholders can express their concern over implementation of new technology or new treatment options. The teams encourage discussion of incentives and detractors of the stakeholders and solicit early feedback regarding why a project will or will not work. It is at the identification stage that solicitation of those in favor and the nay-sayers of the project can express their opinions without any judgment from the others on the team.
Giving Weight to the Problem
Following discussion of the problem space, teams analyze and provide a numerical value to the various issues and concerns prior to proceeding with the project. At this time, the highest value points of intervention among the identified key stakeholders are discussed or placed on a flip chart or white board. In systems thinking methodology, these highest value points are known as the levers that allow for the creation of a virtuous cycle of change.6 Healthcare has to make transitions to be truly effective in the modern world. A change in paradigm is needed. This requires that value, defined as the health outcome for a particular medical condition per unit of cost expended, must be applied and added to healthcare; and healthcare itself must be treated as a business that performs in a competitive environment to ultimately provide client or customer satisfaction.10 Teams should specifically target particular stakeholders to be the likely users or payers for the solution they will develop and identify the needs that are addressed by their particular innovation. The teams discuss the obstacles for implementation with the various stakeholders and how those roadblocks can be overcome.
Solution Phase of the Project
Based on the incentives and needs identified in their analysis, teams design initial solutions to their selected clinical challenge. Teams are encouraged to prototype potential solutions for unmet needs as proposed to the existing standard of care. Expert mentors are recruited from patient advocacy groups, local hospitals, and industry to supplement, evaluate, or assist teams. With rough prototypes, teams can receive feedback directly from end users, such as patients, doctors, hospital administrators, and payers, and rapidly review their proposed solutions. Teams talk about the potential impact on relevant stakeholders and the impact on the workflow in a clinical setting.
Implementation: When the Rubber Meets the Road
Teams are asked to present a concise summary of their clinical challenge, stakeholder analysis, and proposed solution at the conclusion of the hackathon weekend. In addition to directly addressing the technical feasibility of their proposals, teams must demonstrate a plan of action for implementing, distributing, and measuring their solution. Final team evaluation is based on a comprehensive, systems-level description of the need and the likelihood of successful implementation.
Table 1 provides an example framework for a systems team approach that targeted implementation of a telemedicine project for a clinical practice.
Bottom Line: Hackathons are fairly new as a mainstream approach in healthcare innovation. This systems model offers a practical addition to ways of coming up with new technology, new ideas, new treatment, new diagnostics, and new improvements in workflow in the practice of medicine. The hackathon approach collects all of the stakeholders and identifies many of the obstacles before launching a new project or idea. Now all those parties who have a vested interest in the project have voiced their opinions, including their rejection of the idea, before launching and spending time and wasting money on a project that might be doomed to failure. Now there is a model for creating a four-phase structured opportunity for interdisciplinary collaboration. Happy hacking!
References
1. Siefert AL, Khalid A, et al. The Yale Center for Biomedical Innovation and Technology (CBIT): one model to accelerate impact from academic health care innovation. Acad Med. 2019;94:528-534.
2. Howe J. The rise of crowdsourcing. Wired. June 1, 2006.
www.wired.com/2006/06/crowds/.
3. Liu L, Sidani JE, Shensa A, et al. Association between social media use and depression and U.S. young adults. Depress Anxiety. 2016;33:323-331.
4. Ostrovsky A, Barnett M. Accelerating change: fostering innovation in healthcare delivery at academic medical centers. Healthc (Amst). 2014;2(1):9-13.
5. Speck RM, Weisberg RW, Fleisher LA. Varying goals and approaches of innovation centers in academic health systems: a semistructured qualitative study. Acad Med. 2015;90:1132-1136.
6. Gubin TA, Iyer HP, Liew SN, et al. (2017). A systems approach to healthcare innovation using the MIT hacking medicine model. Cell systems. 2017;5(1):6-10.
7. Asch DA, Terwiesch C, Mahoney KB, Rosin R. Insourcing healthcare innovation. N Engl J Med. 2014;370:1775-1777.
8. Siefert AL, Cartiera MS, Khalid AN, et al. The Yale Center for Biomedical Innovation and Technology (CBIT): one model to accelerate impact from academic health care innovation. Acad Med. 2019;94:528-534.
9. Wang JK, Roy SK, Barry M, et al. Institutionalizing healthcare hackathons to promote diversity in collaboration in medicine. BMC Med Educ. 2018;18:269.
10. Koch U, Stout S, Landon BE, Phillips RS. From healthcare to health: A proposed pathway to population health. Healthcare. 2016; 4(4):291-297.
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