健康檢查中心流程模擬之效率最佳化探討

The study of the optimal effectiveness of health examination procedure simulation

10.6834/CSMU.2012.00142

陳思安

健康檢查 ； 等候時間 ； Health examination ； waiting time

中山醫學大學醫療產業科技管理學系碩士班學位論文

2012年

碩士

廖宏昌

繁體中文

由於人口結構轉變以及醫療技術的進步，國人疾病型態由急性疾病漸漸轉變為糖尿病、心臟病及高血壓等慢性疾病，大多數疾病都可以透過瞭解疾病之發展史來擬定預防措施，國內預防工作大多採用公共衛生之三段五級來做預防，強調「預防勝於治療」的重要性，在人們尚未出現症狀時發現疾病潛在及危險因子並加以介入，透過定期健康檢查以維持其健康的生活型態並減少疾病之發生，然而，健康檢查的流程相當繁鎖且複雜，受檢者往往無法在預期的時間內完成檢查，因此，如何管理健康檢查流程並提升服務品質及效率為一大考驗。 本研究欲針對健康檢查之受檢流程進行改善，擬定改善方案，採用Microsoft visual studio 2010建構模擬系統環境，並運用反應曲面法配適迴歸模型，再藉由基因演算法找出最佳方案，從受檢者以及經營者的角度進行敏感度分析。 研究結果發現在平均等候時間(Y1)之下，預約間隔時間約為3分鐘，也就是將每一位受檢者的預約間隔時間定為3分鐘並且增加檢查項目，依人員的經驗進行受檢流程調度，帶領受檢者檢查，最能降低平均等候時間。 在平均健康檢查時間(Y2)之下，預約間隔時間為10分鐘，需將每一位受檢者的預約間隔時間間隔10分鐘並且依其人員的經驗帶領受檢者檢查，毋須增加檢查項目，最能降低平均健康檢查時間。 在檢查站平均閒置時間(Y3)之下，預約間隔時間為受檢者同時到達，並且依其人員的經驗帶領受檢者檢查，毋須增加檢查項目，最能降低檢查站平均閒置時間。 在理想函數(Y4)之下，每一位受檢者的預約間隔時間間隔4-5分鐘，並且依其人員的經驗帶領受檢者進行檢查並增加檢查項目，此函數採用加權平均的概念，為取得中間平衡點，係為較佳方案。

With the change of population structure and the improvement of medicine in Taiwan, the disease pattern has changed from acute illnesses from chronic diseases such as diabetes mellitus, cardiovascular diseases and hypertension. Most of which could be prevented by understanding the progression of the disease. Public health policy to prevent those diseases is mostly under the concept of a three-level (primary, secondary and tertiary prevention) and a five-stage (promotion, specific protection, screening, limitation of disability and rehabilitation) system, which emphasizes that “prevention is better than treatment”. Through regular health check-ups and change of lifestyles, we can discover the latent diseases and its risk factors, and preventive interventions can be done to decrease the incidence of chronic illnesses. However, the process of health check-up is very sophisticated, which enables the receivers to complete within an expected time. Therefore, it is a great task to manage and improve the health check-up procedures in order to improve the quality of it. This study aimed to improve the procedure of health examinations. A systemic environment was built by using Microsoft visual studio 2010; regression model was adopted by the response surface methodology; and the best solution was found via genetic algorithms. Finally, the sensitivity analysis was made from the aspects of the recipients and the operators The study found that under the average waiting time (Y1), the appointment interval between each health examination recipient was around 3 minutes, which means that when appointments for the recipients are separated every 3 minutes along with more examinations, adjusted by experienced staff, a minimal average waiting time could be achieved. Under the average health examination time (Y2), the appointment interval between each health examination recipient was 10 minutes. In this circumstance, if we separate each health examination recipient in 10 minutes, without examinations added, adjusted by experienced staff, we could achieve a minimal health examination of time. Under the average idle time (Y3) of each medical examination unit, the appointment interval between each recipient was to arrive at the same time and be adjusted by experienced staff, without adding extra examinations, so that we could achieve a minimal idle time for medical examination units. Under the ideal function (Y4), the appointment interval between each recipient was 4-5 minutes; with extra examination added, and be adjusted by experienced staff, we can achieve the best solution under the concept of weighted average.

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