Just as it is often true that some generals prepare to fight
the last war, so too it is also the case that certification is getting ready to
validate last generation's client-server technology. The famous example is the
construction after World War I of the Maginot Line by
The prospective buyers of EHR technology are physician practices (eligible professionals (EP)) and hospitals. They are best protected from the unprofessional practices of a small - very small - minority of system sales people through their own professional procurement practices, diligently reviewing written proposals, specifications, and contracts. It is unlikely to be the basis of a legal claim against a software vendor installed at a given site that failed to satisfy meaningful use criteria for provider that the software system or modules were certified. The provider receives the reimbursement (if any is forthcoming) and is responsible for attaining and demonstrating a use of the system that delivers healthcare services in a more effective way according to the criteria of meaningful use. From such a perspective, certification may be of value to the vendor but it furnishes a false sense of security to the prospective buyers (such as hospitals and eligible physicians).
On the one hand, some of the meaningful use criteria, including those that capture basic clinical transactions, are best delivered by an underlying system consisting of a standard relational database, a frontend query and reporting tool, and a data model that represents the patient demographics, diagnoses and procedures, and related clinical nomenclature. The user interface at which the meaningful use of the technology, including the capturing of data electronically, reporting of data electronically, and the manipulation of quality measures is the contract at which the meaningful use is delivered. Multimillion dollar HIS systems are candidates for "over kill" from a transactional perspective in addressing such use yet at the same time lack the necessary infrastructure to support quality metrics through aggregation and inquiry via a data warehouse function.
On the other hand, some of the meaningful use criteria - in particular the requirement to report about 100 quality measures - are poorly accommodated by the vast majority of HIS system on the market today. I do not know of a single exception where the HIS system provides for the aggregation and analysis of metrics in a way similar to what business intelligence (now 'clinical intelligence') does in business verticals such as retail, finance, telecommunications. Once again, the user interface at which the quality measures are surfaced is (in effect) the contract, but it will prove impractical to generate such a result. If these systems propose to perform the aggregations of a year's worth of data based on transactional detail, the predictable result will be a long, slow process. Reinventing the wheel is hard work, but that is the path on which existing HIS and PPMS (EHR) systems have embarked. I hasten to add that the quality metrics are critical path and required. However, the path to the efficient and effective production of them does not lie through certification.
Those providers that are currently reporting quality metrics from a data warehouse that gets its data from the transactional EHR are concerned that they are out of compliance. It is widely reported that Intermountain Healthcare is one such enterprise.[2] Are they now supposed to certify their data warehouse? Where is the value-added in that?
A long list of clinical quality measure requires reporting a percentage of a total aggregate of a given diagnostic condition; for example, percentage of patients aged 50 years and older who received an influenza immunization during the flu season (PQR1 110 / NQF 0041). These are what other business operations such as retail or finance call "business intelligence" questions. In the context of healthcare, we might call them "clinical intelligence" - or just plain quality measures - but the function is similar - to make possible the tracking of improvements in the delivery of care. To manage enhancements by measuring outcomes in aggregate. The periodic calculation of some 94 percentages requires scanning the entire database and performing an analysis, review, and aggregation of a totality of the diagnostic data. Even though most records will not satisfy a given diagnosis - whether coronary artery disease of diabetes mellitus - they will have to be examined. The lessons of some two decades of computing in finance, telecommunications, retail, manufacturing, and fast food are clear, but not always obvious to those medical professional who have spent their time in healthcare IT. When you attempt to perform business intelligence (BI) against the operational, transactional system, then something has got to give. Either the performance of the transactional system is brought to its knees or the BI process has to wait. In fact, system design for high performance transactions processing are poorly adapted to generate the results required to perform business intelligence. The difference is between update intensive operations and query intensive ones, between updating and scanning. That is why the data warehouse was invented - in order to collect and aggregate the data required for reporting in optimal format, allowing the transactional system to do its job supporting clinical process whereas clinical intelligence is used to guide process improvements.
The counter-argument that certification of the functionality around clinical data warehousing ought to be rolled up into the certification process is the reduction to absurdity of the process itself. There will always be some such functionality - if not data warehousing, then cloud computing, database appliances, artificial intelligence in clinical decision support, and so on. The list is limited only by our imagination and that of our fellow innovators. The Meaningful Use Proposal has got it basically right (though one can (and should) argue about details). The reporting of quality measures, based on aggregated clinical detail is a proven method in other disciplines of driving improvements in outcomes by surfacing, managing, and reducing variability from the quality norm. ('If you can't measure it, you can't manage it') However, this value is provided by implementing systems that directly address the superset of meaningful use criteria captured in the proposal, not by driving the process up stream into one particular system architecture that happens to have emerged in the early 1990s and gotten some significant traction.
To see the full Comment submitted to www.regulations.gov on the rule-making for reimburseable EHR investments go here: http://www.b-eye-network.com/files/EHR
Certification _Lou Agosta's Feedback to Centers for Medicare and Medicaid
Services, HHS.pdf
[1] Clayton
Christensen, The Innovator's Dilemma.
[2] For example - http://www.healthcareitnews.com/news/meaningful-use-criteria-too-high-and-too-many
Posted February 18, 2010 7:07 AM
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