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Treatment- and work-related aspects have been neglected in health-related quality of life (HRQOL) measures in multiple sclerosis (MS). We aimed to develop a brief instrument covering all important impairment-, activity-, participation-, and treatment-related aspects for use in research and practice.

The 27-item Multiple Sclerosis Quality of Life Questionnaire (MS-QLQ27) was developed using open item collection, a multidisciplinary expert panel, and cognitive pretesting. It was evaluated for reliability, construct validity, and responsiveness in 100 patients presenting with relapse (84 at follow-up ~14 days later). Construct validity was analyzed by correlating the MS-QLQ27 with the disease-specific Hamburg Quality of Life Questionnaire in MS (HAQUAMS) and generic HRQOL instruments. The Expanded Disability Status Scale (EDSS) was used to analyze known-groups validity. Responsiveness was determined as the correlation of changes in MS-QLQ27 scores with changes in validation criteria.

Internal consistency was high (Cronbach α = 0.94 at baseline and 0.93 at follow-up). Convergent validity was supported by direction and magnitude of associations with disease-specific and generic instruments. Correlations with change in convergent criteria were strong, indicating responsiveness. The HAQUAMS showed the strongest associations with the MS-QLQ27. The MS-QLQ27 showed the highest effect size compared with other patient-reported outcomes and the EDSS. It successfully distinguished between levels of disease severity.

These results indicate that the MS-QLQ27 is a reliable, valid, and highly responsive instrument for assessing HRQOL during relapse evolution in MS. Its advantages are that it is brief yet comprehensive, covering work- and treatment-related aspects not addressed in previous measures.

From the Institute for Health Services Research in Dermatology and Nursing (HB, MA, CB) and Institute of Neuroimmunology and Multiple Sclerosis (CH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany. 

Christine Blome, PhD, Institute for Health Services Research in Dermatology and Nursing, University Medical Center Hamburg-Eppendorf, Martinistr 52, 20246 Hamburg, Germany; 

The authors thank all the patients who participated in this study and the Scientific Communication Team of the Institute for Health Services Research in Dermatology and Nursing (IVDP), University Medical Center Hamburg-Eppendorf (UKE), in particular Mathilda Meyer and Mario Gehoff, for copy editing.

 The authors declare no conflicts of interest.

 This study was funded in part by the German Federal Ministry of Education and Research (grant 01EH1101B).

 The material was exhibited as a poster presentation at the 25th Annual Conference of the International Society for Quality of Life Research; October 24-27, 2018; Dublin, Ireland.

Health-related quality of life (HRQOL) is considered a key outcome for persons with multiple sclerosis (MS) and is increasingly being assessed in both clinical practice and trials.

 Measures of HRQOL can contribute to clinical trials by more fully assessing therapeutic efficacy

 and by being more comprehensive than scales that assess only the degree of neurologic deficit. Whereas in clinical trials accuracy, validity, and responsiveness of instruments are most relevant, barriers to the adoption of HRQOL in clinical practice arise mainly from choosing and interpreting HRQOL scores.

 Time and resources are limited in routine medical practice, creating a need for tools that are simple, short, and easy to interpret.

In patients with MS, HRQOL is associated with physical and mental factors such as depression and anxiety symptoms, fatigue, and cognitive functioning.

 Social functioning, from sexual disturbances to free-time activities and work-related issues, affects HRQOL

 and is considered to be more difficult to manage and, therefore, is underrecognized.

 Work-related problems or even unemployment due to MS are common in this population even when physical disability is low.

 can pose a significant burden on people with MS.

Despite the number of disease-specific instruments that have been developed in the past 20 years and the many phase 2 and 3 trials, there is still no HRQOL instrument generally accepted and adapted widely in routine care. Neither has there been established an agreed-on tool to monitor the impact of MS relapses from a patient perspective. Some of the HRQOL instruments put a focus on comprehensiveness and are, therefore, rather long and time-consuming, such as the Functional Assessment of Multiple Sclerosis (59 items)

 or the Multiple Sclerosis Quality of Life Inventory (138 items).

 Other instruments are briefer but do not include important aspects of HRQOL, such as work life problems. Examples are the Multiple Sclerosis International Quality of Life questionnaire,

 and the Hamburg Quality of Life Questionnaire in Multiple Sclerosis (HAQUAMS).

 To our knowledge, the aspect of treatment burden is lacking in all available instruments. Regarding psychometrics, only some have been tested for responsiveness to change (eg, the Patient-Reported Indices for Multiple Sclerosis,

 the Multiple Sclerosis International Quality of Life questionnaire,

 and the Multiple Sclerosis Quality of Life-54).

To capture the manifold factors of HRQOL impairment described previously herein, a comprehensive standardized instrument is needed. At the same time, to be suitable for use in both research and clinical practice, the instrument should be as brief as possible and should be able to depict clinical change. The instrument should be applicable to monitor relapse and long-term treatment. Its content should be rigorously based on patient input to capture the most patient-relevant outcomes.

 To our knowledge, an instrument with this combination of characteristics is currently lacking. Therefore, we aimed to fill this gap with the newly developed 27-item Multiple Sclerosis Quality of Life Questionnaire (MS-QLQ27), presented in this report.

The MS-QLQ27 was developed in a 4-step procedure: (1) open item collection, (2) multidisciplinary expert panel, (3) cognitive pretesting, and (4) longitudinal validation study.

Data on patient-relevant impairments were collected in an open survey of 59 patients with relapsing-remitting MS (RRMS) recruited at the MS outpatient clinic of the University Medical Center Hamburg-Eppendorf (UKE) between May 2013 and July 2013. Patients were in different disease stages, that is, either in relapse or in remission. In a questionnaire, patients were asked to describe, in their own words, impairments due to their disease (RRMS) in general, as well as during a relapse, and impairments in different areas of their lives.

Items for the MS-QLQ27 were defined by a multidisciplinary expert panel that included patients, methodologists, neurologists, and study nurses. Inclusion of the patient perspective and preferences at this stage was essential in selecting and wording the final items. To add clinical and methodological knowledge, experts in MS care and psychometrics were involved in the discussion.

The frequency with which impairments had been mentioned in the item collection survey was used as the basis of the decision process. The expert panel categorized and discussed these impairments regarding their suitability to capture general and condition-specific burden. Items were included if they were both frequently mentioned and clinically relevant; items were excluded if they were redundant, ambiguous, and/or infrequently mentioned in the open item collection. Finally, 27 items were incorporated into the MS-QLQ27 pilot version.

The MS-QLQ27 was subsequently tested for comprehensiveness and practicality in cognitive interviews with 10 patients with RRMS. Interviews were conducted at the center where recruitment for the open item data collection took place. Debriefing questions were used to identify items or words that were not understood or that were interpreted inconsistently by respondents and to obtain suggestions for revising questions. Patients also assessed the structure and layout of the questionnaire.

One hundred patients with RRMS were enrolled consecutively in a prospective, uncontrolled cohort study at the MS outpatient clinic of the University Medical Center Hamburg-Eppendorf (UKE) (n = 65) and at an outpatient neurologic practice in Hamburg, Germany (n = 35), between November 2014 and January 2016. To validate and test the instrument under clinical conditions, patients with RRMS with confirmed exacerbation who were due to receive treatment in the following 24 hours were included in the study. A relapse is a “patient-reported, or objectively observed, event typical of an acute inflammatory demyelinating event in the central nervous system, current or historical, with a duration of at least 24 hours.”

 We excluded patients with a major impairment of visual, hand, or cognitive function who were unable to complete the questionnaire on their own.

Case report forms were completed by patients and their neurologists before relapse treatment (baseline) and approximately 14 days later (follow-up). These forms included demographic and clinical data as well as disease-specific and generic HRQOL instruments as convergent validation parameters for MS-QLQ27 instrument evaluation.

For disease-specific HRQOL, we used the validated HAQUAMS,

 version 10.0. Its total score is based on 6 subscales: fatigue, thinking, upper limb mobility, lower limb mobility, mood, and communication. Generic HRQOL was assessed with the widely used preference-based questionnaire EQ-5D-3L.

 This tool records 3 levels of severity in 5 dimensions (morbidity, self-care, usual activities, pain/discomfort, anxiety/depression) and yields a single index value from 0 (lowest) to 1 (highest).

 The EuroQol Visual Analogue Scale (EQ VAS) recorded each respondent’s self-rated health on a vertical visual analogue scale with end points that were labeled 100 (best imaginable health state) and 0 (worst imaginable health state).

Distributional properties were explored using descriptive statistics: mean, standard deviation, percentage of patients scoring the minimum and maximum possible scores (floor and ceiling effects), and missing values. Internal consistency was assessed using Cronbach α and corrected item scale correlations.

Convergent validity was assessed by means of cross-sectional associations (Pearson correlation) among the HAQUAMS (subscales and composite score), EQ-5D-3L, and EQ VAS.

In accordance with Consensus-based Standards for the Selection of Health Measurement Instruments criteria,

 responsiveness was defined as the correlation of changes in MS-QLQ27 with changes in convergent criteria, which was tested for by determining partial correlations of posttreatment values while controlling for pretreatment values.

We hypothesized stronger associations with the HAQUAMS, which is disease-specific, than with the EQ-5D-3L and EQ VAS, which are generic.

Known-groups validity was assessed by examining MS-QLQ27 total score by baseline Expanded Disability Status Scale (EDSS) through 1-way analysis of variance with Scheffé post hoc tests. The EDSS score groups were defined as follows: 0 to 2.5, minor impairment; 3.0 to 4.5, moderate impairment; and 5.0 or greater, severe impairment.

 For known-groups validity analysis, we also anticipated differences between patients with short (≤5 years) and long (>20 years) disease duration.

The global score was computed as the arithmetic mean of all valid items (from 1 = not at all impaired to 5 = extremely impaired). If more than 75% of items were invalid or missing, no global score was computed. Within the MS-QLQ27, we used a filter question on patient employment status (“Do you work or are you in training or studying?”). If a patient ticked “No, due to multiple sclerosis” or “No, for other reasons,” the global score was computed without items 26 and 27, which relate to work life impairment. In this event, items 26 and 27 were not counted as missing.

To identify underlying dimensions of the MS-QLQ27, based on which potential subscales could be determined, a factor analysis with varimax rotation was performed over the 27 items, and factors with an eigenvalue greater than 1 were extracted. All statistical analyses were performed using SPSS Statistics for Windows, version 22.0 (IBM Corp).

The validation study was approved by the ethical review committee of the Medical Association of Hamburg and was conducted in accordance with the Declaration of Helsinki. All patients gave written informed consent before the start of the study.

Fifty-nine patients with RRMS (37 women [63%]) with a mean (SD) age of 37.3 (9.9) years completed the questionnaire during open item collection. The item pool contained 398 entries relating to impairments. Informed by the expert panel and cognitive pretesting, the final instrument, which was named MS-QLQ27, contained 27 physical, mental, and treatment-specific impairments as well as items relating to leisure, social, and work life issues. As a result of the pretesting, modifications in wording and use of additional examples in 3 items were made to ensure content comprehension. For example, the term 

The validation study sample consisted of 100 patients at baseline, of which 84 also participated at follow-up (

; all supplemental is in the online version of this article at IJMSC.org). Out of the 84 patients at follow-up, 61 patients (73%) self-reported as female, 20 self-reported as male, and 3 did not specify their sex. Mean (SD) age was 38.3 (18.9) years and disease duration was 8.3 (7.6) years. The EDSS scores ranged from 0.0 to 6.5, with moderate mean (SD) EDSS disability of 2.7 (1.6).

There were only small differences in demographic and clinical characteristics among participants between baseline and follow-up. The overall dropout rate at follow-up was 16%. Patients were mainly lost to follow-up due to a failure to present at a scheduled appointment (follow-up). The dropout analysis showed that the demographic and disease characteristics of dropouts did not differ significantly from those of the remainder of the sample. Descriptively, patients who dropped out were older, had a longer disease duration, and showed higher severity of MS.

During mean (SD) follow-up of 17 (4.4) days, patients were treated with cortisone pulse therapy for 3 to 5 days: 84% were treated with high-dose oral corticosteroids (500–1000 mg/d) and 16% with ultrahigh dose oral corticosteroids (>1500 mg/d).

The mean (SD) MS-QLQ27 global score at baseline was 2.31 (0.72) (range, 1–5); this score decreased significantly to 1.95 (0.72) at follow-up (

). With an effect size of −0.5, this improvement depicted by the MS-QLQ27 was considerably greater than that in the other HRQOL instruments showing effect sizes around 0.3.

Distributional Characteristics of MS-QLQ27 

Difficulties with walking, paresthesia (eg, numbness and tingling), and fatigue followed by physical weakness were the most pronounced impairments at baseline (

). For items relating to social life, such as “lack of understanding of others” or “limited social interaction,” lower mean values were found and fewer patients reported the highest possible value, indicating less pronounced impairment.

The number of missing values per MS-QLQ27 item at baseline was between 6.0% and 13.1% (average, 7.2%). At follow-up, we found a lower number of missing items, ranging from 1.3% to 10.3% (mean, 3.5%). Most missing values were found for the following items: at baseline, for item 25 “side effects of the treatment” (13.1%) and item 20 “limited sex life” (10.7%), and at follow-up, for item 26 “not able to work” (10.3%). Sixty-two percent of the patients were working at baseline according to the MS-QLQ27 question on occupational status, 18% answered “No, due to multiple sclerosis,” 10% answered “No, for other reasons,” and 10% were missing.

Cronbach α coefficients indicated high reliability at both measurement points, with values of 0.93 (baseline) and 0.94 (follow-up). The corrected item scale correlation ranged from 

 = 0.31 to 0.76 at baseline, with a large proportion of items (23 of 27) showing values greater than or equal to 0.5. Item 4 (“problems with eyesight”) correlated very weakly with the overall scale (baseline 

The factor analysis with varimax rotation revealed 7 factors with an eigenvalue greater than 1, explaining 72.3% of item variance. However, multiple items loaded highly and to a similar extent on more than 1 factor, which means that they could not be assigned to specific dimensions. Thus, items could not reasonably be assigned to different subscales so that only the global score was determined.

As anticipated, strong correlations of the MS-QLQ27 score were found with the HAQUAMS total score, both cross-sectionally (

). The MS-QLQ27 correlated to a lesser extent but still highly significantly with the generic EQ-5D-3L at both measuring times (

 < .001). The association between the MS-QLQ27 and EQ VAS was moderate, both cross-sectionally (

Change in the MS-QLQ27 score was moderately associated with change in the HAQUAMS subscales “fatigue,” “thinking,” “mobility upper limb,” and “mobility lower limb” (

 < .001) and to a lesser extent with the subscale “mood” (

 < .05). The “communication” subdomain was not correlated with the MS-QLQ27 longitudinally (

Results for known-groups validity indicate that the MS-QLQ27 successfully distinguished between groups of low, moderate, and high disease severity as measured with the EDSS: As expected, individuals with greater disability had significantly higher MS-QLQ27 scores. The post hoc test was significant at baseline for the comparison between patients with low and severe impairment (

 = .012), and likewise at follow-up among all 3 groups.

Individuals with longer disease duration had significantly higher MS-QLQ27 scores (

), as anticipated. At baseline and follow-up, differences in MS-QLQ27 scores were significant between patients with short (≤5 years) and moderate (>5–20 years) disease duration (

 = .014) and between those with short and long (>20 years) disease duration (

With the MS-QLQ27, we aimed to fill a gap in the range of MS-specific HRQOL instruments currently available and to develop a valid and responsive questionnaire that is brief, comprehensive (encompassing aspects such as work life and treatment burden), easy to complete (by using a single response scale for all items), and suitable for use in clinical practice and research.

There is still no agreed-on instrument to document the evolution of relapses. Commonly used severity and disability measures have been found to insufficiently capture the impacts of relapses that both patients and clinicians consider relevant.

 Only a limited percentage of relapses show EDSS-relevant alterations, and many cohort studies on relapse treatments have focused on only global clinical impression. New approaches to measure patients’ views on treatment benefit should fill this gap.

 The MS-QLQ27 offers another sensitive option that might be applicable in relapse treatment approaches: being aware that high-dose corticosteroids are of limited effectiveness and associated with substantial adverse effects.

After identification of impairments in general and during relapse in an open item collection process and discussion of the results by an expert panel that included patients, the pilot version of the MS-QLQ27 was tested using a cognitive pretest to ensure comprehensibility and practicability. The development process included patients during all steps and is, therefore, expected to ensure content validity. In the final version of the instrument, patients are asked to rate to what extent the 27 listed impairments have affected their lives in the past 7 days.

The distributional characteristics at baseline indicated a relatively high rate of missing values in MS-QLQ27 items, notably concerning treatment adverse effects, limitations in sexuality, and absenteeism/not being able to have a job. Missing values for treatment adverse effect items were probably high because some patients did not receive any treatment at baseline. At follow-up, the number of missing items was lower, with a satisfactory mean value of 3.5%.

The relatively high proportion of “not at all” impaired responses at baseline can be attributed to the rather low disease severity in the sample (mean [SD] EDSS score, 2.7 [1.61]), which decreased further by follow-up due to relapse treatment. Accordingly, both the MS-QLQ27 global score and other HRQOL measures decreased considerably by follow-up. This effect was found to be strongest in the MS-QLQ27, which underlines its responsiveness to change even within the short period of a relapse.

The mean values as reported for items relating to burden in work life (items 26 and 27) indicate a substantial patient burden that has to be adequately taken into account when measuring the impact of relapses for people with MS, which is in line with previous results on patients’ treatment benefit.

 On the other hand, we found lower mean values for items relating to social life, such as “lack of understanding of others” or “limited social interaction.” Thus, these items might be less relevant in the context of a relapse.

Cronbach α of the MS-QLQ27 was high at both baseline (α = 0.94) and follow-up (α = 0.93), indicating excellent interrelatedness of items. Item-total correlations ranged from 0.4 to 0.7, except for item 4 “problems with eyesight” (r = 0.05), which indicates that the corresponding item did not correlate with the overall scale. However, visual dysfunction is one of the most common manifestations and very early symptom of RRMS, often resulting from acute demyelinating optic neuropathy but not correlated to other MS impairments. Approximately three-quarters of the sample reported problems with eyesight at baseline. Moreover, from the patient perspective, it is one of the symptoms most relevant for HRQOL.

 Thus, from a purely psychometric perspective, the item on problems with eyesight could be deleted. But because the MS-QLQ27 can be used in shared decision-making in clinical practice, where all relevant aspects of HRQOL should be included, we decided to keep all patient-relevant items in the questionnaire, including the problems with eyesight item.

To test for convergent validity, we hypothesized correlations of the MS-QLQ27 score with changes in other HRQOL measures. Hypothesis testing showed the expected directions and magnitudes of correlations. The responsiveness of the MS-QLQ27 is supported by highly significant correlations with improvement in disease-specific and generic HRQOL. As expected, stronger (and highly significant) correlations were found with the HAQUAMS than with the generic HRQOL measures. Known-groups validity was supported with respect to disability according to EDSS scores and short (≤5 years) versus long (>20 years) disease duration. Most importantly, the MS-QLQ27 showed the strongest effect size for responsiveness. A long-term study is necessary to depict the responsiveness through longer MS evolution.

Compared with the existing MS-specific HRQOL instruments, the MS-QLQ27 is, to our knowledge, the first to cover not only long-term burden but also relapse-related impairments in 2 aspects: first, in the item development, patients were explicitly asked to name relapse-related impairments; second, the instrument was tested for responsiveness to relapse treatment. In addition, the MS-QLQ27 is shorter than many of the existing instruments. As such, it lends itself to use for relapse treatment evaluation in clinical practice from the patient perspective. To our knowledge, it is also the only shorter instrument that covers work life and treatment burden, both of which are highly relevant aspects of HRQOL in patients with MS.

One limitation of this study is that the sample includes only patients in current relapse, which restricts generalization to other MS populations. In addition to the excellent internal consistency found in this study, future research should assess test-retest reliability. Further investigations should focus on other patient groups, for example, those in remission, with secondary progressive MS, or with greater disease severity, to gain more information about the validity of the MS-QLQ27 in long-term MS treatment.

In conclusion, the MS-QLQ27 is a brief, reliable, valid, and responsive HRQOL questionnaire. It captures patient-relevant burden, including physical, mental, social, work, and treatment-specific aspects thereof, and is suitable for use in clinical practice and research.

The 27-Item Multiple Sclerosis Quality of Life Questionnaire: A New Brief Measure Including Treatment Burden and Work Life

Approximately 10 out of every 100,000 people in Pakistan have multiple sclerosis (MS), yet there is a dearth of research on MS in the country, with most prior studies limited by small sample sizes. We wish to report on the largest study of MS patients from Pakistan. The objectives of this study were to identify demographic characteristics, disease characteristics, hospitalization causes, and past and current treatments of patients with MS in Pakistan. A retrospective review of patient records of all patients diagnosed with MS was carried out at the Department of Medicine at the Aga Khan University Hospital in Karachi and the Pakistan Institute of Medical Sciences in Islamabad. Medical records were used to generate a list of patients who were admitted at participating centers with a diagnosis of MS between December 2019 and September 2020. The diagnosis of MS was based on McDonald criteria. The study was approved by the ethics review committees of both participating centers.

The study included 188 patients (mean age, 31.1 ± 11.22 years), with 37.2% men and 62.8% women. Relapsing-remitting MS was the most common type (81%), followed by primary progressive (10%) and secondary progressive (9%). The most common finding on T2-weighted fluid-attenuated inversion recovery MRI sequences was the presence of multiple foci (69.2%), most seen in the periventricular region (52.1%), followed by the juxtacortical region (49.3%). A single focus of gadolinium enhancement was observed in 20% of patients, most seen in the spinal cord (23.9%), followed by the periventricular area (18.1%).

Medication infusion was the most common reason for hospitalization, reported in 16% of cases, followed by exacerbation of MS in 13.8% cases, and infection in 4.3% cases. Ocrelizumab (5.3%), steroids (3.8%), and rituximab (3.2%) were the most common treatments prescribed. Patients had been treated previously with oral and intravenous steroids, azathioprine, and mitoxantrone, as shown in 

A detailed study of MRI lesions found multiple foci to be the most prevalent (69.2%), with periventricular and juxtacortical lesions the most common sites (52.1% and 49.3%, respectively). Incidental MS was reported in less than 1% of MRI scans.

 Disease characteristics and MRI findings in our group of MS patients were consistent with publications from other parts of the world.

 We explored reasons for hospitalization, the most common of which were MS exacerbation and medication infusions. Most patients (83%) were not taking any medications at their most recent evaluation. A prior study stated that 95% of patients received pulse steroids.

 Other treatments mentioned in literature include interferon beta, methotrexate, mitoxantrone,

 ocrelizumab, teriflunomide, alemtuzumab, and, per informal reports from neurologists, rituximab and azathioprine.

 Wasay et al found that less than one-fourth of all patients received disease-modifying therapies, of which 11% received methotrexate, 10% received mitoxantrone, and 1% received interferon beta therapy.

 However, recent years have seen a rise in the use of disease-modifying therapies due to an aggressive disease course or secondary progressive MS.

Presentations and Treatment of Multiple Sclerosis in Pakistan: A Retrospective Review of 188 Cases

 To access the article and evaluation online, go to 

 The target audience for this activity is physicians, advanced practice clinicians, nursing professionals, pharmacists, mental health professionals, social workers, and other health care providers involved in the research and treatment of people with multiple sclerosis (MS).

Characterize existing electronic medical record (EMR) platforms designed specifically for care of people with MS.

Describe relevant variables that are captured in the EMR that allow identification of EMR-based cohorts of people with MS.

In support of improving patient care, this activity has been planned and implemented by the Consortium of Multiple Sclerosis Centers (CMSC) and Intellisphere, LLC. The CMSC is jointly accredited by the Accreditation Council for Continuing Medical Education, the Accreditation Council for Pharmacy Education, and the American Nurses Credentialing Center, to provide continuing education for the health care team.

This activity was planned by and for the healthcare team, and learners will receive .5 Interprofessional Continuing Education credit for learning and change.

 The CMSC designates this journal-based activity for a maximum of .5 

. Physicians should claim only the credit commensurate with the extent of their participation in the activity.

 The CMSC designates this enduring material for .5 contact hour of nursing continuing professional development (none in the area of pharmacology).

 This knowledge-based activity (UAN JA4008165-9999-22-033-H01-P) qualifies for (.5) contact hour (.05 CEUs) of continuing pharmacy education credit.

 This activity is awarded 0.5 CE credits.

 As a jointly accredited organization, the CMSC is approved to offer social work continuing education by the Association of Social Work Boards Approved Continuing Education program. Organizations, not individual courses, are approved under this program. State and provincial regulatory boards have the final authority to determine whether an individual course may be accepted for continuing education credit. The CMSC maintains responsibility for this course. Social workers completing this course receive .5 continuing education credits.

 It is the policy of the Consortium of Multiple Sclerosis Centers to mitigate all relevant financial disclosures from planners, faculty, and other persons that can affect the content of this CE activity. For this activity, all relevant disclosures have been mitigated.

, has served as physician planner for this activity. He has disclosed no relevant relationships. 

, has disclosed no relevant relationships. Authors 

 have disclosed no relevant financial relationships.

, CMSC, and Intellisphere, LLC who are in a position to influence content have disclosed no relevant financial relationships. 

 CMSC continuing education director, has served as a planner and reviewer for this activity. She has disclosed no relevant financial relationships.

Release Date: November 1, 2022; Valid for Credit through: November 1, 2023.

In order to receive CE credit, participants must:

1) Review the continuing education information, including learning objectives and author disclosures.

3) Complete the evaluation, which is available at 

Statements of Credit are awarded upon successful completion of the evaluation. There is no fee to participate in this activity.

 This educational activity may contain discussion of published and/or investigational uses of agents that are not approved by the FDA. The CMSC and Intellisphere, LLC do not recommend the use of any agent outside of the labeled indications. The opinions expressed in the educational activity are those of the faculty and do not necessarily represent the views of the CMSC or Intellisphere, LLC.

 Participants have an implied responsibility to use the newly acquired information to enhance patient outcomes and their own professional development. The information presented in this activity is not meant to serve as a guideline for patient management. Any medications, diagnostic procedures, or treatments discussed in this publication should not be used by clinicians or other health care professionals without first evaluating their patients’ conditions, considering possible contraindications or risks, reviewing any applicable manufacturer’s product information, and comparing any therapeutic approach with the recommendations of other authorities.

The electronic medical record (EMR) has revolutionized health care workflow and delivery. It has evolved from a clinical adjunct to a multifaceted tool, with uses relevant to patient care and research.

A MEDLINE literature review was conducted to identify data regarding the use of EMR for multiple sclerosis (MS) clinical care and research.

Of 282 relevant articles identified, 29 were included. A variety of EMR integrated platforms with features specific to MS have been designed, with options for documenting disease course, disability status, and treatment. Research efforts have focused on early diagnosis identification, relapse prediction, and surrogates for disability status.

The available platforms and associated research support the utility of harnessing EMR for MS care. The adoption of a core set of discrete EMR elements should be considered to support future research efforts and the ability to harmonize data across institutions.

From the Mellen Center for Multiple Sclerosis Treatment and Research, Cleveland Clinic, Cleveland, OH, USA (CS, MM); and the UCSF Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA (RB). 

: Marisa McGinley, DO, MSc, Mellen Center U-10, Cleveland Clinic, 9500 Euclid Ave, Cleveland, OH 44195; 

 Dr Bove is a recipient of the National Multiple Sclerosis Society Harry Weaver Award; has received research support from the National Multiple Sclerosis Society, the Hilton Foundation, the California Initiative to Advance Precision Medicine, the Sherak Foundation, Akili Interactive, and Roche Genentech; and has received personal compensation for consulting from Alexion, Biogen, EMD Serono, Novartis, Pear Therapeutics, Roche Genentech, and Sanofi. Dr McGinley has served on scientific advisory boards for EMD Serono, Genzyme, and Genentech; consulted for Octave; received research funding from Novartis and Biogen; and receives funding via a KL2 grant (KL2TR002547) from the Clinical and Translational Science Collaborative of Cleveland via the National Center for Advancing Translational Sciences component of the National Institutes of Health. Dr Swetlik declares no conflicts of interest.

The electronic medical record (EMR) has changed how information is documented and consumed in all facets of health care. It was originally created for clinical billing, but over time EMR has been refined and is now in daily use, as well as being used in subspecialties and research. An EMR is an electronic version of the medical chart that contains information about a patient’s health and condition but often does not transfer between clinicians or health systems. In comparison, an electronic health record is broader, typically viewed and used across multiple providers, with complete information regarding all the patient’s medical conditions and health status. In multiple sclerosis (MS) care, EMR tools have become increasingly available, with provider- and patient-reported information readily collected and used for clinical and research applications. In a 2016 survey, 91% of neurology clinicians welcomed the opportunity for MS-specific documentation, and a similar proportion showed interest in extended and interconnected electronic documentation for patients with MS.

 Platforms specific to MS facilitate patient engagement through patient-reported outcomes and data visualization tools that share relevant health care information. In addition to aiding clinical care, EMR facilitates research studies when data entry is accurate, consistent, and comprehensive. These high-quality data regarding patient clinical status, symptoms, and quality of life capture longitudinal information that may aid in early diagnosis, monitor response to treatment, anticipate risk of relapse, and identify patients for clinical trial participation.

 However, clear and current characterization of available tools and their effect on clinical care and research efforts has not been described. This review highlights available EMR tools, their current use in clinical care, and how they may improve our characterization and understanding of MS.

Ovid MEDLINE was searched for articles from inception to April 27, 2022. Keywords and Medical Subject Headings (MeSH) related to MS, EMR, and point-of-care tools were used in combination to search for articles (

, available online at IJMSC.org). Additional articles were identified by the authors based on their knowledge of and review of citations in retrieved articles.

The inclusion criteria for the narrative review included description of the data entry tools for the EMR, applications of these tools, and the clinical impact of these tools to evaluate characteristics of patients with MS, including diagnosis, progression, relapse, disability, and comorbidities. Papers were abstracted into a standardized spreadsheet with title, citation, authors, and abstract included. Review of this information was performed independently by 2 authors (C.S. and M.M.). Authors abstracted agreement for inclusion independently, and overlapping articles were included in the final narrative review. Abstracts without full-length accompanying articles were excluded.

Of 282 articles identified, 29 were included that reported prospective validation studies of EMR tools, large observational studies, and/or review articles discussing the use of real-world EMR data.

Standardized Data Entry Tools for the EMR  

An early innovation in standardized data entry tools was the creation of a nationwide, EMR-embedded MS-based registry associated with a national health care system (Department of Veterans Affairs [VA]). The VA MS Surveillance Registry (MSSR) is one of the oldest EMR-based cohorts, comprising patients who have been followed since the mid-1990s.

Newer EMR tools have since been designed, including the Cleveland Clinic’s Multiple Sclerosis Performance Test (MSPT). The MSPT is a tablet-based battery of patient-reported outcomes and performance tests, including walking speed, manual dexterity, processing speed, and contrast sensitivity.

 The MSPT interfaces with a secure, cloud-based system to allow for integration into the EMR. This interface consists of an application programming interface that conforms to Health Level 7 standards using Fast Healthcare Interoperability Resources and Clinical Document Architecture standards. This type of application programming interface uses encryption (ie, AES-256) to allow for bidirectional communication between the MSPT device and the EMR.

 This allows the data to instantaneously integrate with the EMR and be inserted into note templates to allow for real-time utilization for all office visits (

). High rates of patient completion overall have been noted, particularly among younger patients and patients with less severe disability.

 In addition, the integration of this technology facilitates more consistent data capture of neuroperformance tests and patient-reported outcomes, as completion rates in all testing domains increased after MSPT implementation compared with before MSPT implementation.

 After MSPT implementation, follow-up patient completion rates increased significantly over time, from 13.9% of patients completing the MSPT in December 2015 to 77.2% completing in May 2018 (

 < .001), with an increase in completion of walking and manual dexterity measures in particular. The MSPT is used at all Cleveland Clinic MS outpatient clinical encounters.

The NorthShore Health System in the Chicago (Illinois) area designed a tool kit that includes measures to assess anxiety, disability, fatigue, motor function, and cognition.

 In addition to disease-specific data entry, note generation can also be customized. Clinical practice is streamlined through discrete data entry for progress notes rather than free text. In addition, clinicians receive notifications for quality improvement based on collected data. For example, entering a patient who screens positive for symptoms of depression or anxiety will generate an alert to address these symptoms through medication, specialist referral, or deferring. Early evaluation confirms overall high tool kit use by physicians and overall little missing data.

The MS NeuroShare platform at Sutter Health in Northern California is another example of a dual-facing platform, viewable to clinician and patient, that displays a patient’s data relevant to MS in the EMR.

 Simple displays, such as laboratory values, were found to be used more than those that required additional entered information, such as the Timed 25-Foot Walk test (T25FW).

Research Applications of EMR-Based Tools 

The creation of a “learning health system” has been proposed to facilitate research efforts beyond individual clinical care. An example of a learning health system in MS is the MS PATHS network.

 Composed of 10 health care institutions under a shared governance model, each institution contributes data captured during routine clinical care, including patient-completed measures from the MSPT, quantitative imaging measures based on brain magnetic resonance imaging, and DNA, RNA, and serum biobanking.

Studies comparing patients with MS identified in the EMR compared with gold standard research data have been conducted and show that patients with MS can be accurately identified via EMR-based searches.

 A recent validation study compared 4142 patients with MS with 323 research patients who also received clinical care at the University of California San Francisco to assess concordance with disability measures, including the Expanded Disability Status Scale (EDSS), T25FW, and disease subtype. The data captured in the clinical chart generally matched research data.

Recent efforts have focused on characterizing the prevalence and incidence of MS on a national level. Algorithms to accurately identify MS in administrative health care data sets have been developed using 

International Classification of Diseases, Ninth (ICD-9)

 codes and MS disease-modifying therapy (DMT) use within 1 year.

 These algorithms were applied, with physician-adjudicated MS cases as the reference standard, to generate an estimated 2010 prevalence of MS in the US adult population, accumulated over 10 years, of 309.2 per 100,000, with more than 700,000 cases of MS in the United States.

In EMR-based investigations, a prodromal phase before diagnosis of suspected MS-related symptoms has been proposed, particularly in patients with relapsing-remitting MS. In a retrospective, multicenter study, a mean of 3.14 health care contacts per patient per year were found, with a median of 6 prescriptions and 6 ancillary tests in the 5 years before MS diagnosis. Although a comparable age-matched control cohort was not available, back pain, myalgias, joint pain, gastrointestinal symptoms, sensory symptoms, and psychiatric symptoms were all found to present in the 5 years before a classical demyelinating event and subsequent MS diagnosis.

 Similarly, natural language processing (NLP) tools have been explored in smaller studies attempting to use computerized programs to identify and mine clinician-entered narrative signs and symptoms in the chart in an effort to diagnosis MS.

 Based on NLP, as many as 40% of patients with MS could be correctly identified as such before entrance of an 

 code in their chart. Challenges arose in discriminating MS from other known neurologic disorders, including stroke, neuropathy, or migraines, as 90% of patients flagged for potential MS were found to have an alternative diagnosis based on a gold standard 

 code comparator, creating a posttest probability of 10%.

Data from the EMR have been imbedded into the Scalable Precision Medicine Oriented Knowledge Engine (SPOKE) to obtain high-dimensional health status profiles and identify individuals at risk for MS.

 A knowledge graph that uses 16 nodes of more than 3 million types, SPOKE considers biological mechanisms in the setting of patient-specific health data analytics. High-dimensional individual health status profiles can then be obtained from SPOKE (SPOKEsigs), allowing a random forest classifier to identify individuals at risk for MS up to 5 years before their documented diagnosis based on data extracted from the University of California San Francisco EMR. Similarly, machine-based learning principles, which rely on systems learning and improving from experience without direct reprogramming, have been applied to promote early identification of approximately half of patients with MS through inclusion of highly relevant variables related to MS, with a specificity of 91.3%.

 These studies suggest that statistical modeling using EMR data has the potential to aid in the early diagnosis of MS.

Relapse activity prediction tools have also been developed to characterize disease activity. Using EMR data linked with research data from the Comprehensive Longitudinal Investigation of Multiple Sclerosis at Brigham and Women’s Hospital (CLIMB) cohort, a training set of 1435 patients was created, as well as a validation set of 186 patients with EMR-only data. In the training set, EMR-based demographic and clinical information was extracted, and NLP was applied to free-text clinical narratives, such as outpatient encounters, radiology reports, and discharge summaries. The study’s aim was to predict the future risk of relapse within 1 year using previous relapse history based on EMR data without requiring actual relapse history. Consistent with previous literature, the final model used predictors of age, disease duration, and number of relapses in the previous year, avoiding use of DMTs and imaging results, to create a parsimonious and timeless model independent of changing therapeutic strategies.

 Other clinical tools measuring severity of disability, such as the Multiple Sclerosis Severity Score (MSSS) and radiographic features such as brain parenchymal fraction (BPF), were also extracted from the EMR and compared with the research-grade CLIMB data. Training and testing data sets were used to develop a BPF algorithm, which was then tested with a validation data set. The performance of the BPF algorithm in the validation set was reduced from a mean 

 of 0.226 to 0.016 when only codified EMR variables (eg, prescriptions, demographics, and billing codes for diagnostic procedures) were included. It was reduced to 0.000760 when only EMR narrative variables from NLP (eg, symptoms, signs, medications, magnetic resonance imaging reports, and the treating neurologist’s impression) were included. Thus, neither type of EMR data alone was sufficient to produce an estimate of BPF. When the BPF algorithm included only sex, age at symptom onset, and disease duration, a mean 

 of 0.2860 was generated, suggesting that the existing EMR variables are not informative enough to be a surrogate measure of BPF. However, EMR-derived MSSS was able to differentiate patients with relapsing-remitting disease and those with progressive disease. Considering differences in sex, age at symptom onset, and disease duration, patients with primary and secondary progressive MS had a higher mean EMR-derived MSSS than those with relapsing-remitting MS on the validation set (with an observed MSSS of 4.36 compared with a derived MSSS of 3.22 for patients with progressive disease and an observed MSSS of 0.73 compared with a derived MSSS of 1.10 for patients with relapsing-remitting disease).

Surrogate measures for the EDSS have been evaluated. In a study of 1599 US-based patients, key symptom terms related to EDSS domains were mapped to EDSS scores and then searched for across the problem list and the vitals tables, including T25FW results and orders for medical equipment. A severity score was assigned to each term based on expert opinion, and 

 codes, procedural codes, and orders for durable medical equipment were mapped to 

 codes with the aim of assessing pharmacy and medical costs based on severity.

Laura M. Rees, PhD

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