為高風險，低敏感性的經直腸前列腺切片手術，
開發以患者為導向，基於醫學研究證據的醫療共識輔助解釋程式
許家禎
嘉義市 陽明醫院 泌尿科
Develop a Computer-Assisted, Evidences-Based, Patient-Oriented Consensus Explanation System for Hight Risk, Low Sensitive Procedure: Transrectal Prostate Biopsy
Jia-Jen Shee
Department of Urology, Yang Ming Hospital, Chia-Yi City, Taiwan
Purpose
Transrectal Prostate Biopsy (TRPB) is the most necessary procedure while igniting a prostate cancer (CaP) management. However, some studies prove the sensitivity of TRPB diagnosis to around 53%, and the negative predictive value of the sextant core procedure was only 36%. One the other way, total perioperative complications of the TRPB may rise to more than 75%. We try to introduce a clinical computer assistant program with evidences-based data and visualization techniques to count the personal possibility of CaP to the patient for better-informed consensus before TRPB.
Materials and Methods
In the beginning, we raise a small investigate to know that the patient considers most on “the necessary” for a high-risk surgical procedure. For TRPB, we collect Asian-Taiwanese related articles that provide a countable probability of CaP with different risk factors. A PC based computer assistant software was developed from those scientific data. It needs to input Age, PSA, free-PSA, DRE, prostate volume and TRUS finding for analysis. The personal probability of CaP can be well counted and informed in this program. It presents the analysis result with both figure and text explanation on screen. Further summary paper prints with color text on both English and Chinese are available, too.
Result
The program is called PPCaP (means: Personal Probability of CaP). In our preliminary test, the program can well accept by patients. It had convinced four patients, whose PSA raised but strongly refused TRPB initially, to accept procedures. One of the 4 cases accepts the suggestions in a 1-month interval after the program running two times to proves that his CaP incidence is rising by time.
Conclusion
Our Consensus Assist software can help clinical work. We still need to cooperate for larger-scale IRB proved project to test the software.