Abstract
Background
Emerging evidence shows the lasting impact of SARS-CoV-2 infection on health care use and needs. Policy-makers require data on population-level service use to understand patient needs and health system impacts following hospitalization for COVID-19.
Objective
To compare health service use within 12 months following hospitalization for COVID-19 among people with and without pre-existing disabilities, and to determine the extent to which such use is related to disability and other risk factors.
Design
Population-based cohort study, Ontario, Canada.
Participants
Adults with and without disabilities hospitalized for COVID-19, 01/25/2020–02/28/2022.
Main Measures
We used Poisson regression to model adjusted rate ratios (aRR) of ambulatory care visits, diagnostic testing, emergency department (ED) visits, hospital admissions, and palliative care visits within 1-year post-discharge, comparing patients with and without disabilities. Models were adjusted sequentially for sociodemographic factors, comorbidities, and prior health service use. The importance of each set of covariates in its ability to explain observed associations was determined by calculating relative changes in disability parameter coefficients after each sequential risk-adjustment.
Key Results
The cohort included 25,320 patients with disabilities and 15,953 without. In the year after hospitalization for COVID-19, people with disabilities had higher rates of ambulatory care visits, diagnostic tests, ED visits, hospital admissions, and palliative care visits. A significant proportion of these associations was explained by sociodemographic factors, comorbidities, and prior health service use. However, adjusted relative rates associated with disability remained elevated, even after adjustment, for ambulatory care visits (aRR 1.09, 95% CI 1.08, 1.10), diagnostic tests (aRR 1.14, 95% CI 1.12, 1.16), ED visits (aRR 1.25, 95% CI 1.21, 1.29), and hospital admissions (aRR 1.21, 95% CI 1.16, 1.29).
Conclusions
These findings support the need to develop and evaluate models of care for the post-COVID-19 condition that address the needs of people with disabilities.
Supplementary Information
The online version contains supplementary material available at 10.1007/s11606-025-09396-8.
KEY WORDS: cohort studies, disabled persons, COVID-19, post-acute COVID-19 syndrome
INTRODUCTION
The World Health Organization reported 770 million SARS-CoV-2 infections worldwide in the first 4 years of the COVID-19 pandemic.1 Emerging evidence shows the lasting impact of these infections on individuals’ health care use and needs, which includes development of post-COVID-19 condition.1 This enormous burden necessitates planning of health care resources to support people long term. To plan properly, policy-makers require data on population-level health service use to understand patient needs and associated health system impacts. It is essential that a health equity lens be applied to this planning to ensure supports are accessible to all.2 Yet, the needs of people with disabilities in this context have received little attention.
Globally, one in five individuals has a disability.3,4 Disabilities are heterogeneous and include physical, sensory, psychiatric, and developmental disabilities. People with disabilities are at heightened risk for acquiring SARS-CoV-2 infection as a result of elevated rates of immune compromise, social risk factors such as poverty, difficulty understanding and following public health guidance, and higher likelihood of living in congregate care settings where exposure to the virus is more likely.5–8 They are also at risk of experiencing severe short-term consequences of COVID-19 and being hospitalized due to physiological vulnerabilities related to their disability, higher rates of comorbid conditions such as cardiovascular disease (which can be exacerbated by infection), and barriers accessing high-quality health care.5–13 These same risk factors could place people with disabilities at risk of worse long-term outcomes after a COVID-19 hospitalization. However, the post-discharge health service use of people with disabilities, and the extent to which such use is related to their disability or other risk factors, has rarely been examined.14
To address these evidence gaps, we compared health services use, including ambulatory care, diagnostic tests, emergency department (ED) visits, hospitalizations, and palliative care, within 12 months following hospitalization for COVID-19 among people with and without pre-existing physical, sensory, and developmental disabilities, and investigated the extent to which such use is related to their disability or other known risk factors.
METHODS
Study Design and Setting
We conducted a population-based cohort study in Ontario, Canada, following the REporting of studies Conducted using Observational Routinely-collected Data (RECORD) guidelines.15 Ontario’s population of approximately 15 million residents receives health care services for all medically necessary care at no direct cost to residents. We accessed and analyzed data at ICES (formerly the Institute for Clinical Evaluative Sciences), an independent, non-profit research institute that uses routinely collected health administrative data derived from Ontario residents’ health care encounters for health system planning, management, and improvement.
Data Sources
Datasets, linked at the individual level using unique encoded identifiers, included the Ontario Laboratories Information System (OLIS) and Public Health Case and Contact Management (CCM) databases for COVID-19 cases, Ontario Health Insurance Plan (OHIP) database for outpatient visits, National Ambulatory Care Reporting System for ED visits, Canadian Institute for Health Information Discharge Abstract Database for hospitalizations, Ontario Mental Health Reporting System for hospital admissions in facilities with designated mental health beds, Ontario Disability Support Program (ODSP) database for disability-related income support, COVAXON for COVID-19 vaccination receipt, Registered Persons Database for vital statistics, and Census data for socio-demographics. ICES data are valid and complete for socio-demographics, primary diagnoses for hospital stays, and physician billing claims.16
Study Population
We included adults ≥ 18 years with a hospitalization for COVID-19 who were discharged alive between January 25, 2020, and February 28, 2022, excluding those with invalid age or sex data, who were ineligible for OHIP for >3 months in the year before index, or who resided in a long-term care facility. The study period was chosen as it corresponds to the first five waves of the COVID-10 pandemic, when infection rates and hospitalizations were highest.17 We used OLIS and CCM to identify laboratory-confirmed COVID-19 cases diagnosed within 14 days before or 3 days after admission to identify people admitted both with and for COVID-19.18,19
Among these patients, disability status was ascertained using algorithms developed to identify physical, sensory, and developmental disabilities in health administrative data.20–23 These algorithms capture diagnoses associated with functional limitations and need for accommodation when using health care,20–24 and have been applied in Ontario.6,10 A disability was deemed present if a relevant diagnosis was found in ≥ 2 physician visits (using physician billing codes), or ≥ 1 ED visits or ≥ 1 hospital admissions (using ICD-10 and DSM codes) between database inception (1988) and COVID-19 hospitalization admission date.6,10 In main analyses, we compared people with any disability to those without a documented disability. In pre-planned secondary analyses, we further compared (1) people with a physical disability only, sensory disability only, developmental disability only, and multiple disabilities, separately, to those without a disability, and (2) people with a disability receiving ODSP (as a proxy for greater disability-related support needs) and those not receiving ODSP, separately, to those without a disability. This latter analysis was restricted to individuals aged 18 to 64 years, the eligible age group for ODSP, and included only hospitalizations for COVID-19 up to April 30, 2021, the latest date of the ODSP database update. Finally, we undertook a sensitivity analysis excluding osteoarthritis, glaucoma, and cataracts from the disability definition—as these were the most common disability diagnoses but may vary in their impacts on functional limitations.
Outcomes
The outcomes were the number of ambulatory care visits, diagnostic tests, ED visits not resulting in hospital admission, hospitalizations, and palliative care visits up to 12 months after the COVID-19 hospitalization discharge date. We censored at death (5.6%), 90 days after loss of OHIP eligibility (0.1%), or end of follow-up (March 31, 2022), whichever came first.
Covariates
We measured baseline characteristics at admission: age; sex; neighborhood income quintile; Ontario Marginalization Index quintiles related to households and dwellings, material resources, age and the labor force, and racialized and newcomer populations;25 rurality; Comorbidities recorded in the 5 years before admission,26 selected based on their higher prevalence in people with disabilities20,27,28 and their impact on health service use; health service use in the 12 months before admission; pre-admission COVID-19 vaccination status; wave of the pandemic when the admission occurred; and, as indicators of the severity of COVID-19 illness, length of stay, diagnosis of delirium or myocardial infarction during the admission, intensive care unit admission, mechanical ventilation, Frailty Risk Score at discharge,29 and LACE Index score at discharge (predicting risk of death and 30-day readmission).30
Analyses
We reported the baseline characteristics of patients by pre-existing disability status, and compared the balance across groups using standardized differences.31
We used Poisson regression to compare patients with and without disabilities on their rates of ambulatory care visits, diagnostic tests, ED visits, hospitalizations, and palliative care visits. A model offset term (in months) was used to account for differential follow-up time. Models were sequentially adjusted for sociodemographic factors, comorbidities, and prior health service use. Given their theoretical importance, all variables measured within each of these categories were included. The importance of each set of covariates in its ability to explain the association between disability status and health service use was determined by calculating the relative changes in the parameter coefficient associated with disability status after each sequential risk-adjustment model, expressed as a proportion.30 To do this, we used the formula: |βu − βA|/|βu| (where βu and βA are the unadjusted and adjusted parameter estimates for disability), along with bootstrapping to estimate the lower and upper boundaries of the 95% CI.32
In sensitivity analyses, we further adjusted for COVID-19 vaccination status, wave of the COVID-19 pandemic when the admission occurred, and severity of COVID-19 illness.
We repeated the analyses (1) for people with physical, sensory, developmental, and multiple disabilities, separately, compared to those without a disability; (2) for people with disabilities using and not using ODSP, separately, compared to those without a disability; and (3) excluding people with only osteoarthritis, glaucoma, or cataracts from the disability group.
Missing data were minimal (< 1.2%), so descriptive and unadjusted analyses included all cohort members, and multivariable modeling was performed using a complete case analysis.
Analyses used SAS version 9.4 (SAS Institute Inc., Cary, NC).
Ethics
Data use was authorized under section 45 of Ontario’s Personal Health Information Protection Act and approved by the Mount Sinai Hospital Research Ethics Board (22–0188-E).
RESULTS
Baseline Characteristics
There were 25,320 adults with disabilities and 15,953 without disabilities hospitalized for COVID-19 between January 25, 2020, and February 28, 2022 (Fig. 1), who were followed for a median of 9.8 and 10.4 months, respectively. Compared to people without disabilities, those with disabilities were older and more likely to have multiple pre-existing comorbid conditions, higher prior health service use, prior palliative care, and COVID-19 vaccination receipt. During the index hospitalization, they were also more likely to have been diagnosed with delirium, had longer hospital length of stay, and had higher frailty and LACE scores (Tables 1 and 2).
Figure 1.
Creation of the study cohort. OHIP, Ontario Health Insurance Plan.
Table 1.
Sociodemographic Characteristics of Patients with and without Pre-existing Disabilities with a Hospitalization for COVID-19. Data Presented as n (%) Unless Otherwise Specified
| Disability (N = 25,320) |
No disability (N = 15,953) |
Standardized difference | |
|---|---|---|---|
| Age, median (IQR), years | 70 (58–80) | 48 (35–59) | 1.26 |
| Male sex | 13,144 (51.9) | 8201 (51.4) | 0.01 |
| Neighborhood income quintile (Q) | |||
| Q1 (lowest) | 7897 (31.2) | 4460 (28.0) | 0.07 |
| Q2 | 5573 (22.0) | 3368 (21.1) | 0.02 |
| Q3 | 4629 (18.3) | 3178 (19.9) | 0.04 |
| Q4 | 3917 (15.5) | 2769 (17.4) | 0.05 |
| Q5 (highest) | 3202 (12.6) | 2119 (13.3) | 0.02 |
| Missing | 102 (0.4) | 59 (0.4) | 0.01 |
| ON-MARG: households and dwellings | |||
| 1 (least marginalized) | 4965 (19.6) | 3841 (24.1) | 0.11 |
| 2 | 3702 (14.6) | 2552 (16.0) | 0.04 |
| 3 | 3804 (15.0) | 2343 (14.7) | 0.01 |
| 4 | 4828 (19.1) | 2853 (17.9) | 0.03 |
| 5 (most marginalized) | 7760 (30.6) | 4178 (26.2) | 0.10 |
| Missing | 261 (1.0) | 186 (1.2) | 0.01 |
| ON-MARG: material resources | |||
| 1 (least marginalized) | 2992 (11.8) | 1992 (12.5) | 0.02 |
| 2 | 4210 (16.6) | 2874 (18.0) | 0.04 |
| 3 | 4892 (19.3) | 3142 (19.7) | 0.01 |
| 4 | 5456 (21.5) | 3207 (20.1) | 0.04 |
| 5 (most marginalized) | 7509 (29.7) | 4552 (28.5) | 0.02 |
| Missing | 261 (1.0) | 186 (1.2) | 0.01 |
| ON-MARG: age and labor force | |||
| 1 (least marginalized) | 5929 (23.4) | 5287 (33.1) | 0.22 |
| 2 | 4996 (19.7) | 3402 (21.3) | 0.04 |
| 3 | 4449 (17.6) | 2811 (17.6) | 0.00 |
| 4 | 4249 (16.8) | 2262 (14.2) | 0.07 |
| 5 (most marginalized) | 5436 (21.5) | 2005 (12.6) | 0.24 |
| Missing | 261 (1.0) | 186 (1.2) | 0.01 |
| ON-MARG: racialized and newcomer populations | |||
| 1 (least marginalized) | 2454 (9.7) | 1272 (8.0) | 0.06 |
| 2 | 3153 (12.5) | 1602 (10.0) | 0.08 |
| 3 | 4089 (16.1) | 2173 (13.6) | 0.07 |
| 4 | 5904 (23.3) | 3572 (22.4) | 0.02 |
| 5 (most marginalized) | 9459 (37.4) | 7148 (44.8) | 0.15 |
| Missing | 261 (1.0) | 186 (1.2) | 0.01 |
| Rural residence | 1494 (5.9) | 869 (5.4) | 0.02 |
| Missing | 91 (0.4) | 55 (0.3) | 0.00 |
Table 2.
Clinical Characteristics of Patients with and without Pre-existing Disabilities with a Hospitalization for COVID-19. Data Presented as n (%) Unless Otherwise Specified
| Disability (N = 25,320) |
No disability (N = 15,953) |
Standardized difference | |
|---|---|---|---|
| Comorbidities | 463 (1.8) | 96 (0.6) | 0.11 |
| Acute myocardial infarction | 1328 (5.2) | 804 (5.0) | 0.01 |
| Alcohol and substance use disorder | 3203 (12.7) | 1172 (7.3) | 0.18 |
| Asthma | 8393 (33.1) | 2791 (17.5) | 0.37 |
| Cancer | 2894 (11.4) | 490 (3.1) | 0.33 |
| Cardiac arrhythmia | 16,114 (63.6) | 4704 (29.5) | 0.73 |
| Chronic hypertension | 3100 (12.2) | 510 (3.2) | 0.34 |
| Chronic obstructive pulmonary disease | 4350 (17.2) | 601 (3.8) | 0.45 |
| Congestive heart failure | 4523 (17.9) | 906 (5.7) | 0.39 |
| Coronary syndrome | 189 (0.7) | 66 (0.4) | 0.04 |
| Decompensated cirrhosis | 1013 (4.0) | 65 (0.4) | 0.25 |
| Deep vein thrombosis/pulmonary embolism | 4295 (17.0) | 1256 (7.9) | 0.28 |
| Dementia | 10,951 (43.3) | 3646 (22.9) | 0.44 |
| Diabetes mellitus | 824 (3.3) | 341 (2.1) | 0.07 |
| Immunocompromised | 7293 (28.8) | 3620 (22.7) | 0.14 |
| Non-psychotic disorder | 2312 (9.1) | 347 (2.2) | 0.30 |
| Pneumonia | 639 (2.5) | 303 (1.9) | 0.04 |
| Psychotic disorder | 7184 (28.4) | 1745 (10.9) | 0.45 |
| Renal failure | 1487 (5.9) | 242 (1.5) | 0.23 |
| Stroke | 463 (1.8) | 96 (0.6) | 0.11 |
| Health care use < 12 months before index | |||
| Ambulatory care visits, median (IQR) | 11 (6–19) | 7 (3–14) | 0.42 |
| Emergency department visits, median (IQR) | 0 (0–1) | 0 (0–1) | 0.12 |
| Hospitalizations, median (IQR) | 0 (0–1) | 0 (0–0) | 0.40 |
| Palliative care | 326 (1.3) | 62 (0.4) | 0.10 |
| Unique prescriptions, median (IQR) | 10 (1–18) | 0 (0–2) | 1.14 |
| Completed primary COVID-19 vaccination series with ≥ 1 Health Canada-approved booster | 2472 (9.8) | 731 (4.6) | 0.20 |
| Pandemic wave | |||
| Wave 1 (02/26/2020–08/31/2020) | 1782 (7.0) | 1060 (6.6) | 0.02 |
| Wave 2 (09/01/2020–02/28/2021) | 5274 (20.8) | 2700 (16.9) | 0.10 |
| Wave 3 (03/01/2021–07/31/2021) | 7524 (29.7) | 5772 (36.2) | 0.14 |
| Wave 4 (08/01/2021–12/14/2021) | 1801 (7.1) | 1599 (10.0) | 0.10 |
| Wave 5 (12/15/2021–02/28/2022) | 8939 (35.3) | 4822 (30.2) | 0.11 |
| Delirium | 2914 (11.5) | 708 (4.4) | 0.26 |
| Myocardial infarction at index hospitalization | 255 (1.0) | 146 (0.9) | 0.01 |
| ICU admission | 4366 (17.2) | 3042 (19.1) | 0.05 |
| Mechanical ventilation | 1652 (6.5) | 1154 (7.2) | 0.03 |
| Total length of stay, median (IQR), days | 7 (3–13) | 4 (2–9) | 0.40 |
| Hospital frailty risk score at discharge | |||
| 0 | 7679 (30.3) | 8341 (52.3) | 0.46 |
| 0.1–4.9 | 10,908 (43.1) | 5847 (36.7) | 0.13 |
| 5.0–8.9 | 3983 (15.7) | 1097 (6.9) | 0.28 |
| ≥ 9.0 | 2750 (10.9) | 668 (4.2) | 0.26 |
| LACE score | |||
| 0–6 | 4789 (18.9) | 6215 (39.0) | 0.45 |
| 7–10 | 12,915 (51.0) | 7693 (48.2) | 0.06 |
| ≥ 11 | 7616 (30.1) | 2045 (12.8) | 0.43 |
Primary Outcomes
In the year after hospitalization for COVID-19, people with disabilities had higher rates of ambulatory care visits (1419.5 vs. 999.9 per 1000 person-months), diagnostic tests (378.9 vs. 227.8), ED visits (93.4 vs. 58.5), hospital admissions (56.2 vs. 26.0), and palliative care visits (15.2 vs. 4.4) than people without disabilities (Table 3, Fig. 2). Sociodemographic factors, comorbidities, and prior health service use explained 100.0% of the association between disability and palliative care visits and between 52.8% (hospital admissions) and 76.3% (ambulatory care visits) of the association with the other outcomes, with comorbidities being the dominant explanatory factor (Table 4). However, even after adjusting for these factors, adjusted relative rates of health service use associated with disability status remained elevated for ambulatory care visits (aRR 1.09, 95% CI 1.08, 1.10), diagnostic tests (aRR 1.14, 95% CI 1.12, 1.16), ED visits (aRR 1.25, 95% CI 1.21, 1.29), and hospital admissions (aRR 1.21, 95% CI 1.16–1.29) (Table 3; eTable 1). Findings were similar after further adjusting for COVID-19 vaccination status, pandemic wave, and severity of COVID-19 illness (eTable 2).
Table 3.
Rates of Ambulatory Care Visits, Diagnostic Tests, Emergency Department Visits, Hospitalizations, and Palliative Care Visits, Comparing Patients with and without Pre-existing Disabilities Following Hospitalization for COVID-19
| Rate per 1000 person-months | RR (95% CI) |
Adjusted RR (95% CI)* |
Adjusted RR (95% CI)† |
Adjusted RR (95% CI)‡ |
|
|---|---|---|---|---|---|
| Ambulatory care visits | |||||
| Disability | 1419.5 |
1.42 (1.41, 1.43) |
1.36 (1.35, 1.37) |
1.17 (1.16, 1.18) |
1.09 (1.08, 1.10) |
| No disability | 999.9 | Referent | Referent | Referent | Referent |
| Diagnostic tests | |||||
| Disability | 378.9 |
1.66 (1.64, 1.69) |
1.49 (1.47, 1.52) |
1.21 (1.19, 1.23) |
1.14 (1.12, 1.16) |
| No disability | 227.8 | Referent | Referent | Referent | Referent |
| Emergency department visits | |||||
| Disability | 93.4 |
1.60 (1.55, 1.64) |
1.97 (1.92, 2.04) |
1.42 (1.37, 1.46) |
1.25 (1.21, 1.29) |
| No disability | 58.5 | Referent | Referent | Referent | Referent |
| Hospital admissions | |||||
| Disability | 56.2 |
2.16 (2.08, 2.25) |
1.92 (1.84, 2.00) |
1.36 (1.30, 1.42) |
1.21 (1.16, 1.29) |
| No disability | 26.0 | Referent | Referent | Referent | Referent |
| Palliative care visits | |||||
| Disability | 15.2 |
3.42 (3.13, 3.75) |
1.07 (0.97, 1.18) |
0.81 (0.73, 0.90) |
0.77 (0.69, 0.86) |
| No disability | 4.4 | Referent | Referent | Referent | Referent |
*Adjusted for socio-demographics (age; sex; neighborhood income, households and dwellings, material resources, age and the labor force, and racialized and newcomer populations quintiles; rurality)
†Adjusted for socio-demographics and comorbidities recorded in the 5 years before the index admission
‡Adjusted for socio-demographics, comorbidities, and prior health service use (number of ambulatory care visits, emergency department visits, and hospital admissions; receipt of palliative care; and number of prescription drugs in the 12 months before the index admission)
Figure 2.
Unadjusted (red) and adjusted (blue) rate ratios of health care use among adults with and without disabilities hospitalized with COVID-19 between January 25, 2020, and February 28, 2022. Models were adjusted for a comprehensive set of sociodemographic factors, comorbidities, and prior health service use. ED, emergency department.
Table 4.
Cumulative Effects on the Disability-Health Service Use Association of Adjusting Sequentially for Blocks of Risk Factors
| Outcomes | Proportion change of association that could be explained by collective adjustment of sequential covariate sets | Proportion change of association that could be explained by sequential covariate set adjustments | |||
|---|---|---|---|---|---|
| Socio-demographic (Model 1) |
Model 1 + Comorbidities (Model 2) |
Model 2 + Prior health service use (Model 3) |
Comorbidities (Model 1 vs. 2) |
Prior health service use (Model 2 vs. 3) |
|
| Ambulatory care visits |
12.2 (8.9, 15.8) |
54.8 (50.8, 59.7) |
76.3 (71.6, 81.7) |
48.5 (45.0, 52.9) |
47.6 (40.2, 55.9) |
| Diagnostic tests |
21.2 (16.7, 26.3) |
63.2 (56.7, 71.1) |
74.4 (67.5, 82.8) |
53.3 (47.1, 61.5) |
30.5 (23.2, 43.1) |
| Emergency department visits |
45.5 (36.6, 56.5) |
25.6 (15.5, 36.7) |
52.8 (42.8, 66.7) |
48.9 (42.7, 56.0) |
36.5 (28.8, 51.4) |
| Hospital admissions |
15.5 (10.6, 20.9) |
60.5 (54.0, 68.2) |
75.2 (68.4, 83.7) |
53.2 (47.3, 60.8) |
37.2 (28.3, 50.5) |
| Palliative care visits |
94.6 (75.2, 100.0) |
100.0 (93.5, 100.0) |
100.0 (95.8, 100.0) |
100.0 (70.0, 100.0) |
25.3 (1.2, 100.0) |
Secondary Analyses
People with physical and multiple disabilities had the highest rates of ambulatory care visits and diagnostic testing, and those with developmental and multiple disabilities had the highest rates of ED visits and hospitalizations in the year after hospitalization for COVID-19 (eTable 3). Again, sociodemographic factors, comorbidities, and prior health service use were strong explanatory factors (eTable 4) but adjustment did not completely attenuate associations.
In the sub-cohort of 18- to 64-year-olds with a hospitalization before April 30, 2021, 1034 (8.8%) had disabilities and were receiving ODSP, 4603 (39.2%) had disabilities but were not receiving ODSP, and 6111 (52.0%) did not have disabilities. Disparities in comorbidities, prior health service use, and COVID-19 severity were larger for people with disabilities receiving ODSP than those not (eTable 5). People with disabilities receiving and not receiving ODSP had higher rates of health service use than those without disabilities in the year after hospitalization for COVID-19, with differences largest for people with disabilities receiving ODSP (eTable 6). Again, socio-demographics, comorbidities, and prior health service use were strong explanatory factors (eTable 7), but adjustment did not completely attenuate results.
Finally, findings were similar to the main analysis after excluding individuals with only osteoarthritis, glaucoma, or cataracts from the disability group (eTable 8).
DISCUSSION
This large, population-based study found that in the first 2 years of the COVID-19 pandemic, people with disabilities had higher rates of health services use in the year after hospitalization for COVID-19 compared to people without disabilities, with the highest rates in people receiving disability-related income supports. While socio-demographics, comorbidities, and prior health service use were important explanatory variables, they did not completely account for observed associations. Our findings highlight the need to plan accessible and inclusive long-term health care supports for people with disabilities hospitalized for COVID-19.
Our study identified adults hospitalized for COVID-19 using established methods.18,19 However, findings are not generalizable to all individuals with a COVID-19 infection, only those requiring hospitalization. Given the study covered the first 2 years of the pandemic, findings also may not be generalizable to more recent years.33 Still, as the most severe phase of the pandemic,17 waves 1 to 5 have implications for planning for future public health emergencies. Ontario health records do not include self-reported disability status, so we used published algorithms that rely on medical diagnoses.20–23 This poses several limitations. First, we may have misclassified people with disabilities who did not have a formal diagnosis, or who did not seek health care for their disability. We also were not able to differentiate between people with disabilities who do and do not experience significant functional limitations. There was a high prevalence of people with disabilities admitted for COVID-19 in our cohort; this could be partly explained by the broad definition of disability used. However, our results were robust when analyzed by ODSP status. We lacked symptom and biochemical testing data to ascertain COVID-19 infection severity.34 However, we used proxies (e.g., mechanical ventilation) that likely reflect the underlying severity of COVID-19. Residual confounding could explain some of our results; for example, the age distributions of the study groups were different such that, even after adjustment, age could possibly explain some of our findings. We also could not measure broader supports available to people with disabilities (e.g., personal support workers, family). Finally, we could not determine if observed patterns are specific to COVID-19 patients, or if similar post-discharge disparities in health service use between people with and without disabilities might have been observed for other infections such as influenza.
People with disabilities are at elevated risk of acquiring SARS-CoV-25–8 and having severe short-term outcomes following infection compared to those without disabilities.5–13 In the general population, multiple incident health conditions and symptoms such as frailty, cognitive dysfunction, fatigue, depression, anxiety, and cardiovascular sequelae are common months after hospitalization for COVID-19 and are especially elevated in those with severe infection.19,34–36 Mounting evidence suggests these complex symptoms associated with the post-acute phase of COVID-19 have significant impacts on health systems, in part, reflected in greater ambulatory, emergency, and inpatient health care use in the months following SARS-CoV-2 infection.37,38 However, few studies have examined these issues in people with disabilities. One survey of US adults found people with disabilities were more likely than those without to report symptoms >4 weeks after a COVID-19 infection and to see a health care provider, seek emergency care, or be hospitalized for these symptoms.14 However, surveys often exclude individuals with disabilities that impact cognition or communication,39,40 and the study did not ascertain whether disability preceded the COVID-19 infection. Our study used population-based data to show elevated long-term health system impacts in people with pre-existing disabilities.
Our analyses suggest these impacts are partly explained by sociodemographic, health, and health care differences between people with and without disabilities. A greater burden of comorbid conditions and older age have contributed to the vulnerability of people with disabilities to SARS-CoV-2 infection and severe short-term COVID-19-associated outcomes.5–13 In our cohort, adjustment for this pre-existing complexity partly, but not completely, reduced associations between disability and outpatient care, ED visits, and hospital admissions after COVID-19 hospitalization, and reversed the association for palliative care. The latter finding might signify that a higher burden of comorbidities largely drove the increased risk for palliative care in people with disabilities, but that after accounting for these factors, they have reduced access.41,42 Finally, incident health conditions and symptoms are elevated in patients with severe SARS-CoV-2 infection.37,38 Yet, while people with disabilities in our cohort had longer hospital stays, more delirium, and higher frailty and LACE scores, indicating greater severity of illness that could influence health services use, adjustment for these factors did not affect results.
Other unmeasured factors may explain the remaining risk observed among people with disabilities. For example, there may be a higher risk of unanticipated complications in this group, such as progression and worsening of symptoms related to the disability. The impact of the sequelae of COVID-19 and post-COVID-19 condition on the trajectories of disability bears further study. Observed elevated rates of ED visits and hospital admissions in patients with disabilities could also reflect known barriers to accessing high-quality outpatient care.42,43 While patients with disabilities in our study also tended to have higher rates of ambulatory visits and diagnostic testing, this larger volume of outpatient care use does not necessarily indicate a higher quality of care; physical, communication, and attitudinal barriers within outpatient care settings may result in residual unmet needs which are reflected in the higher emergency and inpatient care observed.42 Finally, findings may reflect barriers to other supports (e.g., home care, meal support, transportation) for people with disabilities, resulting in poorer long-term health.
Our study adds to the mounting evidence of the disproportionate negative impacts of the COVID-19 pandemic on people with disabilities, showing that future emergency responses must consider their needs from the start.2 The higher health service use among people with disabilities in the year after hospitalization for COVID-19 shows the need for planning to ensure access to outpatient health services and reduce the need for emergency and hospital care. This presents an urgent opportunity for the development of accessible post-discharge models of care and to determine their effectiveness for people with disabilities. Several models of care have been developed to support people in the general population who experience the long-term sequelae of COVID-19, including screening and support by primary care teams, advanced testing by specialty clinics, treatment of symptoms of the post-COVID-19 condition by multidisciplinary rehabilitation services, and coordination of care referrals across multiple settings.37 However, care of patients following severe SARS-CoV-2 infection is fragmented and inequitable.37 Given the known barriers to care experienced by people with disabilities,41–43 there is a need to evaluate post-COVID-19 services in relation to physical accessibility of clinic spaces and transportation, efforts to address the communication needs of patients (e.g., American Sign Language interpretation), coordination of care with other medical providers managing comorbid conditions, coordination with disability-related supports (e.g., home care, transportation), as well as disability-related training needs of health care providers in these settings.44 Consideration of the needs of patients with disabilities following a hospitalization for COVID-19 is required in efforts to address the health system impacts of COVID-19.
Supplementary Information
Below is the link to the electronic supplementary material.
Author Contribution
HKB: contributed to the conception and design of the study; analysis and interpretation of the data; drafting of the manuscript; agrees to be accountable for all aspects of the work.
TAS: contributed to the conception and design of the study; analysis and interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
HC: contributed to the conception and design of the study; analysis and interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
SL: contributed to the conception and design of the study; analysis and interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
YL: contributed to the interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
CMB: contributed to the interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
PB: contributed to the interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
AMC: contributed to the interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
ASD: contributed to the interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
SG: contributed to the interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
MH: contributed to the interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
FR: contributed to the interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
AAV: contributed to the interpretation of the data; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
KQ: contributed to the conception and design of the study; analysis and interpretation of the data; drafting of the manuscript; critically revised the manuscript for important intellectual content; approves the final version to be published; agrees to be accountable for all aspects of the work.
Funding
Research reported in this publication was supported by research funding from the Canadian Institutes of Health Research (GA4 -177772), and The Long COVID Web, which is funded by the CIHR. This research was undertaken, in part, thanks to funding from the Canada Research Chairs Program to Dr. Hilary K. Brown (CRC 2019-00158). This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health (MOH) and the Ministry of Long-Term Care (MLTC). The funding sources had no role in the design or conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. Parts of this material are based on data and/or information compiled and provided by the Ontario Ministry of Health (MOH), the Canadian Institute for Health Information (CIHI), and the Ontario Ministry of Children, Community and Social Services (MCCSS). We thank IQVIA Solutions Canada Inc. for use of their Drug Information File; parts of this material are based on data and information compiled and provided by the Ontario Ministry of Health. However, the analyses, conclusions, opinions and statements expressed in the material are those of the author(s), and not necessarily those of MOH, CIHI or MCCSS; no endorsement is intended or should be inferred. This document used data adapted from the Statistics Canada Postal CodeOM Conversion File 2021, which is based on data licensed from Canada Post Corporation, and/or data adapted from the Ontario Ministry of Health Postal Code Conversion File, which contains data copied under license from ©Canada Post Corporation and Statistics Canada. This does not constitute endorsement by Statistics Canada of this project.
Data Availability
Data used for this study were housed at ICES, an independent not-for-profit corporation. While data sharing agreements prohibit ICES from making the data set publicly available, access can be granted to those who meet pre-specified criteria for confidential access, available at www.ices.on.ca/. Requests to access ICES data for research purposes may be submitted to ICES’ Data and Analytic Services. Visit http://www.ices.on.ca/DAS for more information, including contact details.
Declarations
Ethical Approval
The use of data in this project was authorized under section 45 of Ontario’s Personal Health Information Protection Act and approved by the Mount Sinai Hospital Research Ethics Board (22-0188-E).
Consent to Participate
Not applicable
Consent for Publication
Not applicable
Conflict of Interest
The authors declare that they do not have a conflict of interest.
Footnotes
Prior Presentation
This work was presented at the Canadian Association for Health Services and Policy Research in Ottawa, Canada, May 2024.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data used for this study were housed at ICES, an independent not-for-profit corporation. While data sharing agreements prohibit ICES from making the data set publicly available, access can be granted to those who meet pre-specified criteria for confidential access, available at www.ices.on.ca/. Requests to access ICES data for research purposes may be submitted to ICES’ Data and Analytic Services. Visit http://www.ices.on.ca/DAS for more information, including contact details.