Combining multiple indicators to assess hospital performance in Iran using the Pabon Lasso Model

Abstract

One of the most important and useful models for assessing hospital performance is the Pabon Lasso Model, a graphical model that determines the relative performance of hospitals using three indicators: 1. Bed Occupancy Rate (BOR); 2. Bed Turnover (BTO); 3) Average Length of Stay (ALS). The aim of this research is to investigate the performance of the hospitals affiliated with Urmia University of Medical Sciences in Iran during the year 2009 based on the Pabon Lasso Model.
This cross-sectional descriptive study was undertaken in 2009. All the 23 hospitals affiliated with Urmia University of Medical Sciences were included. To ensure accuracy and reliability of data, the required data on BOR, BTO, and the ALS were accumulated by referring to the Statistical Year Book of the Urmia University of Medical Sciences. Data analysis was performed using the Pabon Lasso Model and SPSS 16 statistical software.
Across all hospitals, the following average results for each performance indicator were obtained: ALS = 2.84 days, BOR = 63.55% and BTO = 85.44 times per year. Six hospitals were located in the Pabon Lasso Model zone 1, two hospitals in zone 2, eight hospitals in zone 3, and seven hospitals in zone 4 of the model.
The study showed that 60.87% of the studied hospitals had low performance in terms of either BOR or BTO, or both. Thus, the analysis on why that low performance may have occurred, and suggestions to enhance future performance, is provided.

Full text

Australasian Medical Journal AMJ 2011, 4, 4, 175-179
175
Combining multiple indicators to assess hospital performance in Iran using the Pabon
Lasso Model
Mohammadkarim Bahadori
1
*, Jamil Sadeghifar
2
, Pejman Hamouzadeh
2
, Seyyed Mostafa Hakimzadeh
1,2
,
Mostafa Nejati
3
1 Health Management Research Centre, Baqyattallah University of Medical Sciences, Tehran, Iran
2 Department of Health Management and Economics, School of Public Health, Tehran University of Medical
Sciences, Tehran, Iran
3 School of Management, Universiti Sains Malaysia (USM), Malaysia
RESEARCH
Please cite this paper as: Bahadori M, Sadeghifar J,
Hamoudzadeh P, Hakimzadeh M, Nejati M. Combining
Multiple Indicators to Assess Hospital Performance in Iran
using the Pabon Lasso Model. AMJ 2011, 4, 4, 175-179
http//dx.doi.org/10.4066/AMJ.2011.620
Abstract
Background
One of the most important and useful models for assessing
hospital performance is the Pabon Lasso Model, a graphical
model that determines the relative performance of
hospitals using three indicators: 1. Bed Occupancy Rate
(BOR); 2. Bed Turnover (BTO); 3) Average Length of Stay
(ALS). The aim of this research is to investigate the
performance of the hospitals affiliated with Urmia
University of Medical Sciences in Iran during the year 2009
based on the Pabon Lasso Model.
Method
This cross-sectional descriptive study was undertaken in
2009. All the 23 hospitals affiliated with Urmia University of
Medical Sciences were included. To ensure accuracy and
reliability of data, the required data on BOR, BTO, and the
ALS were accumulated by referring to the Statistical Year
Book of the Urmia University of Medical Sciences. Data
analysis was performed using the Pabon Lasso Model and
SPSS 16 statistical software.
Results
Across all hospitals, the following average results for each
performance indicator were obtained: ALS = 2.84 days, BOR
= 63.55% and BTO = 85.44 times per year. Six hospitals were
located in the Pabon Lasso Model zone 1, two hospitals in
zone 2, eight hospitals in zone 3, and seven hospitals in zone
4 of the model.
Conclusion
The study showed that 60.87% of the studied hospitals had
low performance in terms of either BOR or BTO, or both.
Thus, the analysis on why that low performance may have
occurred, and suggestions to enhance future performance,
is provided.
Key Words
Performance assessment, key performance indicators,
hospital, Pabon Lasso Model, Iran
Background
Despite conspicuous and undeniable scientific and
technological progress, healthcare systems worldwide still
face numerous challenges
1
. Factors such as inefficiencies
and failure to meet patients’ expectations continually
threaten healthcare systems
2
. Hospitals play a key role in
providing healthcare services and can positively impact the
efficiency of these systems
3–4
. Hospitals in developed and
developing countries account for 40% and 80% of the
healthcare sector costs respectively. Thus, the impact of
evaluating performance of hospitals and changing systems
as a result could be particularly significant
5
.
Corresponding Author:
Mohammadkarim Bahadori.
Health Management Research Centre,
Baqyatallah University of Medical Sciences,
Tehran, Iran
Tell: +98.2182482416
Fax: +98.2188057022
E-mail: bahadorihealth@gmail.com

Australasian Medical Journal AMJ 2011, 4, 4, 175-179
176
Performance evaluation is an effective technique used by
hospital management to assess and supervise hospital
activities; nevertheless, it has been relatively neglected in
previous research of healthcare productivity
6
.
Numerous methods have been presented for use in
evaluating the performance of hospitals and how to analyse
the results obtained from such evaluations
7
. An important
and useful model for the evaluation of hospital performance
is the Pabon Lasso Model. This graphical model was
introduced in 1986 by Pabon Lasso for use in determining
the relative performance of the hospitals. It uses three
indicators to evaluate the overall performance of a hospital,
namely: BOR, BTO and ALS
8
. Interpretation of performance
using this model is based on a chart which is divided into
four parts by two crossing lines: the longitudinal axis (x)
shows the mean for BOR and the transverse axis (y) shows
the BTO. Each hospital assigns itself special features by
being positioned in one of the four parts (zones) of the chart
(see Table 1). By identifying and analysing to which zone a
hospital belongs, the management team can make a more
logical and relevant assessment of how to best improve the
performance
9
.
Table 1: Description and interpretation of each of the
zones of the Pabon Lasso Model
10-12
Zone Definition Interpretation
1 Low BTOs and
low BORs
The number of beds is high
relative to the current
demand, the hospital
demonstrates poor
performance
2 Low BOR but high
BTO rate
(common among
obstetric and
gynaecology
hospitals)
Indicates multiple patients
requiring short-term
hospitalisation. There is
potential for unnecessary
hospitalisation and surplus bed
capacity among these
hospitals
3 High BOR and
high BTOs
These hospitals have reached
an appropriate efficiency with
the minimum number of beds
used
4 High BORs and
low BTOs
(common among
psychiatric and
elderly medicine)
Indicates long-term
hospitalisation of the patients,
perhaps under-using other
outpatient facilities and
incurring high costs
Although not all the features associated with each zone of
the Pabon Lasso Model may be applicable to every hospital,
this kind of analysis is useful for quick identification of the
hospitals with weak performance and highlighting areas to
direct rectification of their inefficiencies. However, a
limitation of the Pabon Lasso Model is that performance
indicators may be affected by a number of factors that
cannot be measured using this simplistic instrument, such
as access to communication facilities, lack of availability of
home- or community-care, geographic location, teaching
hospital status, the number of employees and hospital
policies
11–12
.
This study will evaluate the performance of the hospitals
affiliated with the Urmia University of Medical Sciences
using the Pabon Lasso Model. The subsequent aim was to
inform policy makers during the compilation of plans for
increasing the productivity of the hospitals by determining
strategies for effective utilisation of the existing resources.
Method
This cross-sectional descriptive study was undertaken in
2009 in the West Azerbayjan province. This province is
located in North-West Iran and has 17 townships, with
Urmia Township at its centre. All 23 hospitals affiliated with
the Urmia University of Medical Sciences were included in
this research.
To ensure accurate and reliable data collection, the general
data (including the number of active beds, number of active
bed-days, number of occupied bed-days and number of
discharges) and performance data (including BOR, BTO, and
ALS) were accumulated from the statistical almanac of the
Urmia University of Medical Sciences, issued quarterly by
the statistics and information centre. Using descriptive
statistics, the annual status of the mentioned indicators was
determined. The data was then analysed using the Pabon
Lasso Model and SPSS 16 Statistical Software.
Results
All the hospitals were public except for one, which was a
specialist psychiatry hospital and belonged to a
governmental sector. Four hospitals were teaching
hospitals. The overall number of the active beds, active bed-
days, occupied bed-days and the number of discharges were
2,659, 970,535, 722,901 and 220,690 respectively. Based on
the results, in all of the studied hospitals (except for the
psychiatric hospital), the following average values were
recorded: ALS: 2.84 days, BOR: 63.55%, BTO: 85.44
times/year. The reason for excluding data from the above
mentioned psychiatric hospital was because of the
particularly lengthy admissions in that hospital which could
significantly skew the results. Six hospitals (no. 8, 11, 12, 14,
20, 23) were located in zone one of the model, indicating
inefficiency in the use of the resources available to them, as
they tended to have low BTOs and BORs. There were eight
hospitals in zone three, which represents high levels of
efficiency. Finally two hospitals (no. 17, 22) and seven

Australasian Medical Journal AMJ 2011, 4, 4, 175-179
177
hospitals (no. 1, 2, 3, 4, 7, 9, 21) belonged to zones 2 and 4
respectively (see Table 2 & Chart 1).
Discussion
Many indicators exist in the literature for measuring
hospital performance. It is important to apply those
measures to monitor the performance of a hospital, as it
will result in a number of benefits, such as indicating
important organisational goals for the policy makers,
directing planning of future services, and management of
available resources.
Using a single performance indicator may result in incorrect
and/or misleading conclusions about the overall
performance of a hospital. For instance, high BOR can result
from either high ALS due to the efficient use of hospital
resources for needy patients, or the existence of
unnecessary hospitalisations resulting in inefficient use of
resources. Nonetheless, only few studies have investigated
the use of multiple indicators to evaluate the hospital
sector. This study has applied the Pabon Lasso Model which
provided us with a quick evaluation about the overall
performance of the hospital by charting three indicators
(BOR, BTO, ALS). Besides, by using graphical charts, the
relationship between multiple performance indicators were
identified better and could facilitated the analysis process.
Obviously many differences exist in the performance of the
multiple studied hospitals; however a better understanding
about such differences must be based on objective
evidences. Overall, the average values for each of the three
performance indicators of the studied hospitals were BOR
63.55%, ALS 2.84 days, and BTO 85.44/year.
As highlighted earlier, in our study we found that six
hospitals (26.10%) lay in zone 1, two hospitals (4.34%) in
zone 2, eight hospitals (39.13%) in zone 3 and seven
hospitals (30.43%) in zone 4 of the Pabon Lasso Model.
These results are in line with previous studies that showed a
relatively low performance of hospitals in Iran. For instance,
in 2000, Shahrestani undertook a study to evaluate the
performance of the country hospitals and found out that 14
provinces lay in zone 1, 10 provinces in zone 2, and only one
province lay in zone 3 of the Pabon Lasso Model. In the
same study, the average of the BOR, BTO and ALS indicators
for the West Azerbayjan province were recorded as 43.05%,
28 times/year, 6.87 days respectively. These statistics place
the province generally in zone 1 of the Pabon Lasso Model,
indicating a low overall performance for the province
11
. A
close comparison between the present study’s results with
Shahrestani’s study indicates that improvement of the
performance indicators under study has occurred over the
nine-year time span between the two studies. This
improvement may due to a change in age distribution and
prevalent diseases and, perhaps due to different data
collection and analysis methods.
In Goshtasbi’s study of performance evaluation of the
hospitals existing in the Kohgilouyeh-Bouyer-Ahmad
province based on the Pabon Lasso Model, from a total of
six hospitals under investigation, two hospitals lay in zone 3,
three lay in zone 1 and one hospital lay in zone 4
10
. In
another study, Sajjadi evaluated the performance of the
hospitals affiliated with the Isfahan University of Medical
Sciences based on the Pabon Lasso Model and showed that
from a total of 31 hospitals under study, two cases lay in
zone 1, 14 cases lay in zone 2, 13 hospitals lay in zone three,
and 2 cases located in zone 4 of the Pabon Lasso Model
chart
13
.
Considering the results, the suitable strategy for the
hospitals located in zone 1 of the Pabon Lasso Model is to
focus on their weak points so that they can improve upon
these. Therefore, they need to identify and rectify the
factors that caused low BTOs and low BORs, and eventually
pushed the hospital to fall under zone 1. Regarding the
hospitals located in the zone 4, the suitable strategy will be
directing the tendency towards providing the bedridden
patients with diagnostic-therapeutic services partly as
outpatients, thereby overcoming the shortcomings and
improving the BTO.
As for the hospitals located in zone 2, with a low BOR, there
seems to be unnecessary hospitalisation and surplus bed
capacity. Hence, it is suggested that suitable measures are
taken for rationalising the hospitalisation in a more efficient
manner. Finally, for the hospitals under zone 3 of the
model, they should follow their strategy to ensure having a
consistently efficient service provision with an optimised
number of beds used.
Conclusion
The current study has looked into 23 hospitals in Iran and
evaluated their performance through the Pabon Lasso
Model. The results showed that while some of the studied
hospitals (39.13%) had significantly good performance
indicators (both high BOR and high BTO), the rest of the
hospitals had a poor performance in one or more of the
performance indicators. The authors have discussed the
results and proposed some suggestions on how to improve
the performance of these hospitals.

Australasian Medical Journal AMJ 2011, 4, 4, 175-179
178
Based on the indicators from the Pabon Lasso Model, the
areas of improvement for each hospital could be identified.
These weak areas would then need to be enhanced, by
modifying the current policies and strategies, as well as
applying necessary changes, in order to lead the hospital
towards performing at its maximum performance capacity.
Future research should try to explore the factors that have
caused the low efficiency of these hospitals and propose
more practical way to overcome them.
References
1. Groene O, Garcia-Barbero M. Health promotion in
hospitals: evidence and quality management: Citeseer;
2005; 1-120.
2. Jakab M, Harding A, Preker A, Hawkins L. Organizational
reform and management of public providers: focus on
hospitals: common performance problems in public
hospitals and their causes: Washington D.C. World Bank;
2000.
3. Barnum H, Kutzin J. Public Hospitals in Developing
Countries: Resource Use, Cost, Financing. Baltimore,
Maryland; John Hopkins University Press: 1993; 1-335.
4. Ersoy K, Kavuncubasi S, Ozcan YA, Harris JM. Technical
efficiencies of Turkish hospitals: DEA approach. J Med Sys.
1997;21(2):67-74.
5. Aversion A. Comparative study of evaluation and
supervision mechanism of services delivery in public and
private hospitals of Tehran. Tehran: Islamic Azad University,
Science and Research Branch; 2002.
6. Farzianpour M, Rangraz Jeddi F, Mousavi G. How often do
the managers use the statistics for hospital management?
Feyz Journal. 2003;27:92-98.
7. Mehrotra A, Lee S, Dudley R. Hospital performance
evaluation: what date do we want, how do we get it, and
how should we use it?. Washington D.C; National Business
Coalitions on Health: 2006.
8. Lasso P. Evaluating hospital performance through
simultaneous application of several indicators. Bulletin of
the Pan American Health Organization. 1986;20(4):341-57.
9. Asefzadeh S. Hospital Management & Research. Ghazvin:
Qazvin University of Medical Sciences; 2007.
10. Goshtasebi A, Vahdaninia M, Gorgipour R, Samanpour A,
Maftoon F, Farzadi F, et al. Assessing Hospital Performance
by the Pabon Lasso Model. Iranian Journal of Public Health.
2009;38(2): 119-124.
11. Shahrestani T. Using three major indicators (bed
occupancy rate, Bed Turnover, and average length of stay)
to assess the performance of Iranian hospitals in a Pabon
Lasso model; [MSc Dissertation] Tehran: Iran University of
Medical Sciences; 2000.
12. Thomas S, Normand C, Smith S. Social health insurance:
further options for Ireland. Report prepared by TCD and
published by the Adelaide Hospital Society; 2008; 1-48.
13. Sajadi H, Hariri M, Sajadi Z. Assessment performance of
hospitals affiliated to the Isfahan University of Medical
Sciences according to Pabon Lasso model in 2007 Tehran:
Health Economics Research Centre; 2007.
PEER REVIEW
Not commissioned. Externally peer reviewed.
CONFLICTS OF INTEREST
The authors declare that they have no competing interests.

Australasian Medical Journal AMJ 2011, 4, 4, 175-179
179
Figures and Tables
Table 2: Frequency distribution of different indicators for the studied hospitals
BTO BOR ALS Discharges Occupied
bed-days
Active
bed-days
Active
beds
Hospital
No.
57.91 87.40 5.51 25938 142916 163520 448 1
83.93 70.90 3.08 19493 60038 84680 232 2
57.17 83.75 5.35 11428 61138 73000 200 3
12.91 75.32 21.29 1201 25567 33945 93 4
96.86 64.27 2.42 15898 38472 59860 164 5
119.42 79.99 2.44 25008 61020 76285 209 6
80.34 89.39 4.06 6027 24471 27375 75 7
36.83 37.49 3.71 1107 4105 10950 30 8
73.47 65.75 3.27 5137 16799 25550 70 9
146.87 77.72 1.93 7349 14184 18250 50 10
35.40 9.70 1.00 354 354 3650 10 11
28.71 17.14 2.18 660 1439 8395 23 12
86.48 72.21 3.05 20480 62465 86505 237 13
70.21 61.67 3.21 7503 24085 39055 107 14
91.32 81.73 3.27 11951 39079 47815 131 15
122.21 82.43 2.46 15288 37609 45625 125 16
91.91 60.78 2.41 6536 15751 25915 71 17
131.63 79.87 2.21 7387 16325 20440 56 18
123.12 84.04 2.49 15399 38343 45625 125 19
61.37 41.31 2.46 4168 10253 24820 68 20
84.81 65.24 2.81 7288 20479 31390 86 21
142.34 62.99 1.62 3832 6208 9855 27 22
57.31 22.41 1.43 1258 1800 8030 22 23
Chart 1: The status of the studied hospitals based on the Pabon Lasso Model