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 Table of Contents  
ORIGINAL ARTICLE
Year : 2021  |  Volume : 23  |  Issue : 2  |  Page : 145-148

An analysis of length of hospital stay of COVID-19 patients admitted in a dedicated COVID-19 hospital


1 Department of Community Medicine, Armed Forces Medical College, Pune, Maharashtra, India
2 Deputy Assistant Director Health, HQ 15 Inf Div, Amritsar, Punjab, India
3 O/o DGAFMS, IHQ of MoD, New Delhi, India

Date of Submission24-Oct-2020
Date of Decision17-Dec-2020
Date of Acceptance26-Dec-2020
Date of Web Publication21-Jul-2021

Correspondence Address:
Maj (Dr). Aayush Maj
Department of Community Medicine, Armed Forces Medical College, Pune - 411 040, Maharashtra
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jmms.jmms_156_20

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  Abstract 


Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has placed an unprecedented strain on Indian healthcare systems, with rapidly increasing demand for life-saving equipment and intensive care unit beds. The present study presents an analysis of average length of stay (LOS) as per different demographic and clinical factors in a dedicated COVID hospital. As the pandemic escalates, average LOS in COVID hospital will form the basis of determining the optimum requirement for healthcare resources (beds, staff, and equipment), which is a key priority for bolstering a strong public health response against COVID-19. Materials and Methods: Using the medical records at a dedicated COVID-19 hospital, the demographic details and select clinical characteristics of 342 admitted patients (from July 13, 2020, to August 30, 2020) were abstracted. Hospital LOS, calculated from the actual admission and discharge dates, was compared within the categories of demographic and clinical characteristics using Student's test and analysis of variance. SPSS version 20 was used for descriptive as well as inferential statistics. Results: The mean LOS was 9.93 ± 4.45 days with a range of 3–37 days. LOS increased with increasing age, with maximum being for >61 years (12.69 ± 7.14) and minimum for the younger age category of <40 years (8.88 ± 1.95) (P = 0.001). As COVID-19 severity increased, LOS increased, with longest being for severe patients (25.59 ± 7.30) and shortest being for Mild patients (8.74 ± 1.80) (P = 0.001). LOS was also longer for patients having multiple comorbidities (13.00 ± 7.96) and shortest for those with no comorbidities (9.33 ± 2.96) (P = 0.001). Conclusion: LOS is significantly affected by age, severity, and comorbidities. The actual duration and factors influencing LOS are crucial for health administrators and policymakers to better allocate the already scarce health resources.

Keywords: Coronavirus disease 2019, demographics, length of stay, severe acute respiratory syndrome coronavirus 2


How to cite this article:
Maj A, Bobdey S, Kumar S, Sahu R, Vashisht R, Bhaskar V, Faujdar D S, Yadav AK, Kaushik S K, Bhatia S S. An analysis of length of hospital stay of COVID-19 patients admitted in a dedicated COVID-19 hospital. J Mar Med Soc 2021;23:145-8

How to cite this URL:
Maj A, Bobdey S, Kumar S, Sahu R, Vashisht R, Bhaskar V, Faujdar D S, Yadav AK, Kaushik S K, Bhatia S S. An analysis of length of hospital stay of COVID-19 patients admitted in a dedicated COVID-19 hospital. J Mar Med Soc [serial online] 2021 [cited 2021 Dec 3];23:145-8. Available from: https://www.marinemedicalsociety.in/text.asp?2021/23/2/145/322063




  Introduction Top


An acute respiratory disease caused by novel coronavirus was first traced in December 2019, from Wuhan, China. The infectious agent responsible was named as severe acute respiratory syndrome coronavirus 2 and disease named as coronavirus disease 2019 (COVID-19). Ever since the outbreak in December 2019, the virus has rapidly spread across the globe and was declared a pandemic by the WHO on March 11, 2020.[1] The disease is still evolving; however, at the time of the article being sent for printing, the common clinical symptoms include fever, cough, fatigue, shortness of breath, sore throat, and anosmia, with the prognosis being poorer for those with preexisting comorbidities.[2] The Indian Council of Medical Research (ICMR) has recommended that based on disease presentation and clinical assessment, every case of COVID-19 has to be classified as either mild, moderate, or severe for ensuring provision of standard treatment as per laid down protocol.[3]

In India, with the cases still rising in majority of states, the risk of healthcare services being overwhelmed cannot be ignored. Understanding and predicting hospital bed demand and an estimate of how long each patient will require hospital care provide crucial evidence for decision-making and contingency planning.[4],[5] Thus, accurate knowledge on hospital length of stay (LOS) and factors affecting it in COVID-19 scenario is crucial for planning of allocation of scarce medical resources to those most in need.

So far, many studies have described COVID-19 epidemiology, clinical aspects, prevention, and control which have allowed researchers and policymakers to understand the disease better.[6],[7] However, studies on factors affecting the hospital LOS are few. As per the present level of understanding of the disease, factors such as increased age and presence of comorbidities are related to more severe manifestations of the disease.[2],[8] Therefore, to describe the distribution of demographic and clinical presentation of patients admitted in a dedicated COVID-19 hospital, as well as to explore the association of patient characteristics and length of hospital stay, the present study was undertaken.


  Materials and Methods Top


The study was a retrospective medical record-based study. The details of the patient including their demographic profile and relevant characteristics such as age, gender, and comorbidities if any were abstracted from the electronic and physical medical records of the patients admitted in a dedicated COVID hospital located in Northern India. Medical records of all COVID-19 patients diagnosed after a positive reverse transcriptase–polymerase chain reaction (RT-PCR)/rapid antigen-based test and admitted in the hospital from July 13, 2020 to August 30, 2020 were included in the study.

Patients with fatal outcomes were excluded from the study. The classification of patients as mild/moderate/severe and their clinical management at the hospital was carried out as per the protocol laid down by the Ministry of Health and Family Welfare.[3] Hospital LOS was calculated from the actual admission and discharge dates. The hospital strictly followed the ICMR policy for discharge of COVID 19 patients, i.e., mild cases were discharged after 10 days of symptom onset and no fever for 3 days, moderate cases were discharged after 10 days of symptom onset in case of absence of fever without antipyretics, resolution of breathlessness, and no oxygen requirement, and severe cases were discharged on clinical recovery and after one negative test by RT-PCR (after resolution of symptoms).[9] The study was approved by the institutional ethics committee. Student's t-test and analysis of variance were carried out to compare average LOS. The data were analyzed using an electronic statistical software (IBM SPSS for Windows, version 20.0. IBM Corp., Armonk, NY, USA).


  Results Top


A total of 342 patients who admitted and discharged from the hospital between July 13 and August 31, 2020, were included in the study. The mean age of the patients was 41 ± 17.28 years and 70.5% of them were males. Out of the total patients, 79.8% were mild, 15.2% moderate, and 5% severe. Among the 342 patients, 16.4% of patients had a single comorbidity (e.g., hypertension/diabetes mellitus/COPD), 14% had multiple comorbidities, and most (69.6%) had no comorbidities. The baseline characteristics of the patients are summarized in [Table 1].
Table 1: Distribution of baseline characteristics

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The mean LOS was 9.93 ± 4.45 days with a range of 3–37 days. The analysis of LOS as per demographic profile, disease severity, and comorbidities is depicted in [Table 2]. LOS significantly increased with increasing age, with maximum being for >61 years (12.69 ± 7.14) and minimum for the younger age category of <40 years (8.88 ± 1.95). There was no significant difference in LOS between males and females. As COVID-19 severity increased, LOS increased significantly, with longest being for severe patients (25.59 ± 7.30) and shortest being for mild patients (8.74 ± 1.80). The LOS was significantly longer for patients having multiple comorbidities (13.00 ± 7.96) and shortest for those with no comorbidities (9.33 ± 2.96).
Table 2: Hospital length of stay as per age, gender, severity, and comorbidities

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  Discussion Top


Length of hospital stay (LOS) is an important indicator of utilization of medical services and is often used to assess the efficiency of hospital management, quality of care, and evaluation of functional processes. Decreased LOS has been associated with decrease in risks of opportunistic infections with improvements in the treatment outcome and lower mortality rates.[10],[11] Furthermore, in the present pandemic scenario, shorter hospital LOS increases the bed turnover rate which in turn helps in treating more number of needy patients and overall results in lower social costs. In the mid of COVID-19 pandemic, better understanding of how long patients remain in hospital is critical for planning and predicting bed occupancy as well as associated staff and equipment requirement for providing care to needy patients and planning for the surge, in case the pandemic spirals out of control.

In the present study, we found that hospital stay was longer for elderly patients, especially for those more than 60 years old. This may be due to the understanding that as age increases, disease severity may increase which in turn may affect the LOS. Similar findings were observed in a detailed global COVID-19 report which analyzed data of over 25 countries across the globe and a few other studies.[12],[13] There was no significant difference in LOS observed in both sexes, which is acceptable as the disease has not shown any predilection for either sex in terms of occurrence or severity. Our study also showed that LOS increased as disease severity increased. One study similarly pointed out that critical COVID-19 patients have a higher percentage of bacterial coinfections and a higher mortality rate than patients with moderate disease and thus also longer hospital stays. The same study showed that the median LOS for moderate COVID-19 patients was 15 days (interquartile range – 12–22 days), which was significantly different from that of critical patients (21 days, interquartile range –12–48 days).[14] Finally, in our study, LOS was significantly longer for patients having multiple comorbidities and shortest for those with no comorbidities. It is now well known that the presence of comorbidities leads to a more severe disease course.[2],[15] A latest study has shown that obesity is an important predictor of a more severe respiratory presentation of COVID-19 and severe elevation of inflammatory markers, likely leading to higher oxygen demands at admission, prolonged oxygen requirement during hospitalization, delayed viral clearance, and extended hospital stay.[16] Similarly, one research also showed that severe pneumonia at presentation was significantly related to greater LOS, and the median length of hospital stay varies from 22 days for pneumonia patients to 25 days for those with severe pneumonia.[17]

Limitations

The present study, despite having the distinction of being one of its kinds in the Indian scenario, is not devoid of limitations. First, factors such as symptoms at onset, clinical parameters, and occurrence of complications, that have a huge impact on the LOS, were not taken into consideration due nonavailability of uniform data. Second, laboratory parameters such as neutrophil count, lymphocyte count, and C-reactive protein levels could not be analyzed. Third, a measure of correlation between age, severity, and comorbidities can be calculated after the analysis done above which might give additional insights into the relation between these variables and LOS. Considering availability of limited data, the main objective of our study was to describe the effect of selected variables on LOS; however, in the future, more detailed studies should be undertaken in this direction. Finally, this was a retrospective study with data abstraction from the electronic medical record and hence limited to the availability of data recorded in the physical/electronic case sheets.


  Conclusion Top


The present study is unique in that it presents LOS of the same disease and patients undergoing the same treatment as per the predefined protocols. It highlights the impact of demographics and certain select characteristics on LOS of a COVID-19 patient. The study will help policymakers and administrators in evidence-based allocation of scarce medical resources.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
World Health Organization. Virtual Press Conference on COVID-19 – March 11, 2020. Available from: https://www.who.int/docs/default-source/coronaviruse/transcripts/who-audio-emergencies-coronavirus-press-conference-full-and-final-11mar2020.pdf. [Last accessed on 2020 Sep 20].  Back to cited text no. 1
    
2.
Guan WJ, Liang WH, Zhao Y, Liang HR, Chen ZS, Li YM, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: A nationwide analysis. Eur Respir J 2020;55:2000547.  Back to cited text no. 2
    
3.
Ministry of Health and Family Welfare. Clinical Management Protocol: COVID-19; 2020. Available from: https://www.mohfw.gov.in/pdf/UpdatedClinicalManagementProtcolforCOVID19dated03072020.pdf. [Last accessed on 2020 Sep 11].  Back to cited text no. 3
    
4.
Rosenbaum L. Facing COVID-19 in Italy-Ethics, logistics, and therapeutics on the epidemic's front line. N Engl J Med 2020;382:1873-5.  Back to cited text no. 4
    
5.
Rodriguez-Morales AJ, Cardona-Ospina JA, Ocampo GE, Peña VR, Rivera HY, Escalera-Antezana JP, et al. Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis. Travel Med Infect Dis 2020:34:101623.  Back to cited text no. 5
    
6.
Zhang L, Li B, Jia P, Pu J, Bai B, Li Y, et al. An analysis of global research on SARS-CoV-2. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi 2020;37:236-45.  Back to cited text no. 6
    
7.
Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel coronavirus from patients with pneumonia in China. N Engl J Med 2020;382:727-33.  Back to cited text no. 7
    
8.
Li X, Xu S, Yu M, Wang K, Tao Y, Zhou Y, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allergy Clin Immunol 2020;146:110-8.  Back to cited text no. 8
    
9.
Ministry of Health and Family Welfare. Updated Revised Discharge Policy for COVID-19; 2020. Available from: https://www.mohfw.gov.in/pdf/ReviseddischargePolicyforCOVID19.pdf. [Last accessed on 2020 Sep 11].  Back to cited text no. 9
    
10.
Bueno H, Ross JS, Wang Y, Chen J, Vidán MT, Normand SL, et al. Trends in length of stay and short-term outcomes among Medicare patients hospitalized for heart failure, 1993-2006. JAMA 2010;303:2141-7.  Back to cited text no. 10
    
11.
Rotter T, Kinsman L, James E, Machotta A, Gothe H, Willis J, et al. Clinical pathways: Effects on professional practice, patient outcomes, length of stay and hospital costs. Cochrane Database Syst Rev 2010;(3):CD006632.  Back to cited text no. 11
    
12.
Consortium, I.S.A.R.a.E.I. COVID-19 Report. Technical Report; 2020. Available from: https://media.tghn.org/medialibrary/2020/04/ISARIC_Data_Platform_COVID-19_Report_8APR20.pdf. [Last accessed on 2020 Sep 11].  Back to cited text no. 12
    
13.
Li B. The association between symptom onset and length of hospital stay in 2019 novel coronavirus pneumonia cases without epidemiological trace. J Natl Med Assoc 2020;112:516-7.  Back to cited text no. 13
    
14.
Feng Y, Ling Y, Bai T, Xie Y, Huang J, Li J, et al. COVID-19 with different severities: A multicenter study of clinical features. Am J Respir Crit Care Med 2020;201:1380-8.  Back to cited text no. 14
    
15.
Sanyaolu A, Okorie C, Marinkovic A, Patidar R, Younis K, Desai P, et al. Comorbidity and its impact on patients with COVID-19. SN Compr Clin Med 2020;(2):1069-76.  Back to cited text no. 15
    
16.
Moriconi D, Masi S, Rebelos E, Virdis A, Manca ML, De Marco S, et al. Obesity prolongs the hospital stay in patients affected by COVID-19, and may impact on SARS-COV-2 shedding. Obes Res Clin Pract 2020;14:205-9.  Back to cited text no. 16
    
17.
Liu X, Zhou H, Zhou Y, Wu X, Zhao Y, Lu Y, et al. Risk factors associated with disease severity and length of hospital stay in COVID-19 patients. J Infect 2020;81:e95-7.  Back to cited text no. 17
    



 
 
    Tables

  [Table 1], [Table 2]



 

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