Abstract
Background
Early hospital discharge planning can help to reduce the length of stay and unplanned readmission in high-risk patients. Therefore, it is important to select patients who can benefit from a personalized discharge planning based on validated tools. The modified Blaylock Risk Assessment Screening Score (BRASS) is routinely used in the Molinette Hospital (Turin, Italy) to screen patients at high risk for discharge, but the effectiveness of the discharge planning is uncertain in intermediate-risk patients.
Objective
To evaluate the best strategy for discharge planning by the Continuity of Care Hospital Unit (CCHU) in intermediate-risk patients according to modified BRASS.
Design
Cluster-randomized, multiple crossover trial.
Participants
Adult patients admitted in the Medicine and Neurology departments of the Molinette Hospital in Turin, Italy, between June 2018 and May 2019 with a BRASS intermediate risk.
Interventions
A routine discharge planning strategy (RDP, Routine Discharge Plan), which involved the management of all intermediate-risk patients, was compared to an on-demand discharge planning strategy (DDP, on-Demand Discharge Planning), which involved only selected patients referred to the CCHU by ward staff.
Main Measures
The primary outcome was the 90-day hospital readmission for any cause (HR90). Secondary outcomes included the prolonged length of stay (pLOS).
Key Results
Eight hundred two patients (median age 79 years) were included (414 RDP and 388 DDP). Comparing RDP vs. DDP periods, HR90 was 27.6% and 27.3% (OR 1.01, 90%CI 0.76–1.33, p = 0.485); and pLOS was 47 (11.4%) and 40 (10.3%) (OR 1.24, 95%CI 0.72–2.13, p = 0.447), respectively.
Conclusions
This is one of the largest randomized study conducted to compare the effectiveness of two different hospital discharge planning strategies. In patients with intermediate risk of hospital discharge, a RDP offers no advantage over a DDP and results in an unnecessary increase in staff workload.
Trial Registration
Clinicaltrials.gov: NCT03436940
Supplementary Information
The online version contains supplementary material available at 10.1007/s11606-023-08186-4.
Keywords: discharge planning, continuity of care, hospital readmission, cluster-randomized trial
INTRODUCTION
The hospital discharge represents a critical issue, especially for frail patients.1,2 The need for a timely and effective planning of discharge from acute hospitals has become of increasing importance, over the years, due to the higher number of elderly patients, the need to reduce hospitalization times, and a greater awareness of assuring continuity of care.3 In particular, a discharge is considered “complex” or “protected” when the acute event that led to hospitalization is followed by a condition of permanent or temporary disability, representing an obstacle to the return at home.3–5 The same problems may also arise in patients with chronic diseases admitted to hospital following an exacerbation of the same underlying disease or a deterioration of the overall clinical situation.
The impact of complex discharge on hospital activity is well known and it has been calculated that about 30% of all discharges in internal medicine wards are delayed by non-medical causes, mainly represented by the lack of effective discharge planning and reduced availability of long-term or rehabilitation centers.5 For these reasons, a careful and timely clinical care evaluation of the patient and a planning of the interventions necessary for a proper discharge are essential to assure the “continuity of care” of these patients.6 A recently updated Cochrane review reports that a structured discharge plan, tailored to the individual patient, may contribute to a small reduction of the hospital length of stay and of the readmission rates in older people with a medical condition.7 In addition, discharge planning strategies may be associated with an improvement in overall patient satisfaction with the care received as well as with an increase in health worker satisfaction.7
For a proper management of hospital discharges, it is necessary to timely identify the most critical cases, evaluating the psycho-physical and social conditions at admission and during hospitalization.3,6,8 In 2012, the Piedmont Region established the Continuity of Care Hospital Unit (CCHU) in each hospital to achieve an effective integration between hospitals and post-discharge health services. The CCHU provides support for hospitalized patients who may require ongoing healthcare after discharge due to their clinical conditions or frailty. Consisting of a team of physicians, nurses, and social workers, the CCHU collaborates closely with hospital department staff and the Local Health Unit (responsible for managing healthcare services after discharge) to develop personalized discharge plans. To identify patients at high risk who can benefit from the Continuity of Care Hospital Unit support, the Piedmont Region recommends using the Blaylock Risk Assessment Screening Score (BRASS) at the time of admission.9
In a previous study, we analyzed the performance of the BRASS instrument in our hospital and subsequently developed and validated a simplified version.10 While there is consensus on taking care of all high-risk patients (with a BRASS > 7 points), the best strategy for intermediate-risk patients (with a BRASS of 4–6) is unclear.
The purpose of the present study was to evaluate in the Internal Medicine and Neurology departments of our hospital the best strategy for intermediate-risk patients, by comparing in a cluster-randomized trial with multiple crossover a routine discharge planning versus an on-demand planning, according to the requests of the department staff.
METHODS
Study Design and Setting
This was a cluster-randomized, multiple crossover, non-blinded trial comparing two discharge planning strategies on patients admitted in the Internal Medicine and Neurology departments of the Molinette Hospital, Città della Salute e della Scienza in Turin, Italy (Trial Registration: ClinicalTrials.gov Identifier- NCT03436940). The eight departments involved in the study (6 Internal Medicine, 2 Neurology) were randomized to adopt the strategies of discharge planning (RDP [Routine Discharge Plan] and DDP [on-Demand Discharge Planning]) according to two different sequences, alternated over four periods of 3 months each (see Supporting Table S1). The departments of Internal Medicine and Neurology were selected for their highest prevalence (at the hospital level) of patients at risk of complex discharge. Moreover, in these departments, the BRASS is routinely recorded by nurses for all patients within 48 h from admission.
Participants
All patients aged 18 years or older residents in Piedmont consecutively admitted in the Internal Medicine or Neurology departments of the Molinette Hospital, with a simplified BRASS10 ranging from 4 to 6 (intermediate risk), between June 2018 and May 2019, were eligible to be included in the study. The local Ethics Committee (CS2/378/2017) approved this study.
Randomization
Randomization was performed by stratifying the departments (Internal Medicine, Neurology). In order to facilitate the conduct of the study, three of the four neurology departments that partially shared both inpatient and nursing wards were considered a single cluster for randomization. In addition, one of the five internal medicine units was separated into two different clusters as the hospital wards were located in different hospital areas. The departments were then randomly allocated to the sequences indicated in Supporting Table S1. The randomization was performed by AE using STATA version 13 (see Supporting Methods 1 for details). Actual allocations in the randomization sequences were reported in Supporting Table S2. Allocation was not masked.
Procedures
Within 48 h from admission, the simplified BRASS10 was calculated for each patient and was communicated to the CCHU. The simplified BRASS scale stratifies patients into low (score ≤ 3), intermediate (score 4–6), or high (score ≥ 7) risk of complex discharge. In patients at intermediate risk of complex discharge, the method for activating the discharge planning service was determined by the assignment resulting from the randomization procedure described in Supporting Fig. 1S (step 1). In each department, the discharge planning service was systematically activated by the CCHU during the RDP strategy period, and following individualized requests of the departments during the DDP strategy period. Patients for whom the special planning service of discharge is activated are taken care of during the hospitalization by a team of CCHU and evaluated together with the referring clinician (step 2). The special discharge planning service consists of a multidisciplinary assessment, which should result in a more appropriate post-acute and/or discharge pathway proposal on the basis of the patient’s clinical, welfare, and social needs. Patient needs may include transfers to rehabilitation hospitals or nursing homes, home care, palliative care, and provision of medical devices. Subsequently, the proposed discharge plan is shared with the patient and their caregivers (step 3).
A report describing the discharge plan is also sent for approval to the Local Health Unit according to the patient residence. In case of a negative response from the Local Health Unit or a change in clinical conditions or refusal by the caregiver and/or patient, the CCHU evaluation is reactivated to redefine a discharge plan.
Outcomes
The primary outcome was the proportion of hospital readmissions for any cause within 90 days from the date of discharge. The outcome was calculated only for patients discharged alive.
Secondary endpoints included:
Proportion of hospitalizations with long length of stay (pLOS [prolonged length of stay]). The endpoint was calculated for all hospitalized patients. A hospitalization was considered pLOS if its duration was greater than the 90th percentile of the specific DRG LOS calculated at regional level in Piedmont in 2016.
Proportion of deaths from any cause within 90 days of the date of discharge. The endpoint was calculated only for patients discharged alive.
Incidence of activations of the CCHU in the DDP and RDP periods.
Data Collection
The simplified BRASS was calculated by the nurses of the participating wards. Other patients’ demographic and clinical information were collected using the Hospital Discharge Records (SDOs). The SDOs of all hospitals in the Piedmont Region were used for the detection of readmissions in any hospital within 90 days from the date of patient discharge (primary outcome), the length of hospitalizations, and destinations of discharge. The 90-day survival status after discharge was ascertained through the Unique Regional Registry.
Sample Size
The study was designed to detect an absolute reduction of 7.5% (from 32.5 to 25%, odds ratio = 0.69) in the proportion of readmissions within 90 days of discharge of patients treated with RDP versus DDP. Based on the data collected for the year 2015, a total of 1000 patients discharged alive during the whole year from the departments included in the study would determine an 84% power to detect the hypothesized difference in the proportion of readmissions at 90 days (7.5%) between the two groups with a one-sided 5% alpha error. Taking into account the cluster randomization and the crossover design of the study (4 periods, 9 wards), the intervention was planned in 36 cluster-periods. Assuming an intraclass correlation coefficient (ICC) of 0.2% in the 90-day readmissions, with an average of approximately 28 patients enrolled in the 36 clusters, the power of the study would be approximately 79% (see Supporting Methods 2 for details).
Statistical Analysis
All patients were included in the analyses according to an intention to treat basis.
Due to the hierarchical structure of the data (patients nested within periods, periods nested within hospital wards), primary outcome (90-day hospital readmission) and dichotomous secondary outcomes were compared using three-level mixed-effects logistic regression models.11 We included as fixed effects the strategy variable (RDP or DDP) along with the variables indicating the stratification factors (Internal Medicine or Neurology ward), sequence (test for carry-over effect), and period, whereas hospital ward and period ward were included as random effects. Measures of effect were also reported by adjusting for age, gender, and simplified BRASS. A sensitivity analysis was performed for readmission and pLOS considering death in the absence of the two outcomes as a separate event and estimating the effect of the discharge strategy with the multinomial logistic model. Finally, we conducted an integrative analysis to evaluate the effect of the CCHU special discharge plan, regardless of the activation periods by RDP or DDP. We compared patient outcomes (90-day hospital readmission rates and pLOS) between those taken in charge by the CCHU and those who did not. To perform the comparisons, we used two-level mixed-effects logistic regression models, in which we considered the hospital ward as a random effect. For the primary outcome comparisons, 90% confidence intervals (CIs) were presented according to one-sided 5% alpha error used for the sample size considerations. For all other analyses, 95% CIs were reported. All statistical analyses were performed using STATA version 14.0.
Role of the Funding Source
The study was planned and conducted employing only staff personnel, without any external funding.
RESULTS
From June 2018 to May 2019, six wards of internal medicine and two wards of neurology were randomized to apply the two hospital discharge planning strategies at alternating periods based on two different sequences. Data were not collected during the first 2 months of 2019 for unavailability of the electronic databases due to system upgrading.
The mean number of patients who met the inclusion criteria admitted to each ward during each quarter was 25 (SD = 17). A total of 802 patients were included in the study (414 hospitalized during the RDP and 388 during the DDP strategy periods) and 754 (392 RDP, 362 DDP) were discharged alive and included in the comparison for the primary outcome of the study (90-day readmission) (Fig. 1).
Figure 1.
Study flow chart.
Overall, 720 (89.8%) patients were admitted in medicine wards and 82 (10.2%) in the neurology wards. The median age at admission was 79 years (IQR 70–84); and 406 (50.6%) were males. Diseases and disorders of the respiratory system (179 [22.3%]) and of the circulatory system (162 [20.2%]) were the most common conditions. Patient characteristics were well balanced between the period strategies except for gender (prevalence of females was 53.4% and 45.1% for RDP and DDP, respectively) (Table 1).
Table 1.
Characteristics of Patients by Allocation to the Discharge Planning Strategy Periods
| All periods | RDP periods | DDP periods | |
|---|---|---|---|
| N of patients | 802 | 414 | 388 |
| Males | 406 (50.6%) | 193 (46.6%) | 213 (54.9%) |
| Age at admission, median (IQR) | 79 (70, 84) | 78 (70, 84) | 79 (70, 84) |
| Age at admission, mean (SD) | 74.7 (13.7) | 74.4 (13.9) | 75.0 (13.6) |
| Simplified BRASS | |||
| 4 | 333 (41.5%) | 173 (41.8%) | 160 (41.2%) |
| 5 | 265 (33.0%) | 136 (32.9%) | 129 (33.2%) |
| 6 | 204 (25.4%) | 105 (25.4%) | 99 (25.5%) |
| Admission department | |||
| Internal medicine | 720 (89.8%) | 368 (88.9%) | 352 (90.7%) |
| Neurology | 82 (10.2%) | 46 (11.1%) | 36 (9.3%) |
| MDC at admission | |||
| Nervous system | 104 (13.0%) | 60 (14.5%) | 44 (11.3%) |
| Respiratory system DDs | 179 (22.3%) | 96 (23.2%) | 83 (21.4%) |
| Circulatory system DDs | 162 (20.2%) | 69 (16.7%) | 93 (24.0%) |
| Digestive system DDs | 56 (7.0%) | 34 (8.2%) | 22 (5.7%) |
| Hepatobiliary system and pancreas DDs | 37 (4.6%) | 21 (5.1%) | 16 (4.1%) |
| Musculoskeletal system and connective tissue DDs | 24 (3.0%) | 12 (2.9%) | 12 (3.1%) |
| Endocrine, nutritional, and metabolic system DDs | 41 (5.1%) | 19 (4.6%) | 22 (5.7%) |
| Kidney and urinary tract DDs | 39 (4.9%) | 15 (3.6%) | 24 (6.2%) |
| Blood and blood forming organs and immunological DDs | 21 (2.6%) | 9 (2.2%) | 12 (3.1%) |
| Myeloproliferative DDs (poorly differentiated neoplasms) | 20 (2.5%) | 11 (2.7%) | 9 (2.3%) |
| Infectious and parasitic DDs (systemic or unspecified sites) | 62 (7.7%) | 35 (8.5%) | 27 (7.0%) |
| Other disorders | 57 (7.1%) | 33 (8.0%) | 24 (6.2%) |
MDC, major diagnostic category; RDP, Routine Discharge Plan; DDP, on-Demand Discharge Planning; DDs, diseases and disorders
As expected, the incidence of activations of the CCHU for the discharge plan was higher during the RDP periods (286 [69.1%]) in comparison with the DDP periods (153 [39.4%]), with an absolute difference of + 29.6% (95%CI 23.1–36.2%) (Fig. 2).
Figure 2.
Proportion of patients with special planning service of discharge activated by study period.
Among the patients discharged alive, 90-day hospital readmission (primary outcome) was 27.6% in the RDP group and 27.3% in the DDP group (odds ratio [OR] 1.01, 90% CI 0.76 to 1.33, one-sided p = 0.485). Findings were nearly identical after adjustment for age, gender, and simplified BRASS (OR 1.01, 90% CI 0.76 to 1.34, one-sided p = 0.471) (Table 2). No significant carry-over (p = 0.531) or period (p = 0.460) effects were detected.
Table 2.
RDP vs. DDP Comparison on Primary and Secondary Endpoints
| Unadjusted for patient characteristics | Adjusted for patient characteristics§ | |||||
|---|---|---|---|---|---|---|
| RDP | DDP | OR RDP vs. DDP (95%CI) |
p | OR RDP vs. DDP (95%CI) |
p | |
| 414 | 388 | |||||
| Special planning service of discharge activated | 286 (69.1%) | 153 (39.4%) | ||||
| 90-day hospital readmission* | 108 (27.6%) | 99 (27.3%) | 1.01 (0.76, 1.33) | 0.485 | 1.01 (0.76, 1.34) | 0.471 |
| Prolonged length of stay | 47 (11.4%) | 40 (10.3%) | 1.24 (0.72, 2.13) | 0.447 | 1.25 (0.73, 2.14) | 0.421 |
| 90-day mortality* | 67 (16.2%) | 53 (13.7%) | 1.17 (0.78, 1.75) | 0.460 | 1.25 (0.82, 1.89) | 0.297 |
DDP, on-Demand Discharge Planning; RDP, Routine Discharge Plan
Confidence intervals are 95% and p-values are two-sided except for the primary outcome (90-day hospital readmission) which has 90% CI and one-sided p-value
*Including only patients discharged alive
§Adjusted for age, gender, and simplified BRASS score
Patients with pLOS were 47 (11.4%) during the RDP period and 40 during the DDP period (10.3%) (OR 1.24, 95% CI 0.72 to 2.13, p = 0.447) (Table 2).
After discharge, 67 (16.2%) admitted during the RDP period and 53 patients admitted during the DDP period (13.7%) died within 90 days (OR 1.17, 95% CI 0.78 to 1.75, p = 0.460) (Table 2).
Sensitivity analyses performed with multinomial logistic model on 90-day hospital readmission and pLOS confirmed no significant difference between the two discharge planning strategies (Supporting Table S3).
In Supporting Table S4, we reported the characteristics and outcomes of patients according to CCHU discharge plan activation, independently from study periods. Slightly higher in-hospital (6.8% vs. 5.0%) and 90-day post-discharge mortality (11.2% vs. 10.1%) among patients cared for by the CCHU suggest a potentially greater clinical complexity in this patient population. In Supporting Table S5, we reported the outcome comparisons according to the activation of the CCHU discharge plan. An absolute reduction, although not significant, in the risk of readmission within 90 days was found in patients referred by CCHU for a special discharge plan (25.4% vs. 29.9%, adjusted OR 0.79, 95% CI 0.57 to 1.10, p = 0.166). Similar results in term of the incidence of prolonged hospitalizations were found in the two groups of patients (11.4% vs. 10.2%, adjusted OR 1.16, 95%CI 0.74 to1.82, p = 0.528).
DISCUSSION
This cluster-randomized, multiple crossover trial is one of the largest randomized study conducted to compare the effectiveness of two different strategies of activating special hospital discharge planning. In patients at intermediate risk of complex discharge, a routine discharge planning strategy, compared to an on-demand strategy, was found to be not superior in reducing the incidence of hospital readmissions and of prolonged length of stay. Since a RDP strategy implies an increased burden of activity on the CCHU, these findings may have practice implications for patient management and for the reorganization of hospital care.
During the study, the implementation of the routine strategy was carried out for 69% of hospitalized patients screened with a BRASS of 4–6 points, suggesting some further selection operated by the treating physician, by local nurses, and also by the CCHU. On the other hand, during the DDP periods, it was considered by the ward staff that only 39% of the same population of patients could benefit from a special discharge planning by CCHU, corresponding to 56.5% relative reduction of workload.
The integrative analysis that we conducted in order to compare patients managed or not by the CCHU showed a nominal reduction in the risk of readmission (OR = 0.79) consistent with the main evidence on the efficacy of special discharge planning, which would result in a small reduction in readmission rates.7,12 Therefore, the lack of superiority of the routine activation strategy can be explained by assuming that in the intermediate-risk group only a minority of patients benefited from the plan.
Rasmussen et al. in their literature review12 suggest that the benefit of special discharge planning interventions may be wider in non-European settings. Indeed, among the studies evaluated in the review, all statistically significant associations were found in studies conducted in non-European countries. Hence, the impact of special discharge planning may be altered by the context of implementation, which may differ according to healthcare systems and social characteristics.
A weakness of our study was the reduction of about 20% of the expected sample size due to the interruption of the enrolment in the first 2 months of 2019, but the study design should have limited the risk of bias, limiting the problem only to the reduction of the hypothesized statistical power. This drawback, however, should not compromise the conclusions of our study, as the precision of the estimate (lower limit of the 90% confidence interval for the odds ratio = 0.76) allows us to exclude that the benefit of the routine strategy in reducing readmissions is compatible with what was assumed as a meaningful effect (odds ratio = 0.69).
In conclusion, our study suggests that a routine strategy in planning hospital discharge in patients with intermediate risk of complex discharge does not translate in any benefit for the patients while it is more demanding for the CCHU. The CCHU should therefore apply a routine approach to high-risk patients only, allowing the addition of selected patients at intermediate risk, selected by the ward staff.
Supplementary Information
Below is the link to the electronic supplementary material.
Data Availability
The data used for the study cannot be shared publicly as they contain sensitive information about the participants. Upon reasonable requests and with the approval of the local ethics eommittee, a de-identified dataset may be made available.
Declarations
Conflict of Interest
The authors declare that they do not have a conflict of interest.
Footnotes
An early version of this work was presented as an oral communication at the 46th Conference of the Italian Association of Epidemiology (Padua, Italy, 29 June–1 July 2022).
Publisher's Note
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data used for the study cannot be shared publicly as they contain sensitive information about the participants. Upon reasonable requests and with the approval of the local ethics eommittee, a de-identified dataset may be made available.