Factors Affecting the Effectiveness of Discharge Planning Implementation: A Case-Control Cohort Study

ABSTRACT Background In many hospitals, a discharge planning team works with the medical team to provide case management to ensure high-quality patient care and improve continuity of care from the hospital to the community. However, a large-scale database analysis of the effectiveness of overall discharge planning efforts is lacking. Purpose This study was designed to investigate the clinical factors that impact the efficacy of discharge planning in terms of hospital length of stay, readmission rate, and survival status. Methods A retrospective study was conducted based on patient medical records and the discharge plans applied to patients hospitalized in a regional medical center between 2017 and 2018. The medical information system database and the care service management information system maintained by the Ministry of Health and Welfare were used to collect data and explore patients' medical care and follow-up status. Results Clinical factors such as activities of daily living ≤ 60, having indwelling catheters, having poor control of chronic diseases, and insufficient caregiver capacity were found to be associated with longer hospitalization stays. In addition, men and those with indwelling catheters were found to have a higher risk of readmission within 30 days of discharge. Moreover, significantly higher mortality was found after discharge in men, those ≥ 75 years old, those with activities of daily living ≤ 60, those with indwelling catheters, those with pressure ulcers or unclean wounds, those with financial problems, those with caregivers with insufficient capacity, and those readmitted 14–30 days after discharge. Conclusions The findings of this study indicate that implementing case management for discharge planning does not substantially reduce the length of hospital stay nor does it affect patients' readmission status or prognosis after discharge. However, age, underlying comorbidities, and specific disease factors decrease the efficacy of discharge planning. Therefore, active discharge planning interventions should be provided to ensure transitional care for high-risk patients.


Introduction
Improvements in medical care quality, nutrition, and environmental hygiene have led to continuing growth in the older adult population worldwide. The share of the global population aged 65 years or above is projected to raise from 10% in 2022 to 16% in 2050. The number of persons aged 65 years or over worldwide is projected to be more than twice the number of children (United Nations, 2022). Population aging has been the fastest in Asia. In Taiwan, the older adult population exceeded 14% in 2018 and is projected to exceed 20% in 2025 (Ministry of the Interior, Taiwan, ROC, 2021).
Population aging reflects a change in the demographic structure that typically increases the population living with chronic diseases and disabilities. The total number of disabled people in Taiwan exceeded 800,000 in 2018 and is estimated to increase to 1.3 million in 2031 (Ministry of the Interior, Taiwan, ROC, 2021). Because the rate of disability related to acute conditions after hospital discharge is as high as 50%, corresponding medical care and public health policies have become more important (World Health Organization, Organisation for Economic Co-operation and Development, & The World Bank, 2018). In addition, because medical resources are limited, rising numbers of people with long-term care needs occupying acute beds in hospitals will necessarily increase the average length of hospital stays and rates of readmission. Therefore, promoting effective discharge planning is essential in clinical practice.
Discharge marks the beginning of the emergence of care problems. Therefore, discharge planning must assess the specific types of care and resources patients may need after discharge and then provide the necessary health knowledge, care guidance, home environment improvement advice, and social resource introductions during hospitalization (Pellett, 2016). Discharge planning is intended to solve the problems of patients and their families in a planned way, with the aim of helping make the discharge process smooth, comfortable, and comprehensive for patients and their families. Hospital-based case management models should provide time-effective and integrated medical professional care to ensure patients receive goodquality, cost-effective care (Case Management Society of America, 2016).
A systematic review of 30 controlled trials conducted by Gonçalves-Bradley et al. in 2016 found that personalized discharge planning shortened the length of hospital stays, reduced the 3-month readmission rate by 13%, and increased patient and medical staff satisfaction (Gonçalves-Bradley et al., 2016). Although analysis in previous studies on the effectiveness of hospital discharge planning focused on hospitalization days, readmission rates, and mortality, most of these studies focused on a single disease/procedure such as heart failure, stroke, diabetes, orthopedic surgery, and mental illness (Henke et al., 2017;Nunes & Queirós, 2017;Xiao et al., 2019). Large-scale database analyses on the effectiveness of overall discharge planning are lacking in the literature.
The purpose of discharge planning is to help ensure patients obtain guidance for follow-up care and other arrangements as soon as possible with the goals of reducing discharge anxiety and care load and facilitating a smooth discharge experience for patients and their families. The benefits of discharge planning realized by the hospital and health insurance providers include reduced hospitalization stays and lower readmission rates. Furthermore, discharge planning increases hospital bed utilization and turnover rates and reduces overall medical expenses. Therefore, the purpose of this study was to explore the effectiveness of discharge planning and investigate the clinical factors affecting length of hospitalization, readmission rates, and follow-up status after discharge.

Study Design and Sample
This retrospective study was conducted at a 1,000-bed medical center in Yunlin County, Taiwan. Patients' medical records were collected from the medical information system database and the care service management information system of the Ministry of Health and Welfare. Data were collected retrospectively from patients who had received medical treatment and follow-up care at the center between January 2017 and December 2018. Factors affecting the effectiveness of discharge planning implementation were compared between patients who were hospitalized for more than 30 days, were readmitted within 14-30 days after discharge, or died within 30 days after discharge and patients in the control group (hospitalization < 30 days, no readmission between 14 and 30 days after discharge, and survival through 30 days after discharge).

Ethical Considerations
The study protocol was reviewed and approved by the institutional review board of National Taiwan University Hospital (IRB number: 201810056RIND). Signed informed consent from the patients was waived because of the retrospective nature of the study.

Data Collection and Variables
After being exported from the databases, data were first sorted, and patients with incomplete data, predischarge mortality, a critical illness, or an advisory against discharge were excluded. The relevant data for this study were extracted from two databases: (a) the Hospital Medical Information System database, which provided basic demographic and clinical characteristics, including gender, age, medical diagnosis, main caregivers, Activities of Daily Living Scale scores, indwelling catheter and tube status (including nasogastric tube or feeding tube, tracheostomy tube, surgical drainage tube, and Foley/ urinary catheter), unclean wound status, dates of readmission, and financial concerns, and (b) the Care Service Management Information System of the Ministry of Health and Welfare, which contains data on patient medical and follow-up care situations after hospital discharge.

Activities of Daily Living Scale
The daily activity function was evaluated based on Activities of Daily Living Scale scores. The scale assesses the respondent's performance on 10 self-care activities, including seven self-care abilities (eating, grooming/personal hygiene, toileting, bathing, dressing and undressing, stool control, urinary control functions) and mobility (shifting/turning between wheelchair and bed, walking/ walking on flat ground, up and down stairs). Each item is scored as "complete independence," "partial assistance," or "complete dependence," and the total possible score is 100, with higher scores associated with a higher degree of independence in life activities. After the score was imported automatically, it was divided into five grades: totally dependent (0-20), severely dependent (21-60), moderately dependent (61-90), mildly dependent (91-99), and completely independent (100).
Hospitalization was defined as total length of hospital stay. Readmission refers to the patient being readmitted to the hospital after discharge. Survival status refers to the survival or death of the patient between discharge and the end of the follow-up period (September 30, 2020).

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Statistical Analysis
Continuous variables included age and total hospitalization days and were expressed as mean ± standard deviation. Categorical variables, including gender, activities of daily living (ADLs), diagnostic department, discharge status, main caregivers after discharge, and long-term care service utilization, were expressed in numbers and percentages (%). Correlations between the above variables were calculated using the Pearson's chi-square test and expressed as correlation coefficients. Odds ratios (ORs) were tested using Bonferroni post hoc tests of the respective variables. Multivariate analysis was performed using binary logistic regression when p < .05.
For correlations between diagnostic department, discharge status, ADL values, and total length of stay, the differences were analyzed using Student's t tests or one-way analyses of variance, after which binary variable regression was used for multivariate regression analysis. The impact of the implementation of discharge planning on length of hospitalization was assessed using the Kaplan-Meier curve for single-variable analysis and the log-rank test. The Cox regression model was used for multivariate analysis. IBM SPSS Statistics Version 22.0 (IBM Inc., Armonk, NY, USA) was used for various analyses. A p value of less than .05 was used to determine statistical significance.

Results
Data from 7,796 patients hospitalized between 2017 and 2018 and accepted for discharge planning were used as the initial sample in this study. Over half (4,365, 56.0%) of the participants were male, the median age was 77 years (range: 2-105 years; mean ± standard deviation: 73.5 ± 14.4 years), and 4,401 cases (56.5%) were older than 75 years. In terms of reason for admission, 4,832 patients were admitted because of an internal-medicine-related disease; 1,141, because of surgery; 329, because of a neurologic disease; 133, because of an orthopedic disease; and 1,361, because of other diseases.

Hospital Length of Stay
Of the 953 patients who were hospitalized for more than 30 days, 553 (58.0%) were male. Most of them were below the age of 75 years (n = 517, 53.2%), whereas 19.9% (n = 190) had ADL scores of 60 or lower, and 17.9% (n = 171) had indwelling catheters or tubes (as shown in Table 1). Among those patients who stayed in the hospital for over 30 days and were below 75 years old, several had lower ADL scores (60 or lower), indwelling catheters or tubes, pressure ulcers or unclean wounds, and poorly controlled chronic diseases. Nonetheless, most of the patients (n = 932, 97.8%) who stayed for over 30 days had other medical conditions, which included 675 (70.8%) patients who required prolonged treatment or rehabilitation, 154 (16.2%) who had comorbidities or complications, and 103 (10.8%) who had sustained disease progression.
Those patients with hospital stays over 60 days included a significantly higher proportion of male patients ( p = .022), those aged < 75 years ( p < .001), those with ADL scores ≤ 60 ( p < .001), those with indwelling catheters or tubes ( p < .001), and those with pressure ulcers or unclean wounds ( p < .001). Furthermore, the requirement for inclusion in discharge planning was having two or more items ( p < .001), which was also responsible for the markedly higher percentage of patients who stayed in the hospital for more than 60 days (as shown in Table 1). Of all the patients reviewed, only two (1.0%) had medical issues that demanded prolonged treatment or rehabilitation.
The  84, 9.47]) were associated with a significantly increased risk of hospitalization for more than 60 days (Table 2).

Readmission After Discharge
Nine hundred fifty-four patients exhibited factors affecting readmission within 14 days of discharge, including 576 (60.4%) men, who were mostly ≥ 75 years old (490, 51.4%). Patients with lower ADL scores (ADL score ≤ 60, n = 654, 68.6%), with indwelling catheters and tubes (n = 698, 73.2%), and with pressure ulcers or unclean wounds were found to be at a higher risk for readmission within 14 days after discharge (Table 3). Six hundred eighty-six patients were readmitted within 30 days after discharge. Analysis of the factors affecting readmission within this period showed risk factors included being male, being < 75 years, having an ADL score ≤ 60, and having indwelling catheters or tubes ( Table 3).
Analysis of the association between caregiver and readmission within 14 days and 30 days after discharge found that patients who lived alone or who were cared for by a spouse, family member, friend, or hired caretaker had a higher risk of readmission within 14 days and that those who lived alone or were cared for by a hired caretaker had a higher risk of readmission within 30 days after discharge.
Multivariate analysis revealed that being male, being ≥ 75 years old, having an ADL score ≤ 60, having indwelling catheters or tubes, living alone, and being cared for by a caregiver independently increased the risk of readmission because of clinical factors within 14 days after discharge (Table 4).

Postdischarge 30-Day Mortality and Survival
The results of univariate analysis revealed that factors including gender, age, criteria of discharge planning, and main caregivers after discharge increased mortality risk within 30 days after discharge for patients with one or more of the following  characteristics: ≥ 75 years old, with prolonged hospital stays, with readmission within 14 days, with an ADL score ≤ 60, with indwelling catheters or tubes, and with pressure ulcers or unclean wounds. In contrast, being cared for by a caregiver was found to have no effect on postdischarge mortality risk (Table 5).

Discussion
Discharge planning is an integral but ill-defined process in most acute care settings. Length of hospitalization, readmission rate, and discharge outcome are widely used indicators of hospital care quality. The results show that poor ADL scores (≤ 60), having indwelling catheters or tubes, and having unclean wounds had the greatest negative impacts on discharge planning efficacy. As the results of this study were mixed and complicated, further exploration of the ideal protocol and method for implementing the discharge planning process is still warranted. The proportion of men in this study was relatively high (56.0%), which is consistent with that of overall hospitalization in Taiwan. According to the statistics of the National Health Insurance Administration, Ministry of Health and Welfare (2021), about 2 million people are hospitalized in Taiwan annually. The crude hospitalization rate for men over 45 years old is higher than that for women, and the average age of hospitalization has been trending consistently downward in recent years. Men more than women tend to self-perceive their health as good, which may contribute to their relatively lower use of medical resources, as determined by number of outpatient visits and the utilization rate of adult health examinations (Vlassoff, 2007). However, the hospitalization rate, hospitalization costs, and average cost per outpatient visit are higher in men than women (Damery & Combes, 2017), indicating that men seek medical assistance only after their illness is more serious, which may result in more follow-up care issues requiring attention (Hoffmann & Allers, 2016).
Most of the sample used in this study were aged 75 years or older. In general, older adults represent a large proportion of hospitalized patients and tend to have more comorbid chronic illnesses and disabilities and to require age-appropriate management to lessen the risk of adverse events during hospitalization. Older adults account for 18.52% of the population in Yunlin County, making it the most aged county in Taiwan (Ministry of the Interior, Taiwan, ROC, 2019). Most of the older adult patients in this study had functional dependencies, which required the help of another person to carry out daily household duties and provide assistance with basic needs. These characteristics of older adult homecare after hospitalization support the need for comprehensive functional assessment as part of discharge planning (Mabire et al., 2018). The LACE index has been shown to predict hospital readmissions and death with variable accuracy (van Walraven et al., 2010). However, this index has been shown to predict mortality and frequent readmissions at lower thresholds and at better accuracy in younger than older individuals. Age should be taken into account when using the LACE index to identify patients at a high risk (Fry et al., 2020).
Variables found to be independently associated with risk of readmission or death after discharge from hospital included length of stay ("L"), acuity of the admission ("A"), patient comorbidity (as measured using the Charlson comorbidity index score; "C"), and emergency department use (i.e., number of visits in the 6 months before admission; "E"). The LACE index may be used to quantify risk of death or unplanned readmission within 30 days after discharge from the hospital (van Walraven et al., 2010). Another prediction model, referred to as the HOSPITAL score, uses seven independent factors: hemoglobin at discharge, discharge from an oncology service, sodium level at discharge, procedure during the index admission, index type of admission, number of admissions during the last 12 months, and length of stay. This model was developed to identify the risk of potentially avoidable 30-day readmission in medical patients before discharge (Donzé et al., 2013). Both the LACE index and HOSPITAL score models have been used effectively to identify patients at a high risk of readmission (Su et al., 2020) and to predict mortality in multimorbid older patients (Aubert et al., 2022). However, the characteristics of these high-risk patients are not addressed in these models. In this study, eight criteria are used to determine the need for implementing discharge planning. These include ADL score less than 60, having indwelling catheters or tubes, having pressure ulcers or unclean wounds, having poor control of chronic diseases, readmission to the hospital within 14 days because of the same condition, having financial problems, and having major caregivers or living alone. Although these are high-risk indicators for long-term care needs, the primary task of implementing discharge planning is to identify high-risk cases early to help facilitate postdischarge planning (Hoyer et al., 2019). Although discharge planning has been promoted for many years in Taiwan, the number of recipients receiving discharge planning remains limited because of manpower availability and the priorities of each hospital. Comprehensive screening for major cases is insufficient in most institutions.
The findings of previous studies have shown discharge planning to achieve a small reduction in hospital length of stay for hospitalized older adults (Gonçalves-Bradley et al., 2016), and nursing diagnoses as the modality of admission and male gender have been shown to be significant determinants of length of hospital stay (D'Agostino et al., 2019). Results of Note. ADL = activity of daily living; OR = odds ratio.

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Hui-Wen PO et al. Effectiveness of Discharge Planning VOL. 31, NO. 3, June 2023 this study indicate that being male, having an ADL score ≤ 60, and having indwelling catheters or tubes are significantly associated with longer hospital stays. Moreover, disease severity and complexity may prolong hospitalization duration. Aging is accompanied by various chronic conditions that often require hospitalization (Dharmarajan et al., 2016). In this study, we found that, whereas the ratio of > 75-year-old admissions was high, the proportion of hospitalizations that lasted over 30 or 60 days and were considered excessively long was relatively small, showing that long-term hospitalization factors for elderly patients relate to more complicated variables such as chronic diseases, medical history, and poor social support structure in addition to the basic physiological conditions of age and gender. Decreasing the rate of hospital readmissions is a high-priority task in efforts to improve hospital healthcare quality. In Taiwan, the most common causes for patients being readmitted to the hospital are disease factors such as progressive chronic disease and the exacerbation of chronic conditions (Dai et al., 2002). Significant associations have been found between readmission factors and the demographic and clinical characteristics of patients (Coffey et al., 2019). Careful analysis has shown that case management promotes the efficacy of discharge planning in nursing units and also offers the potential for making improvements to further reduce patient readmission rates (Henke et al., 2017;Kucharczuk et al., 2022). In this study, being male, having indwelling catheters and tubes, and living alone or having different caregivers were associated with a higher risk of readmission. Discharge planning may not affect the proportion of patients discharged home rather than to residential care (Gonçalves-Bradley et al., 2016). In contrast, elderly patients and patients with lower ADL scores were found to have decreased readmission rates when they received hospital discharge planning. Lower readmission rates have been noted in the discharge planning group in studies of high-risk elderly patients with chronic medical conditions (Gonçalves-Bradley et al., 2016). Early interventions starting during the hospital stay and continuing after discharge are more effective in reducing readmissions (Braet et al., 2016;Luther et al., 2019). Therefore, discharge planning helps ensure a safe transition through improved clinician communication, patient education, information technology systems, involvement of community-based providers, and arrangements for prompt follow-up.
It remains uncertain whether discharge planning has an effect on postdischarge mortality, complication rates, or patient health status at follow-up (Gonçalves-Bradley et al., 2016;Khera et al., 2020). Early discharge planning with acutely admitted older adults has been associated with fewer hospital readmissions, but not with changes in length of hospital stay or mortality (Wu et al., 2019). However, discharge planning may positively affect the satisfaction of patients and healthcare professionals (Gonçalves-Bradley et al., 2016). The analysis in this study showed that patients aged ≥ 75 years, with prolonged hospital stays, with readmission within 14 days of discharge, with ADL scores ≤ 60, with indwelling catheters or tubes, or with pressure ulcers or unclean wounds experienced higher mortality rates within 30 days after discharge. In addition, type of caregiver was found to have no effect on postdischarge mortality, although a previous study found older adults with lower performance status and with caregivers to experience higher rates of postdischarge mortality (Rezaei-Shahsavarloo et al., 2020). In addition, prolonged hospital stays and readmission were found to be strongly associated with multiple comorbidities, which increases the risk of mortality after discharge (López Pardo et al., 2016;Wu et al., 2019).
This study was affected by several limitations. First, the retrospective study design used limits patients' long-term follow-up. In addition, database access was restricted by the care management information system database of the Ministry of Health and Welfare, with data access limited to the application list, application date, evaluation date, and application items. This limited the amount of follow-up data that could be accessed for the discharged patients. Second, selection bias may have influenced the case study and case selection. Importantly, we could not consistently distinguish among individual differences in discharge effectiveness because information on different patient experiences during admission or with death after discharge were not available for all patients. Thus, the generalization of results to other populations or geographic areas may be limited.
In conclusion, the results support that advanced age, underlying comorbidities, and specific disease factors decrease the efficacy of discharge planning. In addition, implementing case management in discharge planning was found to have no substantial effect on reducing the length of hospitalization or on the readmission status and prognosis of patients after discharge. However, the active intervention of discharge planning, emphasizing nurse-led early discharge planning and self-management education as well as instructional discharge letters and medication plans from attending physicians, will help prepare patients to resume daily life activities and maintain their health after discharge. Effective management of transitional care from the hospital to the community Note. ADL = activity of daily living; HR = hazard ratio.

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will help discharged patients and their family continue to conduct prescribed health recovery and promotion activities, access and use related healthcare resources after returning home, and improve overall quality of care.