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Peter A. Berman, Rajeev Ahuja, and Vijaysekar Kalavakonda
FIGURE 12.3
India: Distribution of Members and Claims, by Age
14 12
share (percent)
10 8 6 4 2
0
80 >
5
–8 76
0
–7
–7
71
5 –6
66
0 –6
61
5 –5
56
0 51
5
–5 46
–4
0 41
5
–4 36
0
–3 31
5
–3 26
0
–2 21
5
–2
–1
16
0 –1
11
–0 00
06
5
0
age group (years) share in membership
share in claims
Source: Authors’ own construction using the health insurance dataset.
(Rs 18,178). With total claims by individual and group business disaggregated, the female claims ratio is lower than that for males in individual business but higher in group business. This trend is true in all three geographical groupings: metros, other metros, and nonmetros. This could perhaps be due to a stronger female voice/power profile when women are insured as a part of a group rather than as individuals. The average claim amount for both females and males is lower in group business than in individual business. In terms of age distribution, too, the dataset is fairly representative. Around 77 percent of all insured individuals belong to the age group 0 to 45, but they file only 64 percent of total claims (figure 12.3), implying cross-subsidy from younger to older members. Furthermore, group members are younger than individual members. In terms of the cost of treating various illnesses, the dataset is well represented. Claims information is disaggregated into 30 types of the most important illnesses and covers both treatment costs and frequencies. Figure 12.4 shows the costs of the 10 most expensive treatments, which account for about 16.4 percent of total claims—about 10 out of every 63 claims per 1,000 members. The treatment cost varies considerably across cities. This is well-captured in the dataset, as shown in figure 12.5. For example, treatment cost is highest in Mumbai and nearly half as costly in Surat.