Association between clinic-level quality of care and patient-level outcomes in multiple sclerosis

BACKGROUND Multiple sclerosis (MS) quality of care guidelines are consensus-based. The effectiveness of the recommendations is unknown. OBJECTIVE To determine whether clinic-level quality of care affects clinical and patient-reported outcomes. METHODS This nationwide observational cohort study included patients with adult-onset MS in the Swedish MS registry with disease onset 2005-2015. Clinic-level quality of care was measured by four indicators: visit density, magnetic resonance imaging (MRI) density, mean time to commencement of disease-modifying therapy, and data completeness. Outcomes were Expanded Disability Status Scale (EDSS) and patient-reported symptoms measured by the Multiple Sclerosis Impact Scale (MSIS-29). Analyses were adjusted for individual patient characteristics and disease-modifying therapy exposure. RESULTS In relapsing MS, all quality indicators benefitted EDSS and physical symptoms. Faster treatment, frequent visits, and higher data completeness benefitted psychological symptoms. After controlling for all indicators and individual treatment exposures, faster treatment remained independently associated with lower EDSS (-0.06, 95% confidence interval (CI): -0.01, -0.10) and more frequent visits were associated with milder physical symptoms (MSIS-29 physical score: -16.2%, 95% CI: -1.8%, -29.5%). Clinic-level quality of care did not affect any outcomes in progressive-onset disease. CONCLUSION Certain quality of care indicators correlated to disability and patient-reported outcomes in relapse-onset but not progressive-onset disease. Future guidelines should consider recommendations specific to disease course.

[1]  V. Tomassini,et al.  Clinical Outcomes of Escalation vs Early Intensive Disease-Modifying Therapy in Patients With Multiple Sclerosis , 2019, JAMA neurology.

[2]  Gavin Giovannoni,et al.  International consensus on quality standards for brain health-focused care in multiple sclerosis , 2018, Multiple sclerosis.

[3]  Pierre Grammond,et al.  Silent lesions on MRI imaging – Shifting goal posts for treatment decisions in multiple sclerosis , 2018, Multiple sclerosis.

[4]  R. Osborne,et al.  The role of health literacy in explaining the association between educational attainment and the use of out-of-hours primary care services in chronically ill people: a survey study , 2018, BMC Health Services Research.

[5]  G. Launoy,et al.  Socio-economic status influences access to second-line disease modifying treatment in Relapsing Remitting Multiple Sclerosis patients , 2018, PloS one.

[6]  M. Greenwood,et al.  Meta-analysis of the Age-Dependent Efficacy of Multiple Sclerosis Treatments , 2017, Front. Neurol..

[7]  T. Eikemo,et al.  Exploring the differences in general practitioner and health care specialist utilization according to education, occupation, income and social networks across Europe: findings from the European social survey (2014) special module on the social determinants of health , 2017, European journal of public health.

[8]  L. Kappos,et al.  Safety and tolerability profile of daclizumab in patients with relapsing-remitting multiple sclerosis: An integrated analysis of clinical studies. , 2016, Multiple sclerosis and related disorders.

[9]  L. Lönn,et al.  Guidelines for the use of magnetic resonance imaging in diagnosing and monitoring the treatment of multiple sclerosis: recommendations of the Swedish Multiple Sclerosis Association and the Swedish Neuroradiological Society , 2016, Acta neurologica Scandinavica.

[10]  M. Zaffaroni,et al.  Variations in multiple sclerosis practice within Europe - Is it time for a new treatment guideline? , 2016, Multiple sclerosis and related disorders.

[11]  Pierre Grammond,et al.  Defining reliable disability outcomes in multiple sclerosis. , 2015, Brain : a journal of neurology.

[12]  F. Barkhof,et al.  Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis—clinical implementation in the diagnostic process , 2015, Nature Reviews Neurology.

[13]  J. Hillert,et al.  The Swedish MS registry – clinical support tool and scientific resource , 2015, Acta neurologica Scandinavica.

[14]  T. Kalincik Multiple Sclerosis Relapses: Epidemiology, Outcomes and Management. A Systematic Review , 2015, Neuroepidemiology.

[15]  D. Centonze,et al.  Achieving patient engagement in multiple sclerosis: A perspective from the multiple sclerosis in the 21st Century Steering Group. , 2015, Multiple sclerosis and related disorders.

[16]  Xinyue Qin,et al.  Systematic Review of Clinical Practice Guidelines Related to Multiple Sclerosis , 2014, PloS one.

[17]  Thomas Kohlmann,et al.  Systematic literature review and validity evaluation of the Expanded Disability Status Scale (EDSS) and the Multiple Sclerosis Functional Composite (MSFC) in patients with multiple sclerosis , 2013, BMC Neurology.

[18]  A. P. D. Ponce de Leon,et al.  Socioeconomic differences in healthcare utilization, with and without adjustment for need: An example from Stockholm, Sweden , 2013, Scandinavian journal of public health.

[19]  I. Sperduti,et al.  The importance of physician–patient relationship for improvement of adherence to long-term therapy: data of survey in a cohort of multiple sclerosis patients with mild and moderate disability , 2012, Neurological Sciences.

[20]  C. Pozzilli,et al.  Real‐life impact of early interferonβ therapy in relapsing multiple sclerosis , 2009, Annals of neurology.

[21]  L. Kappos,et al.  Long-term subcutaneous interferon beta-1a therapy in patients with relapsing-remitting MS , 2006, Neurology.

[22]  J. Wolinsky,et al.  Neurologic consequence of delaying glatiramer acetate therapy for multiple sclerosis: 8‐year data , 2005, Acta neurologica Scandinavica.

[23]  A Thompson,et al.  The Multiple Sclerosis Impact Scale (MSIS-29): a new patient-based outcome measure. , 2001, Brain : a journal of neurology.