Abstract
Objectives
To examine the nursing home to nursing home transfer rates before and during the early COVID-19 pandemic and to identify risk factors associated with those transfers in a state with a policy to create COVID-19-care nursing homes.
Design
Cross-sectional cohorts of nursing home residents in prepandemic (2019) and COVID-19 (2020) periods.
Setting and Participants
Michigan long-term nursing home residents were identified from the Minimum Data Set.
Methods
Each year, we identified transfer events as a resident's first nursing home to nursing home transfer between March and December. We included residents' characteristics, health status, and nursing home characteristics to identify risk factors for transfer. Logistic regression models were conducted to determine risk factors for each period and changes in transfer rates between the 2 periods.
Results
Compared to the prepandemic period, the COVID-19 period had a higher transfer rate per 100 (7.7 vs 5.3, P < .05). Age ≥80 years, female sex, and Medicaid enrollment were associated with a lower likelihood of transfer for both periods. During the COVID-19 period, residents who were Black, with severe cognitive impairment, or had COVID-19 infection were associated with a higher risk of transfer [adjusted odds ratio (AOR) (95% CI): 1.46 (1.01-2.11), 1.88 (1.11-3.16), and 4.70 (3.30-6.68), respectively]. After adjusting for resident characteristics, health status, and nursing home characteristics, residents had 46% higher odds [AOR (95% CI): 1.46 (1.14-1.88)] of being transferred to another nursing home during the COVID-19 period compared to the prepandemic period.
Conclusions and Implications
In the early COVID-19 pandemic, Michigan designated 38 nursing homes to care for residents with COVID-19. We found a higher transfer rate during the pandemic than during the prepandemic period, especially among Black residents, residents with COVID-19 infection, or residents with severe cognitive impairment. Further investigation is warranted to understand the transfer practice better and if any policies would mitigate the transfer risk for these subgroups.
Keywords: Nursing home to nursing home transfers, COVID-19 policy, risk factors for transfers
Long-term residential nursing home care is common among older adults.1, 2, 3 In 2020, there were 1.3 million nursing home residents in the United States.4 As the US population ages, the provision of long-term residential care has emerged as a critical policy issue for states that are the primary stakeholders in providing long-term services and support through the state's Medicaid program.
For long-term residents, the nursing home is not only a source of 24/7 care but is also regarded as the residents’ community and home. However, about 10% of residents stay at more than 1 nursing home each year, including direct transfers between 2 nursing homes and indirect transfers (via hospitals or emergency departments) to another nursing home.5, 6, 7, 8, 9 Although transferring residents to another nursing home for care needs could be beneficial, previous research shows that moving long-term nursing home residents between facilities can create a traumatic experience for the individual, leading to functional decline, increased loneliness, isolation, behavioral problems, falls, hospitalizations, and even death.10, 11, 12, 13, 14, 15
In 2020, the COVID-19 pandemic abruptly altered the operations of nursing homes, where the first outbreaks occurred. In the State of Michigan, the first COVID-19 case in nursing homes was identified in March 2020. Promptly, in April 2020, the Michigan Department of Health & Human Services (MDHHS) established COVID-19 Regional Hubs—a group of nursing homes to care for residents with COVID-19. The COVID-19 Regional Hub designation could apply to the whole facility or a unit in the facility. Residents with COVID-19 could be transferred to a Regional Hub if their existing facility could not care for them or safely isolate them from other residents (MSA 20-27).16 In September 2020, in response to the second wave of the pandemic and the recommendations from the Michigan Nursing Homes COVID-19 Preparedness Task Force, MDHHS established Care and Recovery Centers (CRCs) to replace Regional Hubs (MSA 20-72, MSA 20-77).17 , 18 Although Regional Hubs were exclusively nursing homes, CRCs could be based in nursing homes or hospitals. The policies that established Regional Hubs and CRC nursing homes could increase transfers between nursing homes for residents with COVID-19. Still, the degree to which facility to facility transfers occurred is unknown.
For this study, we aimed to measure nursing home to nursing home transfer rates, identify risk factors associated with the transfer, and determine whether the transfer rates and risk factors differed between the prepandemic (March to December 2019) and the COVID-19 (March to December 2020) periods. We focused on direct transfers between 2 nursing homes to address the impact of COVID-19-care nursing home policies on transfers. Because of Michigan's COVID-19 policies and the disproportional COVID-19 effects on minority populations,19, 20, 21, 22 we hypothesized that compared with the prepandemic period, during the early COVID-19 pandemic, the nursing home to nursing home transfer rate would be higher. Moreover, Black residents, residents with COVID-19 infection, or residents living in nursing homes with a small number of beds would have higher transfer rates.
Methods
Data Sources
We used Minimum Data Set (MDS) files from the State of Michigan to identify the cohorts and the nursing home provider file from the Centers for Medicare & Medicaid Services (CMS) (https://data.cms.gov/provider-data/dataset/4pq5-n9py) to identify nursing home characteristics. We also used Medicaid eligibility status obtained from state enrollment data.
Long-Term Nursing Home Residents
For each year, we identified long-term residents with at least 100 days total in any nursing homes during the year, including carry-over days from the previous year if that stay crosses over the calendar year.5 We used 2018 and 2019 data to create the prepandemic cohort and 2019 and 2020 data for the COVID-19 cohort. This approach excludes those who resided in nursing homes for short-term post-acute care only.
Study Residents
The first COVID-19 case in Michigan nursing homes was identified on March 10, 2020. Therefore, we restricted the study residents to those in nursing homes between March and December 2019 and 2020, respectively. We also excluded residents who did not have demographic information (age, sex, race, marital status) from MDS files and whose nursing home provider identification was not in the CMS provider file (N = 1079 for 2019 and 847 for 2020 cohorts).
Transferred vs Nontransferred Residents
We used only nursing home assessments from MDS files to identify direct nursing home to nursing home transfers. First, we identified residents who stayed in more than 1 nursing home during the year. For any 2 sequent nursing home stays, the following criteria must be met to be qualified to have a direct transfer event between 2 nursing homes: (1) discharge status was “to a nursing home” on the discharge assessment of the first nursing home; (2) the admission status was “from a nursing home” on the admission assessment of the second nursing home; and (3) the number of days between discharge date and admission date was 0 or 1. We used only the first nursing home to nursing home transfer event per resident between March and December to identify residents who had a transfer (the transferred residents).
Those who stayed in only 1 nursing home during the study period (March to December) were the nontransferred resident comparison group.
Resident Characteristics and Health Status
From MDS files, we obtained residents’ age (mean age > 80 years), sex (female), race (White, Black, other), and marital status (married). We included Medicaid enrollment status (yes/no) for each year from the Medicaid eligibility data if residents had participated in the program during the year.
We selected appropriate assessments for transferred and nontransferred residents to obtain health status from MDS files. We used the last assessment before the transfer (ie, the discharge assessment) for those with a transfer and the assessment (quarterly or annual) closest to August 1 (the midpoint of study period) for those without a transfer.
We included the following measures of health status: limitations on daily living activities [Activities of Daily Living (ADL) score = 3 extensive assistance or 4 = total dependence], presence of distress (Distressed Behavior Score >0),23 presence of depression [score ≥10 of Patient Health Questionnaire (PHQ-9) depression module from residents or staff], presence of behavioral problems (any behavioral problems checked on MDS form Section E Behavior), severe cognitive impairment [Cognitive Function Scale (CFS) = 4 (severe impairment)]. In addition, we identified residents with COVID-19 based on the diagnoses [International Classification of Diseases, Tenth Revision (ICD-10), code U07.1] on the assessment for the COVID-19 cohort.
Nursing Home Characteristics
We obtained the following facility characteristics from the CMS nursing home provider file: the number of beds, hospital-based status, for-profit status, and high 5-star quality rating (star rating >3). In addition, we linked the nursing home street address to the Neighborhood Atlas (https://www.neighborhoodatlas.medicine.wisc.edu) to obtain the Area Deprivation Index (ADI) value for the state of Michigan. We classified nursing homes in disadvantaged areas if the state ADI value was ≥8.24, 25, 26, 27, 28
Statistical Analysis
We first examined differences in transfer rates, resident characteristics, health status, and nursing home characteristics between prepandemic and COVID-19 cohorts using the χ2 test or t test, as appropriate. For each cohort, we then examined if the transfer rate differed by resident characteristics, health status, and nursing home characteristics. Logistic regression models were conducted for each cohort to determine the risk for transfer for each characteristic—crude and adjusted for all other characteristics so that we would identify significant factors associated with the transfer in each period after accounting for all other characteristics.
To identify risk factors for the COVID-19 period, we used a logistic regression model that initially included the same resident characteristics, health status, and nursing home characteristics as those used in the prepandemic period. This allowed us to compare the results with those from the prepandemic period to see any change in the risk association during the pandemic. We then added the COVID infection indicator to the model to examine the risk of having COVID-19 for transfer and if having COVID-19 could modify risk associations for other characteristics.
Lastly, using data from the 2 cohorts, we conducted an adjusted logistic regression model, including resident characteristics, health status, and nursing home characteristics (no COVID-19 infection indicator), to determine the risk for transfers in the COVID-19 period compared to the prepandemic period. All models were adjusted for nursing home clustering effects. Statistical analysis was performed using SAS 9.4 (SAS Institute Inc) and Stata SE17 (Stata Corp LLC). The university institutional review board approved this study.
Results
We identified 19,045 and 16,370 long-term nursing home residents as our study cohorts for prepandemic and COVID-19 periods, respectively (Table 1 ). The number of residents in the COVID-19 period was lower than that in the prepandemic period, consistent with prior research showing fewer nursing home residents during the pandemic.29, 30, 31 The overall transfer rate (Table 1) and the patterns of monthly transfer rate (Figure 1 ) were different between the 2 periods. The overall transfer rate was higher during the COVID-19 pandemic than in the prepandemic period (7.7 vs 5.3 per 100, P < .05). In addition, in the prepandemic period, the monthly transfer rates declined over the study period (Figure 1; test for trends P < .05). However, the monthly transfer rates in the COVID-19 period showed 3 peak months, May, August, and November (test for trends, P = .259). Those peak months could correspond to when Regional Hubs and CRCs were established, and/or COVID-19 waves occurred before COVID-19 vaccines became available in December 2020.
Table 1.
Characteristics of Nursing Home Residents and Their Nursing Homes Before and During the COVID-19 Pandemic
| Characteristics | Prepandemic (March to December 2019) | COVID-19 (March to December 2020) | P Value∗ |
|---|---|---|---|
| Total residents, n | 19,045 | 16,370 | |
| Residents who were transferred to another nursing home, n | 1011 | 1253 | |
| Transfer rate per 100 | 5.3 | 7.7 | <.05 |
| Resident characteristics | |||
| Age (mean, SD) | 79.5 (12.8) | 78.5 (13.0) | <.05 |
| Age ≥80 y | 54.4 | 50.2 | <.05 |
| Female | 67.8 | 67.3 | .33 |
| White | 79.6 | 80.4 | .16 |
| Black | 18.3 | 17.6 | |
| Other race | 2.1 | 2.0 | |
| Married | 18.8 | 17.6 | <.05 |
| Medicaid enrollee | 91.1 | 88.9 | <.05 |
| Health status† | |||
| ADL limitations | 40.7 | 34.2 | <.05 |
| Any distressed behaviors | 16.4 | 14.8 | <.05 |
| Depression | 0.4 | 0.7 | <.05 |
| Any behavioral problems | 19.0 | 17.4 | <.05 |
| Severe cognitive impairment | 10.2 | 9.7 | .14 |
| Facility characteristics | |||
| Large bed size (>130) | 40.2 | 39.9 | .67 |
| Hospital-based | 2.7 | 2.7 | .73 |
| For-profit status | 66.5 | 66.3 | .70 |
| High 5-star quality rating‡ | 67.3 | 68.9 | <.05 |
| In disadvantaged areas§ | 26.9 | 26.2 | .13 |
| With COVID-19, %‖ | n/a | 11.4 | n/a |
Values are percentages unless otherwise noted.
t test or χ2 test between 2 cohorts.
ADL: activities of daily living; limitations: ADL = 3 (extensive assistance) or 4 (total dependence); Distressed Behavior Score >0; Patient Health Questionnaire depression module (PHQ-9) from residents or staff score ≥10; any behavioral problems checked on MDS form Section E Behavior; Cognitive Function Scale = 4 (severe impairment).
5-star rating >3.
Area deprivation index (ADI) of nursing homes, based on a state scale of 1-10; 10 is the most disadvantaged area. Disadvantaged areas if ADI ≥ 8.
COVID diagnosis (ICD-10 U07.1) on MDS assessment.
Fig. 1.
Monthly transfer rates per 100 among long-term nursing home residents.
Even though there was a difference in transfer rates between the 2 periods, the characteristics of residents and nursing homes between the 2 periods were similar (Table 1), with a few slight differences reaching statistical significance. For example, residents in the COVID-19 cohort were slightly younger than the prepandemic cohort (mean age 78.5 vs 79.5, P < .05), less likely to be married (17.6% vs 18.8%, P < .05), less likely to be enrolled in Medicaid (88.9% vs 91.1%, P < .05), had better health status [eg, less likely to have limitations on activities of daily living (ADL score = 3 or 4: 34.2% vs 40.7%, P < .05), distressed behaviors (14.8% vs 16.4%, P < .05), or behavioral problems (17.4% vs 19.0%, P < .05)], and were more likely to stay in high-quality nursing homes (5-star quality rating >3: 68.9% vs 67.3%, P < .05). During the early months of the COVID-19 pandemic, 11.4% of residents had a COVID-19 diagnosis listed in their MDS assessment records.
We then examined risk factors associated with the transfer in each period. During the prepandemic period (Table 2 ), significant factors that were associated with a lower likelihood of being transferred included age ≥80 years [adjusted odds ratio (AOR) 0.51, 95% CI 0.44-0.60], female sex (AOR 0.83, 95% CI 0.72-0.95), Medicaid enrollment status (AOR 0.75, 95% CI 0.60-0.94), and severe cognitive impairment (AOR 0.67, 95% CI 0.52-0.88). Only 1 risk factor associated with transfers was found in the prepandemic period: being married (AOR 1.44, 95% CI 1.23-1.68).
Table 2.
Risks for Transfer in the Prepandemic (2019) Period by Resident Characteristics, Health Status, and Nursing Home Characteristics
| Transfer Status |
OR (95% CI) for Transfer Risks§ |
|||
|---|---|---|---|---|
| No, % (n = 18,034) | Yes, % (n = 1011) | Crude | Adjusted | |
| Resident characteristics | ||||
| Age ≥ 80 y | 55.3 | 37.5 | 0.48 (0.42-0.56) | 0.51 (0.44-0.60) |
| Female | 68.3 | 58.7 | 0.66 (0.58-0.75) | 0.83 (0.72-0.95) |
| White | 79.8 | 76.2 | 0.81 (0.67-0.98) | Ref |
| Black | 18.1 | 21.3 | 1.22 (1.00-1.49) | 1.15 (0.92-1.45) |
| Other race | 2.1 | 2.6 | 1.24 (0.78-1.97) | 1.20 (0.76-1.92) |
| Married | 18.5 | 25.3 | 1.50 (1.29-1.74) | 1.44 (1.23-1.68) |
| Medicaid enrollee | 91.2 | 89.1 | 0.79 (0.63-0.98) | 0.75 (0.60-0.94) |
| Health status∗ | ||||
| ADL limitations | 40.6 | 42.4 | 1.08 (0.94-1.24) | 1.16 (1.00-1.35) |
| Any distressed behaviors | 16.4 | 16.7 | 1.03 (0.84-1.26) | 0.77 (0.51-1.15) |
| Depression | 0.4 | 0.3 | 0.77 (0.24-2.46) | 0.71 (0.22-2.32) |
| Any behavioral problems | 18.9 | 19.9 | 1.06 (0.88-1.28) | 1.37 (0.95-1.98) |
| Severe cognitive impairment | 10.3 | 7.7 | 0.73 (0.57-0.93) | 0.67 (0.52-0.88) |
| Facility characteristics | ||||
| Large bed size (>130) | 40.4 | 36.0 | 0.83 (0.64-1.07) | 0.79 (0.61-1.03) |
| Hospital-based | 2.8 | 1.8 | 0.63 (0.25-1.58) | 0.74 (0.28-1.93) |
| For-profit status | 66.1 | 73.5 | 1.42 (1.05-1.93) | 1.21 (0.86-1.71) |
| High 5-star quality rating† | 67.6 | 62.0 | 0.78 (0.61-1.01) | 0.82 (0.64-1.04) |
| In disadvantaged areas‡ | 27.0 | 25.1 | 0.91 (0.71-1.16) | 0.79 (0.61-1.02) |
For Race: White race is the reference for the adjusted model.
Bold for significant OR at P < .05.
ADL: activities of daily living; limitations: ADL = 3 (extensive assistance) or 4 (total dependence); Distressed Behavior Score >0; Patient Health Questionnaire depression module (PHQ-9) from residents or staff score ≥10; any behavioral problems checked on MDS form Section E Behavior; Cognitive Function Scale = 4 (severe impairment).
5-star rating >3.
Area deprivation index (ADI) of nursing homes, based on a state scale of 1-10; 10 is the most disadvantaged area. Disadvantaged areas if ADI ≥8.
Crude and adjusted models adjusted for nursing home clustering effects, adjusted models adjusted for resident characteristics, health status, and nursing home characteristics.
Table 3 shows the risks for transfer in the COVID-19 period by resident characteristics, health status, and nursing home characteristics. Model 1 (without the indicator for COVID-19 infection) and model 2 (with the indicator for COVID-19 infection) show similar AOR for each characteristic. We found the same resident characteristics that were associated with a lower likelihood of transfer as in the prepandemic period: age ≥ 80 years (AOR 0.70, 95% CI 0.60-0.80), female sex (AOR 0.80, 95% CI 0.70-0.93), and Medicaid enrollment status (AOR 0.78, 95% CI 0.63-0.97). However, we found 3 new risk factors associated with being transferred in the COVID-19 period: residents identifying as Black (AOR 1.46, 95% CI 1.01-2.11), having severe cognitive impairment (AOR 1.88, 95% CI 1.11-3.16), and having COVID-19 (AOR 4.70, 95% CI 3.30-6.68).
Table 3.
Risks for Transfer in the COVID-19 (2020) Period by Resident Characteristics, Health Status, and Nursing Home Characteristics
| Transfer Status |
OR (95% CI) for Transfer Risks∗ |
||||
|---|---|---|---|---|---|
| No, % (n = 15,117) | Yes, % (n = 1253) | Crude | Model 1 | Model 2 | |
| Resident characteristics | |||||
| Age ≥80 y | 51.1 | 38.5 | 0.60 (0.49-0.73) | 0.69 (0.60-0.80) | 0.70 (0.60-0.80) |
| Female | 67.9 | 59.4 | 0.69 (0.59-0.81) | 0.80 (0.69-0.92) | 0.80 (0.70-0.93) |
| White | 81.1 | 71.6 | 0.59 (0.35-0.98) | Ref | Ref |
| Black | 16.9 | 26.6 | 1.78 (1.05-3.02) | 1.62 (1.13-2.32) | 1.46 (1.01-2.11) |
| Other race | 2.0 | 1.8 | 0.92 (0.60-1.40) | 1.00 (0.62-1.61) | 1.01 (0.63-1.62) |
| Married | 17.5 | 19.2 | 1.12 (0.94-1.33) | 1.09 (0.92-1.29) | 1.14 (0.97-1.34) |
| Medicaid enrollee | 89.0 | 87.6 | 0.87 (0.71-1.06) | 0.79 (0.63-0.98) | 0.78 (0.63-0.97) |
| Health status† | |||||
| ADL limitations | 34.0 | 36.6 | 1.12 (0.97-1.30) | 1.02 (0.87-1.20) | 1.05 (0.89-1.24) |
| Any distressed behaviors | 14.7 | 15.9 | 1.10 (0.87-1.39) | 0.84 (0.59-1.20) | 0.81 (0.56-1.17) |
| Depression | 0.7 | 0.4 | 0.58 (0.23-1.46) | 0.61 (0.25-1.50) | 0.71 (0.28-1.78) |
| Any behavioral problems | 17.3 | 19.2 | 1.13 (0.89-1.44) | 1.35 (0.90-2.02) | 1.44 (0.94-2.21) |
| Severe cognitive impairment | 9.2 | 15.4 | 1.79 (1.13-2.83) | 1.87 (1.13-3.08) | 1.88 (1.11-3.16) |
| Facility characteristics | |||||
| Large bed size (>130) | 40.6 | 32.4 | 0.70 (0.39-1.26) | 0.70 (0.39-1.24) | 0.62 (0.35-1.08) |
| Hospital-based | 2.8 | 1.3 | 0.45 (0.21-0.98) | 0.83 (0.33-2.14) | 1.02 (0.41-2.53) |
| For-profit status | 65.1 | 80.4 | 2.19 (1.12-4.29) | 1.88 (0.92-3.83) | 1.65 (0.83-3.27) |
| High 5-star quality rating‡ | 68.6 | 72.2 | 1.19 (0.79-1.79) | 1.27 (0.82-1.99) | 1.42 (0.91-2.21) |
| In disadvantaged areas§ | 26.0 | 29.1 | 1.17 (0.62-2.18) | 0.94 (0.54-1.63) | 0.97 (0.57-1.67) |
| COVID-19 indicator‖ | 9.6 | 33.4 | 4.74 (3.35-6.72) | 4.70 (3.30-6.68) | |
For race: White race is the reference for the adjusted model. Bold for significant OR at P < .05.
Crude, model 1, and model 2 adjusted for nursing home clustering effects; both model 1 and model 2, adjusted for resident characteristics, health status, and nursing home characteristics; model 1 without the COVID-19 indicator, model 2 included the COVID-19 indicator.
ADL: activities of daily living; limitations: ADL = 3 (extensive assistance) or 4 (total dependence); Distressed Behavior Score >0; Patient Health Questionnaire depression module (PHQ-9) from residents or staff score ≥ 10; any behavioral problems checked on MDS form Section E Behavior; Cognitive Function Scale = 4 (severe impairment).
5-star rating >3.
Area deprivation index (ADI) of nursing homes, based on a state scale of 1-10; 10 is the most disadvantaged area. Disadvantaged areas if ADI ≥ 8.
COVID diagnosis (ICD-10 U07.1) on MDS assessment.
Finally, using data from both cohorts, we determined the risk of being transferred during the COVID-19 period compared to the prepandemic period. After adjusting for resident characteristics, health status, and nursing home characteristics, Table 4 shows that during the early months of the COVID-19 pandemic, residents had 46% higher odds of transfer to another nursing home (AOR 1.46, 95% CI 1.14-1.88).
Table 4.
Adjusted Odds Ratios for Transfer During Early COVID-19 (2020) Compared to the Prepandemic (2019) Period
| OR (95% CI)∗ | |
|---|---|
| COVID-19 (2020) | 1.46 (1.14-1.88) |
| Resident characteristics | |
| Age ≥ 80 y | 0.60 (0.54-0.67) |
| Female | 0.81 (0.73-0.89) |
| White | Ref |
| Black | 1.39 (1.08-1.80) |
| Other race | 1.11 (0.79-1.57) |
| Married | 1.25 (1.11-1.41) |
| Medicaid enrollee | 0.78 (0.66-0.92) |
| Health status† | |
| ADL limitations | 1.09 (0.97-1.21) |
| Any distressed behaviors | 0.80 (0.61-1.07) |
| Depression | 0.62 (0.31-1.26) |
| Any behavioral problems | 1.36 (1.02-1.82) |
| Severe cognitive impairment | 1.23 (0.84-1.80) |
| Facility characteristics | |
| Large bed size (>130) | 0.74 (0.52-1.05) |
| Hospital-based | 0.78 (0.33-1.82) |
| For-profit status | 1.51 (1.00-2.29) |
| High 5-star quality rating‡ | 1.03 (0.78-1.37) |
| In disadvantaged areas§ | 0.87 (0.61-1.23) |
For race: White race is the reference for the adjusted model. Bold for significant OR at P <.05.
Adjusted for resident characteristics, health status, nursing home characteristics, and nursing home clustering effects.
ADL: activities of daily living; limitations: ADL = 3 (extensive assistance) or 4 (total dependence); Distressed Behavior Score >0; Patient Health Questionnaire depression module (PHQ-9) from residents or staff score ≥ 10; any behavioral problems checked on MDS form Section E Behavior; Cognitive Function Scale = 4 (severe impairment).
5-star rating >3.
Area deprivation index (ADI) of nursing homes, based on a state scale of 1-10; 10 is the most disadvantaged area. Disadvantaged areas if ADI ≥ 8.
Discussion
Using Michigan MDS assessment data, we found that, compared with the prepandemic period, during the early COVID-19 pandemic, there was a higher nursing home to nursing home transfer rate among long-term residents. Residents who were older (age ≥ 80 years), female sex, and enrolled in Medicaid were less likely to move to another nursing home in either period. Risk factors for transfer, however, changed between the prepandemic and COVID-19 periods. Consistent with our hypotheses, Black residents or residents with COVID-19 were associated with a higher risk of transferring to another nursing home during the pandemic. However, one unexpected finding was the change in the association between severe cognitive impairment and transfer between the 2 periods. The association changed from a lower likelihood in prepandemic to a higher likelihood during the COVID-19 period.
Our results indicated that nursing homes in Michigan transferred more long-term residents, especially those with COVID-19 infection, to another nursing home during the early months of the COVID-19 pandemic, with almost half of the transfers (40.2%) to 38 Regional Hubs and CRCs out of the 428 nursing homes in Michigan. Our findings likely reflect the response of Michigan nursing homes to the state COVID-19 care policies to manage COVID-19 infection. The 3 resident characteristics (age ≥80 years, female sex, and Medicaid enrollment) associated with a lower risk for transfer were consistent in both periods, suggesting that transferring those residents to another nursing home is less common. Yet, increased transfer rates were found in 2 subgroups during the early months of the COVID-19 pandemic in addition to those with COVID-19 infection—Black residents and residents with severe cognitive impairment.
One possible explanation could be that these 2 subgroups had higher rates of COVID-19 infection. Our post hoc analyses showed that Black residents had a higher COVID-19 infection rate than White residents (18.3% vs 9.9%, P < .05), but similar infection rates were found between those with and without severe cognitive impairment (9.1% vs 9.8%, P = .376). We used the ICD-10 code recorded on the MDS assessments to identify residents with COVID-19 infection. Because during the early months of the pandemic, nursing homes experienced staff shortages, there is concern that there could be potential underreporting of COVID-19 cases as this new disease had to be entered as a new ICD-10 code rather than a check box on MDS assessments.
Another possible explanation for higher transfer rates among Black residents is the uneven racial distribution in the communities across Michigan and the geographic distribution of the 38 Regional Hub and CRC nursing homes. Many of the Regional Hubs and CRCs were located around the Detroit areas, which could confound who got a transfer to another nursing home. Another possibility for a higher transfer rate among those with cognitive impairment is that nursing homes with limited resources during the pandemic could no longer care for residents with cognitive impairment and decided to transfer them to other nursing homes.
Further investigation is warranted to better understand appropriate transfer practice for these subgroups, who may be more vulnerable to adverse effects from transfers, and if any policies would balance the potential risk and the public health benefit from these transfers. Our study has several limitations. We used Michigan nursing home MDS assessment data to examine the nursing home to nursing home transfers under the state COVID-19 care policies. Our findings may not generalize to other states' experiences with nursing home transfers. However, the results from our study can provide insights for other states to plan their responses to future outbreaks or other emergencies that could affect nursing home care. Understanding the subgroups mostly affected during a pandemic and how residents' needs may differ from one subgroup to another may help target future efforts and interventions to control outbreaks in the event of a future pandemic. Although we did not include comorbidities identified in the MDS files as risk factors because of concerns about the incompleteness of active diagnoses, we included residents’ health status in our models. This descriptive analysis examined the association between risk factors and transfer, and we cannot assert the causal relationship between risk factors and transfer. We did not examine the reasons for the transfer, such as changes in care needs, financial coverage, staffing, nursing home closure, or organizational policy for transfers, which were beyond the scope of this study. Lastly, our results were from the early months of the COVID-19 pandemic, which may not represent the later COVID-19 pandemic impact, like the surge of the Omicron COVID-19 variant in 2021. Nevertheless, our results could assist states in developing COVID or other outbreak care policies that might affect nursing home transfer practices for long-term nursing home residents.
Conclusions and Implications
The COVID-19 pandemic has devastated people's lives and challenged long-term care in nursing homes, renewing attention from policymakers, researchers, nursing homes, individual providers, families, and residents to come together to rethink and reinvent strategies for better long-term care.32, 33, 34 Our study provided the first insight into the effect of the COVID-19 pandemic on nursing home to nursing home transfers in the context of a state policy to create COVID-19-care nursing homes. Our findings suggest that nursing homes in Michigan responded to the state's COVID-19 care policies by transferring more residents with COVID-19 infection to another nursing home. Yet, 2 subgroups of residents experienced higher transfer risk during the early COVID-19 pandemic, which requires further investigation. Identifying residents at risk for transfer and determining the underlying causes could aid policymakers and nursing homes in designing and implementing promising policies and strategies to mitigate the risk of moving long-term residents to another nursing home.
Footnotes
Funding source: This work was supported by the Patrick and Catherine Weldon Donaghue Medical Research Foundation.
The authors declare no conflicts of interest.
References
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