Healthcare providers and eligible primary physician practices are undergoing analysis paralysis because of all the government impositions on improving healthcare with the following list of complex problems to solve: HIPAA’s Version 5010 conversion, ICD-10 migrations, Meaningful Use (MU) of EHRs and Attestation , Accountable Care Organizations (ACOs) , Data Aggregation and mining for successful Quality Measurement Reporting and Performance Improvement Requirements, CPOE implementations, CDA and the CCD template based document generation for sharing patient information between health providers, Natural Language Processing (NLP), Private Health Information (PHI) in the Cloud, internal demand for emerging technologies, the Mayan prediction of the end of the world, Et cetera, Et cetera, Et cetera.
Health IT
I always tend to “cringe” when I read about comparisons between Health IT, medical devices and other healthcare related software with respect to other verticals (e.g., finance, insurance, retail).
Why compare?
Saying that the financial industry is many “light years” ahead is extremely inaccurate. Comparing the processing of debits, credits, interests, etc. with medical information and imagery is like comparing apples to guanabanas (a tropical fruit found worldwide near the Equator).
Healthcare is definitely more complex than other verticals therefore it has complex interoperability issues.
The reason healthcare has interoperability challenges is because it has to deal with extremely complex workflows, scenarios and data. It also faces other regulatory constraints that hinder sharing of data between diverse organizations that interact with the same patients. State local laws also hinder as well.
Healthcare is the number 1 trail-blazer for technology.
Many technologies currently used by other verticals had their birth in trying to solve medical problems; companies in order to survive the regulatory red-tape (read FDA) diverted their attention to applying their inventions to other areas. For example, the CAD (Computer Aided Detection) for health anomalies would modify their products to serve other areas such as security and defense.
Healthcare has provided quite good interoperability solutions to the world. DICOM is ubiquitous in the radiology sub-domain of healthcare. HL7 has been quite successful for exchanging patient data between various source systems. X12 is also a standard for exchanging information between providers and payors.
SQL and MUMPS are of the same technological era.
Great minds from the Massachusetts General Hospital contributed to the creation of MUMPS. MUMPS was created near 1967 and SQL in 1970, so if we want to compare them based on age they are both post-baby-boomers.
SQL may have conquered more market but that does not necessarily mean that it’s better. In technology like any other space the consumer trend has nothing to do with quality. If the opposite were the case then there would be more Apples than PCs. Intersystems Cache is an example of vanguard technology.
Excerpt from Wikipedia: “The European Space Agency announced on May 13, 2010 that it will use MUMPS (InterSystems Caché) to support the Gaia mission. This mission aims to map the Milky Way with unprecedented precision.’
Why didn’t the agency choose SQL? Obviously there is a big reason. Maybe it’s because SQL has no way of meeting the high-bar of unprecedented precision.
We should try to stop blaming technology for the US healthcare problems. Most of these problems root-causes stem from poor policies, savage competition between providers, imprisonment of the patient data, organizational silos, etc.
