Skepticism about measurement: Hospital beds edition

by Shubho Roy.

The Covid 19 pandemic has motivated many studies based on data about the disease and the response. However, measurement in India is often weak. There is a need for greater caution before using such data. In this article, we look closely at one such issue: estimating health care capacity based on hospital beds.

The health care infrastructure response to Covid 19 has been to ramp up the number of hospital beds. However, severe and critical care patients in India may often need ventilators and ICU beds. There are no measures available about the number of ventilators or ICU beds in India. Researchers have taken to guesswork in order to address this gap. How reasonable are these estimates?

Extrapolation from the count of hospital beds

It makes sense to use hospital beds as a standardised measure of hospital capacity. Infrastructure, equipment and manpower standards for hospitals have been built on a per bed basis. The number of nurses, doctors, equipment, and even floor space is a function of the number of beds in the hospital. For example, according to the Indian government, a hospital should ideally have 80 to 85 sq m of plinth area per bed; there should be a toilet for every six beds; and one operation theatre for every 50 beds in the general ward. This makes estimating the availability of health facilities easier. Count the number of hospital beds in a country, and you have a sense of the overall health care capacity. Both the World Health Organization and the World Bank track the number of hospital beds per 1000 population as a measure of health care capacity.

Estimates

If we work within such quantification of hospital capacity based on the number of beds, how many ventilators and ICU beds might be present in India? The central government formulated the IPH Standards in 2012, to improve capacity in government health services (run mostly by the state governments). The standards for district-hospitals (at pg.5) requires 300 district-hospital beds per million population. IPH standards for district-hospitals states that five to ten per cent of the total beds in a district-hospital should be ICU beds (See page 25) and each ICU bed should have a ventilator (amongst other equipment). If the entire country were to be up to IPHS standards, there should be 416,189 district hospital beds and between 41,618 to 20,809 ventilators in the country (in the government system).

In reality, the numbers will probably be lower than the standards. Experts have tried to estimate the availability of hospital beds, ICUs and ventilators for the present epidemic. Rajagopalan and Choutagunta have estimated the availability of hospital beds (both in government and private sector) in various Indian states. Singh et al. use a 2008 paper by Yeolekar and Mehta, which estimates that there are around 5-8% ICU beds in government hospitals. Singh et al. assume that around 50% of the ICU beds have a ventilator. This gives them a range of 35,699 to 57,119 ventilators for the entire country (in the government system). Similarly, Kapoor et al. estimate that there should be around 35,699 ICU beds and 17,850 ventilators for the country.

For U.P., they estimate 3,813 ICU beds and 1,907 ventilators.

The ground reality in Uttar Pradesh

How do the government aspirations and expert estimates stack up against the ground reality? In 2019, India’s supreme audit institution (the CAG), carried out a performance audit of Hospital Management in Uttar Pradesh. U.P. has 75 districts and 174 district hospitals (in 2018). The CAG covered seven districts (out of 75) for its audit of 16 government hospitals. In addition, three out of 11 district-hospitals of Lucknow were audited (See Table 45 at pg. 93). The seven districts which were fully covered by the audit (for district-hospitals) are distributed across the five administrative regions of U.P. The CAG found that the reality was far away from the aspiration or estimates.

The seven districts have a population of 25.9 million. As per IPH standards, they should have 7,700 district-hospital beds. The CAG found 2,275 beds, a shortfall of over 70%. If the districts follow IPH standards, there should be 385 to 770 ICU beds for the ideal 7,700 district-hospital beds. Even if IPH standards were maintained on a base of 2,275 beds, there should have been 113 to 228 ICU beds in the sampled district hospitals. The CAG found that ` 10 out of the 11 district hospitals had no ICU beds’. Only the Gorakhpur district hospital had 13 ICU beds (3% of its total beds). In short, of the seven districts examined by the CAG, there were 13 ICU beds, all located in one district.

Even where there were ICU beds, the CAG found shortages of equipment considered essential for an ICU bed (as per IPH standards). The CAG noted:

“audit observed that only six High-end Monitors were available against the requirement of 14, seven Infusion pumps were available against the requirement of 14, while Ventilators, Ultrasound for invasive procedures and Arterial Blood Gas (ABG) analysis machine were not available at all in D.H. Lucknow. Similarly, in D.H. Gorakhpur, there were no Ventilators, Infusion Pumps, Ultrasound for invasive procedures and ABG analysis machine.”

(pg. 34 of the CAG Report)

In the seven districts where the CAG audited district hospitals, the CAG found no ventilators. Even in the district-hospitals in Lucknow (outside the seven districts), 2% of the beds were ICU, and there were no ventilators.

The CAG report only covers seven districts out of U.P.’s 75 districts. U.P. is one of India’s poorest states. The government of U.P. also operates some super-speciality hospitals where facilities might be better, but they will be few. These seven districts constitute 11% of U.P.’s population. While the findings may not be representative of India, they are not inconsequential. The gap between central government standards, expert estimations, and reality is vast. Table 1 shows the gap between these numbers for the 11 districts of U.P.

Target and reality gap between hospital beds, ICUs and ventilators

Measurement approach	Hospital Beds	ICU Beds	Ventilators
IPH standards	7,700	385 - 770	385 - 770
Expert estimation (from UP numbers)	8,339	419	210
If existing beds maintained ICU ratio	2,275	113 - 228	113 - 228
CAG findings (Reality)	2,275	13	0

Goodhart’s law

Why is there such a large discrepancy between the IPH standards, expert estimates and the reality observed by the CAG? We may conjecture that Goodhart’s Law is at work. Goodhart’s law states: “When a measure becomes a target, it ceases to be a good measure”.

For too long, the academic and policy literature, in India, has emphasised one metric: the number of beds available in government hospitals. Press articles regularly criticize the government for India’s low bed to population ratio (See here, here and here). An easy way out for politicians and officials is to look good in such measurement, while skimping on other elements of health care. Between 2014-2018 the Central Government spent Rupees 8.5 billion for the country out of which Rupees 1.5 billion was spent in U.P., under the National Health Mission, to upgrade facilities in state government hospitals. The result was a rapid expansion in the number of beds (the measure which health policy makers are sensitive to), and not much else.

This problem is not limited to hospital beds. It extends to other parts of the health sector. The central government operates a detailed database called the Health Management Information System. As an example, Smriti Sharma shows that there are significant discrepancies in the database. Numbers which portray the system in poor light are under-reported while the numbers which show the health system positively are inflated.

Using the hospital bed measure to estimate the availability of health care capacity is misleading. Even when the government sets up new facilities, measurement is being done on the basis of new beds. Till April 11, the government had set aside 100,000 hospital beds and 11,500 ICU beds in 586 hospitals. On May 15, the Maharashtra government planned to set aside another 100,000 beds, just in Mumbai with an additional 1,000 ICU beds. In thinking about the situation in health care, this is not enough information. We need to know the facilities and personnel that will be available for these beds.

A general philosophy in India is to be very careful about using data. Researchers need to gain confidence in the quality of the measurement process. This is particularly critical where the agency which performs a function is also the source of data about the same function. When the underlying data is weak, no amount of cleverness in statistics can rescue the distortion of our view of what is going on.

References

Assessing Healthcare Capacity in India. Shruti Rajagopalan and Abishek Choutagunta, Mercatus Working Paper, Mercatus Center at George Mason University, Arlington, VA, April 2020.

Covid 19 in India: State-wise estimates of current hospital beds, intensive care unit (ICU) beds and ventilators, Geetanjali Kapoor, Aditi Sriram, Jyoti Joshi, Arindam Nandi, and Ramanan Laxminarayan, Center for Disease Dynamics, Economics and Policy, Princeton University April 2020.

Covid 19 | Is India’s health infrastructure equipped to handle an epidemic?, Prachi Singh, Shamika Ravi and Sikim Chakraborty, Up Front, Brookings, March 24, 2020.

Covid-19 in India in the coming months: The puzzles faced by leaders of health care organisations, Ajay Shah, The Leap Blog, June 2020.

Hospital Management in Uttar Pradesh, Comptroller and Auditor General of India, 2019.

Problems of the Health Management Information System (HMIS): the experience of Haryana., Smriti Sharma, The Leap Blog, June 2016.

Prudent public health intervention strategies to control the coronavirus disease 2019 transmission in India: A mathematical model-based approach., Sandip Mandal, Tarun Bhatnagar, Nimalan Arinaminpathy, and Anup Agarwal Indian Journal of Medical Research. 2020 10.4103/ijmr.IJMR_504_20.

 

The author is a researcher at the University of Chicago and would like to thank Renuka Sane and Rajeswari Sengupta for their valuable inputs.