How to Avert Catastrophic Expense in General Ward Patients of Public Hospitals: Some insights from Tertiary Care Hospital

Introduction

Affordable health care concept is not fundamentally different from what was conceived as per Alma Ata declaration about seven decades ago. World is still struggling to meet that great vision. During all these years, now we have better understanding and frameworks in the form of Universal Health Care Coverage. Lot of emphasis is now on equity and fairness in financial contribution. This is one of the important goal of the health systems. All countries are doing efforts to fill the cube of Universal Health Coverage (UHC), as per their situation and capacity. It implies to cover more population for health services, expand the scope of the health service interventions, and provide financial protection in a way to minimize Out of Pocket Expense (OOP). OOP has been given due importance in UHC. High OOP forces poor people either NOT to get treatment when sick OR leads to some financial catastrophe, which is unfair and inequitable.

One of the fundamental question is how to measure this financial catastrophe. Economists use two cutoffs for this: either >10% of total expenses on treatment OR >40% of capacity to pay, that excludes expenses on food item from total expenses. Look at this hypothetical example to appreciate and feel these definitions. In this table there are three categories of families: Low expense, middle expense and high expense. Total expense has been divided into food and non food groups. Catastrophe cutoff values have been calculated applying both definitions.

There is a Low expense family, who barely spends one USD on food per day. Any medical expense more that 5-6 USD will cast catastrophe. Even simple episode of cough and cold or diarrhea will incur expense more than this. There is no buffer available. These families struggle to save on food and other items. For middle expense group, there is some buffer available, but any admission of 1-2 days will cost more than 50-80 USD and incur catastrophe. Higher Expense group have higher buffers. But they may also experience catastrophe if not protected. Chemotherapy for a cancer treatment for one year at 4 weekly intervals may cost more than 2500 USD every month. !!

Different community based surveys have used these cutoffs and have used different methods to define the expenses. Despite these limitations, useful data can be generated to see impact of various policy measures on OOP. This table shows OOP in different countries differ a lot. (Table 2) Part of this variation is due to differing methods and definitions.

Countries chose different Financial protection mechanisms depending on various socio political factors. But except for few countries like Thailand, success rate was very limited. China implemented New Cooperative Medical Scheme. It was not successful to address CHE. Inclusion of essential medicines and supplies was beneficial but not fool proof (13). There was partial success in countries like Mongolia(14), South Korea (15), Nigeria (16) and India (17), with various insurance schemes. Thailand achieved success (18). But they have traversed long tedious path to strengthen the health systems and streamline various financing mechanisms. Thus, countries should continue efforts in this direction.

One of the concerns is how health facilities and hospitals can contribute to minimize CHE and OOP? With this in mind Jitali Randhawa et al did a small study to understand whether financial protection given to families has some impact on OOP or not? This paper tries to answer the question: how hospital administration can improve financial protection?

Methodology

Data was collected from 190 patients from general wards of tertiary care institute. There are two types of wards in the institute: General and Private. Low income families use General wards. We presumed catastrophe to have occurred if families had to take loan or dispose off their assets to get the treatment. We focused only on the direct expense on medicines, supplies, diagnostics, and user-fees. We used the term “Poor Free” as measure of financial protection. In India, for families with defined cutoff of income and assets, poverty line is defined. Families below this line are called Below Poverty Line (BPL) families. Such families are given BPL cards and they are entitled for many benefits including free treatment. Even such families have to incur expenses on medicines, supplies and diagnostics if these are not available in the health facility.

Daily visit was made to wards to enlist patients scheduled for discharge, review the files for treatment received and interviewed patients for expenses incurred, financial protection received and any evidence of catastrophe. There was no recall bias due to this method.

Results

Table 3 show mean total medical expense with 95% CI. First column defines the two groups that were compared. For poor free status, Group 1 is those who were not poor free and Group 2 were poor free. Mean expense was substantially less among group 2 ( Poor free) than group 1 (those who were Not poor free.) Similarly, those who availed loan or disposed assets incurred larger expense.

Kernel density plots visually show less expenses among poor free (Figure 1) and higher expenses among those who took loan (Figure 2) or disposed assets. (Figure 3). As financial protection and catastrophe can interact, we analysed the data to see this interaction. Figure 4 illustrates interaction of these variables.

Yellow and Red boxes show catastrophe in form of loan or disposing assets. Adjoining boxes show No catastrophe. Expenses among groups with Catastrophe were higher. First two boxes in each plot are for NOT poor free and last two are for poor free.

We found that both ‘poor free’ and ‘not poor free’ had to incur catastrophic expense. Further analysis on nature of expense and utility of financial protection, showed that poor free had very less expense for diagnostics, supplies and user fees. For medicines expense was not different for poor free compared to not poor free (data not shown). For catastrophic groups, expense was substantially higher on medicines and supplies.

Conclusions and Recommendations

In summary, our study showed that BPL status helped to reduce medical expenses on user fees, diagnostics and supplies. We also found that even BPL families had to take loans and dispose assets for treatment. We propose that health facilities should work on to identify top 10 costly conditions and develop comprehensive strategy which takes into consideration expected cost of treatment, per capita income or expenditure and does not depend only on BPL status.

Hospitals should devise mechanisms to consider per capita income and/ or expense and expected expenses on treatment and provide protection for atleast more costly disease conditions. At the same time, hospitals should work towards cost minimization by doing medical audits of costly disease conditions and work out comprehensive strategies. This may add value to existing financial protection strategies.

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