Implementing Inter-professional Discharge Planning to Reduce Time for Patient Discharge
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Discharge Planning to Reduce Time for Patient DischargeAbstract
Problem: Discharging patients from the hospital can be a complicated process that comes with challenges. Hospital data from the telemetry/ medical-surgical unit in August 2021 identified an average time of 419 minutes from the time of written discharge to the actual time the patient leaves the unit, and the goal time is 120 minutes. This delay has also affected emergency department length of stay as the average number in the hospital is approaching 4 hours. Purpose: To implement and evaluate the n-by-T strategy and interprofessional discharge planning in a telemetry/ medical-surgical unit to reduce the time between eligibility for discharge and time of discharge. Methods: The quality improvement project involves utilizing a discharge checklist with the n-by-T strategy during interprofessional rounds to safely schedule a number of patients (n) for the same or next day discharge by a goal time (T) for the patients on a 51-bed telemetry/ medical-surgical unit. The evaluation includes the use of the discharge checklist during discharge rounds, the average speed of the discharge process (difference in time of eligibility for discharge and time of discharge), the average time of discharges (this is the time the patient leaves the unit), the length of stay, the unit’s 7-day and 30-day readmission rates. Results: In August 2021 pre-implementation, the speed of discharge process was 419 minutes, and the length of stay was 4.33 days. Post implementation, the average speed of discharge was 628 minutes in October, 302 minutes in November, and 261 minutes in December. The average length of stay post-implementation was 4.04 days, 3.69 days, and 3.98 days, for October, November, and December, respectively. Conclusions: Implementation of interprofessional discharge planning and the n-by-T strategy was associated with decreased length of stay, and improved discharge speed.Identifier to cite or link to this item
http://hdl.handle.net/10713/18880Collections
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Day of Discharge Planning Utilizing the n-by-T StrategyBackground: Hospital discharges are a complex process that can directly impact a patient’s length of stay and decrease the quality of care that the patients receive. An ineffective discharge process increases the number of unplanned readmissions, which are costly to hospitals and affect patients negatively. Local Problem: The medical providers on the General Surgery Unit at a Maryland hospital recognized the need for a discharge process that would increase the number of before-noon discharges. The unit experienced many late-day discharges which would contribute to increased night shift admissions. The unit also experienced higher than average readmission rates when compared to the rest of the organization. Interventions: The purpose of this Doctor of Nursing Practice project was to implement and evaluate the n-by-T strategy into the discharge process for the medical patients on a 30-bed general surgery unit starting October 1, 2018. The quality improvement project involved utilizing a discharge checklist with the n-by-T strategy during morning rounds to safely schedule a number of patients (n) for same day discharge by a goal time (T). The medical director set a daily goal of two patients discharged by noon. Pre-implementation data was collected from September 1-30, 2018. Post-implementation data was collected from October 1, 2018 through November 30, 2018. Data collection included the use of the discharge checklist Monday through Friday during discharge rounds, the average time of discharges, the average length of the discharge process, and the unit’s 7-day and 30-day readmission rates. Results: Pre-implementation data collected in September 2018 showed an average time of discharge of 15:30, the average speed of the discharge process was 2.80 hours, the 7-day readmission rate for the unit was 7.27%, and the 30-day readmission rate for the unit was 21.82%. The average discharge time post-implementation was 15:26 and the average discharge process time was 2.99 hours. The 7-day readmission was 2.22% and 4.91% for October 2018 and November 2018, respectively. The 30-day readmission rate was 6.22% and 10.27% for October 2018 and November 2018, respectively. The discharge checklist was completed 38 out of 45 days, with an 84% completion rate Conclusions: There was no statistically significant change in the average discharge time or the average length of the discharge process. The readmission rates showed statistically significant improvement in 7-day and 30-day rates post-implementation. Post-implementation provider feedback was positive from the providers for placing an emphasis on prioritizing patients for earlier same-day discharges. The process of this quality improvement project was successful, though sustainability at the project site was dependent on a re-evaluation of the discharge checklist due to the time burden associated with it. Future projects are recommended to assess other methods, besides an independent discharge checklist, in assessing patient readiness for before-noon same-day discharges. Future projects also include implementation on other inpatient units within the organization or to outpatient settings, such as subacute rehabilitation facilities.
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Biopsychosocial Predictors of Perception of Discharge Readiness and Its Association to 30-day Readmission in Chronic Heart Failure PatientsBackground: Of 1 million U.S. patients discharged from hospitals with a diagnosis of heart failure (HF) annually, 24% will be readmitted to the hospital within 30 days. Since some readmissions are preventable, the identification of risk factors is critical to improve discharge processes. Lower readiness for hospital discharge (RHD) is a new risk factor that has been associated with re-hospitalization. Purpose: The purpose of this study was to: 1) establish the psychometric properties of the readiness for hospital discharge scale short form (RHDS-SF); 2) identify predictors of RHDS-SF scores; and 3) examine the association between patient assessment of readiness for hospital discharge and 7-day post discharge self-care of heart failure (SCHF) scores, and 30-day hospital readmission risk for HF patients discharged from acute care hospitals. Methods: A cross-sectional secondary data analysis of data from the Improving Heart Failure Outcomes (IHO) study was conducted. IHO was a prospective study examining nursing care of HF patients admitted to acute care hospitals. Subjects and Setting: Subjects included 487 HF patients from a national sample of 36 hospitals. Results: In this sample, 21% were readmitted within 30 days. The intra-class correlation coefficient for 30 day readmission was 19%. Cronbach's alpha estimates for the 3-item RHDS-SF, was acceptable (α= 0.74) [vs the 4-item RHDS-SF (α= 0.37)]. Multi-level modeling (MLM) methods with data nested within hospitals were used to test associations. Patient characteristics associated with RHD were: Beck Depression Inventory scores (t= -2.60, p=0.01), baseline SCHF confidence (t=2.90, p≤0.005), pre discharge Dutch HF knowledge (t=2.50, p= 0.01), age (t=-2.26, p=0.02), and New York Heart Association class (t=2.31, p=0.02). Predictors of HF self-care practices 7-days post hospital discharge were: nurse 3 item RHDS scores (t= 3.59, p≤0.05), baseline SCHF maintenance (t= 3.18, p≤0.005), and baseline SCHF confidence (t= 2.13, p=0.04). No significant association was found between readiness for hospital discharge and 30-day readmission. Conclusions: The psychometric estimates for the RHDS-SF 3-item scale are acceptable. Patient and nurse RHDS scores were significantly associated with SCHF scores 7 days post discharge. Lack of statistical power precluded adequate modeling of associations with 30-day readmission.
