The research article discusses the various measurement concepts and epidemiological transition in the form of changing disease burden in India and how is that going to affect the health insurers in days to come.
At a time, when India is going for universal health forits marginalized population, there is an urgent need for some economic evaluations of this mammoth health intervention. Quality adjusted life years (QALY),healthy adjusted life expectancy (HALE),Quality adjusted life expectancy (QALE), Disability adjusted life years (DALY) and Life years gained are all common outcome measures that gauge the twin risks of mortality and morbidity,and in the process, leverage quantity for quality of health.
It is very interesting to understand what constitutes risk in health insurance particularly when we have to insure a large group or a community. We all are aware that advancement of technology has commuted mortality with morbidity. The above phenomenon has given rise to a new risk in the form of “Disease burden” now considered a good indicator of health risk. It is the burden that a particular disease process inflicts in a given area as calculated by cost, morbidity, and mortality. The quantified version is called‘the summary measures of population health’.
The measures broadly fall into two categories. Health expectancy and Health Gap. Health expectancies indicate number of years of life gained as a result of improved health services along with improvement in other socio-economic considerations. It also indicates number of years of improved quality of life. Similarly Health gaps quantify lost years of full health vis-vis some ‘ideal ‘health status standards.
These are measures that cull in information on mortality and morbid health outcomes to typify the health riskof a given population with a single number. As the life expectancy started increasing due to advancement of healthcare services, triggered by technological improvement, various measures were needed to reflect the impact of morbidity on mortality. It called for developing indicators to adjust mortality with morbidity or disability.
As stated above, QALYs, DALYs, HALEsor life years gained are all common outcome measures derived as a result of assessment of any health intervention. DALYs is calculated by summing ‘years of Life Lost’ and ‘Years of Life Lived’ with disability for specific location, age group, sex, and year or most often specific population. In simple words, it means years of healthy life lost as a result of premature death and sufferings. DALY has two components: Years of Life Lost (YLLs) and Years of Life Lived with disability (YLDs).
In other words DALY = YLL+YLD
The YLL reflects the number of deaths multiplied by the standard life expectancy at the age at which death takes place. We use the following formula to calculate YLL= N X L
N = stands for number of deaths at particular age ,sex and cause
L = reflects standard life expectancy at age of death in years
Similarly YLD is calculated as under:-
YLD = I X DW XL
I = denotes number of incident cases
DW = denotes disability weight
L = denotes average duration of the case until remission or death (years)
Similarly HALE is calculated using age-specific death rates and years of life lived with disability per capital.
The above measures focus either at health expectancies or at health gap . Health expectancies as the name suggests quantify the years of life gained or years of improved quality oflife as a result of a health intervention.Some popular measures of health expectancies are Active Life Expectancy (ALE),Disability-Free Life Expectancy (DFLE),Disability-Adjusted Life Expectancy (DALE), Healthy Adjusted Life Expectancy (HALE),Quality Adjusted Life Expectancy (QALE).
Health gaps on the other hand measures lost years of full or complete health against a pre determined ideal or accepted health status. Some popular measures are Potential Years of Life Lost (PYLL),Healthy Years of Life Lost (HYLL),Quality Adjusted Life Years (QALY) and Disability Adjusted Life Years (DALY).
The moot point, here is why do we need to understand these complex but intriguing concepts as health insurers. Ideally health insurers would like QALY to go up as they represent gain of years of healthy live lived and DALY to go down as they represent loss of years of healthy live lived. It means higher DALY would indicate higher risk and on the other hand, higher QALY would indicate lesser risk. In other word, QALY needs to be improved upon and DALY needs to be lessened as far as possible.
The life expectancy of female in India in 2016 is 70.33 years and that of male is 66.93 years .This is a quantum jump from 1990 and 2006 .This is an indication that more Indians are able to attain their adulthood and old age. But what is disturbing is healthy adjusted life expectancy (HALE). It is only 59.67 years in female and barely 58.18 years in male in the year 2016. If we look at Bangladesh, the life expectancy at birth of female and male is 75.10 and 70.47and the HALE is 64.04 and 61.69 years for female and male respectively.Even Bhutan has better HALE for female and male than India.
Poor level of HALE means more people are living with disability in India. In such scenario, the health system of a country,struggles with a population that suffers from chronic or life style diseases. Insurers have to come out with policies dealing with such emerging chronic conditions. Most of the policies in India deal with acute conditions or a chronic condition that becomes acute so that hospitalization is needed. It may be noted here that most of the policies in India trigger only when inpatient hospitalization takes place.
This brings to our notice the importance of the popular measure known as “Years lived with disability”. YLD as it is popularly knownis a measure that takes into account both the number of individuals suffering from disability consequent upon a particular disease or injury andalso takes into account the severity of the disability. YLD, unfortunately is on rise in India. In the year 2016, its share to the total disease burden (DALYs) was 33% .It was merely 17% in 1990.What could also worry the insurers is the rapidly changing epidemiological transition of India .The contribution of non-communicable diseases (NCDs) to DALY has risen to 55.4% in 2016 from 30.5% in 1990 , whereas the contribution of communicable, maternal, neonatal, and nutritional diseases (CMNNDs) has come down to 32.7% in 2016 from 60.9% in 1990.The changing risk profile as result is a cause of concern for health insurers in India.If we look at distribution of deaths from Communicable, maternal, neonatal, and nutritional diseases (CMNNDs )and Non- communicable diseases (NCD) by all age groups taken together in India in 2016, the Non –communicable diseases contributed 61.8% as against 27.5% in Communicable, maternal, neonatal, and nutritional diseases. The remaining 10.7% was contributed by Injuries. The share of NCD in the age group of 40-69 was highest at 73.2%. It was 71.6% at age of over 70 years. The total population of India is1316 million people, who experience an unprecedented millions of disability adjusted life years (DALYs). In 2016 , the share of cardiovascular diseases to DALY rose 14.1% as against 6.9% in 1990 with a population 864 million. Similarly in 2016 , the share of Chronic respiratory diseases to DALY rose 6.4% as against 4.5% in 1990 with a population 864 million. The share of cancer to DALY rose from 2.3% in 1990 to 5% in 2016.Similarly the contribution of other non-communicable diseases rose to 7.4 % in 2016 from 4.9% (1990)
Living longer with disability may prove very costly to insurers unless India’s health system wakes up from the deep slumber and emboldens its primary healthcare. Health insurers need to develop products and institutional settings around this emerging risk. They have to move away from traditional health settings i.e. hospitals to more innovative institutional settings like home care and sub-acute care settings. They must also look for palliative healthcare centres to better address the healthcare needs of elderly population who as statistics clearly suggests would live with more disability in days to come.
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(Dr.) Abhijit Chattoraj, Chairprofessor-IBM, BIMTECH