術後疼痛病患使用自控止痛裝置疼痛模型分析研究

疼痛，一直以來總是令人唯恐避之不及，尤其是手術後伴隨而來的疼痛更是讓人難以忍受。在早期的醫學上，就已有醫學人員發展出麻醉藥來減輕病患的疼痛。但是若使用過量的麻醉藥，亦會使人產生不舒服的副作用，甚至有生命危險。隨著醫學及科技快速的進步，美商Hospira研發出病患自控止痛裝置(PCA)。此裝置能夠在無醫護人員的狀態下，有效的給予病患適當的麻藥，以達到減輕病患疼痛的目的。此外在個人行動裝置(PDA)逐漸普及的情況下，i-Pain系統發展出利用PDA裝置來收集病患術後疼痛的紀錄與評估。此外收集來的紀錄可與PCA裝置的病歷進行整合，成為一個完整的病歷資料。藉由i-Pain系統的幫助，醫師得以藉由主觀上的疼痛分數分析對病患的嗎啡使用量進行客觀的調整，對於巡房的醫護人員更能節省時間和提高效率。本篇論文的研究目的是希望透過i-Pain系統以PDA裝置收集病患術後疼痛的評估與紀錄，並且搭配PCA裝置的紀錄找出兩者間的關係。而在研究過程中，將針對性別一致且大部分手術相同的婦產科病患為研究對象。經過一段時間的病歷資料收集後，篩選出在術後四到八小時內有巡視過的病患紀錄，並且針對這些病患的當下疼痛分數 (VASr)、最痛疼痛分數(VASw)及PCA裝置的紀錄為變數，建立起病患疼痛分數的分析模型。最後的實驗結果，呈現出一個數學模型，讓我們能輸入傳統的PCA裝置紀錄推測病患的疼痛分數。PCA裝置紀錄包括按鍵的次數、平均藥劑使用量以及按鍵次數與給藥次數的比率。

關鍵字

i-Pain系統；病患自控止痛裝置；個人行動裝置；疼痛

並列摘要

Pain is a physiological effect that people hate, as it hurts, especially after an operation. In the past, medical staff found that using anesthetics could release pain. But using anesthetics over the standard dose can make patients feel uncomfortable and even put them in a risky situation. With the aid of new technology, Hospira developed a patient-controlled analgesia device. This device can give patients a shot to release the pain without the aid of a nurse. By using a popular personal digital assistants device (PDA), the i-Pain system uses the PDA to collect a patient’s records. It can also receive data from the Patient-Controlled Analgesia (PCA) and combine this with the PDA’s information to complete the patient’s record. Because of the i-Pain system, clinicians can regulate morphine better using a visual analogue scale (VAS) score, which saves a nurse time. The major purpose of this study is to evaluate the relationship between a patient’s VAS from a PDA and the records from the PCA device. The participants were patients of the same sex and most of them were at the same operation - in the obstetrics and gynecology department of Shin Kong Wu Ho-Su Memorial Hospital. The result of this study presents a model with the VAS scores and the traditional medical records which are the Demands, the Mean Drug Consumption (MDC) and the D/D ratio from PCA devices. Through the model, we could input these variables to infer the patients’ VAS scores.

並列關鍵字

i-Pain system ； Patient-Controlled Analgesia ； personal digital assistants ； Pain

參考文獻

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術後疼痛病患使用自控止痛裝置疼痛模型分析研究

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