ISSN: 0443-511
e-ISSN: 2448-5667
Herramientas del artículo
Envíe este artículo por correo electrónico (Inicie sesión)
Enviar un correo electrónico al autor/a (Inicie sesión)
Tamaño de fuente

Open Journal Systems

Hospital efficiency measured by bed space use in a secondary care hospital

How to cite this article: Moreno-Martínez R, Martínez-Cruz RA. Hospital efficiency measured by bed space use in a secondary care hospital. Rev Med Inst Mex Seguro Soc. 2015;53(5):552-7.



Received: 05/02/2014

Accepted: 04/05/2015

Hospital efficiency measured by bed space use in a secondary care hospital

Roberto Moreno-Martínez,a Rocío Alejandra Martínez-Cruzb

aCoordinación de Información y Análisis Estratégico, Jefatura de Prestaciones Médicas, Delegación Estatal en Chiapas, Tapachula

bUnidad de Medicina Familiar No. 25, Delegación Estatal en Chiapas,  Tuxtla Gutiérrez

Instituto Mexicano del Seguro Social, Chiapas, México

Communication with: Roberto Moreno-Martínez

Telephone: 52 0196256158


Background: In recognition that the availability of resources in the medical facility forms part of the factors that influence the quality of healthcare, it is of vital importance to measure their outcome. The aim of this study was determine the efficiency of the medical facility through the use of beds in a secondary level hospital.

Methods: Through the Health Information Management System (HIMS), we examined statistical reports from July 2012 to June 2013 including variables such as expenses, patient days, occupancy rate, average length of stay by specialty and medical division, results were obtained for each strategic indicator, and these results were related assumptions proposing to assess hospital efficiency.

Results: Overall, we identified optimal efficiency of the medical facility without analysis of services, leads to deteriorating and low efficiency. The overall outcome of the five indicators applied overlooked saturation of services within the medical unit. However, the overall analysis shows the problem, noting the advantage of evaluating the same scenario from different perspectives.

Conclusions: The include indicators measuring hospital efficiency resource based bed, allows considering deficiencies identified, so that decision making is strengthened the decision making health.

Keywords: Management indicators, Efficiency, Resource allocation, Health services administration

Health systems in Latin America face challenges in equity, efficiency and access to care services. Learning how to deal with these challenges begins with a comprehensive analysis that considers all possible scenarios in the process of providing health services and is the basis for correct decision making in healthcare. In the report on global health in 2013, The World Health Organization (WHO) shows that research provides the scientific data needed to define the services and support policies required in a given environment; as well as to measure the progress made in achieving a goal by using valid and appropriate indicators.1 By performing data analysis with various indicators of a particular process in health, the issues of phenomena that occur in healthcare can be clearly identified through an approach that considers most or all possible scenarios.2,3 Medical care units at hospitals are spaces where different medical specialties interact, as well as other scientific disciplines in administrative areas, which together make up network of care processes, in addition to being the place where the population’s most complex health problems are met.

Knowing with what and how a hospital’s medical services cater to its users, considering the resources available, becomes a real challenge, given the different variables that affect patient care, but which together determine the hospital’s efficiency.2 Frenk and Murray define efficiency as "the degree to which the desired results are achieved with the available resources".4 The WHO identifies three causes of inefficiency in health services that directly involve hospital services: hospital admissions, inappropriate length of stay, and the underutilization of available resources.5 As the bed is the base hospital structure,6 the analysis of hospital indicators that measure the volume and use of the bed allows us to evaluate specific aspects of efficiency, providing valuable information on the services a hospital provides. In this evaluation of hospital efficiency, we will consider two strategic indicators outlined in the Instituto Mexicano del Seguro Social’s (IMSS) 2013 sourcebook: Average number of days per stay in second-level units (Days), percentage of hospital occupancy in second-level units (PO),7 and three indicators used by the Secretaria de Salud: Bed Rotation Index (BRI); Interval of Bed Replacement (IBR), and the index of hospital beds per 1000 patients (Table I). The aim of this study is to evaluate hospital efficiency in a secondary hospital using indicators that measure the use of the bed as a resource.

Table I efficiency indicators that measure the use of the hospital bed resource
Indicator Characteristics
second-level units
Formula:Patient days in SLU x 100
Range of ranking:Bed days in SLU
80-85% > 85 < 80 > 100
Measures the utilization of installed capacity, as well as the adequacy and availability of resources for a given demand.It translates the sufficiency of service based on the demands of the population
of days
stay in
second-level units
Formula:Patient days in SLU
Range of ranking:Hospital discharges in SLU
4.3 4.4-5.29 < 4.3
Determines the average time in days or fraction of days the bed lies unoccupied from one entry to another.It translates the degree of optimization of the census bed resource and efficiency in the resolution of the health problems of patients.
Interval of
of beds in
Formula: Bed days - patient days in a given period
Range of rankings:Total expenditures
1 > 1 < 1
Measures the average time that the unit uses to attend patients in the process of hospitalization (stay of a patient in a census bed, within a period of 24 h).Short stays and low-risk puerperium programs are excluded.Detects managerial problems associated with bed management, determines the efficiency in the use of the bed.

Hospital bed rotation
Formula:Total discharges in the SLU hospital
Range of rankings:Total beds in SLU
52 > 52 < 52
Determines the average number of patients who make use of a hospital bed. Assesses the potential capacity of the unit from its resources, it is an approach to its proper use for example, a low rate of rotation implies that the discharges are lower than potentially possible (underfilled).
per 1000 population
Formula: Total census beds in institutions x 100
Range of ranking: Total population for that period
1 > 1 < 1
Determine the number of census beds available in institutions of the public sector to serve the population per 1000 inhabitants. Rates the availability of beds to cater to a certain place and period, as well as the coverage of population based on this resource.
SLU: Second level units
Source: Own elaboration based on: 2013 medical indicators Methodological Manual.nstituto  Mexicano  del  Seguro  Social..Mexico, 2013 Dirección  General  de  Evaluación  del  Desempeño.  Secretaría  de Salud.Mexico, 2012


Considering the sources, the design of this study is ecologically exploratory, using the hospital bed as the unit of analysis. The statistical reports from the Hospital General con Medicina Familiar 1 Tapachula (HGZMF 1) dating from July 2012 to June 2013, obtained from the Medical Information Operating System (MOIS), were examined, including variables such as patients discharged, patient stay, occupancy rate, and average duration of stay by specialty and division; proceeding then to obtain the results of the indicators based on the mechanics of calculation, as noted in IMSS’s 2013 Methodology Manual of Medical Indicators and the Secretaria de Salud in Mexico’s 2011 Handbook of Indicators for Evaluation of Hospital Services. The indicators used were: average number of days spent in second-level units, hospital occupancy percentage in second-level units, Bed Rotation Index and Interval of Bed Replacement, and to assess the potential demand for medical care, the index of countable beds. To measure hospital efficiency, the variation that exists between these indicators was related and analyzed, considering the parameters and benchmarks for each indicator (Table II). Four levels of efficiency are proposed:

Table II Relation of hospital efficiency indicators
Indicators Percentage
Hospital occupation
Average number of days stay Interval of
replacement of bed
Bed Rotation
Variation of indicators Impaired
Source: Own elaboration based on: Vargas Fuentes, Mauricio.Gerencia de Servicios de Salud. Instituto Centroamericano de Salud Pública  (ICAP). Costa Rica.  1989;  Manual  Metodológico de Indicadores Médicos 2013.  Instituto  Mexicano del Seguro  Social. México 2013; Secretaría de Salud. Observation of Hospital Performace 2011. Dirección General de Evaluación del Desempeño. Secretaría de Salud. México, 2012

Level of impaired efficiency: when a bed remains unoccupied many days it shows poor productivity due to an excess or deficit of patients discharged and, as the average number of days spent and the occupancy percentage are sensitive to these changes, we find that services are underutilized or over-utilized.

Low level of efficiency: when a hospital bed has low productivity due to the lengthening of the average time between the admittance and discharge of patients, which indicates a low occupation and a rise in average hospital stay, affecting in turn the number of hospital discharges.

Average efficiency level: hospital discharges have increased, showing adequate productivity of the bed, however the IBR is negative reflecting the fact that there are more patients than beds, so that the occupation and the average hospital stay have also increased.

Optimum level of efficiency: the resource of the hospital bed is properly exploited, demonstrating adequate supply and demand for services.



Addressing hospital efficiency from the perspective of bed resources, without consideration for other dimensions such as structure, process and outcome,8-10 from the perspective of quality health services, this may be the study’s greatest limitation, however, in compliance with current policies in which decisions must be based on the strategic analysis, the study indicates important areas of opportunity for intervention. Another important limitation is the difficulty of making inferences from the results of this study to other hospital units, given the infrastructure available to each medical unit and the demand for medical care, in this case the use of the indicators proposed here would useful.


The HGZMF 1 Tapachula is composed of 25 medical services in four divisions, it has 133 beds and serves 141,870 users. The overall result of the five indicators indicate optimum efficiency, sufficient hospitalization service and adequate reserve capacity in beds 18.7% (Figure 1). The index is 0.94 beds per 1,000 users, with a surplus of 20 beds. These results contrast with the observable saturation of the services available to the medical unit. According to the assumptions made in this study in order to evaluate hospital efficiency, the Pediatrics and Internal Medicine divisions show an average level of efficiency, which highlights the lack of beds for patient care, and registers more discharges than expected. The Surgery division had level low efficiency, with underutilization of beds by 24%, resulting from a high productivity per bed which is then left unoccupied for periods of time. It appears that surgery patients are treated in the beds belonging to other services that have less demand, which prevents the operating collapse of these divisions; the high number of days of hospitalization in these services requires the review of protocols of care for these patients. The Gynecology division has a deteriorated level of efficiency; an average hospital stay of 2.2 days is registered, and more than its capacity of patients installed in beds. An analysis of services reveals impaired efficiency in eleven services, of these six (Hematology, Nephrology, Neonatology, Neurosurgery, Neurology, Pediatrics and Internal Medicine) present overcrowding, an insufficient number of beds, and fewer beds per day available than patients per day (Table III).

Indicators according to services
Beds Discharges Patient days %
Days1 IRB2 BRI3
Gynecology Division
25 3080 6761 74.1 2.2 0.8 123
46 2608 12888 76.8 4.9 1.5 56.7
Internal Medicine Division
44 2473 13947 86.8 5.6 0.9 56.2
Pediatrics Division
18 1121 5869 89.3 5.2 0.6 62.3
Total HGZ MF1
133 9144 39465 81.3 4.3 1 68.8

Figure 1 Behavior of indicators measuring the resource of the hospital bed by division. General Hospital con Medicina Familiar 1 Tapachula, Chiapas

Table III Level of hospital efficiency by medical service, Hospital General con Medicina Familiar 1 Tapachula, Delegación Chiapas
Division Services Indicators Result
Beds Discharges Patient days %
of Days
IBR2 BRI3 Level
of efficiency
Internal medicine Dermatology 1 2 12 3.3 6.0 176.5 2.0 Low
Clinical Psychiatry 1 2 11 3.0 5.5 177.0 2.0 Low
Cardiology 2 140 595 81.5 4.3 1.0 70.0 Optimal
Gastroenterology 6 366 1953 89.2 5.3 0.6 61.0 Medium
Hematology 1 84 679 186.0 8.1 -3.7 84.0 Impaired
Internal medicine 21 1051 6231 81.3 5.9 1.4 50.0 Medium
Nephrology 4 694 3635 249.0 5.2 -3.1 173.5 Impaired
Neurology 2 123 790 108.2 6.4 -0.5 61.5 Impaired
Rheumatology 1 7 30 8.2 4.3 47.9 7.0 Low
and nutrition
1 4 11 3.0 2.8 88.5 4.0 Impaired
Total 44 2473 13947 86.8 5.6 0.9 56.2 Medium
Surgery Maxillofacial surgery 1 41 206 56.4 5.0 3.9 41.0 Low
Reconstructive Plastic surgery 2 33 164 22.5 5.0 17.2 16.5 Low
Surgical Oncology 4 191 1036 71.0 5.4 2.2 47.8 Low
Urology 5 315 1435 78.6 4.6 1.2 63.0 Low
Neurosurgery 1 110 757 207.4 6.9 -0.5 110.0 Impaired
General Surgery 15 1107 4211 76.9 3.8 1.1 73.8 Impaired
Ophthalmology 2 13 35 4.8 2.7 53.5 6.5 Impaired
and orthopedics
14 739 4851 94.9 6.6 0.4 52.8 Medium
Otolaryngology 2 59 193 26.4 3.3 9.1 29.5 Impaired
Total 46 2608 12888 76.8 4.9 1.5 56.7 Low
Gynecology Total 25 3080 6761 74.1 2.2 0.8 123.0 Impaired
Pediatrics Neonatology 7 439 2920 114.3 6.7 -0.8 62.7 Impaired
Pediatrics medical 7 611 2649 103.7 4.3 -0.2 87.3 Impaired
Pediatric Surgery 2 71 300 41.1 4.2 6.1 35.5 Impaired
Total 18 1121 5869 89.3 5.2 0.6 62.3 Medium
Total HGZMF1 133 9144 39465 81.3 4.3 1.0 68.8 Optimal
1Days stay, 2Interval of replacement beds, 3Bed rotation index
Source: MOIS delegation Chiapas, IMSS July 2012 - June 2013

The reasons for healthcare services were also reviewed, and an important phenomenon was identified that might be aggravating the unavailability of beds in services; in the first half of 2013, the reasons for healthcare services in hematology were compatible with hospital management by isolation techniques. The medical unit lacks specific rooms for isolation, and when these cases arise the patient is accommodated in a ward, leaving the rest of the beds located in the room inaccessible. This situation is also observed with patients with infectious diseases.


Efficiency can be measured in existing levels of idle capacity or when the structure of resources reflects excesses or shortfalls in certain areas. The analysis of the indicators used contrasts sharply with what was observed by division and service. The HGZMF 1 Tapachula actively participates within the framework of the agreements of exchange of services in the health sector, laying the foundations for an integrated health system in which the population has universal access to quality services,1,11 due to which it is guaranteed to have an infrastructure based on its needs. One of the causes of inefficiency in hospital services referred to in the literature is the inappropriate size of some facilities,12 which Carreño confirms, noting that the number of installed beds in an institution positively determines the results of the indications.13 In our study we observed some services with high demand and exceeded capacity, and some services with low demand for care and underutilized capacity, which will likely prevent the collapse of services with higher demand by offering its underutilized installations. Services with indicators that point to the unexpected extended stay of patients were identified, a condition that is also reflected in the IBR indicating slowness in the reoccupation of a bed after a patient is discharged. This situation is probably due to the complexity of the conditions that are addressed in health services, derived from the current burden of disease on the population,14 however, it opens a window of opportunity for a review of the protocols of healthcare under which patients are cared for, among other conditions. The bed index, which only considers potential users within a service area, reveals that the medical unit has a surplus of 20 beds, which contrasts with the observed saturation of services and suggests that patients from other areas of service may be in this unit. The underutilization observed in some services allows for the opening of lines of operational research to determine if there is demand for these services or, if not, provides the opportunity to use their beds. In recent years, strategies to reduce hospital costs have been based on the reduction of hospital beds, decreased stays, and reducing the number of admissions,15-19 therefore alternative proposals to this problem are: physical reorganization of services and adjusting the indicator by type of patients seen in the services through a patient classification system, such as groups with related diagnosis.20 The new management tools should be aimed at trying to predict occupancy levels of beds in order to make more efficient use of them while excess capacity is removed.21-24


The efficiency of HGZMF 1 based on bed resources is seriously compromised, immediate intervention is necessary for the hospital to be able to meet its user population’s demand for medical care. The provision of more beds in service, redefining the area of ​​services, and a revision of health care protocols are some useful strategies to strengthen the medical unit.

  1. World Health Organization. Informe sobre la salud en el mundo: Investigaciones para una cobertura sanitaria universal. World Health Organization. 2013.
  2. Jiménez Paneque Rosa E. Indicadores de calidad y eficiencia de los servicios hospitalarios: Una mirada actual. Rev Cubana Salud Pública. 2004 [citado 2015 Mar 09]; 30(1): Available from: &pid=S0864- 34662004000100004&lng=es.
  3. Chirinos E., Rivero E., Goyo A, Méndez E., Figueredo. Indicadores de Gestión para medir la Eficiencia Hospitalaria. Negotium: revista de ciencias gerenciales 2008;4(10):50-63.
  4. Murray CJL, Frenk J. A WHO framework for health system performance assessment. World Health Organization 2000.
  5. World Health Organization. Informe sobre la salud en el mundo: La financiación de los sistemas de salud; el camino hacia la cobertura universal. World Health Organization 2010.
  6. Secretaría de Salud. Observatorio del Desempeño Hospitalario 2011. Dirección General de Evaluación del Desempeño. Secretaría de Salud. México, 2012.
  7. Dirección de Prestaciones Médicas. Manual Metodológico de Indicadores Médicos 2013. Instituto Mexicano del Seguro Social. México 2013.
  8. Donabedian A. Approaches to assessment: What to assess in evaluating the quality of medical care? Milbank Mem Fund Quart. 1986;44:167-70.
  9. Ministerio de Salud Pública de Cuba. Indicadores Básicos para el Análisis del Estado de Salud de la Población. Dirección Nacional de Registros Médicos y Estadísticas de Salud. República de Cuba 2010.
  10. Vargas-Fuentes Mauricio Gerencia de Servicios de Salud. Instituto Centroamericano de Salud Pública (ICAP). Costa Rica 1989.
  11. Secretaría de Salud. Manual de Lineamientos para el Intercambio de Servicios en el Sector Salud. México 2011.
  12. Posnett J. Are bigger hospitals better? In: Mckee M, Healy J, eds. Hospitals in a changing Europe. Buckingham, Open University Press, 2002.
  13. Carreño A. Medición de la calidad, la eficiencia y la productividad en hospitales públicos de tercer nivel de atención en Bogotá. Revista Universidad & Empresa. 2008;17:203-222.
  14. Kuri-Morales P, Chávez-Cortés C. La transformación de sistema y los espacios de la salud pública. Gaceta Médica de México 2012; 148:509-517.
  15. Olukoga A. Unit costs of inpatient days in district hospitals in South Africa. Singapore Med J 2007; 48 (2):143-7.
  16. Kuntz L, Scholtes S, Vera A. Incorporating efficiency in hospital-capacity planning in Germany. Eur J Health Econ. 2007;8(3):213-223.
  17. Shah BR, Reed SD, Francis J, Ridley DB, Schulman KA. The cost of inefficiency in US hospitals, 1985-1997. J Health Care Finance 2003;30(1):1-9.
  18. Green LV. How many hospital beds? Inquiry 2002-2003;39(4):400-412.
  19. Kirby A, Kjesbo A. Tapping into hidden hospital bed capacity. Healthc Financ Manage 2003;57(11):38-41.
  20. Vargas-González. Indicadores de gestión hospitalaria. Revista de Ciencias Sociales 2007; 3 (XIII): 444-454.
  21. Utley M., Gallivan S, Treasure T, Valencia O. Analytical methods for calculating the capacity required to operate an effective booked admissions policy for elective inpatient services. Health care Manag Sci 2003;6(2):97-104.
  22. Mackay M, Lee M. Choice of models for the analysis and forecasting of hospital beds. Health Care Manag Sci 2005;8(3):221-30.
  23. Mackay M. Practical experience with bed occupancy management and planning systems: an Australian view. Health Care Manag Sci 2001;4(1):47-56.
  24. Jones SA, Joy MP, Pearson J. Forecasting demand of emergency care. Health care Manag Sci 2002; 5 (4):297-305.

Conflict of interest statement: The authors have completed and submitted the form translated into Spanish for the declaration of potential conflicts of interest of the International Committee of Medical Journal Editors, and none were reported in relation to this article.

Enlaces refback

  • No hay ningún enlace refback.