ENTIMOS: Decision Support Tool Highlights Potential Impact of Non-intravenous Therapies for Multiple Sclerosis on Patient Care via Clinical Scenario Simulation.

INTRODUCTION: Administration of intravenous (IV), high-efficacy treatments (HETs) for the treatment of multiple sclerosis (MS) poses a high resourcing and planning burden on infusion centres, resulting in treatment delays that may increase the risk of breakthrough disease activity. Simulation tools can be used to systematically analyse capacity scenarios and identify and better understand constraints, therefore enabling decision-makers to optimise patient care. We have previously applied ENTIMOS, a discrete event simulation model, to assess scenarios of patient flow and care delivery using real-life data inputs from the neurology infusion suite at Charing Cross Hospital London. The model predicted that, given current capacity and projected demand, patients would experience high-risk treatment delays within 30 months. OBJECTIVE: This study aimed to address key healthcare challenges for MS patient care management as seen from a neurologist's perspective. We used ENTIMOS to predict the impact of several distinct and clinically plausible scenarios on patient waiting times at the same MS infusion suite and to quantify mitigation strategies needed to assure continuity of care. METHODS: We used real-world experience of an expert neurologist to identify five clinical scenarios: (1) switching patients to a subcutaneous (SC) MS treatment of the same therapeutic agent, in the same hospital setting; (2) extending opening times to the weekend; (3) reducing the number of infusion chairs (to simulate social distancing measures applied during the coronavirus disease 2019 [COVID-19] pandemic); (4) increasing demand for infusions; and (5) increasing the scheduling approval time. Patient waiting time for next due infusion and time to high-risk treatment delays (≥ 30 days) were the main analysed model outputs. Previously published base case results were used as reference. All hypothetical scenarios were run over a 3-year horizon (with the exception of scenario 1, which was run over a 3- and 5-year horizon). Strategies to mitigate treatment delays were analysed and discussed. RESULTS: Switching 50% of patients to SC treatment of the same therapeutic agent administered in hospital postponed the predicted high-risk treatment delays to shortly beyond the 3-year simulation timeframe (month 38). Weekend opening reduced waiting times from 20 days to 4 days and prevented treatment delays, however, at elevated labour costs. Reducing the infusion chairs increased waiting time to 53 days on average and 86 days at the end of the simulation, leading to high-risk treatment delays within 6 months. An increased demand for infusions increased waiting time to 26 days on average and 47 days at the end of the simulation, leading to high-risk treatment delays within 22 months. Prolonged scheduling approval time did not reduce the waiting time, nor postpone the high-risk treatment delays. CONCLUSION: Decision makers need transparency on capacity constraints to better plan resourcing at infusion suites and MS treatments. Our results showed that various mitigation measures, such as increasing capacity by additional infusion chairs per year and transferring patients to other infusion suites, may help prevent treatment delays. Switching patients from IV to an SC version of the same therapeutic agent reduced the waiting time moderately and postponed high-risk treatment delays. It was insufficient to prevent high-risk treatment delays in the long term.

Patients with multiple sclerosis and other neurological conditions receive therapies that are often given intravenously. Due to increasing demand for intravenous infusions, specialist infusion centres face challenges with scheduling and insufficient personnel numbers, which contributes to the increasing costs of care. Computer-based decision support tools can help hospital administrators predict demand for infusions, plan resources and estimate overall costs. We used a computer-based decision support tool, "ENTIMOS", to predict demand at a multiple sclerosis infusion suite in London and to simulate possible solutions. The tool predicted that over the next 3 years patients would face increasing waiting time for their treatment and many would experience high-risk treatment delays of 30 days or longer. We tested several different, realistic scenarios where treatment demand was exacerbated and alleviated: we tested what would happen if patients were discharged from the infusion suite (decreasing demand), if the centre opened for 7 days instead of 5 days a week (increasing capacity), if social distancing measures were in place (decreasing capacity), and other scenarios. We found that high-risk treatment delays could be avoided if the centre adds infusion chairs to the suite or switches patients out of the infusion suite (e.g. to a treatment administered at home). The most effective long-term solution would be to have treatment options for multiple sclerosis that could be taken by patients at home. These treatments would be required to have the same benefits and the same or lower risk as the intravenous infusion therapies that are used today. It would help reduce labour costs of healthcare and may enable patients with multiple sclerosis to manage their disease at home.

Methotrexate for the neurologist.

The use of methotrexate in clinical practice has expanded significantly in recent years, as an effective chemotherapeutic agent as well as disease-modifying treatment for conditions such as rheumatoid arthritis, psoriasis and Crohn's disease. It is also used as a steroid-sparing agent for a range of inflammatory diseases of the central and peripheral nervous systems. Clinical neurologists must, therefore, know how to start and uptitrate methotrexate, its monitoring requirements and its potential toxicities. This review aims first to explore the evidence base for using methotrexate in various neurological diseases and second to discuss important practicalities around its use, ensuring its safe application and appropriate monitoring.

Development of Autoimmune Thyroid Disease in Multiple Sclerosis Patients Post-Alemtuzumab Improves Treatment Response.

CONTEXT: Alemtuzumab is an anti-CD52 monoclonal antibody used in the treatment of relapsing-remitting multiple sclerosis (MS). Between 20% and 40% of alemtuzumab-treated MS patients develop autoimmune thyroid disease (AITD) as a side effect. OBJECTIVE: The objective of this work is to determine whether MS disease progression following alemtuzumab treatment differs in patients who develop AITD compared to those who do not. DESIGN, SETTING, AND PATIENTS: A retrospective analysis of 126 patients with relapsing-remitting MS receiving alemtuzumab from 2012 to 2017 was conducted at a tertiary referral center. MAIN OUTCOME MEASURES: Thyroid status, new relapses, Expanded Disability Status Scale (EDSS) score change, and disability progression following alemtuzumab were evaluated. RESULTS: Twenty-six percent (33 out of 126, 25 female, 8 male) of alemtuzumab-treated patients developed AITD, 55% of which was Graves disease. EDSS score following alemtuzumab was reduced in patients who developed AITD compared to those who did not (median [interquartile range]; AITD: -0.25 [-1 to 0.5] vs non-AITD: 0 [1-0]. P = .007]. Multivariable regression analysis confirmed that the development of AITD was independently associated with EDSS score improvement (P = .011). Moreover, AITD patients had higher relapse-free survival following alemtuzumab (P = .023). There was no difference in the number of new focal T2 lesions and contrast-enhancing magnetic resonance imaging lesions developed following alemtuzumab between the 2 groups. CONCLUSION: Graves disease was the most common form of AITD developed by MS patients following alemtuzumab. This study suggests that MS patients who develop AITD may have an improved response to alemtuzumab, as measured by reduced disability and lower relapse rate.

Increasing Therapist Productivity: Using Lean Principles in the Rehabilitation Department of an Academic Medical Center.

The Department of Rehabilitation Services, within the University of Maryland Medical Center's 650-bed academic medical center, was experiencing difficulty in meeting productivity standards. Therapists in the outpatient division believed they were not spending enough time performing billable patient care activities. Therapists in the inpatient division had difficulty keeping pace with the volume of incoming referrals. Collectively, these issues caused dissatisfaction among referral sources and frustration among the staff within the rehabilitation department. The department undertook a phased approach to address these issues that included examining the evidence, using Lean process improvement principles, and employing transformational leadership strategies to drive improvements in productivity and efficiency. The lessons learned support the importance of having meaningful metrics appropriate for the patient population served, the use of Lean as an effective tool for improving productivity in rehabilitation departments, the impact of engaging staff at the grassroots level, and the importance of having commitment from leaders. The study findings have implications for not only rehabilitation and hospital leadership, but CEOs and managers of any business who need to eliminate waste or increase staff productivity.