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I-Tech to make healthcare Hi-Tech
Konda Vishweshwar Reddy is an Indian politician and a member of parliament from Telangana. He won the Indian general election, 2014. He worked as CEO & Managing Director of Wipro Healthcare IT Ltd., CEO & Managing Director of GE Medical Systems Information Technology and Managing Director, Citadel Research and Solutions, Ltd. He is involved in various health care programs and has conducted many health camps and health education programs with an emphasis on women and child health and nutrition.


The human body is definitely the most complex machine that mankind ever had to work on. With Kurt Godel’s theory of incompleteness essentially meaning “no system can understand itself” becoming an axiomatic truth and David Hilbert attempting to prove that a system can be a complete system and can understand itself, he could not fructify his attempts through a mathematical process, now called the Hilbert Program.

In essence, what this means is that, the doctors have to work with something they do not completely understand – the human body. Yet their work is of utmost importance, the outcome of which impacts the quality of life and death itself. Unlike engineers who use logical mathematics to work on machines which are incomparably simpler than the human body, or lawyers who used law and reasoning in the profession, doctors do not have the luxury of simply applying logic or reasoning or mathematics on a complex and incomprehensible machine. Any such unscientific attempt may turn out to be risky. Doctors essentially have to be dependent on knowledge while practicing medicine.

Healthcare is a knowledge-based business. Data is sounds, electrical signals, lab parameters, names, numbers etc. When data is structured and labelled, it becomes information. When information is put into context, it becomes knowledge. Data has no meaning in itself and is not comprehensible. While information is comprehensible as compared to data, it is not sufficient to take executable decisions. Knowledge can be used to understand objects and conditions based on which executable decisions can be taken. Unlike engineering and law, modern medicine has taken this route as the professional approach and probably the only way when dealing with a complex machine such as a human body and mind.

Then came computers and information technology. And Information Technology is all about converting data into information and information into useful knowledge, exactly what doctors have been doing in the profession. The enlightened doctors knew the significance of Health Informatics in the seventies. Strange as it seems, Information Technology can help doctors more than it can help engineers, lawyers or Chartered Accountants.

Challenges in Health Informatics: The healthcare industry has been slow to adopt information technology. Many factors have been attributed to this: doctors’ reluctance to adopt new technology, lack of budget for computerization in hospitals, lack of suitable software and products, etc. However the biggest challenge was the very nature of information in healthcare as compared to the nature of information in other industries. In the banking industry, for example, the nature of data is related to account numbers, amount of money in the account, amount of money to be withdrawn or transferred to another account etc. This type of data can easily be converted to information and conveniently designed to fit into database. In an airline industry, the data is related to seats reservation, name of the destination, name of the passenger, cost of the ticket etc. Similarly, in the hotel industry, the information is about room reservation, booking dates, cost of the room etc. This information too is simple for conversion.. In contrast to this, the nature of information in healthcare is very complex and the content of data is humongous. In fact, a single 300-bed hospital can generate more data than the State Bank of India with more than 85000 branches in the country. And this is the reason that more than 20 years ago you could transfer money from one bank to another bank electronically; more than 20 years ago you could book a hotel room in Australia sitting in India; and more than 20 years ago you could even book an airline ticket from anywhere in the world to any other destination. Despite this, even today we are unable to transfer electronic medical record from one hospital to another.

This also brings to us yet another problem – standards in health informatics. One is the very nature of information in the healthcare industry and the other is the challenge of standardization of the information across the enterprises in the healthcare industry.

Standards in Healthcare IT: The industry recognises the need of standards in healthcare IT. There are broadly five categories of standards:

1. Codes and Terminology standards – codes and terminology for clinical observation, for diseases / diagnosis, for procedures / surgeries, drug codes etc.

2. ID Standards – patient ID, physician ID, institution code etc.

3. Formats and contents standards – Data capture forms and minimum data sets.

4. Communication and messaging protocols

5. Security and access control protocols

The first category of standards that is the Codes and Terminology standards primary deals with the problem of health informatics – trying to put the code to a particular human condition so that it fits in a database. The observations of the doctors go merely


beyond reading lab reports and patient vitals, the observations sometimes border on intuition. Clinical observations are highly nebulous data and codifying it and trying to fit into database is like trying to capture a cloud and putting it in a box. Capturing the severity of the condition is a special challenge that has not yet been overcome. The other categories of standards are more to do with technologies and implementation. Recognising the problems of lack of standardization through the 70s, 80s and 90s, many groups and organisations started developing standards for various aspects of Healthcare IT, leading to the problem of “too many standards” dwarfing the very purpose of standardization.

We are now attempting to overcome this situation and universal standards have begun to emerge. On the clinical side ICD codes, LOINC and SNOMED are becoming the most widely accepted coding systems. SNOMED has, by far proved to be the most comprehensive clinical coding system. While its very complexity is daunting, healthcare organisations and doctors are just beginning to use it.

Standards for Drug codes are as important as disease codes to avoid item identification errors. But going beyond standards for drug coding, if all the attributes of the drugs are captured and coded, then not only the item identification errors would be eliminated, but also potential medication errors by doctors, nurses and pharmacists can be avoided through Drug Decision Support systems. If the drugs are mapped to all their clinical attributes like indications, contraindications, side effects, drug-drug interactions, etc., then the system will have the ability to act as a drug decision support system, significantly reducing or eliminating medication errors. In India we do not have a National drug to start with, something that needs to be addressed urgently.

But the Holy Grail of health informatics is achieving semantic interoperability. Semantic interoperability goes beyond merely using the same set of codes – disease codes, drug codes, procedure codes between two systems. Firstly, the code or the term should have the same taxonomy, context and meaning in both the systems. Secondly, the code or the term should have the same taxonomy context and meaning in the system and outside in the real world, as to how the doctors, nurses and healthcare professionals understand and use the information. A simple non-clinical example- in the patient registration form, if the patient’s age is 6, then to the outside world, it means that the patient is a child; to the admission clerk, it automatically means that the patient should be admitted to a paediatric ward; to the billing person, it means that the payer is not the patient but the patient’s parent or guardian; to the F&B department, it means that the patient should be served child’s meals; to the housekeeping department, patient’s age 6 years means that the patient should be supplied with a child size patient gown; to the biochemistry department, it means that the patient’s lab parameters are different; and to the doctors and nurses, it means that the patient needs to be given paediatric dosage of medicine and many other such indications. In the outside world, the term “age 6” is merely the number of years since birth, but in the real world, the term “age 6” has lot more implications that the human brain processes automatically. And true semantic interoperability is achieved through proper taxonomy, mapping, capturing minimum data sets of attributes of the code or term. Semantic interoperability makes the system intelligent without the need for dependent on high cutting edge technologies like artificial intelligence etc.

Wisdom is a combination of knowledge and experience. In the human world wisdom comes with age. In reality wisdom merely means a lot of knowledge available at one point or person. And for humans, lot of knowledge by one human is accumulated only across years and years of gaining knowledge through experience. However, in a system where information and knowledge is accumulated from inputs and experiences of numerous individuals and their clinical observations, the system can gain wisdom in a short period of time. And we hear terms like wisdom management system in information technology.

Whether it is e-health or Telemedicine or EMR or Hospital Information Systems, the greatest challenge in health informatics is definitely not the technology or its costs. It is in the semantics- words and terms, their meanings, how they are codified and represented in computers, how their meaning essentially remains the same in the computerized information system and in the real world healthcare, standardization of terms and codes representing information across two different systems or two different enterprises – when these challenges of semantics are overcome, the true benefits of health informatics can be realised. Medical errors start to disappear; clinical knowledge gets institutionalized in a manner that junior Doctors can start performing like highly experienced doctors, best practices can be extracted from the system and database, EMRs start yielding clinical wisdom.

Now, this leap in technology for health informatics is what we look forth to!


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