A qualitative exploration of the discharge process and factors predisposing to readmissions to the intensive care unit.
ABSTRACT: Quantitative studies have demonstrated several factors predictive of readmissions to intensive care. Clinical decision tools, derived from these factors have failed to reduce readmission rates. The purpose of this study was to qualitatively explore the experiences and perceptions of physicians and nurses to gain more insight into intensive care readmissions.Semi-structured interviews of intensive care unit (ICU) and general medicine care providers explored work routines, understanding and perceptions of the discharge process, and readmissions to intensive care. Participants included ten providers from the ICU setting, including nurses (n?=?5), consultant intensivists (n?=?2), critical care fellows (n?=?3) and 9 providers from the general medical setting, nurses (n?=?4), consulting physicians (n?=?2) and senior resident physicians (n?=?3). Principles of grounded theory were used to analyze the interview transcripts.Nine factors within four broad themes were identified: (1) patient factors - severity-of-illness and undefined goals of care; (2) process factors - communication, transitions of care; (3) provider factors - discharge decision-making, provider experience and comfort level; (4) organizational factors - resource constraints, institutional policies.Severe illness predisposes ICU patients to readmission, especially when goals of care were not adequately addressed. Communication, premature discharge, and other factors, mostly unrelated to the patient were also perceived by physicians and nurses to be associated with readmissions to intensive care. Quality improvement efforts that focus on modifying or improving aspects of non-patient factors may improve outcomes for patients at risk of ICU readmission.
Project description:Reducing the 30-day unplanned hospital readmission rate is a goal for physicians and policymakers in order to improve quality of care. However, data on the readmission rate of critically ill patients in Japan and knowledge of the predictors associated with readmission are lacking. We investigated predictors associated with 30-day rehospitalization for medical and surgical adult patients separately.Patient data from 502 acute care hospitals with intensive care unit (ICU) facilities in Japan were retrospectively extracted from the Japanese Diagnosis Procedure Combination (DPC) database between April 2012 and February 2014. Factors associated with unplanned hospital readmission within 30 days of hospital discharge among medical and surgical ICU survivors were identified using multivariable logistic regression analysis.Of 486,651 ICU survivors, we identified 5583 unplanned hospital readmissions within 30 days of discharge following 147,423 medical hospitalizations (3.8% readmitted) and 11,142 unplanned readmissions after 339,228 surgical hospitalizations (3.3% readmitted). The majority of unplanned hospital readmissions, 60.9% of medical and 63.1% of surgical case readmissions, occurred within 15 days of discharge. For both medical and surgical patients, the Charlson comorbidity index score; category of primary diagnosis during the index admission (respiratory, gastrointestinal, and metabolic and renal); hospital length of stay; discharge to skilled nursing facilities; and having received a packed red blood cell transfusion, low-dose steroids, or renal replacement therapy were significantly associated with higher unplanned hospital readmission rates.From patient data extracted from a large Japanese national database, the 30-day unplanned hospital readmission rate after ICU stay was 3.4%. Further studies are required to improve readmission prediction models and to develop targeted interventions for high-risk patients.
Project description:Variation in intensive care unit (ICU) readmissions and in-hospital mortality after ICU discharge may indicate potential for improvement and could be explained by ICU discharge practices. Our objective was threefold: (1) describe variation in rates of ICU readmissions within 48 h and post-ICU in-hospital mortality, (2) describe ICU discharge practices in Dutch hospitals, and (3) study the association between rates of ICU readmissions within 48 h and post-ICU in-hospital mortality and ICU discharge practices.We analysed data on 42,040 admissions to 82 (91.1%) Dutch ICUs in 2011 from the Dutch National Intensive Care Evaluation (NICE) registry to describe variation in standardized ICU readmission and post-ICU mortality rates using funnel-plots. We send a questionnaire to all Dutch ICUs. 75 ICUs responded and their questionnaire data could be linked to 38,498 admissions in the NICE registry. Generalized estimation equations analyses were used to study the association between ICU readmissions and post-ICU mortality rates and the identified discharge practices, i.e. (1) ICU discharge criteria; (2) bed managers; (3) early discharge planning; (4) step-down facilities; (5) medication reconciliation; (6) verbal and written handover; (7) monitoring of post-ICU patients; and (8) consulting ICU nurses. In all analyses, the outcomes were corrected for patient-related confounding factors.The standardized rate of ICU readmissions varied between 0.14 and 2.67 and 20.8% of the hospitals fell outside the 95% control limits and 3.6% outside the 99.8% control limits. The standardized rate of post-ICU mortality varied between 0.07 and 2.07 and 17.1% of the hospitals fell outside the 95% control limits and 4.9% outside the 99.8% control limits. We could not demonstrate an association between the eight ICU discharge practices and rates of ICU readmissions or post-ICU in-hospital mortality. Implementing a higher number of ICU discharge practices was also not associated with better patient outcomes.We found both variation in patient outcomes and variation in ICU discharge practices between ICUs. However, we found no association between discharge practices and rates of ICU readmissions or post-ICU mortality. Further research is necessary to find factors, which may influence these patient outcomes, in order to improve quality of care.
Project description:<h4>Background</h4>The transition out of the hospital is a vulnerable time for patients, relying heavily on communication and coordination of resources across care settings. Understanding the perspectives of inpatient and outpatient physicians regarding factors contributing to readmission and potential preventive strategies is crucial in designing appropriately targeted readmission prevention efforts.<h4>Objective</h4>To examine and compare inpatient and outpatient physician opinions regarding reasons for readmission and interventions that might have prevented readmission.<h4>Design</h4>Cross-sectional multicenter study.<h4>Participants</h4>We identified patients readmitted to general medicine services within 30 days of discharge at 12 US academic medical centers, and surveyed the primary care physician (PCP), discharging physician from the index admission, and admitting physician from the readmission regarding their endorsement of pre-specified factors contributing to the readmission and potential preventive strategies.<h4>Main measures</h4>We calculated kappa statistics to gauge agreement between physician dyads (PCP-discharging physician, PCP-admitting physician, and admitting-discharging physician).<h4>Key results</h4>We evaluated 993 readmission events, which generated responses from 356 PCPs (36 % of readmissions), 675 discharging physicians (68 % of readmissions), and 737 admitting physicians (74 % of readmissions). The most commonly endorsed contributing factors by both PCPs and inpatient physicians related to patient understanding and ability to self-manage. The most commonly endorsed preventive strategies involved providing patients with enhanced post-discharge instructions and/or support. Although PCPs and inpatient physicians endorsed contributing factors and potential preventive strategies with similar frequencies, agreement among the three physicians on the specific factors and/or strategies that applied to individual readmission events was poor (maximum kappa 0.30).<h4>Conclusions</h4>Differing opinions among physicians on factors contributing to individual readmissions highlights the importance of communication between inpatient and outpatient providers at discharge to share their different perspectives, and suggests that multi-faceted, broadly applied interventions may be more successful than those that rely on individual providers choosing specific services based on perceived risk factors.
Project description:Intensive care unit (ICU) readmission rates are commonly viewed as indicators of ICU quality. However, definitions of ICU readmissions vary, and it is unknown which, if any, readmissions are associated with ICU quality.Empirically derive the optimal interval between ICU discharge and readmission for purposes of considering ICU readmission as an ICU quality indicator.Retrospective cohort study.A total of 214,692 patients discharged from 157 US ICUs participating in the Project IMPACT database, 2001-2008.We graphically examined how patient characteristics and ICU discharge circumstances (eg, ICU census) were related to the odds of ICU readmissions as the allowable interval between ICU discharge and readmission was lengthened. We defined the optimal interval by identifying inflection points where these relationships changed significantly and permanently.A total of 2242 patients (1.0%) were readmitted to the ICU within 24 hours; 9062 (4.2%) within 7 days. Patient characteristics exhibited stronger associations with readmissions after intervals >48-60 hours. By contrast, ICU discharge circumstances and ICU interventions (eg, mechanical ventilation) exhibited weaker relationships as intervals lengthened, with inflection points at 30-48 hours. Because of the predominance of afternoon readmissions regardless of time of discharge, using intervals defined by full calendar days rather than fixed numbers of hours produced more valid results.It remains uncertain whether ICU readmission is a valid quality indicator. However, having established 2 full calendar days (not 48 h) after ICU discharge as the optimal interval for measuring ICU readmissions, this study will facilitate future research designed to determine its validity.
Project description:Evidence indicates that suboptimal clinical handover from the intensive care unit (ICU) to general wards leads to unnecessary ICU readmissions and increased mortality. We aimed to gain insight into barriers and facilitators to implement and use ICU discharge practices.A mixed methods approach was conducted, using 1) 23 individual and four focus group interviews, with post-ICU patients, ICU managers, and nurses and physicians working in the ICU or general ward of ten Dutch hospitals, and 2) a questionnaire survey, which contained 27 statements derived from the interviews, and was completed by 166 ICU physicians (21.8%) from 64 Dutch hospitals (71.1% of the total of 90 Dutch hospitals).The interviews resulted in 66 barriers and facilitators related to: the intervention (e.g., feasibility); the professional (e.g., attitude towards checklists); social factors (e.g., presence or absence of a culture of feedback); and the organisation (e.g., financial resources). A facilitator considered important by ICU physicians was a checklist to structure discharge communication (92.2%). Barriers deemed important were lack of a culture of feedback (55.4%), an absence of discharge criteria (23.5%), and an overestimation of the capabilities of general wards to care for complex patients by ICU physicians (74.7%).Based on the barriers and facilitators found in this study, improving handover communication, formulating specific discharge criteria, stimulating a culture of feedback, and preventing overestimation of the general ward are important to effectively improve the ICU discharge process.
Project description:BACKGROUND:Various factors can contribute to high mortality rates in intensive care units (ICUs). Here, we intended to define a population of patients readmitted to general ICUs in Poland and to identify independent predictors of ICU readmission. METHODS:Data derived from adult ICU admissions from the Silesian region of Poland were analyzed. First-time ICU readmissions (?30 days from ICU discharge after index admissions) were compared with first-time ICU admissions. Pre-admission and admission variables that independently influenced the need for ICU readmission were identified. RESULTS:Among the 21,495 ICU admissions, 839 were first-time readmissions (3.9%). Patients readmitted to the ICU had lower mean APACHE II (21.2 ± 8.0 vs. 23.2 ± 8.8, p < 0.001) and TISS-28 scores (33.7 ± 7.4 vs. 35.2 ± 7.8, p < 0.001) in the initial 24 h following ICU admission, compared to first-time admissions. ICU readmissions were associated with lower mortality vs. first-time admissions (39.2% vs. 44.3%, p = 0.004). Independent predictors for ICU readmission included the admission from a surgical ward (among admission sources), chronic respiratory failure, cachexia, previous stroke, chronic neurological diseases (among co-morbidities), and multiple trauma or infection (among primary reasons for ICU admission). CONCLUSIONS:High mortality associated with first-time ICU admissions is associated with a lower mortality rate during ICU readmissions.
Project description:<h4>Objective</h4>To evaluate whether communication failures between home health care nurses and physicians during an episode of home care after hospital discharge are associated with hospital readmission, stratified by patients at high and low risk of readmission.<h4>Data source/study setting</h4>We linked Visiting Nurse Services of New York electronic medical records for patients with congestive heart failure in 2008 and 2009 to hospitalization claims data for Medicare fee-for-service beneficiaries.<h4>Study design</h4>Linear regression models and a propensity score matching approach were used to assess the relationship between communication failure and 30-day readmission, separately for patients with high-risk and low-risk readmission probabilities.<h4>Data collection/extraction methods</h4>Natural language processing was applied to free-text data in electronic medical records to identify failures in communication between home health nurses and physicians.<h4>Principal findings</h4>Communication failure was associated with a statistically significant 9.7 percentage point increase in the probability of a patient readmission (32.6 percent of the mean) among high-risk patients.<h4>Conclusions</h4>Poor communication between home health nurses and physicians is associated with an increased risk of hospital readmission among high-risk patients. Efforts to reduce readmissions among this population should consider focusing attention on this factor.
Project description:OBJECTIVES:Unplanned readmissions to the intensive care unit (ICU) are highly undesirable, increasing variance in care, making resource planning difficult and potentially increasing length of stay and mortality in some settings. Identifying patients who are likely to suffer unplanned ICU readmission could reduce the frequency of this adverse event. SETTING:A single academic, tertiary care hospital in the UK. PARTICIPANTS:A set of 3326 ICU episodes collected between October 2014 and August 2016. All records were of patients who visited an ICU at some point during their stay. We excluded patients who were ?16 years of age; visited ICUs other than the general and neurosciences ICU; were missing crucial electronic patient record measurements; or had indeterminate ICU discharge outcomes or very early or extremely late discharge times. After exclusion, 2018 outcome-labelled episodes remained. PRIMARY AND SECONDARY OUTCOME MEASURES:Area under the receiver operating characteristic curve (AUROC) for prediction of unplanned ICU readmission or in-hospital death within 48?hours of first ICU discharge. RESULTS:In 10-fold cross-validation, an ensemble predictor was trained on data from both the target hospital and the Medical Information Mart for Intensive Care (MIMIC-III) database and tested on the target hospital's data. This predictor discriminated between patients with the unplanned ICU readmission or death outcome and those without this outcome, attaining mean AUROC of 0.7095 (SE 0.0260), superior to the purpose-built Stability and Workload Index for Transfer (SWIFT) score (AUROC=0.6082, SE 0.0249; p=0.014, pairwise t-test). CONCLUSIONS:Despite the inherent difficulties, we demonstrate that a novel machine learning algorithm based on transfer learning could achieve good discrimination, over and above that of the treating clinicians or the value added by the SWIFT score. Accurate prediction of unplanned readmission could be used to target resources more efficiently.
Project description:<h4>Background</h4>Hospital readmissions is an increasingly serious international problem, associated with higher risks of adverse events, especially in elderly patients. There can be many causes and influential factors leading to hospital readmissions, but they are often closely related, making hospital readmissions an overall complex area. In addition, a comprehensive coordination reform was introduced into the Norwegian healthcare system in 2012. The reform changed the premises for readmissions with economic incentives enhancing early transfer from secondary to primary care, making research on readmissions in the municipalities more urgent than ever. General practitioners (GPs) and nursing home physicians, have traditionally held a gatekeepers function in hospital readmissions from the municipal healthcare service, as they are the main decision-makers in questions of hospital readmissions. Still, the GPs' gatekeeper function is an under-investigated area in hospital readmission research. The aim of the study was to increase knowledge about factors that lead to hospital readmissions among elderly in municipal healthcare, with special attention to GPs' and nursing home physicians' decision making.<h4>Method</h4>The study was conducted as a comparative case study. Two municipalities affiliated with the same hospital, but with different readmission rates were recruited. Twenty GPs and nursing home physicians from each municipality were recruited and interviewed. Forty hours of observation were conducted during the huddles in one long-term and one short-term nursing home in each municipality.<h4>Results</h4>Seven themes describing how different factors influence physicians' decision-making in the hospital readmission process in two municipalities were identified. Poor communication, continuity and information flow account for hospital readmissions in both municipalities. Several factors, including nurse staffing and competence, patients and their families, time constraints and experience affected physicians' decision-making.<h4>Conclusion</h4>Communication, continuity and information flow contributed to hospital readmissions in both municipalities. The cross-case analysis revealed slight differences between municipalities. More research focusing on GPs' and nursing home physicians' decision-making, nursing home nurses and home care nurses' experience of hospital readmissions and discharges is needed.
Project description:Heart failure is a prevalent health problem associated with costly hospital readmissions. Transitional care programs have been shown to reduce readmissions but are costly to implement. Evidence regarding the effectiveness of telemonitoring in managing the care of this chronic condition is mixed. The objective of this randomized controlled comparative effectiveness study is to evaluate the effectiveness of a care transition intervention that includes pre-discharge education about heart failure and post-discharge telephone nurse coaching combined with home telemonitoring of weight, blood pressure, heart rate, and symptoms in reducing all-cause 180-day hospital readmissions for older adults hospitalized with heart failure.A multi-center, randomized controlled trial is being conducted at six academic health systems in California. A total of 1,500 patients aged 50 years and older will be enrolled during a hospitalization for treatment of heart failure. Patients in the intervention group will receive intensive patient education using the 'teach-back' method and receive instruction in using the telemonitoring equipment. Following hospital discharge, they will receive a series of nine scheduled health coaching telephone calls over 6 months from nurses located in a centralized call center. The nurses also will call patients and patients' physicians in response to alerts generated by the telemonitoring system, based on predetermined parameters. The primary outcome is readmission for any cause within 180 days. Secondary outcomes include 30-day readmission, mortality, hospital days, emergency department (ED) visits, hospital cost, and health-related quality of life.BEAT-HF is one of the largest randomized controlled trials of telemonitoring in patients with heart failure, and the first explicitly to adapt the care transition approach and combine it with remote telemonitoring. The study population also includes patients with a wide range of demographic and socioeconomic characteristics. Once completed, the study will be a rich resource of information on how best to use remote technology in the care management of patients with chronic heart failure.ClinicalTrials.gov # NCT01360203.