應用貝氏理論之72小時急診回診提醒機制

The reminding mechanism with Bayesian theory for the emergency revisit with in 72 hours

郭大威(DA-WEI GUO)

指導教授 ： 賀嘉生

中原大學/工學院/資訊工程研究所/碩士(2013年)

https://doi.org/10.6840/cycu201300549

摘要

中文摘要
透過醫療診斷輔助機制協助提醒醫護人員於判斷病症、病因的ㄧ項參考性數據，協助於提升醫療品質、降低病患回診機率的發生，現代社會交通複雜、意外事故頻傳，加上慢性病、精神疾病患者的增加，使得各地區醫院急診室成為醫療體系當中最為忙碌的單位。如何有效率的提昇急診醫療品質及降低病患回診的發生，使病人重複回診次數降低和於72小時內回診人數減少，成為一項刻不容緩的重要方向。
近年來國人普遍就醫次數有逐年上升的趨勢，各地醫療院所急診就診人數亦有逐年增加的趨勢，這使得一天二十四小時不能片刻停止運作的急診室幾乎成為醫療院所中最為忙碌的單位。其服務內容與醫療品質亦不斷地受到衝擊。為了有效確保急診醫療品質，使得每一位到急診就醫的病患都能得到完善且完備的醫療照護，如何建立與採行醫療輔助指標系統來監控與改善急診醫療作業，成為各醫療院所的當務之急。
本研究著重於將曾經可能發生回診的狀況彙整後，運用貝氏理論的原理反向推導出前因，比對原始資料後進行分析修改，套用系統架構推導病患因為疾病因素發生重複性回診的機率值。應用於回診提醒系統，針對每位到院就診病患進行推演，計算出可能回診的機率並於適當時機提醒醫護人員針對該名病患是否需要做進一步的檢查檢驗或者是加強護理指導及衛教單張的宣導，重覆這一類方式來降低回診機率的發生。主要目的在於建立急診病患72小時內重返入院的疾病因素知識庫、運用貝氏理論原理建置回診提醒機制系統，進而降低病患就診後發生回診的可能性。

關鍵字

決策輔助系統 ； 醫療輔助提醒機制 ； 貝氏理論 ； 72小時重複回診

並列摘要

Abstract
Through medical diagnosis assistance mechanism, it is possible to remind the medical personnel while in determining one reference data for symptoms and the causes of the diseases. And it can facilitate raising the level of medical quality and lowering the reoccurrence of chances that patients return for treatment. In modern society, amid the complex traffic patterns with frequent reported accidents in addition to increases in chronic diseases as well as mental patients, therefore all emergency clinics for regional hospitals have become the busiest unit within medical system. Hence how to effectively raise the level of medical quality as well as lower the occurrence of patient revisit, decrease repeated revisits and the number of revisit to hospital within 72 hours timeframe have become one of the pressing and indispensible indicators.
During recent years it has been witnessed that there is a trend indicating the increase of patient going to the hospital. Moreover the number of emergency clinic visit for all hospitals and clinics has also risen on annual basis prompting the emergency clinic nonstop running 24x7 to become the busiest unit among all hospitals and clinics. Thus its service content as well as medical quality has undergone constant onslaught. In order to effectively ensure emergency medical quality and provide comprehensive medical care for every patient arrived for medical assistance, and how to establish and adopt medical assistance indicator system so as to surveillance and enhance medical operation have become the top priority for all hospital and clinics as result.
This study placed the efforts at compiling data for the probable and possible patient revisits and applied the reverse derivation from Bayes’ theorem to deduce the antecedents then proceeded to compare against original data so as to analyze and revise. Then it was followed with applying system architecture to deduce the patient factors leading up to probabilities for occurrence of repeated clinic revisit. After applied clinic revisit reminder system for derivation which targeted to all patients came to the clinics, we calculated the probability for clinic revisit in addition to timely remind medical personnel for determining whether further inspection and examination for this patient or strengthening nursing guidance as well as health care leaflets promotion is necessary. In addition the repetition of this kind of approach was observed that it could lower the probability of clinic revisit. The main objective rests at the establishment for disease factor knowledge database for 72-hour clinic revisit by emergency clinic patients. Alternatively this thesis applied Bayes’ theorem to set up clinic revisit reminder mechanism system so as to lower the possibility for occurrence of clinic revisit by the patient who had already received medical care.

並列關鍵字

Decision support system ； 72-hour clinic revisit ； Bayes' theorem ； Reminder mechanism for medical assistance

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