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      Emergency department presentation and readmission after index psychiatric admission: a data linkage study

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          Abstract

          Objective

          To use linked administrative datasets to assess factors associated with emergency department (ED) presentation and psychiatric readmission in three distinctive time intervals after the index psychiatric admission.

          Design

          A retrospective data-linkage study.

          Setting

          Cohort study using four linked government minimum datasets including acute hospital care from July 2005 to June 2012 in New South Wales, Australia.

          Participants

          People who were alive and aged ≥18 years on 1 July 2005 and who had their index admission to a psychiatric ward from 1 July 2007 to 30 June 2010.

          Outcome measures

          ORs of factors associated with psychiatric admission and ED presentation were calculated for three intervals: 0–1 month, 2–5 months and 6–24 months after index separation.

          Results

          Index admission was identified in 35 056 individuals (51% -males) with a median age of 42 years. A total of 12 826 (37%) individuals had at least one ED presentation in the 24 months after index admission. Of those, 3608 (28%) presented within 0–1 month, 6350 (50%) within 2–5 months and 10 294 (80%) within 6–24 months after index admission. A total of 14 153 (40%) individuals had at least one psychiatric readmission in the first 24 months. Of those, 6808 (48%) were admitted within 0–1 month, 6433 (45%) within 2–5 months and 7649 (54%) within 6–24 months after index admission. Principal diagnoses and length of stay at index admission, sociodemographic factors, Charlson Comorbidity Index score, drug and alcohol comorbidity, intellectual disability and other inpatient service use were significantly associated with ED presentations and psychiatric readmissions, and these relationships varied somewhat over the intervals studied.

          Conclusion

          Social determinants of service use, drug and alcohol intervention, addressing needs of individuals with intellectual disability and recovery-oriented whole-person approaches at index admission are key areas for investment to improve trajectories after index admission.

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          Most cited references35

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          Comorbidity of mental disorders with alcohol and other drug abuse. Results from the Epidemiologic Catchment Area (ECA) Study.

          The prevalence of comorbid alcohol, other drug, and mental disorders in the US total community and institutional population was determined from 20,291 persons interviewed in the National Institute of Mental Health Epidemiologic Catchment Area Program. Estimated US population lifetime prevalence rates were 22.5% for any non-substance abuse mental disorder, 13.5% for alcohol dependence-abuse, and 6.1% for other drug dependence-abuse. Among those with a mental disorder, the odds ratio of having some addictive disorder was 2.7, with a lifetime prevalence of about 29% (including an overlapping 22% with an alcohol and 15% with another drug disorder). For those with either an alcohol or other drug disorder, the odds of having the other addictive disorder were seven times greater than in the rest of the population. Among those with an alcohol disorder, 37% had a comorbid mental disorder. The highest mental-addictive disorder comorbidity rate was found for those with drug (other than alcohol) disorders, among whom more than half (53%) were found to have a mental disorder with an odds ratio of 4.5. Individuals treated in specialty mental health and addictive disorder clinical settings have significantly higher odds of having comorbid disorders. Among the institutional settings, comorbidity of addictive and severe mental disorders was highest in the prison population, most notably with antisocial personality, schizophrenia, and bipolar disorders.
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            Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community.

            Readmissions to hospital are common, costly and often preventable. An easy-to-use index to quantify the risk of readmission or death after discharge from hospital would help clinicians identify patients who might benefit from more intensive post-discharge care. We sought to derive and validate an index to predict the risk of death or unplanned readmission within 30 days after discharge from hospital to the community. In a prospective cohort study, 48 patient-level and admission-level variables were collected for 4812 medical and surgical patients who were discharged to the community from 11 hospitals in Ontario. We used a split-sample design to derive and validate an index to predict the risk of death or nonelective readmission within 30 days after discharge. This index was externally validated using administrative data in a random selection of 1,000,000 Ontarians discharged from hospital between 2004 and 2008. Of the 4812 participating patients, 385 (8.0%) died or were readmitted on an unplanned basis within 30 days after discharge. Variables independently associated with this outcome (from which we derived the mnemonic "LACE") included length of stay ("L"); acuity of the admission ("A"); comorbidity of the patient (measured with the Charlson comorbidity index score) ("C"); and emergency department use (measured as the number of visits in the six months before admission) ("E"). Scores using the LACE index ranged from 0 (2.0% expected risk of death or urgent readmission within 30 days) to 19 (43.7% expected risk). The LACE index was discriminative (C statistic 0.684) and very accurate (Hosmer-Lemeshow goodness-of-fit statistic 14.1, p=0.59) at predicting outcome risk. The LACE index can be used to quantify risk of death or unplanned readmission within 30 days after discharge from hospital. This index can be used with both primary and administrative data. Further research is required to determine whether such quantification changes patient care or outcomes.
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              Frequent use of the hospital emergency department is indicative of high use of other health care services.

              We sought to determine the proportion of emergency department patients who frequently use the ED and to compare their frequency of use of other health care services at non-ED sites. A computerized patient database covering all ambulatory visits and hospital admissions at all care facilities in the county of Stockholm, Sweden, was used. Frequent ED patients were defined as those making 4 or more visits in a 12-month period. Frequent users comprised 4% of total ED patients, accounting for 18% of the ED visits. The ED was the only source of ambulatory care for 13% of frequent versus 27% of rare ED users (1 ED visit). Primary care visits were made by 72% of frequent ED users versus 57% by rare ED visitors. The corresponding figures for hospital admission were 80% and 36%, respectively. Frequent ED visitors were also more likely to use other care facilities repeatedly: their odds ratio (adjusted for age and sex) was 3.43 (95% confidence interval [CI] 3.10 to 3.78) for 5 or more primary care visits and 29.98 (95% CI 26.33 to 34.15) for 5 or more hospital admissions. In addition, heavy users had an elevated mortality (standardized mortality ratio 1.55; 95% CI 1.26 to 1.90). High ED use patients are also high users of other health care services, presumably because they are sicker than average. A further indication of serious ill health is their higher than expected mortality. This knowledge might be helpful for care providers in their endeavors to find appropriate ways of meeting the needs of this vulnerable patient category.
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                Author and article information

                Journal
                BMJ Open
                BMJ Open
                bmjopen
                bmjopen
                BMJ Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2044-6055
                2018
                28 February 2018
                : 8
                : 2
                : e018613
                Affiliations
                [1 ] departmentDepartment of Developmental Disability Neuropsychiatry, School of Psychiatry , University of New South Wales , Sydney, New South Wales, Australia
                [2 ] departmentCentre for Healthy Brain Ageing, School of Psychiatry , University of New South Wales , Sydney, New South Wales, Australia
                Author notes
                [Correspondence to ] Professor Julian Trollor; J.Trollor@ 123456unsw.edu.au
                Author information
                http://orcid.org/0000-0002-7685-2977
                Article
                bmjopen-2017-018613
                10.1136/bmjopen-2017-018613
                5855390
                29490956
                87a72e32-7e49-4485-a24e-dd208773dca5
                © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 10 July 2017
                : 07 January 2018
                : 11 January 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Categories
                Health Services Research
                Research
                1506
                1704
                Custom metadata
                unlocked

                Medicine
                psychiatric admission,readmission,emergency department presentation,mental health service,data linkage

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