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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 good-quality, 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.
Methods Study Design and SampleThis 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 ConsiderationsThe 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 VariablesAfter 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 ScaleThe 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).
Statistical AnalysisContinuous 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.
ResultsData 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 StayOf 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).
Table 1. - Clinical Characteristics Associated With Hospital Length Clinical Factor n Hospital Stay ≥ 30 Days Hospital Stay ≥ 60 Days YesNote. ADL = activity of daily living.
*p < .05. **p < .01. ***p < .001.
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.
Two hundred seven patients were hospitalized for more than 60 days, of whom 132 (63.8%) were male. Most were younger than 75 years (n = 117, 56.5%), 91.8% had lower ADL scores ≤ 60 (n = 190), and 82.6% had indwelling catheters or tubes (n = 171).
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 multivariate analyses revealed that being male (OR = 1.37, 95% CI [1.02, 1.84]), being < 75 years old (OR = 2.50, 95% CI [1.87, 3.34]), having an ADL score ≤ 60 (OR = 9.84, 95% CI [4.16, 23.27]), and having indwelling catheters or tubes (OR = 4.17, 95% CI [1.84, 9.47]) were associated with a significantly increased risk of hospitalization for more than 60 days (Table 2).
Table 2. - Multivariate Analysis of Clinical Factors Affecting Hospital Length Clinical Factor Wald OR 95% CI p Male 4.42 1.37 [1.02, 1.84] .035 < 75 years old 38.49 2.50 [1.87, 3.34] < .001 ADL score ≤ 60 27.10 9.84 [4.16, 23.27] < .001 With tubes 11.67 4.17 [1.84, 9.47] .001 With wounds 1.82 1.32 [0.88, 1.97] .177 Inclusion criteria ≥ 2 0.40 0.75 [0.30, 1.85] .529Note. ADL = activity of daily living; OR = odds ratio.
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).
Table 3. - Clinical Characteristics Associated With Readmission Clinical Factor n Readmission ≤ 14 Days Readmission ≤ 30 Days Yes
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