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博碩士論文 etd-0719100-142513 詳細資訊
Title page for etd-0719100-142513
論文名稱
Title
醫療品質管理之研究—以加護病房生命徵象之心跳監測過程為例
A Study of Quality Management in Health Care-Vital Signs Monitoring Process at ICU
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
105
研究生
Author
指導教授
Advisor
召集委員
Convenor

口試委員
Advisory Committee
口試日期
Date of Exam
2000-07-14
繳交日期
Date of Submission
2000-07-19
關鍵字
Keywords
加護病房、醫療品質管理、全面品質管理、控制圖、病歷維護、生命徵象偵測、非直接病人照護
intensive care unit (ICU), total quality management, health care quality management, control chart method, patient records maintaining, vital signs monitoring, non-patient care
統計
Statistics
本論文已被瀏覽 5651 次,被下載 4183
The thesis/dissertation has been browsed 5651 times, has been downloaded 4183 times.
中文摘要

製造業與服務業經常使用全面品質管理方法,來持續改善公司全面性品質; 同樣地,全面品質管理方法於醫療品質管理,亦扮演著關鍵的角色。許多經驗顯示改善相關醫療品質時,會面對非直接病人照護、病歷與生命徵象偵測之主要問題。本研究以全面品質管理方法改善加護病房醫療品質進行探討,包括部份解決方案及品質管理典範; 並以加護病房生命徵象偵測之過程為例。
我們討論以 〝醫療品質發展生命週期 〞方法,改善非直接病人照護品質;此週期共包括七個階段:品質需求分析、品質規格訂定、品質設計、品質施行、品質測試、品質維護與品質確認。 並深入探討前三階段,以改善加護病房非直接病人照護品質。透過品質需求分析,加護病房有關非醫療品質,涵蓋了行政品質、設備品質與環境品質。
改善病歷品質,首先將醫療資訊系統分類為行政作業系統、決策支援系統、臨床資訊系統與醫療資訊系統。根據此分類與經驗,發現一些有趣結果。例如,目前高雄與台南之教學醫院實施的資訊系統多以行政與臨床資訊系統為主;另外,其諮詢系統使用的病歷,並不完全涵蓋重要資料或不易使用線上病歷。為了改善加護病房病人病歷維護品質,本文建構病歷維護模式,並設計加護病房病人病歷應有資訊。
提高生命徵象偵測品質﹐有效偵測生命徵象結果與控制異常生命徵象是很重要的。為了改善加護病房生命徵象偵測品質,本研究以心跳資料為例;醫護人員可以藉著心跳狀況,瞭解人體自律神經的互動關係。我們使用數位機將心跳圖轉換成電腦可以運算之資料檔,且依據病人病歷記載資訊,將病人樣本分成死亡與正常二類;並進一步將資料轉換成可以反應更多心臟資訊的頻譜資料,以作統計分析。為了發現與目標值不一致之微小心跳異動,經過本研究實驗數種控制圖方法後,我們建議使用Cusum控制圖法。使用病人心跳為觀察變數,Cusum法可依警訊指出某時段之心跳是否改變,及偵測平均值是否異動。本研究發現死亡樣本之落於上下界限外觀測值的個數較多,其明顯指出於偵測生命徵象過程時,死亡樣本之Cusum控制圖提供及時需要之醫療資訊。而且Cusum控制圖亦使加護病房醫護人員,明白病人心跳是否連續加快或減慢與自律神經的調整,以採取進一部的應變措施。
Abstract
Total quality management (TQM) approach is often used to carry out company-wide continuous quality improvement plans in manufacturing and service industries. Similarly, TQM can also play a critical role for quality management in health care. Aiming to improve health care quality, experiences showed that major problems of non-patient care, patient records and vital signs monitoring are encountered. In this study, we aim to introduce TQM for quality improvement for intensive care unit (ICU) operations, including some solutions and the prototype of quality management. And vital signs monitoring at ICU is taken as an example of process.
For quality improvement of non-patient care, Health Care Quality Development Life Cycle, including (1) quality requirement analysis, (2) quality specification review, (3) quality design, (4) quality implementation, (5) quality testing, (6) quality maintaining, and (7) quality validation, is discussed. The prototype of the first three phases for quality improvement at ICU is explored. Through quality requirement analysis, non-patient care quality at ICU is defined in areas of administration, facility and environment.
For quality improvement of patient records maintaining, firstly, scope of health care information systems is categorized as administrative operational system, decision support system, clinical information system, and medical information system. According to this categorization and experience, some interesting result is found. For instance, the current applications of information systems for teaching hospitals in southern Taiwan surveyed are that most applications are administrative and clinical. And the essential information of patient records used in each information system is not complete or not easily accessed. Model of the patient record maintaining is introduced and the prototype design of patient records is recommended for quality improvement of patient records maintaining at ICU.
To improve quality of vital signs monitoring is one essential requirement and specification for ICU quality improvement. Effective outcome measures of vital signs monitoring and early detecting of abnormal vital signs is considered important. For quality improvement of vital signs monitoring at ICU, heart rate graphs are taken as examples in our study through the heart rate graphs monitoring. Health professionals can understand the interactions of human autonomic nervous system. By use of digitizer, the computable heart rate data is acquired from each graph and grouped into mortality and near-to-normal cases. Then spectrum form of heart rate data, describing more about heart function, is used for statistical analysis. Several control chart methods have been experimented to detect small heart rate shifts from target, cumulative sum control chart (Cusum) is adopted in our study. The observable variable is the patient’s heart rate, the purpose is to check the alarms pointed out by Cusum that could be partially be ascribed to changes of heart rate trend over time, and to a shift in the monitoring process mean. From summaries of nonconformities in the Cusum charts, mortality cases obviously have more nonconformities. It is obvious that Cusum control charts of mortality cases provide diagnostic information for vital signs monitoring process. In addition, Cusum charts may also inform ICU professionals that there is a small shift of patient heart rate, a continuously increasing or decreasing heart rate, and the adjustment of sympathetic nerve and parasympathetic nerve. In those cases, some special care is needed.
目次 Table of Contents
ABSTRACT i
TABLE OF CONTENTS iv
LIST OF TABLES vii
LIST OF FIGURES viii
CHAPTER 1 INTRODUCTION 1
1.1 Research Background 1
1.2 Problem Statement 2
1.3 Objective and Methodology 4
1.3.1 Research Objectives 4
1.3.2 Research Methodology 5
1.4 Outline of the Dissertat5ion 6
CHAPTER 2 LITERATUR7E REVIEW 8
2.1 Health Care and Total Quality Management (TQM) 9
2.1.1 Quality and TQM 9
2.1.2 TQM Applications in Manufacturing Industry 10
2.1.3 TQM Applications in Health Care Industry 11
2.2 Health Care and Process 13
2.2.1 Process and Total Quality Management (TQM) 13
2.2.2 TQM/Process Applications in Manufacturing Industry 14
2.2.3 TQM/Process Applications in Health Care Industry 15
2.3 Health Care and Continuous Quality Improvement (CQI) 16
2.3.1 CQI and Process 16
2.3.2 CQI Applications in Manufacturing Industry 17
2.3.3 CQI Applications in Health Care Industry 17
2.4 Health Care and Statistical Process Control (SPC) Techniques 18
2.4.1 QI and Quality Control Tools 18
2.4.2 SPC Techniques and CQI 19
2.4.3 SPC Applications in Manufacturing Industry 20
2.4.4 SPC Applications in Health Care Industry 21
CHAPTER 3 HEALTH CARE QUALITY 23
3.1 Non-Patient Care Problems 26
3.1.1 Non-Patient Care 26
3.1.2 Decision Making and Administrative Operation 27
3.1.3 TQM Approach and SPC Techniques 29
3.2 Patient Record Maintaining Problems 31
3.2.1 Patient Record Maintaining 31
3.2.2 Automation of Patient Records 34
3.2.3 Integrated DBMS 34
3.3 Patient Vital Signs Monitoring Problems 35
3.3.1 Patient Vital Signs Monitoring 35
3.3.2 SPC and Control Chart Methods 36
3.3.3 Cusum Control Chart 37
CHAPTER 4 NON-PATIENT CARE 39
4.1 Health Care Quality Development Life Cycle (HCQDLC) 39
4.2 ICU Care Quality Requirements 44
4.3 Non Patient Care at ICU 44
CHAPTER 5 Patient record maintaining 47
5.1 History and Scope of Information Systems 47
5.1.1 History of Health Care Information Systems 47
5.1.2 Scope of Health Care Information Systems 48
5.2 Patient Record Maintaining Problems 49
5.2.1 Patient Record and Vital Signs Monitoring 49
5.2.2 Information Flow of Patient Records 50
5.2.3 Integrated Database Management System 50
5.3 Prototype Design 53
CHAPTER 6 Vital Signs Monitoring 55
6.1 Quality Requirements of Vital Signs Monitoring 55
6.2 Computing and Data Resources 57
6.3 Using Cusum Technique 59
6.3.1 Control Chart Methods 59
6.3.2 Initial Experiments of Control Chart Methods 60
6.3.3 Spectrum Data 62
6.3.4 Cusum Procedures 65
6.4 Result and Discussion 66
6.4.1 Mortality Cases 68
6.4.2 Near-to-Normal Cases 68
6.4.3 Zoomed Cases 69
CHAPTER 7 CONCLUSIONS 72
7.1 Summary 72
7.2 The Major Contributions and Findings 73
7.3 Future Research 75

REFERENCES 77
APPENDIX 85
Appendix 1. Spectrum Analysis 88
Appendix 2. Figures of Heart Rate Data 88
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