Risk Factors for Inpatient Psychiatric Readmission: Are There Gender Differences?

Factors associated with unplanned readmissions for patients with mental and behavioural disorders in China: a quantitative analysis

BACKGROUND

Unplanned readmissions among patients with mental and behavioural disorders (MBDs) disrupt inpatient recovery and impose financial burdens on families and healthcare systems.

OBJECTIVES

To estimate the 31-day unplanned inpatient readmission rates for MBDs in China and identify determinant profiles from the perspective of individual, hospital, and contextual levels.

METHODS

Data from patients with MBDs were collected from the medical records of 99 public hospitals across 10 cities. A total of 49,352 inpatient admissions were analysed based on the proposed conceptual model using multilevel logistic regressions.

RESULTS

The 31-day unplanned readmission rate (excluding 0-1-day returns) was 8.6% (95% CI: 8.4-8.9%). Determinant profiles differed across the overall group and subgroups. The number of general practitioners within cities was associated with reduced risk of unplanned readmissions. Hospital factors such as facility type and size, human resources, and revenue size were associated with unplanned readmissions only in specific subgroups. Additionally, individual-level factors, including demographic information (e.g. gender, age, marital status, and occupational status), disease-related factors (e.g. primary diagnostic group, condition at admission, and other diagnoses), and clinical characteristics (e.g. length of stay and medical costs), were associated with unplanned readmissions across all subgroups.

CONCLUSION

The study emphasises collaborative efforts from health systems, hospitals, and patients to reduce unplanned readmissions for MDBs. Health systems should focus on improving access to care, enhancing quality, and ensuring continuity while providing incentives for hospitals. Additionally, hospitals should prioritise the identification and effective management of their high-risk patients.

Socio-demographic predictors of the time interval between successive hospitalizations among patients with borderline personality disorder

Background: Borderline personality disorder (BPD) affects 0.7 to 2.7% of the adult population and higher rates are reported in inpatient care. Hospitalizations of BPD patients are a complex and controversial challenge for mental health professionals. Recurrent hospitalizations are common and it is essential to identify risk factors that characterize patients who benefit from their hospitalization and those who return to the ward shortly after discharge. Aim: To investigate the potential link between BPD patients' socio-demographic factors and the expected time interval between their successive hospitalizations. Methods: A retrospective analysis of 1051 hospitalization records from 174 BPD patients. Through univariate, bivariate, and multivariate analyses, we investigated the possible relationship between patients' primary socio-demographic factors and the time between their successive hospitalizations. Results: Patients' age, marital status, and living arrangement were found to be statistically connected with the time interval between successive hospitalizations. Specifically, being older, married and/or patients to live with one's spouse/partner seem to be linked with a longer time interval between successive hospitalizations compared to patients who are young, single/divorced and/or those who live with their parents. Conclusions: The expected time interval between successive hospitalization of BPD patients can be partly explained by their socio-demographic characteristics.

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.

Risk factors associated with 30-day unplanned hospital readmission for patients with mental illness

Unplanned hospital readmission rate is up to 43% in mental health settings, which is higher than in general health settings. Unplanned readmissions delay the recovery of patients with mental illness and add financial burden on families and healthcare services. There have been efforts to reduce readmissions with a particular interest in identifying patients at higher readmission risk after index admission; however, the results have been inconsistent. This systematic review synthesized risk factors associated with 30-day unplanned hospital readmissions for patients with mental illness. Eleven electronic databases were searched from 2010 to 30 September 2021 using key terms of 'mental illness', 'readmission' and 'risk factors'. Sixteen studies met the selection criteria for this review. Data were synthesized using content analysis and presented in narrative and tabular form because the extracted risk factors could not be pooled statistically due to methodological heterogeneity of the included studies. Consistently cited readmission predictors were patients with lower educational background, unemployment, previous mental illness hospital admission and more than 7 days of the index hospitalization. Results revealed the complexity of identifying unplanned hospital readmission predictors for people with mental illness. Policymakers need to specify the expected standards that written discharge summary must reach general practitioners concurrently at discharge. Hospital clinicians should ensure that discharge summary summaries are distributed to general practitioners for effective ongoing patient care and management. Having an advanced mental health nurse for patients during their transition period needs to be explored to understand how this role could ensure referrals to the general practitioner are eventuated.

Exploring risk factors for re-hospitalization in a psychiatric inpatient setting: a retrospective naturalistic study

BACKGROUND

The reduction of multiple psychiatric hospitalizations is an important clinical challenge in mental health care. In fact, psychiatric re-hospitalization negatively affects the quality of life and the life expectancy of patients with psychiatric disorders. For these reasons, identifying predictors of re-hospitalization is important for better managing psychiatric patients. The first purpose of the present study was to examine the readmission rate in a large sample of inpatients with a psychiatric disorder. Second, we investigated the role of several demographical and clinical features impacting re-hospitalization.  METHOD: This retrospective study enrolled 1001 adult inpatients (510 men and 491 women) consecutively admitted to the University Psychiatric Clinic, Sant'Andrea Hospital, Sapienza University of Rome between January 2018 and January 2022. To identify risk factors for psychiatric re-hospitalization, we divided the sample into 3 subgroups: the Zero-Re group which had no readmission after the index hospitalization, the One-Re group with patients re-admitted only once, and the Two-Re with at least two re-admissions.  RESULTS: The groups differed according to previous hospitalizations, a history of suicide attempts, age at onset, and length of stay. Furthermore, the results of the regression model demonstrated that the Two-Re group was more likely to have a history of suicide attempts and previous hospitalizations.

DISCUSSION

These results indicate the importance of assessing risk factors in psychiatric hospitalized patients and implementing ad hoc prevention strategies for reducing subsequent re-hospitalizations.

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.

The Impact of 90-day Physician Follow-up Care on the Risk of Readmission Following a Psychiatric Hospitalization

AIMS

This study measures the impact of 90-day physician follow-up care after psychiatric hospitalization among 3,311 adults and youth, with risk of subsequent readmission within six months.

METHODS

A 5-year investigation was conducted based on Quebec (Canada) medical administrative databases. Cox proportional-hazards regression was performed, with 90-day follow-up care as the main independent variable, controlling for various sociodemographic, clinical, and other service use variables.

RESULTS

Within the 90-day follow-up period after patient discharge, or in the first 30 days, receiving at least one consultation per month as opposed to no consultation was associated with a reduced risk of psychiatric readmission. Women showed an increased readmission risk compared to men, while those living in less materially deprived areas a decreased risk as opposed to more deprived areas. Patients hospitalized for suicide attempt or schizophrenia spectrum and other psychotic disorders, and those with co-occurring mental and substance-related disorders or chronic physical illnesses, especially illnesses high on the severity index, also presented a heightened risk of hospitalization. Patients hospitalized for personality disorders or receiving a high continuity of physician care showed a reduced risk of readmission.

CONCLUSION

This study demonstrates that follow-up care, if provided within the first 30 days of discharge or monthly during the 90-day follow-up period, decreased the risk of readmission, as did having a high continuity of physician care prior to and within the 90-day follow-up period. However, few patients in this study had received such high-quality care, indicating that the Quebec system needs to considerably improve its discharge planning processes.

Predictors of behavioral health unit readmission within 30 days of discharge: A retrospective study

Several studies have aimed to describe associated demographic and psychiatric risk factors that would lead to readmission to a behavioral health unit within 30 days of discharge. Here we considered 1,095 patients that were discharged from Millcreek Community Hospital (MCH) in Erie, Pennsylvania between June 2018 and June 2019. We extracted electronic medical data and analyzed various risk factors using a SPSS software and performed Chi square analysis to determine significance. We determined that patients between the age 30–39 that were diagnosed with major depressive disorder or bipolar disorder, and patients that had 12 or more previous behavioral health admissions were significantly more likely to be readmitted within 30 days of discharge. By analyzing risk factors that lead to a higher percentage of readmission rates, physicians can be more readily equipped and prepared while treating inpatient psychiatric patients. These physicians can take more precautionary measures when discharging patients with specific characteristic profiles to prevent the risk of being readmitted within 30 days of discharge.

Smartphone ownership and use of mental health applications by psychiatric inpatients

Little is known about the use of mental health smartphone applications during the greatest period of vulnerability - immediately following discharge from a psychiatric inpatient unit. Currently, no data are available regarding smartphone ownership or technology literacy of individuals who receive inpatient psychiatric treatment. The goal of this study was to determine psychiatric inpatients' smartphone ownership, current uses of, and interest in utilizing apps to aid in mental health treatment after discharge. A single time point self-report survey was given to patients prior to discharge from a psychiatric inpatient unit at a major academic hospital in a metropolitan area of the United States. Of the 101 survey respondents, 82.8% indicated that they own a smartphone, and over 70% indicated that they use smartphone apps, can access the internet from their phones, and use social media. While only 25.3% reported that they currently use a mental health app, a majority of respondents (53.2%) expressed interest in using such apps in the future, and almost 60% would use those apps to track their mental health. Our data suggest that there is significant untapped potential for utilizing smartphone applications for psychiatric monitoring and treatment following discharge from an inpatient psychiatric unit.

Factors Related to 30-day Readmission following Hospitalization for Any Medical Reason among Patients with Mental Disorders: Facteurs liés à la réhospitalisation à 30 jours suivant une hospitalisation pour une raison médicale chez des patients souffrant de troubles mentaux

OBJECTIVE

This study evaluated the contributions of clinical, sociodemographic, and service use variables to the risk of early readmission, defined as readmission within 30 days of discharge following hospitalization for any medical reason (mental or physical illnesses), among patients with mental disorders in Quebec (Canada).

METHODS

In this longitudinal study, 2,954 hospitalized patients who had visited 1 of 6 Quebec emergency departments (ED) in 2014 to 2015 (index year) were identified through clinical administrative databanks. The first hospitalization was considered that may have occurred at any Quebec hospital. Data collected between 2012 and 2013 and 2013 and 2014 on clinical, sociodemographic, and service use variables were assessed as related to readmission/no readmission within 30 days of discharge using hierarchical binary logistic regression.

RESULTS

Patients with co-occurring substance-related disorders/chronic physical illnesses, serious mental disorders, or adjustment disorders (clinical variables); 4+ outpatient psychiatric consultations with the same psychiatrist; and patients hospitalized for any medical reason within 12 months prior to index hospitalization (service use variables) were more likely to be readmitted within 30 days of discharge. Patients who made 1 to 3 ED visits within 1 year prior to the index hospitalization, had their index hospitalization stay of 16 to 29 days, or consulted a physician for any medical reason within 30 days after discharge or prior to the readmission (service use variables) were less likely to be rehospitalized.

CONCLUSIONS

Early hospital readmission was more strongly associated with clinical variables, followed by service use variables, both playing a key role in preventing early readmission. Results suggest the importance of developing specific interventions for patients at high risk of readmission such as better discharge planning, integrated and collaborative care, and case management. Overall, better access to services and continuity of care before and after hospital discharge should be provided to prevent early hospital readmission.

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.

The Association between the Mental Health Nurse-to-Registered Nurse Ratio and Patient Outcomes in Psychiatric Inpatient Wards: A Systematic Review

Nursing skill mix in inpatient mental health wards varies considerably between countries. Some countries have an all-registered mental health nurse workforce; others have a mix of registered mental health and registered nurses. Understanding the optimal nursing skill mix in mental health inpatient units would inform service planning. This report aims to examine the association between the registered mental health nurse-to-registered nurse ratio and psychiatric readmission (or referral to community crisis services) in adult mental health inpatients. A systematic review was performed. We searched key databases for observational and experimental studies. Two researchers completed title-and-abstract and full-text screening. Our search identified 7956 citations. A full-text review of four papers was undertaken. No studies met our inclusion criteria. We report an empty review. Despite the obvious importance of the research question for the safe staffing of inpatient mental health services, there are no studies that have tested this association.

Risk factors of hospitalization for any medical condition among patients with prior emergency department visits for mental health conditions

BACKGROUND

This longitudinal study identified risk factors for frequency of hospitalization among patients with any medical condition who had previously visited one of six Quebec (Canada) emergency departments (ED) at least once for mental health (MH) conditions as the primary diagnosis.

METHODS

Records of n = 11,367 patients were investigated using administrative databanks (2012-13/2014-15). Hospitalization rates in the 12 months after a first ED visit in 2014-15 were categorized as no hospitalizations (0 times), moderate hospitalizations (1-2 times), and frequent hospitalizations (3+ times). Based on the Andersen Behavioral Model, data on risk factors were gathered for the 2 years prior to the first visit in 2014-15, and were identified as predisposing, enabling or needs factors. They were tested using a hierarchical multinomial logistic regression according to the three groups of hospitalization rate.

RESULTS

Enabling factors accounted for the largest percentage of total variance explained in the study model, followed by needs and predisposing factors. Co-occurring mental disorders (MD)/substance-related disorders (SRD), alcohol-related disorders, depressive disorders, frequency of consultations with outpatient psychiatrists, prior ED visits for any medical condition and number of physicians consulted in specialized care, were risk factors for both moderate and frequent hospitalizations. Schizophrenia spectrum and other psychotic disorders, bipolar disorders, and age (except 12-17 years) were risk factors for moderate hospitalizations, while higher numbers (4+) of overall interventions in local community health service centers were a risk factor for frequent hospitalizations only. Patients with personality disorders, drug-related disorders, suicidal behaviors, and those who visited a psychiatric ED integrated with a general ED in a separate site, or who visited a general ED without psychiatric services were also less likely to be hospitalized. Less urgent and non-urgent illness acuity prevented moderate hospitalizations only.

CONCLUSIONS

Patients with severe and complex health conditions, and higher numbers of both prior outpatient psychiatrist consultations and ED visits for medical conditions had more moderate and frequent hospitalizations as compared with non-hospitalized patients. Patients at risk for frequent hospitalizations were more vulnerable overall and had important biopsychosocial problems. Improved primary care and integrated outpatient services may prevent post-ED hospitalization.

Factors associated with 30-day and 1-year readmission among psychiatric inpatients in Beijing China: a retrospective, medical record-based analysis

BACKGROUND

Psychiatric readmissions negatively impact patients and their families while increasing healthcare costs. This study aimed at investigating factors associated with psychiatric readmissions within 30 days and 1 year of the index admissions and exploring the possibilities of monitoring and improving psychiatric care quality in China.

METHODS

Data on index admission, subsequent admission(s), clinical and hospital-related factors were extracted in the inpatient medical record database covering 10 secondary and tertiary psychiatric hospitals in Beijing, China. Logistic regressions were used to examine the associations between 30-day and 1-year readmissions plus frequent readmissions (≥3 times/year), and clinical variables as well as hospital characteristics.

RESULTS

The 30-day and 1-year psychiatric readmission rates were 16.69% (1289/7724) and 33.79% (2492/7374) respectively. 746/2492 patients (29.34%) were readmitted 3 times or more within a year (frequent readmissions). Factors significantly associated with the risk of both 30-day and 1-year readmission were residing in an urban area, having medical comorbidities, previous psychiatric admission(s), length of stay > 60 days in the index admission and being treated in tertiary hospitals (p < 0.001). Male patients were more likely to have frequent readmissions (OR 1.30, 95%CI 1.04-1.64). Receiving electroconvulsive therapy (ECT) was significantly associated with a lower risk of 30-day readmission (OR 0.72, 95%CI 0.56-0.91) and frequent readmissions (OR 0.60, 95%CI 0.40-0.91).

CONCLUSION

More than 30% of the psychiatric inpatients were readmitted within 1 year. Urban residents, those with medical comorbidities and previous psychiatric admission(s) or a longer length of stay were more likely to be readmitted, and men are more likely to be frequently readmitted. ECT treatment may reduce the likelihood of 30-day readmission and frequent admissions. Targeted interventions should be designed and piloted to effectively monitor and reduce psychiatric readmissions.

Community health services and risk of readmission in public psychiatric hospitals of Belo Horizonte, Brazil, 2005-2011

INTRODUCTION

The readmission phenomenon in psychiatry not only reflects the severity and chronicity of the underlying disorders, but also indicates the quality of mental healthcare. In the context of the Brazilian mental healthcare reform, no study has included the availability of outpatient care among the potential determinants for psychiatric readmission.

OBJECTIVE

To correlate the availability of community healthcare resources at the place of residence with the risk of psychiatric readmission.

METHODS

All admission records from 2005 to 2011 in the two public psychiatric hospitals of Belo Horizonte were included (n=19,723). Variables related to patients and characteristics of hospitalization were collected, and indicators of community healthcare coverage were calculated for each place of residence yearly. The outcome of interest was early (<7 days), medium-term (8-30 days) and late (31-365 days) readmissions. The analysis was based on Cox regressions.

RESULTS

The coverage of basic health units and of psychiatrists was associated with lower readmission risks. Coverage of specialized centers for psychosocial attention (Centros de Atenção Psicossocial [CAPS]) and psychologists did not show any protective effects. Young, male patients and those residing outside the capital had greater risk of early readmission. Compared to other psychotic disorders, mood disorders and neurotic disorders were seen as protective factors for readmission.

CONCLUSION

Regionalized attention offered by the CAPS did not result in reduced readmission risks.

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.