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Background: "Kooth" is a web-based mental health platform commissioned by the National Health Service (NHS), local authorities, charities, and businesses in the UK. The platform gives children and young people (CYP) access to an online community of peers and a team of counsellors. This study reports an early economic evaluation of the potential benefits of Kooth in the UK. Methods: An early evidence cost calculator was built to estimate the potential costs and savings of implementing Kooth from a UK NHS and crime sector perspective. A decision tree structure was used to track the progress of CYP with emerging mental health needs (EMHN), comparing CYP with access to Kooth to CYP without access to Kooth. The model implemented a 12-month time horizon and followed a typical Kooth contract in relation to costing, engagement, and CYP demographics. Results: The base case results followed a cohort of 2160 CYP. The results of the cost calculator estimated that engagement with Kooth is associated with a cost saving of £469,237 to the NHS across a 12-month time horizon, or £236.15 per CYP with an EMHN. From a combined NHS and UK crime sector perspective, the cost savings increased to £489,897, or £246.54 per CYP with an EMHN. The largest cost savings were provided by an estimated reduction of 5346 GP appointments and 298 antidepressant prescriptions. For this cohort, the model predicted that engagement with Kooth averted 6 hospitalisations due to suicidal ideation and 13 hospitalisations due to self-harm. Furthermore, the number of smokers and binge drinkers was reduced by 20 and 24, respectively. When a crime sector perspective was taken, 3 crimes were averted. Discussion: This early model demonstrates that Kooth has the potential to be a cost-saving intervention from both an NHS and a combined NHS and UK crime sector perspective. Cost savings were provided through aversion in clinical and social outcomes. The model used a conservative approach to balance the uncertainty around assumptions of the intermediate outcomes (GP and medication use). However, it is limited by a paucity of costing data and published evidence relating to the impact of digital mental health platforms.
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BACKGROUND: An economic model was developed with guidance from the National Institute for Health and Care Excellence (NICE) 'Managing Common Infections' (MCI) Committee to evaluate the cost effectiveness of different antibiotic treatment sequences for treating Clostridioides difficile infection (CDI) in England. METHODS: The model consisted of a 90-day decision tree followed by a lifetime cohort Markov model. Efficacy data were taken from a network meta-analysis and published literature, while cost, utility and mortality data were taken from published literature. A treatment sequence was defined as a first-line intervention or a different second-line intervention, and used constant third- and fourth-line interventions. The possible first- and second-line interventions were vancomycin, metronidazole, teicoplanin and fidaxomicin (standard and extended regimens). Total costs and quality-adjusted life-years (QALYs) were calculated and were used to run a fully incremental cost-effectiveness analysis. Threshold analysis was conducted around pricing. RESULTS: Sequences including teicoplanin, fidaxomicin (extended regimen) and second-line metronidazole were excluded based on recommendations from the committee. The final pairwise comparison was between first-line vancomycin and second-line fidaxomicin (VAN-FID), and the reverse (FID-VAN). The incremental cost-effectiveness ratio for FID-VAN compared with VAN-FID was £156,000 per QALY gained, and FID-VAN had a 0.2% likelihood of being cost effective at a £20,000 threshold. CONCLUSION: First-line vancomycin and second-line fidaxomicin was the most cost-effective treatment sequence at the NICE threshold for treating CDI in England. The main limitation of this study was that the initial cure and recurrence rates of each intervention were applied constantly across each line of treatment and each round of recurrence.
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INTRODUCTION: Chronic pain is one of the most prevalent causes of disability worldwide, and digital interventions may be one of the ways to meet this need. Randomised controlled trials have demonstrated that digital interventions can be effective in treating chronic pain. This study aimed to establish the clinical effectiveness of a web-based pain management programme (PMP), specifically whether it would lead to improved clinical outcomes and reduced health care costs in a real-world clinical setting. METHODS: Of 738 participants, 438 engaged with the programme and 300 did not. Two analyses were conducted: a within-subjects pre-post comparison of clinical outcomes for participants who completed the programme and a between-groups comparison of health care usage for those who engaged and those who did not. RESULTS: Participants who completed the programme made significant improvements with regard to their perceived health status, level of disability, mood, confidence managing pain, problems in life due to pain and level of pain. Around one-third of participants made reliable changes in their levels of disability, depression and anxiety. There was no relationship between gender or age and engagement with the programme. Those who engaged with the programme demonstrated reduced health care costs in the year following referral, whereas health care costs of non-engagers increased. Limitations of the study include a high drop-out rate and a non-randomised comparison group. Results must therefore be interpreted with some caution. CONCLUSION: A web-based pain management programme can be clinically effective and may be a useful addition to the treatments offered by pain management services.