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Nursing & Health Sciences Mar 2020A pilot study was conducted to determine the feasibility of a longitudinal investigation of patients' coping during the early postdischarge period. Recruitment was...
A pilot study was conducted to determine the feasibility of a longitudinal investigation of patients' coping during the early postdischarge period. Recruitment was conducted on a general medical unit and a surgical orthopedic unit. Forty-four participants were recruited with 95% retention. Demographic characteristics plus measures of discharge risk and perceived readiness (expected coping) were collected before discharge. Measures of coping (experienced) and the use of supports and services were collected on the first day postdischarge, the end of the first week, and during weeks 3 and 5. Considerable variability was evident in coping scores, and not all participants exhibited improvement over time. Four patterns of coping were identified: ongoing recovery, initial shock, bumpy road, and progressive decline. Further investigation is required to validate the observed coping patterns. A better understanding of conditions affecting patient coping during the transition from hospital to home will support efforts to reduce unplanned use of acute care services.
Topics: Adaptation, Psychological; Aged; Female; Humans; Longitudinal Studies; Male; Middle Aged; Patient Discharge; Patient Readmission; Patient Satisfaction; Patients' Rooms; Pilot Projects
PubMed: 31692227
DOI: 10.1111/nhs.12658 -
Physical Review. E Jun 2016The energy landscapes framework is applied to a configuration space generated by training the parameters of a neural network. In this study the input data consists of...
The energy landscapes framework is applied to a configuration space generated by training the parameters of a neural network. In this study the input data consists of time series for a collection of vital signs monitored for hospital patients, and the outcomes are patient discharge or continued hospitalisation. Using machine learning as a predictive diagnostic tool to identify patterns in large quantities of electronic health record data in real time is a very attractive approach for supporting clinical decisions, which have the potential to improve patient outcomes and reduce waiting times for discharge. Here we report some preliminary analysis to show how machine learning might be applied. In particular, we visualize the fitting landscape in terms of locally optimal neural networks and the connections between them in parameter space. We anticipate that these results, and analogues of thermodynamic properties for molecular systems, may help in the future design of improved predictive tools.
Topics: Electronic Health Records; Humans; Machine Learning; Neural Networks, Computer; Patient Discharge
PubMed: 27415390
DOI: 10.1103/PhysRevE.93.063310 -
Ontario Health Technology Assessment... 2013Chronically ill people experience frequent changes in health status accompanied by multiple transitions between care settings and care providers. Discharge planning... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Chronically ill people experience frequent changes in health status accompanied by multiple transitions between care settings and care providers. Discharge planning provides support services, follow-up activities, and other interventions that span pre-hospital discharge to post-hospital settings.
OBJECTIVE
To determine if discharge planning is effective at reducing health resource utilization and improving patient outcomes compared with standard care alone.
DATA SOURCES
A standard systematic literature search was conducted for studies published from January 1, 2004, until December 13, 2011.
REVIEW METHODS
Reports, randomized controlled trials, systematic reviews, and meta-analyses with 1 month or more of follow-up and limited to specified chronic conditions were examined. Outcomes included mortality/survival, readmissions and emergency department (ED) visits, hospital length of stay (LOS), health-related quality of life (HRQOL), and patient satisfaction.
RESULTS
One meta-analysis compared individualized discharge planning to usual care and found a significant reduction in readmissions favouring individualized discharge planning. A second meta-analysis compared comprehensive discharge planning with postdischarge support to usual care. There was a significant reduction in readmissions favouring discharge planning with postdischarge support. However, there was significant statistical heterogeneity. For both meta-analyses there was a nonsignificant reduction in mortality between the study arms.
LIMITATIONS
There was difficulty in distinguishing the relative contribution of each element within the terms "discharge planning" and "postdischarge support." For most studies, "usual care" was not explicitly described.
CONCLUSIONS
Compared with usual care, there was moderate quality evidence that individualized discharge planning is more effective at reducing readmissions or hospital LOS but not mortality, and very low quality evidence that it is more effective at improving HRQOL or patient satisfaction. Compared with usual care, there was low quality evidence that the discharge planning plus postdischarge support is more effective at reducing readmissions but not more effective at reducing hospital LOS or mortality. There was very low quality evidence that it is more effective at improving HRQOL or patient satisfaction.
Topics: Chronic Disease; Health Status; Hospital Mortality; Humans; Length of Stay; Ontario; Patient Discharge; Patient Readmission; Quality of Life
PubMed: 24167538
DOI: No ID Found -
Journal of Clinical Nursing May 2019To describe which nursing activities are observed during the discharge of older patients with chronic diseases and to investigate the consistency between the nursing... (Observational Study)
Observational Study
AIMS AND OBJECTIVES
To describe which nursing activities are observed during the discharge of older patients with chronic diseases and to investigate the consistency between the nursing activities actually observed and those documented.
BACKGROUND
The discharge from hospital of older patients with chronic diseases is a critical transition that can lead to dissatisfaction, delays in discharge, re-admission, adverse events and increased mortality. Although nurses' interventions during discharge are important for patient outcomes, little is known about the nursing activities actually performed as compared with those documented.
DESIGN
An observational study of the nursing activities performed during patients' discharge and a retrospective audit of the nursing records of the same patients and nurses.
METHODS
Structured nonparticipant observations were conducted of the activities performed by nurses at discharge. A retrospective audit of the nursing records relating to patient discharge, including the nursing diary and the assessment of critical issues at hospital discharge, was also conducted. The STROBE guidelines were followed (See Supporting Information Appendix S2).
RESULTS
During hospital discharge of 102 patients, 1,224 nursing activities were observed. The number of activities was not related to patients' age, gender and educational level, nor to nurses' postgraduate education. Statistically significant correlations emerged between the number of activities observed and the nurses' work experience.
CONCLUSIONS
A predefined discharge plan guiding nurses' activities during discharge would enable them to respond better to the care needs of elderly patients.
RELEVANCE TO CLINICAL PRACTICE
Results from the study could help clinical nurses to address care priorities of patients at discharge, by using appropriate plans and checklists and improving recording rates. Novice nurses should be supported when caring for elderly patients with chronic disease at discharge.
Topics: Adult; Aged; Chronic Disease; Female; Humans; Male; Nurse's Role; Nursing Records; Nursing Staff, Hospital; Patient Discharge; Retrospective Studies
PubMed: 30653788
DOI: 10.1111/jocn.14782 -
Urologic Oncology Feb 2022Hospital readmission is associated with adverse outcomes and increased cost, and as such, has been identified as a metric for surgical quality and a target for shifts in...
PURPOSE
Hospital readmission is associated with adverse outcomes and increased cost, and as such, has been identified as a metric for surgical quality and a target for shifts in health policy. However, the disposition of patients who undergo radical cystectomy for bladder cancer and the association between discharge locations and readmission rates is poorly understood. Understanding the patterns and characteristics of readmission after radical cystectomy will help inform discharge planning and expectations and may have long-term impacts on quality and cost of care delivery. We hypothesize that patients will have varying readmission rates based on their discharge location.
MATERIALS AND METHODS
An observational analysis of the Nationwide Readmissions Database was performed for all patients who underwent elective radical cystectomy in 2016 to 2017. The patients were grouped by the following criteria: whether they were discharged home, home with care, or to a facility. Univariate analysis was performed using the Chi-square test for categorical variables and the Kruskal-Wallis test for continuous variables. A multivariable logistic regression was conducted to evaluate if discharge locations impact patient readmissions at 30- and 90-days.
RESULTS
The final dataset included 4,947 patients discharged home with care, 2,127 patients discharged to home or self-care, and 1,232 patients discharged to a facility. Discharge to a facility was strongly associated with higher 30-day (OR 1.49, CI 1.26-1.76) and 90-day readmission rates (OR 1.46, CI 1.23-1.74). Additionally, home health care was strongly associated with increased 30-day readmission rates (OR 1.22, CI 1.08-1.37) relative to routine discharge home.
CONCLUSIONS
Our analysis suggests that discharge location independently predicts readmission following RC. Further study with more granular patient- and system-level data may aid in identifying structural characteristics and processes that can reduce readmissions and their associated economic impact, while maintaining quality of care delivered.
Topics: Aged; Cystectomy; Female; Humans; Male; Patient Discharge; Treatment Outcome
PubMed: 34393041
DOI: 10.1016/j.urolonc.2021.07.020 -
AMIA ... Annual Symposium Proceedings.... Nov 2009The discharge planning process can be successful when information is shared among the patient, caregiver, and provider from admission through post discharge. The... (Review)
Review
The discharge planning process can be successful when information is shared among the patient, caregiver, and provider from admission through post discharge. The objective of this paper was to evaluate the association of information sharing among patients, caregivers, and health care providers and the impact on the discharge process. The authors identified reports of the discharge planning process through systematic electronic database searches. The eligibility criteria were 1) usual discharge planning process, and 2) patient, caregiver, or provider perception or feedback. Of the eligible articles, all voiced concern about a broken discharge planning process that affected the information exchanged among all involved in patient care. Outcomes related to satisfaction, knowledge transfer, and communication were identified. The initial evidence suggests information sharing through interdisciplinary patient care can play a significant role in the future.
Topics: Humans; Information Dissemination; Medical Informatics; Outcome Assessment, Health Care; Patient Discharge
PubMed: 20351814
DOI: No ID Found -
The Health Care Manager 2019Hospital leaders encourage morning discharge of patients to boost patient flow. This work presents a detailed process of a building model for forecasting patient...
Hospital leaders encourage morning discharge of patients to boost patient flow. This work presents a detailed process of a building model for forecasting patient discharge before noon applying the Box-Jenkins methodology using weekly historic data. Accurately forecasting is of crucial importance to plan early discharge activities, influenced by the fluctuations in daily discharges process. The objective is to find an appropriate autoregressive integrated moving average (ARIMA) model for forecasting the rate of patients out by noon based on the lowest error in a statistical forecast by applying the mean absolute percentage error. The results obtained demonstrate that a nonseasonal ARIMA model classified as ARIMA(2,1,1) offers a good fit to actual discharge-before-noon data and proposes hospital leaders short-term prediction that could facilitate decision-making process, which is important in an uncertain health care system environment.
Topics: Forecasting; Humans; Models, Statistical; Patient Discharge; Time Factors
PubMed: 30920992
DOI: 10.1097/HCM.0000000000000262 -
Annals of the Royal College of Surgeons... Apr 2016Introduction Discharge planning improves patient outcomes, reduces hospital stay and readmission rates, and should involve a multidisciplinary team (MDT) approach. The...
Introduction Discharge planning improves patient outcomes, reduces hospital stay and readmission rates, and should involve a multidisciplinary team (MDT) approach. The efficacy of MDT meetings in discharge planning was examined, as well as reasons for delayed discharge among vascular surgical inpatients. Methods Dedicated weekly MDT meetings were held on the vascular ward in Royal Derby Hospital for three months. Each patient was presented to the discharge planning meeting and an expected date of discharge was decided prospectively. Patients who were discharged after this date were considered 'delayed' and reasons for delay were explored at the next meeting. Results Overall, 193 patients were included in the study. Of these, 42 patients (22%) had a delayed discharge while 29 (15%) had an early discharge. The main reasons for delay were awaiting beds (30%), social (14%) and medical (45%). In 64%, the cause for delay was avoidable. Two-thirds (67%) of all delays were >24 hours. This totalled 115 bed days, of which 67 could have been avoided. However, 32 bed days were saved by early discharge. This equates to a net loss of 35 bed days, at a net cost of £2,936 per month or £35,235 per year. The MDT meetings also improved the quality of discharge planning; the variability between expected and actual discharge dates decreased after the first month. Conclusions Discharge planning meetings help prepare for patient discharge and are most effective with multidisciplinary input. The majority of delayed discharges from hospital are preventable. The main causes are awaiting transfers, social services input and medical reasons (eg falls). There is an obvious financial incentive to improve discharge planning. The efficiency of the MDT at discharge planning improves with time and this should therefore be continued for best results.
Topics: Humans; Length of Stay; Patient Care Team; Patient Discharge; Prospective Studies; Vascular Surgical Procedures
PubMed: 26924480
DOI: 10.1308/rcsann.2016.0093 -
Clinical Nursing Research Oct 2016Patient characteristics and lack of preparedness are associated with poor outcomes after hospital discharge. Our purpose was to explore the association between patient...
Patient characteristics and lack of preparedness are associated with poor outcomes after hospital discharge. Our purpose was to explore the association between patient characteristics and patient- and nurse-completed Readiness for Hospital Discharge Scale (RHDS). We conducted a prospective study of 70 Veterans being discharged from medical and surgical units. Differences in RHDS knowledge subscale scores were found among literacy levels, with lower perceived knowledge reported for those with marginal or inadequate literacy (p = .03). Differences in RHDS expected support subscale scores were also found, with those who were unmarried and/or living alone (p < .001) anticipating less support upon discharge. No other differences were found. Similar differences were found for the RHDS completed by nurses. These findings suggest that the RHDS appears responsive to differences in health literacy and social environment, adding to evidence of its utility as a tool to identify, and plan interventions for, those at risk for readmission.
Topics: Adult; Aged; Aged, 80 and over; Female; Health Literacy; Humans; Male; Middle Aged; Nursing Staff; Patient Discharge; Patient Readmission; Prospective Studies; Social Support; Surveys and Questionnaires; Veterans
PubMed: 26787745
DOI: 10.1177/1054773815624380 -
Journal of Nursing Management Apr 2019(a) Assess nurses' readiness to learn (RTL) before receiving education on the re-engineered discharge (RED) programme and (b) measure utilization of the RED discharge...
AIMS
(a) Assess nurses' readiness to learn (RTL) before receiving education on the re-engineered discharge (RED) programme and (b) measure utilization of the RED discharge process from patient chart reviews following an educational intervention.
BACKGROUND
Preventable readmissions are of great concern. Rural areas are at a disadvantage, due to decreased access to health care and other disparities.
METHODS
Sixty-nine participants completed the Self-Directed Learning Readiness Scale prior to the RED education intervention. Thirty-minute education interventions were provided addressing various learning preferences.
RESULTS
Participants scored high M = 219.8 (SD 23.7) on the SDLR, indicating nurses' high RTL prior to educational intervention. Chart reviews found usage of the RED 12 actionable item pre-intervention, (n = 60) M = 6.55 (SD 1.478) compared to post-intervention (n = 60) M = 10.08 (SD 1.544) indicated statistically significant improvement in pre-discharge patient education and planning (t = 17.730, p = 0.000 [CI 3.13-3.93]).
CONCLUSION
Current study found that nurses with higher levels of RTL who underwent RED educational sessions significantly improved delivery of the RED process documented in the medical record.
IMPLICATIONS FOR NURSING MANAGEMENT
Those responsible for education initiatives must make understanding nurses' learning preferences a priority to improve the quality of bedside practice.
Topics: Adult; Aged; Clinical Competence; Education, Nursing, Continuing; Female; Humans; Male; Middle Aged; Nursing Staff, Hospital; Patient Discharge; Program Evaluation; Quality Improvement; Surveys and Questionnaires
PubMed: 30223308
DOI: 10.1111/jonm.12719