How does discharge against medical advice affect risk of mortality and unplanned readmission? A retrospective cohort study set in a large UK medical admissions unit.
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ABSTRACT: Objectives
To assess the frequency of discharge against medical advice (DAMA) in a large UK teaching hospital, explore factors which increase the risk of DAMA and identify how DAMA impacts patient risk of mortality and readmission.Design
Retrospective cohort study.Setting
Large acute teaching hospital in the UK.Patients
36 683 patients discharged from the acute medical unit of a large UK teaching hospital between 1 January 2012 and 31 December 2016.Measurements
Patients were censored on 1 January 2021. Mortality and 30-day unplanned readmission rates were assessed. Deprivation, age and sex were taken as covariates.Results
3% of patients discharged against medical advice. These patients were younger (median age (years) (IQR)): planned discharge (PD) 59 (40-77); DAMA 39 (28-51), predominantly of male sex (PD 48%; DAMA 66%) and were of greater social deprivation (in three most deprived quintiles PD 69%; DAMA 84%). DAMA was associated with increased risk of death in patients under the age of 33.3 years (adjusted HR 2.6 (1.2-5.8)) and increased incidence of 30-day readmission (standardised incidence ratio 1.9 (1.5-2.2)).Limitations
Readmission to acute hospitals outside of the local health board may have been missed. We were unable to include information regarding comorbidity or severity of presentation.Conclusions
These data highlight the vulnerability of younger patients who DAMA, even in a free-at-the-point-of-delivery healthcare setting.
SUBMITTER: Alagappan A
PROVIDER: S-EPMC10069606 | biostudies-literature | 2023 Mar
REPOSITORIES: biostudies-literature
Publications
How does discharge against medical advice affect risk of mortality and unplanned readmission? A retrospective cohort study set in a large UK medical admissions unit.
Alagappan Anand A Chambers Thomas J G TJG Brown Erik E Grecian Sheila M SM Lockman Khalida Ann KA
BMJ open 20230327 3
<h4>Objectives</h4>To assess the frequency of discharge against medical advice (DAMA) in a large UK teaching hospital, explore factors which increase the risk of DAMA and identify how DAMA impacts patient risk of mortality and readmission.<h4>Design</h4>Retrospective cohort study.<h4>Setting</h4>Large acute teaching hospital in the UK.<h4>Patients</h4>36 683 patients discharged from the acute medical unit of a large UK teaching hospital between 1 January 2012 and 31 December 2016.<h4>Measurement ...[more]
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Project description:BackgroundDischarge against medical advice may be associated with more readmissions.ObjectiveTo evaluate DAMA in patients with acute ischemic stroke (AIS) and identify the relationship between DAMA and 30-day unplanned readmissions.DesignA retrospective cohort study.ParticipantsThe National Readmission Database was used to identify inpatients with a primary diagnosis of AIS who were either discharged home or DAMA between 2010 and 2017 in the USA.MeasuresDemographic features, hospital type, comorbidities, stroke risk factors, severity indices, and treatments were compared between patients discharged routinely and DAMA. Multivariable logistic regression was used to evaluate predictors of DAMA, and a double robust inverse probability of treatment weighting method was used to assess the association between DAMA and 30-day unplanned readmissions.Key resultsOverall, 1,335,484 patients with AIS were included, of whom 2.09% (n = 27,892) were DAMA. The prevalence of DAMA in AIS patients increased from 1.65 in 2010 to 2.57% in 2017. The rates of 30-day unplanned readmissions for DAMA and non-DAMA patients were 16.81% and 7.78%, respectively. Patients with drug abuse, alcohol abuse, smoking, prior stroke, psychoses, and intravenous thrombolysis had greater odds of DAMA. DAMA was associated with all-cause readmissions (OR, 2.04; 95% CI, 2.01-2.07) and remained a strong predictor for transient ischemic attack/stroke-specific and cardiac-specific causes of readmissions.ConclusionsAlthough the DAMA rate is low in AIS patients, DAMA is a risk factor for all-cause and recurrent stroke-specific readmissions. Future studies are needed to address issues around compliance and engagement with health care to reduce DAMA.
| S-EPMC8131431 | biostudies-literature
Project description:BackgroundReducing 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.MethodsPatient 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.ResultsOf 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.ConclusionsFrom 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.
| S-EPMC5831844 | biostudies-literature
Project description:ImportanceHospital readmissions contribute to higher expenditures and may sometimes reflect suboptimal patient care. Individuals discharged against medical advice (AMA) are a vulnerable patient population and may have higher risk for readmission.ObjectivesTo determine odds of readmission and mortality for patients discharged AMA vs all others, to characterize patient and hospital-level factors associated with readmissions, and to quantify their overall cost burden.Design, setting, and participantsNationally representative, all-payer cohort study using the 2014 National Readmissions Database. Eligible index admissions were nonobstetrical/newborn hospitalizations for patients 18 years and older discharged between January 2014 and November 2014. Admissions were excluded if there was a missing primary diagnosis, discharge disposition, length of stay, or if the patient died during that hospitalization. Data were analyzed between January 2018 and June 2018.ExposuresDischarge AMA and non-AMA discharge.Main outcomes and measuresThirty-day all-cause readmission and in-hospital mortality rate.ResultsThere were 19.9 million weighted index admissions, of which 1.5% resulted in an AMA discharge. Within the AMA cohort, 85% were younger than 65 years, 63% were male, 55% had Medicaid or other (including uninsured) coverage, and 39% were in the lowest income quartile. Thirty-day all-cause readmission was 21.0% vs 11.9% for AMA vs non-AMA discharge (P < .001), and 30-day in-hospital mortality was 2.5% vs 5.6% (P < .001), respectively. Individuals discharged AMA were more likely to be readmitted to a different hospital compared with non-AMA patients (43.0% vs 23.9%; P < .001). Of all 30-day readmissions, 19.0% occurred within the first day after AMA discharge vs 6.1% for non-AMA patients (P < .001). On multivariable regression, AMA discharge was associated with a 2.01 (95% CI, 1.97-2.05) increased adjusted odds of readmission and a 0.80 (95% CI, 0.74-0.87) decreased adjusted odds of in-hospital mortality compared with non-AMA discharge. Nationwide readmissions after AMA discharge accounted for more than 400 000 inpatient hospitalization days at a total cost of $822 million in 2014.Conclusions and relevanceIndividuals discharged AMA have higher odds of 30-day readmission at significant cost to the health care system and lower in-hospital mortality rates compared with non-AMA patients. Patients discharged AMA are also more likely to be readmitted to different hospitals and to have earlier bounce-back readmissions, which may reflect dissatisfaction with their initial episode of care.
| S-EPMC7290410 | biostudies-literature
Project description:IntroductionDischarge against medical advice (DAMA) is an unexpected event for patients and healthcare personnel. The study aimed to assess the prevalence of DAMA in neonates along with characteristics of neonates who got DAMA and, causes and predictors of DAMA.Methods and findingsThis case-control study was carried out in Special Care Newborn Unit (SCANU) at Chittagong Medical College Hospital from July 2017 to December 2017. Clinical and demographic characteristics of neonates with DAMA were compared with that of discharged neonates. The causes of DAMA were identified by a semi-structured questionnaire. Predictors of DAMA were determined using a logistic regression model with a 95% confidence interval. A total of 6167 neonates were admitted and 1588 got DAMA. Most of the DAMA neonates were male (61.3%), term (74.7%), outborn (69.8%), delivered vaginally (65.7%), and had standard weight at admission (54.3%). A significant relationship (p < 0.001) was found between the variables of residence, place of delivery, mode of delivery, gestational age, weight at admission, and day and time of outcome with the type of discharge. False perceptions of wellbeing (28.7%), inadequate facilities for mothers (14.5%), and financial problems (14.1%) were the prevalent causes behind DAMA. Predictors of DAMA were preterm gestation (AOR 1.3, 95% CI 1.07-1.7, p = 0.013), vaginal delivery (AOR 1.56, 95% CI 1.31-1.86, p < 0.001), timing of outcome after office hours (AOR 477.15, 95% CI 236-964.6, p < 0.001), and weekends (AOR 2.55, 95% CI 2.06-3.17, p < 0.001). Neonates suffering from sepsis (AOR 1.4, 95% CI 1.1-1.7, p< 0.001), Respiratory Distress Syndrome (AOR 3.1, 95% CI 1.9-5.2, p< 0.001), prematurity without other complications (AOR 2.1, 95% CI 1.45-3.1, p < 0.001) or who were referred from north-western districts (AOR 1.48, 95% CI 1.13-1.95, p = 0.004) had higher odds for DAMA.ConclusionsIdentification of predictors and reasons behind DAMA may provide opportunities to improve the hospital environment and service related issues so that such vulnerable neonates can complete their treatment. We should ensure better communication with parents, provide provision for mothers' corner, especially for outborn neonates, maintain a standard ratio of neonates and healthcare providers, and adopt specific DAMA policy by the hospital authority.
| S-EPMC10118186 | biostudies-literature
Project description:ObjectivesUnplanned 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.SettingA single academic, tertiary care hospital in the UK.ParticipantsA 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 measuresArea under the receiver operating characteristic curve (AUROC) for prediction of unplanned ICU readmission or in-hospital death within 48 hours of first ICU discharge.ResultsIn 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).ConclusionsDespite 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.
| S-EPMC5640090 | biostudies-literature
Project description:PurposeEarly discharge from the intensive care unit (ICU) may constitute a strategy of resource consumption optimization; however, unplanned readmission of hospitalized patients to an ICU is associated with a worse outcome. We aimed to compare the effectiveness of the Stability and Workload Index for Transfer score (SWIFT), Sequential Organ Failure Assessment score (SOFA) and simplified Therapeutic Intervention Scoring System (TISS-28) in predicting unplanned ICU readmission or unexpected death in the first 48 hours after discharge from the ICU.MethodsWe conducted a prospective cohort study in a single tertiary hospital in southern Brazil. All adult patients admitted to the ICU for more than 24 hours from January 2008 to December 2009 were evaluated. SWIFT, SOFA and TISS-28 scores were calculated on the day of discharge from the ICU. A stepwise logistic regression was conducted to evaluate the effectiveness of these scores in predicting unplanned ICU readmission or unexpected death in the first 48 hours after discharge from the ICU. Moreover, we conducted a direct accuracy comparison among SWIFT, SOFA and TISS-28 scores.ResultsA total of 1,277 patients were discharged from the ICU during the study period. The rate of unplanned ICU readmission or unexpected death in the first 48 hours after discharge from the ICU was 15% (192 patients). In the multivariate analysis, age (P = 0.001), length of ICU stay (P = 0.01), cirrhosis (P = 0.03), SWIFT (P = 0.001), SOFA (P = 0.01) and TISS-28 (P<0.001) constituted predictors of unplanned ICU readmission or unexpected death. The SWIFT, SOFA and TISS-28 scores showed similar predictive accuracy (AUC valueswere 0.66, 0.65 and 0.67, respectively; P = 0.58) [corrected].ConclusionsSWIFT, SOFA and TISS-28 on the day of discharge from the ICU have only moderate accuracy in predicting ICU readmission or death. The present study did not find any differences in accuracy among the three scores.
| S-EPMC4658118 | biostudies-literature
Project description:ImportanceChildren born very preterm (<32 weeks) are at risk of ongoing morbidity and admission to pediatric intensive care units (PICUs) in childhood. However, the influence of the timing of neonatal discharge on unplanned PICU admission has not been established.ObjectiveTo examine whether the timing of neonatal discharge (postmenstrual age and season) is associated with subsequent unplanned PICU admission.Design, setting, and participantsThis retrospective cohort study used linked national data from the National Neonatal Research Database and Paediatric Intensive Care Audit Network (PICANet) for children born from January 2013 to December 2018 at 22 to 31 weeks' gestational age who were admitted to a neonatal unit in England and Wales and were discharged home at 34 weeks' postmenstrual age or later. All National Health Service (NHS) neonatal units and PICUs in England and Wales were included. Children were followed up until 2 years of chronological age. Data analysis was conducted from October 2023 to August 2024.ExposuresTiming of discharge.Main outcomes and measuresThe primary outcome was unplanned PICU admission between neonatal discharge and chronological age 2 years to any PICU within England and Wales. Survival analysis using a flexible parametric model was conducted with season of discharge (time-dependent factor), gestation, sex, birth weight less than the 10th centile, bronchopulmonary dysplasia, necrotizing enterocolitis, brain injury, and earlier neonatal discharge (lower quartile of postmenstrual age at discharge for gestation) as variables.ResultsOf 39 938 children discharged home (median [IQR] gestational age, 29 [27-31] weeks; 21 602 [54.1%] male), 1878 (4.7%) had unplanned PICU admission. More than half of admissions occurred within 50 days of neonatal discharge (1080 [57.5%]). Compared with summer, the risk of unplanned PICU admission following neonatal discharge was 2.58 times higher in winter and 2.35 times higher in autumn (winter: adjusted hazard ratio [aHR], 2.58; 95% CI, 1.68-3.95; autumn: aHR, 2.35; 95% CI, 1.84-2.99). Among children born at 28 to 31 weeks' gestational age, earlier neonatal discharge was associated with increased risk (aHR, 1.30; 95% CI, 1.13-1.49), but this was not true for children born younger than 28 weeks' gestational age.Conclusions and relevanceIn this retrospective cohort study of preterm children, autumn and winter discharge were associated with the highest risk of unplanned PICU admission following neonatal discharge. For children born at 28 to 31 weeks' gestational age, discharge at lower postmenstrual age was also associated with increased risk. Further work is required to understand whether delaying neonatal discharge for some children born at 28 to 31 weeks' gestational age is beneficial and to consider the wider costs and implications of prolonging neonatal care.
| S-EPMC11565260 | biostudies-literature
Project description:Hospital readmissions due to COVID-19 are one of the main concerns for the health system due to risks to the patient's life and increased use of health resources. Studies focusing on this issue are important to understand the risk factors and create strategies to avoid readmissions. We evaluated the readmission of patients with confirmed COVID-19 in a private hospital in southern Brazil, between March 2020 and 2021. Also, the characteristics and clinical outcomes of patients admitted to the intensive care unit (ICU) and nonadmitted were compared. Poisson regression models with prevalence ratio (PR) with 95% confidence intervals (95% CIs) were applied to confirm the association between variables and ICU admission. Of the 2084 hospitalized patients with COVID-19, 1806 were discharged alive. Among them, 106 were readmitted for unplanned reasons during one year. Early hospital readmission (≤30 days) occurred in 52.8% of the cases. The main reasons were respiratory, gastroenterological, kidney, and cardiac disease. The median age was 73.0 years old and women correspond to 52.8%. The presence of at least one comorbidity was detected in 87.7% of patients. Hypertension, diabetes, cardiac, and lung disease were more frequent. The ICU admitted patients (n = 43; 40.5%) mostly had 4-5 comorbidities, pulmonary involvement ≥50%, length of stay (LOS), and days between discharge and first readmission. Longer LOS (PR: 3.46; 95% CI: 1.24-5.67), days between discharge/first readmission (PR: 2.21; 95% CI: 1.15-5.88), and pulmonary involvement (≥50%; PR: 1.59; 95% CI: 1.11-3.54) were independently associated with ICU admission. Longer LOS, longer days between discharge/first readmission, and pulmonary involvement (≥50%) were associated with ICU admission in readmitted patients. Readmissions evaluation is pivotal and may help in ensuring safe care transition and postdischarge follow-up.
| S-EPMC9347576 | biostudies-literature
Project description:ObjectiveTo study characteristics and outcomes of patients with stroke, traumatic brain injury (TBI), and epilepsy with discharge against medical advice (DAMA).Data sources/study settingRetrospective analysis of the 2013 Nationwide Readmissions Database, a nationally representative inpatient administrative dataset.Study designAssociations between predictors and DAMA at index admission were analyzed using adjusted logistic models. We examined 30-day all-cause readmissions.Data collection methodsPatients aged ≥18 years at index admission for International Classification of Diseases-9 diagnosis code of epilepsy, TBI, or stroke were included.Principal findingsDischarge against medical advice occurred in 1998/58278 patients (3.43 percent) in the epilepsy group, 1762/211 213 (0.83 percent) in the stroke group, and 1289/74 652 (1.73 percent) in the TBI group. Factors consistently associated with increased likelihood of DAMA included lower age, male sex, non-Medicare and nonprivate insurance, lower socioeconomic status, and behavioral risk factors (smoking history, alcohol history, and drug use). The crude 30-day all-cause readmission rate for those with DAMA from their index admission was 16.4 percent for the stroke cohort, 13.9 percent for epilepsy, and 13.4 percent for TBI. DAMA at index admission was significantly associated with increased risk of 30-day all-cause readmission among all groups (adjusted odds ratio 1.79, 95% CI: 1.65-1.94, P < .0001).ConclusionsAge, sex, insurance status, socioeconomic status, and behavioral factors were associated with DAMA in neurological patients. Further research is needed to develop interventions to reduce DAMA in high-risk groups.
| S-EPMC7518816 | biostudies-literature
Project description:ImportanceAlthough discharges against medical advice (DAMA) are associated with greater morbidity and mortality, little is known about current racial and ethnic disparities in DAMA from the emergency department (ED) nationally.ObjectiveTo characterize current patterns of racial and ethnic disparities in rates of ED DAMA.Design, setting, and participantsThis cross-sectional study used data from the Nationwide Emergency Department Sample on all hospital ED visits made between January to December 2019 in the US.Main outcomes and measuresThe main outcome was odds of ED DAMA for Black and Hispanic patients compared with White patients nationally and in analysis adjusted for sociodemographic factors. Secondary analysis examined hospital-level variation in DAMA rates for Black, Hispanic, and White patients.ResultsThe study sample included 33 147 251 visits to 989 hospitals, representing the estimated 143 million ED visits in 2019. The median age of patients was 40 years (IQR, 22-61 years). Overall, 1.6% of ED visits resulted in DAMA. DAMA rates were higher for Black patients (2.1%) compared with Hispanic (1.6%) and White (1.4%) patients, males (1.7%) compared with females (1.5%), those with no insurance (2.8%), those with lower income (<$27 999; 1.9%), and those aged 35 to 49 years (2.2%). DAMA visits were highest at metropolitan teaching hospitals (1.8%) and hospitals that served greater proportions of racial and ethnic minoritized patients (serving ≥57.9%; 2.1%). Odds of DAMA were greater for Black patients (odds ratio [OR], 1.45; 95% CI, 1.31-1.57) and Hispanic patients (OR, 1.16; 95% CI, 1.04-1.29) compared with White patients. After adjusting for sociodemographic characteristics (age, sex, income, and insurance status), the adjusted OR (AOR) for DAMA was lower for Black patients compared with the unadjusted OR (AOR, 1.18; 95% CI, 1.09-1.28) and there was no difference in odds for Hispanic patients (AOR, 1.03; 95% CI, 0.92-1.15) compared with White patients. After additional adjustment for hospital random intercepts, DAMA disparities reversed, with Black and Hispanic patients having lower odds of DAMA compared with White patients (Black patients: AOR, 0.94 [95% CI, 0.90-0.98]; Hispanic patients: AOR, 0.68 [95% CI, 0.63-0.72]). The intraclass correlation in this secondary analysis model was 0.118 (95% CI, 0.104-0.133).Conclusions and relevanceThis national cross-sectional study found that Black and Hispanic patients had greater odds of ED DAMA than White patients in unadjusted analysis. Disparities were reversed after patient-level and hospital-level risk adjustment, and greater between-hospital than within-hospital variation in DAMA was observed, suggesting that Black and Hispanic patients are more likely to receive care in hospitals with higher DAMA rates. Structural racism may contribute to ED DAMA disparities via unequal allocation of health care resources in hospitals that disproportionately treat racial and ethnic minoritized groups. Monitoring variation in DAMA by race and ethnicity and hospital suggests an opportunity to improve equitable access to health care.
| S-EPMC10685883 | biostudies-literature