1 Introduction

Beginning in March 2020, hospitals experienced immediate decreases in hospitalizations that then rapidly rebounded to pre-pandemic levels by summer 2020 [1]. While ED visits then decreased, hospital admissions increased due to sicker patients requiring admission [2]. As a result of these rapid shifts in hospitalizations, additional pressure was put on staffing and discharge throughput [3, 4]. By April 2020, nearly all academic hospitals had developed new respiratory isolation units and described disruption in typical rounding structures that included health professionals rounding separately: 90% of sites decreased in-room encounters across all provider types [5]. As a result, team disruptions may have led to decreased communication and collaboration around discharge planning [6].

Meanwhile, for patients and families, the experience of being hospitalized was directly impacted during COVID-19 by visitation policies [7]. Restrictive policies ensured healthcare worker (HCW) safety but presented a trade-off of decreased time of caregivers—unpaid family or friends—at the bedside of hospitalized patients. Importantly, high-quality discharge planning includes patients and their caregivers and is critical to understanding barriers to safe discharge and the effectiveness of discharge teaching [8,9,10,11]. Actively engaging caregivers in hospital discharge processes is associated with as much as a 25% decrease in hospital readmissions [12, 13].

While it is likely that COVID-19 pandemic conditions created system changes to the structure and processes of care—such as rapid shifts in unit census, medical management of a new and deadly infectious disease, and changes to patient visitation policies—that adversely affected the quality of discharge preparation and created additional barriers to patients’ ability to recover in the community after discharge, there is little information about whether or how the system changes related to the pandemic impacted the quality of discharge preparation, and which patients may have been most impacted. In this study, we sought to understand the impact of COVID-19 through qualitative interviews with patients who were discharged into a locked-down community, and quantitative analyses exploring how COVID-19 changes within the hospital, personal characteristics, and discharge destination impacted patient-reported discharge readiness.

2 Methods

This convergent mixed methods study [14] was part of a larger parent study aiming to improve the quality of discharge planning from a quaternary care academic health sciences center University Hospital in the Intermountain West. Interviews were conducted with a sample of discharged patients during April 2020, and quantitative analyses were conducted on hospital data collected between April 22, 2020 and February 9, 2021.

2.1 Ethical approval

This research was performed in accordance with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of University of Utah. Informed consent was obtained from all participants included in the study.

2.2 Measures

For the qualitative portion, we developed an interview guide to understand participants’ ability to engage in self-management post-discharge, and to explore whether and how the discharge planning process identified potential needs post-discharge and contributed to successful transitions home after hospitalization. (See Supplementary Material.)

For the quantitative portion, the primary outcome measure was the eight-item Readiness for Hospital Discharge Scale (RHDS) [15,16,17,18,19] completed by the patient, assessing four dimensions of readiness that independently and mutually serve as outcomes of discharge preparation: perceptions of physical readiness to care for self (through recognition of availability of supportive persons and resources), knowledge (through education of a support person who can reinforce the information), ability to cope at home, and the level of expected support (having someone to help at home). The RHDS is correlated with quality of discharge teaching; difficulties coping post-discharge; care coordination and utilization of post-discharge services; lower perception of readiness at discharge is associated with increased use of both informal and formal support post-discharge; and hospital readmissions [18,19,20,21,22,23]. The RHDS uses a 0–10 point rating scale for each item; higher scores indicate greater readiness. A total mean score of less than 7 indicates low readiness and greater risk of readmission [16].

2.3 Setting and sample

Interview participants were identified from those discharged from medical and surgical hospital units in March 2020, who were at least 18 years of age, spoke English (English need not be the first language), were able to communicate verbally, previously completed the RHDS, and indicated a willingness to be interviewed. Interviews occurred until data saturation was reached.

The quantitative sample were patients discharged by general internal medicine (GIM) teams during the first months of the COVID-19 pandemic (April 22, 2020–February 9, 2021). Patients were at least 18 years of age, spoke English (English need not be the first language), and were able to communicate verbally. Because of the implications for unique discharge processes, patients admitted due to a primary or secondary psychiatric diagnosis; enrolled in palliative/hospice care; residing in a skilled nursing facility (SNF) upon admission; overseen by transplant or bariatric surgical services; seen for unfunded end stage renal disease; and/or prisoners were excluded from this study.

2.3.1 Procedures

After discharge orders were placed into the electronic health record, clinical research coordinators approached patients in person (prior to March 14th) or via their hospital room phone to comply with COVID-19 safety precautions after March 14th. The IRB-approved informed consent script was completed with each patient. Consenting patients then verbally completed the RHDS. All qualifying patients on participating units were called, but many were not in their rooms or had already been discharged by the time the call was placed.

Patients who completed the RHDS in March 2020 and indicated they were willing to participate in a follow-up interview, were contacted via telephone in April 2020. Semi-structured interviews took approximately 30 min. Interview participants received a $10 gift card after completion of the interview. Interviews were audio-recorded and professionally transcribed.

Finally, unit occupancy data and dates related to patient visitation policy changes were retrospectively collected from hospital administrative records for all dates between April 22, 2020 and February 9, 2021.

2.3.2 Quantitative analysis

Numeric variables were summarized with mean and standard deviation (SD); categorical variables are summarized with number and percent. Univariable linear regression models of the RHDS and its 4 subdomains were done for all variables. Multivariable linear regressions were done with analyses exploring hypothesized interactions between discharge destination, admission for COVID-19, and visitor policy. All variables were included in the multivariable models except for variables that we decided to exclude a priori due to possible collinearity with other variables in the models (unit COVID proportion occupied, unit proportion of COVID patients, and admission type). In addition, as less than 7 indicates low readiness and greater risk of readmission, a dichotomized RHDS score was also created to allow for a sensitivity analysis using logistic regression for determining the factors associated with a high readiness for discharge.

Some levels of race and ethnicity were combined for regression analysis due to low counts. Long-term acute care (LTAC) was collapsed into the “other discharge destination” category in regression models, which also included acute rehabilitation facility, homeless shelter, COVID-19 hotel, and “left against medical advice”. Unit Census Percentage Occupied was based on total occupancy divided by capacity, while Unit COVID-19 Percentage Occupied was based on the number of COVID-19 patients on the unit divided by capacity. Thus, a 40-bed unit with 20 patients, 4 of whom are COVID-19 patients, would be at 50% Census Percentage Occupied and 10% COVID-19 Percentage Occupied. For these variables, “Proportion” instead of “Percentage” indicates that the decimal value is used instead of the percentage value (e.g. 0.5 rather than 50). Day of Pandemic was based off how many days had passed since the hospital enacted pandemic measures on March 14, 2020. Data collection for this study was briefly halted at that time and restarted on April 22, 2020, so the “Day of Pandemic” variable for this dataset begins on day 39. For models, this variable was converted to “Month of Pandemic” to aid in interpretation of the coefficients. Estimates, 95% confidence intervals (CI), and p-values are reported; statistical significance is defined as p-values less than 0.05. All analyses were conducted using R v4.0.3.

2.3.3 Qualitative analysis

Transcripts were reviewed for accuracy before coding. Authors A.B., S.R., K.F., and K.S. engaged in coding of the transcripts. Deductive codes were initially created based upon the interview guides [24]. Additional inductive codes emerged during coding, were discussed with the team, and then added to the codebook. After coding was completed, we used a thematic analysis process of reviewing codes to discuss and identify key themes [25]. Disagreements were documented and discussed during weekly meetings until consensus was reached. Trustworthiness criteria [24] were addressed to support rigor throughout data collection and analysis. Credibility was addressed by peer review and weekly team meetings. Additionally, team members reviewed each other’s coding and engaged in reflexivity by discussing biases and assumptions, to ensure accuracy across coding. An audit trail was maintained throughout data collection and analysis.

3 Results

The quantitative sample included 638 unique GIM patients who completed the RHDS on the day of discharge. Twenty-two readmission events were excluded, bringing the total sample analyzed to 616 first-visit observations. See Table 1 for full demographic information about this sample and the additional 38 patients who completed interviews.

Table 1 Summary statistics
Full size table

3.1 Quantitative results

RHDS total and subscale scores were most affected by patients’ discharge destination; among non-COVID admissions, those discharged to home health (− 0.48 (− 0.95, − 0.02), p = 0.041) or SNF (− 1.39 (− 2.04, − 0.74), p < 0.001) versus the patient’s own home reported lower overall readiness scores (Table 2). This finding was confirmed in our sensitivity analysis in which RHDS was dichotomized as high vs low readiness (Table 3). However, on subscale scores, among non-COVID admissions, those discharged to SNF had lower personal status scores (− 1.79 (− 2.58, − 1.00), p < 0.001, Table 4) and lower knowledge scores (− 1.80 (− 2.88, − 0.71), p < 0.001, Table 5), but higher perceived coping ability (− 1.62 (− 2.34, − 0.91), p < 0.001, Table 6) when compared to those discharged to their own homes.

Table 2 Contributors to patient readiness for hospital discharge scale (RHDS) total score variance
Full size table
Table 3 Contributors to RHDS dichotomized categories of high (≥ 7) and low (< 7) discharge readiness
Full size table
Table 4 Contributors to personal status (RHDS subdomain) score variance
Full size table
Table 5 Contributors to knowledge (RHDS subdomain) score variance
Full size table
Table 6 Contributors to perceived coping ability (RHDS subdomain) score variance
Full size table

From the interaction between COVID-19 diagnosis and discharge destination we find that relative to non-COVID-19 admissions, COVID-19 patients discharged to a SNF rated their personal status [2.24 (0.87, 3.62), p < 0.001, Table 4] and coping ability [1.38 (0.14, 2.63), p = 0.030, Table 6] higher at discharge compared to those discharged to their own home. In contrast, relative to non-COVID-19 admissions those with a COVID-19 diagnosis and discharged to “other destination” reported significantly lower ratings for expected support [− 4.81 (− 7.98, − 1.63), p = 0.003, Table 7] compared to those discharged to their own home. From the interaction between discharge destination and hospital visitor policy, personal status varied by visitor policy where, relative to when one visitor was allowed, during a no visitation policy, those discharged to “other destination” reported higher personal status [2.55 (0.25, 4.84), p = 0.030, Table 4] when compared to those discharged to their own home.

Table 7 Contributors to expected support (PT-RHDS subdomain) score variance
Full size table

Age additionally influenced readiness scores, where adults 31–45 reported the lowest total readiness levels [− 0.46 (− 0.87, − 0.06), p = 0.025, Table 2] compared to the young adults 18–30, a finding that was also confirmed in our sensitivity analysis using the dichotomized RHDS total score (Table 3). Perceived coping ability after discharge varied by age where, again, those age 31–45 reported lower levels than the youngest adults (18–30) [− 0.46 (− 0.91, − 0.02), p = 0.042, Table 6]. No additional differences were found between age categories.

Finally, the only evidence of a system-level factor contributing to variability in discharge readiness ratings was for the expected support subscale, where increased percent occupancy was associated with increased expected support scale scores [1.75 (0.07, 3.44), p = 0.042, Table 7].

3.2 Qualitative results

Across interviews, participants identified three key themes related to their experiences of hospital-to-home transitions during the pandemic: (1) perceptions of discharge process; (2) influence of personal resources at home; (3) post-discharge impact of COVID-19. (See Table 8 for themes and exemplar quotes).

Table 8 Qualitative themes and exemplar quotes
Full size table

3.2.1 Theme 1: Discharge process during COVID-19

During interviews, participants mostly shared positive experiences of receiving discharge education and information packets. However, several participants identified negative aspects of the discharge process such as instructions delivered while they were not completely aware or were on pain medication. Due to COVID-19 restrictions, one participant shared not receiving verbal instructions, only the printed packet of information. Multiple participants shared feeling ill-prepared to know what to expect after leaving the hospital, particularly after a few months had passed. Overall, while most participants identified receiving helpful discharge education, several shared examples of lacking verbal explanations and experienced limited time spent on discharge instructions.

3.2.2 Theme 2: Influence of personal resources at home

The social resources of interview participants influenced how participants described the discharge process. Most participants identified having support networks at home and shared positive feedback of the discharge process and ability to follow discharge instructions. A few participants shared initial difficulty in performing activities of daily living (such as toileting, showering, etc.) and decreased mobility which became easier after time. Moreover, when participants were asked if they had access to recommended community resources, most denied accessing supportive services or failed to identify a need for community resources since they had support at home.

The experiences above were in contrast to participants with fewer resources or from out-of-state, who shared increased difficulty post-discharge. For example, one participant received preparation for the long car ride but did not receive instructions regarding home care. Another shared that where they are living was experiencing higher rates of COVID-19 that limited ability to follow through with physical therapy appointments.

3.2.3 Theme 3: Post-discharge impact of COVID-19

The impact of COVID-19 was most clearly seen post-discharge. Several participants shared that COVID-19 restriction resulted in more in-home aid post-discharge or had positive effects on their work situation as they could recover and work from home. In contrast, others discharged to a home in a different state shared struggles accessing resources such as finding available outpatient follow-up and therapy appointments.

4 Discussion

In this study, we explored the impact of COVID-19 system changes on patient-reported discharge readiness and transitions home during the pandemic. Our quantitative findings revealed that discharge destination most significantly impacts discharge readiness, rather than system changes during the pandemic, but that impact varies across different readiness constructs. Adult patients (vs. young and older adult patients) and those being discharged to places other than home or to out-of-state residences report lower readiness. For those discharged to a community setting other than to home or SNF, variability in the Personal Status discharge readiness subscale was additionally affected by the hospital visitor policy. In support of this finding, our interviews with participants who were primarily discharged to home revealed high personal readiness for discharge and coping. However, this group still noted gaps in discharge communication, homegoing preparation, and experienced barriers to needed follow-up care.

Contrary to what was expected, we found little evidence that the system changes occurring during Covid-19 impacted the overall readiness of patients discharged to home settings, even for those with an unplanned admission. While prior work suggested that higher unit census and larger size of units are associated with lower patient discharge readiness [21], the impact of unit on discharge readiness may be driven by additional intrinsic factors such as nursing staff level of education or experience that were not captured in our study. Conversely, it is possible that COVID-19 system changes had limited impact on those who were able to return home and had stable social network and resources, findings that align with other qualitative research conducted with patients from this parent study [26]. Further work to associate this with risk of readmission in the setting of COVID-19 and other system disruptions would help determine whether interventions can be tailored to prevent revisits/readmissions by avoiding inappropriate discharge location [27].

Across all scales, patients age 31–45 reported feeling less ready for hospital discharge. This suggests there are nuances to patient perception of readiness based on age, and aligns with prior work that found that those younger than 55 years were less ready for discharge on all subscales compared to those aged 55–64 [28]. It has been posited that age-based differences reflect the way that younger patients (< 50) are treated during the discharge process, where assumptions are made regarding the ability to cope at home resulting in less discharge teaching [8]. Our findings may also reflect the stress that this age range may be expecting in terms of balancing multiple competing priorities, such as work, family, and caregiving responsibilities upon returning home after hospitalization, particularly during the COVID-19 pandemic.

While the majority of prior data on patient readiness for discharge has been limited to patients returning home, one study reported that out of a population of readmitted patients, 28% felt unready to discharge on index hospitalization; this did not vary based on discharge destination [29]. Our data contradict these findings, suggesting that the discharge destination has an impact on the patient's readiness to be discharged and, thus, identifying a potential area for improving the quality of discharge support. Decisions to go to an institutional setting such as SNF or LTAC are driven by clinical and functional status, but can reflect a lack of support at home [30]. In the realities of clinical practice, discharge teaching regarding self-care is limited for patients discharged to home [21, 29] and may be much more limited for patients being discharged to institutional settings, with the assumption they will be receiving ongoing assistance and teaching as needed. However, the fact that non-COVID-19 patients discharged to SNF or LTAC report lower readiness across all readiness subscales likely shows a gap in support in discharge preparation. Similarly, interview participants who were discharged home, but lived in a different state than where they received hospital care, reported experiencing more post-discharge difficulties, which were compounded by COVID-19. Additional preparation may be needed for these patients, particularly when contact with their social networks is disrupted.

This study is limited in several ways. First, the important demographic variable of race/ethnicity was collapsed due to limited numbers represented across categories, and we did not have access to variables that may better indicate homegoing support such as marital status or clinical details such as length of stay or homegoing with medical devices that, in addition to demographic and social factors, have been shown to be associated with patient discharge readiness [31]. Further, while we believe that the system variables created capture contextual system disruptions during each discharge event, we were unable to include other potential variables indicating system disruptions and stressors during the pandemic. For example, given that discharge preparation is a core nursing function, and unit-based nurse staffing has been shown to impact RHDS, future studies should consider more comprehensively exploring whether and how nurse staffing strains during COVID-19 has impacted patient readiness. Additionally, interviews were conducted early in the pandemic with patients who were mainly discharged to home, limiting our ability to qualitatively explore the effect of discharge destination. Finally, we are unable to explain an outlying finding wherein increasing COVID-19 unit census contributed to improved expected support, suggesting the need to perhaps explore this variable and relationship in greater detail.

5 Conclusion

We found little evidence that hospital census and visitor policies during COVID-19 impacted patient-reported discharge readiness for the larger population of patients discharged from medicine units. Rather, our analyses uncovered patient populations likely in need of additional support during hospital discharge when contact restrictions or staffing limit in-person anticipatory planning: adult (vs. younger adult and older adult patients) being discharged to institutional settings. As health systems and clinicians continue to learn from the experiences of COVID-19, efforts aimed at improving hospital discharge, care transitions, and post-discharge outcomes may wish to give focused attention on these populations reporting lower discharge preparation.