A lifespan strategy to prevent adverse outcomes associated with psychiatric hospitalisation
Bibliographic record
Abstract
Psychiatric hospitalisation is not a desired outcome. It disrupts an individual's life and is costly to the health-care system.1Stensland M Watson PR Grazier KL An examination of costs, charges, and payments for inpatient psychiatric treatment in community hospitals.Psychiatr Serv. 2012; 63: 666-671Crossref PubMed Scopus (66) Google Scholar Few individuals with mental illness ever require hospitalisation, but this subset is inarguably the most ill. Comprehensive data for some of the most devastating outcomes that can occur, such as suicide, homicide, and accidental death, are lacking for this group. Research by Florian Walter and colleagues2Walter F Carr MJ Mok PLH et al.Multiple adverse outcomes following first discharge from inpatient psychiatric care: a national cohort study.Lancet Psychiatry. 2019; (published online June 3.)http://dx.doi.org/10.1016/S2215-0366(19)30180-4Summary Full Text Full Text PDF PubMed Scopus (39) Google Scholar in The Lancet Psychiatry gathered Danish population-level registry data for more than 60 000 individuals after discharge from their first psychiatric hospitalisation. These individuals were compared with more than 1·5 million non-hospitalised individuals on their risks of all-cause mortality, suicide, accidental death, non-fatal self-harm, perpetration of violent criminality, and being hospitalised because of violence post-discharge over a long period. For some individuals, data were available for more than 20 years post-discharge. Over time, individuals who had been psychiatric inpatients were at substantially increased risk for each of the adverse outcomes, with 32·0% (95% CI 31·6–32·5)having at least one outcome in the first 10 years after discharge, versus 3·5% (3·5–3·6) of the comparators who had never been hospitalised: around a ten-fold increase in risk. The period of highest risk was the first 3 months post-discharge, especially for suicide and for self-harm (the most common adverse outcome), but risks remained elevated among former psychiatric inpatients in the long term. Although these findings are perhaps not surprising, and align with previous literature,3Walter F Carr MJ Mok PLH et al.Premature mortality among patients recently discharged from their first inpatient psychiatric treatment.JAMA Psychiatry. 2017; 74: 485-492Crossref PubMed Scopus (28) Google Scholar, 4Chung DT Ryan CJ Hadzi-Pavlovic D Singh SP Stanton C Large MM Suicide rates after discharge from psychiatric facilities: a systematic review and meta-analysis.JAMA psychiatry. 2017; 74: 694-702Crossref PubMed Scopus (305) Google Scholar, 5Gatov E Rosella L Chiu M Kurdyak PA Trends in standardized mortality among individuals with schizophrenia, 1993–2012: a population-based, repeated cross-sectional study.CMAJ. 2017; 189: E1177-E1187Crossref PubMed Scopus (52) Google Scholar these results appear to be the first quantification of these outcomes together on a population level. The strong observational study design, and long-term follow-up with outcomes measured using two national patient health registers, a national crime register, and a national death register, lend credence to the results. One important point to emphasise is that this was an epidemiological study, designed appropriately to highlight health disparities and raise awareness about the need to address them. The goal was not to isolate the causal effects of psychiatric hospitalisation (or mental illness) on the risk for these negative outcomes. What the independent effect of psychiatric hospitalisation or severe mental illness might be if all of the other factors that could be driving outcome risk were measurable and accounted for is not known. Such factors include, but are not limited to, socioeconomic marginalisation (poverty and unemployment), social environment effects (history of abuse and violence, alienation from familial support systems, or social isolation), and medical complexity (burden of acute and chronic illnesses). These risk factors are known to be elevated in populations of people hospitalised for psychiatric problems.6Allen J Balfour R Bell R Marmot M Social determinants of mental health.Int Rev Psychiatry. 2014; 26: 392-407Crossref PubMed Scopus (475) Google Scholar We believe that the value of Walter and colleagues' study2Walter F Carr MJ Mok PLH et al.Multiple adverse outcomes following first discharge from inpatient psychiatric care: a national cohort study.Lancet Psychiatry. 2019; (published online June 3.)http://dx.doi.org/10.1016/S2215-0366(19)30180-4Summary Full Text Full Text PDF PubMed Scopus (39) Google Scholar is therefore not only in increasing our understanding about psychiatric hospitalisation as a process of care, but also in showing how much psychiatric hospitalisation probably acts as an aggregate proxy for a number of factors that increase the likelihood of adverse outcomes, and shorten lives. This study speaks to the need to find ways to reduce the risks of adverse outcomes by focusing on the complex system of post-discharge services and resources. Improving post-discharge outcomes is a laudable goal. Some evidence exists around which post-discharge and transitional care models could reduce risk for various adverse outcomes,7Vigod SN Kurdyak PA Dennis CL et al.Transitional interventions to reduce early psychiatric readmissions in adults: systematic review.Br J Psychiatry. 2013; 202: 187-194Crossref PubMed Scopus (162) Google Scholar and we hope that Walter and colleagues study2Walter F Carr MJ Mok PLH et al.Multiple adverse outcomes following first discharge from inpatient psychiatric care: a national cohort study.Lancet Psychiatry. 2019; (published online June 3.)http://dx.doi.org/10.1016/S2215-0366(19)30180-4Summary Full Text Full Text PDF PubMed Scopus (39) Google Scholar will stimulate more research about how to safeguard people discharged from inpatient psychiatric care. However, considering only the time after the psychiatric hospitalisation might not address the elevated risk of adverse outcomes that persist long after the brief period following discharge, and that are based on risk factors that develop over a lifetime. A more upstream lifespan approach could reduce exposure to some of the developmental factors that underlie adverse outcomes such as those being studied.6Allen J Balfour R Bell R Marmot M Social determinants of mental health.Int Rev Psychiatry. 2014; 26: 392-407Crossref PubMed Scopus (475) Google Scholar, 8Lewis AJ Galbally M Gannon T Symeonides C Early life programming as a target for prevention of child and adolescent mental disorders.BMC Med. 2014; 12: 33Crossref PubMed Scopus (112) Google Scholar Such an approach could help to prevent psychiatric hospitalisations, or even the development of a serious mental illness, in the first place. This approach would have to be multi-pronged, with input from the public health, social services, and medical sectors. Indicators or metrics of success would not necessarily be measurable in the short term—a challenge for garnering investment from governing bodies with a need to demonstrate immediate results. However, complex problems are not often successfully addressed with simple solutions. The epidemiological evidence generated in Walter and colleagues' study2Walter F Carr MJ Mok PLH et al.Multiple adverse outcomes following first discharge from inpatient psychiatric care: a national cohort study.Lancet Psychiatry. 2019; (published online June 3.)http://dx.doi.org/10.1016/S2215-0366(19)30180-4Summary Full Text Full Text PDF PubMed Scopus (39) Google Scholar highlights the intense susceptibility of people hospitalised for psychiatric disorders to very serious outcomes for a long time after their first hospitalisation. Many of these outcomes are not rare, and are occurring in very young people, and especially in young men, who could otherwise have many years to contribute to society. Therefore, although a more upstream approach to prevention might be disruptive and expensive in the short term, this study and other research on the developmental origins of health and disease and on the social determinants of health suggest that this approach could have the greatest long-term gain. Research to more precisely explain the mechanisms for the observed outcome disparities in this at-risk group will guide the nature of the comprehensive social and health programmes aiming to prevent them. SNV has received royalties from UpToDate Inc related to authorship of materials regarding depression and pregnancy. PAK declares no competing interests. Multiple adverse outcomes following first discharge from inpatient psychiatric care: a national cohort studyPeople discharged from inpatient psychiatric care are at higher risk than the rest of the population for a range of serious fatal and non-fatal adverse outcomes. Improved inter-agency liaison, intensive follow-up immediately after discharge, and longer-term social support are indicated. Full-Text PDF Open Access
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".