Performance Evaluation of Hormozgan University of Medical Sciences (HUMS) hospitals based on Pabon Lasso Model

Article History: Received: 14 Jul 2018 Revised: 16 Sep 2018 Accepted: 18 Dec 2018 Background: Hospitals need a system for evaluating and monitoring performance for promotion the efficiency and effectiveness of their services and outcomes. Pabon Lasso model is a graphical chart that can be used to identify the current status and performance level of hospitals by combining hospital indicators, simultaneously. Therefore, this study aimed to evaluate the performance of Hormozgan University of Medical Sciences (HUMS) hospitals during a six-year period using this model. Methods: This descriptive study includes all teaching and non-teaching hospitals affiliated with the HUMS. After gathering the required information related to three indices: Bed Occupancy Rate, Bed Turnover Rate and Average Length of Stay for the years 2009 to 2014 from the statistical systems and yearbooks, the situation of hospitals in terms of indices by drawing Pabon Lasso graphical charts using SPSS version 16, were analyzed. Results: The results showed that during a six-year period, on average, 26 percent of hospitals were placed in zone I, that is the inefficient area, 28 percent in zone II, 30 percent in zone III which is an efficient area of the model and 16% in zone IV of the Pabon Lasso model. Conclusion: The findings indicated that the utilization of hospitals beds is relatively desirable. Periodic monitoring of province centers and determining their status in the model, and also, performance assessment from another dimension is suggested in order to achieve more comprehensive and more accurate results.


Introduction
ospitals have a significant role in delivery of healthcare services therefore, its productivity and efficiency will have a significant impact on improving health system performance (1). Hospitals need a performance evaluating system for development and competition in order to measure efficiency and effectiveness of programs, processes and their human resources (2). The results of the evaluation indicate how activities and resource utilization are conducted in every hospital (3). Hospital performance can be assessed in different areas which shortly include: efficiency, productivity, quality and access (4). Efficiency and appropriate productivity are necessary both for countries` economy and for the survival of organizations and institutions such as health centers (5).
Providing desirable health services based on related indicators requires managers and planners' awareness of hospitals performances. Moreover, determining trends and patterns in administrative data can inform decision makers in health services management (6,7). In order for efficient management and monitoring patient care, the hospitals should creat an information management system which leads to generating types of indicators such as performance indicators that are helpful in measuring, determining progress and improving organization decision-making (8,9). These indices indicate vital and significant factors in the organizational success and concentrate on the critical aspects of organizational performance nowadays and also in the future reflecting efficiency and effectiveness of organizational units (10)(11)(12).
In hospitals, indicators such as the hospital bed occupancy rate, average patient stay, bed turnover rate, bed turnover interval, and mortality are among the most important and effective performance indicators that should be examined on a regular basis (13,14). Health experts also state that, a day bed expense, bed occupancy rates, average of patient stay, bed turnover and average of interval in bed occupancy are the main economic indices to measure the performance and the most common efficient indices of hospital which indicate the optimal use of resources to transform inputs into outputs (12)(13)(14)(15).
Researches show that there are different indicators for measuring hospitals Productivity in which the most significant and the most practical ones are: Bed Occupancy Rate (BOR), Bed Turnover Rate (BTR) and the Average Length of Stay (ALS) in the hospital. Accordingly, using an approach which can apply these indices simultaneously and in a mixed model provides the possibility to draw several conclusions in a single comparison and evaluate the hospital services in diverse situations (14)(15)(16). Lacking a descriptive model and using a single index could lead to inaccurate perception about the total performance of a hospital (17). In the same vein, one of the efficient techniques of performance comparison of health centers and evaluation of their efficiency is using graphical plots such as Pabon Lasso which can compare the above-mentioned indicators at the same time (18). This model can provide a quick assessment of the overall performance of hospitals by combining three indices of BOR, BTR, and ALS in the right way. This graphical model was for the first time introduced by Pabon Lasso in 1986 to determine the relative performance of hospitals (19). As shown in figure 1, the horizontal axis of this rectangular graph is BOR, and the vertical axis is BTR. The average point of the length of stay is determined by connecting each hospital coordinate point to the center coordinate and extension to the opposite sides. This graph divides the hospitals into four groups: 1-The first group is the hospitals with low bed turnover rate and low bed occupancy rate which indicate extra bed compared to demand.

2-
The second group is the hospitals with high bed turnover rate and low bed occupancy rate which indicate unnecessary beds, an oversupply of beds or use of beds for examining patients.
3-The third group involves high bed turnover rate and high bed occupancy rate which illustrate hospitals in which have reached a proper level of productivity and have relatively a few numbers of empty beds. 4-Finally, the fourth group, hospitals with high bed occupancy rate and low bed turnover rate which indicate hospitalized patients with chronic diseases or unnecessary long-term hospitalization.
Combining indices of bed turnover rate, bed occupancy rates and the average length of stay in hospital form the basis of each hospitals location in the model mentioned above (20)(21)(22). Accordingly, the present study examined the hospitals affiliated with Hormozgan University of Medical Sciences (HUMS) in a six-year period to monitor the trends of the centers and review their probabilistic change and the possibility of comparing them during the considered years simultaneously.

Materials and Methods
This descriptive study was conducted in 2016. The ethical considerations of this research were to obtain an authorization from the vice-chancellor for research and technology to get the required information from the statistics and information technology management and hospitals.
The data collection tool was a form that was designed according to the objectives of the study in order to collect the data needed to draw Pabon Lasso graph. The form included, three performance indicators, namely, bed occupancy rate, bed turnover and patient stay average, and also the number of active beds and hospitals wards for each of the 13 hospitals under study, during 12 months from 2009 to 2014 (from March 2008 to March 2014). The required information was collected from the Statistical Yearbooks and the Management Information System (MIS) of the Statistics and Information Technology department of HUMS. Then, the average of their annual performance was calculated and based on the mentioned indices; the Pabon Lasso graph was drawn for every six years separately using SPSS software (Version 16). Regarding the average of the indices, the studied hospitals were divided into four areas shown in Figure1. Then, each of these hospitals was located in one of the areas in the graph based on the bed turnover and bed occupancy rate. Finally, the data were evaluated according to the location of each hospital specified in the graph. This study was adapted from the proposal number 9273 approved by HUMS, Bandar Abbas, Iran.

Results
Four hospitals out of the 13 hospitals, which were located in Bandar Abbas city are educational, and the rest are non-educational hospitals.
The average of three indicators, including BOR, BTR and patient stay from 2009 to 2014 related to all studied hospitals is represented in Table 1 The hospital's code specified in the graphs is based on the numbers defined in the methods section. The percentage of hospitals located in each quarter is shown in

Discussion
According to the result, in HUMS hospitals during the six years, the ALOS was 2.7 days, BOR 75.8% and bed turnover index was 101 per year. Comparing indices of the hospitals of HUMS, with country standards for a total of the six years, the province condition was desirable.
In the present study, the percentage of the centers, which were located in zone 3 in According to the results of this study, in the total of six years, 26% of the hospitals have been found in the first area i.e. the inefficient area, 28% in the second area, 30% in the third area that is the efficient area of the model and the rest 16% in the fourth area of Pabon Lasso model. Some of the studies investigated the centers in a one-year period, and other studies examined the hospitals in more than a one-year period. For example, Lotfi et al. (23), investigated the range of efficient hospitals from 2007 to 2013 among 16 hospitals of Iran Universities of Medical Sciences. Their findings showed that among the examined centers in every seven years, the number of hospitals located in zone 1, 2 and 4 was more than the number of efficient hospitals in Zone 3. Also, Emamgholipour et al. (26), in a five-year period evaluated the trend of hospital performance in all 21 hospitals affiliated to Guilan University of Medical Sciences (GUMS) using Pabon Lasso model within 2010-2015. Based on the findings, the performance of GUMS hospitals has been on an increasing trend in recent years. The number of hospitals in zone 1 has decreased from 6 to 3, and the number of hospitals in zone 3 has increased from 5 to 6 from 2010 to 2015. Based on Pabon Lasso graph in this study and other studies conducted with the same goal, there are different statistics for the number of efficient hospitals.
Since several variables such as the type of specialization, type of ownership, being a public and private center as well as being an educational and non-educational hospital, hospital geographic location and other factors can have an impact on their performance, thus more attention should be paid comparing the centers and the results of the similar studies using the mentioned model. Considering and comparing the graphs of the study during the six-year period, the distribution of hospitals among the first, second and third area of the model were not significantly different. However, based on the results, the highest percentage of hospitals are located in the third area with a small percentage difference compared to other areas. Since this area represents the ideal and optimal performance of the centers, therefore, managerial strategies should be taken into account in order to maintain the current position.
The centers have been found in the first area, with lower bed occupancy and turnover were more than average, indicating the lack of optimal use of resources. Thus improving the efficiency of these centers is an essential part of managers and planners program in the deputy of treatment.
Hospitals that were located in the second and fourth areas, reflects the relative efficiency, therefore, there is a need for managerial follow-up and corrective actions to improve performance indicators.
Although during the study years, the hospital's performance indicators have been in a state of moderate to good compared to national standards, comprehensive evaluation of the centers is necessary in order to achieve maximum efficiency and productivity. In this regard, evaluating the center's performance from other aspects such as quality, the level of access to services, human resources, productivity and so on, along with the use of other statistical and mathematical techniques is recommended which can be beneficial to achieve more comprehensive and accurate results. As a challenge in this study, it is notable that the lack of confidence in some of the indicators led to the extraction of raw data and the recalculation of indicators in order to obtain more accurate information. Since the real and correct information can be a great help to hospital managers for decision making, therefore, direct and specialized monitoring of related centers on the performance of statistical units and, if necessary, training new staff is recommended.

Conclusion
Pabon Lasso model is a graphic chart which can be applied to identify hospitals efficiency rate in line with improving the productivity of existing facilities of health services.
In this study, it seems hospitals that have poor performance can help to reduce patient referral to other centers, which is the main reason of reducing bed occupancy by recruiting medical specialist and deploying advanced diagnostic and therapeutic equipment. Also, it seems essential to provide diagnostic-therapeutic services for hospitalized patients as an outpatient treatment as far as possible in the centers which have unnecessary hospitalizations.
It is suggested that periodic monitoring and comparing with standard by the graphical models be done in order to determine their distance with desirable conditions and provide solutions to eliminate causes of inefficiency.
As mentioned, one of the strengths of this study was the simultaneous review of all university hospitals over a six-year period and a fast review of the trend of changes in indicators during this period. Finally, large organizations like hospitals need to be complemented by efficient managerial systems, which it is almost impossible without the use of IT capabilities.
In order for an optimal use of the potential of ICT, design and utilization from structured and integrated dashboards as an effective tool to monitor operations of the hospital on existing information systems, based on important indicators and charts with the aim of quick and timely access to required information, are suggested.

Conflicts of interest
The authors declared no competing interests.