تحلیل کارایی و تخصیص منابع بیمارستانی با استفاده از روش تحلیل پوششی داده‌های متمرکز

این مقاله، کارایی و تخصیص منابع به بخش‌های مختلف بیمارستانی را با استفاده از روش تحلیل پوششی داده‌های متمرکز با فرض بازده متغیر با استفاده از نرم‌افزار متلب تحلیل کرده است. داده‌های مدنظر از واحد آمار، واحد حسابداری و واحد کنترل عفونت بیمارستان الزهرای اصفهان، برای تخصیص تخت به 31 بخش درمانی در سال 1390جمع‌آوری شد. شاخص‌های ورودی، دربردارندۀ تعداد تخت، تعداد پزشکان، تعداد پرستاران، فضای اختصاص داده‌شده به هر بخش و شاخص‌های خروجی، دربردارندۀ تعداد بیمار پذیرش‌شده، چرخش تخت، درصد اشغال تخت و تعداد مشاوره‌های انجام‌شده است. یافته‌ها نشان داد مجموع تعداد تخت فعال از 739 به 343.99، مجموع تعداد پزشکان از 399 به 391.51، مجموع تعداد پرستاران از 1258 به 1239.21 و مجموع فضای تخصیصی به بخش‌ها از 19010 به 15668.69 متر مربع تغییر پیدا کرده است. همچنین، میزان مجموع کاهش ورودی‌های به‌دست‌آمده از مدل متمرکز، بیشتر از میزان کاهش مجموع ورودی‌های به‌دست‌آمده از مدل‌های کلاسیک بود. محدودیت‌های اضافه‌شده به مدل مربوط به منابع نیز تحقق یافت. مطابق این نتایج، مجموع مصارف ورودی بخش‌ها کاهش یافته است؛ در حالی که مجموع تولیدات خروجی کاهش نیافته است.

Efficiency Analysis and Hospital Resource Allocation Using Centralized Data Envelopment Analysis

Purpose: This paper aims to illustrate the use of centralized data envelopment analysis with the variable return to scale in resource allocation at different wards of hospitals based on efficiency.   Design/methodology/approach: Data were collected from the statistics unit, accounting unit and the hospital infection unit for 31 clinical wards in Alzahra hospital, Isfahan, Iran, in the last quarter of 2011. The input sets represented by the number of beds, number of physicians, number of nurses and the physical space allocated to the ward, are used in the analysis. Three output sets consisted of the number of inpatients, beds turnover, beds occupancy ratio, and the number of consultants provided by the ward to represent the performance and activity of the ward. The radial centralized DEA based on the inputoriented and variable return to scale model was applied using MatLab software, to find out how to reallocate the hospital resources to the wards.   Findings: The values of inputs and outputs obtained from the centralized DEA model helps the centralized decisionmaker to take the right remedial actions for continuous improvement. The findings indicated that in this study the total number of active beds is proposed to be decreased from 739 to 343.99, the total number of physicians from 399 to 391.51, the total number of nurses from 1258 to 1239.21, and the total allocation of space to the wards from 19010 to 15668.69 square meters.   Research limitations/implications: The proposed approach is rather simple and it can easily be extended in different directions, allowing, for example, the consideration of joint constraints, goals, bounds on the changes of inputs and outputs, or on the allocated resources, but then one must be aware that such constraints are specifically defined for the case study and may be different in other hospitals. In this study, two constraints were considered to control the number of allocated nurses to two wards: ED and ICU, based on the current standards. Also, the proposed model was based on the criteria for which the data was available. It is clear that a centralized resource allocation approach implies a subordination of the behaviour of individual units to the goals of the system as a whole.   Practical implications: The results of the proposed centralized DEA model based on the performance criteria provide useful managerial implications for the resource allocation of hospital wards. The study proves the usefulness of centralized DEA as a decisionmaking tool in the health sector. Also, instead of reducing the inputs of any ward, the total input consumption of the wards is reduced, and as it is guaranteed, the total output production does not decrease.   Social implications: Public health and way to provide health care is an important issue in all countries, and health care providers trying within an existing resource, to provide the highest quality care. Allocating the resources in hospital wards based on the proper criteria increases the quality of the care and the efficiency of the healthcare sector.   Originality/ value: Many prior DEA studies have focused on health care efficiency. This paper is probably one of the first attempts that use a centralized model to analysis different hospital wards efficiency. Since resource allocation mechanisms can be influenced by the behaviour of the organization, the optimal allocation of a resource based on the needs is an important task of the health system. Furthermore, selecting the most appropriate set of input and output criteria is an important step in any efficiency measurement study.