Policy makers are tantalized by the allure of high tech and the tempting promise that it can do what they are unable to do – organize the status quo into a more coherent system. The efforts described by Dr. Brailer are a beginning. But as long as the delivery system is fragmented along countless political, geographical, practice and ownership lines, they will falter on those fault lines. Meanwhile consultants will earn lots of money. I recall an adage I learned early on – automated stupidity is still stupidity.

I would be curious, though, to know more about why Dr. Brailer considers HIPAA such an obstacle.

I would also suggest that doctor attitudes toward using computers in their practice is something that needs to be understood and overcome. My direct experiences with the health care delivery system are only as a patient or family member of a patient. Only once, have I encountered a physician who sat at a computer in his office for any reason other than to see a computerized image.
And that was in Ireland in 2003. They will speak their patient notes into a recorder in the hall. They will rifle through an inch thick file looking to discover the last prescription they wrote for me. But sitting in front of a computer seems somehow unnatural.

Am I wrong in that perception? What are the barriers to physician acceptance? Is it generational?

I am in complete agreement with him about the shape health IT incentives should take.

I also second the motion that we train a health IT workforce. This will create new jobs, but we also need to recruit clinician champions from successful implementations to get on the road and inspire others.

Nobody knows better than David what the challenges are to health information exchange, and it seems clear that industry isn’t going to develop spontaneously. We need some significant incentives for information sharing, and we need to figure out if these exchanges are ‘thin’ (basically a directory service) or ‘thick’ (accumulators of data, partly supported by extracting aggregate statistical knowledge from those databases, provided we can find a privacy policy that we can trust). We do have some standards now for data exchange. CCHIT has been requiring EHRs to be able to send and receive a CCD since July 2008, but the transport mechanism and protocol for an EHR to interact with an HIE/HIO wasn’t quite proven at that time. We are on track to test that mechanism starting in July 2009. Since we also test HIEs, at that point we’ll be checking both ends of the connection, getting closer to plug-and-play than ever before.

Being a solo practitioner operating an electronic (paperless) medical office for over 6 years, I have yet to see a penny of financial incentive from either government or private payers. Most doctors don’t want a government hand-out in order to computerise their records. Rather, they would like to see concrete measures that would make such a huge expense financially worthwhile in the long run, i.e. ability to collect higher reimbursements in return for appropriate use of technology in daily practice. They would also like to know that interoperability of systems is mandatory and the cost is not dumped on physician practices.

The most valuable and immediate method for the government to spur adoption technology by small physician practices would be get out of the business of price-fixing for medical care by the CMS. Allowing each practice to set (and collect) its own market-based rates, and allowing patients to select their medical provider based on the value they assign to the service provided, will enable practices to slowly catch up to current and appropriate levels of revenue, whereby they will be able to afford the high costs of converting to an electronic medical office. Otherwise, it will be impossible for physicians stuck at 2001 reimbursement levels (absorbing 8 years of declining revenues) to be able to afford the initial and ongoing costs of digitization.

I have to respectfully disagree with the whole concept of PQRI and e-Rx initiatives. The notion of claims-based reporting is such an enormous blunder, that it will be a near-impossible task (especially for small offices without data-entry staff) to complete these onerous tasks in order to qualify for bonus payments. One has to just see the results of the 2007 PQRI process to realise the scale of this disaster. Any clinician worth his degree will confrim that remembering to add extra CPT-II codes to a superbill at the time of patient visit is a near-impossibility, in the midst of a busy schedule.This scheme was obviously designed with large group practices in mind, and to minimise any incentive payment obligations while still appearing to foster reporting of “Quality care”. For most folks who did get the bonuses, it was all about adding a very fancy cover to a rather ordinary book.

Finally, the new government will need to set up a non-partisan body with adequate authority to regulate IT vendors and level the playing field between physician practices and IT companies, whereby disputes can be quickly resolved and fair play ensured in the health IT field.

I certainly believe that there is an important role to be played by Medicare in collecting and promulgating information about the effectiveness of health care technologies and that such efforts can help make the health care system more efficient overall as well as helping individual patients receive the best possible care at the lowest possible cost. The challenge can be exemplified by looking at pharmaceuticals used to treat chronic conditions.

Analyzing effectiveness in the real world, as opposed to efficacy in trials, is difficult, however. The need to capture information that reflects the breadth of experience of actual patients requires large populations and makes controlled clinical trials prohibitively expensive. In such populations, there are many factors that can cloud the connection between patient outcomes and the treatments, specifically pharmaceuticals in real word usage and make it difficult to infer causality.

One possible data source for capturing data on drug use among large populations is administrative or claims data resulting from the process of billing insurance carriers for medical care. Such data sets enable the analysis of patient histories over extended periods by accumulating claims for services, which including diagnoses and procedures. However, such claims rarely include clinical information in needed to assess the need for treatment or the severity of disease.

We have been actively engaged in research using data from one of the rare cases where such clinical data is collected as part of the claims process. – the case of epoetin to treat anemia (see: http://www.mtppi.org/frameset.asp?Pg=/&MI=1). In this case, Medicare requires providers to report the hematocrit, or red blood cell level of patients in order to be reimbursed for their anemia treatment.

Since anemia is the primary driver of epoetin dosing, we have applied advanced statistical techniques to correct for the tendency of patients with the most severe anemia to receive the most aggressive treatment. We feel that this example can be used as a pattern for the possibilities of collecting limited clinical data via the claims process to be used for measuring effectiveness.

In addition, using the claims process to collect such information will only be useful when the prescription is itself billed to the insurance provider and is accompanied by an encounter with a provider that is also billed. If the test yielding the physiological data to be analyzed can be required for payment, and the connection between that measurement and the prescription can be reliably made.

As we wait for electronic records to come online, collecting even limited clinical information in these circumstances could greatly enhance the ability of researchers to develop evidence of effectiveness based on administrative data that include large populations.