Information technology (IT) is reinventing healthcare markets. In India, ventures such as Practo and 2nd.MD inform consumers about the quality of care, help verify diagnoses, analyse and rank healthcare providers. The success of these ventures attests to the information challenges that have dogged healthcare before the arrival of IT-based innovations. Understanding the relationship between IT and healthcare markets is key to comprehending the future of healthcare. But to understand why IT in healthcare is so revolutionary, it is important to understand the fundamental information asymmetry issues that underlie healthcare interactions.
Why Information Matters in Healthcare
So what is information asymmetry? To understand the ideas at stake, it may help to turn to another tricky product purchase decision – buying a second-hand phone. Since the seller of the phone will have first-hand information on the actual working condition of the phone, she or he will be more informed about the quality of the phone than the buyer. This is a fundamental issue of asymmetry in information.
As a result of this asymmetry, the seller can try to rip the buyer off by selling a lemon or a phone of bad quality. Of course, there may be other sellers trying to sell a good phone in a decent working condition. But to the extent that buyers do not want to pay a high price, without knowing the phone quality with certainty, sellers of the better quality but more expensive used phones may not want to sell at the prices on offer. Buyers will, therefore, have to choose from the poor quality phones.
In this extreme case, due to the lack of information on the quality, the higher quality used phones remain unsold. Breakdowns of this type can occur for many used goods markets including cars, computers and the healthcare market. This is the central insight of a celebrated 1970 paper by the Nobel Prize-winning economist George Akerlof, who argued that the uncertainty about product quality completely eliminates the market for a higher quality product.
Before Akerlof, one of the first economists to formalise the problem of information was Kenneth Arrow. Arrow remains the youngest winner of the Nobel Memorial Prize for Economics, which he won in 1972 at the age of 51. His work on asymmetric information in healthcare markets (Arrow 1963) is still widely used in understanding and analysing the healthcare market.
Arrow posited that the asymmetry of information in the healthcare market would limit the ability of free-market solutions to deliver health care efficiently. Why would this asymmetry arise? On the one hand, healthcare providers know more about treatment than patients and would want to profit from their information advantage. On the other hand, patients know more about their own health and habits. Thus patients would be tempted to lie about themselves to save on costs. Hence the healthcare market, just like the market for used phones, will be inefficient.
Contrary to these theoretical predictions, however, in 2018, the used phones market internationally was worth around $17 billion and expected to grow at a much faster rate than the new smartphone market (Deloitte 2016). This would not be possible if only bad quality phones were available in the market.
The difference here comes from the fact that online portals, third party appraisals, and the proliferation of online review sites have made hitherto restricted information accessible to everyone.
In the case of second-hand cars, similarly, the invention of simple devices such as the odometer helped fill in crucial information. Odometer data helps determine the value of a used car, thus bridging the gap in information asymmetry between buyers and sellers. The government also played its part. The Federal Odometer Act in the US made tampering with odometers a federal offence, ensuring that the device could continue to serve its critical informational function.
Although the worlds of used phones or used cars in the US may seem distant from the Indian healthcare sector, in fact, a similar suite of information innovations can work in the healthcare industry as well.
Information Issues in the Healthcare Sector
In many underdeveloped markets where coverage is not universal, people attempt to buy health insurance only when they expect imminent medical expenditure. Interest in health insurance increases proportionately with the anticipated health expenditure burden. At the same time, there might be healthy individuals who wish to buy health insurance to avoid health expenditure risks in the future. Unfortunately, health insurance companies find it very difficult to differentiate between these two varied motivations among those who seek to buy health insurance.
The fundamental problem is again one of information asymmetry. An individual typically knows more about his or her medical needs than the healthcare insurance provider. Moreover, sicker individuals prefer more insurance coverage than healthy individuals when insurance companies cannot differentiate between the two. This represents a situation in which a more informed insuree gains an unfair information advantage.
These information problems could be divided into two broad categories, based on whether the problem is caused due to uncertainty in information (the lemons problem) or due to uncertainty in the effort of the individual. This uncertainty in effort primarily arises due to problems of moral hazard. For example, consider the public provision of healthcare, where healthcare providers are often paid a fixed salary. Since the providers know more about their personal effort than patients, such fixed compensation may reduce their incentive to work hard for their patients.
Differences in quality of information, on the other hand, more often affect private healthcare provision. As hospitals seek to maximise their profits in conditions of competition from other hospitals, they may prescribe unnecessary procedures or treatment. Given information asymmetries, it may be very difficult for a patient to figure out whether the quality of care provided was appropriate or not. Emerging IT innovations can solve both sets of information problems.
Doctors Know More than Patients, or Do They?
In the private healthcare market, buyers are held responsible for understanding what they are purchasing. The proliferation of online information goes a long way towards solving the problem of information asymmetry. In developed markets, the internet may offer a vast sea of information about the quality of a hospital’s services and discussion forums on physician’s services. How are some of these technologies making markets more efficient?
There is a simple solution to information asymmetry regarding the quality of a product – readily accessible information on quality. For example, while booking a restaurant on Zomato, the star-rating and average price information help consumers to make a decision. E-Retailers such as eBay and Amazon similarly rely on buyer reviews.
Similar solutions exist for the healthcare market as well. 2nd.MD connects patients with medical specialists around the world for second opinions, reducing costs for patients and increasing efficiency. The website provides information on the experience, research and certifications of consulting physicians.
Pre-formatted and digitised patient records and online patient consults can lead to better and quicker healthcare access for most of the developing world.
Based out of India, Practo helps patients in India find a doctor, solicit advice, and get basic answers related to medical care. It helps digitise reports so they can be read universally. This service solves many challenges in emerging country healthcare markets. First, the difficulties in finding a doctor, and second, the non-transferability of medical reports. Pre-formatted and digitised patient records and online patient consults can lead to better and quicker healthcare access for most of the emerging world.
When Doctors do not Show Up
The issues in public healthcare services, on the other hand, relate to incentives and the challenges in observing effort. Since public healthcare personnel are usually paid a fixed salary, it is unlikely that they would put in extra effort. This issue plagues India’s public healthcare model. In a 2008 article, former vice-chairman Arvind Panagariya stated that the nation-wide absentee rate in public health centres hovered around 40%. Further, only around 20% and about 45% of patients looking for outpatient and indoor care in India respectively avail public services (Panagariya 2008).
Physicians and nurses are routinely not found at work during their duty hours (Banerjee, Duflo and Glennerster 2008). Such practices flourish despite regular inspections because inspectors are easily co-opted.
These are moral hazard issues because the behaviour of employees changes after they enter into a job contract and their efforts cannot be observed by their employer, in this case, the government. Therefore, investing in technologies to monitor effort could improve the behaviour of agents and reduce absenteeism of medical officers and nurses.
In a 2008 paper, Abhijit Banerjee, Rachel Glennerster and Esther Duflo from the Massachusetts Institute of Technology tried to analyse if this was indeed the case. In a randomised control trial in Udaipur, Assistant Nurse Midwives (ANMs) were offered attendance incentives at public rural healthcare sub-centres.
A health survey prior to the intervention suggested two important findings. First, only one out of four patients who needed medical care went to these public health centres. Second, these centres were open only around 40% of the time on an average. The absenteeism could be a possible explanation for the patient preferences. If an ANM is usually absent, patients would be discouraged to use the facility.
In November 2005, the non-governmental organisation (NGO) Seva Mandir, which works for disadvantaged sections of the society and has a strong presence in Rajasthan, collaborated with the government to start a monitoring programme to possibly improve the attendance of ANMs in rural sub-centres. ANMs in the treatment group were asked to be present on Mondays and register their presence through a time and date stamping machine. The government stipulated that if ANMs were absent on the monitoring Monday for more than 50% of the time, they could be penalised initially by docking pay or even suspension in case of continuing absenteeism. A total of 16 randomly selected sub-centres received monitoring; another 12 sub-centres were assigned to the control group. The data for the evaluation came from random unannounced visits by the monitor.
The results showed that devices introduced as part of the monitoring programme indeed increased presence by the ANMs in the first six months of the programme. ANMs were present for around 60% of the time on Mondays, compared to around 30% both in the untreated group as well as other days in the treated group.
Investing in technologies to monitor effort could improve the behaviour of agents and reduce absenteeism of medical officers and nurses.
However, after some months, the absenteeism started to increase again and attendance fell much lower than the baseline number of 44% by the end of the evaluation. The researchers argued that the increase in absenteeism was accounted for by faulty machines or approved exemptions.
Some of the machines were observed to have been deliberately broken and there was an increase in the number of exemptions given to the ANMs.
Overall, this study showed that monitoring is a costly exercise, both monetarily and otherwise. Its execution needs to be perfect. It did improve healthcare outcomes but subject to caveats. Could the use of more sophisticated technology improve outcomes?
In a similar study implemented by the National Rural Health Mission (NRHM) in Karnataka and reported in a 2017 Journal of Development Economics paper, researchers Iqbal Dhaliwal and Rema Hanna found that a biometric device with an attached mobile phone increased staff attendance by about 15%.
Although Karnataka is one of the more developed states of India with an advanced healthcare programme, it is plagued with poor attendance by healthcare workers. On an average, the attendance in healthcare centres hovers around 35%.
To counter high rates of absenteeism, the government set up a system in which a biometric scanner scanned the thumb-prints of healthcare workers twice a day. This data was then uploaded to the central server using a cell phone. As an IT intervention, this system was more robust than Seva Mandir’s and got good results.
However, researchers find that almost all of the results were driven by non-physician staff. The intervention did not impact the attendance of the doctors. This lack of an effect occurred mostly because the doctors cannot be easily penalised or fired for absenteeism.
How far can technological interventions go, if the eco-nomic incentives are not well-aligned?
Is IT the Magic Pill?
Online information aggregation, more informed patients and biometric attendance systems are making healthcare markets more efficient and accessible. However, these advances come with their own costs. So far, we have discussed some of the ways that IT innovations can help solve information problems.
Healthcare data is sensitive. Consider the following scenario. Say you might have a genetic disposition towards heart disease. If a genome-mapping firm sells this private data to insurance industries, it might lead to your paying a higher premium for insurance, regardless of whether you actually have heart disease. Information, therefore, is a double-edged sword. It must be wielded with caution.
In a similar vein, digitised records offer comparability, portability and ease of use. But they are still fraught with issues. Electronic Health Records (EHR) data can be inaccurate and incomplete. They can also lead to higher susceptibility to hacking. As more and more health records go digital, theft is also on the rise. The sensitive and subjective nature of digitised healthcare records, therefore, is a big barrier that IT has to address.
Regulators around the world are coming to recognise privacy issues surrounding personal health data. In the US, the Health Insurance Portability and Accountability Act of 1996 (HIPAA) created a regulatory framework to protect individuals’ health information and assign them well-defined rights over such information held by public and private agencies (Annas 2003). Similarly, the European Union has the 1998 Directive on Data Protection, while Canada has the Personal Information Protection and Electronic Documents Act since 2000 (Agrawal and Johnson 2007). In India, the draft of the Digital lnformation Security in Healthcare Act (DISHA) was placed in the public domain for comments in 2018.
The US has had more than 2,306 breaches affecting over 262.4 million individuals since May 2009, when the Department of Health and Human Services set up a HIPAA Breach Reporting Tool website. The “breach portal” captures all breaches affecting more than 500 people. The staggering scale of these breaches should itself be a cause for concern. Experts quoted in a 2018 report on the specialist portal Healthcare Info Security noted that medical devices are especially prone to security risks, although hacking and theft also remain major concerns.
The Way Forward
Healthcare markets are not the only markets to be plagued with healthcare asymmetry nor are they first to turn to IT for a solution. However, there is a long way ahead for IT in healthcare. Healthcare markets are plagued mainly by two different kinds of uncertainties, one related to information and the other to effort. We discussed how technology can overcome such problems. In essence, simple innovations in IT can have far-reaching effects in healthcare markets. These innovations are not without pitfalls but they go a long way in improving the functioning of healthcare markets.
Akerlof, G., 1970. The Market for ‘Lemons’: Quality Uncertainty and the Market Mechanism. Quarterly Journal of Economics, 84(3), pp. 488-500.
Arrow, K., 1963. Uncertainty and the Welfare Economics of Medical Care. The American Economic Review, 53(5), pp. 941-973.
Banerjee, A., Duflo, E., and Glennerster, R., 2008. Putting a Band-Aid on a Corpse: Incentives for Nurses in the Indian Public Health Care System. Journal of the European Economic Association, 6(2-3), pp. 487-500.
Dhaliwal, I. and Hanna, R., 2017. The Devil is in the Details: The Successes and Limitations of Bureaucratic Reform in India. Journal of Development Economics, 124, pp.1-21.
Panagariya, A., 2008. India: The Crisis in Rural Health Care. Brookings Institution, Washington, D.C.
Annas, G.J., 2003. HIPAA Regulations-a New Era of Medical-Record Privacy? New England Journal of Medicine, 348(15), pp.1486-1490.
McGee, M. K., 2018. Health Data Breach Tally: The Latest Additions. Healthcare Info Security, May 17.
Agrawal, R. and Johnson, C., 2007. Securing Electronic Health Records without Impeding the Flow of Information. International Journal of Medical Informatics, 76(5-6), pp.471-479.
Deloitte, 2016. Used Smartphones: the $17 Billion Market you may never have Heard of. TMT Predictions 2016. Deloitte Touche Tohmatsu, London.