Quality of Transition of Care from Hospital to Home for Patients Hospitalized for COVID-19

Abstract

Objective: To measure the quality of the transition of care for COVID-19 patients after discharge from hospital to home. Method: A cross-sectional, prospective study carried out in a hospital in Santa Catarina, with 201 patients hospitalized for COVID-19. An instrument was used to characterize the patients and the Brazilian version of the Care Transitions Measure. The data were analyzed using descriptive statistics, represented by absolute and relative frequency, and Cronbach’s alpha and parametric tests were used, including the t-test, considering statistical significance at p < 0.05. Results: There was a predominance of male patients (55.2%), with a mean age of 22.2 years (SD = 9.9), 79.6% white, and 60.2% married or in a stable union. The overall mean of the CTM-15 was 52.97, with the highest mean observed in the preparation for self-management factor (58.31) and the lowest in the care plan factor (34.00). Conclusion: The quality of the transition of care for patients hospitalized due to COVID-19 was unsatisfactory.

1. Introduction

Transition of care is a crucial process in delivering health services to ensure the coordination and continuity of patient care in different care settings [1,2]. Although it is an essential concept, its understanding is still limited and it is often confused with terms such as continuity of care, discharge planning, and coordination of care. Recent studies highlight the need to improve coordination between the various levels of healthcare to guarantee comprehensive care [3,4].

During the transition of care, patients, family members, caregivers, and health professionals are involved in meeting the patient’s individual needs. This process, which aims to bridge the gap between the hospital environment and the community, is key to avoiding adverse events such as medication errors and readmissions [5,6]. However, effective care transition strategies are still little explored, despite the obvious benefits, such as reduced length of stay and readmission rates [4,7,8].

Over time, integration and connectivity of care are crucial in a fragmented health system, especially in the face of challenges such as the COVID-19 pandemic [9]. Discharging these patients and others with comorbidities requires a joint commitment from the healthcare team, patients, and families to ensure an appropriate transition to primary healthcare to prevent unnecessary readmissions [10,11].

Evaluating the quality of care transitions is fundamental to improving transition practices and post-discharge management [12,13,14]. However, there are still significant gaps in the literature regarding the factors that influence the transition of care, especially in patients with COVID-19 and possible cases of long-term COVID-19 [13,14]. This study aims to measure the quality of the transition of care of patients with COVID-19 who have been discharged from hospital to home.

2. Materials and Methods

2.1. Study Context

This is a cross-sectional, prospective study with a quantitative approach, following the recommendations of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guideline [15].

2.2. Study Setting and Timeframe

The study was carried out at the Florianópolis Hospital, located in the greater Florianópolis area, in the state of Santa Catarina. The institution provides 100% of its services through the Unified Health System (UHS) and had 8234 patients in the year 2019, of which 737 were in general surgery, 4912 in clinical medicine, 1011 in orthopedics, and 1574 in pediatrics.

In 2020, due to the pandemic, the hospital became a reference for COVID-19, making all beds (wards and ICU) available and suitable for patients infected with the coronavirus. In 2021, schedules and activities resumed after the pandemic was controlled through vaccination.

Sociodemographic data, health conditions, and the Care Transitions Measure (CTM) questionnaire [16] were collected within 30 days of discharge to the community, by telephone, from 1 November 2020.

2.3. Population and Selection Criteria

The population consisted of 201 patients who were hospitalized for COVID-19 and discharged home between 1 November 2020 and 31 May 2021. Therefore, no sample calculation was carried out.

Inclusion criteria were: hospitalization for COVID-19 for more than 24 h; being over 18 years old; having been affected or being a family member of a person affected by COVID-19, requiring healthcare; having been discharged to the community.

The exclusion criteria: not being able to provide information for data collection, discharge due to death or hospital transfer.

Thirty-seven patients did not agree to take part. Two hundred and thirteen patients did not answer the phone after at least three attempts on different days and at different times, one hundred and sixty-nine died, and thirty-seven were excluded because they were not COVID-19 patients. This represents a total of 657 patients.

2.4. Instrument, Study Variables, and Data Collection

The instrument’s items are organized into four factors: Factor 1: “preparation for self-management” (items 4 to 6 and 8 to 11); Factor 2: “understanding of medication” (items 13 to 15); Factor 3: “preferences ensured” (items 1 to 3); and Factor 4: “care plan” (items 7 and 12). The CTM-15 Brazil consists of 15 items, with response options on a 4-point Likert scale (“Strongly disagree = 1”, “Disagree = 2”, “Agree = 3”, “Strongly agree = 4”, “Don’t know/don’t remember/not applicable = 0”). In this sense, the higher the score, the higher the quality of the transition of care.

The final CTM-15 score was calculated using a formula, converting the data into a linear scale from 0 to 100 points, with each individual’s score EC = [E/3] * 100, where E is the Individual’s Original Score and EC is the Standardized Score, as recommended by the instrument’s authors. However, in order to calculate the overall value of the survey, the authors advise measuring the answers and passing them on to a scale of 0 to 100; consequently, values above 51 would indicate an acceptable level of satisfaction [17].

In this study, we used the instrument translated into Portuguese for Brazil. According to (17) the authors, the instrument uses the criterion of a score above 70 as satisfactory, although there is no scientific evidence, it is just a convention. In this sense, we used a comparison with other studies and recognized the items or factors with the best or worst scores.

The variables were linked to sociodemographics such as age, gender, date of birth, marital status, municipality of residence, among others; health conditions; previous health history; and the Care Transitions Measure instrument to assess the quality of the transition of care—Brazilian version [16].

For prospective data collection, patients and their families were invited to participate in the study by telephone within 30 days of being discharged from the hospital to their homes, starting on 1 November 2020. A volunteer undergraduate nursing student duly trained to conduct the interviews participated in the data collection to ensure scientific rigor. Before collecting the data, a pilot test was carried out with volunteers from the research group to identify possible inconsistencies and/or biases during the interviews. Data collection only began once it had been confirmed that there were no irregularities.

First of all, the undergraduate nursing student phoned the research participants, introducing herself and explaining the research, its objectives, and how the data collection interview would be carried out. The Free and Informed Consent Term (FICT) was explained to those who agreed to take part. After verbal acceptance, the questionnaire on sociodemographic variables (self-reported) and health conditions and the Care Transitions Measure were administered. For patients who were unable to speak, a family member or caregiver took part in the interview. Data collection took place between 1 November 2020 and May 2021 from Monday to Friday during business hours.

2.5. Statistical Analysis

The data analyzed, such as sociodemographic variables and comorbidities, were represented by absolute and relative frequency. The CTM-15 items were represented by frequencies and by the mean and standard deviation. The 4 factors and the general factor, calculated from the CTM-15 items, were represented by mean and standard deviation as well as median and interquartile range (median [P25; P75]) and minimum and maximum. Cronbach’s alpha was also calculated for the 4 factors and the overall factor to measure the instrument’s internal consistency. The means of the CTM factors were compared with the sociodemographic and clinical variables using parametric tests; the t-test for independent samples was used to compare the means of variables with 2 categories and the analysis of variance (one-way ANOVA) to compare the means of variables with more than 2 categories. The significance level adopted was p < 0.05. The analyses were carried out using SPSS, v.25.

3. Results

The study included 201 patients who had been hospitalized for COVID-19 and discharged. There was a predominance of males, 55.2%, with a mean age of 22.2 (SD = 9.9). The majority were white (79.6%), married, or in a stable union (60.2%). Around 39.5% said they had studied up to secondary school, while 32.8% had higher education. Those who worked, were pensioners, or were retired accounted for 79.1%.

About the results of the CTM-15, the overall consistency of the scale was assessed using Cronbach’s alpha, resulting in 0.874. The overall CTM-15 score ranged from 58.31 to 34.00, with an average of 52.97. When evaluating the averages by factor, the highest score was found for preparation for self-management (58.31) and the lowest for the care plan (34.00) (

Table 1. Measure of central tendency and dispersion of the CTM-15 instrument, 2021. (N = 201).

	Mean (SD)	Min–Max	P50 [P25; P75]	N	Alpha
General CTM	52.97 (9.68)	31–87	55.56 [46.15; 60.00]	201	0.874
Preparation for self-management	58.31(13.58)	24–100	61.90 [47.62; 66.67]	201	0.895
Understanding of medication	53.66 (9.14)	33–100	55.56 [44.44; 55.56]	196	0.416
Preferences assured	52.47 (13.40)	11–100	55.56 [44.44; 66.67]	200	0.604
Care plan	34.00 (6.16)	8–100	33.33 [33.33; 33.33]	200	0.591

Source: Research data, 2021.

).

Analysis of the absolute and relative frequency of each of the options in the CTM-15 Brazil items showed that item 12 had the highest agreement rate (agree or agree very much), with 185 (93.9%) responses. Item 14 had the highest level of disagreement (strongly disagree or disagree), with 183 (93.4%) responses, as shown in Figure 1. It is worth noting that, as recommended by the instrument’s authors, the items answered with the option “Don’t know/don’t remember/not applicable” were not taken into account when calculating the average final score, as explained in

Table 2. Responses of participants regarding the CTM-15 Brazil, according to the items of the instrument, 2021. (N = 201).

	CATEGORIES
	Don’t Know/Don’t Remembe/Not Applicable	Strongly Agree	Agree	Strongly Disagree	Disagree	Mean (SD)
	n (%)	n (%)	n (%)	n (%)	n (%)
Item 1: Before leaving the hospital, the healthcare team and I agreed on goals for my health and how they would be achieved.	4 (2)	0 (0)	60 (29.9)	131 (65.2)	6 (3)	57.53 (17.04)
Item 2: The hospital staff considered my preferences and those of my family or caregiver in deciding what my health needs would be after I left the hospital.	3 (1.5)	2 (1)	97 (48.3)	98 (48.8)	1 (0.5)	49.83 (17.69)
Item 3- The hospital staff considered my preferences and those of my family or caregiver in deciding where my health needs would be met after I left the hospital.	9 (4.5)	3 (1.5)	94 (46.8)	92 (45.8)	3 (1.5)	49.83 (18.68)
Item 4: When I left the hospital, I had all the information I needed so that I could look after myself.	2 (1)	0 (0)	66 (32.8)	129 (64.2)	4 (2)	56.28 (16.86)
Item 5: When I left the hospital, I clearly understood how to look after my health.	12 (6)	1 (0.5)	51 (25.4)	133 (66.2)	4 (2)	58.02 (16.54)
Item 6: When I left the hospital, I clearly understood the warning signs and symptoms I should look out for to monitor my health condition.	5 (2.5)	3 (1.5)	78 (38.8)	102 (50.7)	13 (6.5)	54.59 (20.98)
Item 7: When I left the hospital, I received a written, legible, and easy-to-understand plan that described how all my health needs would be met.	6 (3)	4 (2)	179 (89.1)	11 (5.5)	1 (0.5)	34.87 (10.32)
Item 8: When I left the hospital, I had a good understanding of my health condition and what could make it better or worse.	8 (4)	1 (0.5)	48 (23.9)	143 (71.1)	1 (0.5)	58.20 (15.32)
Item 9: When I left the hospital, I had a good understanding of what I was responsible for in terms of looking after my health.	0 (0)	0 (0)	33 (16.4)	158 (78.6)	10 (5)	62.85 (14.98)
Item 10: When I left the hospital, I felt confident that I knew what to do to look after my health.	5 (2.5)	1 (0.5)	50 (24.9)	131 (65.2)	14 (7)	60.20 (18.59)
Item 11: When I left the hospital, I felt confident that I would be able to do the things I needed to do to look after my health.	12 (6)	1 (0.5)	51 (25.4)	127 (63.2)	10 (5)	59.08 (18.06)
Item 12: When I left the hospital, I was given a written, legible, and easy-to-understand list of appointments or tests that I needed to attend within the next few weeks.	4 (2)	7 (3.5)	185 (92)	4 (2)	1 (0.5)	33.16 (9.22)
Item 13: When I left the hospital, I clearly understood why I was taking each of my medications.	11 (5.5)	0 (0)	69 (34.3)	118 (58.7)	3 (1.5)	55.09 (16.99)
Item 14: When I left the hospital, I clearly understood how to take each of my medicines, including the quantity and timings.	5 (2.5)	0 (0)	6 (3)	183 (91)	7 (3.5)	66.84 (8.60)
Item 15: When I left the hospital, I clearly understood the possible side effects of each of my medications.	6 (3)	2 (1)	158 (78.6)	34 (16.9)	1 (0.5)	39.15 (13.97)

Source: Research data, 2021.

.

Table 3. Comparison of the means of the 4 factors of the CTM-15 with the clinical variables and comorbidities of patients hospitalized for COVID-19 in a hospital in SC, southern Brazil, 2021. N = 201.

	Preparation for Self-Management		Understanding of Medication		Preferences Secured		Care Plan
	Mean (SD) (n)	p	Mean (SD) (n)	p	Mean (SD) (n)	p	Mean (SD) (n)	p
Influenza 1
Negative	60.0 (13.7) (81)	0.068	53.9 (8.5) (78)	0.030	54.7 (12.9) (81)	0.283	33.3 (0.0) (81)	0.129
Positive	55.0 (13.0) (35)		50.2 (7.4) (33)		51.7 (15.5) (35)		32.4 (5.6) (35)
First hospitalization 1
No	59.4 (16.3) (20)	0.695	53.9 (11.0) (20)	0.897	50.0 (11.7) (20)	0.377	33.3 (0.0) (20)	0.695
Yes	58.1 (13.5) (173)		53.6 (9.1) (168)		52.8 (13.6) (172)		34.1 (8.8) (172)
Other hospitalization 3
2nd hospitalization	64.9 (12.7) (7)	0.351	55.6 (6.4) (7)	0.393	46.0 (11.9) (7)	0.275	33.3 (0.0) (7)	>0.999
3rd hospitalization	56.5 (17.7) (13)		53.0 (13.0) (13)		52.1 (11.5) (13)		33.3 (0.0) (13)
Severity of illness 2
Moderate	61.9 (11.9) (39)	0.149	53.4 (10.6) (38)	0.417	55.8 (11.0) (39)	0.082	33.8 (9.0) (39)	0.201
Critical	58.2 (12.2) (50)		54.0 (7.7) (47)		53.2 (13.3) (50)		33.0 (2.4) (50)
Severe	56.7 (13.5) (51)		55.9 (10.0) (51)		49.7 (14.0) (50)		36.3 (13.8) (50)
Hypertension 1
No	56.9 (14.4) (105)	0.131	53.3 (9.1) (101)	0.575	50.7 (12.7) (104)	0.058	34.0 (9.0) (104)	0.963
Yes	59.8 (12.6) (96)		54.0 (9.2) (95)		54.3 (13.9) (96)		34.0 (7.2) (96)
Diabetes mellitus 1
No	58.1 (13.2) (140)	0.783	53.5 (8.7) (135)	0.790	52.7 (13.4) (139)	0.744	34.2 (9.0) (139)	0.653
Yes	58.7 (14.5) (61)		53.9 (10.2) (61)		52.0 (13.5) (61)		33.6 (5.7) (61)
Chronic obstructive pulmonary disease 3
No	58.2 (13.5) (200)	-	53.6 (9.1) (195)	-	52.3 (13.2) (199)	-	34.1 (8.1) (199)	-
Yes	81.0 (0.0) (1)		66.7 (0.0) (1)		88.9 (0.0) (1)		16.7 (0.0) (1)
Asthma 1
No	57.9 (13.7) (184)	0.158	53.5 (9.3) (180)	0.584	52.1 (13.4) (183)	0.230	34.2 (8.4) (183)	0.386
Yes	62.8 (11.6) (17)		54.9 (7.6) (16)		56.2 (13.3) (17)		32.4 (4.0) (17)
Chronic respiratory disease 3
No	58.2 (13.7) (197)	0.647	53.7 (9.1) (192)	0.798	52.5 (13.5) (196)	0.993	34.0 (8.2) (196)	0.847
Yes	61.9 (6.7) (4)		52.8 (10.6) (4)		52.8 (10.6) (4)		33.3 (0.0) (4)
Chronic heart failure 1
No	58.4 (13.6) (186)	0.779	53.9 (9.3) (181)	0.263	52.1 (13.6) (185)	0.208	34.1 (8.5) (185)	0.743
Yes	57.4 (13.1) (15)		51.1 (6.7) (15)		56.7 (10.3) (15)		33.3 (0.0) (15)
Obesity 1
No	58.8 (14.6) (87)	0.662	54.4 (8.8) (85)	0.334	52.4 (12.8) (86)	0.940	33.3 (8.4) (87)	0.312
Yes	57.9 (12.8) (114)		53.1 (9.4) (111)		52.5 (13.9) (114)		34.5 (7.9) (113)
Smoking 3
No	58.3 (13.7) (193)	0.960	53.6 (9.2) (188)	0.411	52.6 (13.4) (192)	0.489	34.1 (7.9) (192)	0.770
Yes	58.5 (9.1) (8)		55.6 (8.4) (8)		50.0 (14.5) (8)		31.3 (13.9) (8)
Does physical exercise 1
No	59.0 (13.7) (151)	0.219	53.4 (9.1) (148)	0.456	53.5 (13.4) (150)	0.056	33.4 (6.2) (151)	0.091
Yes	56.3 (13.2) (50)		54.5 (9.4) (48)		49.3 (13.1) (50)		35.7 (12.3) (49)
Physical exercise 4
1x a week	59.1 (2.8) (2)	0.517	55.6 (0.0) (2)	0.628	44.4 (0.0) (2)	0.837	33.3 (0.0) (2)	0.916
2x a week	52.2 (14.1) (15)		52.4 (6.8) (14)		48.1 (11.6) (15)		34.4 (4.3) (15)
3x or more a week	57.9 (13.1) (33)		55.4 (10.6) (32)		50.2 (14.2) (33)		36.5 (14.9) (32)
No. of comorbidities 2
None	55.4 (16.5) (33)	0.536	54.3 (10.7) (32)	0.964	47.2 (13.2) (32)	0.107	32.8 (13.5) (33)	0.272
1 comorbidity	58.8 (12.7) (73)		53.3 (7.8) (70)		53.3 (12.7) (73)		34.3 (5.5) (72)
2 comorbidities	58.2 (13.1) (54)		53.6 (8.7) (53)		54.1 (12.7) (54)		35.5 (8.0) (54)
3 or more	59.9 (13.2) (41)		53.8 (10.7) (41)		52.8 (15.1) (41)		32.5 (6.4) (41)

Source: Research data, 2021. ¹ T-test for independent samples, ² Analysis of Variance (ANOVA), ³ Mann–Whitney test, ⁴ Kruskal–Wallis test.

shows that the mean of the CTM medication understanding factor among patients “without” influenza (mean = 53.9) is higher, with a statistically significant difference concerning the mean of patients “with” influenza (mean = 50.2) (p = 0.030), but without clinical significance. According to the data presented in Table 3 and

Table 4. Sociodemographic characterization of patients compared to the 4 factors of the CTM-15 Brazil, Santa Catarina, 2021. (N = 201).

	Preparation for Self-Management		Understanding of Medication		Preferences Secured		Care Plan
	Mean (SD) (n)	p	Mean (SD) (n)	p	Mean (SD) (n)	p	Mean (SD) (n)	p
Sex 1
Male	58.4 (13.9) (111)	0.902	53.6 (8.9) (109)	0.880	52.7 (13.2) (110)	0.812	33.3 (9.6) (110)	0.202
Female	58.2 (13.3) (90)		53.8 (9.5) (87)		52.2 (13.8) (90)		34.8 (5.9) (90)
Age 2
21 to 59	57.8 (14.1) (120)	0.822	53.6 (9.2) (116)	0.984	52.3 (13.1) (120)	0.966	33.9 (7.2) (119)	0.655
60 to 69	58.7 (10.3) (40)		53.6 (7.5) (40)		52.8 (13.7) (40)		33.3 (7.5) (40)
≥70	59.3 (15.1) (41)		53.9 (10.7) (40)		52.8 (14.3) (40)		35.0 (11.1) (41)
Spouse 1
Single/widowed/divorced	57.1 (13.5) (80)	0.327	53.2 (8.7) (79)	0.597	52.3 (14.3) (79)	0.850	33.3 (9.2) (79)	0.352
Married/stable union	59.1 (13.6) (121)		53.9 (9.5) (117)		52.6 (12.8) (121)		34.4 (7.4) (121)
Race 1
White	58.4 (14.0) (160)	0.835	54.0 (9.6) (157)	0.294	52.2 (13.5) (160)	0.501	34.0 (7.7) (159)	0.898
Black + Brown	57.9 (12.1) (41)		52.3 (7.2) (39)		53.8 (13.2) (40)		34.1 (9.8) (41)
Income ranges 2
Below 1 m.w.	60.7 (13.9) (32)	0.310	55.6 (8.5) (32)	0.059	52.9 (16.4) (31)	0.609	32.8 (6.7) (32)	0.808
Between 1 and 3 m.w.	56.8 (13.9) (120)		52.1 (8.6) (118)		51.7 (13.0) (120)		33.6 (8.4) (120)
Above 3 m.w.	59.5 (11.3) (18)		55.6 (5.7) (16)		54.9 (11.7) (18)		34.3 (6.9) (18)
Family income bracket 3
Below 1 m.w.	58.1 (13.2) (10)	0.874	52.8 (8.8) (10)	0.763	54.4 (12.2) (10)	0.455	36.7 (7.0) (10)	0.529
Between 1 and 3 m.w.	57.8 (13.9) (100)		54.8 (10.2) (99)		50.9 (13.3) (99)		34.0 (10.0) (100)
Between 4 and 6 m.w.	59.2 (12.0) (54)		52.4 (7.0) (53)		54.5 (13.4) (54)		34.0 (4.5) (54)
Above 7 m.w.	56.7 (15.2) (11)		53.1 (7.4) (9)		53.5 (13.0) (11)		34.8 (11.7) (11)
Read 4
No	54.0 (10.4) (4)	0.320	47.2 (5.6) (4)	0.096	52.8 (10.6) (4)	0.993	33.3 (0.0) (4)	0.847
Yes	58.4 (13.6) (197)		53.8 (9.2) (192)		52.5 (13.5) (196)		34.0 (8.2) (196)
Schooling 2
Up to 4th grade	59.9 (11.4) (28)	0.299	52.9 (8.4) (27)	0.511	54.9 (11.4) (27)	0.233	31.0 (9.8) (28)	0.160
5th to 8th grade	62.0 (15.0) (26)		55.3 (10.9) (26)		54.7 (15.4) (26)		35.3 (5.4) (26)
HS	56.5 (14.2) (77)		52.9 (7.8) (76)		50.1 (13.3) (77)		34.0 (8.3) (77)
IHE/CHE/ specialization	58.3 (13.4) (64)		54.7 (10.3) (61)		53.3 (13.6) (64)		34.9 (8.3) (63)
Remuneration 1
Does not work	59.7 (13.1) (42)	0.464	54.2 (11.5) (40)	0.693	53.8 (11.7) (42)	0.459	35.0 (6.2) (41)	0.400
Works/retired/pensioner	57.9 (13.7) (159)		53.5 (8.5) (156)		52.1 (13.8) (158)		33.8 (8.6) (159)
Hospitalization sector
COVID-19 hospitalization	58.3 (13.6) (201)	-	53.7 (9.1) (196)	-	52.5 (13.4) (200)	-	34.0 (8.2) (200)	-
Status 4
Discharged	58.5 (13.4) (198)	0.039	53.7 (9.2) (193)	0.231	52.6 (13.3) (197)	0.321	34.0 (8.2) (197)	0.868
Transferred	42.6 (16.0) (3)		48.1 (6.4) (3)		44.4 (19.2) (3)		33.3 (0.0) (3)

Source: Research data, 2021. ¹ T-test for independent samples, ² Analysis of Variance (ANOVA), ³ Kruskal–Wallis test, ⁴ Mann–Whitney test, HS: High School, IHE: Incomplete Higher Education, CHE: Complete Higher Education.

, no statistically significant differences were found between the CTM-15 factors and the sociodemographic and clinical variables of patients who were hospitalized and discharged to the community.

4. Discussion

Analysis of the results of this study provided an assessment of the quality of the transition of care from hospital discharge to home for patients hospitalized for COVID-19 in a hospital in southern Brazil.

The results revealed a total CTM-15 score considered unsatisfactory, diverging from previous studies that presented different averages. For example, while [1] found a satisfactory average, other studies such as [13,18,19] obtained higher averages.

The sociodemographic profile of COVID-19 patients in our study is in line with the findings of other national and international studies [13,18,20]. However, some studies have presented opposite results concerning patients’ gender, ethnicity, and marital status, highlighting the heterogeneity of these profiles [21]. The most commonly reported comorbidities in our results were hypertension and diabetes mellitus, corroborating other studies that have highlighted other chronic conditions [13].

The reliability analysis of the CTM-15 showed satisfactory internal consistency values, consistent with the findings of studies carried out in different geographical contexts, such as Sweden with 0.946 [22], China with 0.93 [23], Korea with 0.91 [24], Asia with 0.87 [25], and the Brazilian context with 0.92 [20], 0.876 [18], and 0.869 [13].

Specifically, items 12 and 14 of the CTM-15 Brazil related to the “care plan” and “understanding of medication” showed variations in the participants’ responses, reflecting the complexity and importance of these aspects during the transition of care [1,18]. Strategies to promote health education are fundamental to improving patients’ understanding of their post-discharge care [26].

In a study conducted with nurses in Portugal (2019), the importance of the information transmitted during the transition of care in the emergency department to ensure patient safety was highlighted. The use of a standardized document based on the identify, situation, background, recommendation (ISBAR) methodology was identified as fundamental to improving the quality of nursing care [27].

The need for discharge planning by the multi-professional team during hospitalization was also highlighted, to identify the patient’s needs and understanding of their health condition and set goals for home care [28].

In this study, factor 1 “preparation for self-management” showed a significant association with the variable “discharge”, indicating the importance of the patient understanding their health and goals for home care. This appropriate structuring of the transition of care at the time of hospital discharge is positively associated with a reduction in readmissions and patient satisfaction with care [7]

On the other hand, factor 2 “understanding of medication” was associated with those who had not been tested for influenza, highlighting the importance of patients understanding the medication prescribed. Inadequate health literacy was identified as a factor contributing to lower CTM scores, reflecting difficulties in understanding post-discharge medical instructions and self-care [24].

In factor 3 “assured preferences”, there was a significant association with the presence of comorbidities, such as hypertension, and the practice of physical exercise. This suggests that patients with comorbidities and those who practice physical activity have different preferences in the transition of care. The study [18] found significant differences between patients with primary and secondary cancer. This indicates variations in preferences during the transition of care depending on the patient’s type of cancer, highlighting the importance of considering the specific characteristics of each health condition when planning the transition of care.

As for factor 4 “care plan”, a lower average was observed, indicating weakness in the structuring and provision of official records for guidance at this stage. This situation may be related to the lack of institutional care transition programs and the need for strategies to guide these activities [19].

Previous research, such as that carried out in Rochester by [29], has shown the effectiveness of care transition programs, such as Mayo Clinic Care Transitions, in reducing hospital readmissions, emergency room visits, and total care costs. However, there are still challenges to overcome, such as fragmented communication and the lack of standardized processes between care providers.

Limitations

The limitations of this study are related to the difficulty of contacting the interviewees by telephone and the fact that the interview dealt with personal questions, which may have caused discomfort in answering over the phone. In addition, the results of the evaluation of the transition of care using the CTM-15 scale may have been affected by the families’ feelings of gratitude towards the health services. Family members may feel the need to respond positively because of the attention and care they receive during times of vulnerability. This may lead family members to respond according to what they think the interviewers would like to hear, emphasizing positive experiences. However, the study remains relevant, as this field of management, care, and patient profiling is still unexplored in Brazil.

5. Conclusions

The study revealed a low quality of care transition for patients hospitalized for COVID-19, with unsatisfactory scores on the CTM-15, with an overall average of 52.97. Although no significant differences were found between sociodemographic and clinical variables, the internal consistency of the instrument was considered good, in line with previous national and international studies developed with the adult population, children, and those with comorbidities.

These results offer important insights for healthcare professionals, especially nurses, allowing for more accurate assessments and the implementation of more effective actions during hospital discharge.

The implementation of care transition programs is essential to improve post-discharge follow-up, reducing complications and hospital readmissions, as well as reducing costs. Further research is needed to better understand the post-COVID-19 care transition and public policies are fundamental for this period, filling knowledge gaps and providing evidence for the adoption of care transition programs in Brazil.