The COVID-19 Impact on Inpatient Hospital Admissions in Indiaa Cross-Sectional Study

Aim & Objectives

We have started this novel study with key aim to assess positive or any negative impact of COVID-19 situation on IPD (other than COVID-19) hospital admissions count in India. We included all (public/private/rural/urban) health facilities across 36 states and union territories in India. The data were obtained from online HMIS (Health Management Information System) of GoI, Ministry of Health and Family Welfare (MoHFW). This study has done an analysis on IPD health service utilization during COVID-19 situation, of significant and more prevalent diseases in India. The key objective of this study is to assess the increase / decrease in the IPD patients during the covid-19 years in comparison to the pre-pandemic period. The Mean IPD patient is considered for comparison.

Methods & Materials

This research study is done for assessing the COVID-19 impact on IPD service utilization. Change in the numbers of IPD patients during COVID-19 epoch is assumed to be effects of pandemic. COVID-19 era IPD patient’s data is compared to pre-pandemic years for above purpose. As the index case was reported in January 2020, epoch before 1st January 2020 is called the pre-pandemic era. From 1st January 2020 onward the period is taken as the pandemic epoch as discussed above.

This study was not sample survey and included all IPDs (indoor patients) of 36 states and union territories of India. Hence there is no requirement of any statistical t-test or ANOVA. There is no question of generalisability of data as the data included the entire population of IPD admissions. Hence we do not feel any requirements for applying inferential statistical methods. This is a novel, comparative, cross- sectional, research study to assess the extent of the invisible impacts of the COVID-19 as stated above. Health facility- based retrospective study was conducted for IPD admissions in India, across 36 states and UTs from 1st  January 2018 to 31st  May 2021. The data collected from HMIS, for IPD admissions during this study period is available in Table- 1and presented as Figure-1 for easy visualization. The HMIS reporting arrangement is used by all 36 states and UTs of India [26]. This study included all the (Public-private-rural- urban) health facilities of 36 states and UTs of India, on HMIS.

Study Variables and Operational Definition

The variables included for this study were IPD count of following inpatients:-

• Inpatient (Male)- Children<18yrs
• Inpatient (Male)- Adults
• Inpatient (Female)- Children<18yrs
• Inpatient (Female)- Adults
• Inpatient - Malaria
• Inpatient - Dengue
• Inpatient - Typhoid
• Inpatient - Asthma, Chronic Obstructive Pulmonary Disease (COPD), Respiratory infections
• Inpatient - Tuberculosis
• Inpatient - Pyrexia of unknown origin (PUO)
• Inpatient - Diarrhoea with dehydration
• Inpatient - Hepatitis Any unusual change, in the pattern or count of above mentioned variables during the COVID-19 pandemic compared to pre-pandemic period in IPD services utilization is considered as COVID-19 pandemic impact for this study purpose. Microsoft office and stata15.1 software were only utilized for this study data collection and analysis.

Table1: Total IPD admissions of Public-private-rural-urban health facilities of 36 states and UTs of India registered during different months of the study period (study size of variables).

Participants Inclusion criteria - Any IPD registered on HMIS related to Operational Definition given above.

Exclusion criteria - Any IPD services not related to Operational Definition given above.

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• Data sources / measurement The Data source link is given below. - https://hmis.nhp.gov.in/#!/standardReports
• Ethical Consideration This study did not require ethical endorsement and informed consent. The data utilized for this study were publicly available for anyone. This study is in acquiescence with Indian data policy.
• Data Analysis Stata 15.1 and Microsoft office were only utilized for different calculations such as difference in IPD and mean IPD cases as well as for comparison of 24-month pre-pandemic epoch (2018–2019) with 17-month pandemic epoch in 2020-2021, (Table 2 & Figure 2).

For determining the magnitude of IPD count change due to the pandemic, we compared it to the pre- pandemic mean IPD for above mentioned 12 variables; (Table 3 & Figure 3). The period prevalence for IPD admissions were taken as a count of inpatient admissions during specified period divided by the total population during that period (population source- The World Bank data 2018-2021[27]).

Results

The total numbers of IPD of different variables mentioned above during the study period is presented as Table 1 and Figure 1. The Figure 1 is also highlighting lockdown period impact on IPD. The GoI (Government of India) enforced an obligatory nationwide lockdown from 25th March 2020 ending on 31st May 2020. The figure-1 clearly demonstrates an unusual decline/dip in IPD admissions count during this lockdown period highlighted with an arrow. Figure 2 show that all mean IPDs under study reduced during COVID-19 era of this study.

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The total registered IPD during the study period were Table 1

1. 27614161number of Inpatient (Male)- Children<18yrs;
2. 72174649 number of Inpatient (Male)- Adults;
3. 24945573number of Inpatient (Female)- Children<18yrs;
4. 121090894 number of Inpatient (Female)- Adults;
5. 872855 number of Inpatient of Malaria,
6. 393407 number of Inpatient of Dengue,
7. 1509552 number of Inpatient of Typhoid,
8. 5415845 number of Inpatient of Asthma, Chronic Obstructive Pulmonary Disease (COPD), Respiratory infections,
9. 742661 number of Inpatient of Tuberculosis,
10. 7173524 number of Inpatient of Pyrexia of unknown origin (PUO),
11. 7603860 number of Inpatient of Diarrhoea with dehydration,
12. 505806 number of Inpatient of Hepatitis Outcome data The outcome data of this study is presented as Tables 2-4 and Figures 2-4 for easy visualization of readers.

Table-2, 3, 4 and figure-2, 3, 4 demonstrates that the mean IPD admissions during COVID-19 period were 5387311 whereas the mean IPD admissions for pre-pandemic period were 7435770.

The mean IPD admission reduced by 2048459 numbers during COVID-19 pandemic period of this study or in percentage reduced by 27.55% presented as Table 2 and Figure 2 for easy visualization. This study found that there is a significant reduction in various IPD admissions for medical conditions other than COVID-19, during the COVID-19 period which must be a matter of concern for important stakeholders of the health system in the light of our knowledge that it is possible to reduce the burden of disease in a small period.

Discussion

This research study observed a massive drop in IPD admissions during April 2020, after imposition of national lockdown in India. The mean numbers of IPD admission decreased during COVID-19 as compared to pre-pandemic epoch. IPD admissions other than COVID-19 reduced by 27.55 percent in India, during the COVID-19 period of this study. Actually this IPD should have increased due to the fact that COVID-19 aggravates pre-existing medical and social conditions like domestic violence etc. as indirect effect of COVID-19 [28, 29]. There are wide geographical variations in prevalence of COVID-19 in India [30]. The mortality count increased at emergency ward in India, inducing a sense of fear among the population [31]. The prevalence of sexually transmitted disease (STD) was also altered during COVID-19 [32, 33, 34]. IPD admissions are critical for NCD (non- communicable diseases) like cancers as well as incidence of such NCDs are also increasing in India [35]. Due to the above mentioned facts it is questionable that how the IPD admissions decreased during COVID-19. Why? Naturally such question is coming to researcher mind. Possible factors responsible for this reduction in IPD admissions may be

• Lockdown induced reduced mobility.
• Fear of COVID-19 infection at hospital.
• Reduced income due to loss of jobs as indirect COVID-19 impact, leading to reduced OOPE (out of pocket expenditure) capacity.
• Scarcity of bed for IPD admissions other than COVID-19 cases.
• Self or family ignorance and social ignorance or negligence.
• Lack of doctors and staff for attending medical conditions other than COVID-19.
• COVID-19 illness and mortality among healthcare workers.
• Disturbance within the hospital system due to pandemic.
• Decrease in the referral rate as a result of reduction in (OPD) outpatient.
• Encouragement by medical insurance companies and others to find alternative way to receive medical care like telemedicine.
• Regular news about the patient death and excessive IPD costs charged by hospital spread through media or non medical healthcare professionals.

A decrease in IPD for conditions which prevalence or incidence is not dependent on COVID-19, may pose a grave risk if left untreated. The question arises what happened to these patients? Like other nations, the response of healthcare in India to this unexpected COVID-19 was to mitigate the perceived requirements of COVID-19. This study of HMIS data revealed that, the pandemic resulted in a universal reduction of IPD services utilization of all study variables. The future consequences of this reduction in IPD services utilization in India may augment mortality rates in the coming years for diseases other than COVID-19. Added to this COVID-19 hampered several other essential health services utilization as direct/indirect impact of COVID-19 [36, 37, 38, 39, 40]. The readers may love to read key researcher other papers discussing COVID-19 impact on health services available at WHO Covid-19 research database [41].

Future VERSION of this research study will try to reveal that up to what time and magnitude IPD services recovers during upcoming years.

The influence of COVID-19 on patients of chronic medical conditions who require regular IPD care may be of grave consequences. It is quite predictable that the majority of the population could not manage to pay for private hospitals due to cost factors. Patients recently diagnosed with NCDs may not be able to get the IPD treatment, as well as previous NCDs patients missed their regular therapy. It is quite obvious from this study that patients with conditions other than COVID-19 will face an amplified risk in coming years for complications, morbidity and mortality owing to missed IPD services utilization. Deferred initiations and interruption in treatment may augment NCDs disease progression, reappearance, as well as stress, and premature mortality with morbidity.

COVID-19 epoch negative impact on IPD is due to factors, such as health workers shifting for the COVID-19 pandemic control, etc [42]. The IPD decline may be due to prior information of COVID-19 by media and channels which may have prejudiced health-seeking behaviour.

Strength and Limitations of this Study

The strength of this study is the data set on IPD activity for all HMIS (MoHFW) registered hospitals in India. Furthermore this is a unique attempt to describe the bearing of SARS-CoV-2 pandemic on IPD in India. A limitation of this study is lack of data from any other source as well as lack of data for other significant medical conditions.

Conclusions and Recommendations

The HMIS data should be more regular and frequent for making judicious decision in responding to emergencies like COVID-19. Moreover, an in-depth HMIS data set can make us available insights into epidemiology, utilization patterns, and burden outcomes like mortality rates. There is room for improvement in HMIS data. The lesson learnt from this pandemic is the need to prepare strategies and policies whereby the reaction to pandemics is not at the cost of other health care needs. One area for upgrading is timeliness and health authorities need to take into description the population health needs, equity and notify the public accordingly [43]. The strategy should take into account an evaluation of the negative consequences to population health needs if already existing healthcare resources are shifted from one care need to another. For hospitals, the framework or action plan would denote that their reaction to pandemic situations is phased-in and in line with clinical need. The framework should be prearranged around specialist with the aim to reduce disruption to the prerequisite of other medical conditions. This requires the orderliness of hospitals with flexibility in their ability to react to different conditions, and for providing a safe patient environment at times of distress. Telemedicine and well-targeted information drive to educate the community of consequences of not seeking care may improve outcome. The states at bottom ranks in the NITI AAYOG health index report must be focussed more by the centre [44, 45]. The Government of India advised all the states for PHMC establishment by the end of 2022 [46].

The civil registration system of birth and death should be improved with transparency for satisfaction of the accredited organizations like WHO [47].

We Recommend the Following:

• Governments of India should make strategies on priority to trim down burden of morbidity and mortality, in order to reap the benefits of Demographic Dividend. The COVID-19 management should not be prioritized at the cost of other NCDs and CDs.
• Government need a robust and flexible framework to respond to distress with considerations of rigorous restrictions which interrupt routine essential health services, leading to a vicious cycle on the health need of population.
• Government of India should focus on proper and timely data collection.
• The states of India must comply with the central government guidelines [48, 49, 50, 51].

Funding

The author declares that no fund has been taken for this research study from any individual or agencies.

Declarations

This version of paper has not been previously published in any peer reviewed journal and is not currently under consideration by any journal. The document is Microsoft word with English (India) language and 8059 words Total including all. Ethics approval and consent to participate: Not applicable. This study has not involved any human or animals in real or for experiments. The submitted work does not contain any identifiable patient/participant information. Consent for publication: The author provides consent for publication. Availability of data and materials: Electronic records from HMIS (health management information system) of MoHFW (ministry of health and family welfare), Government of India. Conflicts of Interest/ Competing Interest: There are no conflicts / competing of interest Authors’ contributions: The whole work is done by the key Author - Dr Piyush Kumar, M.B.B.S., E.M.O.C., P.G.D.P.H.M., -Senior General Medical Officer- Bihar Health Services- Health Department- Government of Bihar, India, and Co- authors, Advocate Anupama, Senior Lawyer, Bar-council, Patna, Bihar, Dr Abhishek Sinha, Dr. Priyanka Verma, Dr Alok and Harshika Singh. Acknowledgements I am thankful to Advocate Anupama my wife and daughters Aathmika-Atheeva for cooperation. Author information: The author is currently working as Senior General Medical Officer for the government of Bihar.