Exploring the predictors of early readmission to psychiatric hospital

A predictive model for readmission within 1-year post-discharge in patients with schizophrenia

BACKGROUND

Schizophrenia is a pervasive and severe mental disorder characterized by significant disability and high rates of recurrence. The persistently high rates of readmission after discharge present a serious challenge and source of stress in treating this population. Early identification of this risk is critical for implementing targeted interventions. The present study aimed to develop an easy-to-use predictive instrument for identifying the risk of readmission within 1-year post-discharge among schizophrenia patients in China.

METHODS

A prediction model, based on static factors, was developed using data from 247 schizophrenia inpatients admitted to the Mental Health Center in Wuxi, China, from July 1 to December 31, 2020. For internal validation, an additional 106 patients were included. Multivariate Cox regression was applied to identify independent predictors and to create a nomogram for predicting the likelihood of readmission within 1-year post-discharge. The model's performance in terms of discrimination and calibration was evaluated using bootstrapping with 1000 resamples.

RESULTS

Multivariate cox regression demonstrated that involuntary admission (adjusted hazard ratio [aHR] 4.35, 95% confidence interval [CI] 2.13-8.86), repeat admissions (aHR 3.49, 95% CI 2.08-5.85), the prescription of antipsychotic polypharmacy (aHR 2.16, 95% CI 1.34-3.48), and a course of disease ≥ 20 years (aHR 1.80, 95% CI 1.04-3.12) were independent predictors for the readmission of schizophrenia patients within 1-year post-discharge. The area under the curve (AUC) and concordance index (C-index) of the nomogram constructed from these four factors were 0.820 and 0.780 in the training set, and 0.846 and 0.796 for the validation set, respectively. Furthermore, the calibration curves of the nomogram for both the training and validation sets closely approximated the ideal diagonal line. Additionally, decision curve analyses (DCAs) demonstrated a significantly better net benefit with this model.

CONCLUSIONS

A nomogram, developed using pre-discharge static factors, was designed to predict the likelihood of readmission within 1-year post-discharge for patients with schizophrenia. This tool may offer clinicians an accurate and effective way for the timely prediction and early management of psychiatric readmissions.

Factors Associated with Readmission within 30 Days of Hospital Discharge of Psychiatric Patients: Case-Control Study

BACKGROUND

Readmission, defined as any admission after discharge from the same hospital, has negative implications for health outcomes. This study aims to identify the sociodemographic and clinical factors associated with hospital readmission among psychiatric patients.

METHODOLOGY

This case-control study analyzed 202 clinical records of patients admitted to a psychiatric hospital between 2019-2021. The sample was selected using simple random sampling. Qualitative variables were presented using frequencies, percentages, and chi-square tests for association. Quantitative variables were described using central tendency measures and dispersion of data, investigated with the Kolmogorov-Smirnov test, Student's t-test or Wilcoxon test as appropriate. Regression analysis was conducted to determine factors linked to readmission. p < 0.05 was considered.

RESULTS

Women accounted for a higher readmission rate (59%). Patients diagnosed with schizophrenia had a higher readmission rate (63%), experienced longer transfer times to the hospital during readmissions, and had shorter hospital stays. Polypharmacy and pharmacological interactions were associated with readmission. Olanzapine treatment was identified as a risk factor for readmission (ExpB = 3.203, 95% CI 1.405-7.306, p = 0.006).

CONCLUSIONS

The findings suggest avoiding polypharmacy and medications with high side effect profiles to reduce readmissions. This study offers valuable insights for clinical decision-making from admission to discharge planning, aiming to enhance the quality of care.

Importance of GP contact on readmission rate following psychiatric acute care: A Danish Nationwide study

Insufficient acute psychiatric care substantially impacts patient well-being and healthcare quality. Early readmissions after discharge from psychiatric care are common, and preventing these is important for the patients as well as appropriate resource allocation. The relationship between post-discharge general practitioner (GP) contact and readmission rates remains to be explored, as does the association between pre-hospital GP contact and post-discharge engagement.

AIM

This study examines post-discharge GP contact and its association with outpatient revisits and inpatient readmissions among unplanned psychiatric hospital contacts, including the impact of pre-visit GP contact on post-discharge care within 14 days.

METHODS

Utilizing data from the Danish healthcare system (2019-2023), unplanned psychiatric hospital contacts and subsequent 14-day GP encounters were analyzed.

RESULTS

Of 298,085 unplanned psychiatric hospital contacts, 12.6% had a 14-day revisit as an outpatient and 13.6% had a 14-day readmission as an inpatient. During regular business hours, GP contact was associated with a decreased risk of unplanned outpatient revisits (HR 0.45, 95% CI 0.44-0.47) and inpatient readmissions (HR 0.43, 95% CI 0.41-0.44). Similarly, utilizing GP on-call services was linked to a reduced risk of unplanned revisits (HR 0.87, 95% CI 0.81-0.94) and readmissions (HR 0.81, 95% CI 0.76-0.87). Having a GP contact within two days before an unplanned psychiatric hospital contact increased the likelihood of having a GP contact within 14 days post-discharge.

CONCLUSION

Post-discharge GP encounters were associated with lower rates of 14-day outpatient revisits and inpatient readmissions following unplanned psychiatric hospital contacts. GP contact before psychiatric hospital contact enhances attendance at post-discharge appointments, suggesting a potential efficacy of promoting GP appointments for mental health care.

Metabolic disturbances are risk factors for readmission to psychiatric hospitals in non-smokers but not in smokers: results from a Swiss psychiatric cohort and in first-episode psychosis patients

Background

Psychiatric patients are at high risk of readmission, and a high body mass index has previously been shown as a risk factor. We sought to replicate this finding and 1) to prospectively assess the association of metabolic syndrome and its five components with readmission in psychiatric hospitals and 2) to identify other clinical and sociodemographic predictors of readmission.

Methods

Between 2007 and 2019, data on 16727 admissions of 7786 adult and elderly patients admitted to the Department of Psychiatry of the Lausanne University Hospital, were collected. Metabolic syndrome was defined according to the International Diabetes Federation definition. Cox frailty models were used to investigate the associations between readmission and metabolic disturbances.

Results

A total of 2697 (35%) patients were readmitted to our psychiatric hospital. Novel risk factors for readmission in non-smokers were identified, including being overweight (HR=1.26; 95%CI=[1.05; 1.51]) or obese (HR=1.33; 95%CI=[1.08; 1.62]), displaying hypertriglyceridemia (HR=1.21; 95%CI=[1.04; 1.40]) and metabolic syndrome (HR=1.26; 95%CI=[1.02; 1.55]). Central obesity and hyperglycemia increased the risk of readmission when considering the Health of the Nation Outcome Scales variable. In first-episode psychosis patients, obesity (HR=2.23; 95%CI=[1.14; 4.30]) and high-density lipoprotein hypocholesterolemia (HR=1.90; 95%CI=[1.14; 3.20]) doubled the risk of readmission.

Conclusion

The observed interaction between smoking and metabolic variables are compatible with a ceiling effect; metabolic variables increase the risk of readmission in non-smokers but not in smokers who are already at higher risk. Future studies should determine whether better metabolic monitoring and treatment can reduce readmission risk.

Effects of the Implementation of a Patient-Oriented Discharge Summary (PODS) on Pre- and Postdischarge Outcomes

A patient-oriented discharge summary (PODS) is a patient-facing process to provide best practices in discharge planning. The PODS process was implemented in phases in 22 units of a large, publicly funded psychiatric hospital in Canada. The authors studied 7,624 discharges. Sustained implementation of the PODS process attained an ongoing PODS completion rate of 86.5%. Rates of medication reconciliation, patient-centered medication education, follow-up appointment scheduling, and medical discharge summary completion within 48 hours of discharge significantly improved over the implementation phase. Despite high uptakes of these best practices, more distal outcomes (e.g., follow-up appointment attendance and hospital readmission) did not improve.

A 13-item Health of the Nation Outcome Scale (HoNOS-13): validation by item response theory (IRT) in patients with substance use disorder

BACKGROUND

The Health of the Nation Outcome Scale (HoNOS) is a widely used 12-item tool to assess mental health and social functioning. The French version has an added 13th item measuring adherence to psychotropic medication. The aim of the current study is to uncover the unknown pattern of the new item 13 and to compare the unidimensional and multidimensional fit of the new HoNOS-13 using Item Response Theory (IRT). This research question was studied among inpatients with substance use disorder (SUD).

METHODS

Six hundred and nine valid questionnaires of HoNOS-13 were analyzed using unidimensional (one-factor) and multidimensional (two-factor) IRT modeling.

RESULTS

The multidimensional model suggesting a first factor capturing psychiatric/impairment-related issues and a second factor reflecting social-related issues yielded better goodness-of-fit values compared to the unidimensional solution. This resulted in an improvement of all slope parameters which in turn translates to better discriminative power. Significant improvement in item location parameters were observed as well. The new item 13 had a good discriminative power (1.17) and covered a wide range of the latent trait (- 0.14 to 2.64).

CONCLUSIONS

We were able to validate the 13-item questionnaire including medication compliance and suggest that the HoNOS-13 can be recommended as a clinical evaluation tool to assess the problems and treatment needs for inpatients with SUD. Interestingly, the majority of item response categories are endorsed by respondents who are below and above the average levels of HoNOS. This indicates that the scale is able to discriminate between participants both at the low and at the high ends of the latent trait continuum. More importantly, the new item 13 has a good discriminative power and covers a broad range of the latent trait below and above the mean. It therefore has the desired profile of a good item and is a useful measure for the assessment of mental health and social functioning. Trial registration ClinicalTrials.gov, Identifier: NCT03551301. Registered: 11.06.2018. Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT03551301 .

Evaluation of a Pathway team for homeless mental health in-patients

AIMS AND METHOD

The Pathway model is an enhanced care coordination model for homeless people in hospital. We aimed to evaluate the first attempt to apply it on psychiatric wards, which started in 2015 in South London. We developed a logic model which expressed how the Pathway approach might work. Two predictions from this model were tested, using propensity scores and regression to estimate the effect of the intervention among people who were eligible for it.

RESULTS

The Pathway team theorised that their interventions would reduce length of stay, improve housing outcomes and optimise the use of primary care - and, more tentatively, reduce readmission and emergency presentations. We were able to estimate effects on length of stay (-20.3 days; 95% CI -32.5 to -8.1; P = 0.0012) and readmission (a non-significant reduction).

CLINICAL IMPLICATIONS

The marked reduction in length of stay, explicable in terms of the logic model, constitutes preliminary support for the Pathway model in mental health services.

Are early post-discharge physician contacts associated with 30-day psychiatric re-hospitalisation? A nationwide claims data based retrospective cohort study in Austria free of immortal time bias

OBJECTIVES

Cost containment and quality of care considerations have increased research interest in the potential preventability of early re-hospitalisations. Various registry-based retrospective cohort studies on psychiatric re-hospitalisation have focused on the role of early post-discharge service contacts, but either did not consider their time-dependent nature ('immortal time bias') or evaded the issue by analysing late re-hospitalisations. The present study takes care of the immortal time bias in studying early psychiatric re-hospitalisations.

METHODS

In a retrospective cohort study using nationwide electronic claims data in Austria, 10,689 adults discharged from acute psychiatric inpatient wards were followed up for 30 days. Cox regression analyses were performed with post-discharge psychiatric and general practitioner contacts as time-dependent covariates and time to first psychiatric re-hospitalisation as outcome.

RESULTS

Post-discharge ambulatory physician contacts were significantly associated with a decreased psychiatric re-hospitalisation rate (hazard ratio 0.77 [95% CI 0.69; 0.87], p < 0.0001), with similarly strong contributions to this association by general practitioners and psychiatrists.

CONCLUSIONS

Despite avoiding the immortal time bias and controlling for several confounders, we suggest to be cautious with a causal interpretation of the identified association, since potentially relevant confounders, such as disease severity, were unavailable in our claims data base.

Risk of hospital admission after discharge from postpartum psychiatric emergency department visits: A focus on the social determinants of health

OBJECTIVE

Of those with postpartum psychiatric emergency department (ED) visits, a minority of receive hospital admission at their initial visit. Among those discharged, we aimed to determine subsequent risk of psychiatric admission, and understand how social determinants of health (SDOH) - individually and collectively - impact this risk.

METHOD

From all postpartum individuals discharged from psychiatric ED visits in Ontario, Canada (2008-2020)(n = 13,130), we generated adjusted relative risks (aRR) for psychiatric inpatient admission within 365 days post-ED visit by four SDOH (age, neighbourhood income, community size, immigration) and other clinical factors. Using latent class analysis (LCA) to identify subgroups based on clustering of SDOH, we then compared adjusted risk across subgroups.

RESULTS

Psychiatric admission occurred for 9.5% (n = 1242) within 365 days. Across SDOH, risk was lower among adolescents (vs. ≥35 years aRR 0.80, 95%CI 0.65-0.97) and immigrants (<5 years in Canada vs. Canadian-born/long-term residents 0.70, 0.51-0.96; ≥5 years in Canada 0.79, 0.65-0.95). Among four identified subgroups, compared to the "older/urban/high-income" subgroup (11.1% admission), the "urban/immigrant/low-income" (7.6%; 0.68, 0.55-0.82) and "young/rural/low-income" subgroups (9.7%; 0.78, 0.63-0.96), but not the "semi-urban/middle-income" subgroup (9.5%; 0.86, 0.73-1.01), were at lower admission risk.

CONCLUSIONS

Future research is needed to explore reasons for SDOH-based differences in admission risk, and inform equitable postpartum services.

Profiles, correlates, and risk of death among patients with mental disorders hospitalized for psychiatric reasons

This study identified profiles of hospitalized patients with mental disorders (MD) based on their 3-year hospitalization patterns and clinical characteristics and compared sociodemographic profiles and other service use correlates as well as risk of death within 12 months after hospitalization. Quebec (Canada) medical administrative databases were used to investigate a 5-year cohort of 4,400 patients hospitalized for psychiatric reasons. Latent class analysis, chi-square tests and survival analysis were produced. Three profiles of hospitalized patients were identified based on hospitalization patterns and other patient characteristics. Profile 3 patients had multiple hospitalizations and early readmissions, worst health and social conditions, and used the most outpatient services. Profiles 2 and 1 patients had only one hospitalization, of brief duration in the case of Profile 2 patients, who had mainly common MD and made least use of psychiatric care. All Profile 1 patients were hospitalized for serious MD but received least continuity of physician care and fewest biopsychosocial interventions. Risk of death was higher for Profiles 3 and 2 versus Profile 1 patients. Interventions like early follow-up care after hospitalization for Profile 3, collaborative care between general practitioners and psychiatrists for Profile 2, and continuous biopsychosocial care for Profile 1 could be greatly improved.

Predictors of Length of Hospitalization and Impact on Early Readmission for Mental Disorders

Length of hospitalization, if inappropriate to patient needs, may be associated with early readmission, reflecting sub-optimal hospital treatment, and translating difficulties to access outpatient care after discharge. This study identified predictors of brief-stay (1-6 days), mid-stay (7-30 days) or long-stay (≥31 days) hospitalization, and evaluated how lengths of hospital stay impacted on early readmission (within 30 days) among 3729 patients with mental disorders (MD) or substance-related disorders (SRD). This five-year cohort study used medical administrative databases and multinomial logistic regression. Compared to patients with brief-stay or mid-stay hospitalization, more long-stay patients were 65+ years old, had serious MD, and had a usual psychiatrist rather than a general practitioner (GP). Predictors of early readmission were brief-stay hospitalization, residence in more materially deprived areas, more diagnoses of MD/SRD or chronic physical illnesses, and having a usual psychiatrist with or without a GP. Patients with long-stay hospitalization (≥31 days) and early readmission had more complex conditions, especially more co-occurring chronic physical illnesses, and more serious MD, while they tended to have a usual psychiatrist with or without a GP. For patients with more complex conditions, programs such as assertive community treatment, intensive case management or home treatment would be advisable, particularly for those living in materially deprived areas.

Personality predictors of 6-month readmission in adult psychiatric inpatients

Readmission of psychiatric inpatients is highly prevalent and places a significant financial burden on the healthcare system. Rehospitalisation is often used as a metric of quality of care in psychiatric settings, but little is known about how specific personality traits impact readmission in adult psychiatric inpatients. A convenience sample of 94 adults (mean age = 36.8 years; female = 54.3%; European American = 76.6%) at an inpatient psychiatric hospital completed the Personality Inventory for DSM-5-Brief Form (PID-5-BF; American Psychiatric Association, 2013); demographic and medical information and readmission data were extracted via chart review. Poisson regression was used to predict number of readmissions at 6 months after discharge from PID-5-BF domain scores of Negative Affectivity, Detachment, Antagonism, Disinhibition and Psychoticism. Twenty-three patients (24.5%) were readmitted at least once by 6-month follow-up. Higher PID-5-BF Negative Affectivity domain scores predicted greater number of readmissions at 6 months (incidence rate ratio (IRR) = 1.14, robust standard error (RSE) = 0.05, p < .01, 95% confidence interval [1.04, 1.25]). The other PID-5-BF domain scores were not significantly related to number of readmissions. Thus, greater negative affect, indicative of higher trait neuroticism, heightened experience of negative emotions and poor self-concept, was a significant personality predictor of readmission in the study. These results suggest that assessing this trait domain might help to identify psychiatric inpatients at greater risk for readmission and determine those most in need of enhanced services to reduce rehospitalisation.

Exploring Discharge Outcomes and Readmission Rates of Mothers Admitted to a Psychiatric Mother and Baby Unit

To evaluate change in Health of the Nation Outcome Scale (HoNOS) scores from admission to discharge, readmission rates after 28-day and six months post-discharge, and factors associated with readmission in a Mother and Baby Unit (MBU). An exploratory cohort study was completed of mother-infant dyads admitted to a public psychiatric MBU in Australia between March 2017 and August 2018 (18 months). Admission and discharge scores on the clinician-rated Health of the Nation Outcome Scale (HoNOS) were compared using dependent samples t-tests. The frequency of readmission to any psychiatric inpatient unit within six months of discharge was determined from medical records. Characteristics of mothers who were and were not readmitted were evaluated. Of the 82 mother-infant dyads admissions, 12 (14.63%) women were readmitted within six months, and six (7.31%) were readmitted within 28-days. Total HoNOS scores significantly improved between admission and discharge (t₍₈₁₎=9.45, p<.000). Descriptive statistics for demographics, diagnoses, Mental Health Act status and discharge supports were computed for women readmitted and not readmitted. While these readmission rates and HONOS scores reflect a successful MBU admission, further research is required with larger sample sizes and more specific maternal and infant mental health outcome measures.

Predicting Hospital Readmissions from Health Insurance Claims Data: A Modeling Study Targeting Potentially Inappropriate Prescribing

BACKGROUND

 Numerous prediction models for readmissions are developed from hospital data whose predictor variables are based on specific data fields that are often not transferable to other settings. In contrast, routine data from statutory health insurances (in Germany) are highly standardized, ubiquitously available, and would thus allow for automatic identification of readmission risks.

OBJECTIVES

 To develop and internally validate prediction models for readmissions based on potentially inappropriate prescribing (PIP) in six diseases from routine data.

METHODS

 In a large database of German statutory health insurance claims, we detected disease-specific readmissions after index admissions for acute myocardial infarction (AMI), heart failure (HF), a composite of stroke, transient ischemic attack or atrial fibrillation (S/AF), chronic obstructive pulmonary disease (COPD), type-2 diabetes mellitus (DM), and osteoporosis (OS). PIP at the index admission was determined by the STOPP/START criteria (Screening Tool of Older Persons' Prescriptions/Screening Tool to Alert doctors to the Right Treatment) which were candidate variables in regularized prediction models for specific readmission within 90 days. The risks from disease-specific models were combined ("stacked") to predict all-cause readmission within 90 days. Validation performance was measured by the c-statistics.

RESULTS

 While the prevalence of START criteria was higher than for STOPP criteria, more single STOPP criteria were selected into models for specific readmissions. Performance in validation samples was the highest for DM (c-statistics: 0.68 [95% confidence interval (CI): 0.66-0.70]), followed by COPD (c-statistics: 0.65 [95% CI: 0.64-0.67]), S/AF (c-statistics: 0.65 [95% CI: 0.63-0.66]), HF (c-statistics: 0.61 [95% CI: 0.60-0.62]), AMI (c-statistics: 0.58 [95% CI: 0.56-0.60]), and OS (c-statistics: 0.51 [95% CI: 0.47-0.56]). Integrating risks from disease-specific models to a combined model for all-cause readmission yielded a c-statistics of 0.63 [95% CI: 0.63-0.64].

CONCLUSION

 PIP successfully predicted readmissions for most diseases, opening the possibility for interventions to improve these modifiable risk factors. Machine-learning methods appear promising for future modeling of PIP predictors in complex older patients with many underlying diseases.

Peer support for discharge from inpatient mental health care versus care as usual in England (ENRICH): a parallel, two-group, individually randomised controlled trial

BACKGROUND

High numbers of patients discharged from psychiatric hospital care are readmitted within a year. Peer support for discharge has been suggested as an approach to reducing readmission post-discharge. Implementation has been called for in policy, however, evidence of effectiveness from large rigorous trials is missing. We aimed to establish whether peer support for discharge reduces readmissions in the year post-discharge.

METHODS

We report a parallel, two-group, individually randomised, controlled superiority trial, with trial personnel masked to allocation. Patients were adult psychiatric inpatients (age ≥18 years) with at least one previous admission in the preceding 2 years, excluding those who had a diagnosis of any organic mental disorder, or a primary diagnosis of learning disability, an eating disorder, or drug or alcohol dependency, recruited from seven state-funded mental health services in England. Patients were randomly assigned (1:1) to the intervention (peer support plus care as usual) or control (care as usual) groups by an in-house, online randomisation service, stratified by site and diagnostic group (psychotic disorders, personality disorders, and other eligible non-psychotic disorders) with randomly permuted blocks of randomly varying length to conceal the allocation sequence and achieve the allocation ratio. The peer support group received manual-based, one-to-one peer support, focused on building individual strengths and engaging with activities in the community, beginning during the index admission and continuing for 4 months after discharge, plus care as usual. Care as usual consisted of follow-up by community mental health services within 7 days of discharge. The primary outcome was psychiatric readmission 12 months after discharge (number of patients readmitted at least once), analysed on an intention-to-treat basis. All patients were included in a safety analysis, excluding those who withdrew consent for use of their data. The trial is registered with the ISRCTN registry, ISRCTN10043328. The trial was complete at the time of reporting.

FINDINGS

Between Dec 1, 2016, and Feb 8, 2019, 590 patients were recruited and randomly assigned, with 294 allocated to peer support (287 included in the analysis after withdrawals and loss to follow-up), and 296 to care as usual (291 in the analysis). Mean age was 39·7 years (SD 13·7; range 18-75). 306 patients were women, 267 were men, three were transgender, and two preferred not to say. 353 patients were White, 94 were Black, African, Caribbean, or Black British, 68 were Asian or Asian British, 48 were of mixed or multiple ethnic groups, and 13 were of other ethnic groups. In the peer support group, 136 (47%) of 287 patients were readmitted at least once within 12 months of discharge. 146 (50%) of 291 were readmitted in the care as usual group. The adjusted risk ratio of readmission was 0·97 (95% CI 0·82-1·14; p=0·68), and the adjusted odds ratio for readmission was 0·93 (95% CI 0·66-1·30; p=0·68). The unadjusted risk difference was 0·03 (95% CI -0·11 to 0·05; p=0·51) in favour of the peer support group. Serious adverse events were infrequent (67 events) and similar between groups (34 in the peer support group, 33 in the care as usual group). Threat to life (self-harm) was the most common serious adverse event (35 [52%] of 67 serious adverse events). 391 other adverse events were reported, with self-harm (not life threatening) the most common (189 [48%] of 391).

INTERPRETATION

One-to-one peer support for discharge from inpatient psychiatric care, plus care as usual, was not superior to care as usual alone in the 12 months after discharge. This definitive, high-quality trial addresses uncertainty in the evidence base and suggests that peer support should not be implemented to reduce readmission post-discharge for patients at risk of readmission. Further research needs to be done to improve engagement with peer support in high-need groups, and to explore differential effects of peer support for people from different ethnic communities.

FUNDING

UK National Institute for Health Research.

Inpatient Early Intervention for Serious Mental Illnesses Is Associated With Fewer Rehospitalizations Compared With Treatment as Usual in a High-volume Public Psychiatric Hospital Setting

OBJECTIVE

High-acuity publicly funded inpatient psychiatric settings usually feature short lengths of stay and high readmission rates. This study examined the influence of an early intervention program for serious mental illnesses (SMI) on readmissions at 6 and 12 months postdischarge at a high-volume, urban public inpatient psychiatric hospital.

METHODS

The Early Onset Treatment Program (EOTP) is a cost-free, 90-day inpatient multidisciplinary service intervention program for uninsured patients who are within 5 years of SMI onset, funded as a pilot program by the Texas state legislature. Rehospitalization rates at 6 and 12 months were extracted from electronic medical records for EOTP participants (n=165) and comparison patients matched on demographics and diagnosis (n=155). The comparison group received treatment as usual at the same psychiatric hospital. Group re-admission rates were compared using logistic and Poisson regression analyses.

RESULTS

Group membership was a significant predictor of rehospitalization (P<0.0001) at both 6 and 12 months. Expressed as 1/odds ratio (OR), the EOTP group was less likely to readmit once and more than once at 6 months postdischarge (1/OR=3.82 and 4.74, respectively) compared with the non-EOTP group. The EOTP group was also less likely to readmit once and more than once at 12 months postdischarge (1/OR=2.96 and 3.51, respectively).

CONCLUSIONS

The results suggest that participation in the EOTP service in this high-acuity setting was significantly related to reduced likelihood of rehospitalization at 6 and 12 months. Several variables may account for this observation, including length of stay, longer medication adherence, environmental stability, and more individualized and extensive psychotherapy treatment.

Predictive modelling of hospital readmission: Evaluation of different preprocessing techniques on machine learning classifiers

Hospital readmission is a major cost for healthcare systems worldwide. If patients with a higher potential of readmission could be identified at the start, existing resources could be used more efficiently, and appropriate plans could be implemented to reduce the risk of readmission. Therefore, it is important to predict the right target patients. Medical data is usually noisy, incomplete, and inconsistent. Hence, before developing a prediction model, it is crucial to efficiently set up the predictive model so that improved predictive performance is achieved. The current study aims to analyse the impact of different preprocessing methods on the performance of different machine learning classifiers. The preprocessing applied by previous hospital readmission studies were compared, and the most common approaches highlighted such as missing value imputation, feature selection, data balancing, and feature scaling. The hyperparameters were selected using Bayesian optimisation. The different preprocessing pipelines were assessed using various performance metrics and computational costs. The results indicated that the preprocessing approaches helped improve the model’s prediction of hospital readmission.

Readmission after discharge from acute mental healthcare among 231 988 people in England: cohort study exploring predictors of readmission including availability of acute day units in local areas

BACKGROUND

In the UK, acute mental healthcare is provided by in-patient wards and crisis resolution teams. Readmission to acute care following discharge is common. Acute day units (ADUs) are also provided in some areas.

AIMS

To assess predictors of readmission to acute mental healthcare following discharge in England, including availability of ADUs.

METHOD

We enrolled a national cohort of adults discharged from acute mental healthcare in the English National Health Service (NHS) between 2013 and 2015, determined the risk of readmission to either in-patient or crisis teams, and used multivariable, multilevel logistic models to evaluate predictors of readmission.

RESULTS

Of a total of 231 998 eligible individuals discharged from acute mental healthcare, 49 547 (21.4%) were readmitted within 6 months, with a median time to readmission of 34 days (interquartile range 10-88 days). Most variation in readmission (98%) was attributable to individual patient-level rather than provider (trust)-level effects (2.0%). Risk of readmission was not associated with local availability of ADUs (adjusted odds ratio 0.96, 95% CI 0.80-1.15). Statistically significant elevated risks were identified for participants who were female, older, single, from Black or mixed ethnic groups, or from more deprived areas. Clinical predictors included shorter index admission, psychosis and being an in-patient at baseline.

CONCLUSIONS

Relapse and readmission to acute mental healthcare are common following discharge and occur early. Readmission was not influenced significantly by trust-level variables including availability of ADUs. More support for relapse prevention and symptom management may be required following discharge from acute mental healthcare.

Psychiatric readmission rates in a multi-level mental health care system - a descriptive population cohort study

BACKGROUND

Readmission rates are frequently used as a quality indicator for health care, yet their validity for evaluating quality is unclear. Published research on variables affecting readmission to psychiatric hospitals have been inconsistent. The Norwegian specialist mental health care system is characterized by a multi-level structure; hospitals providing specialized -largely unplanned care and district psychiatric centers (DPCs) providing generalized -more often planned care. In certain service systems, readmission may be an integral part of individual patients' treatment plan. The aim of the present study was to describe and examine the task division in a multi-level health care system. This we did through describing differences in patient population (age, sex, diagnosis, substance abuse comorbidity and length of stay) and admissions types (unplanned vs. planned) treated at different levels (hospital, DPC or both), and by examining whether readmission risk differ according to type and place of treatment of index-admission and travel-time to nearest hospital and DPC.

METHODS

In this population-based cohort study using administrative data we included all individuals aged 18 and older who were discharged from psychiatric inpatient care with an ICD-10 diagnosis F2-F6 ("functional mental disorders") in 2012. Selecting each individual's first discharge during 2012 as index gave N = 16,185 for analyses following exclusions. Analysis of readmission risk were done using Kaplan-Maier failure curves.

RESULTS

Overall, 15.1 and 47.7% of patients were readmitted within 30 and 365 days, respectively. Unplanned admission patients were more likely to be readmitted within 30 days than planned patients. Those transferred between hospital and DPC during index admission were more likely to be readmitted within 365 days, and to experience planned readmission. Patients with short travel time were more likely to have unplanned readmission, while patients with long travel time were more likely to have planned readmission.

CONCLUSIONS

DPCs and hospitals fill different purposes in the Norwegian health care system, which is reflected in different patient populations. Differences in short term readmission rates between hospitals and DPCs disappeared when type of admission (unplanned/planned) was considered. The results stress the importance of addressing differences in organisation and task distribution when comparing readmission rates between mental health systems.

A Social Media Study on Mental Health Status Transitions Surrounding Psychiatric Hospitalizations

For people diagnosed with a mental illness, psychiatric hospitalization is one step in a long journey, consisting of clinical recovery such as removal of symptoms, and social reintegration involving resuming social roles and responsibilities, overcoming stigma and self-maintenance of the condition. Both clinical recovery and social reintegration need to go hand-in-hand for the overall well-being of individuals. However, research exploring social media for mental health has considered narrower, disjoint conceptualizations of people with mental illness - either as a patient or as a support-seeker. In this paper, we combine medical records with social media data of 254 consented individuals who have experienced a psychiatric hospitalization to address this gap. Adopting a theory-driven, Gaussian Mixture modeling approach, we provide a taxonomy of six heterogeneous behavioral patterns characterizing peoples' mental health status transitions around hospitalizations. Then we present an empirically derived framework, based on feedback from clinical researchers, to understand peoples' trajectories around clinical recovery and social reintegration. Finally, to demonstrate the utility of this taxonomy and the empirical framework, we assess social media signals that are indicative of individuals' reintegration trajectories post-hospitalization. We discuss the implications of combining peoples' clinical and social experiences in mental health care and the opportunities this intersection presents to post-discharge support and technology-based interventions for mental health.

Sociodemographic and clinical characteristics of patients with recurrent psychiatric readmissions in Qatar

OBJECTIVE

To examine the sociodemographic and clinical characteristics of psychiatric patients with recurrent psychiatric readmissions (RPR).

METHODS

A retrospective study was conducted at Hamad General Hospital in Qatar on psychiatric patients with recurrent readmissions from August 2018 to January 2019.

RESULTS

Of 380 psychiatric patients admitted during the study period, 40 (10.5%) were readmitted within 30 days of discharge. Most of the patients who were readmitted were single, male and unemployed. Psychotic spectrum disorder was the most frequent psychiatric condition and was diagnosed in 18 (45%) patients. A total of 30% of the patients were receiving treatment with anti-psychotics, and a similar number received more than one medication. Most patients showed poor or no compliance. Only 12.5% of patients stayed in the hospital for more than 5 weeks in their last admission during the study period.

CONCLUSIONS

Poor compliance, male sex and single status were the most common demographic and clinical features of patients with RPR. Post-discharge psychiatric care should be tailored to meet the requirements of patients prone to RPR.

The reMAP project: A retrospective, 15-year register study on inpatient care for youth with mental disorders

AIM

We aimed to characterize youth hospitalization trends in a psychiatric inpatient unit from a large, public university hospital with a broad catchment area in Milan, Italy.

METHODS

Hospitalization data of patients with an age at admission ≤ 35 were retrospectively retrieved over a time span of 15 years. The sample was comprised of 1982 admissions to a psychiatric ward, aggregated into ICD-10 diagnostic clusters and then analysed. We investigated the epidemiological trends with a focus on age at admission, gender, nationality and hospitalization rates, length of stay and "revolving door" readmissions within a year.

RESULTS

Hospitalization rates increased for eating Disorders and decreased for non-affective psychotic disorders; median length of stay generally decreased; hospitalization rates for foreign youth increased, in particular for those diagnosed with non-affective psychotic disorders, personality disorders, and substance-related and addictive disorders. The revolving door phenomenon was also associated with non-affective psychoses and neurodevelopmental disorders, while found to increase for eating disorders.

CONCLUSIONS

Hospitalization patterns reflect the general increase of foreign youth in the suburban tissue of a large metropolitan area like Milan. However, our data might underestimate the constant growth of mental health problems in foreign youth due to a generally lower access to services. Novel pharmacological treatments and early intervention programs might explain the decrease of hospitalization duration and hospitalization rate for youth with non-affective psychoses. The observed increase in hospitalization for young patients with eating disorders sustains the development of adequate policies tailored towards specialty wards.

Predictors of civil and forensic inpatient psychiatric readmissions at a Public Mental Health Hospital

Inpatient psychiatric readmissions are increasingly prevalent and associated with worse prognostic outcomes and high economic costs, regardless of the medicolegal ramifications that necessitate them. Unlike most general medical readmissions, psychiatric readmissions are commonly warranted for both medical and legal purposes. However, studies focusing on analyzing the predictors of inpatient psychiatric readmission and their relationship to civil versus forensic readmission are limited. The purpose of this study was to examine the predictors of psychiatric readmission among civil and forensic patients admitted to a psychiatric hospital. In this retrospective chart review, we extrapolated data from medical records of 741 patients admitted from 2012 to 2017 with follow up until 2019. Analyses involved chi-square tests for comparing the distribution of demographic and clinical variables between forensic and civil readmission, and Cox regression to determine predictors of time to first readmission. Our results show that race, diagnosis, restraint/seclusion, type of admission, and disposition are significantly associated with an increased risk of psychiatric readmission. This study has important implications for healthcare providers and policy makers in revising mental health policies and improving systems-based practices for the mental health system. Future efforts in improving community psychiatric services and enhancing inpatient therapeutic environment may reduce psychiatric readmissions.

Psychotropic medication use among personality disordered young adults. A follow-up study among former adolescent psychiatric inpatients

OBJECTIVE

To analyze the use of prescribed psychotropic medication in subjects with personality disorder (PD) diagnosed in early adulthood.

METHODS

The study population consisted of former adolescent psychiatric inpatients (N=508). 63 had a diagnosis of PD, including with borderline PD (BPD) (N=38) and other PD (OPD) (N=25). DSM IV-based psychiatric diagnoses in adolescence were based on the Schedule for Affective Disorder and Schizophrenia for School-Age Children Present and Lifetime (K-SADS-PL). The information on in-or outpatient hospital treatments until the end of 2016 were extracted from the National Care Register for Health Care. Lifetime data on purchases of physician-prescribed psychotropic medications was obtained from the Social Insurance Institution of Finland.

RESULTS

98.4% (N=62) of subjects with PD had purchased at least one type of psychotropic medication during the follow-up period. The use of non-opioid analgesics and antipyretics was over twice as common among subjects with BPD than subjects with OPD (57.9% vs.28.0%, p=0.020). Anxiolytic use was 1.5 times more common among subjects with BPD than subjects with OPD (65.8% vs. 40.0%, p=0.044) CONCLUSIONS: Psychotropic medication use was common among subjects with PD. The use of non-opioid analgesics, antipyretics and anxiolytics was more common among subjects with BPD.

Factors associated with 30-days and 180-days psychiatric readmissions: A snapshot of a metropolitan area

Psychiatric re-hospitalization rate is a widely used quality indicator within mental health care. This study aims to investigate which variables are implied in determining readmissions over two intervals after the index event, 30 days and 6 months. The study sample included 798 inpatients, it was divided into two groups: not readmitted patients (NRP) and readmitted patients (RP), which has been further split into: Readmitted within 30 days (RP30dd) and Readmitted during the 150-day period (between 31 and 180 days) after the index discharge (RP150). A multivariate logistic regression with backward selection method was performed in order to find variables independently associated with readmission. The overall incidence of readmissions was 16.04%. Discharge to a Psychiatric Nursing Home was found to be a protective factor for all the groups. In adds, for the overall readmission, compulsory index admission and higher education (this lasts as in RP30dd group) were protective factors; whereas higher length of stay (as for readmission within 31-180 days) and a diagnosis of Personality Disorder were risk factors. The patient-specific factors significantly associated with likelihood of rehospitalization in the final model do identify some high-risk groups toward to whom possibly address prevention strategies.

'If we would change things outside we wouldn't even need to go in…' supporting recovery via community-based actions: A focus group study on psychiatric rehospitalization

BACKGROUND

Psychiatric rehospitalization is a complex phenomenon in need of more person-centred approaches. The current paper aimed to explore how community-based actions and daily life influence mental health and rehospitalization.

DESIGN, SETTING AND PARTICIPANTS

The qualitative study included focus group data from six European countries including 59 participants. Data were thematically analysed following an inductive approach deriving themes and subthemes in relation to facilitators and barriers to mental health.

RESULTS

Barriers consisted of subthemes (financial difficulty, challenging family circumstances and stigma), and facilitators consisted of three subthemes (complementing services, signposting and recovery). The recovery subtheme consisted of a further five categories (family and friends, work and recreation, hope, using mental health experience and meaning).

DISCUSSION

Barriers to mental health largely related to social determinants of mental health, which may also have implications for psychiatric rehospitalization. Facilitators included community-based actions and aspects of daily life with ties to personal recovery. By articulating the value of these facilitators, we highlight benefits of a person-centred and recovery-focused approach also within the context of psychiatric rehospitalization.

CONCLUSIONS

This paper portrays how person-centred approaches and day-to-day community actions may impact psychiatric rehospitalization via barriers and facilitators, acknowledging the social determinants of mental health and personal recovery.

PATIENT OR PUBLIC CONTRIBUTION

The current study included participants with experience of psychiatric rehospitalization from six different European countries. Furthermore, transcripts were read by several of the focus group participants, and a service user representative participated in the entire research process in the original study.

Predicting Patients' Readmission: Do Clinicians Outperform a Statistical Model? An Exploratory Study on Clinical Risk Judgment in Mental Health

This study explores whether clinicians or a statistical model can better identify patients at risk of early readmission and investigates variables potentially associated with clinicians' risk judgment. We focus on a total of 142 patients discharged from acute psychiatric wards in the Verona Mental Health Department (Italy). Psychiatrists assessed patients' risk of readmission at 30 and 90 days postdischarge, predicted their postdischarge compliance, and assessed their Global Assessment of Functioning (GAF) score at admission and discharge. Clinicians' judgment outperformed the statistical model, with the difference reaching statistical significance for 30-day readmission. Clinicians' readmission risk judgment, both for 30 and 90 days, was found to be statistically associated with predicted compliance with community treatment and GAF score at discharge. Clinicians' superior performance might be explained by their risk judgment depending on nonmeasurable factors, such as experience and intuition. Patients with a poorer GAF score at discharge and poor assumed compliance were predicted to have a higher risk of readmission.

Mindfulness-based crisis interventions (MBCI) for psychosis within acute inpatient psychiatric settings; a feasibility randomised controlled trial

BACKGROUND

Inpatient psychiatric care is a scarce and expensive resource in the National Health Service (NHS), with chronic bed shortages being partly driven by high re-admission rates. Brief inpatient talking therapies for psychosis could help reduce re-admission rates. The primary aim was to assess feasibility and acceptability of a novel, brief, mindfulness-based intervention for inpatients with psychosis. The secondary aim was to collect pilot outcome data on readmission rate, at 6 and 12 months (m) post discharge, and self-report symptom measures at 6 m.

METHODS

The amBITION study (BrIef Talking therapIes ON wards) was a parallel group, feasibility randomised controlled trial (RCT). In addition to treatment as usual (TAU), eligible inpatients with psychotic symptoms were randomly allocated to receive either (Mindfulness-Based Crisis Intervention; MBCI) or a control intervention (Social Activity Therapy; SAT), for 1-5 sessions.

RESULTS

Fifty participants were recruited (26 MBCI; 24 SAT); all received at least 1 therapy session (mean = 3). Follow-up rates were 98% at 6 m and 96% at 12 m for service use data extracted from clinical notes, and 86% for self-report measures. At 6 m follow-up, re-admission rates were similar across groups (MBCI = 6, SAT = 5; odds ratio = 1.20, 95% CI: 0.312-4.61). At 12 m follow-up, re-admissions were lower in the MBCI group (MBCI = 7, SAT = 11; odds ratio = 0.46, 95% CI: 0.14-1.51). Three participants experienced adverse events; none was related to trial participation.

CONCLUSIONS

Delivering a brief mindfulness-based inpatient intervention for psychosis is feasible and acceptable, and may reduce risk of short-term readmission. These promising findings warrant progression to a larger clinical effectiveness trial.

TRIAL REGISTRATION

ISRCTN37625384.

Peer support for discharge from inpatient to community mental health services: Study protocol clinical trial (SPIRIT Compliant)

INTRODUCTION

In the period shortly after discharge from inpatient to community mental health care, people are at increased risk of self-harm, suicide, and readmission to hospital. Discharge interventions including peer support have shown potential, and there is some evidence that community-based peer support reduces readmissions. However, systematic reviews of peer support in mental health services indicate poor trial quality and a lack of reporting of how peer support is distinctive from other mental health support. This study is designed to establish the clinical and cost effectiveness of a peer worker intervention to support discharge from inpatient to community mental health care, and to address issues of trial quality and clarity of reporting of peer support interventions.

METHODS

This protocol describes an individually randomized controlled superiority trial, hypothesizing that people offered a peer worker discharge intervention in addition to usual follow-up care in the community are less likely to be readmitted in the 12 months post discharge than people receiving usual care alone. A total of 590 people will be recruited shortly before discharge from hospital and randomly allocated to care as usual plus the peer worker intervention or care as usual alone. Manualized peer support provided by trained peer workers begins in hospital and continues for 4 months in the community post discharge. Secondary psychosocial outcomes are assessed at 4 months post discharge, and service use and cost outcomes at 12 months post discharge, alongside a mixed methods process evaluation.

DISCUSSION

Clearly specified procedures for sequencing participant allocation and for blinding assessors to allocation, plus full reporting of outcomes, should reduce risk of bias in trial findings and contribute to improved quality in the peer support evidence base. The involvement of members of the study team with direct experience of peer support, mental distress, and using mental health services, in coproducing the intervention and designing the trial, ensures that we theorize and clearly describe the peer worker intervention, and evaluate how peer support is related to any change in outcome. This is an important methodological contribution to the evidence base.

TRIAL REGISTRATION

This study was prospectively registered as ISRCTN 10043328 on November 28, 2016.

Clinical risk model to predict 28-day unplanned readmission via the accident and emergency department after discharge from acute psychiatric units for patients with psychotic spectrum disorders

BACKGROUND

Unplanned readmissions rates are an important indicator of the quality of care provided in a psychiatric unit. However, there is no validated risk model to predict this outcome in patients with psychotic spectrum disorders.

AIMS

This paper aims to establish a clinical risk prediction model to predict 28-day unplanned readmission via the accident and emergency department after discharge from acute psychiatric units for patients with psychotic spectrum disorders.

METHOD

Adult patients with psychotic spectrum disorders discharged within a 5-year period from all psychiatric units in Hong Kong were included in this study. Information on the socioeconomic background, past medical and psychiatric history, current discharge episode and Health of the Nation Outcome Scales (HoNOS) scores were used in a logistic regression to derive the risk model and the predictive variables. The sample was randomly split into two to derive (n = 10 219) and validate (n = 10 643) the model.

RESULTS

The rate of unplanned readmission was 7.09%. The risk factors for unplanned readmission include higher number of previous admissions, comorbid substance misuse, history of violence and a score of one or more in the discharge HoNOS overactivity or aggression item. Protective factors include older age, prescribing clozapine, living with family and relatives after discharge and imposition of conditional discharge. The model had moderate discriminative power with a c-statistic of 0.705 and 0.684 on the derivation and validation data-set.

CONCLUSIONS

The risk of readmission for each patient can be identified and adjustments in the treatment for those with a high risk may be implemented to prevent this undesirable outcome.

Internet-based aftercare for patients with personality disorders and trauma-related disorders: A pilot study

Preventing readmission after hospital discharge is a major issue with regard to the continuity of patients' recovery process and the financial burden on the healthcare system, but adequate aftercare services are lacking. Therefore, a pilot study was conducted to examine the feasibility and acceptability of an Internet-based aftercare program for patients with personality disorders (PD) and / or trauma-related disorders as well as to obtain a preliminary estimate of effects on symptomatology and readmission. Patients' satisfaction with the program and symptomatology (KPD-38, BDI-II) were assessed prior to hospital discharge (t1) and after three months of participation (t2). Log data on program utilization (i.e., logins, page hits, and chat use) were automatically assessed via server logs. N = 31 of 45 eligible patients consented to participate. 84% used the intervention at least once. The average duration of participation was 63 days (SD = 4.6). Patients attended on average 7.2 out of 12 group chat sessions (SD = 4.0). Findings indicate very high acceptance of and satisfaction with the intervention. Symptomatology on all outcomes was stable, no deteriorations could be observed. 20% reported readmission within the aftercare period. Efficacy and cost-effectiveness should be tested with a large-scale randomized controlled trial.

Association between DSM-5 and ICD-11 personality dimensional traits in a general medical cohort and readmission and mortality

BACKGROUND

Personality has long been studied as a factor associated with health outcomes. Investigations of large, generalizable clinical cohorts are limited by variations in personality diagnostic methodologies and difficulties with long-term follow-up.

METHODS

Electronic health records of a cohort of patients admitted to a general hospital were characterized using a previously developed natural language processing tool for extracting DSM-5 and ICD-11 personality domains. We used Cox regression and Fine-Gray competing risk survival to analyze the relationships between these personality estimates, sociodemographic features, and risk of readmission and mortality.

RESULTS

Among 12,274 patients, 2379 deaths occurred in the course of 61,761 patient-years at risk, with 19,985 admissions during follow-up. Detachment was the most common personality feature. Presence of disinhibition was independently associated with a higher mortality risk, while anankastic traits were associated with a lower mortality risk. Increased likelihood of readmission was predicted by detachment, while decreased likelihood of readmission was associated with disinhibition and psychoticism traits.

CONCLUSIONS

Personality features can be identified from electronic health records and are associated with readmission and mortality risk. Developing treatment strategies that target patients with higher personality symptom burden in specific dimensions could enable more efficient and focused interventions.

Hospital length of stay among older people treated with flexible and integrative psychiatric service models in Germany

OBJECTIVE

Since 2012, a new law (§64b, Book V of the Social Security Code [SGB V]) regulates the implementation of flexible and integrative psychiatric treatment projects (FIT64b) in Germany. FIT64b allows rapid discharge of patients from inpatient to outpatient settings and cost reductions of hospital stays. Several psychiatric centres exclusively provide FIT64b; others provide FIT64b alongside with standard health care. The aim of the study was to assess the average hospital length of stay (AHLS) of older patients with mental illness included in FIT64b projects.

METHODS

A secondary data analysis was conducted using administrative data from eight German mental health centres providing FIT64b. The effects of gender, age, type of centre, and main diagnosis on AHLS were calculated for all older patients with age 65 years or older (n = 3495) treated in FIT64b in the year 2016. Data were analysed with descriptive statistics and robust multiway procedures.

RESULTS

The AHLS of older people with mental illness was 4.8 (SD = 11.5) days. The AHLS was shorter in centres exclusively providing FIT64b than in centres providing FIT64b alongside with standard health care: 3.2 (SD = 6.4) vs 8.4 (SD = 17.8) days, P = .001. This difference was particularly marked among patients with schizophrenia spectrum disorders, mood disorders, and neurotic, stress-related, and somatoform disorders.

CONCLUSIONS

FIT64b relates to very short AHLS even among older people. Centres using FIT64b alongside with standard health care usually provide standard care to most patients, which could lead to lower fidelity in the implementation of FIT64b.

Risk factors for early unplanned readmission in patients with bipolar disorder: A retrospective observational study

OBJECTIVES

Evidence regarding the relationships between patient, hospital, and regional factors and early unplanned readmission (short-term outcome) in patients with bipolar disorder is lacking. This study aimed to examine risk factors associated with early unplanned readmission in patients with bipolar disorder.

METHOD

We retrospectively analyzed adult bipolar patients (ICD-10; F31) between April 2012 and March 2014 in the Japanese Diagnosis Procedure Combination database. We examined factors affecting the 30-day unplanned readmission using multivariable logistic regression analysis.

RESULTS

A total of 2688 patients admitted to psychiatric beds were included. Multivariate analysis showed that unchanged or exacerbation discharge outcome (adjusted odds ratio [aOR]: 1.93; 95% confidence interval [CI]: 1.06-3.51, p = 0.031), unplanned or urgent admission settings (aOR: 1.51; 95% CI: 1.00-2.26, p = 0.048), physical comorbidity (chronic pulmonary disease) (aOR: 4.74; 95% CI: 1.30-17.29, p = 0.018), presence of psychiatric acute-care beds (aOR: 1.72; 95% CI: 1.02-2.87, p = 0.040), and intermediate-level hospital psychiatric staffing (aOR: 1.82; 95% CI: 1.14-2.91, p = 0.012) were significantly associated with higher early unplanned readmission, while higher density of psychiatrists in the area (aOR: 0.50; 95% CI: 0.29-0.87, p = 0.014) was significantly associated with lower early unplanned readmission.

CONCLUSIONS

The results suggest that not only careful management of high-risk patients but also consideration of functional differentiation in psychiatric inpatient care, psychiatric resource allocation, and follow-up support for patients with bipolar disorder are needed for reducing the early unplanned readmission rate.

Patient-Level Predictors of Psychiatric Readmission in Substance Use Disorders

Repeated psychiatric readmissions are a particular challenge in the treatment of substance use disorders and are associated with substantial burden for patients and their associates and for healthcare providers. Factors affecting readmission rates are heterogeneous and need to be identified to better allocate resources. Within the Swiss healthcare system, such data on substance use disorder patients are largely missing. Understanding these factors might bear important implications for future healthcare planning. Thus here, we examine risk factors of inpatient readmission. We retrospectively analyzed all admissions to the hospital's department of addictive disorders in the year 2016. Patients included in the study were followed over a period of 1 year after discharge regarding readmissions to the clinic. Besides the demographic, social, and economic data, we extracted data concerning patient history, admission, and discharge as well as clinical data regarding type and number of substances abused and comorbid diagnoses. In order to describe severity of cases, we furthermore included the scores of the Health of the Nation Outcome Scale (HoNOS) at admission and at discharge as documented in the medical database. Of the 554 patients included in the study, 228 (41.2%) were readmitted within 12 months. Previous admissions, concomitant use of different substances, presence of psychosis or mania, and a higher severity score at discharge increased the likelihood of readmission. The odds for readmission were furthermore higher in patients not being married, living alone, and being unemployed. When all (bivariate) statistically significant factors are included into a logistic regression model, the previous number of admissions and the HoNOS clinical score at discharge significantly contributed to this model. Our findings stress that patients with higher symptom load at discharge are prone to be readmitted within 12 months. The same applies for patients with previous admissions. These findings suggest that the development of specific interventions to prevent premature discharge before satisfactory symptom remission, in particular in those patients with previous admissions in their patient history, might help to prevent readmissions.

Implementation of the Brøset Violence Checklist on an Acute Psychiatric Unit

BACKGROUND: Violence on inpatient psychiatric settings has significant consequences for patients and staff. Research is needed to determine if Brøset Violence Checklist (BVC) is an accurate predictor of violence. AIMS: The study aims were to determine the relationship between BVC scores and incidence of violent behavior within 24 hours, to compare scores among those requiring high-level nursing interventions for violence, and to investigate the impact of scores on length of stay (LOS) and 30 day-readmission rates. METHOD: Retrospective cohort study. RESULTS: Logistic regression indicates 3.4 times greater risk of violence for every additional point on admission BVC (odds ratio = 3.4, 95% confidence interval = [2.29, 5.08], p < .0001). Patients requiring high-level interventions for violence had higher mean BVC scores on both Day 1 and 2 of admission. Pearson correlation was significant for positive association between BVC on admission and LOS (p < .001). Findings did not establish a link between BVC scores and violence with 30-day readmission rates. CONCLUSIONS: Efforts toward early identification and management of agitation and disruptive behavior is encouraged. Results showed increased risk of violence with every additional point on BVC on admission; further attention should be paid to these patients on admission when using violence screening tools.

Cost-effectiveness of care for people with psychosis in the community and psychiatric hospitals in the Czech Republic: an economic analysis

BACKGROUND

The absence of economic evidence hinders current reforms of hospital-based mental health systems in central and eastern Europe. We aimed to assess the cost-effectiveness of discharge to community care for people with chronic psychoses compared with care in psychiatric hospitals in the Czech Republic.

METHODS

We did a prospective study of people aged 18-64 years with chronic psychotic disorders in the Czech Republic who had been discharged into community services or were receiving inpatient psychiatric care for at least 3 months at baseline. We measured health-related quality of life with the EuroQol five-dimension five-level questionnaire. Adjusting for baseline differences between the two groups, we assessed differences in societal costs in 2016 and quality-adjusted life-years (QALYs) during a 12-month follow-up, which we then used to estimate the incremental cost-effectiveness ratio (ICER). We did multiple sensitivity analyses to assess the robustness of our results.

FINDINGS

In our baseline case scenario, we included 115 patients who were either community service users (n=35) or inpatients (n=80) at baseline. The two groups were similar in terms of baseline characteristics. The annual QALY was 0·77 in patients receiving community care at baseline compared with 0·80 in patients in hospital at baseline (difference 0·03, 95% CI -0·04 to 0·10), but the costs of discharge to the community were €8503 compared with €16 425 for no discharge (difference €7922, 95% CI 4497-11 346), such that the ICER reached more than €250 000 per QALY. This ICER is substantially higher than levels that are conventionally considered to be cost-effective and the estimated probability that discharge to the community was cost-effective was very high (≥97%). None of the sensitivity analyses changed these results qualitatively.

INTERPRETATION

This study provides economic evidence for deinstitutionalisation by showing that discharge to community care is cost-effective compared with care in psychiatric hospitals in the Czech Republic. These findings add to the human rights and clinical-based arguments for mental health-care reforms in central and eastern Europe.

FUNDING

Ministry of Education, Youth and Sports of the Czech Republic; EEA and Norway Grants.

Predictive models for hospital readmission risk: A systematic review of methods

OBJECTIVES

Hospital readmission risk prediction facilitates the identification of patients potentially at high risk so that resources can be used more efficiently in terms of cost-benefit. In this context, several models for readmission risk prediction have been proposed in recent years. The goal of this review is to give an overview of prediction models for hospital readmission, describe the data analysis methods and algorithms used for building the models, and synthesize their results.

METHODS

Studies that reported the predictive performance of a model for hospital readmission risk were included. We defined the scope of the review and accordingly built a search query to select the candidate papers. This query string was used as input for the chosen search engines, namely PubMed and Google Scholar. For each study, we recorded the population, feature selection method, classification algorithm, sample size, readmission threshold, readmission rate and predictive performance of the model.

RESULTS

We identified 77 studies that met the inclusion criteria, out of 265 citations. In 68% of the studies (n = 52) logistic regression or other regression techniques were utilized as the main method. Ten (13%) studies used survival analysis for model construction, while 14 (18%) used machine learning techniques for classification, of which decision tree-based methods and SVM were the most utilized algorithms. Among these, only four studies reported the use of any class imbalance addressing technique, of which resampling is the most frequent (75%). The performance of the models varied significantly among studies, with Area Under the ROC Curve (AUC) values in the ranges between 0.54 and 0.92.

CONCLUSION

Logistic regression and survival analysis have been traditionally the most widely used techniques for model building. Nevertheless, machine learning techniques are becoming increasingly popular in recent years. Recent comparative studies suggest that machine learning techniques can improve prediction ability over traditional statistical approaches. Regardless, the lack of an appropriate benchmark dataset of hospital readmissions makes a comparison of models' performance across different studies difficult.

Mental health service users' experiences of psychiatric re-hospitalisation - an explorative focus group study in six European countries

Background

Psychiatric re-hospitalisation is considered costly and disruptive to individuals. The perspective of the mental health service user is largely unexplored in literature.

The purpose of our study was to explore service users’ experiences of psychiatric re-hospitalisation across six countries in Europe.

Method

Eight focus groups were conducted in Romania, Slovenia, Finland, Italy, Austria and Norway.

Results

A total of 55 service users participated in the study. All participants had been in receipt of mental health services for at least 1 year, and had experienced more than one psychiatric hospitalisation. The experience of re-hospitalisation was considered: (1) less traumatising than the first hospitalisation, (2) to be necessary, and a relief, (3) occurring by default and without progress, (4) part of the recovery process.

Conclusions

Psychiatric re-hospitalisation was considered inevitable by the study participants, in both positive and negative terms. Striking similarities in service user experiences were found across all of the six countries, the first experience of psychiatric hospitalisation emerging as especially significant. Findings indicate the need for further action in order to develop more recovery and person-centred approaches within hospital care. For psychiatric inpatient care to be a positive part of the recovery process, further knowledge on what therapeutic action during the hospital stay would be beneficial, such as therapy, activities and integration with other services.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3317-1) contains supplementary material, which is available to authorized users.

The development of an occupational therapy intervention for adults with a diagnosed psychotic disorder following discharge from hospital

Background

A deterioration in mental health and admission to an acute mental health unit can result in skill loss and decreased participation in daily life. Furthermore, discharge from hospital is associated with high risks of social isolation and suicide. This intervention development study aims to describe the rationale, methods and processes of developing an intervention for adults with a diagnosed psychotic disorder following discharge from hospital. The intervention aims to increase participation in self-care and leisure, wellbeing and quality of life and reduce crisis service use.

Methods

The UK Medical Research Council framework for the development of complex interventions was used to guide the process of developing the intervention to ensure the developed intervention is empirically justifiable and evidence based. The development involved a systematic and literature reviews and focus groups with people with psychosis and clinical staff to understand the problems the intervention should address and approaches to resolving these.

Results

A manualised 4-month intervention named Graduating Living skills Outside the Ward (GLOW) was developed for use by occupational therapists for people with a diagnosed psychotic disorder following discharge from hospital. The one-to-one stepped intensity intervention is of 4 months in duration and takes place in the person's home and in community locations. The intervention aims to increase occupational performance of domestic and personal self-care, leisure and some productive roles.

Conclusions

The intervention developed in this study has potential to improve the efficiency of community mental health services following discharge from hospital as it is evidence-based, time-limited and manualised and aims to reduce hospital admissions and crisis service use. The intervention will be tested to assess its clinical and cost effectiveness in a randomised controlled trial.

Predicting psychiatric readmission: sex-specific models to predict 30-day readmission following acute psychiatric hospitalization

PURPOSE

Psychiatric readmission is a common negative outcome. Predictors of readmission may differ by sex. This study aimed to derive and internally validate sex-specific models to predict 30-day psychiatric readmission.

METHODS

We used population-level health administrative data to identify predictors of 30-day psychiatric readmission among women (n = 33,353) and men (n = 32,436) discharged from all psychiatric units in Ontario, Canada (2008-2011). Predictor variables included sociodemographics, health service utilization, and clinical characteristics. Using derivation data sets, multivariable logistic regression models were fit to determine optimal predictive models for each sex separately. Results were presented as adjusted odds ratios (aORs) and 95% confidence intervals (CI). The multivariable models were then applied in the internal validation data sets.

RESULTS

The 30-day readmission rates were 9.3% (women) and 9.1% (men). Many predictors were consistent between women and men. For women only, personality disorder (aOR 1.21, 95% CI 1.03-1.42) and positive symptom score (aOR 1.41, 95% CI 1.09-1.82 for score of 1 vs. 0; aOR 1.44, 95% CI 1.26-1.64 for ≥ 2 vs. 0) increased odds of readmission. For men only, self-care problems at admission (aOR 1.20, 95% CI 1.06-1.36) and discharge (aOR 1.44, 95% CI 1.26-1.64 for score of 1 vs. 0; aOR 1.79, 95% CI 1.17-2.74 for 2 vs. 0), and mild anxiety rating (score of 1 vs. 0: aOR 1.30, 95% CI 1.02-1.64, derivation model only) increased odds of readmission. Models had moderate discriminative ability in derivation and internal validation samples for both sexes (c-statistics 0.64-0.65).

CONCLUSIONS

Certain key predictors of psychiatric readmission differ by sex. This knowledge may help to reduce psychiatric hospital readmission rates by focusing interventions.

Needs, Perceived Support, and Hospital Readmissions in Patients with Severe Mental Illness

People with severe mental illness have multiple and complex needs that often are not addressed. The purpose of this study was to analyse needs and support perceived and the relationship with hospital readmission. We assessed 100 patients with severe mental illness at discharge from an acute inpatient unit in terms of needs (Camberwell Assessment of Needs), clinical status (The Brief Psychiatric Rating Scale), and social functioning (Personal and Social Performance); we also followed up these patients for 1 year. The group of patients who were readmitted had more total needs than did the non-readmitted, in addition to more unmet needs, although the differences were not significant. The highest risk factor for rehospitalisation was the number of previous admissions. In addition, the help of informal carers in alleviating psychological distress was associated with the risk of readmission. The main conclusion concerns the role of the psychological support provided by informal networks in preventing readmission.

Experiences of people with a personality disorder or mood disorder regarding carrying out daily activities following discharge from hospital

Introduction

People with a diagnosed personality or mood disorder can experience challenges to participating in everyday life. Having a relapse of symptoms and an admission to hospital can further disrupt daily life. The aim of this study is to explore the experiences of people with a personality or mood disorder regarding carrying out everyday activities following discharge from hospital.

Method

Semi-structured interviews were carried out with 16 service users, by a researcher with lived experience of mental health problems and admissions to hospital.

Findings

Five themes were identified: The cumulative effect of multiple admissions on activities of daily living; the consequences of long admissions on daily living; reduced activities caused by social isolation in the first few months post-discharge; activities that people would like to do better post-discharge from hospital and longer term goals.

Conclusion

The findings of this study identified challenges people with a personality or mood disorder experience post-discharge from hospital regarding developing a daily routine, managing their home environment and participating in social activities. This indicates the importance of occupational therapy provision following discharge from hospital.

Pre-discharge factors predicting readmissions of psychiatric patients: a systematic review of the literature

BACKGROUND

Readmission rate is considered an indicator of the mental health care quality. Previous studies have examined a number of factors that are likely to influence readmission. The main objective of this systematic review is to identify the studied pre-discharge variables and describe their relevance to readmission among psychiatric patients.

METHODS

Studies on the association between pre-discharge variables and readmission after discharge with a main psychiatric diagnosis were searched in the bibliographic databases Ovid Medline, PsycINFO, ProQuest Health Management and OpenGrey. Relevant publications published between January 1990 and June 2014 were included. For each variable, the number of papers that considered it as a predictor of readmission and that found a significant association was recorded, together with the association direction and whether it was found respectively in bivariate and in multivariate analyses.

RESULTS

Of the 734 articles identified in the search, 58 papers were included in this review, mainly from the USA and concerning patients with severe mental disorders. Analysed variables were classified according to the following categories: patients' demographic, social and economic characteristics; patients' clinical characteristics; patients' clinical history; patients' attitude and perception; environmental, social and hospital characteristics; and admission and discharge characteristics. The most consistently significant predictor of readmission was previous hospitalisations. Many socio-demographic variables resulted as influencing readmission, but the results were not always homogeneous. Among other patients' clinical characteristics, diagnosis and measures of functional status were the most often used variables. Among admission characteristics, length of stay was the main factor studied; however, the results were not very consistent. Other relevant aspects resulted associated with readmission, including the presence of social support, but they have been considered only in few papers. Results of quality assessment are also reported in the review. The majority of papers were not representative of the general psychiatric population discharged from an inpatient service. Almost all studies used multivariate analytical methods, i.e., confounders were controlled for, but only around 60% adjusted for previous hospitalisation, the variable most consistently considered associated to readmission in the literature.

CONCLUSIONS

The results contribute to increase knowledge on pre-discharge factors that could be considered by researchers as well as by clinicians to predict and prevent readmissions of psychiatric patients. Associations are not always straightforward and interactions between factors have to be considered.

Impact of length of stay for first psychiatric admissions on the ratio of readmissions in subsequent years in a large Brazilian catchment area

PURPOSE

This study aims to verify the impact that the length of stay has on the rates of readmission for patients who were first admitted to various inpatient psychiatric units in a large catchment area in a middle-income country.

METHODS

The study included all patients who were first admitted to the 108 acute psychiatric beds available in the catchment area of Ribeirão Preto, Brazil, for a period of 8 years. Demographic features, inpatient unit of discharge, diagnosis and length of stay were assessed by bivariate analysis. An analysis of the time span between first admission and readmission was also conducted using survival curves estimated by the Kaplan-Meier formula. For the analyses of the risk of readmissions, a logistic regression analysis was conducted.

RESULTS

From a total of 6261 patients admitted in the period of the survey, approximately one-third (2006) had at least one other readmission during the follow-up period. The rates per year of early readmission (within 90 days after discharge) varied from 16.1 to 20.9 %. The risk of readmission was higher immediately after discharge. The survival analysis showed that ultrashort length of stay (1-2 days) was associated with reduced odds of readmission, but multivariate logistic analysis showed no association between length of stay and the odds of readmissions. The predictors of early readmission included the diagnosis of depressive, bipolar, psychotic, and non-alcohol-related disorders, younger ages and unemployment.

CONCLUSIONS

Duration of the first psychiatric admission was not associated with a higher risk of readmissions. Predictors for early readmissions of first-time-admitted psychiatric patients seem to be more related to the severity of the psychiatric diagnosis and demographic characteristics.

Predictors of psychiatric rehospitalization among elderly patients

The population of Hong Kong and the proportion of elderly people have been increasing rapidly. The aim of this retrospective cohort study is to determine predictive factors for psychiatric rehospitalization within 2 years among elderly patients who were discharged from psychiatric wards, in attempt to reduce their rehospitalization rate and to reintegrate them into the community. Patients aged 65 and over, who were discharged from psychiatric wards of Pamela Youde Nethersole Eastern Hospital from 1 March 2010 to 29 February 2012, were identified. Rehospitalization within 2 years after discharge was the primary outcome measure, and the time to rehospitalization was measured as the secondary outcome. Patients were subgrouped into readmitted and non-readmitted groups. Logistic regression and Cox regression analyses were applied to the potential predictive factors with odds ratios and hazard ratios obtained, respectively, for the significant findings. Kaplan-Meier survival curves were plotted for graphical representation of the study results in survival analysis. 368 individuals satisfying the study criteria were identified. The same four factors were shown to be significantly associated with rehospitalization in both multiple logistic regression and Cox regression survival analysis. Referral to other psychiatric disciplines upon discharge (p< 0.001, OR=0.325, HR=0.405) was associated with a lower rehospitalization risk and correlated to a longer time to rehospitalization. History of suicidal behaviors (p< 0.001, OR=4.906, HR=3.161), history of violent behaviors (p< 0.001, OR=5.443, HR=3.935) and greater number of previous psychiatric admissions (p< 0.001, OR=1.250, HR=1.121)  were associated with a higher rehospitalization risk and predicted earlier rehospitalization. The rehospitalization rate of elderly patients was 5.2% at 1 month, 9.5% at 3 months, 15.0% at 6 months, 17.1% at 1 year, 18.8% at 1.5 year and 20.9% at 2 years.