Bed Management System Can Increase Hospital Revenues: Experiences of a Referral Cardiovascular Center

Document Type : Original Article

Authors

1 Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, IR Iran

2 Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, IR Iran.

Abstract

Background: Cardiovascular diseases are the leading cause of death worldwide; therefore, the importance of cardiac care hospitals is on the rise day by day. The efficient use, optimal
allocation, and maximum utilization of resources are the inseparable components of
modern management. Given the scarcity of resources, especially beds, and the complexity
of the existing processes in the hospital revenue system, the establishment of systematic
bed management is the right solution to this problem. The present study aimed to
determine the relationship between increased revenues and bed management.
Methods: This cross-sectional study was conducted in Rajaie Cardiovascular Medical and Research Center, Tehran, Iran. Data of 613 adult patients that had undergone coronary bypass grafting and heart valve surgery were collected from the hospital medical records. Diagnosis-Related Group (DRG)-2015 was used for the standard hospital length of stay (LOS), and hospital indices were recalculated and compared with their observed values. Data were analyzed using the Spearman correlation coefficient, the Mann–Whitney test, the Wilcoxon test, and the Kruskal–Wallis test. A P value of less than 0.05 was considered significant.
Results: Significant differences existed between the mean LOS and its standard values. The results showed that by the implementation of bed-management, the current LOS was halved, the bed turnover increased from 10.57 to 21.14 times, and the revenue increased by 33%.
Conclusions: A potential increase in revenues was observed after considering the standards of the bed management system in our hospital. According to the results obtained, revenues can be increased with higher patient admission and shortening patient queues by
establishing systems that define a standard to control LOS, without increasing the number
of beds. (Iranian Heart Journal 2021; 22(2): 6-16)

Keywords

References

  1. Suleiman Awwad M, Mohammad Agti DA. The impact of internal marketing on commercial banks' market orientation. International Journal of Bank Marketing. 2011; 29(4):308-32.
  2. Zare M, Ali S, Asefzade S, Alijanzadeh M, Sanei F. Assessment  of specific income and  cost  of 22 Aban hospital of Lahijan, Iran, in 2012. International Journal of Current Life Sciences. 2014; 4(11):9524-9528. Available at: http://www.bretj.com (accessed 3 January 2016).
  3. Nabilo B. Superior organizational pattern in health sector, Tadbir magazine. 2007; 145:102‐ 105.
  4. Karimi I. Health economy”, Tehran Gap Publishing, Iran. 2004.
  5. Oliveira S, Portela F, Santos MF, Machado J, Abelha A. Hospital bed management support using regression data mining models. IWBBIO. 2014; 1651-1660.
  6. Ghaffari S, Jackson TJ, Doran CM, Wilson A, Aisbett C. Describing Iranian hospital activity using Australian refined DRGs: A case study of the Iranian social security organization. Health Policy. 2008; 87(1):63-71.
  7. Hariri M, Sajadi H, Sadat. Improve the productivity of hospital. 2016. available at: www.hospitalmanagment.ir, (accessed 10 July 2016).
  8. Biørn E, Hagen TP, Iversen T, Magnussen J. How different are hospitals’ responses to a financial reform? The impact on efficiency of activity-based financing. Health care management science. 2010; 13(1):1-16.
  9. Ataollahi F, Bahrami M, Abesi M, Mobasheri F, Khani S. A Goal programing Model for reallocation of inpatient beds in Educational Shahid MohamadiI Educational Hospital of Bandar Abbas, IRAN. Health care management. 2014; 5(1):59-68.
  10.  Schmidt R, Geisler S, Spreckelsen C. Decision support for hospital bed management using adaptable individual length of stay estimations and shared resources. BMC medical informatics and decision making. 2013; 13(1):3. Available at: http://www.biomedcentral.com/1472-6947/13/3, (accessed 20 February 2016).
  11. D’Alessandro D, Coppola M, Chiarello P. Energy consumption in Hospital: preliminary results of the ICEOs Project. Proceedings of Clima 2007 Wellbeing Indoors. 2007. Available at: http//www.inive.org/members_area/medical, (Accessed 14 Mar 2016).
  12. Hatam N, Pourmohammadi K, Bastani P. Javanbakht M. The survey of hospital size effect on technical efficiency in social security hospitals. Journal of Razi Medical Sciences. 2012; 20(108):56-64.
  13. Kebriaei A, Kazemi M, Khosravi E, Comparative Assessment of Discharge Process in Ali-ebne Abitaleb and Quaem Hospitals. Journal of Health Informatics management. 2009; 7(1): 24-33.
  14. Amiri M. The effect of autonomy plan in the performance of public hospitals and the University of Medical Sciences Iran’s Health Services.  Medical Record Master Degree, Faculty of Management and Information Research of Iran. 1997.
  15. Khurma N.  Analysis, Modeling and Improvement of Patient Discharge Process in a Regional Hospital. Electronic Theses and Dissertations. 2009. 155. Available at: http://scholar.uwindsor.ca/etd/155,  (Accessed 10 Mar 2016).
  16. Proudlove N, Gordon K, Boaden R. Can good bed management solve the overcrowding in accident and emergency departments? Emergency Medicine Journal. 2003; 20(2):149-55.
  17. Patrick Ch. Revenues cycle phases and process. BHM, Health care solutions. 2013. Available at: http://bhmpc.com/2013/12/healthcare-revenue-cycle/, (Accessed 11 January 2016).
  18. Mathauer I, Wittenbecher F. Hospital payment systems based on diagnosis-related groups: experiences in low-and middle-income countries. Bulletin of the World Health Organization. 2013; 91(10):746-56A.
  19. Riahi L, Hajinabi K, Aghamohammadi F. The Relation of Hospital Bed Indicators with Electricity Consumption rate in Hamedan University of Medical Science Hospitals. Healthcare Management. 2010; 2(11): 59-66.
  20. Kroneman M, Siegers JJ. The effect of hospital bed reduction on the use of beds: a comparative study of 10 European countries. Social science & medicine. 2004; 59(8):1731-40.
  21. Bystrov V, Staszewska-Bystrova A, Rutkowski D, Hermanowski T. Effects of DRG-based hospital payment in Poland on treatment of patients with stroke. Health Policy. 2015; 119(8):1119-25.
  22. Rahimi B, Yusefzade H, Khalesi N, Valinejadi A, Gozali A, Akbari S, et al.
  23. Analysis of the efficiency and optimal consumption of resources in selected hospitals in Urmia province through data envelopment analysis. Journal of Health Administration. 2012; 15(47):91-102.
  24. Kokangul A. A combination of deterministic and stochastic approaches to optimize bed capacity in a hospital unit. Computer methods and programs in biomedicine. 2008; 90(1):56-65.
Iranian Heart Journal
Volume 22, Issue 2
April 2021
Pages 6-16

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