How we helped a 100M investment fund make a data-driven decision

Main goals of the research

In 2016, a $100M investment fund turned to Singularex to conduct research on global digital health markets.

Our goal was to evaluate 92 countries and identify those which had the highest potential for investment and required new solutions in this field. Six data scientists conducted this research for two months.

Technologies and sources used

We developed our own methodology for calculating healthcare system efficiency. The composite index consisted of the Outcomes index developed by the Economist Intelligence Unit Healthcare; indicators developed by the World Health Organization (WHO); and a set of data out of the Human Development Report based on public opinion polls.

Then, relying on the data for “Healthcare Expenditures Per Capita” on the website of the World Bank, we determined the optimal level of investment for the maintenance of one utility unit of the healthcare system and ranked countries by return on investment.

Some Digital Health market insights

The dependence of public satisfaction on medicine and healthcare expenditures

It is commonly believed that the higher the cost, the better the quality and the higher the level of public satisfaction with medicine. However, according to our research, this dependence is not so strong.

Thus, in the USA, the UK and Canada, the satisfaction level is 77%, and expenditures per capita are $9,400, $3,940 and $5,300 respectively (2014).

The life cycle of healthcare systems

We concluded that every healthcare system can be in one of four phases of development, according to S-curve theory.

We studied the countries at the opposite ends of the S-curve – the most prominent representatives of the “Emergence” and “Decline” periods – and pointed out their key particularities and preconditions.

The dynamics of healthcare systems efficiency

The arrangement of the countries on the life cycle curve allowed us to analyze the dynamics the healthcare systems’ efficiency over 9 years (2005-2013).

Efficiency dynamics allows us to trace the influence of crisis developments on specific countries.

For example, in 2008, the global financial downturn affected the healthcare sector. The return on investment in developed countries started to decline. That caused a love in healthcare systems from the “Stagnation” to the “Decline” stage over the next 6 years.

We concluded that countries in the “Decline” and “Stagnation” stages demonstrated the greatest need for transformation, while “emerging innovations” were appropriate for the
countries in the “Emergence” and “Growth” periods. Introducing these innovations will enable the countries to continue their development and bypass the “Decline” stage.

Innovation capacity of the countries

Based on the analysis of the S-curve, we selected the countries with the highest efficiency indicators in each period of the lifecycle, then ranked them according to the Global Innovation Index (GII) calculated by Cornell University.

We identified three types of countries:

• A high GII and a moderating rate of development – leaders of innovation.
• A high rate of innovation and a low value of the current indicator – candidates who are “innovators” or “dark horses”.
• A low value of GII and moderating dynamics – conservatives that do not develop in this field.

Then we ranked the countries – leaders and “dark horses” – by the level of innovation capacity and identified the most attractive ones for investment.

Country profiles

In the study, special attention was paid to identification of the countries’ cities-clusters that have the highest concentration of start-up “crowds” and developed educational and scientific sectors.

General information was reflected in the “Country Profiles”:

The result of Digital Health Markets research

Based on the results of our research, we determined the top 10 countries that were most promising for investors and formed their profiles. The investment company studied the profiles and chose four countries with the highest potential. We prepared a list of the most promising startups and their contacts. This how the investment company made a data-driven decision and invested in the most perspective digital healthcare startups and companies.

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