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Self-Reported Unmet Healthcare Needs due to COVID-19 Pandemic and Emergency Services Use and Hospitalization among Cancer Survivors

Open AccessPublished:January 17, 2023DOI:https://doi.org/10.1016/j.focus.2023.100065

      Highlights

      • The COVID-19 pandemic has significantly disrupted healthcare delivery.
      • In 2020, 33.7% US cancer survivors reported unmet healthcare needs due to COVID-19.
      • Cancer survivors with unmet needs were 31% more likely to use emergency services.
      • Future studies should examine long-term effects of the pandemic on cancer care.

      Abstract

      Introduction

      The COVID-19 pandemic has significantly disrupted the entire healthcare system, resulting in unmet needs for medical care (e.g., delayed or forgone care) among patients with cancer.

      Materials and Methods

      Using 2020 National Health Interview Survey data, we examined the prevalence of unmet healthcare needs and whether having delayed or forgone healthcare experience is associated with increased emergency services use and hospitalizations. A multivariable logistic regression model was used to assess the associations between unmet healthcare needs due to COVID-19 and emergency services use and hospitalization, controlling for potential confounding. All analysis was conducted in March and April 2022.

      Results

      Among 2,386 study participants living with cancer (representing 25.6 million US adults), 33.7% reported having unmet healthcare needs due to COVID-19. The prevalence of unmet healthcare needs was higher among younger cancer survivors and those with higher education. In adjusted analysis, cancer survivors with unmet healthcare needs were 31% more likely to report any emergency services use (adjusted OR 1.31, 95% CI: 1.05-1.65) than those without. Having unmet healthcare needs was not significantly associated with hospitalization (P=0.465).

      Conclusions

      Our findings highlight the unmet need for cancer care due to the pandemic and potential adverse health outcomes.

      Keywords

      INTRODUCTION

      To date, many studies have documented delays or disruptions of healthcare access during the COVID-19 pandemic,1-3 but have not examined how this has affected emergency department (ED) visits and hospitalizations among cancer survivors. Cancer survivors with unmet healthcare needs—such as poorly managed symptoms or inappropriate distress management —are more likely to have unnecessary hospitalizations and ED visits.4,5 Using nationally representative survey data, we examined the prevalence of unmet healthcare needs among cancer survivors during the COVID-19 pandemic and how these unmet needs were associated with emergency health services use and hospitalization in the US.

      METHODS

      We conducted a cross-sectional study using the 2020 National Health Interview Survey (NHIS) data. The study sample included US adults ages 18 years or older with a self-reported diagnosis of any cancer (N=2,386; representing 25.6 million). Unmet healthcare needs were identified by the self-reported experience of having delayed or forgone needed medical care due to the COVID-19 pandemic; this was a summative assessment of all medical care types (e.g., annual checkup, follow-up visit, treatment) during the pandemic. Study outcomes included 1) any emergency services use and 2) overnight hospitalization of any cause.
      Wald chi-square test adjusted for survey design was used to compare the baseline characteristics of cancer survivors by unmet healthcare needs status based on the difference between observed and expected weighted cell frequencies.6 Sample baseline characteristics included (1) sociodemographic data: age, sex, race and ethnicity, education, family income, census region, urbanization, and insurance type and (2) clinical characteristics: the number of comorbidities, COVID history, and cancer treatment status. Multivariable logistic regression models were used to assess the associations between binary variables of unmet needs status and emergency services use and hospitalization, controlling for potential confounding factors. Confounding factors of healthcare access include cancer type, active treatment status, age, sex, race/ethnicity, education, family income, census region, residence urbanicity, insurance, COVID-19 status, and comorbidity. We reported the odds ratio (OR) and corresponding 95% confidence intervals (CI). All analyses were conducted using SAS 9.4 (Cary, NC) in March 2022 and accounted for the complex survey design. This study was deemed exempt from review by the University of Florida Institutional Review Board because we used deidentified, publicly available data. This study adhered to the JBI critical appraisal checklist for cross-sectional studies.

      RESULTS

      Among 2,386 respondents (weighted, 25.6 million) included in the study, 33.7% (weighted %) reported having unmet healthcare needs due to COVID-19. Prevalence of unmet healthcare needs was higher among cancer survivors in ages 18-49 (40.7% [95% CI, 31.8-49.7] vs. 24.6% [95% CI, 21.2-28.0] in ages 75+) and those in college graduates (41.0% [95% CI, 37.2-44.8] vs. 28.0% [95% CI, 23.0-33.0] in high school graduates). There were no significant differences in unmet healthcare needs by other socioeconomic characteristics (Table 1).
      Table 1Prevalence of Unmet Need for Care by Characteristics of Cancer Survivors in the U.S.: NHIS 2020a
      Unmet Need for CarebAdjusted Odds of Unmet Needc

      (95% CI)
      Sample

      n
      Weighted

      N
      Yes, %

      95% CI
      No, %

      95% CI
      P
      Age Group<.001
      18-49220363816940.7 (31.8-49.7)59.3 (50.3-68.2)Ref
      50-64563669772039.3 (34.0-44.5)60.7 (55.5-66.0)0.87 (0.57-1.35)
      65-74743700790034.3 (30.4-38.2)65.7 (61.8-69.6)0.64 (0.42-0.98)
      ≥75860725252824.6 (21.2-28.0)75.4 (72.0-78.8)0.40 (0.26-0.63)
      Sex0.272
      Male9861066436332.2 (28.3-36.0)67.8 (64.0-71.7)Ref
      Female14001393195535.0 (31.7-38.2)65.0 (61.8-68.3)1.12 (0.89-1.41)
      Race/Ethnicity0.468
      NH white20822034261633.1 (30.6-35.7)66.9 (64.3-69.4)Ref
      NH black133169601530.0 (20.4-39.6)70.0 (60.4-79.6)0.87 (0.51-1.48)
      Hispanic101162550841.1 (26.4-55.9)58.9 (44.1-73.6)1.14 (0.64-2.03)
      Other7093218041.3 (26.8-55.8)58.7 (44.2-73.2)1.31 (0.71-2.44)
      Education<.001
      Less high school202323913831.3 (21.7-40.9)68.7 (59.1-78.3)Ref
      High school graduate520666292928.0 (23.0-33.0)72.0 (67.0-77.0)0.91 (0.55-1.50)
      Some college/associate709702429332.4 (28.1-36.7)67.6 (63.3-71.9)1.05 (0.66-1.68)
      College graduate955766995841.0 (37.2-44.8)59.0 (55.2-62.8)1.65 (1.01-2.74)
      Family Income Level0.692
      >400% FPL11171109420134.9 (31.4-38.5)65.1 (61.5-68.6)Ref
      200%-400% FPL703720266632.9 (28.3-37.4)67.1 (62.6-71.7)0.79 (0.55-1.13)
      <200% FPL566629944932.6 (27.0-38.3)67.4 (61.7-73.0)0.78 (0.55-1.10)
      Census Region0.1251.01 (0.69-1.49)
      Northeast426440018336.9 (29.6-44.2)63.1 (55.8-70.4)Ref
      Midwest575543699231.3 (26.9-35.7)68.7 (64.3-73.1)0.79 (0.55-1.13)
      South830974511531.3 (27.3-35.3)68.7 (64.7-72.7)0.78 (0.55-1.10)
      West555501402838.4 (32.8-44.0)61.6 (56.0-67.2)1.01 (0.69-1.49)
      Level of Urbanization0.375
      Large central metro567608190936.5 (31.4-41.6)63.5 (58.4-68.6)Ref
      Large fringe metro565618818634.2 (28.4-40.1)65.8 (59.9-71.6)0.98 (0.70-1.37)
      Medium/small metro825799591233.5 (29.5-37.5)66.5 (62.5-70.5)0.98 (0.73-1.32)
      Nonmetropolitan429433031029.6 (24.0-35.3)70.4 (64.7-76.0)0.90 (0.62-1.31)
      Insurance Coverage0.775
      Private12911354742034.4 (31.1-37.7)65.6 (62.3-68.9)Ref
      Public and other10411001402833.3 (29.4-37.1)66.7 (62.9-70.6)1.18 (0.91-1.53)
      No54103486929.8 (15.2-44.3)70.2 (55.7-84.8)0.78 (0.36-1.70)
      Number of Other Chronic Conditions0.594
      0724776799232.0 (27.7-36.3)68.0 (63.7-72.3)Ref
      1859880751835.1 (30.6-39.6)64.9 (60.4-69.4)1.30 (0.99-1.72)
      ≥2803802080734.0 (29.9-38.1)66.0 (61.9-70.1)1.44 (1.07-1.95)
      COVID-19 Status0.146
      Tested and positive5267453749.5 (30.4-68.5)50.5 (31.5-69.6)1.65 (0.76-3.60)
      Tested and negative671683716035.7 (31.5-40.0)64.3 (60.0-68.5)1.05 (0.83-1.33)
      Never tested16631708462132.3 (29.3-35.4)67.7 (64.6-70.7)Ref
      Cancer Site0.101
      Female breast429409188327.0 (21.8-32.2)73.0 (67.8-78.2)NA c
      Prostate297293743730.7 (24.7-36.7)69.3 (63.3-75.3)NA c
      Melanoma110117471038.6 (27.1-50.1)61.4 (49.9-72.9)NA c
      Colorectal96117891236.5 (20.0-53.1)63.5 (46.9-80.0)NA c
      Hematologic8386480830.0 (18.2-41.8)70.0 (58.2-81.8)NA c
      Short-survival cancers e116115760131.3 (21.4-41.2)68.7 (58.8-78.6)NA c
      All other12551319096736.3 (32.7-39.9)63.7 (60.1-67.3)NA c
      Cancer Treatment Status f0.741
      In Treatment287298654133.6 (30.8-36.4)66.4 (63.6-69.2)1.00 (0.71-1.41)
      Not in Treatment20992160977734.8 (28.1-41.5)65.2 (58.5-71.9)Ref
      Abbreviations: NHIS, National Health Interview Survey; CI, Confidence Interval; NH, Non-Hispanic; FPL, Federal Poverty Level; Ref, Reference.
      a The final sample adult response rate was 48.9%.
      b Unmet need for care was classified as “yes” if respondents answered “yes” to either of the two questions, “no” unmet need if “no” to both items: 1) Was there any time when you delayed getting medical care because of the coronavirus pandemic? 2) Was there any time when you needed medical care for something other than coronavirus, but did not get it because of the coronavirus pandemic?
      c Adjusted for age, sex, race/ethnicity, education, family income, census region, level of urbanization, insurance type, the number of comorbidities, COVID history, and cancer treatment status.
      d Cancer site was not included in multivariable analysis due to sex-specific cancers such as breast and prostate and small cell size issue.
      e Included cancers with a relatively short survival time (esophagus, liver, lung, pancreas, and stomach)
      f Cancer treatment including surgery, radiation therapy, chemotherapy, bone marrow transplants, stem cell transplants, or hormone therapy since the start of the pandemic.
      Odds ratios (ORs) are interpreted as a change in odds of emergency services use and hospitalization associated with having any unmet healthcare need. An OR greater than 1 would indicate that cancer survivors with unmet needs were more likely to have emergency services use or hospitalization compared to those without, while an OR less than 1 indicates that they would be less likely.
      In adjusted logistic regression analyses (Table 2) reporting associations between the unmet healthcare needs and emergency services use or hospitalization, cancer survivors with unmet healthcare needs were 31% more likely to report any emergency services use (OR:1.31, 95% CI=1.05-1.65) than those without unmet needs. Having unmet healthcare needs was not significantly associated with hospitalization (OR=0.87, 95% CI=0.60-1.26).
      Table 2Association between Having Unmet Need for Care and Emergency Service Use and Hospitalization.
      Unmet Need for CareAdjusted Odds Ratio (95% CI)
      Adjusted for age, sex, race/ethnicity, education, family income, census region, level of urbanization, insurance type, comorbidity, COVID history, and cancer treatment status. Odds ratios (ORs) are interpreted as a change in odds of emergency services use and hospitalization associated with having any unmet healthcare need. An OR greater than 1 would indicate that cancer survivors with unmet needs were more likely to have emergency services use or hospitalization compared to those without, while an OR less than 1 indicates that they would be less likely.


      Having Unmet Need vs. Not (Reference)
      Yes, %

      95% CI
      No, %

      95% CI
      P
      Any emergency services use44.9 (40.0-49.8)36.9 (34.1-39.8)0.0051.31 (1.05-1.65)
      Any Hospitalization13.4 (10.2-16.5)14.8 (12.5-17.1)0.4720.87 (0.60-1.26)
      Abbreviations: ED, Emergency Department; CI, Confidence Interval.
      a Adjusted for age, sex, race/ethnicity, education, family income, census region, level of urbanization, insurance type, comorbidity, COVID history, and cancer treatment status. Odds ratios (ORs) are interpreted as a change in odds of emergency services use and hospitalization associated with having any unmet healthcare need. An OR greater than 1 would indicate that cancer survivors with unmet needs were more likely to have emergency services use or hospitalization compared to those without, while an OR less than 1 indicates that they would be less likely.

      DISCUSSION

      Per the NHIS 202, one-third of cancer survivors in the U.S. reported unmet healthcare needs due to the COVID-19 pandemic. Cancer survivors with unmet healthcare needs were 31% more likely to have emergency services use, compared with those without unmet needs. These findings highlight unmet needs for healthcare and potential adverse health outcomes among cancer survivors during the pandemic. Prior research suggests poorly managed symptoms or psychological distress are associated with emergency department utilization among cancer survivors.4,5 Further studies should test strategies for aiding cancer survivors with symptom management and psychosocial care in the lack of in-person visits (e.g., remote monitoring).8 To accommodate patients’ ongoing medical needs during the pandemic with limited medical resources, it also requires both providers and payers to adjust health care delivery approaches and payment policies (i.e., expanding coverage for telehealth services) efficiently based on the rapid change in the environment such as lockdowns, fluctuations of the COVID-19 cases, and local vaccination rates.9

      Limitations

      Our results may emphasize the value of emergency preparedness and resource allocation to maximally avoid healthcare disruption in properly responding to another pandemic or similar catastrophic events. Future research, therefore, will be necessary to identify effective and cost-effective alternative healthcare delivery approaches.
      Limitations of this study include cross-sectional design and the use of self-reported information, which cannot measure the temporal relation and is prone to recall bias, respectively. Furthermore, we were not able to determine the type of health services cancer survivors needed in the NHIS data. Lastly, we did not include forgone or delayed care due to financial reasons, which may underestimate the unmet healthcare needs during the economic downturn since the pandemic.

      CONCLUSIONS

      One-third (33.7%) of cancer survivors in the U.S. reported unmet needs for healthcare during the COVID-19 pandemic, and having this experience was associated with an increased likelihood of emergency services use. Our findings highlight unmet needs for healthcare and potential adverse health outcomes among cancer survivors during the pandemic. Future studies are needed to further investigate the impact of delayed or forgone care and the long-term effect of the pandemic on cancer survivorship.
      Credit Author Statement
      • Young-Rock Hong: Conceptualization, Methodology, Formal analysis, Data Curation, Investigation, Resources, Writing - Original Draft, Writing - Review & Editing, Visualization, Project administration
      • Zhigang Xie: Conceptualization, Methodology, Investigation, Formal analysis, Data Curation, Investigation, Writing - Review & Editing
      • Juhan Lee: Investigation, Writing - Review & Editing, Data Curation
      • Kea Turner: Conceptualization, Methodology, Investigation, Writing - Review & Editing
      • Ryan Suk: Conceptualization, Methodology, Investigation, Writing - Review & Editing, Supervision
      All authors reviewed the results and approved the final version of the manuscript.
      Declaration of interests
      The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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      CRediT authorship contribution statement

      Young-Rock Hong: Conceptualization, Methodology, Formal analysis, Data curation, Investigation, Resources, Writing – original draft, Writing – review & editing, Visualization, Project administration. Zhigang Xie: Conceptualization, Methodology, Investigation, Formal analysis, Data curation, Investigation, Writing – review & editing. Juhan Lee: Investigation, Writing – review & editing, Data curation. Kea Turner: Conceptualization, Methodology, Investigation, Writing – review & editing. Ryan Suk: Conceptualization, Methodology, Investigation, Writing – review & editing, Supervision.