تحلیل عوامل مؤثر بر طول مدت اقامت بیماران با استفاده از خوشه‌بندی و قوانین انجمنی (مطالعه موردی: بیمارستان امیرالمؤمنین مراغه)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه مهندسی صنایع، واحد بناب، دانشگاه آزاد اسلامی، بناب، ایران

2 گروه ریاضی، واحد بناب، دانشگاه آزاد اسلامی، بناب، ایران

چکیده

یکی از شاخص‌های عمده در ارزیابی عملکرد بیمارستان‌ها و مدیران آنها، متوسط طول مدت اقامت بیماران است؛ با توجه به اهمیت این شاخص در مطالعه حاضر به بررسی عوامل مؤثر بر طول مدت اقامت بیماران بستری پرداخته شده است. این پژوهش با هدف شناسایی عوامل کلیدی تأثیرگذار بر طول مدت اقامت بیماران و ارائه راهکارهای عملی برای بهبود مدیریت تخت‌های بیمارستانی انجام شده است. داده‌های ۲۶۹۰۷ بیمار با استفاده از ارائه مدل‌های خوشه‌بندی الگوریتم‌های خوشه‌بندی (K-Means) و استخراج قوانین انجمنی (Apriori) تحلیل شدند. داده‌ها شامل 10 ستون عددی و گسسته است. متغیرها شامل 10 مورد که به ترتیب عبارتنداز : جنسیت، وضعیت تاهل، بخش بستری، تخصص پزشک، بیمه، تزریق خون، عمل جراحی، نوع ترخیص، سن و طول مدت اقامت می‌باشد. یافته‌ها نشان داد که متغیرهای عمل جراحی و تزریق خون بیشترین تأثیر را بر طول متوسط طول مدت اقامت در بیمارستان دارند.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Analysis of factors affecting the length of stay of patients using clustering and association rules (Case study: Amir al-Momenin Hospital, Maragheh)

نویسندگان [English]

  • Mahdi Yousefi Nejad 1
  • Karim Farajian 2
  • Hossein Jaleb 2
1 Department of industrial engineering, Bon.C., Islamic Azad University, Bonab, Iran
2 Department of Mathematics, Bon.C., Islamic Azad University, Bonab, Iran
چکیده [English]

One of the major indicators in evaluating the performance of hospitals and their managers is the average length of stay of patients; given the importance of this indicator, the present study has examined the factors affecting the length of stay of hospitalized patients. This study was conducted with the aim of identifying the key factors affecting the length of stay of patients and providing practical solutions for improving the management of hospital beds. Data from 26,907 patients were analyzed using clustering models, clustering algorithms (K-Means) and association rules extraction (Apriori). The data consists of 10 numerical and discrete columns. The variables include 10 items, which are respectively: gender, marital status, hospitalization department, physician specialty, insurance, blood transfusion, surgery, type of discharge, age, and length of stay. The findings showed that the variables of surgery and blood transfusion have the greatest impact on the average length of stay in the hospital.

کلیدواژه‌ها [English]

  • Data mining
  • clustering
  • length of stay
  • Apriori Algorithm

مراجع

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