Background
Room for Innovation
I would like students to focus on the needs of lean, or resource poor, countries and create medical technology that is inexpensive, accessible, and durable. According to the Curb Cut Effect, this technology can most likely be scaled to other communities with similar needs.
Human Development Index
The terms “First-world”, “Third-world, “Developed”, and Undeveloped” are outdated terms to describe a country’s place in the world as solely based in GDP. The Human Development Index (HDI), as stated by the United Nations Development Programme (UNDP), “was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone.”4 The HDI is calculated from life expectancy at birth, access to education, and Gross National Income (GNI is similar to GDP but gives a better picture of standard of living). For example, Norway has a 2019 HDI value of 0.957 and Niger has a 2019 HDI value of 0.394. Norway is #1 in the HDI Ranking and has high levels of life expectancy, education, and GNI. Niger is 189 in the ranking and has very low levels of life expectancy, education, and GNI.5 Adjustments can be made to the HDI to take into account human development inequality, poverty, gender inequality, planetary pressures, etc.
Gini Coefficient
The Gini Coefficient (GC) compares a graph of perfectly equal wealth distribution in a country to the actual wealth distribution in that country (the graphical representation of the income distribution in country is called The Lorenz Curve).6 The comparison yields a number between 0 and 1 (sometimes represented as a percentage). A 0 (0%) value indicates perfect equality and a value of 1 (100%) indicates complete inequality. For example, Norway has a GC value of 0.276 (27.6%) and Niger has a value of 0.343 (34.3%).7 Therefore, Norway has better wealth distribution than Niger. This value, of course, has limitations. The GC is a broad brush and can misrepresent the factors leading to wealth inequality. It is also very important to recognize the different between income and wealth and make sure that the calculated GCs being compared are consistently calculated. Income has more to do with labor markets while wealth has more to do with the balance of power. Therefore, this statistic should be used along with other data and models.
Lean vs. Fat
The HDI and GC are useful for identifying what are known as “lean” and “fat” countries. Since lean countries have less resources than fat counties, they “approach consumption and production with scarcity in mind”.8 Lean economies are perfect to focus on for medical innovation because there is a great need for inexpensive, accessible, and durable technology and they can avoid some of the growing pains and infrastructure problems present in fat countries. Americans have more money, more infrastructure, and more access to medical care while Africans “waste less food and water, owe less money, and maintain a regional carbon footprint that is that lowest in the world.”9 Conversely, Americans are more vulnerable to financial crises while Africans are more vulnerable to pandemics.
Innovation happens in both types of countries, but looks very different. Women in Japan, a fat country, frequently waste a lot of water in public restrooms because they flush multiple times in order to cover up embarrassing noises. A Japanese company, Toto, created the Otohime (Sound Princess) which simulates the sound of a flushing toilet. These devices were installed in public restrooms and became a best-seller in Japan. Halfway around the world in the lean country of Kenya, a very different bathroom issue kickstarted innovation. “Flying toilets” are bagged refuse that are thrown as far as possible from settlements in order to avoid water contamination and night time crime around public toilets. To help illuminate this form of pollution and help African communities, The Umande Trust built a biodigester which is inexpensive and doesn’t use water. It also creates biogas (mainly methane and carbon dioxide produced during the breakdown of waste) which can be used as a reliable source of power in the community.10
5 Medical Challenges for Lean Countries
There are five typical challenges that innovators face when designing medical technology in a lean country.11 One, there is little reliable infrastructure. An electricity grid could be unreliable or nonexistent. Water quality and supply is low. Roads are poor and transportation mostly consists of walking long distances. Two, local medical staff is not trained to use and maintain the equipment. Three, equipment maintenance is too difficult and expensive. Parts may be difficult to obtain. Four, equipment consumables are expensive or difficult to obtain. Sterility standards often requires parts to be replaced between patients. Five, the equipment is not durable. Because the equipment is often used in harsh, extreme, or outdoor environments which they are not built for, they don’t last long. These five challenges need to be considered when designing medical technology for use in lean countries.
The Adjacent Possible
Do you know where your medical records are? Do you still have your birth certificate? Millions of people throughout the world can’t say yes to these questions. Enter Khushi Baby, the result of many years of hard work and collaboration at the Yale Center for Engineering Innovation and Design.12 This small device takes advantage of a relatively new technology called Near Field Communication tags (NFC) to store vaccine records without the need for batteries. NFC tags are typically small stickers.13 In this case, the tags were integrated into the kala dhaga, a black thread traditionally used in some Indian communities to ward off the “evil eye”. Kushi Baby has become very popular in underserved Indian communities as an easily integrated way to decrease infant mortality. This did not happen in a vacuum. The design team utilized something called the Adjacent Possible, a phrase coined by scientist Stuart Kauffman in 2002.14 While he was referring to the process of Evolution, the phrase applies to all successful innovative processes. Basically, most innovations are small steps forward which rely on previous innovations. In the case of Kushi Baby, the step forward in medical care relied on the recently developed NFC technology. NFC in turn relied on RFID technology. Brilliance is rarely a huge jump forward with a single burst of inspiration, but is actually a series of small hops. In order for my students to be truly innovative, they will need to rely heavily on the adjacent possible. They will need scaffolding into the engineering process and guidance from field experts.
Diffusion of Innovation Theory
The Diffusion of Innovation Theory describes the spread of technology and new ideas through a population.15 There are five adopter categories that can be considered when trying to popularize new technology. The innovators take risks and try the technology first. The early adopters are leaders who enjoy adopting new ideas. The early majority feel comfortable following the early adopters. Most of the population falls into the early majority category. The late majority will wait to find out more information about how well the technology performs. The laggards are the most reluctant to adopt new technology and hold out the longest. The public adopts or rejects new technology based on the perceived value of the new idea, compatibility with existing beliefs, difficulty of use, and proven effectiveness and safety.
Vulnerable Populations
Vulnerable populations abound in San Jose, CA. My students can choose to focus on geriatric populations, newborns, those with vaccine allergies, etc. For introductory purposes, I will focus on the homeless population in this area because it has become more visible in the past few years. According to the 2019 City of San Jose Homeless Census & Survey, the homeless population increased by almost 2,000 people between 2017 and 2019 in San Jose. This population has a high rate of psychiatric conditions, and the consequent drug and alcohol abuse, which rarely receive adequate care. Numerous studies from the 1980s to the current day state that “People who are homeless have higher rates of illness and die on average 12 years sooner than the general U.S. Population”.16 This problem is widespread and was greatly exacerbated by a massive pandemic. What can we possibly do?
Demographics for James Lick High School and San Jose, CA
In order to properly serve my students, it is important to understand their demographics. James Lick is a small school (approximately 1100 students) composed mostly of Socioeconomically Disadvantaged (86%) and Hispanic students (80%). We also have fairly high populations of English Language Learners (18%) and Students with Disabilities (15%). A large percentage of our population (20-24%) tests below average on the California Assessment of Student Performance and Progress Research and Inquiry section, so they will need a high level of scaffolding in order thrive during this project.17
San Jose is a large and diverse city (population estimate 1,021,795). According to the 2019 US Census, San Jose’s ethnic breakdown is White 39.9%, Black or African American 3.0%, American Indian and Alaska Native 0.6%, Asian 35.9%, Native Hawaiian and Other Pacific Islander 0.5%, Two or More Races 5.3%, and Hispanic or Latino 31.6%. English is the primary language in 43% of San Jose homes while 57% speak another language. Poverty levels in San Jose can be deceiving because large areas of San Jose and the rest of Santa Clara county have low levels of poverty and high levels of education (High school graduates 84.6%, Bachelor’s degree or higher 43.7%, Persons in poverty 8.7% in 2019). However, the area of San Jose that is of special interest, typically called “East Side”, has a high level of poverty (36% child poverty in 2010). Poverty continues to be tied to race and education in California (22.9% Latinos in poverty and 30.6% Adults without a high school diploma in 2018).18 Most of my students are part of or directly in contact with someone from a vulnerable population.
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