The use of a computer-based decision support system facilitates primary care physicians' management of chronic pain

Citation
Jh. Knab et al., The use of a computer-based decision support system facilitates primary care physicians' management of chronic pain, ANESTH ANAL, 93(3), 2001, pp. 712-720
Citations number
28
Categorie Soggetti
Aneshtesia & Intensive Care","Medical Research Diagnosis & Treatment
Journal title
ANESTHESIA AND ANALGESIA
ISSN journal
00032999 → ACNP
Volume
93
Issue
3
Year of publication
2001
Pages
712 - 720
Database
ISI
SICI code
0003-2999(200109)93:3<712:TUOACD>2.0.ZU;2-0
Abstract
We tested whether computer-based decision support (CBDS) could enhance the ability of primary care physicians (PCPs) to manage chronic pain. Structure d summaries were generated for 50 chronic pain patients referred by PCPs to a pain clinic. A pain specialist used a decision support system to determi ne appropriate pain therapy and sent letters to the referring physicians ou tlining these recommendations. Separately, five board-certified PCPs used a CBDS system to "treat" the 50 cases. A successful outcome was defined as o ne in which new or adjusted therapies recommended by the software were acce ptable to the PCPs (i.e., they would have prescribed it to the patient in a ctual practice). Two pain specialists reviewed the PCPs outcomes and assign ed medical appropriateness scores (0 = totally inappropriate to 10 = totall y appropriate). One year later, the hospital database provided information on how the actual patients' pain was managed and the numb er of patients re -referred by their PCP to the pain clinic. On the basis of CBDS recommendat ions, the PCP subjects "prescribed" additional pain therapy in 213 of 250 e valuations (85%), with a medical appropriateness score of 5.5 +/- 0.1. Only 25% of these chronic pain patients were subsequently re-referred to the pa in clinic within I yr. The use of a CBDS system may improve the ability of PCPs to manage chronic pain and may also facilitate screening of consults t o optimize specialist utilization.