Systematic review of the methods of health economic models assessing antipsychotic medication for schizophrenia

Background Numerous economic models have assessed the cost-effectiveness of antipsychotic medications in schizophrenia. It is important to understand what key impacts of antipsychotic medications were considered in the existing models and limitations of existing models in order to inform the development of future models. Objectives This systematic review aims to identify which clinical benefits, clinical harms, costs and cost savings of antipsychotic medication have been considered by existing models, to assess quality of existing models and to suggest good practice recommendations for future economic models of antipsychotic medications. Methods An electronic search was performed on multiple databases (MEDLINE, EMBASE, PsycInfo, Cochrane database of systematic reviews, The NHS Economic Evaluation Database and Health Technology Assessment database) to identify economic models of schizophrenia published between 2005–2020. Two independent reviewers selected studies for inclusion. Study quality was assessed using the National Institute for Health and Care Excellence (NICE) checklist and the Cooper hierarchy. Key impacts of antipsychotic medications considered by exiting models were descriptively summarised. Results Sixty models were included. Existing models varied greatly in key impacts of antipsychotic medication included in the model, especially in clinical outcomes used for assessing reduction in psychotic symptoms and types of adverse events considered in the model. Quality of existing models was generally low due to failure to capture the health and cost impact of adverse events of antipsychotic medications and input data not obtained from best available source. Good practices for modelling antipsychotic medications are suggested. Discussions This review highlights inconsistency in key impacts considered by different models, and limitations of the existing models. Recommendations on future research are provided

The UPBEAT nurse-delivered personalized care intervention for people with coronary heart disease who report current chest pain and depression: a randomised controlled pilot study

Background: Depression is common in people with coronary heart disease (CHD) and associated with worse outcome. This study explored the acceptability and feasibility of procedures for a trial and for an intervention, including its potential costs, to inform a definitive randomized controlled trial (RCT) of a nurse-led personalised care intervention for primary care CHD patients with current chest pain and probable depression. Methods: Multi-centre, outcome assessor-blinded, randomized parallel group study. CHD patients reporting chest pain and scoring 8 or more on the HADS were randomized to personalized care (PC) or treatment as usual (TAU) for 6 months and followed for 1 year. Primary outcome was acceptability and feasibility of procedures; secondary outcomes included mood, chest pain, functional status, well being and psychological process variables. Result: 1001 people from 17 General Practice CHD registers in South London consented to be contacted; out of 126 who were potentially eligible, 81 (35% female, mean age = 65 SD11 years) were randomized. PC participants (n = 41) identified wide ranging problems to work on with nurse-case managers. Good acceptability and feasibility was indicated by low attrition (9%), high engagement and minimal nurse time used (mean/SD = 78/19 mins assessment, 125/91 mins telephone follow up). Both groups improved on all outcomes. The largest between group difference was in the proportion no longer reporting chest pain (PC 37% vs TAU 18%; mixed effects model OR 2.21 95% CI 0.69, 7.03). Some evidence was seen that self efficacy (mean scale increase of 2.5 vs 0.9) and illness perceptions (mean scale increase of 7.8 vs 2.5) had improved in PC vs TAU participants at 1 year. PC appeared to be more cost effective up to a QALY threshold of approximately £3,000. Conclusions: Trial and intervention procedures appeared to be feasible and acceptable. PC allowed patients to work on unaddressed problems and appears cheaper than TAU

Factors associated with use of psychiatric intensive care and seclusion in adult inpatient mental health services

Aims.Within acute psychiatric inpatient services, patients exhibiting severely disturbed behaviour can be transferred to a psychiatric intensive care unit (PICU) and/or secluded in order to manage the risks posed to the patient and others. However, whether specific patient groups are more likely to be subjected to these coercive measures is unclear. Using robust methodological and statistical techniques, we aimed to determine the demographic, clinical and behavioural predictors of both PICU and seclusion.Methods.Data were extracted from an anonymised database comprising the electronic medical records of patients within a large South London mental health trust. Two cohorts were derived, (1) a PICU cohort comprising all patients transferred from general adult acute wards to a non-forensic PICU ward between April 2008 and April 2013 (N = 986) and a randomly selected group of patients admitted to general adult wards within this period who were not transferred to PICU (N = 994), and (2) a seclusion cohort comprising all seclusion episodes occurring in non-forensic PICU wards within the study period (N = 990) and a randomly selected group of patients treated in these wards who were not secluded (N = 1032). Demographic and clinical factors (age, sex, ethnicity, diagnosis, admission status and time since admission) and behavioural precursors (potentially relevant behaviours occurring in the 3 days preceding PICU transfer/seclusion or random sample date) were extracted from electronic medical records. Mixed effects, multivariable logistic regression analyses were performed with all variables included as predictors.Results.PICU cases were significantly more likely to be younger in age, have a diagnosis of bipolar disorder and to be held on a formal section compared with patients who were not transferred to PICU; female sex and longer time since admission were associated with lower odds of transfer. With regard to behavioural precursors, the strongest predictors of PICU transfer were incidents of physical aggression towards others or objects and absconding or attempts to abscond. Secluded patients were also more likely to be younger and legally detained relative to non-secluded patients; however, female sex increased the odds of seclusion. Likelihood of seclusion also decreased with time since admission. Seclusion was significantly associated with a range of behavioural precursors with the strongest associations observed for incidents involving restraint or shouting.Conclusions.Whilst recent behaviour is an important determinant, patient age, sex, admission status and time since admission also contribute to risk of PICU transfer and seclusion. Alternative, less coercive strategies must meet the needs of patients with these characteristics

A systematic review of economic models across the entire schizophrenia pathway

Background Schizophrenia is associated with a high economic burden. Economic models can help to inform resource allocation decisions to maximise benefits to patients. Objectives This systematic review aims to assess the availability, quality and consistency of conclusions of health economic models evaluating the cost effectiveness of interventions for schizophrenia. Methods An electronic search was performed on multiple databases (MEDLINE, EMBASE, PsycINFO, Cochrane database of systematic reviews, NHS Economic Evaluation Database and Health Technology Assessment database) to identify economic models of interventions for schizophrenia published between 2005 and 2020. Two independent reviewers selected studies for inclusion. Study quality was assessed using the National Institute for Health and Care Excellence (NICE) checklist and the Cooper hierarchy. Model characteristics and conclusions were descriptively summarised. Results Seventy-three models met inclusion criteria. Seventy-eight percent of existing models assessed antipsychotics; however, due to inconsistent conclusions reported by different studies, no antipsychotic can be considered clearly cost effective compared with the others. A very limited number of models suggest that the following non-pharmacological interventions might be cost effective: psychosocial interventions, stratified tests, employment intervention and intensive intervention to improve liaison between primary and secondary care. The quality of included models is generally low due to use of a short time horizon, omission of adverse events of interventions, poor data quality and potential conflicts of interest. Conclusions This review highlights a lack of models for non-pharmacological interventions, and limitations of the existing models, including low quality and inconsistency in conclusions. Recommendations on future modelling approaches for schizophrenia are provided

A single, one-off measure of depression and anxiety predicts future symptoms, higher healthcare costs, and lower quality of life in coronary heart disease patients: Analysis from a multi-wave, primary care cohort study

To determine whether a one-off, baseline measure of depression and anxiety in a primary care, coronary heart disease (CHD) population predicts ongoing symptoms, costs, and quality of life across a 3-year follow-up.Longitudinal cohort study.16 General Practice surgeries across South-East London.803 adults (70% male, mean age 71 years) contributing up to 7 follow-up points.Ongoing reporting of symptoms, health care costs, and quality of life.At baseline, 27% of the sample screened positive for symptoms of depression and anxiety, as measured by the Hospital Anxiety and Depression Scale (HADS). The probability of scoring above the cut-off throughout the follow-up was 71.5% (p<0.001) for those screening positive at baseline, and for those screening negative, the probability of scoring below the cut-off throughout the follow-up was 97.6% (p<0.001). Total health care costs were 39% higher during follow-up for those screening positive (p<0.05). Quality of life as measured by the SF-12 was lower on the mental component during follow-up for those screening positive (-0.75, CI -1.53 to 0.03, p = 0.059), and significantly lower on the physical component (-4.99, CI -6.23 to -.376, p<0.001).A one-off measure for depression and anxiety symptoms in CHD predicts future symptoms, costs, and quality of life over the subsequent three-years. These findings suggest symptoms of depression and anxiety in CHD persist throughout long periods and are detrimental to a patient's quality of life, whilst incurring higher health care costs for primary and secondary care services. Screening for these symptoms at the primary care level is important to identify and manage patients at risk of the negative effects of this comorbidity. Implementation of screening, and possible collaborative care strategies and interventions that help mitigate this risk should be the ongoing focus of researchers and policy-makers

Overview and Use of Tools for Selecting Modelling Techniques in Health Economic Studies

The availability and use of tools to guide the choice of modelling technique are not well understood. Our study aims to review existing tools and explore the use of those tools in health economic models. Two reviews and one case study were conducted. Review 1 aimed to identify tools based on expert opinion and citation searching and explore the value of the tools for health economic models. Review 2, based on citation searching, aimed to describe how those tools have been used in health economic models. Both reviews were conducted using Web of Science and Scopus. Two independent reviewers selected studies for inclusion. A case study, focused on economic evaluations of antipsychotic medication in schizophrenia, was conducted to compare the modelling techniques used by existing models with modelling techniques recommended by identified tools. Seven tools were identified, of which the revised Brennan's toolkit, was assessed to be the most appropriate for health economic models. The seven tools were cited 126 times in publications reporting health economic models. Only 17 of these (13.5%) reported that they used the tool(s) to guide the choice of modelling technique. Application of these tools suggested discrete event simulation is most appropriate for modelling antipsychotic medication in schizophrenia, but discrete event simulation was only used by 17% of existing models. There is considerable inconsistency between the modelling techniques used by existing models and modelling techniques recommended by tools. It is recommended that for future modelling studies the choice of modelling technique should be justified, this can be achieved by the application of model selection tools, such as the revised Brennan's toolkit. Future research is required to explore the barriers to using model selection tools in health economic models and to update existing tools and make them easier to use