Abstract
Background
Checkup visits (i.e., general health checks) can increase preventive service completion and lead to improved treatment of new chronic illnesses. After the onset of the COVID-19 pandemic, preventive service completion decreased in many groups that receive care in safety net settings.
Objective
To examine potential benefits associated with checkups in federally qualified health center (FQHC) patients.
Design
Retrospective cohort study, from March 2018 to February 2022.
Patients
Adults at seven FQHCs in Illinois.
Interventions
Checkups during a two-year Baseline (i.e., pre-COVID-19) period and two-year COVID-19 period.
Main Measures
The primary outcome was COVID-19 period checkup completion. Secondary outcomes were: mammography completion; new diagnoses of four common chronic illnesses (hypertension, diabetes, depression, or high cholesterol), and; initiation of chronic illness medications.
Key Results
Among 106,114 included patients, race/ethnicity was most commonly Latino/Hispanic (42.1%) or non-Hispanic Black (30.2%). Most patients had Medicaid coverage (40.4%) or were uninsured (33.9%). While 21.0% of patients completed a checkup during Baseline, only 15.3% did so during the COVID-19 period. In multivariable regression analysis, private insurance (versus Medicaid) was positively associated with COVID-19 period checkup completion (adjusted relative risk [aRR], 1.15; 95% confidence interval, [CI], 1.10–1.19), while non-Hispanic Black race/ethnicity (versus Latino/Hispanic) was inversely associated with checkup completion (aRR, 0.89; 95% CI, 0.85–0.93). In secondary outcome analysis, COVID-19 period checkup completion was associated with 61% greater probability of mammography (aRR, 1.61; 95% CI, 1.52–1.71), and significantly higher probability of diagnosis, and treatment initiation, for all four chronic illnesses. In exploratory interaction analysis, checkup completion was more modestly associated with diagnosis and treatment of hypertension and high cholesterol in some younger age groups (versus age ≥ 65).
Conclusions
In this large FQHC cohort, checkup completion markedly decreased during the pandemic. Checkup completion was associated with preventive service completion, chronic illness detection, and initiation of chronic illness treatment.
KEY WORDS: primary care, general health checks, checkups, federally qualified health centers, preventive care, chronic illness care.
INTRODUCTION
Checkups visits are healthcare encounters that include multiple screenings, and identification of risk factors, with a goal of initiating early interventions to prevent future illness. Randomized trials have demonstrated that checkups—which do not necessarily need to occur annually,1 and can be described using many other terms,2 such as general health checks, preventive visits, general medical examinations, periodic health evaluations, wellness visits, or preventive service visits—increase preventive care uptake,3–6 as well as detection7–10 and treatment10 of new chronic illnesses. However, checkup completion may be more common in socioeconomically advantaged populations,11,12 raising the question of whether their benefits accrue equitably across social and economic lines. Also, there have been no randomized trials of checkups in Americans since the early 1990s.3,4,13
Additionally, new research on this topic is being conducted in the aftermath of the COVID-19 pandemic, which caused upheavals such as substantial changes in health care delivery patterns. During the early stages of the pandemic, stay-at-home orders led to decreased use of in-person outpatient care14,15 and decreases in cancer screenings.16 Pandemic-related stressors were also associated with increases in blood pressure17 and elevated depressive symptoms.18 Although rates of preventive service completion began to recover in late 2020, these increases were insufficient to erase the screening deficits created during the pandemic’s early months.19,20
To our knowledge, no studies have evaluated the relationship between checkup completion and patient outcomes in U.S. primary care safety net settings. Even before the pandemic, racial and ethnic minority populations frequently lagged behind non-Hispanic Whites in preventive service completion.21,22 The pandemic then exacerbated disparities in services such as cancer screenings.16,23,24
The current study was conducted to examine two related topics in a population of patients served in the safety net: changes in checkup completion after the onset of the pandemic, and potential benefits associated with checkup completion in this safety net population. Our four aims were to: 1) Describe rates of checkup completion among adult federally qualified health center (FQHC) patients; 2) Identify patient characteristics associated with checkup completion; 3) Evaluate the association of checkup completion with previously observed benefits of checkups, and; 4) Explore whether the associations under study in Aim 3 varied by age group. We hypothesized that checkup completion would dramatically decrease after the pandemic’s onset, and that checkup completion would be associated with higher rates of preventive service completion and higher rates of chronic disease detection and treatment initiation.
METHODS
Study Design and Setting
This was a retrospective cohort study of adult patients at seven FQHCs in the state of Illinois. All participating FQHCs are members of AllianceChicago, a health center-controlled network that provides shared health information technology infrastructure to its member organizations.25 Although participating FQHCs did not necessarily have interventions in place to explicitly promote checkup completion, all seven organizations were required to submit annual Uniform Data System (UDS) reports to the Health Resources & Services Administration (HRSA); these reports included multiple measures related to study outcomes (detailed below) such as breast cancer screening, depression screening and management, and cardiovascular disease management.26 All study protocols were approved by the institutional review board at Northwestern University.
The study evaluated four years of data between March 2018 and February 2022. There were two defined study periods, each lasting two years. The Baseline (i.e., pre-pandemic) period ran from March 1, 2018 to February 29, 2020, and the COVID-19 period ran from March 1, 2020 to February 28, 2022.
Inclusion Criteria
Included patients were required to be age ≥ 18 at the study start date, and age ≤ 75 at the study end date; this upper age limit aligned with the age ranges for many recommended preventive services.27,28 Patients were also required to have one or more encounters (in-person or virtual/telehealth) at the same FQHC during both study periods. Patients were excluded if they had a diagnosis of Alzheimer's disease or dementia during the study period, since these conditions may affect patients’ ability to schedule and complete checkup visits and recommended preventive services. We also excluded 209 patients who were missing data on sex (0.2% of those who met all other inclusion criteria).
Variables
Study data were collected from a data warehouse containing electronic health record (EHR) data, including administrative and clinical records, for all participating FQHCs. The primary outcome was a binary measure of whether each patient completed one or more checkup visits during the COVID-19 period. Checkup completion was identified by the presence of any of nine Current Procedural Terminology (CPT) codes during the COVID-19 period, including those for a new non-Medicare patient preventive visit (CPT 99385, 99,386, 99,387), established non-Medicare patient preventive visit (99,395, 99,396, 99,397), a Welcome to Medicare Visit (G0402), or a Medicare Annual Wellness Visit (G0438, G0439). During the COVID-19 public health emergency, checkups could occur in person or virtually; those that occurred virtually were billed using the normal CPT codes, along with a telehealth modifier code.29,30
We also collected several secondary outcomes (all binary measures) for the completion of recommended cancer screening, and newly diagnosed and newly treated chronic illnesses, during the COVID-19 period. In accordance with national recommendations for breast cancer screening,31 we collected data on whether women age 50–74 completed mammography during the COVID-19 period. In addition, we collected data on newly identified chronic illness for the following four conditions: hypertension, diabetes, depression, and hypercholesterolemia/hyperlipidemia (i.e., high cholesterol). These conditions were identified through multiple forms of structured data, including validated sets of International Classification of Diseases, 10th revision (ICD-10) diagnoses32 and other structured codes used to identify chronic illnesses in federal quality metrics.33 For each patient, a chronic illness was defined as “newly identified” if it was not documented in the EHR during the Baseline period, but then documented in the EHR during the COVID-19 period. We also captured whether each patient was prescribed a new medication during the COVID-19 period to initiate treatment for each of these four chronic illnesses.
Using Baseline period data on patient characteristics, several covariates were collected. These variables included age as of March 1, 2020, sex, combined race/ethnicity (patients self-reported race and ethnicity data; all patients who identified as Latino or Hispanic ethnicity grouped together, regardless of race), insurance type, whether the patient’s home zip code was in Chicago, IL, and pre-existing chronic illnesses. We also collected data on the FQHC where each patient obtained care, and checkup completion during the Baseline period.
Statistical Analysis
Statistical analyses were conducted using Stata, version 17.0 (StataCorp; College Station, TX). In unadjusted analysis, we calculated summary statistics for patient characteristics variables, including mean age, frequencies of categorical characteristics, and prevalence of pre-existing chronic illnesses. Patient characteristics were also separately calculated for patients who completed, and did not complete, any checkups during Baseline. Differences between groups were evaluated using t-tests (mean age), Wilcoxon rank-sum tests (ordinal age group), and chi-square tests (unordered categorical variables).
We calculated unadjusted proportions of checkup completion in the COVID-19 period, overall and by subgroups of defined patient characteristics. We also calculated proportions of all secondary outcomes for patients who completed, and did not complete, any checkups during the COVID-19 period.
In multivariable regression analyses for the primary outcome and each secondary outcome variable, we estimated a Poisson regression model with robust variance estimates, which produce relative risk estimates for binary outcomes.34 All regression models adjusted for age group, sex, race/ethnicity, insurance, home zip code, pre-existing chronic illnesses, and the FQHC where each patient received care. Since checkups have been shown to be especially effective in older adults (e.g., Medicare enrollees),9,35 age ≥ 65 was selected as the referent category for the age group variable. For other categorical variables, the largest group was defined as the referent category.
In multivariable regression analyses for secondary outcomes, the regression model for mammography completion was restricted to women age 50–74 during the entire study period,31 and adjusted for mammography completion during Baseline. Each respective regression model for newly diagnosed chronic illness and newly initiated chronic illness medication excluded patients with pre-existing chronic illness (e.g., models for newly diagnosed hypertension and new hypertension medication excluded patients with documented hypertension during Baseline).
We estimated interaction models to explore whether the association between checkup completion and each outcome varied by age group. We identified effect modification in instances where an interaction model produced statistically significant between-group interactions. Age group-specific associations were calculated using Stata’s “lincom” command.
RESULTS
There were 181,345 patients who received care at any participating FQHC during the Baseline period, met age- and diagnosis-related inclusion criteria, and had no missing covariate data. Of these, 75,216 (41.5%) were excluded due to not receiving care at any participating FQHC during the COVID-19 period; 15 patients who did not receive care at the same FQHC during both study periods were additionally excluded.
The final cohort included 106,114 patients (Table 1). Over half of included patients were age 20–29 (28.3%) or age 30–39 (25.9%) at the beginning of the COVID-19 period, and nearly three-fifths of patients were female (58.3%). Patients’ race/ethnicity was most commonly Latino/Hispanic (42.1%), followed by non-Hispanic Black/African American (30.2%) and non-Hispanic White (18.2%). Most included patients had Medicaid insurance (40.4%) or were uninsured (33.9%), and most lived in the city of Chicago (76.7%). The prevalence of pre-existing chronic illness ranged from about one-eighth of included patients with diabetes (12.4%) to nearly one-fourth of patients with hypertension (23.7%). During the Baseline period, included patients had a mean of 6.9 FQHC encounters (standard deviation [SD], 8.0), nearly all of which were in-person.
Table 1.
Baseline Patient Characteristics
| Characteristic | Total* | Checkup Completion During Baseline Period* |
|
|---|---|---|---|
| No | Yes | ||
| N (%) | 106,114 | 83,855 (79.0) | 22,259 (21.0) |
| Age, mean (SD)†‡ | 40.3 (13.9) | 39.9 (13.9) | 41.7 (13.5) |
| Age group, n (%)†‡ | |||
| 20–29 | 30,027 (28.3) | 24,909 (83.0) | 5,118 (17.0) |
| 30–39 | 27,454 (25.9) | 21,826 (79.5) | 5,628 (20.5) |
| 40–49 | 19,363 (18.3) | 14,584 (75.3) | 4,779 (24.7) |
| 50–64 | 23,279 (21.9) | 17,745 (76.2) | 5,534 (23.8) |
| 65–73 | 5,991 (5.6) | 4,791 (80.0) | 1,200 (20.0) |
| Sex, n (%)‡ | |||
| Female | 61,857 (58.3) | 46,763 (75.6) | 15,094 (24.4) |
| Male | 44,257 (41.7) | 37,092 (83.8) | 7,165 (16.2) |
| Race/ethnicity, n (%)‡ | |||
| Latino/Hispanic§ | 44,649 (42.1) | 35,517 (79.6) | 9,132 (20.4) |
| Black non-Hispanic | 32,108 (30.2) | 24,071 (75.0) | 8,037 (25.0) |
| White non-Hispanic | 19,268 (18.2) | 15,996 (83.0) | 3,272 (17.0) |
| Asian/Pacific Islander | 4,180 (3.9) | 3,426 (82.0) | 754 (18.0) |
| Other/missing | 5,909 (5.6) | 4,845 (82.0) | 1,064 (18.0) |
| Insurance, n (%)‡ | |||
| Medicaid | 42,898 (40.4) | 32,845 (76.6) | 10,053 (23.4) |
| Medicare | 3,659 (3.5) | 2,929 (80.0) | 730 (20.0) |
| Uninsured | 36,001 (33.9) | 29,230 (81.2) | 6,771 (18.8) |
| Private | 20,404 (19.2) | 15,806 (77.5) | 4,598 (22.5) |
| Missing | 3,152 (3.0) | 3,045 (96.6) | 107 (3.4) |
| Home zip code, n (%)‡ | |||
| Chicago | 81,363 (76.7) | 63,357 (77.9) | 18,006 (22.1) |
| Non-Chicago | 24,751 (23.3) | 20,498 (82.8) | 4,253 (17.2) |
| Pre-existing chronic illness, n (%)ǁ | |||
| Hypertension‡ | 25,127 (23.7) | 19,010 (75.7) | 6,117 (24.3) |
| Diabetes‡ | 13,188 (12.4) | 10,612 (80.5) | 2,576 (19.5) |
| Depression | 14,747 (13.9) | 11,587 (78.6) | 3,160 (21.4) |
| Hypercholesterolemia/ hyperlipidemia‡ | 17,101 (16.1) | 11,903 (69.6) | 5,198 (30.4) |
Abbreviations:ICD-10, International Classification of Diseases, 10th revision; SD, standard deviation
* In the Total column, all subgroup percents are column percents. In the columns for patients who did and did not complete checkups, all subgroup percents are row percents
† As of March 1, 2020
‡ P < 0.001 for comparison of unadjusted differences between patients who completed, and did not complete, any checkups during Baseline
§ All patients who identified as Latino or Hispanic ethnicity grouped together, regardless of race
ǁ Identified using multiple forms of structured data, including ICD-10 diagnoses and code lists used to identify chronic illnesses in federal quality measurement reporting
During the Baseline period, 22,259 patients (21.0%) completed any checkups (Table 1, right column). For all patient characteristics except the prevalence of pre-existing depression, there were statistically significant differences in checkup completion across defined categories (P < 0.001). For example, checkup completion was relatively high in subgroups such as those age 40–49 (24.7%) and 50–64 (23.8%), females (24.4%), and Black non-Hispanic patients (25.0%).
During the two-year COVID-19 period, included patients had a mean of 4.7 in-person encounters (SD, 6.7) and 2.4 telehealth encounters (SD, 5.1). Concurrently, only 16,188 patients (15.3%) completed one or more checkups. This rate represents a 5.7% absolute decrease, and 27.3% relative decrease, versus 21.0% during Baseline. COVID-19 period checkup completion was uniformly lower across all patient characteristics; some notable results include 12.9% checkup completion among patients age ≥ 65 (Baseline, 20.0%), and 17.7% checkup completion among Black non-Hispanic patients (Baseline, 25.0%).
In multivariable regression analysis, several patient characteristics were associated with COVID-19 period checkup completion (Table 2). After covariate adjustment, checkup completion during Baseline was strongly associated with subsequent completion of another checkup during the COVID-19 period (adjusted relative risk [aRR], 1.89; 95% confidence interval [CI], 1.83–1.95), while male sex was associated with 29% lower probability of checkup completion (aRR, 0.71; 95% CI, 0.69–0.74). Relative to patients age ≥ 65, being age 30–39 (aRR, 1.14; 95% CI, 1.05–1.22), 40–49 (aRR, 1.29; 95% CI, 1.20–1.39), or 50–64 (aRR, 1.26; 95% CI, 1.17–1.35) was associated with higher adjusted probability of checkup completion. Compared with Latino/Hispanic patients, non-Hispanic Black race/ethnicity was associated with 11% lower probability of checkup completion (aRR, 0.89; 95% CI, 0.85–0.93). Relative to Medicaid insurance, private insurance was associated with 15% greater probability of checkup completion (aRR, 1.15; 95% CI, 1.10–1.19). While pre-existing high cholesterol was associated with 17% greater probability of checkup completion (aRR, 1.17; 95% CI, 1.12–1.21), both pre-existing diabetes (aRR, 0.75; 95% CI, 0.72–0.79) and pre-existing depression (aRR, 0.90; 95% CI, 0.86–0.94) were associated with lower probability of checkup completion.
Table 2.
Unadjusted Proportions Completing Checkups and Adjusted Associations Between Patient Characteristics and Checkup Completion, COVID-19 Period
| Characteristic | Checkup Completion During COVID-19 Period, n (row %) |
Adjusted RR (95% CI)* |
|---|---|---|
| Total | 16,188 (15.3) | n/a |
| Checkup during Baseline period | ||
| No | 9,429 (11.2) | Ref |
| Yes | 6,759 (30.4) | 1.89 (1.83–1.95) |
| Age group† | ||
| 20–29 | 3,886 (12.9) | 1.02 (0.95–1.11) |
| 30–39 | 4,076 (14.8) | 1.14 (1.05–1.22) |
| 40–49 | 3,513 (18.1) | 1.29 (1.20–1.39) |
| 50–64 | 3,942 (16.9) | 1.26 (1.17–1.35) |
| 65–73 | 771 (12.9) | Ref |
| Sex | ||
| Female | 11,621 (18.8) | Ref |
| Male | 4,567 (10.3) | 0.71 (0.69–0.74) |
| Race/ethnicity | ||
| Latino/Hispanic | 7,271(16.3) | Ref |
| Black non-Hispanic | 5,690 (17.7) | 0.89 (0.85–0.93) |
| White non-Hispanic | 2,034 (10.6) | 0.99 (0.95–1.05) |
| Asian/Pacific Islander | 533 (12.8) | 1.01 (0.93–1.10) |
| Other/missing | 660 (11.2) | 0.78 (0.73–0.84) |
| Insurance | ||
| Medicaid | 7,422 (17.3) | Ref |
| Medicare | 518 (14.2) | 0.99 (0.91–1.08) |
| Uninsured | 5,032 (14.0) | 0.97 (0.93–1.01) |
| Private | 2,854 (14.0) | 1.15 (1.10–1.19) |
| Missing | 362 (11.5) | 0.99 (0.90–1.09) |
| Home zip code | ||
| Chicago | 12,804 (15.7) | Ref |
| Non-Chicago | 3,384 (13.7) | 0.91 (0.88–0.95) |
| Pre-existing chronic illness | ||
| Hypertension | 4,157 (16.5) | 1.00 (0.97–1.04) |
| Diabetes | 1,776 (13.5) | 0.75 (0.72–0.79) |
| Depression | 2,049 (13.9) | 0.90 (0.86–0.94) |
| Hypercholesterolemia/ hyperlipidemia | 3,283 (19.2) | 1.17 (1.12–1.21) |
Abbreviations: RR, relative risk; CI, confidence interval; Ref, referent category
* Results from Poisson regression model with robust variance estimates. Model adjusted for all patient characteristics listed in Table 2, as well as health center; † As of March 1, 2020
In secondary outcome analysis, COVID-19 period checkup completion was associated with higher adjusted probability of breast cancer screening and all chronic illness-related outcomes (Table 3). Among women ages 50–74, checkup completion was associated with 61% higher adjusted probability of mammography completion (aRR, 1.61; 95% CI, 1.52–1.71). Checkup completion was also associated with greater probability of newly diagnosed chronic illnesses, ranging from 20% greater probability for newly diagnosed depression (aRR, 1.20; 95% CI, 1.11–1.29), to 110% greater probability for newly diagnosed high cholesterol (aRR, 2.10; 95% CI, 2.00–2.21). In addition, checkup completion was associated with greater probability of medications prescribed for a new chronic condition, ranging from 20% greater probability for both hypertension (aRR, 1.20; 95% CI, 1.12–1.28) and diabetes (aRR, 1.20; 95% CI, 1.08–1.32) medications, to 53% greater probability for high cholesterol medication (aRR, 1.53; 95% CI, 1.44–1.63).
Table 3.
Unadjusted Secondary Outcome Data and Adjusted Associations Between Secondary Outcomes and Checkup Completion, COVID-19 Period
| Outcome Measure | Secondary Outcome Completion, COVID-19 Period | Adjusted RR (95% CI) | |
|---|---|---|---|
| Patients With No Checkup Visits, n (%) | Patents Who Completed Checkup, n (%) | ||
| Mammography completion* | 2,582 (23.8) | 1,001 (40.4) | 1.61 (1.52–1.71) |
| Newly diagnosed chronic illness | |||
| Hypertension | 5,229 (7.6) | 1,397 (11.6) | 1.52 (1.43–1.61) |
| Diabetes | 1,376 (1.8) | 386 (2.7) | 1.44 (1.28–1.61) |
| Depression | 3,564 (4.6) | 815 (5.8) | 1.20 (1.11–1.29) |
| Hypercholesterolemia/ hyperlipidemia | 5,259 (6.9) | 1,924 (14.9) | 2.10 (2.00–2.21) |
| New medication for chronic illness† | |||
| Hypertension | 5,619 (8.2) | 986 (8.2) | 1.20 (1.12–1.28) |
| Diabetes | 2,192 (2.8) | 490 (3.4) | 1.20 (1.08–1.32) |
| Depression | 7,582 (9.8) | 1,559 (11.0) | 1.22 (1.16–1.29) |
| Hypercholesterolemia/ hyperlipidemia | 4,331 (5.7) | 1,070 (8.3) | 1.53 (1.44–1.63) |
Abbreviations: RR, relative risk; CI, confidence interval
* Among women age 50–74 during entire 4-year study period
† Among patients who did not have each respective chronic illness during Baseline period
In interaction analyses, age did not significantly modify how checkup completion was associated with mammography, or its association with detection and treatment of diabetes and depression (Table 4). However, for outcomes related to detection and treatment of hypertension and high cholesterol, there were some statistically significant interactions between age and checkup completion. For example, whereas checkup completion was only associated with 44% greater probability of newly diagnosed hypertension among patients ages 50–64 (aRR, 1.44; 95% CI, 1.31–1.59), it was associated with 102% greater probability of newly diagnosed hypertension among patients age ≥ 65 (aRR, 2.02; 95% CI, 1.61–2.53).
Table 4.
Adjusted Associations Between Secondary Outcomes and Checkup Completion During COVID-19 Period, by Age Group, in Interaction Models
| Outcome Measure | Age Group* Adjusted RR (95% CI) |
||||
|---|---|---|---|---|---|
| 20–29 | 30–39 | 40–49 | 50–64 | 65–73† | |
| Mammography completion‡ | n/a | n/a | n/a | 1.50 (1.41–1.59) | 1.64 (1.43–1.89) |
| Newly diagnosed chronic illness§ | |||||
| Hypertension | 1.58 (1.36–1.83) | 1.50 (1.34–1.69)‖ | 1.50 (1.35–1.67)‖ | 1.44 (1.31–1.59)‖ | 2.02 (1.61–2.53) |
| Diabetes | 1.65 (1.13–2.42) | 1.79 (1.41–2.28) | 1.40 (1.14–1.73) | 1.28 (1.06–1.55) | 1.23 (0.74–2.04) |
| Depression | 1.31 (1.14–1.49) | 1.15 (0.99–1.33) | 1.20 (1.02–1.43) | 1.10 (0.93–1.30) | 1.23 (0.81–1.85) |
| Hypercholesterolemia/ hyperlipidemia | 2.81 (2.39–3.30) | 2.38 (2.15–2.63) | 1.74 (1.59–1.91)‖ | 1.99 (1.83–2.15)‖ | 2.73 (2.27–3.27) |
| New medication for chronic illness§ | |||||
| Hypertension | 1.00 (0.85–1.17)‖ | 1.04 (0.90–1.20)‖ | 1.31 (1.16–1.49)‖ | 1.28 (1.14–1.43)‖ | 1.84 (1.43–2.36) |
| Diabetes | 1.28 (0.97–1.68) | 1.27 (1.04–1.54) | 1.10 (0.91–1.33) | 1.21 (1.03–1.44) | 1.08 (0.67–1.73) |
| Depression | 1.34 (1.20–1.49) | 1.25 (1.13–1.38) | 1.19 (1.07–1.33) | 1.12 (1.02–1.24) | 1.31 (1.02–1.68) |
| Hypercholesterolemia/ hyperlipidemia | 1.26 (0.78–2.02) | 1.53 (1.24–1.88)‖ | 1.38 (1.22–1.56)‖ | 1.52 (1.40–1.65)‖ | 2.03 (1.72–2.39) |
Abbreviations: RR, relative risk; CI, confidence interval
* As of March 1, 2020
† Referent category in interaction models
‡ For mammography, interaction analysis examined women aged 52–64 and 65–72 as of March 1, 2020
§ Among patients who did not have each respective chronic illness during Baseline period
‖ Statistically significant age group-by-checkup interaction, compared to referent category of patients aged 65–73
DISCUSSION
In this retrospective cohort study of over 100,000 adult patients at FQHCs in Illinois, several observed results aligned with our hypotheses. There was a 27.3% relative decrease in checkup completion during the two-year period after the onset of the COVID-19 pandemic. Also, in multivariable regression analyses, checkup completion was associated with higher rates of mammography, detection of new chronic illnesses, and new chronic illness treatments.
There were also other notable findings. Baseline period checkup completion, female sex, and private insurance coverage were associated with greater probability of COVID-19 period checkup completion. Relative to patients aged ≥ 65, being age 30–39, 40–49, or 50–64 was associated with greater probability of checkup completion, and Black non-Hispanic race/ethnicity was associated with lower probability of checkup completion (relative to Latino/Hispanic). These adjusted differences by age group and race/ethnicity during the COVID-19 period likely relate to the large observed decreases in checkup completion among groups such as those aged ≥ 65 and non-Hispanic Black patients, who may have elected to forego in-person primary care visits as a form of COVID-19 mitigation.36,37
In interaction analysis, checkup completion among patients aged ≥ 65 was generally associated with particularly high increases in newly diagnosed, and newly treated, hypertension and high cholesterol (versus patients aged 30–39 or 40–49). However, as stated above, during the COVID-19 period checkups among those aged ≥ 65 decreased substantially; older adults who did not complete checkups may therefore have been especially at risk of underdiagnosis and undertreatment of chronic diseases, with accompanying increases in the potential for adverse downstream health outcomes.
This study’s findings were largely consistent with prior studies of checkups outside U.S. safety net settings.2,38 Checkups offer primary care teams an opportunity to screen for several chronic illnesses, deliver preventive services such as vaccinations and selected cancer screenings, and promote other preventive services delivered outside primary care settings (e.g., mammography, colonoscopy). It was therefore unsurprising that checkups seem to be an appropriate venue to address care gaps in these domains after the onset of the COVID-19 pandemic.
Nevertheless, this study makes an important contribution to the evidence base at a time when Americans—and, especially, groups experiencing disparities—have high rates of unidentified and untreated cancers19,20 and chronic illnesses where patients benefit from timely diagnosis and intervention.17,18 In particular, our results are novel because they demonstrate that previously observed benefits associated with checkups2 were also observed in a large cohort of FQHC patients after the onset of the COVID-19 pandemic. To maximize population health, organizations could promote checkups in combination with other interventions that are effective in low-income populations, such as text messaging39 and mailed outreach40 to promote cancer screening, and intensive lay health educator interventions for diabetes care.41 Additionally, policymakers or payers may seek to incentivize checkup completion as a tool for increasing preventive service completion, chronic illness detection, and treatment.
Our findings highlight the potential value of checkups in FQHC populations and other groups experiencing disparities. Given the experimental evidence—mostly from the twentieth century—of checkups’ ability to increase preventive care uptake3–6 and detection7–10 and treatment10 of chronic disease, the associations detected in this observational study may be indicative of the effectiveness of checkups in safety net populations. Nevertheless, new experimental research is needed to better understand the benefits and limitations of checkups in modern primary care settings, both in and outside the safety net. Randomized trials should also examine how social needs may affect checkup completion, such as competing needs that could cause patients to deprioritize checkups42 or as potential barriers to visit attendance (e.g., transportation or financial needs).
This study is not without limitations. We were unable to collect data on healthcare that might have been obtained outside the seven included FQHCs. Also, given the observational study design, our regression analyses may have failed to account for unmeasured factors that could have been the true cause of observed results. Additionally, we were unable to collect more comprehensive data on completion of other preventive services—e.g., colorectal cancer screenings, vaccinations—beyond mammography. We are therefore unable to conclude that the observed association between checkups and increased mammography completion is generalizable to other preventive services. Our reliance on structured clinical codes to identify chronic illnesses likely led to under-identification of pre-existing and new chronic illnesses, which can also be identified through other data sources.43 Findings are likely only generalizable to the population of patients who had the need for (and capacity to obtain) care during the first two years of the COVID-19 pandemic, and may not be generalizable to other FQHCs that differ from the seven Midwestern, predominantly urban included FQHCs.
In conclusion, checkup completion in a large cohort of FQHC patients decreased by about one-fourth after the onset of the COVID-19 pandemic. Checkup completion during the pandemic was associated with higher rates of preventive service completion, chronic illness detection, and new chronic illness treatment. In exploratory analysis, checkups among patients age ≥ 65 were associated with particularly high increases in detection and treatment of hypertension and high cholesterol. This study’s findings underscore the potential value of checkups for patients who receive primary care in the safety net, and the need for efforts to promote checkup completion—and evaluate the effects of such efforts—in these settings.
Acknowledgements:
We wish to acknowledge and thank all of the FQHCs that contributed data to this study. Funding support was provided through institutional funds at AllianceChicago. Interim results were presented at the Illinois Primary Health Care Association Annual Leadership Conference in Chicago, IL on October 6, 2022.
Funding
Funding support was provided through institutional funds at AllianceChicago.
Declarations:
Conflicts of Interest:
The authors report no conflicts of interest.
Footnotes
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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