How do policy makers choose one way or another in a scenario of unlimited needs and meagre resources? Follow the policy that provides the maximum benefit for the entire population. Well, this is not always that simple. In health, for instance, even top-notch policy makers find themselves in a gridlock on how to spend money to control disease. What are the right outcomes when human lives are at stake? To what extent should social outcome and monetary turnover be considered as relevant factors while saving lives? Why invest in controlling one disease rather than another?

 

For instance, let’s think of a fundamental divide in spending in public health, the one between communicable and non-communicable diseases. As the name suggests, communicable diseases are those that can spread from one person to another through various sources and carriers, like Tuberculosis, HIV, Malaria and Ebola. Non-communicable diseases cannot spread from one person to another, examples of this include cancer, diabetes and genetic diseases. Now, we all know that illnesses of all types reduce the quality and productivity of an individual’s life. It is clear that communicable diseases can affect anyone of any age. It is also evident that communicable diseases require a large network and massive spending in order to control the spread of the disease to the entire population.

 

Are we, therefore, saying that the cost of treating non-communicable diseases should be carried by the individual alone? Which factors, then, are to be considered by national institutions in order to contribute to medical treatments efficiently? If we spend on both how do we decide how much to spend on each?

 

Cost Benefit Analysis (CBA) is a customary answer. It is a method of analysis where the costs of an intervention are weighed against its benefits. For the CBA to be done accurately, all the factors which will have an impact need to be considered. The main factors include the cost of the inputs and the research cost, but there are many hidden factors such as the loss of income of a patient, loss in productivity due to a side effect of a medication etc. Several interconnections among costs and benefits make doing an accurate CBA an extremely difficult task.

 

Let us do a straightforward example of CBA to determine our spending on disease prevention. There are two diseases, one is a communicable disease and the other is a non-communicable disease. We assume that the two diseases infect the same numbers of people; we also imagine that we encounter equivalent costs of treatment.

 

Option A. If we use all our money to treat the non-communicable disease, the cost, then, has been the cost of treatment and the benefit is the number of lives saved. Option B. If all the resources are used to contain the communicable disease the cost is still the cost of treatment, but the benefits consist in the number of patients saved and in the aggregate amount of people who have been prevented from being infected. An intuitive comparison between Option A and Option B suggests that resources should be invested to combat communicable disease.

 

Alas,an important aspect of diseases is that they are not always mutually exclusive. Modelling, however sophisticated it may be, is not real world policy-making, where a number of contextual variables affects the costs and benefits of a program. It is not always possible to account for all the variables, simply.

 

To continue with the example. Let us imagine that a patient with a non-communicable disease may be at a high risk of contracting a communicable disease due to his weakened immune system. Even if not fatal, non-communicable disease may have a severe impact on the person’s ability to be productive. Evidently, the cost on society is not just the loss of one individual’s productivity, but it also includes his care for the rest of his life.

 

In India, this was noticeable in the Revised National Tuberculosis Control Program (the national TB control program). The program focused all its resources only on controlling the disease but an important factor was ignored. People who have disease, which compromise their immune system, such as diabetes, are at a higher risk of getting TB. The current program makes no provision for this. The costs for controlling TB have not been properly assessed. A more nuanced CBA of the situation, one that took into account the correlations between TB and other diseases, would have given a better understanding of the true costs involved.

 

The draft of the Indian government’s National Health Policy 2015 presents the current health scenario of the country, the goals that it aims to achieve and the challenges currently being faced by the health system. One of the major concerns of the government is that the cost of care is very high for patients even though government hospitals and medication for many diseases is free. An illness can impoverish the entire family pushing them further into the clutches of poverty. Some of the obvious solutions to this problem would be to increase the number of hospitals and provide for better medical insurance but this is not the complete solution. A nuanced CBA would show that a major part of reducing cost of disease is preventing disease. In the case of communicable disease investment in a cleaner environment, which includes safe drinking water and better air quality is essential towards reducing disease and the cost of care.

 

We may never be able to reach an answer based on objective criteria alone but a nuanced CBA, which incorporates various direct and indirect costs of a disease, may help to create a framework that will help answer these difficult questions.