Multiple Sclerosis and MyChart Messaging: A Retrospective Chart Review Evaluating Its Use

Tethered messaging systems are communication features embedded into the electronic health record that facilitate patient-provider messaging. These messaging portals enable patients to compose and send messages to their providers electronically at any time; these are then reviewed by medical assistants and answered directly or routed appropriately. One such example is the messaging feature within MyChart (Epic Systems Corporation). In this era when the burden-to-benefit ratio of tethered messaging systems for health care exchanges is still being defined, little is known about which patient factors are associated with high messaging rates in electronic health records, especially pertaining to patient populations with specific chronic diseases.

Tethered messaging systems confer well-documented benefits to both patients and health care providers: secure, accessible, and asynchronous communication; more effective care; and increased health care provider productivity.^1–4 At the same time, these messaging systems introduce unique concerns (eg, nonreimbursed increase in workload) and are naturally limited (eg, insufficient information for clinical decision-making).^1,5,6 These factors detract from optimal use and compound health care practitioner burnout.⁷

Patients with multiple sclerosis (MS) stand to benefit just as much, if not more, from the use of tethered messaging systems as other populations of patients. It has been shown that utilization rates vary by clinical setting type and location as well as by clinic specialty.^1,8,9 Most research on tethered messaging utilization patterns is in the context of family medicine or a limited subset of chronic disease–specific visits.^1,4 Although increased morbidity has been associated with higher rates of sustained use of patient portal systems, it remains unclear as to whether this holds true for patients with MS, especially because their increased morbidity may confound rates of tethered messaging utilization for reasons intrinsic to the disease course.^8,10

To clarify the relationship between chronic disease–specific variables and MyChart messaging use, we characterized factors associated with high rates of MyChart messaging in patients with MS in an academic outpatient setting.

METHODS

Patient Selection

We conducted a retrospective cross-sectional analysis of all patients in our academic MS center database (N = 439). Inclusion criteria were 1 or more documented clinic encounters and an MS diagnosis. Patients without documented clinic visits at our center and those without an MS diagnosis were excluded.

Study Site

Patients in this study were seen at our academic MS center in Tampa, Florida. The study included all MyChart messaging activity from August 2015 through August 2019. All patients consented to participation in the MS clinic database.

The University of South Florida’s institutional review board approved this study.

Data Collected

The information extracted was age, sex, time since MS diagnosis, current disease-modifying therapy (DMT), Patient-Determined Disease Steps (PDDS) scale score, total number of unique prescription medications, MyChart subscription status, time since first MyChart message, and total number of MyChart messages.

We categorized MyChart messages into 5 categories: nonurgent medical question, prescription question, test results question, visit follow-up question, and medication refill request. Included messages were all part of conversations that were patient-initiated, and each patient-authored message was included as a distinct data point. Included messages were those that occurred between provider (ie, physician, physician assistant, or advanced registered nurse practitioner) and patient. Excluded messages were those that were visit follow-up questionnaires, direct patient responses to provider-initiated questions, and patient responses consisting of “Thank you” or a variation thereof, such as “You’re the best.” We provide detailed definitions of the study variables in Table S1, which is published in the online version of this article at IJMSC.org.

Anonymized data will be shared upon qualified investigator request for purposes of replicating procedures and results.

Statistical Analysis

Data were analyzed using SAS version 9.4 (SAS Institute Inc). Descriptive statistics were used for demographic and MyChart use level data (users vs nonusers). Independent t test was used to compare the significance of the difference between groups over the specified variables. Pearson correlations were used to determine associations between characteristic variables and MyChart use levels. The significance level was set at P < .01 owing to multiple comparisons.

RESULTS

There were 439 unique patients in the database. The mean ± SD patient age was 51.4 ± 13.1 years. There were 104 male patients (24%) and 335 female patients (76%). The mean ± SD PDDS scale score was 2.0 ± 2.4. The PDDS scale score ranges from 0 to 8, with 0 being normal and 8 being bedridden. A lower score on the PDDS scale indicates less disability.¹¹ A total of 327 patients (74%) were receiving some form of DMT or other off-label medication (TABLE 1). Of the clinic total, 324 patients (74%) were subscribed to MyChart accounts and 314 (72%) had sent at least 1 message through the MyChart portal.

Basic Characteristics of the 12 Participants With MS

On average (mean ± SD), MyChart subscribers were younger (50.1 ± 12.6 vs 55.0 ± 13.7; P < .001), had lower PDDS scores (2.8 ± 2.3 vs 3.5 ± 2.5; P = .0107), and were diagnosed more recently (11.9 ± 8.3 vs 15.8 ± 10.8 years; P = .0013). There was no difference between MyChart subscribers and nonsubscribers for number of unique medications (Table 1).

MyChart users had an annual mean ± SD of 8.5 ± 10.6 messages and an annual median of 5.16 (min. 0; max. 84) messages. Based on this annual average data, the top 15% of MyChart users were sending a minimum of 1 message per week. In descending order of mean ± SD number of messages per patient, message categories were nonurgent medical questions (9.9 ± 18.2), prescription questions (4.0 ± 6.4), refill requests (2.0 ± 3.6), test results (1.8 ± 4.3), and visit follow-up questions (1.4 ± 2.4).

There was a significant difference in current DMT between MyChart users and nonusers (χ² _1,323 = 6.7; P = .009). MyChart users were more likely to be on a high-efficacy DMT (ie, alemtuzumab, natalizumab, ocrelizumab) (Table 1). Total number of MyChart messages was correlated with the total number of unique medications (R = 0.17; P = .003) and negatively correlated with age (R = −0.11; P = .018). There were no significant associations between total number of MyChart messages and PDDS scale scores or time since diagnosis (TABLE 2).

Association Between Total MyChart Messages by Disease-Specific Variables (Pearson Correlation Coefficient)

DISCUSSION

In this retrospective, observational study of MyChart messaging among a clinic cohort of patients with MS, we identified significant demographic and disease-specific differences between users and nonusers as well as demographic and disease-specific variables accounting for increased messaging rates. These findings highlight the importance of disease-specific investigation in the evaluation of tethered messaging systems.

Rates of MyChart messaging subscription at our center are similar to those of other university-based settings, with more than 70% of patients with active patient portal accounts.⁹ Multiple studies have shown that the age range of patients who use MyChart messaging tends to be 36 to 69 years but generally mirrors the patient population of the clinic.^1,6,8,11 In the present cohort, MyChart subscribers were, on average, younger than the total patient population, and messaging rates were negatively correlated with age. Although the clinical relevance of the absolute difference between these ages is likely inconsequential, as the age gap is not meaningfully large enough to account for differences in technological access or aptitude, it does suggest a general trend. In addition to being younger, those who used MyChart had lower PDDS scale scores. Previous studies assessing this at other MS centers demonstrated similar results: patients who were younger and had less disability were more likely to use an electronic messaging portal.¹⁰ Although PDDS scale scores were associated with MyChart subscription status, they were not significantly associated with messaging rates. Patients who generally tend to account for the most messages within patient portals are White and female,^1,4,8,11 although in the present population of patients with MS, there was no difference between messaging rates for male and female patients.

Total number of medications served as an additional surrogate for a patient’s overall morbidity. In the present study, as total number of medications increased, total number of MyChart messages also increased, although this did not have bearing on MyChart user status. This finding is congruent with that of a previously published study, which identified a similar variable’s relationship with overall patient portal use among patients with MS.¹⁰ This suggests that increased overall disease burden (ie, including a patient’s comorbidities) is a predictor of increased messaging rates.

MyChart users were more likely than nonusers to be receiving a high-efficacy DMT. This is consistent with what was reported by a similar study, which found higher messaging rates among those being treated with a second-line therapy compared with those on first-line therapy or no treatment.¹⁰ Unlike PDDS scale score and total number of medications, this variable is more likely a direct reflection of disease severity and an indirect reflection of disease morbidity. This variable may be influenced by the logistical implications of DMT administration, need for DMT-specific monitoring, and DMT tolerability, all of which may contribute to higher rates of messaging.

In the present cohort, most messages were categorized as nonurgent medical questions and prescription questions, and fewer messages were categorized as refill requests, test result questions, or visit follow-up questions. These findings are similar to those reported previously, in which the commonest message subjects were medication adverse effects and prescription refills or requests.¹⁰ Nonurgent medical questions likely account for the greatest number of messages because this message category is the most encompassing.

These data serve as the groundwork for potential process improvement initiatives in the outpatient clinical setting. Application of the demographic and disease-specific variables associated with MyChart subscription and increased messaging rates may enable providers and clinic staff to identify high users early on. Once identified, in-clinic measures may be constructed to mitigate the anticipated MyChart messaging utilization rate to optimize the tethered messaging system for both the patient and the health care provider. These potential in-clinic measures should be the subject of subsequent research endeavors and may include modified patient intake, health care provider checklists, and patient education. Further research would need to corroborate the effect on patient satisfaction and health care associated outcomes, health care provider time investment and burnout, overall clinic productivity, and resource optimization, such as changes in telephone call rates. Finally, as many of the pertinent outcomes we mention are unique to the epidemiology and disease course of MS, this study may also serve as the groundwork for similar investigations in other disease-specific settings.

There were several limitations to this study. The nonurgent medical questions category is broad. This makes it difficult to determine whether any specific realm of medical questioning was more likely in this population and, in turn, difficult to identify a target for intervention. In addition, the message categories did not provide a sense of whether MyChart messaging utilization is of high volume secondary to factors intrinsic to the disease process or to MyChart messaging misuse; thus, it would be helpful to determine criteria for messaging misuse. Last, this research was a single-center study; additional investigation is needed to assess for any regional differences.

CONCLUSIONS

Electronic health record systems have improved health care delivery overall, but their implementation, especially concerning secure messaging systems such as MyChart, has also presented unique challenges. This study assessed MyChart subscription status and messaging utilization at our center, showing that most of our patients use MyChart, and younger age and total number of unique prescription medications were associated with increased messaging rates. The burden-to-benefit ratio of these secure messaging systems is still being defined. Further understanding of the factors that influence MyChart use could be leveraged in many ways, including to improve patient satisfaction, health outcomes, efficiency, cost, and rates of health care provider burnout.

PRACTICE POINTS

» There is a paucity of research evaluating the use of MyChart messaging or other tethered messaging system equivalents in patients with multiple sclerosis (MS).

» Available data have associated increased morbidity with increased rates of sustained use of patient portal systems, but it remains unclear as to whether this holds true in patients with MS, especially because increased morbidity in this population may confound rates of tethered messaging utilization for reasons intrinsic to the disease course.

» Ultimately, these data could be leveraged to improve patient satisfaction, health outcomes, efficiency, cost, and rates of health care provider burnout and thus should be the subject of further research.