The application of future technologies to medical informatics - Medical Informatics

Physician Executive, Jan, 1994 by David S. Greenberg

Although this article will discuss the wonderful information technologies that await the health care field, the important first steps are to define our mission and processes. A few premises:

* Health care is an industry similar to others, whose business rules and processes can be well defined.

* The purpose of applying technology to health care is to achieve dramatic improvements in measures of performance, such as cost, quality, service, and speed, through improvements in data acquisition, organization, and access.

* No application of technology will make an unsuccessful organization successful; the most successful implementations will be modeled after business processes that are already successful in the organization.

* Cost-effective system design mandates use of off-the-shelf, open architectures for health care information systems. Medical informatics does not require the application of unique or proprietary technologies.

* In time, technology will allow for new business processes that will permit quantum leaps in knowledge, efficiency, etc. Current system designs must be as flexible as possible to anticipate and accommodate these new technologies.

The health care industry, while using world-class technology for its diagnostic systems, is remarkably slow to adopt standards and implement systems for its information processes. If this were the transportation industry, we'd still be driving Model Ts, but not sure about which side of the road.

One possible reason for this rather slow adoption of technology and automation is the perception that the rules and processes of health care are too numerous or too mystically complex to succumb to algorithmic reduction. This is true only if you are trying to replace the critical human reasoning function performed by the physician, and in fact many medical informatics initiatives bog down trying to do just that. With the myriad computer systems required to fly a Boeing 747, no one suggests taking off without a pilot on board. The computer systems in that aircraft concentrate on automated monitoring systems, with information displays that support intelligent pilot decisions and automated control functions to carry out the repetitive functions resulting from pilot decisions. This multiplies the effectiveness of the pilot, allowing concentration on tasks that require human skills. Similarly, our medical informatics systems should emphasize multiplication of the physician's effectiveness, and not modeling of the neural network inside his or her brain.

Our mission is not merely to automate existing paper systems to reduce clerical staff costs, but also to achieve a much nobler goal of improving quality of care. The elusive measure of quality means different things to different people. To the medical academician, quality is measured in terms of outcomes--how many of our patients recovered from (or avoided) disease X as compared to some yet-to-be-derived national standard? There is a whole class of development efforts dedicated to measuring and improving performance in this area. One outcome may be the emergence of the OSHA doctor--"This is your computer speaking. Don't order that test. It won't tell you anything. Have you considered diagnosis Y. I would if I were you." Some refer to these as "mother-in-law" systems or "doc-on-a-disk."

To patients-consumers, given a reasonable assumption of proficiency on the parts of their providers, quality can be a matter of how long they are put on hold when they call to make appointments, how long they have to sit in waiting areas, whether nurses know that they were in last week for back pain, whether their lab results are ready when they call, and can the nurses answering calls get immediate access to these results. A whole host of indicators exist that can be classified as "health care delivery quality."

A reasonable approach for the application of technology to medical informatics, and the approach we've adopted locally, is to build a suite of applications that do what is possible today, namely a patient-centered online clinical information system, but with the "hooks" to support the guidelines-based outcomes management tools of tomorrow. By collecting the information we currently use and codifying it in a reasonable database schema, we will have at our disposal the base data from which and upon which more sophisticated clinical management tools can operate. In the meantime, we attempt to apply the best of today's technology to systems that increase our delivery quality, provide a usable clinical record, assist in the quality assurance/improvement function, and allow us to get a better handle on utilization patterns.

The nature of the clinical data in the current medical record is not particularly complex (unless you're trying to decipher handwritten text hieroglyphics). After all, the record is just a collection of data elements organized in some fashion. The typical chart is a study in "nonnormalized," unstructured data. By applying the skills of the data analyst, we really should not have too difficult a time with it. It is really quite amazing that no standards body has yet published a definitive, universally accepted data dictionary for the clinical record, although there are several versions in draft form. Most organizations building a clinical database today still have to "roll their own."