Intellectual Property, Reinsurance, & Microinsurance

-Least developed countries have a risk of lacking proper medical data for poor communities.

-Reinsurers can insure health microinsurers, but are limited to the role of insurer.

-Numerous public health issues in remote, rural villages throughout the world. 

  Intellectual property can be created by community solutions to environmental issues such as the need for clean water. An example could be a certain herb that effectively treats an epidemic, and the data from the effectiveness can become part of a magazine article or technical journal. The rights to the story and/or research study can become intellectual property. If the reinsurance company finances this type of application of knowledge, it can receive part of revenue from the intellectual property.

  This type of information combined with the metadata can be compiled with data analytics. Forecasting can be made on public health improvements in the context of the affiliated microinsurance data sets and comparable data sets.

    By encouraging reinsurance (insurance for insurers), microinsurers can take on more clients who may have serious medical conditions. This is the foundation for proposal for the management of medical data in least developed countries.

THE PRESENTATION:

   Villages and small communities around the world face challenges every day.

Residents of these communities may have face medical issues.

Sometimes, changes in the environment like filtering the local water supply can improve medical issues. 

Microinsurance for health benefits can provide the resources for the medical issues of subscribers. Reinsurance, essentially insurance for insurers, can cover multiple microinsurers.

Metadata, the data without the identity of the subscribers in the various plans, can be used by the reinsurer for determining ratemaking for the microinsurer’s reinsurance policies as well a predictive analytics.

  The Problem and the Proposed Solution:

Problem:

      Improving the local environment (water resources and other issues) can improve health.

However, microinsurance focuses on insurance services.

Proposed Solution:

   The stories about community success….overcoming obstacles to generating clean, affordable water can be intellectual property which can be licensed for technical journals in the form of research studies or novels in general. The reinsurer can make investments in these types of projects and have a financial return on a small portion of the revenue from the publication.

   What is proposed in a free online course for how communities can create these types of projects as a means for financing environmental projects for improving health. The combination of the reinsurance-microinsurance metadata and the success stories create a multidimensional dataset.

• From this, the success in public projects employs unconventional to inform primary health care performance improvement.
• The minimal investment in solutions becoming intellectual property and a source of revenue provides improved measurement methods that are low cost, fit-for-purpose, shareable across information systems, and streamlined for data collectors.
• Leverage existing systems, networks, and workflows to streamline the collection and interpretation of data to support meaningful use of primary health care data.
• From the machine learning mentioned in the first paragraph, the solution provides actionable, accountable, and accessible insights for health care providers, administrators, and/or funders that can be used to optimize the performance of primary health care.
• By means of frontline healthcare workers providing information on public health needs, there can be a way to balance the opportunity for frontline health workers to participate in performance improvement efforts with their primary responsibility as care providers.

Least developed countries (LDC) in that it provides creates multiple levels of medical data as well as forecasts of public health and medical data. I could impact their lives directly because it incentives the creation of public health solutions. In terms of microinsurance and reinsurance, there is a possible source of revenue from the intellectual property rights of the public health solutions.

The idea appears to be innovative as well as feasible. The input of diverse communities is key to how the solution works.

   I believe the project could help many people. The Challenge may help the project in terms of finding the right people who would be able to implement the project in various countries.

   It could be catalytic in that it gives an extra benefit for health insurance service in poor countries. It implements the public health solutions as intellectual property as a possible revenue source which in turn encourages the collection of public health data. Combining this with microinsurance metadata and comparable datasets, machine learning can be implemented to analyze the entire picture of the medical data.

The impact goal in the next year and the next five years as well is to create several successful pilot programs. The project is complicated and creating the program is the key milestone.

   The impact goal would be measured by the data that can be collected, how accurate forecasts are, and the ability of the project to encourage public health projects as well.

   The theory of change is that health data is collected in ways that encourage community development. This is because the goal is for insurers to finance the publication of community development successes, especially in terms of public health.

  From the perspective of the publication of successful solutions, a theory of change is also that each solution in pubic health reduces risk, creates a pathway for future public heath solutions, and allows for predictive analytics to be run on possible outcomes. Each time a community and insurer uses this type of protocol, more accurate data analytics may be able to be compiled which in turn can assist front line healthcare professionals.

The technologies are essentially behavioral technology, ancestral technology, and machine learning.

  Starting in reverse order to the list above, machine learning can take the quantitative components of public health solutions and metadata from the microinsurers to create a predictive analysis of a community or communities.

  For example, a community may only have a few people who smoke cigarettes. A local magazine could an article on the numbers of people who gave up smoking with a wellness and fitness program. The lower number of people who smoke can be combined with the metadata to generate a forecast of future health outcomes in the community.

  If a traditional application of an herbal remedy can help some community members quit smoking, that would be an example of ancestral technology.

  If the overall program above encourages the compilation of data from successful solutions, that would be an example of behavioral technology.

  The collection of data in terms of metadata is collected by the microinsurers. The compilation of the metadata is envisioned to be done by reinsurers. The solutions data or success stories would likely be collected by the reinsurer.

The solution is a free online course for Least Developed Countries and other countries with the greatest demand for microinsurance. By teaching the practitioner in these locations, it is inclusive and diverse in nature.

  Revenue from the publication of community success stories can assist in the funding of multiple microinsurance/reinsurance policies in a small way by means of reinsurers investing part of their portfolio in the technologies needed for communities to publish and receive royalties for community success stories. This could even be accomplished by means of a magazine of successful solutions, with revenue from advertising sales in the publication.

 The metadata of the microinsurers and the data of published research and narratives creates a combined database that can benefit communities. 

  The plan to become financially sustainable to for creating a way for revenue from the publication of community success stories can assist in the funding of multiple microinsurance/reinsurance policies in a small way by means of reinsurers investing part of their portfolio in the technologies needed for communities to publish and receive royalties for community success stories.

 The metadata of the microinsurers and the data of published research and narratives creates a combined database that can benefit communities.  The revenue model for the solution assists in benefiting the community.

There are no examples at this moment of how the plan has achieved financial sustainability at this moment.