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The First Year of the COVID-19 Pandemic: Changes in Preventive Services in Community Health Centers

Published:October 12, 2022DOI:https://doi.org/10.1016/j.amepre.2022.08.023

      Introduction

      Community Health Centers provide comprehensive primary healthcare services to many underserved populations. It is unknown how routine preventive and chronic care services in Community Health Centers may have changed nationwide during the COVID-19 pandemic.

      Methods

      The 2014–2020 Health Resources and Services Administration Uniform Data System of Community Health Centers was used, and data analysis was conducted from November 2021 to May 2022. Data for clinical quality measures in 2020 were treated as during the pandemic, whereas receipt of care in 2019 and before were treated as before the pandemic. Outcomes included 6 clinical quality measures of being up to date for colorectal cancer screening, cervical cancer screening, tobacco screening and cessation counseling, BMI screening and follow-up, depression screening and follow-up, and aspirin use for ischemic vascular disease. A mixed effects regression model was used to estimate changes in measures by year.

      Results

      Between 2019 and 2020, receipt of preventive services declined for each of the 6 clinical quality measures: from 40.8% to 37.7% for colorectal cancer screening, from 48.8% to 44.9% for cervical cancer screening, from 85.8% to 83.4% for tobacco screening and cessation counseling, from 70.7% to 65.4% for BMI screening and follow-up, from 71.1% to 64.9% for depression screening and follow-up, and from 81.5% to 79.4% for aspirin use for ischemic vascular disease.

      Conclusions

      Receipt of preventive services in Community Health Centers declined during the COVID-19 pandemic for each of the 6 clinical quality measures considered in the study. Immediate action is required to support ongoing high-quality, primary healthcare services in Community Health Centers across the nation.

      INTRODUCTION

      Community Health Centers (CHCs) play an important role in providing comprehensive primary healthcare services, including preventive and chronic care, to underserved populations, many of whom are uninsured.
      • Adashi EY
      • Geiger HJ
      • Fine MD.
      Health care reform and primary care–the growing importance of the community health center.
      ,
      • Cole MB
      • Wright B
      • Wilson IB
      • Galárraga O
      • Trivedi AN.
      Medicaid expansion and community health centers: care quality and service use increased for rural patients.
      Evidence of changes in preventive care among CHCs during the coronavirus disease 2019 (COVID-19) pandemic is limited. According to a small-scale study, approximately 50%–90% of CHCs stopped offering colorectal cancer screening and cervical cancer screening, respectively, during the pandemic.
      • Fisher-Borne M
      • Isher-Witt J
      • Comstock S
      • Perkins RB.
      Understanding COVID-19 impact on cervical, breast, and colorectal cancer screening among federally qualified healthcare centers participating in “Back on track with screening” quality improvement projects.
      Another study based on data from 36 CHCs across 19 states also found pandemic-related gaps in combined visit volumes for cervical cancer screening, depression screening and follow-up, and adult weight assessment despite increases in telehealth visits during this time.
      • Simon J
      • Mohanty N
      • Masinter L
      • Hamilton A
      • Jain A.
      COVID-19: exploring the repercussions on federally qualified health center service delivery and quality.
      Declines in care delivery reported among CHCs are consistent with a cumulative 9.1% decline in outpatient care visits among commercial- and Medicare Advantage‒insured persons between January and June 2020 before, during, and after the Centers for Medicare and Medicaid Services issued guidance to delay all nonurgent visits owing to the COVID-19 pandemic in March 2020.
      • Issaka RB
      • Somsouk M.
      Colorectal cancer screening and prevention in the COVID-19 era.
      ,
      • Patel SY
      • Mehrotra A
      • Huskamp HA
      • Uscher-Pines L
      • Ganguli I
      • Barnett ML.
      Trends in outpatient care delivery and telemedicine during the COVID-19 pandemic in the U.S.
      Yet, no previous study has examined the association of the COVID-19 pandemic and multiple preventive and chronic care services among CHCs nationwide.
      It is imperative to consider the effect of the COVID-19 pandemic on routine preventive and chronic care services within CHCs nationwide because findings will have important implications for long-term health outcomes among vulnerable populations served. Using data from a nationwide sample of CHCs, this study assessed changes during the first year of the COVID-19 pandemic in the provision of preventive care and chronic disease management through clinical quality measures that serve as proxies for long-term health outcomes.

      Procedure manual. U.S. Preventive Services Task Force.https://uspreventiveservicestaskforce.org/uspstf/about-uspstf/methods-and-processes/procedure-manual. Updated August, 2022. Accessed July 1, 2022.

      ,

      Uniform Data System (UDS) training and technical assistance, 2021, Health Resources and Services Administration https://bphc.hrsa.gov/datareporting/reporting/index.html. Updated October 3, 2022. Accessed July 1, 2022

      METHODS

      Data for this cross-sectional study were obtained from the 2014 to 2020 Health Resources and Services Administration Uniform Data System (UDS) as reported nationwide by each CHC that received federal funds under the Health Center Programs authorized through Section 330 of the Public Health Service Act.

      Uniform Data System (UDS) training and technical assistance, 2021, Health Resources and Services Administration https://bphc.hrsa.gov/datareporting/reporting/index.html. Updated October 3, 2022. Accessed July 1, 2022

      CHCs located in U.S. Territories were excluded from the analysis. The UDS provides information on demographic, clinical, operational, and financial data per CHC. From 2014 to 2020, between 1,278 and 1,385, CHCs were included, serving 22‒29 million patients each year. UDS data are publicly available, deidentified, and ecologic in nature (aggregated at the CHC organization level).

      Study Sample

      The UDS collects data on 15 clinical quality measures that reflect services identified by the U.S. Preventive Services Task Forces with high certainty that their net health benefit is substantial or moderate to substantial and therefore can serve as a proxy for long-term health outcomes.

      Procedure manual. U.S. Preventive Services Task Force.https://uspreventiveservicestaskforce.org/uspstf/about-uspstf/methods-and-processes/procedure-manual. Updated August, 2022. Accessed July 1, 2022.

      Uniform Data System (UDS) training and technical assistance, 2021, Health Resources and Services Administration https://bphc.hrsa.gov/datareporting/reporting/index.html. Updated October 3, 2022. Accessed July 1, 2022

      • Davidson KW
      • Barry MJ
      U.S. Preventive Services Task Force
      Screening for colorectal cancer: U.S. Preventive Services Task Force recommendation statement [published correction appears in JAMA. 2021;326(8):773].
      • Curry SJ
      • Krist AH
      U.S. Preventive Services Task Force
      Screening for cervical cancer: U.S. Preventive Services Task Force recommendation statement.
      • Krist AH
      • Davidson KW
      U.S. Preventive Services Task Force
      Interventions for tobacco smoking cessation in adults, including pregnant persons: U.S. Preventive Services Task Force recommendation statement.
      • Curry SJ
      • Krist AH
      U.S. Preventive Services Task Force
      Behavioral weight loss interventions to prevent obesity-related morbidity and mortality in adults: U.S. Preventive Services Task Force recommendation statement.
      • Siu AL
      • Bibbins-Domingo K
      U.S. Preventive Services Task Force (USPSTF)
      Screening for depression in adults: U.S. Preventive Services Task Force recommendation statement.
      • Davidson KW
      • Barry MJ
      U.S. Preventive Services Task Force
      Aspirin use to prevent cardiovascular disease: US Preventive Services Task Force recommendation statement.
      Of these, the study considered 6 measures that had data available from 2014 to 2020, with at least one million patients seen across all CHCs to ensure sufficient data to conduct analysis for measures by year. These measures included up-to-date (UTD) colorectal cancer screening, cervical cancer screening, tobacco screening and cessation counseling, adult BMI screening and follow-up, depression screening and follow-up, and aspirin use for ischemic vascular disease (IVD). A detailed description of each measure with the time period required to be UTD is available in Appendix Table 1 (available online).
      Table 1Mean Proportion of Patients With Characteristics in Each CHC From 2014 to 2020, Uniform Data System
      Variables2014–2018, % (95% CI)2019, % (95% CI)2020, % (95% CI)
      201420162018
      n1,2781,3671,3621,3851,375
      Age distribution
       18–64 years64.0 (63.7, 64.3)62.6 (61.9, 63.2)63.6 (63.1, 64.2)
      Male43.4 (43.2, 43.6)43.6 (43.3, 44.0)43.5 (43.2, 43.8)
      Location
       Urban51.5 (50.3, 52.7)57.8 (55.2, 60.4)58.0 (55.4, 60.6)
      Race/ethnic distribution
       White41.9 (41.1, 42.6)41.0 (39.4, 42.5)41.5 (39.9, 43.0)
       Black19.0 (18.5, 19.6)18.4 (17.2, 19.6)19.4 (18.1, 20.6)
       Hispanic26.4 (25.7, 27.0)27.4 (25.9, 28.8)27.6 (26.2, 29.0)
       Asian3.1 (2.9, 3.3)3.2 (2.7, 3.7)3.6 (3.0, 4.1)
       Native Hawaiian/other Pacific Islander1.2 (1.0, 1.4)1.1 (0.7, 1.6)1.9 (1.1, 2.6)
       American Indian/Alaska Native2.2 (2.0, 2.5)2.0 (1.5, 2.5)2.7 (2.1, 3.4)
       More than 1 race1.1 (1.0, 1.1)1.4 (1.3, 1.5)1.5 (1.4, 1.6)
      Language
       Best served in a language other than English18.7 (18.2, 19.3)19.8 (18.6, 21.0)20.9 (19.6, 22.1)
      Poverty level
       At or below 100 of the federal poverty level66.5 (66.1, 67.0)64.3 (63.4, 65.3)63.8 (62.8, 64.8)
      Insurance type distribution
       Uninsured26.7 (26.3, 27.2)24.9 (23.9, 25.8)24.1 (23.1, 25.0)
       Medicaid43.0 (42.5, 43.5)42.7 (41.8, 43.7)42.2 (41.3, 43.2)
       Medicare and dually eligible (2014 Medicare only)13.4 (13.2, 13.6)15.0 (14.5, 15.5)16.5 (15.7, 17.3)
       Private19.2 (18.9, 19.5)20.6 (19.9, 21.3)22.9 (22.3, 23.6)
       Other public0.9 (0.8, 1.0)0.7 (0.6, 0.8)0.8 (0.6, 0.9)
      Homeless7.5 (7.1, 8.0)7.1 (6.2, 8.0)7.8 (6.8, 8.8)
      CHC funding type
       No CHC funding6.0 (5.4, 6.6)5.3 (4.1, 6.5)5.2 (4.0, 6.3)
       MHC funding12.8 (12.1, 13.6)12.6 (10.9, 14.4)12.7 (11.0, 14.5)
       HO funding21.5 (20.6, 22.5)21.7 (19.5, 23.8)21.7 (19.6, 23.9)
       PH funding7.5 (6.9, 8.2)7.8 (6.4, 9.2)7.8 (6.4, 9.2)
      Medicaid expanded as of 201970.0 (68.9, 71.1)70.3 (67.9, 72.7)70.2 (67.8, 72.6)
      Number of unique patients per clinic19,041 (18,493, 19,589)21,543 (20,146, 22,939)20,793 (19,396, 22,190)
      CHC, Community Health Center; HO, Health Care for the Homeless; MHC, Migrant Health Center; PH, Public Housing Primary Care.

      Measures

      The primary exposure for this paper was year as a proxy for the COVID-19 pandemic. Data for clinical quality measures in 2020 were treated as during the pandemic, whereas data for clinical quality measures in 2019 and earlier were treated as before the pandemic. Data from 2014 to 2018 were also included to assess trends in previous years.
      All covariates were at the CHC level. Continuous variables included distributions of age (patients aged 18–64 years), racial/ethnic (patients identified as non-Hispanic White, non-Hispanic Black, Hispanic, non-Hispanic Asian, non-Hispanic Native Hawaiian/other Pacific Islander, non-Hispanic American Indian/Alaska Native, and non-Hispanic multiple races), language (best served in a language other than English), poverty level (at or below 100% of the federal poverty level [FPL]), insurance status (uninsured, Medicaid insured, Medicare or dually insured [2014 was Medicare only], privately insured, and other publicly insured), sex (male), and CHC population size (total unique patients).

      Uniform Data System (UDS) training and technical assistance, 2021, Health Resources and Services Administration https://bphc.hrsa.gov/datareporting/reporting/index.html. Updated October 3, 2022. Accessed July 1, 2022

      Continuous covariates were categorized into ranked balanced tertiles of low, medium, and high proportions on the basis of a previous study.
      • Fedewa SA
      • Cotter MM
      • Wehling KA
      • Wysocki K
      • Killewald R
      • Makaroff L.
      Changes in breast cancer screening rates among 32 Community Health Centers during the COVID-19 pandemic.
      Categorical variables for location (urban versus rural), Section 330 funding types the CHCs received (CHC funding, Migrant Health Center funding, Health Care for the Homeless funding, Public Housing Primary Care [PH] funding), and state expansion of Medicaid to low-income adults by 2019 were also considered.

      Statistical Analysis

      Descriptive statistics of covariates in 2014–2018, 2019, and 2020 were estimated as means and 95% CIs through normal distribution. A test of association was run using either t-test (2 groups) or ANOVA (≥3 groups) on the basis of variable response options to estimate the difference in time trends by sociodemographic covariates. Collinearity between covariates was assessed using 2 methods. A Pearson correlation matrix found an absolute correlation coefficient >0.7 among the proportion of Hispanic patients and patients best served in a language other than English. A regression model found that the proportion of patients best served in a language other than English and CHCs Medicaid expansion status had variance inflation factors >2.5, indicating that both variables were significantly associated with other independent variables in the model. On the basis of these analyses, patients best served in a language other than English and CHCs Medicaid expansion status were excluded from further analyses. A proportion of Native Hawaiian/other Pacific Islander, American Indian/Alaska Native, multiple races, and other publicly insured were excluded from the model because of low sample size. Tukey's Fence method was used to detect outliers in the clinical quality measures. Values that were above/below the upper/lower limit of the upper/lower quartile plus/minus 1.5 times the IQR were removed from the model.,
      • Hoaglin DC
      • Iglewicz B
      • Tukey JW.
      Performance of some resistant rules for outlier labeling.
      The average rates for each clinical quality measure, after this exclusion, varied at most by 3% compared with the original rates. Mixed effects regression models were used to estimate changes in clinical quality measures between years and also through an interaction model with levels of sociodemographic variables, adjusting for random clustering of health centers within states. Covariates were included as fixed effects in the model. CIs were calculated using a normal distribution with chi-square estimation. SAS statistical software was used for all analyses.

      RESULTS

      Table 1 provides descriptive statistics for all covariates in 2014–2018, 2019, and 2020. Covariates were generally similar across the 3 time periods. For example, the proportion of patients aged 18–64 years remained at 62.6%–64.0%, and the proportion of Hispanic patients remained at 26.4%–27.6%. Exceptions to this pattern were the proportion of clinics in urban locations, which increased from 51.5% in 2014–2018 to 57.8% in 2019 and to 58.0% in 2020, primarily driven by an increase in the number of urban clinics as the number of total clinics increased from 1,278 in 2014 to 1,375 in 2020.
      Figure 1 and Table 2 show the year-over-year changes in the 6 clinical quality measures from 2014 to 2020. Between 2019 and 2020, clinical quality measures statistically significantly declined for each of the 6 services. Notably, for colorectal cancer screening, BMI screening and follow-up, and depression screening and follow-up, the declines were a reversal from year-over-year changes from 2014 to 2019. Colorectal cancer screening decreased from 40.8% in 2019 to 37.7% in 2020, after continuously increasing year over year between 1.1% and 3.8% points from 2014 to 2019. BMI screening decreased from 70.7% to 65.4% in 2020, after year-over-year increases between 1.6% and 6.4% points between 2014 and 2019. Depression screening and follow-up decreased from 71.1% to 64.9% in 2020, after year-over-year increases between 2.0% and 10.7% points between 2014 and 2019. Cervical cancer screening, tobacco screening and cessation counseling, and aspirin use for IVD decreased from 48.8% to 44.9%, 85.8% to 83.4%, and 81.5% to 79.4%, respectively, between 2019 and 2020.
      Figure 1
      Figure 1Clinical quality measures over time from 2014 to 2020, Uniform Data System.
      IVD, ischemic vascular disease.
      Table 2Adjusted Year-Over-year Changes in Quality-of-Care Measures
      Variables2014, % (95% CI)2015, % (95% CI)2016, % (95% CI)2017, % (95% CI)2018, % (95% CI)2019, % (95% CI)2020, % (95% CI)
      Colorectal cancer screening
       Overall30.2 (28.2, 32.2)34.0 (32.0, 36.0)35.1 (33.1, 37.1)37.1 (35.1, 39.1)38.9 (36.9, 40.9)40.8 (38.8, 42.8)37.7 (35.4, 40.0)
       Year-over-year change3.8 (2.9, 4.7)1.1 (0.2, 1.9)2.1 (1.2, 2.9)1.8 (1.0, 2.6)1.9 (1.1, 2.7)–3.1 (–4.5, –1.8)
      Cervical cancer screening
       Overall48.0 (46.0, 50.0)47.6 (45.7, 49.5)45.8 (43.9, 47.8)47.5 (45.5, 49.4)48.1 (46.1, 50.0)48.8 (46.9, 50.8)44.9 (42.7, 47.0)
       Year-over-year change–0.4 (–1.2, 0.4)–1.8 (–2.6, –1.0)1.6 (0.8, 2.4)0.6 (1.4, –0.2)0.8 (0.0, 1.5)–4.0 (–5.2, –2.7)
      Tobacco cessation
       Overall82.8 (81.6, 84.0)83.7 (82.5, 84.9)85.4 (84.2, 86.6)86.9 (85.7, 88.1)86.8 (85.7, 88.0)85.8 (84.6, 87.0)83.4 (81.9, 84.8)
       Year-over-year change0.9 (0.3, 1.6)1.6 (1.0, 2.3)1.5 (0.9, 2.2)0.0 (–0.6, 0.6)–1.1 (–1.7, –0.5)–2.4 (–3.4, –1.4)
      BMI screen
       Overall52.6 (50.0, 55.2)56.2 (53.6, 58.7)60.0 (57.4, 62.5)61.5 (59.0, 64.1)67.9 (65.4, 70.5)70.7 (68.2, 73.2)65.4 (62.5, 68.4)
       Year-over-year change3.6 (2.4, 4.8)3.8 (2.6, 5.0)1.6 (0.4, 2.7)6.4 (5.3, 7.5)2.7 (1.7, 3.8)–5.3 (–7.1, –3.4)
      Depression screen
       Overall39.3 (36.3, 42.2)50.0 (47.1, 52.8)59.7 (56.9, 62.6)65.4 (62.6, 68.3)69.1 (66.3, 72.0)71.1 (68.3, 74.0)64.9 (61.6, 68.3)
       Year-over-year change10.7 (9.3, 12.2)9.8 (8.4, 11.2)5.7 (4.3, 7.0)3.7 (2.4, 5.0)2.0 (0.7, 3.3)–6.2 (–8.3, –4.1)
      Aspirin use
       Overall78.3 (77.1, 79.6)78.6 (77.4, 79.9)79.3 (78.0, 80.5)79.4 (78.1, 80.6)81.5 (80.3, 82.7)81.5 (80.2, 82.7)79.4 (77.9, 80.8)
       Year-over-year change0.3 (–0.3, 1.0)0.6 (0.0, 1.3)0.1 (–0.5, 0.7)2.1 (1.5, 2.7)0.0 (–0.6, 0.6)–2.1 (–3.0, –1.1)
      Note: Boldface indicates statistical significance (p<0.05).
      Adjusted for the proportion White, Black, Hispanic, Asian, urban/rural status, ≤100% of the federal poverty level, uninsured, Medicaid insured, Medicare or dually insured (2014 was Medicare only), privately insured, other publicly insured, male, patients without homes, with Community Health Center funding, with Migrant Health Center funding, with Health Care for the homeless funding, and with public housing primary care funding.
      Table 3 depicts the changes in the receipt of the 6 clinical quality measures between 2019 and 2020 by sociodemographic factors. The decline in colorectal cancer screening between 2019 and 2020 was largest in CHCs with a greater proportion of uninsured patients (medium: –3.9%; high: –3.0%), Hispanic patients (high: –3.7%), and patients who are at or below 100% FPL (high: –3.2%) than in CHCs with the lowest tertile of these factors and in PH- than in non-PH‒funded clinics (–3.6%) and in urban than in rural clinics (–3.4%). Similarly, the decline in UTD cervical cancer screening from 2019 to 2020 was larger in CHCs with a greater proportion of uninsured patients (medium: –2.5%) and patients without homes (medium: –3.3) than in CHCs at the lowest tertile and in PH- than in non-PH‒funded clinics (–3.5%) and in urban than in rural clinics (–2.9%). For both colorectal and cervical cancer screening, declines were not as drastic for clinics with greater proportions of White (colorectal medium: 3.8 high: 4.5, cervical high: 2.8) and privately insured (colorectal high: 3.8, cervical high: 3.2) patients as for clinics with the lowest tertile of these factors. The decline in BMI screening and follow-up was highest in CHCs with greater proportions of patients at or below 100% of the FPL (high: –4.6%) than in CHCs with the lowest tertile. The decline in UTD depression screening and follow-up was lower in clinics with greater proportions of patients at or below 100% of the FPL (high: –4.0%) and Medicaid patients (medium: –4.5%, high: –4.2%) than in CHCs at the lowest tertile and in PH- than in non-PH‒funded clinics (–6.8%). The decline in UTD aspirin use for IVD was greater in clinics that received PH funding than in those without PH funding (–3.0%). Additional estimates and differentials are depicted in Appendix Table 2 (available online).
      Table 3Adjusted Differentials in Covariates From 2019 to 2020
      ProportionsColorectal cancer screeningCervical cancer screeningTobacco cessationBMI screenDepression screeningAspirin use
      Age 18–64 years
       Low (≤58.2%)
      Ranges for ranked tertiles did not overlap, but the limits between ranks were less than the hundredths decimal in some cases.
      refrefrefrefrefref
       Medium (58.2%–67.3%)–1.4 (–4.2, 1.4)–1.4 (–4.1, 1.3)0.2 (–1.8, 2.3)–2.3 (–6.1, 1.4)0.4 (–3.6, 4.5)–0.9 (–2.8, 1.0)
       High (≥67.3%)–1.9 (–4.7, 0.9)–1.7 (–4.4, 1.0)–2.1 (–4.1, 0.0)–3.2 (–7.0, 0.6)1.0 (–3.1, 5.0)–0.3 (–2.2, 1.5)
      Location
       Urban–3.4 (–5.7, –1.2)–2.9 (–5.1, –0.8)–0.8 (–2.4, 0.9)–1.8 (–4.9, 1.3)–3.5 (–6.8, –0.2)0.1 (–1.4, 1.7)
       Ruralrefrefrefrefrefref
      White
       Low (≤21.2%)refrefrefrefrefref
       Medium (21.2%–55.4%)3.8 (1.3, 6.3)2.1 (–0.4, 4.5)–0.1 (–2.0, 1.7)0.7 (–2.8, 4.1)3.1 (–0.6, 6.8)–0.3 (–2.0, 1.4)
       High (≥55.4%)4.5 (2.0, 7.1)2.8 (0.3, 5.3)1.0 (–1.0, 2.9)3.2 (–0.4, 6.7)3.6 (–0.2, 7.4)–0.4 (–2.3, 1.4)
      Black
       Low (≤2.5%)refrefrefrefrefref
       Medium (2.5%–20.2%)–2.1 (–4.7, 0.5)–0.5 (–3.0, 2.0)1.0 (–0.9, 2.9)2.4 (–1.1, 5.9)2.8 (–1.0, 6.6)0.8 (–1.0, 2.5)
       High (≥20.2%)–1.2 (–3.9, 1.4)–1.1 (–3.7, 1.4)–1.3 (–3.2, 0.7)–3.2 (–6.8, 0.3)–1.6 (–5.5, 2.2)1.0 (–0.8, 2.8)
      Hispanic
       Low (<6.9%)refrefrefrefrefref
       Medium (≥6.9%–32.2%)–0.3 (–3.0, 2.4)–0.9 (–3.6, 1.7)–0.1 (–2.1, 1.9)–1.0 (–4.7, 2.8)–2.4 (–6.4, 1.7)–1.3 (–3.2, 0.6)
       High (≥32.2%)–3.7 (–6.4, –1.0)–2.4 (–5.0, 0.2)0.6 (–1.4, 2.7)–0.4 (–4.1, 3.4)–1.5 (–5.5, 2.6)–1.0 (–2.9, 0.9)
      Asian
       Low (≤0.5%)refrefrefrefrefref
       Medium (0.5%–14.6%)–0.4 (–3.3, 2.5)–0.2 (–3.0, 2.7)0.2 (–2.0, 2.3)1.8 (–2.2, 5.7)–1.0 (–5.2, 3.3)–0.6 (–2.6, 1.4)
       High (≥14.6%)–1.8 (–4.6, 1.0)–0.9 (–3.6, 1.8)–1.5 (–3.6, 0.5)–0.2 (–3.9, 3.6)–2.7 (–6.8, 1.3)–1.3 (–3.2, 0.6)
      At or below 100 FPL
       Low (≤59.4%)refrefrefrefrefref
       Medium (59.4%–75.8%)–2.1 (–4.7, 0.4)–1.6 (–4.1, 0.8)–0.9 (–2.8, 1.0)–1.7 (–5.2, 1.8)–2.2 (–6.0, 1.5)1.1 (–0.7, 2.9)
       High (≥75.8%)–3.2 (–6.0, –0.5)–2.5 (–5.2, 0.0)–0.1 (–2.1, 1.9)–4.6 (–8.3, –0.9)–4.0 (–8.0, –0.1)0.7 (–1.2, 2.5)
      Uninsured
       Low (≤15.5%)refrefrefrefrefref
       Medium (15.5%–29.4%)–3.9 (–6.5, –1.3)–2.5 (–5.0, –0.1)–1.3 (–3.2, 0.5)0.0 (–3.5, 3.5)–2.9 (–6.7, 0.8)–0.9 (–2.6, 0.9)
       High (≥29.4%)–3.0 (–5.6, –0.3)–1.4 (–4.0, 1.1)–1.4 (–3.4, 0.5)–0.2 (–3.8, 3.5)0.9 (–2.9, 4.8)–0.7 (–2.5, 1.1)
      Medicaid
       Low (≤32.6%)refrefrefrefrefref
       Medium (32.6%–53.5%)–1.7 (–4.3, 1.0)–1.8 (–4.4, 0.7)0.4 (–1.5, 2.4)–2.2 (–5.8, 1.3)–4.5 (–8.3, –0.6)–0.5 (–2.3, 1.3)
       High (≥53.5%)–1.8 (–4.5, 1.0)–2.0 (–4.7, 0.6)0.4 (–1.6, 2.5)–1.9 (–5.6, 1.8)–4.2 (–8.2, –0.2)0.4 (–1.5, 2.3)
      Medicare
      Medicare or dually eligible (2014 Medicare only).
       Low (≤8.8%)refrefrefrefrefref
       Medium (8.8%–16.2%)0.1 (–2.8, 2.9)0.8 (–2.0, 3.5)–0.8 (–2.9, 1.3)–3.0 (–6.9, 0.8)–2.3 (–6.4, 1.8)0.2 (–1.8, 2.1)
       High (≥16.2%)2.5 (–0.3, 5.2)2.9 (0.3, 5.5)1.1 (–0.9, 3.1)–1.1 (–4.8, 2.6)0.0 (–4.0, 4.0)–0.1 (–2.0, 1.8)
      Private
       Low (≤12.8%)refrefrefrefrefref
       Medium (12.8%–23.9%)1.8 (–0.9, 4.5)2.5 (–0.1, 5.1)0.5 (–1.5, 2.5)–0.6 (–4.3, 3.1)0.4 (–3.6, 4.4)0.2 (–1.6, 2.1)
       High (≥23.9%)3.8 (1.0, 6.5)3.2 (0.5, 5.9)0.4 (–2.4, 1.7)1.2 (–2.6, 5.0)1.2 (–2.9, 5.2)–0.2 (–2.2, 1.7)
      Male
       Low (≤41.1%)refrefrefrefref
       Medium (41.1%–44.6%)–0.7 (–3.3, 1.9)0.1 (–1.8, 2.0)–1.8 (–5.3, 1.7)–1.1 (–4.8, 2.6)–0.5 (–2.2, 1.3)
       High (≥44.6%)1.8 (–0.9, 4.5)–0.3 (–2.4, 1.7)–1.3 (–5.0, 2.4)–1.3 (–5.2, 2.7)–0.1 (–2.0, 1.7)
      Homeless
       Low (≤0.5%)refrefrefrefrefref
       Medium (0.5%–3.2%)–1.5 (–4.5, 1.5)–3.3 (–6.1, –0.4)–1.2 (–3.4, 1.0)–1.2 (–5.3, 2.9)–0.5 (–4.9, 3.8)–1.4 (–3.4, 0.7)
       High (≥3.2%)–1.1 (–4.1, 1.9)–2.8 (–5.6, 0.1)–0.2 (–2.4, 2.0)–1.2 (–5.3, 2.8)1.9 (–2.5, 6.2)–1.0 (–3.0, 1.1)
      Funding
       Not CHC funded–2.4 (–11.9, 7.0)1.0 (–8.1, 10.1)–5.0 (–11.9, 1.8)–10.6 (–23.3, 2.2)3.7 (–10.0, 17.4)–2.0 (–8.3, 4.3)
       MHC–2.9 (–6.0, 0.2)–1.3 (–4.3, 1.7)0.7 (–1.6, 3.0)2.7 (–1.5, 6.9)0.7 (–3.9, 5.2)–1.0 (–3.2, 1.1)
       HO–0.6 (–3.1, 1.8)–0.2 (–2.5, 2.1)0.9 (–0.9, 2.7)0.1 (–3.2, 3.3)2.1 (–1.5, 5.6)–0.1 (–1.7, 1.6)
       PH–3.6 (–6.9, –0.2)–3.5 (–6.7, –0.4)–1.2 (–3.6, 1.3)–3.4 (–7.9, 1.1)–6.8 (–11.6, –2.0)–3.0 (–5.3, –0.6)
      Note: Boldface indicates statistical significance (p<0.05).
      Adjusted for the proportion White, Black, Hispanic, Asian, urban/rural status, ≤100% of the FPL, uninsured, Medicaid insured, Medicare or dually insured (2014 was Medicare only), privately insured, other publicly insured, male, patients without homes, with CHC funding, with MHC funding, with HO funding, and PH.
      CHC, Community Health Center; FPL, Federal Poverty Level; HO, Health Care for the Homeless; MHC, Migrant Health Center; PH, Public Housing Primary Care.
      a Ranges for ranked tertiles did not overlap, but the limits between ranks were less than the hundredths decimal in some cases.
      b Medicare or dually eligible (2014 Medicare only).

      DISCUSSION

      In this nationwide study of CHCs during the COVID-19 pandemic, there was a clear decline in 6 clinical quality measures that can serve as proxies for long-term health outcomes.

      Procedure manual. U.S. Preventive Services Task Force.https://uspreventiveservicestaskforce.org/uspstf/about-uspstf/methods-and-processes/procedure-manual. Updated August, 2022. Accessed July 1, 2022.

      Uniform Data System (UDS) training and technical assistance, 2021, Health Resources and Services Administration https://bphc.hrsa.gov/datareporting/reporting/index.html. Updated October 3, 2022. Accessed July 1, 2022

      • Davidson KW
      • Barry MJ
      U.S. Preventive Services Task Force
      Screening for colorectal cancer: U.S. Preventive Services Task Force recommendation statement [published correction appears in JAMA. 2021;326(8):773].
      • Curry SJ
      • Krist AH
      U.S. Preventive Services Task Force
      Screening for cervical cancer: U.S. Preventive Services Task Force recommendation statement.
      • Krist AH
      • Davidson KW
      U.S. Preventive Services Task Force
      Interventions for tobacco smoking cessation in adults, including pregnant persons: U.S. Preventive Services Task Force recommendation statement.
      • Curry SJ
      • Krist AH
      U.S. Preventive Services Task Force
      Behavioral weight loss interventions to prevent obesity-related morbidity and mortality in adults: U.S. Preventive Services Task Force recommendation statement.
      • Siu AL
      • Bibbins-Domingo K
      U.S. Preventive Services Task Force (USPSTF)
      Screening for depression in adults: U.S. Preventive Services Task Force recommendation statement.
      • Davidson KW
      • Barry MJ
      U.S. Preventive Services Task Force
      Aspirin use to prevent cardiovascular disease: US Preventive Services Task Force recommendation statement.
      The declines in colorectal cancer screening, BMI screening and follow-up, and depression screening and follow-up represented a divergence from improvements observed in previous years, likely related to competing priorities and the urgent and acute needs of the early part of the COVID-19 pandemic. Declines were largest for clinical quality measures in CHCs serving high proportions of Hispanic, uninsured, persons ≤100% of the FPL, persons without homes, and PH-funded clinics.
      Changes between 2019 and 2020 indicate a shift from trends in 2014 to 2019, with changes for 3 of 6 measured outcomes being a reversal, suggesting that declines are associated with pandemic-related care disruptions. Before 2020, colorectal cancer screening, BMI screening and follow-up, and depression screening and follow-up increased annually. Cervical cancer screening, tobacco screening and cessation, and aspirin use for IVD remained steady from 2014 to 2019. In fact, before the pandemic, 4 of the 6 measures in this study met or exceeded the associated national screening targets.

      Healthy people 2020. HHS, Office of Disease Prevention and Health Promotion. https://www.healthypeople.gov/2020/data-search/Search-the-Data?nid=4960. Updated November 19, 2021. Accessed October 19, 2022.

      ,

      Healthy people 2030. HHS, Office of Disease Prevention and Health Promotion. https://health.gov/healthypeople/tools-action/browse-evidence-based-resources/statin-use-primary-prevention-cardiovascular-disease-adults-preventive-medication. Updated August, 2022. Accessed July 1, 2022.

      Yet, during the pandemic, all clinical quality measures significantly declined. An important consideration for this study is the aspect of periodicity, specifically for estimates of UTD colorectal cancer, cervical cancer, and tobacco screening and cessation counseling, which are recommended at intervals of >1 year. A decline in these outcomes is concerning given the periodicity of screening because many remained UTD without receiving screening during the measurement period. In addition, because UTD outcomes are most relevant for the prevention and early detection of cancer and other chronic disease outcomes, renewed efforts are needed to ensure that the observed screening measures do not translate to a sustained decline in lost screenings as the pandemic progresses.
      Despite these findings, it is important to note that CHCs provide high-quality care and have been under enormous pressure to care for their patients and communities amidst the rapidly evolving COVID-19 landscape. In fact, there has been evidence to suggest that colorectal cancer screening has been steadily improving, whereas cervical cancer screening has remained constant in CHCs before the pandemic.
      • Huguet N
      • Hodes T
      • Holderness H
      • Bailey SR
      • DeVoe JE
      • Marino M.
      Community health centers’ performance in cancer screening and prevention.
      CHCs also played a critical role in providing high-quality pandemic care to low-income patients.
      • Simon J
      • Mohanty N
      • Masinter L
      • Hamilton A
      • Jain A.
      COVID-19: exploring the repercussions on federally qualified health center service delivery and quality.
      At a peak week in January to May 2020, 67% of CHC visit volumes were for COVID-19 cases, leaving little room for preventive services during this time.
      • Simon J
      • Mohanty N
      • Masinter L
      • Hamilton A
      • Jain A.
      COVID-19: exploring the repercussions on federally qualified health center service delivery and quality.
      In addition, pandemic onset spurred new quality improvement interventions in individual CHCs and networks, including cancer screening modality changes, telehealth adoption, and patient outreach.
      • Fisher-Borne M
      • Isher-Witt J
      • Comstock S
      • Perkins RB.
      Understanding COVID-19 impact on cervical, breast, and colorectal cancer screening among federally qualified healthcare centers participating in “Back on track with screening” quality improvement projects.
      ,
      • Shah SK
      • McElfish PA.
      Cancer screening recommendations during the COVID-19 pandemic: scoping review.
      • Chung K
      • Rafferty H
      • Suen LW
      • Vijayaraghavan M.
      System-level quality improvement initiatives for tobacco use in a safety-net health system during the COVID-19 pandemic.
      • Schad LA
      • Brady LA
      • Tumiel-Berhalter LM
      • et al.
      Impact of COVID-19 on screening rates for colorectal, breast, and cervical cancer: practice feedback from a quality improvement project in primary care.
      • Morley CP
      • Schad LA
      • Tumiel-Berhalter LM
      • et al.
      Improving cancer screening rates in primary care via practice facilitation and academic detailing: a multi-PBRN quality improvement project.
      The extent to which these interventions mitigated large-scale disruptions in care among CHCs nationally is unknown, but preliminary evidence suggests that care has been rebounding after initial disruption in health settings.
      • London JW
      • Fazio-Eynullayeva E
      • Palchuk MB
      • McNair C.
      Evolving effect of the COVID-19 pandemic on cancer-related encounters.
      Nonetheless, this study indicates that the pandemic was potentially associated with nationwide care disruptions that reversed previous trends in preventive services, which previously matched national targets,

      Healthy people 2020. HHS, Office of Disease Prevention and Health Promotion. https://www.healthypeople.gov/2020/data-search/Search-the-Data?nid=4960. Updated November 19, 2021. Accessed October 19, 2022.

      ,

      Healthy people 2030. HHS, Office of Disease Prevention and Health Promotion. https://health.gov/healthypeople/tools-action/browse-evidence-based-resources/statin-use-primary-prevention-cardiovascular-disease-adults-preventive-medication. Updated August, 2022. Accessed July 1, 2022.

      as well as cancer screenings that were consistently lower than national estimates but were on an upward trajectory.
      • Fedewa SA
      • Cotter MM
      • Wehling KA
      • Wysocki K
      • Killewald R
      • Makaroff L.
      Changes in breast cancer screening rates among 32 Community Health Centers during the COVID-19 pandemic.
      ,
      • Huguet N
      • Hodes T
      • Holderness H
      • Bailey SR
      • DeVoe JE
      • Marino M.
      Community health centers’ performance in cancer screening and prevention.
      These findings highlight the need for broad-based interventions across CHCs nationally, and these efforts would be well served by building on the evidence base generated from interventions implemented during the pandemic, which have successfully improved care delivery.
      Larger declines were found for clinics with high proportions of patients who were disproportionally impacted by the pandemic, such as Hispanic patients and those with lower SES. Declines in colorectal cancer screening during the COVID-19 pandemic were particularly steep among CHCs with relatively high proportions of Hispanic persons. CHCs have historically documented large disparities for Hispanic persons in diabetes control and colorectal cancer screening.
      • Cole MB
      • Wright B
      • Wilson IB
      • Galárraga O
      • Trivedi AN.
      Longitudinal analysis of racial/ethnic trends in quality outcomes in community health centers, 2009–2014.
      ,
      • Singh GK
      • Jemal A.
      Socioeconomic and racial/ethnic disparities in cancer mortality, incidence, and survival in the United States, 1950–2014: over six decades of changing patterns and widening inequalities.
      Meanwhile, declines in colorectal and cervical cancer screening were not as drastic for clinics with higher proportions of White persons. The present results suggest that the pandemic may have been disproportionately associated with preventive care among CHCs that serve Hispanic patients. Given that Hispanic patients have relatively higher rates of chronic disease burden, targeted approaches are necessary to address these declines for CHCs with large Hispanic populations. Optimal utilization of electronic health records and data capabilities along with patient-centered medical home recognition and insurance coverage through Medicaid expansion may have contributed to improvements in diabetes control for Hispanic persons in CHCs.
      • Cole MB
      • Kim JH
      • Levengood TW
      • Trivedi AN.
      Association of Medicaid expansion with 5-year changes in hypertension and diabetes outcomes at federally qualified health centers.
      These improvements were most notable 5 years after state Medicaid expansion and may be related to improved financial revenues in CHCs that could expand service capacity.
      • Cole MB
      • Kim JH
      • Levengood TW
      • Trivedi AN.
      Association of Medicaid expansion with 5-year changes in hypertension and diabetes outcomes at federally qualified health centers.
      These and other interventions could potentially be further expanded to address disparities that emerged during the COVID-19 pandemic.
      Proceeding with the narrative that persons most impacted by the COVID-19 pandemic experienced the greatest disruptions to care, clinics with higher proportions of uninsured patients, patients at or below 100% of the FPL, and patients without homes and clinics receiving PH funding provided for clinics immediately accessible to public housing sites

      Uniform Data System (UDS) training and technical assistance, 2021, Health Resources and Services Administration https://bphc.hrsa.gov/datareporting/reporting/index.html. Updated October 3, 2022. Accessed July 1, 2022

      experienced higher declines in clinical quality measures. CHCs with relatively high proportions of uninsured patients had the greatest declines in colorectal and cervical cancer screening. This is consistent with previous literature that found that clinics with high proportions of uninsured patients were less likely to be in top-performing sites for some clinical quality measures.
      • Shi L
      • Lebrun LA
      • Zhu J
      • et al.
      Clinical quality performance in U.S. health centers.
      Meanwhile, clinics with higher proportions of privately insured patients experienced less drastic declines. Consistent with previous literature, CHCs with relatively high proportions of patients at or below 100% of the FPL had the lowest colorectal cancer screening, BMI screening and follow-up, and depression screening and follow-up rates.
      • Singh GK
      • Jemal A.
      Socioeconomic and racial/ethnic disparities in cancer mortality, incidence, and survival in the United States, 1950–2014: over six decades of changing patterns and widening inequalities.
      CHCs with greater proportions of patients without homes or PH-funded sites experienced additional declines in colorectal and cervical cancer screening, depression screening and follow-up, and aspirin use for IVD.

      Uniform Data System (UDS) training and technical assistance, 2021, Health Resources and Services Administration https://bphc.hrsa.gov/datareporting/reporting/index.html. Updated October 3, 2022. Accessed July 1, 2022

      In a recent study of patients without homes in Oklahoma, 64% were overweight or obese, and 79% used tobacco, along with multiple other negative risk factors.
      • Maness SB
      • Reitzel LR
      • Hernandez DC
      • et al.
      Modifiable risk factors and readiness to change among homeless adults.
      It is therefore concerning, albeit not surprising, that clinics that specialize in care to individuals without homes and those in or nearby public housing sites experienced drastic declines during the pandemic. This study's findings support the need for pandemic preparedness with bolstered public health infrastructure and ongoing support and resources for CHCs to be able to rapidly respond to urgent needs in their communities while also maintaining necessary preventive care services and chronic disease management. In addition, the role of social deprivation indices and community-level factors for clinical quality measures must be investigated because CHCs serving minority groups may have been more likely to shift their resources to pandemic-related care.

      Limitations

      Although care has been rebounding nationally since the beginning of the pandemic, it is not possible to determine whether this was the case in CHCs nationwide until additional years of the UDS data are released. Nor was it possible to assess whether increased COVID-19 rates in CHC areas were associated with decreases in the provision of preventive care because addresses for each clinic within a CHC were not provided. In addition, clustering by state prevented state-level analysis. The UDS does not allow for analysis by month, so January and February 2020 are included as part of the pandemic, despite pandemic orders not going into effect in the U.S. until March 2020.
      • Issaka RB
      • Somsouk M.
      Colorectal cancer screening and prevention in the COVID-19 era.
      The UDS only includes data for patients who received care each year and therefore was not able to account for patients falling out of care or who did not receive it within the calendar year reporting period. In addition, temporary CHC closures related to COVID-19 were not specifically documented in the UDS data, which may underestimate the vulnerable population needing care. However, the mean number of patients per clinic only dropped from 21,543 in 2019 to 20,793 in 2020. A sensitivity analysis was run on all clinical quality measures with a cohort of clinics that had data available for both 2019 and 2020, and the results were largely unchanged from those of the main results.

      CONCLUSIONS

      Unique declines in all clinical quality measures that diverged from previous trends indicated pandemic-related disruptions in care within CHCs. As practices adapted to the pandemic, there may be evidence of preventive services rebounding more recently.
      • London JW
      • Fazio-Eynullayeva E
      • Palchuk MB
      • McNair C.
      Evolving effect of the COVID-19 pandemic on cancer-related encounters.
      However, gaps may persist unless screening rebounds are high enough to mitigate these declines.
      • Patel SY
      • Mehrotra A
      • Huskamp HA
      • Uscher-Pines L
      • Ganguli I
      • Barnett ML.
      Trends in outpatient care delivery and telemedicine during the COVID-19 pandemic in the U.S.
      As more years of data are released, future studies to assess interventions that reduce disruptions in the care provided by CHCs will be helpful, as has already been done in individual safety-net hospitals.
      • Chung K
      • Rafferty H
      • Suen LW
      • Vijayaraghavan M.
      System-level quality improvement initiatives for tobacco use in a safety-net health system during the COVID-19 pandemic.
      An additional area for future research includes state-level analysis of CHCs with increased area rates of COVID-19. Efforts to improve long-term health outcomes of underserved groups also need to comprehensively address pandemic-related reductions in clinical quality measures in primary care delivered in CHCs that have high proportions of Hispanic patients, uninsured patients, patients in poverty, patients without homes, and clinics accessible to public housing.

      ACKNOWLEDGMENTS

      All authors are employed by the American Cancer Society, which receives grants from private and corporate foundations. The authors are not funded by these grants and are solely funded through the American Cancer Society funds.
      XH has received a grant from AstraZeneca for research outside of this study. No other financial disclosures were reported.

      CRediT AUTHOR STATEMENT

      Jessica Star: Conceptualization, Data curation, Formal analysis, Methodology, Writing–original draft, Writing–review and editing. Xuesong Han: Writing–review and editing. Laura Makaroff: Writing–review and editing. Adair K. Minihan: Writing–review and editing. Ahmedin Jemal: Writing–review and editing. Priti Bandi: Conceptualization, Supervision, Writing–review and editing.

      Appendix. SUPPLEMENTAL MATERIAL

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