Staffing level in the discharge planning department and average length of stay in acute care wards: A cross-sectional study using a nationwide hospital- and ward-level data in Japan

doi:10.21203/rs.3.rs-4302724/v1

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Research Article

Staffing level in the discharge planning department and average length of stay in acute care wards: A cross-sectional study using a nationwide hospital- and ward-level data in Japan

https://doi.org/10.21203/rs.3.rs-4302724/v1

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Background

The transition from hospital to the next care setting is when care fragmentations are likely to occur, making discharge planning essential; however, the relationship between discharge planning and length of stay is unclear. This study aimed to investigate the association between staffing levels, particularly the number of nurses and medical social workers in the discharge planning department, and the average length of stay at the ward level in acute care hospitals in Japan.

Methods

Applying a cross-sectional approach, we used nationwide administrative hospital- and ward-level data from the fiscal year 2021. A total of 5,580 acute care wards in 1,101 hospitals across 206 secondary medical areas were included. A two-level multilevel regression analysis with random intercept stratified by three types of acute care ward functions was performed by adjusting ward, hospital, and regional characteristics.

Results

A total of 1,017 wards in 70 designated special function hospitals, 3,828 general acute care wards with a 7:1 patient-to-nurse ratio in 596 hospitals, and 735 general acute care wards with a 10:1 patient-to-nurse ratio in 435 hospitals were included in the final analysis. The average length of stay was 12.5 days, 11.5 days, and 18.0 days, respectively. There was a significant association between the total number of nurses and medical social workers per 100 hospital beds in acute care wards with a 7:1 patient-to-nurse ratio, but not in special function wards or in acute care wards with a 10:1 patient-to-nurse ratio. Sensitivity analysis that separately analysed the number of nurses and medical social workers showed that the number of nurses per 100 hospital beds was associated with the average length of stay in acute care wards with a 7:1 patient-to-nurse ratio. Medical social workers per 100 hospital beds showed no association in any ward model.

Conclusions

A greater number of nurses and medical social workers per 100 hospital beds in the discharge planning department, especially greater nurse staffing, was associated with short lengths of stay in acute care wards with a 7:1 patient-to-nurse ratio.

discharge planning

health service research

acute care

quantitative approach

length of stay

The transition period from hospital to the next care setting is a vulnerable and unstable time when care fragmentations are likely to occur [1], making discharge planning essential. Since most patients who require discharge planning are elderly with chronic diseases and functionally dependent [2], their hospitalisations often tend to be prolonged [3,4]. Consequently, meticulous collaboration with the next phase of care is indispensable to prevent adverse events and rehospitalisation.

Various interventions and outcomes have been conducted on discharge planning. As for intervention strategies, multidisciplinary collaboration or a dedicated nurse who serves as a key coordinator for discharge planning is considered effective [5]. From an outcome perspective, discharge planning has been effective in reducing mortality rates, readmission rates, and time to readmission and improving patient and family satisfaction [6,7]. The involvement of professionals may have led to good outcomes. However, the relationship between discharge planning and length of stay remains inconclusive. A recent systematic review of the effectiveness of discharge planning in acute care settings reported a reduction in the length of stay [8]. Another systematic review noted inconsistent associations with the length of stay owing to the heterogeneity of approaches and the lack of a unified component for discharge planning [9–11].

Japan’s population aged 65 years or older accounted for 29.1% of the total population in 2023, marking the highest percentage on record [12]. To overcome this super-aged society, the government has put forward integrated community care as part of its healthcare system, aiming for smooth transitions from hospitals to communities, especially from acute care hospitals to home care [13]. To effectively implement this system, policies such as the addition of discharge planning fees in 2008 and reports on the medical functions of hospital beds since 2014 have been boosted. The purpose of the discharge planning fee was expected to include the goal of reducing the length of stay, along with the promotion of integrated community care systems. An incentive is provided to hospitals by assigning at least one nurse and one medical social worker (MSW) to the discharge planning department. Relatively large hospitals had 10 or more nurses or MSWs allocated [14]. The practice status of discharge planning nurses [15,16] and readmissions within 30 days after discharge [17] have been examined in Japan; however, the impact on the length of stay has not been verified. Further, the relationship between increased staffing in the discharge planning department and length of stay is not well understood.

2.1 Types of hospitals in Japan

In Japan, hospitals and bed types are regulated by the Medical Care Act. Hospitals are classified into six types, including special function hospitals and general hospitals, which were the scope of this study [18]. Special function hospitals’ main role is to provide, develop, evaluate, and train in advanced medical care. As of 2023, there are 88 such hospitals nationwide. Contrastingly, the ward classification is determined by the medical fee system, not by the Medical Care Act, and this study focused on special function hospital admission fees and general ward admission fees. General ward admission fees are categorised into six types, ranging from Type 1 to Type 6. As the type increases to 6, some calculation criteria are eased. General ward admission fees for Type 1 require a 7:1 patient-to-nurse ratio, an average length of stay of 18 days or less, and a discharge-to-home rate of 80% or more. Basic hospitalisation fees for Type 2 to Type 6 require a 10:1 patient-to-nurse ratio and an average length of stay of 21 days or less (Ministry of Health, Labour and Welfare, 2023)[19]. Details on hospitals and wards are shown in Appendix 1. There is ongoing concern about the myriad of Type 1 general ward admissions fees (equates to a 7:1 patient-to-nurse ratio), and policies are being taken to reduce these admissions by strictly limiting the length of stay [20].

2.2 Policies to improve discharge planning in the acute care setting in Japan

In Japan, discharge planning initiatives in acute care hospitals began in earnest with the 2006 reform of the healthcare system. A new discharge planning fee payment was introduced following the 2008 revision of the medical fee system [21]. To receive this payment, the establishment of the discharge planning department became mandatory in 2010. The only requirement regarding discharge planning department personnel, regardless of hospital volume, is a minimum of one dedicated or full-time registered nurse and MSW, with at least one of each profession forming a pair [22]. There are two types of discharge planning fees. With discharge planning fee Type 1, at least one dedicated discharge planning staff member must be assigned to each of the two wards. Additionally, interventions include identifying patients with discharge difficulties, supporting patients’ and caregivers’ decision-making, holding conferences with other necessary professionals, and initiating a discharge support plan within seven days of patient admission. Discharge planning fee Type 2 has no staffing standards, but the same steps as for fee Type 1 must be performed as soon as possible. Moreover, some add-ons incentivise both the hospital and home care provider sides to conduct joint conferences before discharge. Length of stay is a key indicator of smooth coordination.

3.1 Aim

This study aimed to clarify the association between staffing in the discharge planning department at the hospital level and the average length of stay in acute care wards using nationwide data in Japan.

3.2 Hypothesis

We hypothesise that higher staffing levels in the discharge planning department in hospitals are associated with shorter lengths of stay on a ward basis.

4.1 Study design

A cross-sectional study was conducted using nationwide administrative data in Japan.

4.2 Samples and data source

We obtained ward- and hospital-level data on adult acute care wards and hospitals from reports on the medical functions of hospital beds in fiscal year 2021. The 2014 revision of the Medical Care Act introduced the annual reporting system for all hospitals in Japan [14]. This reporting system mandates hospitals with general or long-term care beds to report annually to their local governments (prefectures) for the allocation of appropriate medical resources for each region. Items related to hospital characteristics, such as establishment status and personnel, are reported at the point of July 1, 2020, whereas other items are reported in full-year units from April 1, 2020, to March 31, 2021. The reporting system comprises ward- and hospital-level datasets: the ward-level dataset includes the function name based on the medical fee system, number of beds, number of inpatients, number of full-time equivalent nursing staff, number of rehabilitation staff, percentage of inpatients that meet the criteria of the Severity of a Patient’s Condition and Extent of a Patient’s Need for Medical/Nursing Care tool [23], and annual number of admissions and discharges; the hospital-level dataset includes the establishment category, function type, number of medical staff by profession, and number of staff by profession in the discharge planning department, among others. We included all nationwide general acute care wards for adults except critical care units such as intensive care units, high care units, and stroke care units or emergency room and their corresponding hospitals (Fig. 1).

4.3 Outcome

The outcome variable for this study was the average length of stay at the ward level. Length of stay was defined as the number of hospitalisation days from the total number of admissions by prior location to the total number of discharge destinations, calculated as follows [24]: number of annual inpatients in total/{(total number of admissions by prior location + total number of discharge destinations)/2}.

4.4 Independent variable

For the independent variable, we used staffing levels of nurses and MSWs affiliated with the discharge planning department per 100 hospital beds in the hospital. In Japan, the discharge planning fee in medical reimbursement was established in 2008 [21].

4.5 Covariates

We used ward-, hospital-, and regional-level characteristics from literature reviews as covariates [25, 26].

4.5.1 Ward-level characteristics

To represent the ward-level characteristics, the following variables were employed: type of ward (special function, acute care wards with 7:1 and 10:1 patient-to-nurse ratios, respectively), the annual number of inpatient admissions, number of beds, number of full-time equivalent nursing staff, presence or absence of full-time rehabilitation staff, percentage by admission status (planned, unplanned, emergency), percentage by pre-admission location (home, inpatient transfer, patient transfer, long-term facilities, others), percentage by destination (home, inpatient transfer, patient transfer, long-term care facilities, others), in-hospital mortality rate, presence or absence of discharge planning fee (none, fee Type 1, fee Type 2), and percentage of inpatients meeting the criteria of the Severity of a Patient’s Condition and Extent of a Patient’s Need for Medical/Nursing Care tool. This assessment tool involves checking the presence or absence of items in three categories and scoring accordingly: Item A primarily focuses on monitoring and treatment, Item B on patients' conditions, and Item C on medical conditions, with eight, seven, and seven items, respectively (for more details, see [23]). To ensure the appropriate allocation of healthcare resources and nurse staffing, the Severity of a Patient’s Condition and the Extent of a Patient’s Need for Medical/Nursing Care tool has been a requirement for acute care wards to receive medical reimbursement since 2008 [19]. In acute care wards, nursing staff must record the nursing care needs on a 24-hour basis. Since individual patient records were not available, the following variables were utilised as approximations: the total number of annual general anaesthesia surgeries, the total number of annual cancer treatments (chemotherapy and radiation therapy), and the total number of annual rehabilitations. Because of the nature of the data, the numbers ranging from 0 to 9 were represented using symbolic notation and, therefore, were replaced with an average value of 4.5.

4.5.2 Hospital-level characteristics

The characteristics of hospitals were represented by the following variables: type of ownership (national government, public medical institutions, social insurance bodies, private, others), implementation of the Diagnosis Procedure Combination payment system, adoption of special functions, establishment of regional medical care support, establishment of home health clinic support, adoption of emergency medical service, number of beds, number of physicians per 100 hospital beds, number of nursing staff per hospital 100 hospital beds, and number of rehabilitation staff per hospital 100 hospital beds. Nursing staff comprises registered and licensed practical nurses, excluding nursing assistants, while rehabilitation staff comprises physical, occupational, and speech-language therapists.

4.5.3 Regional-level characteristics

The regional-level factors were adopted on the basis of secondary medical area (SMA) units. In Japan, an SMA is a regional unit defined by the Medical Care Act, which is a system that provides general inpatient care while considering geographical conditions, infrastructure, and other social factors [13]. An SMA is commonly employed to investigate the healthcare resources within a region [27]. As of 2021, 334 SMAs had been established for all 47 prefectures [14]. The variables—number of community care beds per 10,000 people aged 65 years or older, number of rehabilitation beds per 10,000 people aged 65 years or older, and number of long-term care beds per 10,000 people aged 65 years or older—were originally derived from reports of medical functions of hospital beds [14]. Subsequently, we calculated the number of beds by obtaining the population aged 65 years or older from the 2021 Resident Basic Registry [28]. The number of home healthcare support clinics was retrieved from publicly available data in the 2021 datasets [29]. For in-home service agencies, publicly disclosed data for long-term care information in 2021 was utilised [30]. The in-home service agencies variable was created by aggregating the number of service providers for care managers, home-visit care, home-visit night care, 24-hour home-visit service, home-visit rehabilitation, home-visit bathing, and home-visit nursing care.

4.6 Statistical analysis

We excluded all cases with missing data in the selected covariates. We described the mean with standard deviation (SD) or the medians with interquartile ranges (IQR) for the numeric variables and the percentages for the categorical variables of the characteristics of the eligible samples. We depicted boxplots by ward functions to illustrate the distribution of the average length of stay at each ward and the staffing levels in the discharge planning department at the hospital level. To compare the average length of stay among the three wards’ functions, analysis of variance and student’s t-test were conducted. To compare the staffing levels at the discharge planning department among the three wards' functions, the Kruskal–Wallis test and Mann–Whitney U test were performed. To investigate the relationship between the staffing level in the discharge planning department and the average length of hospital stay in the ward, we performed a two-level (level 1 being the ward and level 2 being the hospital) multilevel regression analysis with random intercept stratified by the ward functions, since our data were nested within hospitals. The residual analysis using a null model and adding the regional-level as the third level suggested no significant difference in residual between level 2 and level 3; therefore, we proceeded with a two-level multilevel analysis. The covariates employed in the models were selected based on a univariate analysis that potentially correlated with outcome, identification in previous studies [31, 32], and clinical significance. To test for multicollinearity, variance inflation factors were computed for each independent variable. P-values below .05 were considered significant. To check whether the results would change the model’s results, sensitivity analyses were conducted by segregating the number of nurses and MSWs in the discharge planning department. All analyses used Stata version 16.1 (Stata Corp. College Station, TX, USA).

5.1 Characteristics of study samples

We selected 5,580 acute care wards in 1,101 hospitals in 260 SMAs out of 28,030 wards in 7,019 hospitals in 334 SMAs nationwide as of 2021 (Fig. 1). Of these, there were 1,017 wards in 70 designated special function hospitals, 3,828 general acute care wards with a 7:1 patient-to-nurse ratio in 596 hospitals, and 735 general acute care wards with a 10:1 patient-to-nurse ratio in 435 hospitals. The characteristics of wards, hospitals, and SMAs are shown in Table 1. The median (IQR) number of beds and the annual number of inpatients per ward were approximately 46 (40–50) beds and 13,070 (10,445–14,997) inpatients, respectively—almost the same among the three ward types. The percentage of inpatients who met two or more criteria in Item A and three or more criteria in Item B in the Severity of a Patient’s Condition and Extent of a Patient's Need for Medical/Nursing Care tool was highest in acute care wards with a 7:1 patient-to-nurse ration, at 19.0%. The admission rate from long-term care facilities was 0.2% (IQR 0.1–0.7) for special function wards, 1.8% (IQR 0.7–3.7) for acute care wards with a 7:1 patient-to-nurse ratio, and 5.3% (IQR 2.0–11.9) for acute care wards with a 10:1 patient-to-nurse ratio. Regarding the discharge destination by ward type, the discharge rate to home was 83.3% (IQR 71.8–90.4) for special function wards, 78.0% (IQR 66.6–86.3) for acute care wards with a 7:1 patient-to-nurse ratio, and 75.5% (IQR 61.1–85.7) for acute care wards with a 10:1 patient-to-nurse ratio. The discharge rate to long-term care facilities was 0.3% (IQR 0.1–0.7) for special function wards, 1.9% (IQR 0.8–3.5) for acute care wards with a 7:1 patient-to-nurse ratio, and 6.2% (IQR 2.5–12.9) for acute care wards with a 10:1 patient-to-nurse ratio. Regarding discharge planning fees, it was calculated in all wards only for special function beds. (Table 1). The means (SDs) number of hospital beds were 757 (184.62) for designated special function hospitals, 345 (96.93) for acute care hospitals with a 7:1 patient-to-nurse ratio, and 101 (79.33) for acute care hospitals with a 10:1 patient-to-nurse ratio. For type of establishment, national or public medical institution hospitals accounted for the largest proportion of hospitals with special function wards (68.6%, 48 hospitals). Private hospitals had the highest proportions of acute wards with a 7:1 (41.9%, 250 hospitals) and 10:1 (68.7%, 299 hospitals) patient-to-nurse ratios. Special function hospitals were located in areas with a greater number of SMAs than were wards with acute care wards with 7:1 or 10:1 patient-to-nurse ratios.

Table 1

Characteristics of study participants
	Total		Special function wards		Acute care wards with a 7:1 patient-to-nurse ratio		Acute care wards with a 10:1 patient-to-nurse ratio
	(n = 5,580)		(n = 1,017)		(n = 3,828)		(n = 735)
Variables	n/median	%/IQR	n/median	%/IQR	n/median	%/IQR	n/median	%/IQR
Annual total number of inpatient admissions in the ward	13,070	10,445–14,997	13,033	11,059–14,726	13,205	10,514–15,155	12,394	9,684–14,572
Number of beds per ward	46	40–50	45	41–50	46	41–50	47	40–52
Full-time equivalent nursing staff per ward	32	28–94	30	26–33	29	25–33	22	18–26
Presence or absence of full-time rehabilitation staff assigned to the ward (n, %)
No	5119.0	91.7	1008.0	99.1	3567.0	93.2	544.0	74.0
Yes	461.0	8.3	9.0	0.9	261.0	6.8	191.0	26.0
Percentage of admissions considering annual total number of inpatients by route
Planned admissions	67.9	51.5–80.2	83.1	74.9–89.1	66.0	52.5–77.1	45.0	27.6–61.8
Unplanned admissions	10.0	4.1–20.4	7.6	3.9–13.6	9.6	3.9–18.9	26.3	10.2–45.7
Emergency admissions	16.6	7.8–29.7	6.7	3.1–13.0	19.6	10.8–31.8	18.5	6.0–37.8
Percentage of admissions considering annual total number of inpatients by pre-admission location
Admissions from home	80.5	69.0–88.5	86.5	77.0–93.0	79.1	68.0–86.9	79.9	66.3–89.0
Inpatient transfers	11.7	4.3–22.8	9.4	4.0–18.2	14.3	6.8–24.9	2.1	0.0–8.4
Transfers from other hospitals	1.8	1.0–3.2	1.6	0.8–2.9	1.7	0.9–2.8	4.1	1.9–8.5
Admissions from long-term facilities	1.5	0.4–3.7	0.2	0.1–0.7	1.8	0.7–3.7	5.3	2.0–11.9
Other admissions	0.0	0.0–0.1	0.0	0.0–0.1	0.0	0.0–0.1	0.0	0.0–0.0
Percentage of discharges considering annual total number of inpatient discharges
Discharges to home	78.6	66.9–87.2	83.3	71.8–90.4	78.0	66.6–86.3	75.5	61.1–85.7
Inpatient transfers	8.9	4.1–16.6	9.3	4.7–18.0	9.5	4.8–16.7	3.6	0.0–13.3
Transfers to other hospitals	5.6	3.1–10.6	4.0	2.1–7.1	6.1	3.4–11.5	6.1	3.8–10.7
Discharges to long-term facilities	1.6	0.5–3.7	0.3	0.1–0.7	1.9	0.8–3.5	6.2	2.5–12.9
Other discharges	0.0	0.0–0.0	0.0	0.0–0.1	0.0	0.0–0.0	0.0	0.0–0.0
Percentage of in-hospital mortality	2.0	0.8–3.9	1.0	0.4–1.9	2.1	1.0–3.8	4.4	1.8–7.4
Percentage of patients meeting the criteria in the Severity of a Patient’s Condition and Extent of a Patient’s Need for Medical/Nursing Care Tool among the annual total number of patients in the ward
Two or more criteria in Item A and three or more criteria in Item B	18.0	12.5–23.1	15.2	10.1–20.1	19.0	14–23.9	15.9	8.1–22.5
Three or more criteria in Item C	11.8	2.4–21.55	15.6	3.5–22.6	12.9	3.8–22.3	2.7	0.0–10.0
Annual total number of general anesthesia surgeries	54.0	13.5–247.8	87.5	31.5–295	56.0	16.0–259.3	31.5	0.0–101
Annual total number of cancer treatments (chemotherapy and radiation therapy)	72.0	22.5–205.3	142.0	54–338.5	72.0	22.5–197.75	22.5	4.5–63.0
Annual total number of rehabilitations	327.0	98–590	228.0	82.0–411.0	369.0	107.0–636.5	322.0	78–552.0
Presence or absence of a discharge planning fee^§
None (n, %)	288	5.2	0.0	0.0	79	2.1	209	28.4
Fee Type 1 (n, %)	923	16.5	322	31.7	326	8.5	275	37.4
Fee Type 2 (n, %)	4369	78.3	695	68.3	3423	89.4	251	34.2
Type of ownership*
National government (n, %)	1010	18.1	526	51.7	428	11.2	56	7.6
Public medical institutions (n, %)	2152	38.6	117	11.5	1854	48.4	181	24.6
Social insurance bodies (n, %)	126	2.3	0	0.0	125	3.2	1	0.2
Private (n, %)	2101	37.7	374	36.8	1256	32.8	471	64.1
Other (n, %)	191	3.4	0	0.0	165	4.3	26	3.5
Hospital adopted the DPC payment system (n, %)
No	696	12.5	0	0.0	151	3.9	545	74.2
Yes	4884	87.5	1017	100.0	3677	96.1	190	25.9
Hospital adopted special functions (n, %)
No	4563	81.8	0	0.0	3828	100.0	735	100.0
Yes	1017	18.2	1017	100.0	0	0.0	0	0.0
Hospital adopted regional medical care support (n, %)
No	2581	46.3	964	94.8	931	24.3	686	93.3
Yes	2999	53.8	53	5.2	2897	75.7	49	6.7
Hospital adopted home medical care support (n, %)
No	4774	85.6	1001	98.4	3245	84.8	528	71.8
Yes	806	14.4	16	1.6	583	15.2	207	28.2
Hospital adopted emergency medical services (n, %)
No	3184	57.1	257	25.3	2202	57.5	725	98.6
Yes	2396	42.9	760	74.7	1626	42.5	10	1.4
Population (100,000 people)	7.5	4.2–14.3	9.1	5.1–14.1	7.5	4.3–15.0	5.2	2.1–11.7
Proportion of individuals aged 65 years or older	28.0	24.8–30.5	26.9	22.5–29.3	28.0	24.8–30.6	28.9	26.3–32.8
Number of community care beds per 10,000 people aged 65 years or older	0.4	0.3–0.5	0.4	0.3–0.6	0.4	0.3–0.5	0.4	0.3–0.5
Number of rehabilitation beds per 10,000 people aged 65 years or older	0.6	0.4–0.6	0.6	0.4–0.6	0.5	0.4–0.6	0.5	0.4–0.6
Number of long-term care beds per 10,000 people aged 65 years or older	254.1	220.0–291.8	232.4	203.1–271.0	255.6	220.5–291.8	272.3	230.0–313.7
Number of home health care support clinics per 10,000 people aged 65 years or older	4.3	2.6–6.0	5.3	3.4–7.0	4.0	2.6–5.8	3.7	2.5–5.2
Number of in-home service agencies per 10,000 people aged 65 years or older	126.4	80.0–183.2	153.7	83.6–198.1	121.3	65.9–183.2	117.8	81.2–183.2
DPC: diagnosis procedure combination; IQR: interquartile range

^§ With discharge planning fee Type 1, at least one dedicated discharge planning staff member must be assigned to each of the two wards. Additional interventions include identifying patients with difficulty in discharge, supporting patients' and caregivers’ decision-making, holding conferences with other necessary professionals, and initiating a discharge support plan within seven days of patient admission. Discharge planning fee Type 2 has no staffing standards, but the same steps as those for fee Type 1 must be performed as soon as possible.

* The detailed classification of types of ownership is as follows. National government: Ministry of Health, Labour and Welfare, National Hospital Organization, National University Corporation, National Institute of Occupational Safety and Health, National Research Center for Advanced and Specialized Medical Care, and Japan Community Health Care Organizations. Public medical institutions: prefectures, municipalities, local incorporated administrative agencies, Japanese Red Cross, Saiseikai Imperial Gift Foundation, Hokkaido Social Service Association, National Welfare Federation, and Federation of National Health Insurance Organizations. Social insurance bodies: health insurance societies and their federations, mutual aid associations and their federations, and national health insurance societies. Private: medical corporations, public interest corporations, private university corporations, social welfare corporations, medical co-ops, and companies.

5.2 Average length of stay

The average length of stay for all 5,580 wards was 12.5 days (SD 5.26). When stratified by ward type, the average length of stay was 12.5 days (SD 4.65) for special function wards, 11.5 days (SD 4.36) for acute care wards with a 7:1 patient-to-nurse ratio, and 18.0 days (SD 7.01) for acute care wards with a 10:1 patient-to-nurse ratio. The length of stay for acute care wards with a 10:1 patient-to-nurse ratio was significantly longer (p < .001) compared with that for other wards (Fig. 2).

5.3 Staffing level in the discharge planning department

The median number of nurses and MSWs per 100 hospital beds in the discharge planning department across all 1,101 hospitals was 2.9 (IQR 2.0–4.0). When stratified by ward type, median values were 2.1 (IQR 1.6–2.7) per 100 hospital beds for special function wards, 2.7 (IQR 2.0–3.7) per 100 hospital beds for acute care wards with a 7:1 patient-to-nurse ratio, and 3.5 (IQR 2.3–5) per 100 hospital beds for acute care wards with a 10:1 patient-to-nurse ratio. The number of nurses and MSWs in acute care wards with a 10:1 patient-to-nurse ratio was significantly higher (p < .001). The proportion of nurses in the discharge planning department was 56.1% for hospitals with special function wards and 50% for hospitals with acute care wards with a 7:1 and 10:1 patient-to-nurse ratio, respectively. When considering the individual counts of nurses and MSWs per 100 hospital beds, there was a trend for higher staffing numbers for both nurses and MSWs in hospitals with acute care wards with a 10:1 patient-to-nurse ratio, followed by acute care wards with a 7:1 patient-to-nurse ratio and special function wards (Fig. 3).

5.4 Multilevel linear regression analysis for the length of stay and the discharge planning department structure

Stratified analysis by ward type, while adjusting for covariates, revealed that an increase in one nurse or MSW per 100 hospital beds impacted the length of stay as follows: in hospitals with special function wards, coefficient (coef.) = -0.32, 95% confidence interval (CI) = -0.80 to 0.15, p = .18; in hospitals with acute care wards with a 7:1 patient-to-nurse ratio, coef. = -0.19, 95% CI = -0.33 to -0.06, p < .001; and in hospitals with acute care wards with a 10:1 patient-to-nurse ratio, coef. = -0.12, 95% CI = -0.38 to 0.13, p = .33 (Table 2). Sensitivity analysis separately analysing the number of nurses and MSWs showed that an increase of one nurse per 100 hospital beds was significantly associated with the average length of stay in acute care wards with a 7:1 patient-to-nurse ratio (coef. = -0.21, 95% CI = -0.38 to -0.04, p = .02), whereas an increase of one MSW per 100 hospital beds was non-significantly associated with the average length of stay in any ward model (Appendix 2–4).

Table 2

Results of random intercept multilevel linear regression analysis for length of stay
	Model 1				Model 2				Model 3
	Special function wards				Acute wards with a 7:1 patient-to-nurse ratio				Acute wards with a 10:1 patient-to-nurse ratio
	(n = 1,017)				(n = 3,828)				(n = 735)
Variables	Coef.	95% CI		P	Coef.	95% CI		P	Coef.	95% CI		P
Total number of nurses and MSWs in the discharge planning sector per 100 hospital beds	-0.32	-0.80	0.15	.18	-0.19	-0.33	-0.06	< .001	-0.12	-0.38	0.13	.33
Total number of nurses in the discharge planning sector per 100 hospital beds	-0.10	-0.62	0.41	.70	-0.21	-0.38	-0.04	.02	-0.24	-0.54	0.07	.13
Total number of MSWs in the discharge planning sector per 100 hospital beds	-0.47	-1.33	0.39	.28	-0.18	-0.39	0.03	.09	0.01	-0.39	0.41	.95
MSWs: medical social workers; Coef.: coefficient; 95% CI: 95% confidence interval

Model 1: Multiple regression analysis was conducted using the following adjusting variables: discharge planning nurse ratio in the discharge planning sector; planned admissions in the annual total number of inpatients by route; admissions from home in the annual total by pre-admission location; transfers from other hospitals in the annual total pre-admission location; admissions from long-term facilities in the annual total pre-admission location; discharges to home in the annual total discharges; transfers to other hospitals in the annual total discharges; discharges to long-term facilities in the annual total discharges; patients meeting two or more criteria in item A and three or more criteria in item B in the Severity of a Patient’s Condition and Extent of a Patient’s Need for Medical/Nursing Care tool; the annual total number of general anesthesia surgeries; types of ownership (national government, public medical institutions, privates, other); hospital-adopted regional and medical care support and emergency medical service; number of beds per hospital; physicians, nursing staff, and rehabilitation staff per 100 beds; discharge planning fee (none and Type 2); population (100,000 people); proportion of individuals aged 65 years or older; number of community care beds, rehabilitation beds, and long-term beds per 10,000 people aged 65 years or older; and number of home health care support clinics and in-home service agencies per 10,000 people aged 65 years or older.

Models 2 and 3: All types of ownership, discharge planning fee Type 1, and hospital-adopted diagnosis procedure combination were added to the adjusting variables in Model 1.

A higher number of nurses and MSWs per 100 hospital beds in the discharge planning department, especially higher nurse staffing, was associated with a lower length of stay in acute care wards with a 7:1 patient-to-nurse ratio, but with no significant associations in the special function wards and acute care wards with a 10:1 patient-to-nurse ratio.

Previous studies have examined the effect of discharge planning on the decrease in the length of hospital stay and showed mixed results: discharge planning interventions conducted by a multidisciplinary team including clinical nurse specialists [33] and one systematic review [34] reported no difference or prolonged length of stay. Other randomised controlled trials or comparative studies targeting specific settings, such as exacerbated chronic obstructive pulmonary disease [35], elderly patients [36], and general medical unit interventions [37] revealed a significant reduction in the length of stay. Our findings support the potential contribution of higher staffing levels in the discharge planning department, particularly in terms of nurse staffing, in reducing the length of stay at the ward level in acute care wards with a 7:1 patient-to-nurse ratio. Although this study could not determine the mechanism owing to the study design, this result might be explained by two reasons: strengthening the activities for discharge support for patients and fostering a culture of discharge planning throughout the hospital. Regarding the former, in acute care hospitals in Japan, the specific interventions conducted by discharge planning nurses include screening patients who face challenges with discharge, formulating discharge support plans, collecting information from relevant local professionals during hospitalisation, supporting decision-making for patients and their families, and coordinating pre-discharge conferences with visiting physicians and home care nurses [38, 39]. Additionally, some discharge planning nurses provide follow-up services such as home visiting care after patients are discharged if needed [16]. Thus, more staffing per inpatient in the discharge planning department improved the process and might contribute to shortening the average length of stay as a result. Regarding the second reason, hospitals in which discharge planning nurses are well-staffed, there is likely capacity to expand the scope of activities beyond those mentioned earlier, such as providing education and training on discharge planning for ward nurses [40, 41] and other professionals. Consequently, by increasing cross-organisational activities, discharge planning nurses had a spillover effect in fostering a culture of discharge planning throughout the hospital, which may have influenced the positive outcomes of this study. This finding reinforces the need for appropriate staffing levels in discharge planning departments tailored to hospital functions.

Noteworthy, this study showed the association between higher staffing in the discharge planning department and the shorter average length of stay only in acute care wards with a 7:1 patient-to-nurse ratio, but not in special function hospitals or hospitals with a 10:1 patient-to-nurse ratio. This may be influenced by the difference in hospital types and policies for differentiation of bed functions. As for special function hospitals, because of the nature of providing advanced medical care in a national or large university hospital with a substantial number of beds, special function hospitals may prioritise improving treatment outcomes rather than shortening hospital days [42, 43]. Additionally, as many patients with complex medical conditions are referred from across the country, the hospital itself is not tied to a specific region. Therefore, since the transition to the alternative phase of care often starts from scratch, reliance on post-discharge local resources, rather than the number of staff in the discharge planning department, may have a significant impact. In terms of the length of stay criteria set for each ward under the medical fee system, wards with a 7:1 patient-to-nurse ratio for the length of stay calculation typically have a period of 18 days; this is much shorter than the criteria for special function hospitals (within 26–28 days) and acute care wards with a 10:1 patient-to-nurse ratio (21 days). The revision of the medical fee schedule in 2024 is expected to further shorten the length of stay to within 16 days. This pressure to reduce the average length of stay limit on reimbursement may make staff in discharge planning departments place even more importance on reducing the length of stay as an outcome of their activities.

Contrastingly, in acute care wards with a patient-to-nurse ratio of 10:1, there may be patients with relatively mild conditions, or continue their hospitalisation owing to reasons related to the absence of caregivers or other social factors, despite not needing hospitalisation from a medical standpoint. This situation—'social admission’ [44]—could potentially contribute to an extended length of stay. Staff in discharge planning departments in acute wards with a 10:1 patient-to-nurse ratio may be more concerned with securing a discharge destination and consuming more time for coordination with caregivers and staff at the next care setting than with getting patients discharged quickly.

6.1 Strengths and limitations

The major strength of this study is its focus on acute care hospitals nationwide in Japan, making it highly generalisable within the country. However, due to differences in systems and policies among countries, it is challenging to directly adapt them to overseas contexts.

This study has two main limitations. First, the data were collected during the COVID-19 pandemic, resulting in potential deviations from the figures seen in typical years. Second, in the association between the number of nurses and MSWs per 100 hospital beds and length of stay in acute care wards with a 7:1 patient-to-nurse ratio, the coefficient was extremely small (-0.19). However, even though it may be slight, for patients with prolonged hospitalisations for non-medical reasons, in hospitals experiencing patient overcrowding owing to bed shortage (although bed occupancy rates were not examined in this study), and in countries such as Japan where policies for reducing the length of stay will continue in the case of acute care wards, a coefficient of -0.19 is considered clinically significant.

To increase the accuracy of evaluating the effectiveness of discharge planning, it is necessary to collect more detailed information on structural aspects such as the organisational positioning of the discharge planning department, the years of experience of nurses and MSWs, the number of cases they handle, the presence of a certified nurse or certified nurse specialist qualifications, and information on other tasks besides discharge planning. Furthermore, combining this information with actual specialised interventions and patient characteristics would help clarify the mechanism of discharge planning.

This study examined the association between staffing in the discharge planning department at the hospital level and the average length of stay in acute care wards using nationwide data. Higher staffing in the discharge planning department, particularly of nurses in acute care wards with a 7:1 patient-to-nurse ratio, potentially contributed to the reduction in the length of stay. Further research by obtaining more detailed information on the structure of the discharge planning department and comparing this information with combined patient data is needed.

MSW

medical social worker

SMA

secondary medical area

standard deviation

IQR

interquartile ranges

Ethics approval and consent to participate

This study did not use individual data. All data were obtained from open source and are available on the website. This study adhered to the principles of the Declaration of Helsinki and the study protocol was approved by the Tokyo Medical and Dental University Ethics Review Board on April 17, 2024 (No. C2024-02).

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Funding

This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Author Contribution

AM designed the study, acquired the data, conducted the statistical analyses, and drafted and revised the manuscript. NM and MK supervised the study and statistical analyses and revised the manuscript. All authors agreed to be accountable for all aspects of the work and gave final approval of the manuscript to be published.

Acknowledgments

Not Applicable.

Data Availability

The datasets generated and analysed during the current study are publicly available in the Ministry of Health, Labour and Welfare (http://www.mhlw.go.jp/index.html, in Japanese), Ministry of Internal Affairs and Communications (http://www.soumu.go.jp/, in Japanese), and Japanses government repository (http://www.e-stat.go.jp/en). The detailed data are listed in the references.

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Staffing level in the discharge planning department and average length of stay in acute care wards: A cross-sectional study using a nationwide hospital- and ward-level data in Japan

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Abstract

Figures

1. Introduction

2. Background

2.1 Types of hospitals in Japan

2.2 Policies to improve discharge planning in the acute care setting in Japan

3. The study

3.1 Aim

3.2 Hypothesis

4. Methods

4.1 Study design

4.2 Samples and data source

4.3 Outcome

4.4 Independent variable

4.5 Covariates

4.5.1 Ward-level characteristics

4.5.2 Hospital-level characteristics

4.5.3 Regional-level characteristics

4.6 Statistical analysis

5. Results

5.1 Characteristics of study samples

5.2 Average length of stay

5.3 Staffing level in the discharge planning department

5.4 Multilevel linear regression analysis for the length of stay and the discharge planning department structure

6. Discussion

6.1 Strengths and limitations

7. Conclusion

Abbreviations

Declarations

Competing interests

Funding

Author Contribution

Acknowledgments

Data Availability

References

Additional Declarations

Supplementary Files

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