Variations in Performance of Mental Health Providers in the English NHS: An Analysis of the Relationship Between Readmission Rates and Length-of-Stay

Duration of hospital admission in severe mental illness: is longer better?

A Cochrane review has compared short-stay hospital admission with long-stay/standard admission of patients with severe mental illness for a number of outcomes in a total 2030 participants from 6 randomised trials. It reached the conclusion, supported by limited evidence, that short admissions in mental health units do not increase the risk of death, readmission or worsening of mental state, and pose less risk of delayed discharge and patient's unemployment. This commentary examines the available evidence from previous studies and discusses its relevance to current practice.

Patient and service-level factors affecting length of inpatient stay in an acute mental health service: a retrospective case cohort study

BACKGROUND

The NHS Mental Health Implementation Plan aims to reduce length of inpatient psychiatric stays to a maximum of 32 days, yet provides little guidance on how to achieve this. Previous studies have attempted to analyse factors influencing length of stay in mental health units, focussing mostly on patient factors. These models fail to sufficiently explain the variation in duration of inpatient stay. We assess how the type of service delivered by a trust, in addition to patient factors, influences length of stay.

METHODS

We conducted a retrospective case cohort study in a large inner-city NHS mental health trust for all admissions in a 1 month period. Data was gathered from electronic notes of 105 patients. Descriptive univariate and bivariate analyses were conducted on the data, with multiple regression analysis conducted on statistically significant data.

RESULTS

Short-stay assessment ward admission significantly reduced length of stay. Patients under outpatients or under care co-ordination, admitted through Mental Health Act assessment and formally detained all had longer length of stay. Out of area admissions, locum Consultant care, changing Responsible Clinician and ward transfers all led to longer length of stay. Factors indicating more severe illness such as increased observation level and polypharmacy, as well as diagnoses of psychosis or bipolar disorder were associated with longer duration of stay. Discharges requiring referral to accommodation or rehabilitation led to longer stays. The most significant factors that influenced length of stay were higher observation levels, diagnosis of psychotic illness or bipolar, and discharge to rehabilitation placement. The final model, taking into account all these factors, was able to account for 59.6% of the variability in length of stay.

CONCLUSIONS

The study backs up existing literature which shows patient-factors have an influence on length of stay. The study also demonstrates that service-level factors have an impact on the duration of stay. This data may be used to inform further studies which may aid provision of inpatient and community services in the future.

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.

Clinical database of the CYP-guides trial: An open data resource on psychiatric hospitalization for severe depression

CYP-GUIDES (Cytochrome Psychotropic Genotyping Under Investigation for Decision Support ) is a randomized controlled trial (RCT) of pharmacogenetic decision support in the psychotropic treatment of hospitalized patients with major depressive disorder or severe depression. Patients were treated according to their CYP2D6 functional status or empirically and compared for both their Length of Stay (LOS, primary outcome) at the hospital and Re-Admission Rate (RAR, secondary outcome) 30 days after discharge. The trial was conducted at the Institute of Living (Hartford Hospital, Hartford CT). CYP2D6 genotyping was implemented to infer the functional status of the CYP2D6 enzyme and classify it as sub-normal, normal or supra-normal. The electronic medical record (EMR) transmitted to the physician the indicated drug prescribing guidance. During the RCT, 1500 patients were recruited and 1459 genotyped for CYP2D6. A 1:2 randomization assigned 477 patients to standard therapy (Group S) and 982 to genetically-guided therapy (Group G). In Group S, standard empiric treatment was indicated for all patients. In Group G, medications primarily metabolized by the CYP2D6 enzyme were proscribed for patients with sub- or supra-normal CYP2D6 function. The clinical course, therapeutic guidance, and drug treatment for each patient are being published in this article and deposited in Mendeley Data. These data should be valuable to assess the impact of clinical decision support on utilization of psychiatric resources for treatment of severe depression requiring hospitalization.

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.

Funding approaches for mental health services: Is there still a role for clustering?

Funding for mental health services in England faces many challenges including operating under financial constraints where it is not easy to demonstrate the link between activity and funding. Mental health services need to operate alongside and collaborate with acute hospital services where there is a well-established system for paying for activity. The funding landscape is shifting at a rapid pace and we outline the distinctions between the three main options - block contracts, episodic payment and capitation. Classification of treatment episodes via clustering presents an opportunity to demonstrate activity and reward it within these payment approaches. We have been engaged in research to assess how well the clustering system is performing against a number of fundamental criteria. Clusters need to be reliably recorded, to correspond to health needs, and to treatments that require roughly similar resources. We find that according to these criteria, clusters are falling short of providing a sound basis for measuring and financing services. Yet, we argue, it is the best available option and is essential for a more transparent funding approach for mental health to demonstrate its claim on resources, and that, as such, clusters should be a starting point for evolving a better funding system.

Determinants of hospital length of stay for people with serious mental illness in England and implications for payment systems: a regression analysis

BACKGROUND

Serious mental illness (SMI), which encompasses a set of chronic conditions such as schizophrenia, bipolar disorder and other psychoses, accounts for 3.4 m (7 %) total bed days in the English NHS. The introduction of prospective payment to reimburse hospitals makes an understanding of the key drivers of length of stay (LOS) imperative. Existing evidence, based on mainly small scale and cross-sectional studies, is mixed. Our study is the first to use large-scale national routine data to track English hospitals' LOS for patients with a main diagnosis of SMI over time to examine the patient and local area factors influencing LOS and quantify the provider level effects to draw out the implications for payment systems.

METHODS

We analysed variation in LOS for all SMI admissions to English hospitals from 2006 to 2010 using Hospital Episodes Statistics (HES). We considered patients with a LOS of up to 180 days and estimated Poisson regression models with hospital fixed effects, separately for admissions with one of three main diagnoses: schizophrenia; psychotic and schizoaffective disorder; and bipolar affective disorder. We analysed the independent contribution of potential determinants of LOS including clinical and socioeconomic characteristics of the patient, access to and quality of primary care, and local area characteristics. We examined the degree of unexplained variation in provider LOS.

RESULTS

Most risk factors did not have a differential effect on LOS for different diagnostic sub-groups, however we did find some heterogeneity in the effects. Shorter LOS in the pooled model was associated with co-morbid substance or alcohol misuse (4 days), and personality disorder (8 days). Longer LOS was associated with older age (up to 19 days), black ethnicity (4 days), and formal detention (16 days). Gender was not a significant predictor. Patients who self-discharged had shorter LOS (20 days). No association was found between higher primary care quality and LOS. We found large differences between providers in unexplained variation in LOS.

CONCLUSIONS

By identifying key determinants of LOS our results contribute to a better understanding of the implications of case-mix to ensure prospective payment systems reflect accurately the resource use within sub-groups of patients with SMI.