High- and Low-Cost Healthcare Utilization for Cancer and COVID-19 Patients

Abstract

Background: Healthcare total spending accelerated during the COVID-19 pandemic. Understanding broad high- and low-cost healthcare utilization while the healthcare system is under stress can help identify strategies and gaps to improve the future quality of care while reducing high-cost care and maximizing low-cost care. Methods: This was a population-based cross-sectional study with 56,141 individuals in the U.S. using 2020–2021 Medical Expenditure Panel Survey (MEPS) data sources. We applied a Poisson regression approach to test differences among patients with/without cancer/COVID-19 in healthcare utilization outcomes, including emergency department (ED) visits, inpatient discharge, inpatient nights of stay, outpatient visits, and home provider days. Results: Outpatient visits were affected by both cancer and COVID-19 diagnoses (86% to 109% higher for individuals with cancer and/or COVID-19, p < 0.001). COVID-19 patients with/without cancer had statistically significant increases in high-cost care, including (1) ED visits (151% to 245% higher, p < 0.001), (2) number of inpatient visits (94% to 170%, p < 0.001, p < 0.001), and (3) inpatient nights of stay (259% to 268% higher, p < 0.001). There were no statistically significant differences in home-based utilization when compared to individuals without cancer and without COVID-19. Conclusions: Improving and adopting innovative low-cost home-based care utilization are critical to reduce future healthcare spending and strengthen pandemic preparedness.

1. Introduction

Healthcare spending accelerated during the COVID-19 pandemic globally, referred to as the Pandemic in this study [1]. In the U.S., total healthcare spending accelerated by 10.6% in 2020 during the Pandemic and continued to increase in 2021 and 2022 [2]. The Affordable Care Act (ACA) aims to improve care through focusing on low-cost care (e.g., outpatient, homecare) to ensure quality-, value-, and patient-centered care while reducing high-cost emergency room (ED) and inpatient care [3]. Low-cost outpatient and home healthcare is an important part of the support system for cancer patients in the U.S. [4]. However, homecare expenditure only accounted for 3% of the 4.5 trillion total expenditure in 2022 [2]. Cancer patients require routine access to healthcare for life-sustaining treatments and follow-up care. Cancer patients are at a high risk of being infected by COVID-19 and increased risk of severe illness [5]. The Pandemic has changed the delivery of healthcare worldwide [6]. Yet little is known about overall healthcare utilization for patients with cancer during the Pandemic in the U.S., including low-cost (e.g., outpatient, home-based care) and high-cost care (e.g., emergency room and inpatient).

Healthcare policy makers need to fully understand COVID-19’s impact on low- and high-cost care utilization. Regarding low-cost care, one significant healthcare utilization change was outpatient, in-person visits being replaced by telemedicine [7]. There was a surge in telemedicine for cancer care during the Pandemic [7]. For COVID-19 patients with/without cancer, the majority of healthcare visits were telehealth encounters in the first 30 days of COVID-19 diagnosis [6]. Another significant healthcare utilization change was home-based cancer care developing beyond traditional practice to ensure continuity of care during the Pandemic (e.g., home-based intramuscular cancer therapy, remote monitoring) [8]. Remote monitoring was introduced as a necessity in cancer care during the COVID-19 outbreak [9]. Home rehabilitation in the early postoperative period has proven its effectiveness and has shown a reduction in hospital stays and postoperative complications [10].

Research findings on pandemic-related high-cost healthcare such as emergency department (ED) and inpatient utilization have been mixed depending on the population/chronic conditions studied. In the U.S., ED utilization fluctuated considerably, as observed with the 32% drop between 1 April and 31 June 2020 during the Pandemic [11]. The utilization of EDs remained low in late 2020 and throughout 2021 relative to previous years in California [12]. However, Eskander et al. found that although ED visits in the general population decreased substantially during the Pandemic, the rate of ED visits did not decrease among those receiving cancer-directed surgery [13]. During the Pandemic, many inpatient operations were modified in order to ensure enhanced protection and continued care for vulnerable immunocompromised cancer patients, such as the creation of an inpatient COVID-19 unit [14]. Manzono et al. also found that the mean length of inpatient stay observed among patients’ first COVID hospitalization was 11.2 days, and 24% of cancer patients with COVID-19 were admitted to the intensive care unit. The majority of cancer patients were discharged, with or without home health services [14].

Unfortunately, there have been limited studies on healthcare utilization (particularly low-cost outpatient and homecare at the national level) among cancer patients associated with COVID-19 diagnosis. The objective of this study was to understand healthcare utilization for cancer patients with/without COVID-19 diagnosis during the Pandemic. Specifically, the study examined differences in healthcare utilization (e.g., outpatient, inpatient, ED, and home healthcare) between 2020 and 2021 for cancer and/or COVID-19 patients. It is critical to evaluate healthcare utilization among cancer patients during the Pandemic. The findings can serve as a baseline to further refine strategies, and they can also be used to improve future low-cost cancer care quality improvement.

2. Materials and Methods

2.1. Data Sources

This study used the 2020–2021 Medical Expenditure Panel Survey (MEPS), which is a publicly available and nationally representative sample of the non-institutionalized U.S. civilian population [15]. The MEPS is the only national data source measuring how Americans use and pay for medical care, health insurance, and spending through annual surveys of individuals and families [15]. The overall weighted response rate for the survey was 27.6% in 2020 and 21.8% in 2021 [15]. The study is exempt from approval from the Institutional Review Board (IRB) due to the use of publicly available de-identified data.

2.2. Study Design

This study used the yearly MEPS household-consolidated data and medical condition files [16]. The household-consolidated data files provide estimates of respondents’ health conditions, social and demographic characteristics, use of medical care services, payments, and access to care. The classification of cancer and COVID-19 grouping is defined using the MEPS medical condition file [15]. Cancer (C00-D49) and COVID-19 diagnoses (U07) are classified according to the International Classification of Disease, 10th Revision (ICD-10). There were 56,141 (2020–2021) individuals with MEPS interviews completed nationally. There were 53,138 non-cancer patients (440 had COVID-19) and 3003 cancer patients (213 had COVID-19) (Figure 1).

The case group is individuals with cancer, with or without COVID-19. The reference group is individuals without cancer and without COVID-19. We further breakdown the case group to three groups based on cancer/COVID-19 health status (had COVID-19 without cancer, had cancer without COVID-19, had both cancer and COVID-19).

We used five outcome variables for healthcare utilization operationalized as high-cost and low-cost care. We included outpatient visits and home provider days to represent low-cost care, and ED visits, inpatient visits, and nights of inpatient stays to represent high-cost care [17]. An outpatient visit is defined as a count of visit made during the person’s reference period to a hospital outpatient department that provides health and medical services to individuals without requiring hospitalization overnight. The number of home provider days includes both formal (e.g., paid) and informal (e.g., unpaid) home provider days. Formal providers include home health agencies and other independent paid providers. Informal providers include family and friends that reside outside of the sampled person’s household [15]. High-cost ED or inpatient visits include the number of visits made during an individual’s reference period to a hospital emergency room or the number of inpatient stays, respectively. Inpatient nights of stay refer to the number of nights of inpatient hospital stay during the person’s reference period. Each of these variables was a discrete count variable representing the number of visits or days of healthcare utilization.

Healthcare utilization can be affected by other factors such as age, sex, race/ethnicity, poverty, insurance status, and geographical location of residence [18]. Covariates included social demographic factors. These factors included age groups (0–≤17, 18–≤49, 50–≤64, 65–≤79, ≥80), sex (male, female), ethnicity (Hispanic, non-Hispanic), race (white, Black, Others), insurance (any private, public only, and uninsured), poverty level (poor or earning less than 124% of the Federal Poverty Level (FPL), low income or 125–199% of the FPL, middle income or 200–399% of the FPL, high income or more than 400% of the FPL), and region (Northeast, Midwest, South, West). Statistics for the race category “others” were calculated by combining American Indian or Alaska native, Asian Native/Hawaiian/Pacific Islander, and Multi-racial participants. The MEPS provided the standard poverty variable. “Poor or less than 124% FPL” was a combination of negative poor (less than 100% FPL) and near poor (100–124% FPL) [19].

2.3. Statistical Analysis

We examined differences between selected baseline social demographic characteristics and COVID-19/cancer health status using frequency, mean, and chi-square tests when appropriate. Next, we conducted five multivariable Poisson regression analyses for each of the five discrete healthcare utilization outcome variables to assess differences in healthcare utilization based on different health statuses, adjusted for social demographic characteristics for the U.S. population. The results are presented as incidence rate ratios (IRRs). The IRR allows us to compare the incidence rate between two different groups. The IRR is an incidence rate among a case group divided by an incidence rate among a reference group. Multiple-year combinations, weighting, and data analysis are based on the MEPS guide to multiple-year estimates. We used Stata 17 to conduct the analyses and made a p-value of ≤0.05 the accepted level of statistical significance. The estimation procedures were adjusted by weight for the complex survey design [15].

3. Results

Table 1. Demographic characteristics of cancer and/or COVID-19 patients (weighted).

	Unweighted	Total Count	%	−Cancer/ −COVID 3 %	+COVID/ −Cancer 3 %	+Cancer/ −COVID 3 %	+Cancer/+COVID 3 %	p-Values 1
Total Count and (%)	-	329,897,345 (100%)		298,273,788 (90.41%)	15,443,002 (4.68%)	14,962,242 (4.54%)	1,218,313 (0.37%)
Total Count Unweighted	56,141	-		50,698	2440	2790	213
Cancer Status
Non-Cancer	53,138	313,716,790		95.1	4.9
Cancer	3003	16,180,555				92.5	7.5
Year								<0.001 ***
2020	27,805	164,272,648	49.8	50.4	37.9	52.4	31.4
2021	28,336	165,624,697	50.2	49.6	62.2	47.6	68.6
Age								<0.001 ***
0–≤17	11,936	75,537,491	22.9	24.5	14.2	2.0	1.8
18–≤49	20,747	134,646,337	40.8	42.0	48.5	11.3	16.0
50–≤64	11,174	63,027,437	19.1	18.7	22.7	23.8	28.3
65–≤79	7347	33,566,115	10.2	9.1	9.0	31.0	29.5
≥80	4937	23,119,966	7.0	5.8	5.6	31.9	24.4
Sex								0.002 **
Male	26,681	162,009,327	49.1	49.4	45.8	47.2	39.8
Female	29,460	167,888,018	50.9	50.6	54.2	52.8	60.2
Ethnicity								<0.001 ***
Hispanic	13,612	58,796,587	18.85	19.7	16.4	5.3	6.2
Non-Hispanic	42,529	239,477,201	81.15	80.3	83.6	94.7	93.8
Race								<0.001 ***
White only	42,127	224,012,242	76.2	75.1	80.0	91.67	92.7
Black only	8356	39,877,849	12.9	13.37	11.58	5.5	4.45
Others	5658	36,137,380
Insurance								<0.001 ***
Any Private	32,184	218,100,171	66.1	65.8	73.5	64.7	67.2
Public Only	19,675	91,003,022	27.6	27.5	22.2	35.0	31.8
Uninsured	4282	20,794,152	6.3	6.7	4.3	0.3	1.0
Region								0.066
Northeast	8656	55,542,258	17.0	16.8	18.7	18.2	20.6
Midwest	10,789	67,891,249	20.8	20.6	24.6	19.9	25.2
South	21,272	125,688,361	38.4	38.5	38.0	38.3	37.8
West	14,965	77,980,649	23.8	24.2	18.7	23.6	16.4
Poverty
Poor	12,483	50,853,239	15.4	15.9	12.0	10.4	10.7	<0.001 ***
Low	8083	40,442,943	12.3	12.4	10.8	10.8	4.7
Middle	15,475	93,439,540	28.3	28.4	29.7	24.9	25.6
High	20,100	145,161,623	44.0	43.3	47.5	53.9	59.0

Notes: ¹. p-value was calculated using Pearson’s chi-square. Statistically significant: * p < 0.05, ** p < 0.01, and *** p < 0.001. ³. ‘−’: without the condition. ‘+’: had the condition.

presents the descriptive values of the sample and the relationship between each of the population characteristics and cancer/COVID-19 health status. COVID-19 was found to be more prevalent among cancer patients (7.5% cancer vs. 4.9% non-cancer) using ratios and proportions.

COVID-19 and/or cancer prevalence between 2020 and 2021 also varied by age, gender, race, ethnicity, insurance, and poverty status (p < 0.001). From a categorical Pearson chi-square test, statistically significant differences are seen in all categories except region.

Females had more COVID-19 infections in both the cancer and non-cancer groups (p = 0.002). Cancer patients aged 50 and above had significantly more COVID-19 infections (24.4–29.5% for age 50 and above versus 16% for age 18–49). On the contrary, individuals aged 18–49 without cancer had more COIVD-19 infections (48% for age 18–49 vs. 5.6–22.7% for age above 50). The cancer group, regardless of COVID-19, had a higher proportion of non-Hispanic, white race, publicly insured, and higher-income-level patients. The year 2021 had significantly more COVID-19 diagnoses compared to the year 2020, especially for cancer patients (62.2% 2021 vs. 37.9% 2020 among non-cancer group; 68.6% 2021 vs. 31.4% 2020 among cancer group) (p < 0.001). Regions were similar with regard to COVID-19/cancer status.

Next,

Table 2. Mean and multivariable Poisson regression results for low-cost healthcare utilization in 2020–2021 for cancer and/or COVID-19 patients (weighted).

	Outpatient Visits 1		Home Provider Days 1
	Mean (95%CI)	p-Values 2	Mean (95%CI)	p-Values 2
−COVID/−Cancer 3	9.3 (8.97–9.64)	<0.001 ***	2.67 (2.29–3.05)	<0.001 ***
+COVID/−Cancer 3	14.78 (13.73–15.83)		2.25 (1.5–3.01)
+Cancer/−COVID 3	27.88 (26.47–29.3)		6.18 (4.41–7.94)
+Cancer/+COVID 3	30.6 (26.44–34.77)		3.07 (0.66–5.48)
	Incidence Rate Ratios 4		Incidence Rate Ratios 4
	Reference (−COVID/−Cancer)
+COVID/−Cancer 3	1.47 (1.36–1.59)	<0.001 ***	0.88 (0.63–1.24)	0.479
+Cancer/−COVID 3	1.86 (1.75–1.97)	<0.001 ***	1.01 (0.75–1.37)	0.910
+Cancer/+COVID 3	2.09 (1.80–2.42)	<0.001 ***	0.63 (0.30–1.34)	0.244

Notes: ¹ The regression results were adjusted by covariates. The p-value was calculated using Pearson’s chi-square. ² Statistically significant: * p < 0.05, ** p < 0.01, and *** p < 0.001. ³ ‘−’: without the condition. ‘+’: had the condition. ⁴ The incidence rate ratio (IRR) allows us to compare the incident rate between two different groups. IRR = incidence rate among case group/incidence rate among control/reference group. The case group are individuals with (1) COVID-19 without cancer, (2) cancer without COVID-19, or (3) both cancer and COVID-19. The control/reference group are individuals without cancer and without COVID-19. IRR equal to 1 indicates that the incidence rate is the same in the case group and the reference group. IRR less than 1 indicates that the incidence rate is lower in the case group compared to the reference group. IRR greater than 1 indicates that the incidence rate is higher in the case group compared to the reference group.

shows statistically significant differences with regard to mean visits among COVID-19 and/or cancer patients. The mean outpatient visits vary by health status (30.6, 27.9, 14.78, and 9.3, visits respectively, for individuals with both cancer and COVID-19, cancer without COVID-19, COVID-19 without cancer, and without cancer/COVID-19). The mean home provider days were higher for cancer patients compared to non-cancer patients (3.07–8.18 visits for cancer patients vs. 2.25–2.67 visits for non-cancer patients, p < 0.001), while cancer patients with COVID-19 used less home-based healthcare compared to cancer patients without COVID-19 (6.18 visits for cancer patients without COVID-19 vs. 3.07 visits for cancer patients with COVID-19 p < 0.001). Regarding high-cost care, COVID-19 patients used statistically significantly more high-cost care related to EDs and inpatient visits, including discharges or nights in hospital stays, especially for cancer patients with COVID-19 (p < 0.001).

Table 2 presents the different cancer/COVID-19 health statuses and their association with healthcare utilization adjusted for social demographic characteristics using a multivariable Poisson regression. Table 2 and Figure 2 show that outpatient visits were moderated by cancer and COVID-19 diagnosis (47% higher for individuals with COVID-19 without cancer, 86% higher for individuals with cancer without COVID-19, 109% higher for individuals with both cancer and COVID-19, p < 0.001). There were no statistically significant differences in home provider days among the four groups.

Regarding high-cost care,

Table 3. Mean and multivariable Poisson regression results for high-cost healthcare utilization in 2020–2021 for cancer and/or COVID-19 patients (weighted).

	ED Visits 1		Inpatient Visits 1		Inpatient Night of Stay 1
	Mean (95%CI)	p-Values 2	Mean (95%CI)	p-Values 2	Mean	p-Values 2
−COVID/−Cancer 3	0.15 (0.14–0.16)	<0.001 ***	0.06 (0.06–0.07)	<0.001 ***	0.31 (0.28–0.35)	<0.001 ***
+COVID/−Cancer 3	0.38 (0.34–0.43)		0.17 (0.14–0.20)		1.23 (0.92–1.53)
+Cancer/−COVID 3	0.28 (0.24–0.31)		0.18 (0.16–0.20)		0.9 (0.69–1.11)
+Cancer/+COVID 3	0.66 (0.37–0.96)		0.30 (0.21–0.39)		2.05 (1.03–3.06)
	Incidence Rate Ratios 4	p-values 2	Incidence Rate Ratios 4	p-values 2	Incidence Rate Ratios 4	p-values 2
	Reference (−COVID/−Cancer)
+COVID/−Cancer 3	2.51 (2.23–2.82)	<0.001 ***	2.41 (2.05–2.83)	<0.001 ***	3.68 (2.77–4.89)	<0.001 ***
+Cancer/−COVID 3	1.28 (1.12–1.46)	<0.001 ***	1.33 (1.14–1.57)	<0.001 ***	1.27 (0.93–1.74)	0.125
+Cancer/+COVID 3	3.45 (2.21–5.36)	<0.001 ***	2.70 (1.94–3.74)	<0.001 ***	3.59 (2.10–6.15)	<0.001 ***

Notes: ¹ The regression results were adjusted by covariates. The p-value was calculated using Pearson’s chi-square. ² Statistically significant: * p < 0.05, ** p < 0.01, and *** p < 0.001. ³ ‘−’: without the condition. ‘+’: had the condition. ⁴ The incidence rate ratio (IRR) allows us to compare the incidence rate between two different groups. IRR = incidence rate among case group/incidence rate among control/reference group. The case group are individuals with (1) COVID-19 without cancer, (2) cancer without COVID-19, or (3) both cancer and COVID-19. The control/reference group are individuals without cancer and without COVID-19. IRR equal to 1 indicates that the incidence rate is the same in the case group and the reference group. IRR less than 1 indicates that the incidence rate is lower in the case group compared to the reference group. IRR greater than 1 indicates that the incidence rate is higher in the case group compared to the reference group.

and Figure 2 demonstrate that cancer patients with COVID-19 had the highest and most statistically significant increases in high-cost care, including 245% more ED visits (IRR = 3.45, p < 0.001), a 170% higher number of inpatient visits (IRR = 2.70, p < 0.001), and 268% more inpatient nights of stay (IRR = 3.68, p < 0.001) when compared to individuals without cancer and without COVID-19. Cancer patients without COVID-19 also had statistically significant increases in high-cost care, including 28% more ED visits (IRR = 1.28, p < 0.001), a 33% higher number of inpatient visits (IRR = 1.33, p < 0.001), and a 27% higher number of inpatient nights of stay (IRR = 1.27, p < 0.001) when compared to individuals without cancer and without COVID-19.

Overall, we found that the types of healthcare utilization for cancer patients, including outpatient visits, ED visits, and inpatient visits/length of inpatient stay, were all higher except home-based care visits when compared to individuals without cancer and COVID-19. Cancer patients had a higher proportion of non-Hispanic, white race, publicly insured, and higher-income-level patients.

4. Discussion

Our study provided evidence on overall healthcare utilization at a national level for individuals with cancer and/or COVID-19 during the Pandemic by using population-based data to quantify low- and high-cost healthcare utilization. Previous research has lacked studies evaluating COVID-19’s impact on overall healthcare utilization with consideration of both high- and low-cost care, including outpatient, home, ED, and inpatient healthcare [9,11,14,20,21,22,23]; cancer patient studies [24]; and U.S. studies [8,9,10,13,22], and few studies have used early-stage data sources from the Pandemic [8,21] or local/regional U.S. data [12,14,20].

Regarding low-cost outpatient care, COVID-19 and/or cancer patients seek more low-cost outpatient care than individuals without cancer to continue cancer treatment or necessary COVID-19 treatment [25]. Increased outpatient visits may also be due to canceled inpatient surgeries or inpatient surgery being changed to an outpatient setting early on or during the Pandemic [22,23]. It is likely that some outpatient visits offered telemedicine during the Pandemic to avoid COVID-19 infection for cancer patients. These conversions were more common in patients whose surgery, radiotherapy, chemotherapy, and injection chemotherapy treatments were canceled or postponed [26].

Differing from previous findings that cancer patients utilize more home-based care than non-cancer patients, cancer patients with/without COVID-19 did not show a statistically significant difference in utilizing home-based care, while there were increases in all other types of healthcare utilization. There were multiple reasons for this related to reduced homecare provider days—mainly due to the Pandemic—such as shortages of home healthcare professionals and a combination of considerations for the temporary delay of a cancer treatment or risk of COVID-19 infection for patients, caregivers, and healthcare professionals. Additionally, payment model restrictions and a lack of skilled homecare professionals may have limited complex cancer treatment, especially some innovative home-based cancer treatments. Home-based cancer care developed beyond traditional practice to ensure continuity of care during the COVID-19 pandemic (e.g., home cancer screening, home-based intramuscular cancer therapy, remote monitoring, home rehabilitation post-certain surgeries, palliative care) [8,9,10]. However, there are challenges to implementing low-cost homecare, such as a fragmented healthcare system, lack of payment model support, lack of skilled homecare staff, and geographical differences [27,28,29]. It is important for healthcare policy makers, leaders, and providers to understand the available innovative low-cost care developed during the Pandemic and to understand the barriers to implementing and improving low-cost cancer care. These include the need for better organized care and resources during the COVID-19 post-pandemic to minimize high-cost care and improve low-cost outpatient and home-based care through improving care coordination, supporting necessary telemedicine and homecare workforce and payment models, and adapting innovative low-cost cancer care methods from the Pandemic. The Pandemic has changed the delivery of healthcare in the U.S., especially low-cost outpatient and home-based care. Despite some limitations in telemedicine for clinicians (e.g., challenges in physician examination dealing with regulation changes) and patients (e.g., dealing with technology, privacy concerns) [30], telemedicine has been proven to meet healthcare needs and improve the efficiency and delivery of cancer care, especially during the Pandemic [25]. Also, telemedicine can help reduce healthcare costs and help cancer patients in remote areas (e.g., rural patients) receive optimal care.

Similarly to other studies, we found that high-cost care from 2020 to 2021 was mostly focused on COVID-19 patients regardless of cancer diagnosis, including ED healthcare, inpatient visits, and nights of inpatient stay [24]. Despite overall reduced ED and inpatient visits, patients with severe conditions such as COVID-19 and cancer patients had to seek necessary life-sustaining treatment [24].

Individuals without COVID-19 diagnoses, including both cancer patients and non-cancer patients, had less overall healthcare utilization. Healthcare utilization may have been impacted by factors such as patients’ anxieties, worries, and reduced social support due to social distancing and the shortage of healthcare professionals [31]. This may indicate potential delayed healthcare for existing cancer patients represented by (1) cancer patients without COVID-19, who were significantly less likely to use healthcare across all categories, and (2) cancer patients with COVID-19, who were less likely to receive homecare. These problems, if left unaddressed, may increase cancer morbidity and mortality for years to come [32].

Similarly to other studies, our study also found that the majority of cancer patients were female and 55 years or older. Those with non-Hispanic ethnicity and white patients had more cancer and/or COVID-19 diagnoses. Cancer patients had more public insurance and higher income levels. Due to the relatively small sample of cancer patients who were Hispanic or African American, future studies would benefit from understanding COVID-19’s impacts on other races/ethnicities such as Hispanics or African Americans.

There were several limitations to our study. First, the MEPS response rates were much lower during the 2020–2021 Pandemic period. Second, the study included patient-reported survey data, COVID-19/cancer diagnoses that were not verified by physicians, and limited information on the severity of COVID-19/cancer. Third, there were no available state-level data. Fourth, we do not have data to distinguish between telemedicine or in-person outpatient visits. Nonetheless, this study presented unique and additional insights beyond previously published studies. Our study was able to examine multiple outcomes of healthcare utilization using the number of visits or days that healthcare was utilized and a COVID-19/cancer health status comparison at a national population level during the health service interruption.

The results of the retrospective study showed that cancer patients had no differences in home-based utilization, although they had higher outpatient, ED, and inpatient utilization rates when compared to individuals without cancer and without COVID-19. These findings highlight the importance of improving low-cost care, especially low-cost home-based care, for cancer patients. Healthcare policy makers, leaders, and providers may need to understand, be aware, and consider improving low-cost home-based care and overcoming barriers such as the fragmented healthcare system, the lack of payment model support, the lack of care coordination during outpatient or primary care, and the lack of skilled homecare staff. These findings are applicable to current healthcare management due to the continued impact of COVID-19 and other infectious agents on cancer patients and the need for preparedness for future healthcare interruptions. Understanding the needs of cancer patients could also help understand and improve healthcare for many other patients with chronic conditions. Policy makers could consider improving payment models and training skilled homecare professionals to support innovative homecare methods that were developed during the Pandemic. Healthcare managers can also support care coordination efforts between outpatient, home, ED, and inpatient healthcare to minimize high-cost care. More research is warranted, with a focus on developing low-cost care models, such as improving care coordination, supporting necessary telemedicine, training the homecare workforce, improving homecare payment models, and identifying and adopting innovative low-cost cancer care.

5. Conclusions

Improving and adopting innovative low-cost home-based healthcare utilization are critical to reduce future healthcare spending and strengthen pandemic preparedness.