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In Response
Submit responseWe thank Drs. Wu and Shah for their thoughtful letter. Just to be clear, I was not criticizing bar-code systems in general. Bar-coding is the perfect solution for many identification problems, e.g. the identification of groceries at the checkout counter and we all appreciate the resultant faster checkout times. My criticism was limited to bar coding systems used to verify medication dispensing at the bedside. (1) Both published reports and recent conversations with disappointed CEOs suggest that these systems have not delivered the nursing time savings, and error elimination they promised. Further, they appear to change nursing priorities - an un-intended consequence. I am sure that with time and improved technology these systems will meet their mark, but the available evidence contradicts the frothy hype for rushing to these systems today.
There is a general lesson here. The health care industry expects information technology (IT) – such as bar-coded medication dispensing and physician order entry – to solve many/most of its problems. These are plausible expectations and many will eventually be realized. However, today, the hype and the hope have run far ahead of the evidence and experience. We need to critically examine the benefits and harms of these systems as implemented in operating environments to determine what works and what doesn’t and to identify design flaws and miss-assumptions as Patterson (2) did for bar coding and others have done for CPOE. Only with such knowledge will these products improve and reach their full promise.
The expectations about Six Sigma for health care may also be a bit frothy. Even in manufacturing the real achievement may only be four and a half, rather than Six, Sigma and some question its applicability to fields outside of manufacturing. (3) Given that health outcomes are not influenced by many fold increases in care process investment (4) and the fact that care costs have reached crisis levels - one might wonder whether this is the time to eliminate costly but marginal processes rather than investing even more to perfect them.
I agree that methods for capturing data derived from patients have value and am a fan of the work by Hripcsak, et al. (5) Natural language processing should become a major asset to medical information management.
1. McDonald CJ. Computerization Can Create Safety Hazards: A Bar- Coding Near Miss. Ann Intern Med. 2006; 144:510-516.
2. Patterson ES, Cook RI, Render ML. Improving patient safety by identifying side effects from introducing bar coding in medication administration. J AmMed Inform Assoc. 2002;9:540-53.
3. White E. Rethinking Quality Improvement. Wall Street Journal Sept. 19, 2005, page B3.
4. Sirovich BE, Gottlieb DJ, Welch HG, Fisher ES. Regional Variations in Health Care Intensity and Physician Perceptions of Quality of Care. Ann Int Med, May 2, 2006; Vol 144 (9); 641-649.
5. Hripcsak G, Austin JH, Alderson PO, Friedman C. Use of natural language processing to translate clinical information from a database of 889,921 chest radiographic reports. Radiology. 2002 Jul;224(1):157-63.
Conflict of Interest:
None declared
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Corporate Strategies for Computerization
Submit responseCorporate Strategies for Computerization
The critique of computerization by McDonald (1) highlights advice that all physicians would do well to heed. The ease of bar-coding can allow us to become automatons, shedding our critical thinking in the process. While McDonald touched upon technological alternatives and systematic changes that would improve such innovations as bar-coding, we suggest some additional lessons that medicine can learn from the corporate world.
Corporate principles can enhance patient safety while maintaining a culture of efficiency and effectiveness. The emergence of Six Sigma principles (2) and quality management departments as applied to medicine is promising. Kiosks have been used extensively at airports and financial institutions. The advent of a patient-centric kiosk, where patients self- input their information, has potentially large implications for efficiency and patient safety (3). Another common retail practice involves the repetition of an order. With the exception of blood product administration, this repetition is seldom used in medicine. To review a process with a patient sounds so simple, yet so difficult to enact in clinical practice. Medicine could learn from business by involving its customers – patients – more.
In addition to the technologies mentioned by McDonald, one that deserves mention is natural language processing (NLP). Still in its infancy, NLP can enhance adverse event detection (4). This technology utilizes computer algorithms to detect potential adverse events within the confines of an electronic medical record. The key challenge will be to integrate NLP into processes which inform providers in a timely and appropriate fashion, so as to prevent adverse events. While bar-coding can dull our sensibilities, NLP can heighten our senses to adverse events.
It is inevitable that new technologies will emerge as we shuttle patients through a hospital. How we implement these new technologies should not rest solely with a consultant, a vendor, or a committee. Our technology solutions should be looked upon in the same way that we care for patients—from head to toe.
1. McDonald CJ. Computerization Can Create Safety Hazards: A Bar- Coding Near Miss. Ann Intern Med. 2006; 144:510-516. [PMID: 16585665]
2. Hagland M. Six Sigma: It's real, it's data-driven, and it's here. Health Care Strategic Management. 2005; 23: 12-16. [PMID: 16445106]
3. Porter SC, Cai Z, Gribbons W, Goldmann DA, Kohane IS. The asthma kiosk: a patient-centered technology for collaborative decision support in the emergency department. Journal of the American Medical Informatics Association. 2004;11:458-67. [PMID: 15298999]
4. Melton GB, Hripcsak G. Automated Detection of Adverse Events Using Natural Language Processing of Discharge Summaries. J Am Med Inform Assoc. 2005;12:448–457. [PMID: 15802475]
Conflict of Interest:
None declared