IMPACT OF TRANSITION OF CARE ON CLINICAL OUTCOMES: HISTORICAL COHORTABSTRACT
Objective to verify the impact of transition of care on readmissions and deaths within 30 days after discharge of adult and elderly patients.
Method this is a historical cohort study conducted in a tertiary hospital in southern Brazil. All patients for whom contact was made with the healthcare network services for transition of care at discharge in 2019 were included. Data were analyzed using the Statistical Package for the Social Sciences version 20.0.
Result a total of 705 contacts were made with care network services for patient transitions of care at discharge. There were 3% losses to follow-up. Therefore, 684 patients were considered for readmission assessment and death within 30 days after discharge. Of the follow-ups agreed with the network services at discharge, 73.5% of them were carried out. When compared to the group of patients who had follow-up performed with the group that did not receive follow-up after discharge, the first group had lower rates of readmission and death within 30 days after discharge (for readmission: 19.7% vs. 28.7%; p=0.001 and for death: 5.8% vs. 13.8%; p=0.012).
Conclusion the results of this study reinforce the impact that transition of care has on readmissions and deaths after discharge, reaffirming the importance of coordination and communication between healthcare services in transition qualification and safety.
DESCRIPTORS:
Transitional care; Patient care team; Patient discharge; Patient readmission; Death
RESUMO
Objetivo: verificar o impacto da transição de cuidado nas reinternações e nos óbitos em 30 dias após a alta dos pacientes adultos e idosos.
Método: estudo de coorte histórica realizado em um hospital de nível terciário do sul do Brasil. Foram incluídos todos os pacientes para os quais foi realizado contato com os serviços da rede de atenção à saúde para transição de cuidado no momento da alta, no ano de 2019. Os dados foram analisados por meio do software Statistical Package for the Social Sciences (SPSS), versão 20.0.
Resultado: foram realizados 705 contatos com os serviços da rede de atenção para as transições do cuidado de pacientes no momento da alta. Ocorreram 3% de perdas de seguimento, sendo assim, 684 pacientes foram considerados para a avaliação da reinternação e óbito em 30 dias após a alta. Dos acompanhamentos pactuados com os serviços da rede no momento da alta, 73,5% deles foram realizados. Quando comparados ao grupo de pacientes que tiveram acompanhamento realizado com o grupo que não recebeu acompanhamento após a alta, o primeiro grupo teve menores taxas de reinternação e óbito em 30 dias após a alta (para reinternação: 19,7% vs. 28,7%; p=0,001 e para óbito: 5,8 % vs. 13,8 %; p=0,012).
Conclusão: os resultados do estudo reforçam o impacto que a transição de cuidado tem nas reinternações e nos óbitos após a alta, reafirmam a importância da articulação e da comunicação entre os serviços de saúde na qualificação e segurança das transições.
DESCRITORES:
Cuidado de transição; Equipe de assistência ao paciente; Alta do paciente; Readmissão do paciente; Óbito
RESUMEN
Objetivo verificar el impacto de la transición de la atención en los reingresos y las muertes dentro de los 30 días posteriores al alta de pacientes adultos y ancianos.
Método: estudio de cohorte histórica realizado en un hospital terciario del sur de Brasil. Se incluyeron todos los pacientes que tuvieron contacto con servicios de la red de atención de salud para transición de atención en el momento del alta en 2019. Los datos fueron analizados mediante el software Statistical Package for the Social Sciences (SPSS), versión 20.0.
Resultado se realizaron 705 contactos con los servicios de la red asistencial para las transiciones de atención del paciente al momento del alta. Hubo pérdidas del 3% durante el seguimiento. Por lo tanto, se consideraron 684 pacientes para la evaluación de reingreso y muerte dentro de los 30 días posteriores al alta. De los seguimientos acordados con los servicios de la red en el momento del alta, se realizaron el 73,5% de los mismos. En comparación con el grupo de pacientes a los que se les realizó seguimiento con el grupo que no recibió seguimiento después del alta, el primer grupo tuvo tasas más bajas de reingreso y muerte dentro de los 30 días posteriores al alta (para reingreso: 19,7% vs. 28,7 %; p=0,001 y para muerte: 5,8 % vs. 13,8 %; p=0,012).
Conclusión los resultados del estudio refuerzan el impacto que la transición de la atención tiene en los reingresos y muertes después del alta, reafirmando la importancia de la coordinación y comunicación entre los servicios de salud en la calificación y seguridad de las transiciones.
DESCRIPTORES:
Cuidado de transición; Grupo de atención al paciente; Alta del paciente; Readmisión del paciente; Muerte
INTRODUCTION
Hospitals around the world are seeking to improve bed management by reducing hospital stays and readmission rates. However, improving these indicators is not a simple task, as it involves the need to improve care and management processes, optimizing bed use, ensuring patient safety and continuity of healthcare. In this context, hospital efficiency plays a fundamental role, representing the ability to maximize healthcare service production with available resources, aiming to deliver effective services and minimize costs2.
In Brazil, research has found 30-day readmission rates of 14 and 18.1%3-4, whereas in the United States, these rates range from 11.9 to 14.9%5-6. To improve these indicators, it is important to implement comprehensive strategies that improve care during hospitalization and ensure continuity after hospital discharge.
In pursuit of these goals, a mandatory federal program to reduce hospital readmissions was implemented in the United States, which holds hospitals accountable and encourages coordination and quality of care during transition of care. The program reduced readmission rates and saved Medicare $564 million in 20186.
Fragmentation of care, disarticulation between Healthcare Networks (RAS - Redes de Atenção à Saúde) and lack of knowledge about services make continuity of care difficult and can lead to losses in patient care7. When there are no flows and mechanisms for transferring information, there is the risk of being lost during care. Authors highlighted that bringing hospital care professionals closer to Primary Health Care (PHC) professionals would eliminate the lack of knowledge about professional skills, flows and limitations of services8.
It is known that the efficiency of hospital care depends on the organization and performance of the network that surrounds it. The efficiency of PHC is determined by the increase in the number of Family Health Strategies, and this leads to increased access to services, a reduction in unnecessary hospitalizations and a drop in mortality. Therefore, hospital efficiency is directly linked to the efficiency of PHC 2.
For all these reasons, it is necessary to adopt strategies for transfer of care, which are coordinated and executed by healthcare professionals so that they go beyond the simple act of referring patients to seek post-discharge follow-up within the network, but which promote continuity and comprehensiveness of care7,8.
An important strategy that assists multidisciplinary teams and ensures comprehensive patient care during and after hospitalization is transition of care. It encompasses all interventions that coordinate patient care throughout their care in healthcare services. Transition of care focuses on patients’ and caregivers’ needs, and the main points of this process are education and provision of information about care1.
Post-discharge care is continued through telephone calls, home visits (HVs), outpatient appointments or with the support of Home Care Services (HCS). The use of technology in healthcare services is also a strategy that has been gaining ground9.
Researchers give examples of use of technology, such as mobile phone applications or automatic alerts triggered by systems interconnected between care networks. These examples contribute to qualification of care and to a safer transition for patients after discharge from hospital9.
Some studies point to several benefits of transition of care, the main one being a reduction in readmissions9,10. A randomized clinical trial that compared patients admitted to hospital with patients receiving home care showed that patients receiving home care had the lowest 30-day readmission rates (7% versus 23%)10. Reduction in mortality, hospital costs and adverse events are also positive outcomes of transition of care9.
Hospitals in several countries have been organizing specific teams and/or professionals to manage discharges7,8,11. These teams are multidisciplinary and aim to assist in organizing hospital discharge, serving as a link between healthcare professionals, patients and the RAS11. In countries such as Canada and Spain, there are specific nurses who are responsible for coordinating discharge7,8.
A tertiary hospital in southern Brazil implemented a discharge management team in 201711. This team is made up of physicians, nurses, social workers, pharmacists and nursing interns, and works to organize pending matters for hospital discharge as well as throughout the entire transition of care process.
Among the daily activities carried out, the coordination with the RAS for continuity of patient care after discharge stands out. At this time, the discharge management team contacts the network services to inform patients of hospital discharge and organize continuity of care. This contact occurs between 24 and 48 hours before or after discharge, and serves to agree with the reference health team on the type of follow-up that patients will receive after discharge, including HVs, outpatient or health unit appointments, follow-up of dressings, participation in groups and links with specialized care services.
Some patients are discharged with instructions for follow-up by the municipality’s HCS, and, in these cases, the discharge management team acts as a facilitator for contact among medical teams, ensuring that relevant information about patients is shared in a timely manner.
Considering the importance of the performance of this discharge management team in post-discharge transition of care, given the relevance of the topic and the scarcity of studies in developing countries on the effect of transition of care on healthcare services, this research aimed to verify the impact of transition of care on readmissions and deaths within 30 days after discharge of adult and elderly patients.
METHOD
This is a historical cohort study conducted in the Discharge Management Office of a tertiary hospital in southern Brazil. The sample consisted of all patients for whom the discharge management team contacted RAS services for transition of care at discharge in 2019. The criteria for selecting patients requiring follow-up after discharge were having a high risk of readmission according to the Hospital Score12 and/or requiring complex care (with dressings, invasive devices, among others) and/or having difficulty adhering to treatment and/or requiring rehabilitation and being discharged from the wards.
After 30 days of discharge of these patients, a nurse or social worker from the Discharge Management Office contacted patients and/or family members by telephone to confirm whether the follow-up agreed with RAS services were carried out. During this contact, it was also verified whether a patient had been readmitted or had died after discharge. When encountering difficulties with the calls (non-existent numbers or ineffective contact), this information was sought in the patients’ electronic medical record, in the Unified Health System (e-SUS (Sistema Único de Saúde)) information system or in the State Hospitalization Management System (Gerint - Gerenciamento de Internações).
Data analysis took place in December 2020. The variables collected through review of electronic medical records were age, sex, race, city, marital status, main ICD, comorbidities, level of care complexity (Perroca Scale)13, risk of pressure injury (Braden Scale for Predicting Pressure Sore Risk)14, risk of falls (Morse Fall Scale)15, Charlson Comorbidity Index16, previous oncology hospitalization, medical specialty of hospitalization, length of hospital stay, follow-up for post-discharge care, follow-up performed after 30 days of discharge and as an outcome, readmission and death after 30 days of discharge.
The collected data were tabulated in a Microsoft Excel® spreadsheet and analyzed using the Statistical Package for the Social Sciences (SPSS) version 20.0.
Descriptive analysis was performed using absolute and relative frequency, for categorical variables, and mean and standard deviation, for continuous variables with normal distribution. Median was used for continuous variables without normal distribution. Normality of variables was assessed using the Shapiro-Wilk test. Prevalence rates were compared among groups using the chi-square test. Means were compared using Student’s t-test, and the Mann-Whitney U test was used to compare medians.
Univariate Poisson regression with robust variance was used for these outcomes to assess which factors were independent predictors of readmission and death. The inclusion criteria in the multivariable model were p<0.1 in the univariate regression or clinical relevance of the variable, in which p<0.05 was considered statistically significant. In these models, the variables of interest were analyzed together with other risk factors (confounders) for their effect on the outcome.
The research was approved by Research Ethics Committees.
RESULTS
In 2019, the discharge management team performed 705 transitions of care at patient discharge. Of these, 21 (3%) were unable to assess whether the agreed follow-up was performed or not within 30 days after discharge, therefore being considered follow-up losses. A total of 684 patients were considered for assessing readmission and death outcomes. Table 1 shows the characteristics of patients in each group (follow-up performed or not performed).
The mean age and Charlson Comorbidity Index score were 64.3 years and 3.7, respectively. The ICDs found as the main reasons for hospitalization were diseases of the circulatory system and neoplasms. The most common comorbidities were cerebrovascular disease, peripheral vascular disease, diabetes, heart failure (HF), solid tumor and chronic lung disease.
Of the follow-ups agreed upon at discharge with the health system teams, 73.5% were carried out. The main types of follow-ups for continuity of care were with PHC (39.5% for HV and 24.3% for appointments at the health unit), link with HCS (24.3%) and specialized outpatient appointment (8.9%).
Patients from the capital had more follow-ups than patients from the metropolitan region (p=0.001). Patients with intensive and semi-intensive care needs, according to the Perroca Scale, had more follow-ups than patients with minimal care (p=0.005). Other patient characteristics did not show significant differences among groups.
Regarding the outcomes assessed (Table 2), patients who were followed-up had lower rehospitalization rates and lower incidence of death than patients who did not have post-discharge follow-up (for rehospitalization: 19.7% vs. 28.7%; p=0.001 and for death: 5.8% vs. 13.8%; p=0.012).
Table 3 shows the characteristics of patients with and without readmission and their relative risk estimates, confidence intervals and p-values for univariate and multivariate analysis. Between these two groups, no differences were observed in marital status, location, urgency of admission and length of hospital stay. The characteristics that were included in the multivariate analysis were age (p=0.021), race (p=0.074), solid tumor diagnosis (p=0.053), chronic lung disease (p=0.014), metastatic cancer (p=<0.001), moderate to severe kidney disease (p=0.005), Perroca Scale (p of <0.001 for intensive and semi-intensive care and p of 0.014 for intermediate care when compared to minimum care), previous oncological hospitalization (p=0.002), median number of previous hospitalizations in one year (p=<0.001), agreed follow-up carried out (p=0.010). The Charlson was not included in the multivariate analysis, and comorbidities were included individually.
Characteristics of patients with and without readmission for univariate and multivariate analysis. 2019. Porto Alegre (RS), Brazil
The characteristics that maintained statistical significance in the multivariate analysis for readmission outcome were metastatic cancer (p=0.007) and moderate to severe kidney disease (p=0.005), Perroca Scale (p of 0.005 for intensive and semi-intensive care and p of 0.046 for intermediate care when compared to minimum care), previous oncological hospitalization (p=0.031), median number of previous hospitalizations in one year (p=<0.001) and agreed follow-up carried out (p=0.003).
Table 4 shows the characteristics of patients with and without death outcome and their relative risk estimates, confidence intervals, and p-values for univariate and multivariate analysis. Between these two groups, no differences were observed in sex, race, marital status, location, urgency of hospitalization, length of hospitalization, and median number of previous hospitalizations in one year. The characteristics that were included in the multivariate analysis were age (p=<0.001), peripheral vascular and aortic disease (p=0.062), diabetes with complications (p=0.008), chronic lung disease (0.002), metastatic cancer (p=<0.001), dementia (p=0.028), Perroca Scale (p of 0.005 for intensive and semi-intensive care and p of 0.023 for intermediate care when compared to minimum care), previous oncological hospitalization (p=<0.001), agreed follow-up carried out (p=0.010) and service (p of 0.012 for specialties and p of 0.007 for surgeries when compared to internal medicine service). The Charlson score was not included in the multivariate analysis, and comorbidities were included individually.
Characteristics of patients with and without death for univariate and multivariate analysis. 2019. Porto Alegre (RS), Brazil.
The characteristics that maintained statistical significance in the multivariate analysis for death outcome were the presence of metastatic cancer (p=0.001), Perroca Scale (p of 0.018 intensive and semi-intensive care when compared to minimum care) and agreed follow-up carried out (p=<0.001).
DISCUSSION
In this study, patients’ mean age was 64.3 yearsl, and 56.7% were male. It is common in studies on transition of care, readmission and death to find a population mostly over 60 years old17-19. Elderly patients are the users who most seek care in the health network worldwide, and account for more than half of all hospital admissions. This fact is related to the various chronic diseases and their complications20.
The results of this study demonstrated the greater capacity for effective post-discharge follow-ups carried out in the capital, with a significant difference in relation to the metropolitan region (79% vs. 65%, respectively). Patients usually encounter difficulties in obtaining same-day appointments, and encounter long waiting times for appointments with certain medical specialties and for rehabilitation care. One distinguishing feature of the capital is that it has HCS throughout its territory, whereas few metropolitan municipalities have this service.
The difficulty encountered in accessing public healthcare services in Brazil, especially in municipalities in metropolitan regions, is related to the profound regional inequalities, an important characteristic of the country’s healthcare service21,22. Furthermore, researchers identified a scenario of increased demand and reduced access, which was repeated in almost all states and capitals in Brazil22.
One factor that significantly impacted follow-up implementation was the complexity of care, with most follow-ups being carried out on patients with intensive and semi-intensive care, probably due to the need to prioritize these services by the network.
The researchers concluded that age and male sex are significantly associated with increased risk of readmission and death19. However, in this study, only age was associated with these outcomes.
Additionally, diseases such as HF, Chronic Obstructive Pulmonary Disease (COPD), pneumonia, and metastatic cancer feature prominently in many studies on readmission and death17-19,23. In this study, the diseases most related to readmission were metastatic cancer (RR=1.8; p=0.007) and moderate to severe kidney disease (RR=1.9; p=0.005), and related to death was metastatic cancer (RR=4.6; p=0.001).
Hospitals need to create strategies to improve their performance and quality indicators, and implementing patient transitions of care at discharge helps to improve this, as it has an impact on readmissions, deaths and hospital costs. A systematic review and meta-analysis concluded that post-discharge transitions of care reduced readmissions by 32% within 30 days and 28% within six months, in addition to being cost-effective, by reducing the use of health resources24.
Creating links and coordinating this patient transition with the RAS points is important to encourage maintenance and follow-up of care by the network itself. Transition of care activities carried out by the discharge management team resulted in 73.5% of the follow-ups being carried out, i.e., most patients received some follow-up after discharge carried out by other services. Thus, it is understood that the contact made by the hospital team caused most of the network services to seek to meet the demand and the agreement made at the time a patient was being discharged.
This study also shows that the group of patients who received some follow-up after discharge had significantly lower rates of readmission and death within 30 days compared to the group that did not receive any follow-up. This result supports other studies that also found positive results with continuity of care after discharge and that emphasized the importance of discharge planning as well as carrying out transitions of care among services in the care network18,24,25.
The main forms of continuity of care implemented in this study were HVs, appointments in PHC and follow-up with HCS. Some authors stated that each intervention after discharge results in important improvements in patients’ health, but concluded that HVs were more economical and effective than other transitional care such as calls made by nurse case managers or outpatient appointments23.
Another important aspect is that the group of patients who were readmitted and died within 30 days had a higher Charlson score than the group who were not readmitted and did not die. Patients with multiple comorbidities and in worse physical condition are more likely to be readmitted within 30 days, which is why transition of care becomes so important, especially in these cases17,18.
Through multivariate analyses, it was identified that patients with intensive and semi-intensive care, according to the Perroca Scale, had a higher risk of readmission (RR=1.9; p=0.005) and death (RR=3.3; p=0.018). Other studies that analyzed the relationship between the complexity of patient care and readmissions and deaths concluded that patients with more complex care have a higher risk of these outcomes26,27.
The researchers associated individual factors of care complexity, including broader health, functional and psychosocial problems, with mortality and adverse events, and found that the frequency of these events increased as risk factors increased26. In an analysis of readmissions, patients who required greater care due to, for instance, poor functional status, need for a feeding tube and polypharmacy were prevalent in the group that was readmitted27.
Based on data from the literature together with those found in this research, it can be inferred that patients with a degree of complexity of semi-intensive and intensive care are more likely to be readmitted and die within 30 days. Patients become complex not only due to their multiple chronic conditions, but also due to socioeconomic, cultural and environmental factors26. Identifying the degree of complexity of patients during hospitalization enables implementing care planning by the entire multidisciplinary team, seeking to qualify the discharge and transition of care process26-28.
In the transition of care process, multidisciplinary participation is essential, but the role of nurses is fundamental in organizing hospital discharge and in continuity of care after discharge. Competencies such as comprehensive care, holistic vision, ease of communication and teamwork help nurses identify patients who need care after discharge and play a key role in this management. These competencies also make this professional the facilitator of post-discharge care, as they provide safety and satisfaction to patients, avoiding complications and the need to return to the hospital29,30.
There are some limitations to this study. Since it is a historical cohort study, secondary data collected from medical records were used. Concerning the assessment of outcomes at 30 days, there were losses, albeit few (3%). Moreover, this is a single-center study that limits external validity for some contexts, even within Brazil, with its continental dimensions and regional inequalities.
CONCLUSIONS
The results of this research reinforce the importance and impact that transition of care has on readmissions and deaths within 30 days after discharge, since the group of patients who had continuity of care had the lowest rates of readmission and death. It is worth noting that the result found was that patients with more complex care have a higher risk of readmission and death. Hospital institutions can seek to identify these patients and, based on this, organize continuity of care with extra-hospital services.
The study also reaffirms the importance of coordination and communication among healthcare services in improving the quality and safety of transition of care. Communication between discharge management and RAS teams was essential for them to commit to continuing to care for patients who left the hospital.
The positive results obtained through the discharge management team’s work, with professionals trained to carry out this activity, show that this work has become increasingly necessary in hospital settings, as multidisciplinary action in transition of care qualifies the care process.
REFERENCES
-
1. Shahsavari H, Zarei M, Aliheydari MJ. Transitional care: Concept analysis using Rodgers’ evolutionary approach. Int J Nurs Stud [Internet]. 2019 [cited 2022 Nov 11];99:103387. Available from: https://doi.org/10.1016/j.ijnurstu.2019.103387
» https://doi.org/10.1016/j.ijnurstu.2019.103387 -
2. Araujo EC, Lobo MSC, Medici AC. Eficiência e sustentabilidade do gasto público em saúde no Brasil. J Bras Econ Saúde [Internet]. 2022 [cited 2024 Mar 19];14 Suppl 1:86-95. Available from: https://www.researchgate.net/publication/359862430_Efficiency_and_sustainability_of_public_health_spending_in_Brazil_Eficiencia_e_sustentabilidade_do_gasto_publico_em_saude_no_Brasil
» https://www.researchgate.net/publication/359862430_Efficiency_and_sustainability_of_public_health_spending_in_Brazil_Eficiencia_e_sustentabilidade_do_gasto_publico_em_saude_no_Brasil -
3. Pivatto Júnior F, Ulbrich AHDPS, Gheno J, Fisch MA, Petry RC, Nunes TS, et al. Accuracy of the Simplified HOSPITAL Score to Predict Nonelective Readmission in a Brazilian Tertiary Care Public Teaching Hospital. Qual Manag Health Care [Internet]. 2022 [cited 2022 Nov 08];32(1):30-4. Available from: https://pubmed.ncbi.nlm.nih.gov/35383714/
» https://pubmed.ncbi.nlm.nih.gov/35383714/ -
4. Canto DF, Costa FM, Júnior FP, Paskulin LMG, Dora JM. Performance of the Simplified HOSPITAL Score for Risk Assessment of Hospital Readmission in a Brazilian Tertiary Public Hospital. Am J Med Qual [Internet]. 2022 [cited 2022 Nov 08];37(1):88-9. Available from: https://pubmed.ncbi.nlm.nih.gov/34117167/
» https://pubmed.ncbi.nlm.nih.gov/34117167/ -
5. Jung DH, DuGoff E, Smith M, Palta M, Gilmore-Bykovskyi A, Mullahy J. Likelihood of hospital readmission in Medicare Advantage and Fee-For-Service within same hospital. Health Serv Res [Internet]. 2020 [cited 2022 Nov 11];55(4):587-95. Available from: https://doi.org/10.1111/1475-6773.13315
» https://doi.org/10.1111/1475-6773.13315 -
6. Mitchell AP, Gregg CF, Larry AA, Karen EJM, Mona F, Paul H, et al. The Hospital Readmissions Reduction Program: Nationwide Perspectives and Recommendations: A JACC: Heart Failure Position Paper. JACC: Heart Failure [Internet]. 2020 [cited 2024 Mar 16];8(1):1-11. Available from: https://doi.org/10.1016/j.jchf.2019.07.012
» https://doi.org/10.1016/j.jchf.2019.07.012 -
7. Mauro AD, Cucolo DF, Perroca MG. Hospital - primary care articulation in care transition: Both sides of the process. Rev Esc Enferm USP [Internet]. 2021 [cited 2024 Mar 16];55:e20210145. Available from: https://doi.org/10.1590/1980-220X-REEUSP-2021-0145
» https://doi.org/10.1590/1980-220X-REEUSP-2021-0145 -
8. Costa MFBNA, Andrade SR, Soares CF, Pérez EIB, Bernardino E. A continuidade do cuidado de enfermagem hospitalar para a Atenção Primária à Saúde na Espanha. Rev Esc Enferm USP [Internet]. 2019 [cited 2022 Nov 08];53:e03477. Available from: https://doi.org/10.1590/s1980-220x2018017803477
» https://doi.org/10.1590/s1980-220x2018017803477 -
9. Gheno J, Weis AH. Care transition in hospital discharge for adult patients: Integrative literature review. Texto Contexto Enferm [Internet]. 2021 [cited 2022 Nov 08];30:e20210030. Available from: https://doi.org/10.1590/1980-265X-TCE-2021-0030
» https://doi.org/10.1590/1980-265X-TCE-2021-0030 -
10. Levine DM, Ouchi K, Blanchfield B, Saenz A, Burke K, Paz M, et al. Hospital-level care at home for acutely ill adults a randomized controlled trial. Ann Intern Med [Internet]. 2020 [cited 2022 Nov 08];172(2):77-85. Available from: https://doi.org/10.7326 / M19-0600
» https://doi.org/10.7326 / M19-0600 - 11. Jotz GP, Júnior WC, Kruel AJ, Klug D, Duarte ES, Kraemer FZ, Azevedo ROO. Inovação e Tecnologia no Enfrentamento da Superlotação Hospitalar: a experiência do Hospital Nossa Senhora da Conceição - Porto Alegre/RS. Porto Alegre, RS(BR): Grupo Hospitalar Conceição; 2018.
-
12. Mathys P, Bütikofer L, Genné D, Leuppi JD, Mancinetti M, John G, et al. The Early HOSPITAL Score to Predict 30-Day Readmission Soon After Hospitalization: A Prospective Multicenter Study. J Gen Intern Med [Internet]. 2023 [cited 2024 Mar 16]. Available from: https://doi.org/10.1007/s11606-023-08538-0
» https://doi.org/10.1007/s11606-023-08538-0 -
13. Perroca MG, Gaidzinski RR. Sistema de classificação de pacientes: Construção e validação de um instrumento. Rev Esc Enferm USP [Internet]. 1998 [cited 2022 Nov 08];32(2):153-68. Available from: https://doi.org/10.1590/S0080-62341998000200009
» https://doi.org/10.1590/S0080-62341998000200009 -
14. Jansen RCS, Silva KBA, Moura MES. Braden Scale in pressure ulcer risk assessment. Rev Bras Enferm [Internet]. 2020 [cited 2024 Mar 16];73(6):e20190413. Available from: https://doi.org/10.1590/0034-7167-2019-0413
» https://doi.org/10.1590/0034-7167-2019-0413 -
15. Urbanetto JS, Creutzberg M, Franz F, Ojeda BS, Gustavo AS, Bittencourt HR, et al. Morse fall scale: tradução e adaptação transcultural para a língua portuguesa. Rev Esc Enferm USP [Internet]. 2013 [cited 2022 Nov 08];47(3):569-75. Available from: https://doi.org/10.1590/S0080-623420130000300007
» https://doi.org/10.1590/S0080-623420130000300007 -
16. Glasheen WP, Cordier T, Gumpina R, Haugh G, Davis J, Renda A. Charlson Comorbidity Index: ICD-9. Am Health Drug Benefits [Internet]. 2019 [cited 2022 Nov 08];12(4):188-97. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6684052/
» https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6684052/ -
17. Samuel EV, Viggeswarpu S, Wilson BP, Ganesan MP. Readmission rates and predictors of avoidable readmissions in older adults in a tertiary care centre. J Family Med Prim Care [Internet]. 2022 [cited 2024 Mar 16];11(9):5246-53. Available from: https://journals.lww.com/jfmpc/fulltext/2022/09000/readmission_rates_and_predictors_of_avoidable.47.aspx
» https://journals.lww.com/jfmpc/fulltext/2022/09000/readmission_rates_and_predictors_of_avoidable.47.aspx -
18. Kripalani S, Chen G, Ciampa P, Theobald C, Cao A, McBride M, et al. A transition care coordinator model reduces hospital readmissions and costs. Contemp Clin Trials [Internet]. 2019 [cited 2022 Nov 15];81(615):55-61. Available from: https://doi.org/10.1016/j.cct.2019.04.014
» https://doi.org/10.1016/j.cct.2019.04.014 -
19. Fry CH, Fluck D, Han TS. Frequent identical admission-readmission episodes are associated with increased mortality. Clin Med J R Coll Physicians London [Internet]. 2021 [cited 2022 Nov 15];21(4):E351-6. Available from: https://doi.org/10.7861/clinmed.2020-0930
» https://doi.org/10.7861/clinmed.2020-0930 -
20. Vos T, Lim SS, Abafati C, Abbas KM, Abbasi M, Abbasifard M, et al. Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: A systematic analysis for the Global Burden of Disease Study 2019 [Internet]. Lancet. 2020 [cited 2024 Mar 16];396:1204-22. Available from: https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30925-9/fulltext
» https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)30925-9/fulltext -
21. Azevedo E, Silva G, Giovanella L, Camargo Jr KR. Brazil’s National Health Care System at risk for losing its universal character. Am J Public Health [Internet]. 2020 [cited 2024 Mar 16];110(6):811-2. Available from: https://doi.org/10.2105/AJPH.2020.305649
» https://doi.org/10.2105/AJPH.2020.305649 -
22. Malta DC, Gomes CS, Prates EJS, Santos FP, Almeida WS, Stopa SR, et al. Analysis of demand and access to services in the last two weeks previous to the National Health Survey 2013 and 2019. Rev Bras Epidemiol [Internet]. 2021 [cited 2024 Mar 16];24 Suppl 2. Available from: https://doi.org/10.1590/1980-549720210002.supl.2
» https://doi.org/10.1590/1980-549720210002.supl.2 -
23. Blum MR, Øien H, Carmichael HL, Heidenreich P, Owens DK, Goldhaber-Fiebert JD. Cost-effectiveness of transitional care services after hospitalization with heart failure. Ann Intern Med [Internet]. 2020 [cited 2022 Nov 08];172(4):248-57. Available from: https://doi.org/10.7326/M19-1980
» https://doi.org/10.7326/M19-1980 -
24. Ran L, Jiawei G, Jibin L, Gaoren W, Therese H. Effectiveness of integrating primary healthcare in aftercare for older patients after discharge from tertiary hospitals-a systematic review and meta-analysis. Age Ageing [Internet]. 2022 [cited 2024 Mar 16];51(6):afac151. Available from: https://doi.org/10.1093/ageing/afac151
» https://doi.org/10.1093/ageing/afac151 -
25. Vernon D, Brown JE, Griffiths E, Nevill AM, Pinkney M. Reducing readmission rates through a discharge follow-up service. Futur Healthc J [Internet]. 2019 [cited 2022 Nov 08];6(2):114-7. Available from: https://doi.org/10.7861/futurehosp.6-2-114
» https://doi.org/10.7861/futurehosp.6-2-114 -
26. Adamuz J, Juvé-Udina ME, González-Samartino M, Jiménez-Martínez E, Tapia-Pérez M, López-Jiménezet MM, et al. Care complexity individual factors associated with adverse events and in-hospital mortality. PLOS ONE [Internet]. 2020 [cited 2024 Mar 19];15(7):e0236370. Available from: https://doi.org/10.1371/journal.pone.0236370
» https://doi.org/10.1371/journal.pone.0236370 -
27. Al Sibani M, Al-Maqbali JS, Yusuf Z, Al Alawi AM. Incidence and Risk Factors for 28 Days Hospital Readmission: A Retrospective Study from Oman. Oman Med J [Internet]. 2022 [cited 2024 Mar 19];37(5):e423. Available from: https://omjournal.org/articleDetails.aspx?coType=1&aId=3220
» https://omjournal.org/articleDetails.aspx?coType=1&aId=3220 -
28. Santos CE, Klug D, Losekann MV, Nunes TS, Cruz RP. Analysis of the Perroca Scale in Palliative Care Unit. Rev Esc Enferm USP [Internet]. 2018 [cited 2022 Nov 15];52:e03305. Available from: https://doi.org/10.1590/S1980-220X2017037503305
» https://doi.org/10.1590/S1980-220X2017037503305 -
29. Guzmán MCG, Andrade SR, Ferreira A. Role of nurses for continuity of care after hospital discharge. Texto Contexto Enferm [Internet]. 2020 [cited 2024 Mar 19];29(Spec):e20190268. Available from: https://doi.org/10.1590/1980-265X-TCE-2019-0268
» https://doi.org/10.1590/1980-265X-TCE-2019-0268 -
30. Aued GK, Bernardino E, Silva OBM, Martins MM, Peres AM, Lima LS. Liaison nurse competences at hospital discharge. Rev Gaúcha Enferm [Internet]. 2021 [cited 2024 Mar 19];42(Spec):e20200211. Available from: https://doi.org/10.1590/1983- 1447.2021.20200211
» https://doi.org/10.1590/1983- 1447.2021.20200211
NOTES
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ORIGIN OF THE ARTICLE
Article extracted from the dissertation - Elaboração e validação de checklist para alta hospitalar de pacientes adultos e idosos, presented to the Graduate Program in Nursing, Professional Master’s Degree, Universidade Federal de Ciências da Saúde de Porto Alegre, in 2021.
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APPROVAL OF ETHICS COMMITTEE IN RESEARCH
Approved by the Ethics Committee in Research of the Universidade Federal de Ciências da Saúde de Porto Alegre, under CAAE (Certificado de Apresentação para Apreciação Ética - Certificate of Presentation for Ethical Consideration) 37228320.0.0000.5345 and Opinion 4,499,025, and by the Grupo Hospitalar Conceição Hospital, under CAAE 37228320.0.3001.5530 and Opinion 4.540.922.
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TRANSLATED BY
Letícia Belasco.
