The impact of COVID-19 on heart failure admissions in Suriname-A call for action

Abstract

Introduction

During the height of the COVID-19 pandemic, there was a worldwide reorganization of healthcare systems focusing on limiting the spread of the virus. The impact of these measures on heart failure (HF) admissions is scarcely reported in Low and Middle Income Countries (LMICs) including Suriname. We therefore assessed HF hospitalizations before and during the pandemic and call for action to improve healthcare access in Suriname through the development and implementation of telehealth strategies.

Methods

Retrospectively collected clinical (# hospitalizations per patient, in hospital mortality, comorbidities) and demographic (sex, age, ethnicity) data of people hospitalized with a primary or secondary HF discharge ICD10 code in the Academic Hospital Paramaribo (AZP) from February to December 2019 (pre-pandemic) and February to December 2020 (during the pandemic) were used for analysis. Data are presented as frequencies with corresponding percentages. T-tests were used to analyze continuous variables and the two-sample test for proportions for categorical variables.

Results

There was an overall slight decrease of 9.1% HF admissions (N pre-pandemic:417 vs N during the pandemic: 383). Significantly less patients (18.3%, p-value<0.00) were hospitalized during the pandemic (N: 249 (65.0%)) compared to pre-pandemic (N: 348 (83.3%)), while readmissions increased statistically significantly for both readmissions within 90 days (75 (19.6%) vs 55 (13.2%), p-value = 0.01) and readmissions within 365 days (122 (31.9%) vs 70 (16.7%), p-value = 0.00) in 2020 compared to 2019. Patients admitted during the pandemic also had significantly more of the following comorbidities: hypertension (46.2% vs 30.6%, p-value = 0.00), diabetes (31.9% vs 24.9%, p-value = 0.03) anemia (12.8% vs 3.1%, p-value = 0.00), and atrial fibrillation (22.7% vs 15.1%, p-value = 0.00).

Conclusion

HF admissions were reduced during the pandemic while HF readmissions increased compared to the pre-pandemic period. Due to in-person consultation restrictions, the HF clinic was inactive during the pandemic period. Distance monitoring of HF patients via telehealth tools could help in reducing these adverse effects. This call for action identifies key elements (digital and health literacy, telehealth legislation, integration of telehealth tools within the current healthcare sector) needed for the successful development and implementation of these tools in LMICs.

1. Introduction

The COVID-19 pandemic has led to a worldwide reorganization of our society including the healthcare system, most prominently the implementation of several restrictive measures with the aim to limit the spread of the virus.¹ Patients with heart failure (HF) are in general already a vulnerable population predisposed to decompensation and hospitalization and are thus at elevated risk for the detrimental effects of the COVID-19 pandemic. These effects can be direct through SARS‑CoV‑2 infection and its associated morbidity and mortality or indirect due to the restrictive measures resulting in a decline of provided physical care within clinical and ambulatory settings.² Hence, across several European countries, such as the UK,3, 4, 5 Germany,⁶ Italy^{7 , 8} and Spain,⁹ a significant decline in HF hospitalizations has been reported during the COVID-19 pandemic in 2020 compared to the previous year. The same has also been reported in the U.S.A.,¹⁰ Argentina,¹¹ Brazil,¹² Australia¹³ and Asia.^{14 , 15} Additionally, the decline in HF hospitalizations seems to be associated with a higher in-hospital mortality^{3 , 7} as well as a higher New York Heart Association (NYHA) functional class at admission.^{6 , 12} In High Income Countries (HICs) especially in North America and Europe, implementation of telehealth including virtual consultations, was strongly recommended, reimbursed, and implemented to ensure continuous ambulatory care.16, 17, 18 Early data on the effects of telehealth tools employed during the first year of the pandemic show that these tools are a viable option for quality healthcare delivery compared to in-person care.^{16 , 19} There is however little information available regarding the pandemic mitigating measures and the effect of these measures in Low and Middle Income Countries (LMICs) such as Suriname, situated on the northeast coast of South-America.

The first case of COVID-19 in Suriname was reported on March 13, 2020, which immediately led to strict governmental rules and regulations to limit the transmission until the end of April 2020, when no more official documented active COVID-19 cases were present in Suriname. In June 2020, the number of active cases increased again in Suriname, reaching a peak in August 2020. During this period, the government introduced a nationwide full lockdown and other social distancing measures in various formats, including no social gatherings, no in-person routine ambulatory care, and promotion of remote school and work methods. During these months, the 6 hospitals in the country operated under special protocols geared to only urgent clinical and outpatient care while the majority of care was directed towards COVID-19 cases. Since telehealth strategies are very scarce and not reimbursed by insurance companies in Suriname, HF patients had limited healthcare access during these months. We therefore hypothesize that admissions for heart failure decreased during the pandemic while readmissions increased. In this context, this study aims to analyze and compare the clinical data of HF hospitalizations in the Academic Hospital Paramaribo (AZP) for the months from February to December 2019 (pre-pandemic) and compared to February to December 2020 (during the pandemic). Furthermore, we make a call for action to improve healthcare access in Suriname through the development and implementation of telehealth strategies.

2. Methods

2.1. Study design and site

The Republic of Suriname is a small upper middle income country (Gross Domestic Product, GDP =2.86) situated on the north-east coast of South-America and is part of the Caribbean Community (CARICOM). The 2019 estimated population was 598,000 inhabitants of which 394.000 (65.9%) people are 20 years and older.²⁰ The multiethnic and multicultural population consists mainly of people from African: Creole (15.7%) and Tribal communities (21.7%), and South-Asian: Hindustani (27.4%) and Javanese (13.7%) descent residing mostly in the coastal area, including the capital Paramaribo. The human development index (HDI) is 0.73 and about 70% of the population has at least a basic health insurance. The main economic drivers are the exploitation of natural resources, mainly gold and oil accounting for almost 80% of public sector revenues.²¹ There are 6 hospitals in Suriname of which 4 reside in the capital Paramaribo. The Academic Hospital Paramaribo (AZP) is the largest hospital in Suriname, situated in the capital Paramaribo, with 530 beds and approximately 26.000 annual admissions. The Thorax Center Paramaribo (TCP), with 34 beds and 2500 annual admissions, is located within the AZP, and serves as the reference cardiac center in Suriname. The Center delivers interventional cardiac care to more than 90% of patients with cardiovascular diseases (CVDs) in Suriname. In 2019, the TCP implemented the HF program aimed at improving HF care. At the core of HF care are regular follow-up outpatient consultations focused on HF education by a trained nurse, and optimization of guideline-directed medical therapy (GDMT) by a cardiologist. Our recent publication on HF admissions shows that there were approximately 1274 HF admissions of which 16% readmissions within the TCP between 2013 and 2015.²² Since then, the number of cardiologists has almost doubled, resulting in a total of 12 cardiologists.

2.2. Data collection

For this study, data were retrospectively collected from the medical registry department at the AZP. All hospitalizations with a primary and or secondary International Statistical Classification of Diseases and Related Health Problems (ICD-10) discharge code: I11.0, I13.0, I13.2, and I50.0-I50.9 were retrieved from the administrative electronic health record system. The collected HF patient data include patient demographics (age, sex, residence, and ethnicity), identification number (used to determine number of admissions per patient), admission and discharge date, primary and secondary discharge diagnosis, status after discharge, and all secondary diagnoses. Ethnicity was self-reported and includes Asians: Hindustani, Javanese, and Chinese; African descendants: Creole, and Tribal communities, and Other (Caucasian, Indigenous and Mixed). Exclusion criteria were patients younger than 20 years and those with reversible acute HF secondary to trauma. For our analysis we divided the cohort into 2 groups according to the period. Group 1, the pre-pandemic period, ranging from February 1^st- December 31^st 2019 and was statistically compared to group 2, Pandemic period, ranging from February 1^st- December 31^st 2020. The month of January was excluded from analysis since there was no surveillance yet on COVID-19 at that time.

2.3. Study outcomes

The primary study outcome is HF admissions during the pandemic period compared to the pre-pandemic period. Secondary outcomes are the admission trend, 30-, 90-day and 1 year HF hospital readmission, length of stay, comorbidities, and in-hospital mortality rate during the 2 periods.

2.4. Data analysis

The data were analyzed using Statistical Package for the Social Sciences (SPSS) version 23 (IBM, Chicago, USA). Continuous variables are presented as mean with standard deviation (SD) (parametric analysis) or median (range) (non-parametric analysis). Student's T-test was used for testing statistical significance for the variables age and length of stay (LOS). Categorical variables (all other variables in Table 1 ) are presented as frequencies (N, percentages) and were analyzed for statistical significance using the 2 sample test for proportions. Differences were considered statistically significant when a p-value <0.05 is obtained.

Table 1.

Primary and secondary HF admissions in the TCP-AZP between February- December 2019 and 2020

	2019	2020	p-value
Hospitalizations, N	417	383
Rate of first admissions per 100,000 pop ≥20 yrs	106	97
^Hospitalizations versus patients			0.00
Patients, N (%)	347 (83.1)	249 (65.0)
Readmissions, N (%)	70 (16.7)	134 (35.0)	0.00
Readmissions <30 days, N (%)	27 (6.5)	36 (9.4)	0.09
Readmissions <90 days, N (%)	55 (13.2)	75 (19.6)	0.01
Readmissions <365 days, N (%)	70 (16.7)	122 (31.9)	0.00
Length of stay	7.2 ± 7.5	6.6 ± 4.7	0.15
^Gender
Female, N (%)	167 (48.1)	125 (50.2)	0.64
^Age at first admission, M (±SD)	64.9 ± 13.6	63.9 ± 12.7	0.36
^Ethnicity			0.58
African descent	115 (33.1)	73 (29.3)
Asian descent	178 (51.1)	134 (53.8)
Other	54 (15.5)	42 (16.9)
Risk factors
DM	104 (24.9)	122 (31.9)	0.03
HT	128 (30.6)	177 (46.2)	0.00
Anemia	13 (3.1)	49 (12.8)	0.00
AF	63 (15.1)	87 (22.7)	0.00
Mortality, N (%)	8 (1.9)	1 (0.3)	0.03

*Asian descent (Chinese, Hindustani, Javanese), African descent (Creole and Tribal communities), Other (Indigenous, Mixed, Caucasian). ^ These variables are calculated using the number of patients per year. All other variables are calculated using the number of hospitalizations per year.^# the 2019 mid-year estimated population of Suriname 20 years and older is 394,000.

3. Results

A total of 800 admissions met the inclusion criteria of which 417 were pre-pandemic and 383 during the pandemic, resulting in an overall slight decrease of 9.1% HF admissions (Table 1). The number of patients significantly decreased by 18.3% (347 (83.1%) vs 249 (65.0%), p-value<0.00). In contrast, the number of readmissions increased statistically significantly for both readmissions within 90 days and readmissions within 365 days in 2020 compared to 2019. Patients on average stayed half a day longer in the hospital in 2019 compared to 2020 but this finding was not statistically significant. Table 1 also highlights the significant increase in comorbid admissions with hypertension (HT), diabetes (DM), anemia and atrial fibrillation (AF), all statistically significant more prevalent during the pandemic period compared to pre-pandemic.

Figure 1 outlines the number of admissions on a monthly basis for the 2 study periods and shows that admissions decreased by approximately 35% (48 vs 31 admissions) in March 2020 compared to March 2019 and the decrease remained until April 2020. By mid-April 2020, Suriname had zero official documented COVID-19 cases and hospitals started scaling up their admissions, which reflects the influx of admissions at the end of April and May 2020. By June 2020, the government enforced country-wide lockdowns reducing in-person outpatient care. This resulted in a slight admission decrease in June, but an increase in HF admissions in July and August owing to an increase of readmissions (Figure 2 ). The performed logistic regression with the dependent variable readmission showed no significant association for the factors HT, DM, anemia, AF, sex, age, and ethnicity.

Figure 1.

Monthly HF admissions (N) for 2019 (blue bars) compared to 2020 (orange bars) (left Y-axis). The number of confirmed COVID-19 cases throughout the study period is seen in the grey line (Right y-axis)

Figure 2.

Percentage of 90-day readmission per month for 2019 (blue bars) and 2020 (orange bars)

4. Discussion

Our study shows that during the first 10 months of the COVID-19 pandemic, there was an overall drop in HF admissions varying between these months. We also report that especially early in the pandemic, fewer hospitalizations occurred while a significant number of those admissions were HF readmissions. Furthermore, the HF hospitalized patients in 2020 had significantly more comorbidities than those hospitalized in 2019.

The increase in readmissions during the pandemic could be the result of several factors. For instance, during the pandemic there was decreased ambulatory care due to the governmental restrictions, leading to less strict monitoring of HF symptoms by healthcare providers. Additionally, studies have reported that patients were more reluctant to seek medical attention during the early months of the pandemic and mostly sought care from the cardiologist when HF symptoms were exacerbated, which then lead to being hospitalized.^{23 , 24}

The study has some limitations that need to be taken into consideration. First, because this is a single center study, assessing only the HF admissions of HF patients does not fully capture the clinical history of these patients during the study period; HF patients are multimorbid which can lead to hospitalizations for their underlying conditions at various departments. Those hospitalizations are not included in this analysis. This may also cause selection bias since we included patients from one department in one hospital. However, with this assessment, we intended to present the impact of HF care disruption at the TCP. Another limitation is the lack of robust clinical and socio-demographic data which could give more insight into factors leading to the increase of readmissions and the state of patients entering the hospital during the pandemic. Furthermore, this is a retrospective analysis and some information that was missing could not be gathered. Further research and data collection may elucidate these questions.

A call for action

This study highlights the importance of exploring ways to guarantee the monitoring and management of HF patients in Suriname in times of a pandemic. It is well established that remote healthcare delivery via telehealth tools offers a practical solution and has added value in providing customized care for patients with chronic conditions during the pandemic^{25 , 26} but is also as an additional healthcare tool in the foreseeable future.^{27 , 28} However, this was not implemented in HF care in Suriname. The TCP implemented the HF care program in 2019 to improve HF care through comprehensive nurse-led consultations and educational sessions and is exploring ways to include telehealth. Telehealth can be valuable in times of a pandemic, but also for patients residing outside greater Paramaribo. These patients could be optimally monitored remotely and provided with the necessary care without extra travel time and costs that a physical appointment in the AZP, in the capital, entails. Analysis of the HF clinical patient population in the TCP show that the majority of patients come from the greater Paramaribo area (the capital Paramaribo and 2 surrounding districts), but that about 20% of HF patients travel from more distant districts for (outpatient) clinical care. Furthermore, care through telehealth can have economic benefits, reduce the pressure on outpatient care and contribute to the health related quality of life (HRQoL) of the HF patients.^{29 , 30}

To offer remote care to our HF patients, thorough research and preparation for implementing these tools in low-income settings are urgently needed and will aid in decreasing worldwide disparities in access to healthcare.³¹ This can be summarized into a number of action steps.

• •First, a feasibility study on how care can be offered at a distance whereby the majority of patients can be reached must be conducted. We must examine which tools (e.g., telephone calls, mobile applications, and websites) are most feasible. Additionally, these studies must identify local barriers in order to determine the feasibility of the telehealth tools.
• •Second, the health professionals who will provide the remote care will need to have the tools, knowledge, and skills to provide care in an efficient and responsible manner and must be willing to use these tools. Our team is currently performing such a study in HF patients and health care workers in the TCP and preliminary findings indicate that most patients are confident that a mobile application, as an eHealth tool, to monitor their HF symptoms and for educational purposes can aid in HF management and healthcare delivery. More than 80% of surveyed patients had access to a smartphone with internet (manuscript in development).
• •Third, health care institutions and their providers will have to collaborate with health insurers on models to fund this new form of care.
• •Fourth, this transition requires the commitment of all partners involved in the care of HF patients, ensuring good collaboration between cardiologists, nurses, general practitioners, physiotherapists, dietitians, and social workers to provide complete remote care for HF patients.

To realize the above-mentioned actions, developing policies for telehealth legislation, integrating these tools within the current healthcare sector, intensive cooperation between health workers and the ICT sector and addressing socio-demographic inequalities in healthcare delivery are pivotal to successfully implement these tools in our country.³² This proactive strategic roadmap of actions serves as a call to policy makers, healthcare institutions, health professionals, researchers, and governmental and non-governmental organizations to advance remote care specifically in LMICs. The benefits go beyond clinical HF outcomes and ultimately will lead to a more resilient health infrastructure, reducing the stressors on the health services system and ultimately decreasing health care costs.