Expanded Medical Underwriting in Jordan: A Pilot for Other Emerging Public Health Insurance Markets
By Lisa Beichl
International News, November 2021
Countries developing universal health care via an insurance vehicle face a variety of challenges. Deciding which benefits to include, where to proactively manage health, and how to reimburse network providers are just a sampling of the issues governments concurrently manage.
Optimal choices are data-driven responses. For example, high rates of cervical cancer or increasing narcotics prescriptions are trends that can be managed through product changes, modified network payment structures, or even employer based outreach. This kind of information is typically gleaned from established health insurance claims data. However, in emerging health insurance markets, this level of granular claims data is largely missing. It is difficult to manage medical trends when the root causes are unclear.
Lack of Granular Claims Data
Insufficient claims data increases dependence on country specific studies. Economists evaluate health risks and non-communicable diseases (NCDs) and measure both prevalence and estimated health care costs. While informative, these studies may not fully reflect the health system factors impacting corresponding medical trend increases.
For example, let’s say that public insurance covers insulin provided in the public sector primary care centers. However, the primary care centers in the northern region carry an insufficient volume of medications, and often the waiting time to see a physician is very long. In this instance, the government can analyze the costs of adding a private primary care network for diabetics in the northern region, increasing compliance and reducing overall costs of care due to non-compliance.
Heavy Focus on Health Financing, Not Risk Management
Emerging health insurance economies emphasize health financing and are less experienced with common insurance tools that help manage the risk, not just the costs. For this reason there is insufficient time spent developing an appropriate data infrastructure to identify and manage population health. For example, claims data demands consistent and reliable coding, yet there are few countries developing this infrastructure outside of high level use of Diagnosis Related Groups (DRGs). Rwanda, for example, is one of the few emerging markets that developed a national health insurance coding strategy and trained coders to accurately document health treatment patterns through both diagnosis and procedure coding.
Adequate and accurate claims data provide important detail on the cost of medical treatment, but also on the factors impacting medical trends. For example, in some countries there is an undersupply of specialists. As a result, general practitioners often treat complex specialty cases in the inpatient setting with variable results. Claims data can measure treatment variability across provider specialties and identify high risk diagnoses to immediately refer to a specialty center or a Center of Excellence.
However in many countries, there is still limited information to understand if the benefits are meeting population health needs, and if there opportunities to proactively manage health outcomes today and manage medical trends.
In Jordan, this data gap is significant. While the government focuses on developing long term health insurance claims data solutions, in 2019, an expanded medical underwriting pilot aimed to understand if this common insurance tool could be adapted to collect meaningful risk and public health system utilization data to fill an information gap was created.
Expanding the Questionnaire: Piloting Medical Underwriting in Jordan
Typical underwriting forms include self-reported data on personal health history. This information is used to determine insurability and advise accurate premium setting. While private insurers may use medical underwriting data to deny medical care or determine an individual “uninsurable,” the public insurer may use the exact same data to more accurately price the benefits, estimate appropriate risk pooling levels, and develop programs and tools for the uninsurable to maximize health outcomes.
When the concept of medical underwriting was discussed with the non-governmental organization (NGO) supporting Jordan in developing social health insurance, it was a very difficult sell. There is bias against health insurance tools that are widely used in the private sector. After a series of long discussions, the project was approved, however, nowhere could the term “underwriting” appear, in spite of the fact that it is an evidence-based methodology. As a result, it was named a “Health Needs Appraisal.”
NGO concerns included fear that individuals would not provide personal information, however, 99 percent of the respondents completed the full questionnaires and when asked if they would like to contribute to future government health programs, responded in the affirmative.
In addition to typical insurance underwriting questions including height and weight, recent hospitalizations and presence of non-communicable diseases, further questions highlighted more detailed family risk factors, health literacy levels, as well as the WHO-5 mental health questions. In an effort to more fully comprehend country-specific barriers to primary care, detailed questions were added.
To help estimate future health burden, questions were organized to score individual risk levels regarding important NCDs in Jordan. For example, Chronic Kidney Disease (CKD) is prevalent and expensive. A member was identified as a future CKD risk if he/she had at least three of a series of risk factors including diabetes, and Body Mass Index (BMI)>30 (obese range).
Knowing your future risks is important. When linked with other risk factors including low health literacy levels and mental health risk, governments have some idea of future budget challenges and prevalence rates. For example, if:
Members with diabetes cost 0.15 more than baseline,
Members with low mental health wellbeing cost 0.05 than baseline, but if
Members with diabetes and low mental health cost 0.60 more than baseline, then the government has a much better idea on which current and future health risks to proactively manage.
Unfortunately, the underwriting pilot in Jordan closed prior to completion due to COVID-19, however, preliminary data are promising.
Moving Forward
The full results of the pilot point to important issues in health system use, low health literacy levels, and very high inpatient admissions, and all of these impact medical inflation. If the government simply finances benefits without understanding rationality of system use, it will be forced to respond to trends financially rather than addressing issues from a population health perspective.
The pilot in Jordan demonstrated proof of concept. Underwriting can be used to collect longitudinal data and provide context to the multiple factors impacting health system use and ultimately medical inflation. Other countries selecting an insurance vehicle to achieve universal health coverage may also consider a culturally appropriate underwriting approach to begin the process of data collection for population health management.
Statements of fact and opinions expressed herein are those of the individual authors and are not necessarily those of the Society of Actuaries, the newsletter editors, or the respective authors’ employers.
Lisa Beichl is a global health consultant and owner of Transparent Borders LLC. She can be reached at lisa@transparentborders.com.