Why EMR will continue to be the most hated idea!
Every EMR (Electronic Medical Records System) salesman who tries to sell his merchandise has to go through the most tedious, inconvenient and the least influential person in the process of the actual sale of the software. He/She is that physician who is actually going to use the software. Indeed, the physician is the most unwilling data entry operator of the EMR. So the salesman shows him bells and whistles and bright shiny brochures and colorful screen grabs and assures him the heaven in medical record keeping. As long as he does not elicit screaming from the physician, he can proceed to the next important level of management, taking into his stride some grumbling and impatient muttering from the physician, who clearly did not seem smart enough for his ultra-sleek technology.
During past twenty years, I have used EMR on different platforms starting from word-star, Fox base in the 90’s, C+ in early 2000 till recently the most favored EMR- EPIC. I had also designed a small office-practice software with the help of my talented software engineer friends. That indeed worked very well for me and my group, well, at least for the time being. The best software that made physicians feel happy and empowered were small programs, operated at single site, with limited but essential tools and therefore less clutter on screen and designed around their need. Most importantly they were exclusively – as the name suggests- for Medical Record keeping, and not for Medical Account Keeping.
EMR is a misnomer. It is not medical record keeping system. It is actually Medical Account keeping system. From the point of view of software architect, anything that is not in a box and cannot be processed in Excel sheet is not a data to be bothered about. Doctor’s reports which is actually the most crucial document of his thought process about the patient and his current encounter is just one box, which cannot be processed in Excel. The other boxes- like the insurer, total time spent in visit, level of complexity, medication name, consumables used etc. -are the boxes, that one can work with in Excel. These are the boxes that will ultimately generate big data. Big data will generate trends; trends will help Policy. Problem is, none of these computable boxes capture what is actually wrong with the patient. This computerized medical accounting system helps policy, but does not add any substantial value to actual patient care.
Policy makers, big data scientists and software architects realize this problem. Their solution is to fragment the analogue data of patient care into a digital numerical data. The most prominent example is Pain scale. The EMR screen stubbornly refuses to move to the next level until physician extracts this information from the patient, however annoying it is for the patient, to convert his severity of pain into a number. It is this fragmentation of medical summary from its flowing natural analogue format into digital format of check-boxes, numerical scales and codes that makes a physician extremely weary. It is unnatural, and many times, it does not represent the reality accurately.
EMR- which is actually a medical accounting system, is unfortunately all pervasive and has grown and integrated into the payment and compensation system. The software is built with the logic of industry in mind, where health delivery is a product and therefore all the logistics of capital, raw materials (consumables, labs, pharmaceuticals) is integrated into a sleek logistics from end to end. It serves all the needs and requirements of industry, enterprise and investors. But it does not serve patients as well as it was promised.
The real danger in this is as follows. The expectation from the physicians for fragmented numerical data entry of medical report will keep mounting. The fragmentation will be based on needs of a particular type of data for the policy making. Big data scientists have to be careful about weary and unwilling data entry operators – which in this case are physicians, most of whom do not agree with this project at all. Bad data is only going to give unpredictable and wrong results in the end. The menace of ‘Copy and Paste’ in medical reports as already harming and will continue to imperil retrospective medical research.
Trying to capture health-care delivery by fragmenting into big-data-worthy format is only going to accelerate fragmentation of actual health care delivery itself. This is actually happening, adding to much inconvenience to the patients. The physician community, policy makers, industry leaders, society representatives need to put their mind together and brainstorm what exactly they want to achieve from implementation of EMR.
Founder & CEO @ Giggr Technologies | Design Learning | Building a Digitally Intelligent Platform As Service
9yThe one thing that bears no dispute is the fact that Electronic Medical Record (EMR) as it is available today is "FLAWED" to be at one's charitable best. Perhaps categorizing it more for a record keeping or accounting system is more accurate with respect to its current utility. Because this episodic record has different versions at different instances such as Physician, Hospital, Diagnostic Center, etc. Yes, the record is fragmented because different physicians have different disparate (unconnected) records of the same body that has a common denominator in connecting Vitals, Performance and Emotional Response required to heal (provide treatment) no matter what ailment / condition the body suffers. This is where the example taken with respect to "Degree of pain represented by a scale" finding criticism in this article startles me. That cannot just be the cause of fragmentation alone. Pain may be episodic but it also has to do with other factors relating to emotional response that relates to socio economic and ethnographic factors that have a bearing on all the three critical parts of data - Body Vitals, Performance and Emotional Response. The data will always be fragmented unless the composite of an Individual's data is analyzed commonly by every single healthcare practitioner and institution (where the data represents a connected link from birth until the current episode including conditions such as Congenital, Hereditary & Environmental) deriving an understanding of the caused to define either diagnosis, treatment and / or prognosis. In order for this to happen there needs to be a revolution of sorts where the ownership of data moves from professionals and institutions to Individuals who have the ability to record health not only when they face Disease, Decay & Death but also as a Process of Life, Learning & Living. Big Data may be useful but more important is cognitive (experiential) data that will allow to remedy causes more than just symptoms without the pain of trial and error which is the norm in the healthcare industry.
Corporate Finance | Healthcare Lifesciences & MedTech Leader | Tech Digital Innovation | VC & PE | | Singapore PR | ex-PwC | ex-A*STAR | IIT - Max Planck - NUS - MIT alum
9ythis is one of those articles that really highlights the problems from the user perspective. exceptionally well written and bang on target...
Physician / Health Informatics
9yPerfect diagnosis. We should move forward
Business Development
9yGood read. thanks for sharing
Adjunct Professor
9yEHRs are only a data capture system. Some of the functionalities are focused on how it can be programmed. Which it continues to have discrepancies for several environments. Unfortunately, there are several medical centers that continue to use their workflow and add technology to it. Technology should be a driving force to the workflow. Unfortunately, each physician has a different workflow making it hard for EHRs to adapt to them. There is a lot of work needed to ensure the system supports the workflow of the physician or nurse. Trying to replicate a paper workflow will always have issues. Standardizing documentation might facilitate the documentation. But cleaning the issues and diagnosis list will be a first step to take to ensure the system is clean and functional. The system is as valuable as the data input. if you input garbage you get garbage "garbage in/garbage out." Education is the first step to ensure the usability of any system is succesful