PTJ
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


PHYS THER
Vol. 86, No. 5, May 2006, pp. 761-762

This Article
Right arrow Full Text (PDF)
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Rapid Responses are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Vreeman, D. J
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Vreeman, D. J
Related Collections
Right arrow Evidence-Based Practice
Right arrow Clinical Prediction Rules
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?

Letters and Responses

Clinical Prediction Rules



   To the editor
 
I am writing to commend Childs and Cleland1 for their timely and insightful article on clinical prediction rules (CPRs) (January 2006). Their article highlights the potential value for practicing physical therapists who incorporate such rules into their clinical decision making and care delivery. As the authors note, however, the mere existence of high-quality guidelines does not guarantee that they will actually influence practitioner behavior. An important challenge is that guidelines demand the attention and memory of clinicians who are already overburdened.

I concur with the authors’ recognition and discussion of the practical barriers to using CPRs, but was hoping that they would elaborate further on potential ways to overcome these challenges. I would like to extend their discussion of these issues to include consideration of a widely studied intervention for changing clinician behavior: the computerized suggestion.

While humans struggle with the "prospective recall" necessary to implement guidelines such as CPRs, computers are unflagging data processors. We have convincing evidence that computergenerated suggestions to clinicians about preferred care options can have a measurable and important impact on care outcomes.25 Indeed, in the same issue of JAMA where Stiell et al6 published their implementation trial of the Ottawa ankle rules, McDonald and Overhage7 wrote in an editorial that the Ottawa rules were exemplary not only because of the rigor with which they were developed, but also because they were decidable and actionable—the kind of guideline whose processing could be turned over to a computer. Physical therapists can glean much from the medical informatics community’s 30-plus years of experience in developing and evaluating systems that support clinical decision making. Although computer systems with advanced features such as clinical decision support are not yet common in physical therapist practice,8 they may be an essential tool for enabling busy clinicians to put CPRs and other guidelines into practice.

Many evaluations of systems that implement computerized guidelines have found a substantial benefit. For example, a systematic review of the functionality and effectiveness of such systems found that guideline adherence improved in 14 of 18 systems in which it was measured.9 Additionally, effective systems have described important factors for success in implementing computerized guidelines.10 Certainly, computerized systems are not a panacea for guideline adherence. In particular, the complex sociotechnical interaction presents many challenges, as illustrated in a randomized controlled trial of a computer system with automated care suggestions that was previously shown to increase preventive care and reduce costs, but failed to show improvement in adherence to evidence-based guidelines for managing asthma and chronic obstructive pulmonary disease.11

Childs and Cleland highlighted the value of CPRs, a special subset of the larger body of clinical practice guidelines. Clinical practice rules may have unique challenges to implementation and computerization, in part because executing them often requires input data from both the patient and the provider. Successful computerized implementations may demand creative interfaces to capture and process the needed information. One working example of a clinical decision support system designed to overcome the myriad barriers to implementing guidelines in a busy outpatient pediatric clinic is Child Health Improvement Through Computer Automation (CHICA).12,13 CHICA provides patientspecific suggestions that are informed by both existing information in the electronic health record and data collected at the encounter from families and clinicians. Interestingly, the interface for families and clinicians who interact with CHICA is not a computer workstation, but rather computer-interpretable, bilingual paper forms.

By applying the lessons learned from existing studies of computerized guideline implementations and by adopting systems with effective features that "make it easy to do it right,"14 physical therapists can move more quickly toward our goal of delivering more informed and effective care.

Daniel J Vreeman, PT, DPT

Visiting Assistant Research Professor of
Physical Therapy
Indiana University
Research Scientist
Regenstrief Institute, Inc.

References

  1. Childs JD, Cleland JA. Development and application of clinical prediction rules to improve decision making in physical therapist practice. Phys Ther 2006;86:122–131.[Free Full Text]
  2. Dexter PR, Perkins S, Overhage JM, et al. A computerized reminder system to increase the use of preventive care for hospitalized patients. N Engl J Med 2001;345:965–970.[Abstract/Free Full Text]
  3. McDonald CJ. Protocol-based computer reminders: the quality of care and the non-perfectability of man. N Engl J Med 1976;295:1351–1355.[Abstract]
  4. McDonald CJ. Use of a computer to detect and respond to clinical events: its effect on clinician behavior. Ann Intern Med 1976;84:162–167.[Web of Science][Medline]
  5. McDonald CJ, Hui SL, Smith DM, et al. Reminders to physicians from an introspective computer medical record: a twoyear randomized trial. Ann Intern Med 1984;100:130–138.[Abstract/Free Full Text]
  6. Stiell IG, McKnight RD, Greenberg GH, et al. Implementation of the Ottawa ankle rules. JAMA 1994;271:827–832.[Abstract/Free Full Text]
  7. McDonald CJ, Overhage JM. Guidelines you can follow and can trust: an ideal and an example. JAMA 1994;271:872–873.[Abstract/Free Full Text]
  8. Vreeman DJ, Taggard SL, Rhine MD, Worrell TW. Evidence for electronic health record systems in physical therapy. Phys Ther 2006;86(3):434–449.
  9. Shiffman RN, Liaw Y, Brandt CA, Corb GJ. Computer-based guideline implementation systems: a systematic review of functionality and effectiveness. J Am Med Inform Assoc 1999;6:104–114.[Abstract/Free Full Text]
  10. Tierney WM, Overhage JM, McDonald CJ. Computerizing guidelines: factors for success. In: Proceedings of the American Medical Information Association Annual Fall Symposium 1996: 459–462.
  11. Tierney WM, Overhage JM, Murray MD, et al. Can computer-generated evidence-based care suggestions enhance evidence-based management of asthma and chronic obstructive pulmonary disease? A radomzed, controlled trial. Health Serv Res 2005;40:477–497.[Web of Science][Medline]
  12. Anand V, Biondich PG, Liu G, et al. Child Health Improvement Through Computer Automation: the CHICA system. Medinfo 2004;11(Pt 1):187–191.
  13. Biondich PG, Anand V, Downs SM, McDonald CJ. Using adaptive turnaround documents to electronically acquire structured data in clinical settings. In: Proceedings of the American Medical Information Association Annual Fall Symposium 2003: 86–90.
  14. James BC. Making it easy to do it right. N Engl J Med 2001;345:991–993.[Free Full Text]

Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati    What's this?



This Article
Right arrow Full Text (PDF)
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Rapid Responses are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Vreeman, D. J
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Vreeman, D. J
Related Collections
Right arrow Evidence-Based Practice
Right arrow Clinical Prediction Rules
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati  
What's this?


HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
Copyright © 2006 by the American Physical Therapy Association.