Internet portal use in an academic multiple sclerosis center

Abstract

Objective

To evaluate the use of a secure internet portal in an academic Multiple Sclerosis (MS) Center.

Materials and methods

Retrospective case–control chart review of 240 patients during the years 2008 and 2009. Patient demographic and clinical information was extracted from our online medical records, and portal use metrics were provided by Information Systems. Descriptive statistics were utilized to explore characteristics of portal users, how the portal is used, and what associations exist between medical resource utilization and active portal use. Logistic regression identified independent patient predictors and barriers to portal use.

Results

Portal users tended to be young professionals with minimal physical disability. The most frequently used portal feature was secure patient–physician messaging. Message content largely consisted of requests for medications or refills in addition to self-reported side effects. Independent predictors and barriers of portal use include the number of medications prescribed by our staff (OR 1.69, p<0.0001), Caucasian ethnicity (OR 5.04, p=0.007), arm and hand disability (OR 0.23, p=0.01), and impaired vision (OR 0.31, p=0.01).

Discussion

MS patients use the internet in a greater proportion than the general US population, yet physical disability limits their access. Technological adaptations such as voice-activated commands and easy font-size adjustment may help patients overcome these barriers.

Conclusion

Future research should explore the influence of portal technology on healthcare resource utilization and cost. Additional emedicine applications could be linked to the patient portal for disease monitoring and prospective investigation.

Background and significance

Multiple sclerosis (MS) is the most common chronic and disabling neurological condition affecting young adults in the Western world.¹ Widely considered a chronic inflammatory disorder of the central nervous system, patients typically experience bouts of transient neurological deficits such as loss of sensation, paralysis, and cognitive dysfunction that typically transitions to a steady accumulation of physical and cognitive disability over the ensuing decades. Due to the increasing direct and indirect medical costs related to the care of MS patients² and patient utilization of the internet for medical information,^3–5 there is an interest in internet-based patient portals.^{6 7} The typical demographic characteristics of the MS population—young, Caucasian, educated professionals—lends itself to all forms of emedicine applications. Internet portals may improve patient health and well-being by providing reliable and trusted MS-related information and resources, providing easy and reliable methods for patients to navigate an increasingly complex medical healthcare system, and providing a secure avenue for patients to communicate electronically with their MS provider regarding symptoms and disease management. A 2006 survey discovered that 93% of MS patients use the internet, compared to 75% of the general US population (N=2390).^{8 9} Three-quarters of patients surveyed indicate that they rely on the internet for disease-related health information. A focus group of MS patients at the Mellen Center, Cleveland Clinic Foundation, found that a patient portal would be invaluable, particularly if it allowed for timely communication between patients and clinicians.⁶ The literature suggests that online patient portals could address the limitations inherent to more conventional modes of physician–patient interaction: privacy concerns, wasted time engaging in ‘phone tag,’ and patient's impaired retention of information discussed at clinical encounters.⁴

PatientSite¹⁰ is a patient internet portal developed at Beth Israel Deaconess Medical Center (BIDMC) in Boston, Massachusetts, USA. In order to facilitate patient-centered electronic communication, PatientSite addresses various limitations of conventional communication by allowing individuals to manage their clinic appointments (making, canceling, or rescheduling with department administrators), request prescription refills and referrals directly to their physician's office, view their medical records including labs, pathology, and radiology study results, and communicate directly with their provider regarding non-urgent issues through a secure electronic message system. More recently, PatientSite has been updated to allow patients to upload personal health information from the portal to Google Health or Microsoft HealthVault.^{11 12} In addition, PatientSite provides web links to helpful health-related information, an account statement for patient medical bills, and technological support to portal users. An interactive demonstration of PatientSite can be viewed online.¹³ Since its implementation in 2000, 335 clinicians have enrolled in the portal, and over 50 000 patients have used this system within the past 2 years alone. As of December 2010, our MS clinic has enrolled over 1300 patients.

Although there is interest in the MS community about the implementation of patient portals, to our knowledge there are no published data on general use from an MS cohort. In 2006, Weingart et al¹⁴ published data on PatientSite utilization at BIDMC. Data represented general use of the portal from a pooled sample originating from general and specialty clinics. Due to the heterogeneity of their cohort, the findings lack external validity to our patients in the MS clinic. Our aims for the current pilot study are to determine: (1) Who uses the portal? (2) What are the patient predictors and barriers to portal use? (3) How is the portal being used? (4) Who are the prolific writers to our clinic? (5) Is there an association between portal use and medical resource utilization? Answers to these questions will assist MS providers and healthcare delivery systems to contextualize internet portal use among MS patients in addition to planning future prospective investigations.

Materials and methods

Informaticists at BIDMC randomly queried the electronic records and PatientSite for 240 patient charts from our case load at the BIDMC Multiple Sclerosis Center for this case–control retrospective chart review. Data were collected from our online medical record (OMR) during the time period of 1 January 2008 to 31 December 2009. All eligible patients had to carry a diagnosis of clinically isolated syndrome¹⁵ or multiple sclerosis,¹⁶ be at least 18 years or older, and be actively followed in our clinic during this time as evidenced by progress notes in our OMR. Cases (n=120) were defined as patients enrolled in PatientSite on or before 1 January 2008 and had utilized the portal's messaging feature at least once in the years 2008 and 2009. Controls (n=120) were identified as having never enrolled in PatientSite, or were enrolled, but did not submit a message in both years. These criteria were developed to distinguish patients who consistently used the portal in both years of the retrospective study period from those who did not. The distinction of those who adopted the portal (cases) versus those who did not (controls) was determined a priori to facilitate the logistic regression analysis for identification of patient predictors and barriers to portal use. MS Center clinicians, Allied Health Professionals, and administrative staff routinely advertised the portal to patients at clinic visits and over the telephone when they called into our offices—PatientSite is emphasized to patients as the preferred communication medium in our Center.

Information Systems at BIDMC provided PatientSite specific measures of portal use including feature access (lab and radiology result hits, appointment and prescription requests, and total log-ins). ASN extracted clinical and demographic data from the OMR, in addition to portal messaging content for categorization. Data were organized using a Microsoft Office Excel spreadsheet, and all analyses were completed in SAS version 9.2. The study protocol was approved by the Beth Israel Deaconess Committee on Clinical Investigations (CCI/IRB, Protocol # 2010-P-000147/1).

Statistical methods

To evaluate portal use in our cohort, descriptive statistics are presented for all patients who submitted at least one PatientSite message (n=154). To identify who among this cohort are the more prolific writers, the Pearson or Spearman correlation coefficient, Wilcoxon Rank Sum Test, or Kruskal–Wallis Test is utilized where appropriate. The Dunn Test is used for non-parametric pairwise inference when the Kruskal–Wallis Test is found to be statistically significant.

Case–control comparisons of clinical, demographic, and medical resource utilization data are analyzed with the Wilcoxon rank sum test, Fisher exact test, and χ² test where indicated. Additional analyses evaluating prescribing habits among our Center's physicians according to patient's psychiatric history and portal use are carried out by two-way analysis of variance. Multivariate logistic regression is used to identify patient predictors and barriers to PatientSite adoption. For all statistical tests, the p value is set at 0.05. No correction for multiple statistical comparisons was made for this pilot study, since our goal was to generate hypotheses for future investigation.

To predict the occurrence of PatientSite use in our cohort, we construct a multivariate logistic regression model. Candidate predictors are selected according to patient demographics (age, gender), socio-economic status (race, insurance type, employment status), clinical (psychiatric history, number of medical problems, number of medications prescribed by our staff, disease duration), and physical disability metrics (average 9-Hole Peg Test scores,¹⁷ average visual acuity, or logMAR score¹⁸). Potential predictors are carried forward into model building if found to be significant on univariate analysis with a p value of <0.05 (table 1). Pairwise comparisons between potential predictors are screened for collinearity. Linearity of continuous predictors is assessed prior to model building, and non-linear continuous predictors are either transformed or categorized as required to satisfy model assumptions. To avoid overfitting the model, a sample size of 120 per occurrence allows for a maximum of 12 potential predictors. Model building was accomplished by manually adding each covariate into the model according to the univariate statistical significance level. Confounders are defined as a change of ≥15% of the effect estimate. Collinear covariates are identified by a change of ≥15% of the SE, and subsequently removed from the model.

Table 1.

Univariate comparisons of candidate covariates to PatientSite use

Variable	PatientSite users (n=120)	PatientSite non-users (n=120)	p Value
No of medications prescribed by multiple sclerosis staff, mean (SD)	4.61 (±2.57)	2.49 (±2.10)	<0.0001
Log-transformed average 9-Hole Peg Test score, mean (SD)	3.00 (±0.28)	3.24 (±0.61)	0.0007
Age, n
<55 years	100	74	0.0002
≥55 years	20	46
Medical problems, n
≤3	65	70	0.6028
>3	55	50
LogMAR score (average of both eyes), n
<0.125	109	86	0.000083
≥0.125	11	34
Disease duration (years), n
<5	18	8
5–10	49	36	0.007
>10	53	76
Status of psychiatric history, n
Not active/never	78	87	0.2652
Active	42	33
Gender, n
Female	90	86	0.6617
Male	30	34
Race, n
White	115	99	0.0014
Non-white	5	21
Insurance type, n
Private	108	83	0.0000935
Public	12	37
Employment status, n
Employed	87	74	0.099
Unemployed	33	46

Results

Who uses PatientSite?

One hundred and fifty-four patients from our cohort sent at least one message via PatientSite to our clinic (table 2). In comparison to Non-users, portal users tend to be younger, Caucasian, and less disabled, and possess private insurance (table 1). The overwhelming majority of PatientSite users are employed (73%) and have private insurance (88%), suggesting relative affluence. Although all disease subtypes are represented, relapsing-remitting MS is most common with nearly two-thirds on first-line therapy and one-quarter treated with a second-line agent.

Table 2.

PatientSite cohort

	All	Clinically isolated syndrome	Relapsing-remitting multiple sclerosis	Secondary progressive multiple sclerosis	Primary progressive multiple sclerosis
Sample size, n (%)	154 (100)	12 (8)	118 (77)	17 (11)	7 (4)
Age (years)
Mean (SD)	45.4 (10.7)	49.8 (6.4)	42.9 (10.2)	54.8 (9.7)	55.7 (6.7)
Gender, n (%)
Female	113 (73)	9 (75)	90 (76)	10 (59)	4 (57)
Male	41 (27)	3 (25)	28 (24)	7 (41)	3 (43)
Race, n (%)
White	147 (95)	12 (100)	111 (94)	17 (100)	7 (100)
Non-white	7 (5)	0 (0)	7 (6)	0 (0)	0 (0)
Disease duration–years
Mean (SD)	11.9 (8.2)	5.8 (4.9)	10.7 (6.3)	21.4 (12.6)	18.6 (8.6)
Extended Disability Status Scale
Mean (SD)	2.4 (1.8)	1.8 (1.1)	1.9 (1.3)	5.3 (1.9)	5.3 (1.6)
Insurance type, n (%)
Private	136 (88)	9 (75)	109 (92.4)	13 (76.5)	5 (71.4)
Public	18 (12)	3 (25)	9 (7.6)	4 (23.5)	2 (28.6)
Disease-modifying therapy, n (%)
None	26 (16.9)	6 (50)	13 (11)	3 (17.7)	4 (57.1)
First line	87 (56.5)	5 (41.7)	73 (61.9)	8 (47)	1 (14.3)
Second line	41 (26.6)	1 (8.3)	32 (27.1)	6 (35.3)	2 (28.6)
Employment, n (%)
Employed	113 (73)	10 (83.3)	90 (76.3)	8 (47.1)	5 (71.4)
Unemployed	41 (27)	2 (16.7)	28 (23.7)	9 (52.9)	2 (28.6)

What are the patient predictors of PatientSite use?

Candidate predictors and their univariate relationship to PatientSite user status are presented in table 1. On average, portal users are younger with a shorter disease duration, white, and privately insured.

They are prescribed more medications by MS staff, have less upper-extremity disability, and have better vision. Results of the logistic regression model are presented in table 3. Independent predictors of portal use include total medications prescribed by MS staff (MSRx), white race, and less disability of upper extremity/hand function (log transformed 9-Hole Peg Test score, logHPT) and vision (logMAR).

Table 3.

Logistic regression model to predict the occurrence of PatientSite use

Covariate	Coefficient (β)	SE	Wald χ2	p Value	OR 95% CI
Intercept	1.244	1.950	–	–	–
No of medications prescribed by multiple sclerosis staff	0.524	0.086	36.97	<0.0001	1.69 (1.43 to 2.00)
Insurance type (private vs public)	0.673	0.480	1.97	0.16	1.96 (0.77 to 5.02)
Log transformed average 9-Hole Peg Test score	−1.489	0.597	6.23	0.01	0.23 (0.07 to 0.73)
Average logMAR score (≥0.125 vs <0.125)	−1.180	0.466	6.42	0.01	0.31 (0.12 to 0.77)
Age, in years (<55 vs ≥55)	−0.571	0.410	1.94	0.16	0.57 (0.25 to 1.26)
Moderate disease duration (5–10 years vs <5 years)	0.016	0.597	0.001	0.98	1.02 (0.32 to 3.28)
Longstanding disease duration (>10 years vs <5 years)	−0.222	0.592	0.14	0.71	0.80 (0.25 to 2.56)
Race (white vs non-white) (group vs reference group)	1.617	0.604	7.17	0.007	5.04 (1.54 to 16.46)

After adjusting for all covariates in the model, each additional medication prescribed by our staff conferred a 1.7-fold increased odds that a patient would be a portal user. Barriers to portal use after adjusting for all covariates include being a minority (0.2-fold odds), worse visual acuity (0.31-fold odds) and upper-extremity function (0.23-fold odds). In other words, for every log average second increase on the 9-Hole Peg Test, the patient demonstrates 0.23-fold odds of being a portal user. Worse visual acuity within our model is defined as a logMAR score of 0.125 or greater (which corresponds to 20/26.7 or worse visual acuity).

All covariates not found to be independent predictors of PatientSite use (Age, Private, DzDur1, DzDur2) were positively confounded by average upper-extremity disability (logHPT). The independent predictor logHPT changed the effect estimate of Age by 26.1%, Private by 29.1%, DzDur1 by 68.3%, and DzDur2 by 41.2%. The independent predictor Vision also positively confounded the covariate Private by altering the effect estimate of the latter by 91.2%. Noteworthy is that the covariate Age positively confounded DzDur1 as evidenced by an effect change of 46.6% and DzDur2 by 24.7%.

How is PatientSite used?

During the 2-year study period, portal users logged in a mean (25 –75% IQR) of 110.4 (30–144) times (or approximately once every 6 days). Portal features most frequently used include (mean, and 25%75% IQR) secure messaging (21.6, 4–28), laboratory (10.2, 0–9) and radiology result tabs (9.1, 0–8). Less frequently used features are the prescription request (1.6, 0–1) and the appointment request (0.28, 0–0) tabs that were used by only 54 and 26 patients, respectively. This may reflect the tendency of many patients to use the messaging feature for all activities including appointment requests and prescription refills. Although a small volume of prescription requests were sent, more than one-third of the cohort utilized this feature. As expected, the majority of portal users accessed the laboratory and radiology results tab at least once (figure 1).

Figure 1.

Proportion of cohort utilizing PatientSite features.

Portal non-users (control group) were identified as having never enrolled in PatientSite (n=86, 71.7%), or were enrolled, but did not submit a message in both years (n=34, 28.3%). Of the 34 patients who were enrolled but did not meet criteria as a portal user, the message feature was used to notify our center's providers of MS symptoms or relapse (n=9 patients), request a doctor's letter (n=5) or prescription request (n=13), request a specialty referral (n=7), inquire about research opportunities (n=2), or clarify a lab result (n=1). In addition, of these 34 patients, two utilized the labs and radiology feature. None of these patients utilized the appointment or prescription request tab.

The content of 3326 portal messages was reviewed and categorized. As a single patient message could contain information pertinent to more than one category (ie, requesting a doctor's note and detailing a psychosocial problem they are experiencing), some messages were scored in more than one category to reflect true messaging content. Patient messages regarding medication side effects and prescription refills or requests are the most frequent (n=1433) reflecting 43.1% of the portal message volume to our clinic. Less frequent message types include (count, percent message volume): MS symptoms or relapse (756, 22.7%), MS-related referral requests such as urology, ophthalmology, cognitive neurology, social work, and physical, occupational, or speech therapy (250, 7.5%), letter or doctor's note request (249, 7.5%), research (192, 5.8%), psychosocial (144, 4.3%), lab results or interpretation (125, 3.8%), radiology results or interpretation (61, 1.8%), or other (637, 19.2%). Despite the relative infrequency of these portal messages, over half of the cohort sent an MS-related multidisciplinary referral request, 42.2% sent a request for a doctor's note, and approximately one-third sent a research or laboratory-related message to our clinic (figure 2).

Figure 2.

Proportion of message volume by type.

Who are the prolific writers?

Significant (p<0.0001) and positive correlations to number of messages sent include: number of medications prescribed by MS staff (ρ=0.528), number of newly prescribed medications during the 2-year period (ρ=0.498), number of symptomatic medications prescribed (ρ=0.483), and number of clinic visits (ρ=0.425). A weak correlation exists between total messages sent and EDSS¹⁹—a measure of neurologic impairment and disability (ρ=0.169, p=0.037). Treatment with disease-modifying therapy is associated with a proclivity to message writing (p<0.0001). Patients on second-line therapies sent more messages (36.4±38.7, p<0.05) than those on first-line (17.5±23.2) or no treatment (12.1±15.5)—likely reflecting their greater disease activity or tendency to tolerate medicines poorly. Psychiatric disease is associated with prolific writing behavior (p=0.0253). Patients with active psychiatric disease send more portal messages than those without a history of disease (32.5±40.5 vs 15.5±19.0, p<0.05), while there is no statistically significant difference between those with inactive or remote disease (19.7±14.4) and those otherwise. Those not associated with prolific writing behavior include: disease duration (p=0.22), age (p=0.24), MS subtype (p=0.28), gender (p=0.25), race (p=0.77), employment status (p=0.91), and insurance type (p=0.32).

Is there an association between medical resource utilization and PatientSite use?

The number of clinic visits scheduled was greater among portal users compared to non-users (5.5±3.5 vs 3.8±2.5, p<0.0001). A trend toward a greater proportion of ‘no-shows’ to clinic was found among portal non-users (4.2%±10.7 vs 2.1%±7.3, p=0.12). There was no difference between clinic visit cancellations (p=0.93). Portal utilization also did not discern emergency department visits (p=0.99) or hospitalizations (p=0.25) for MS-related care.

Among MS-related referral visits, urology consultation was more frequent among portal non-users (0.64±2.3 vs 0.28±1.1, p=0.015). There was no difference in the distribution of referral visits between portal users and non-users for physical therapy (p=0.17), occupational therapy (p=0.16), speech therapy (p=0.57), cognitive-behavioral neurology (p=0.87), and neuro-ophthalmology (p=0.13).

Prescribing habits and medication use were more frequent among our MS staff and portal users, respectively. The total number of medications prescribed (regardless of physician specialty) was greater among portal users (9.6±6.2 vs 8.2±6.7, p=0.015). Medications prescribed by MS staff also occurred more frequently among portal users (p<0.0001): total MS medications (4.6±2.6 vs 2.5±2.1), symptomatic medications (3.6±2.5 vs 2.3±2.3), newly prescribed over the 2-year time period (2.2±1.9 vs 0.9±1.1), and intravenous high-dose steroids for confirmed MS relapse (0.6±1.0 vs 0.16±0.4). Scheduled adjuvant intravenous steroid cycles were prescribed more frequently among portal users (0.79±1.8) than among non-users (0.27±0.9), p=0.004.

We investigated the symptomatic medication prescribing habits of our center staff according to patient psychiatric history. Those with no history were prescribed (mean±SD) 2.2±2.2 medications, while patients with inactive/remote and active psychiatric disease were prescribed 3.5±2.3 and 4.0±2.5, respectively. Patients with any history of psychiatric disease, on average, were prescribed more symptomatic MS medications, p<0.0001. There was no interaction between portal user status and patient psychiatric history, p=0.18.

Discussion

Our results are the first to describe the general use of a secure patient internet portal among an MS cohort. The strongest independent predictor of portal use in our cohort is the number of medications prescribed by our staff. This is not surprising, as the most common use of the portal is patient messaging, and the most common message contains medication requests or side effects to prescribed medications. Similarly, the literature describes patient communications through social network sites regarding medication use as a common occurrence—lending evidence that patients with MS will use the internet to explore and communicate medical preferences.²⁰ This is a new insight, as a previous report of PatientSite use among those from a primary care population found that non-enrollees to the portal were more likely to take prescription medications than enrollees (OR 1.1, 95% CI 1.0 to 1.2).¹⁴

Significant physical barriers to the adoption of PatientSite among our cohort include worse vision and upper-extremity function. The contribution of visual and motor dysfunction in MS to the avoidance of computer use was identified by a focus group previously.⁶ Technological adaptations, such as a feature to easily adjust font size and voice commands to circumvent difficulty manipulating a computer mouse and keyboard, should help overcome these barriers for our patients. In addition to physical disability barriers, minority status also is negatively related to portal use. Although only 11% of the cumulative cohort is a minority, a paltry 19% of the minority population met our criteria for PatientSite user status. Even though the minority population in our clinic is under-represented in our portal user cohort, socio-economic status (defined as race, employment, and insurance type) did not influence how the most popular feature of the portal (patient-to-physician messaging) is used once a patient has logged into the system—suggesting the problem is in portal access. Racial disparities at play here may be lack of a personal computer, access to the internet, or privacy at public access locations such as the library. Future studies should aim to identify the barriers to portal use for this population.

Overall, medical resources were utilized similarly between portal users and non-users over the 2-year study period. The greater use of medications in addition to clinic visits for the portal user group likely reflects patients who are younger with earlier and more active disease. Supportive evidence for this assertion is the acknowledgment that urological dysfunction in MS tends to be a later sign of neurological dysfunction²¹ and that urological consultation is more common among portal non-users. In addition, MS relapses are more frequent earlier in the disease course,²² and these data reveal that intravenous methylprednisolone was prescribed for a confirmed MS relapse 3.75 times more frequently in portal users than non-users.

Similarities between PatientSite users from our MS cohort and the previously published primary care cohort by Weingart et al¹⁴ include frequent use of the messaging, laboratory and radiology tab features. Unlike the primary care cohort, our results demonstrate preferential medical resource utilization among portal users compared to non-users. This is apparent by more clinic visits and prescribed medications among portal users in our cohort. While there are more hospitalizations on average among portal non-users in Weingart et al's¹⁴ cohort, our analysis demonstrates no difference in hospitalizations between users and non-users. These observations are likely due to differing disease characteristics between portal users and non-users that govern the need for hospitalizations, and our more homogeneous MS population. The similarities in PatientSite use between these two studies may simply reflect idiosyncratic characteristics of the portal or may validate a common assignment of value by patients for the messaging, laboratory, and radiology tab features.

Our analysis, demonstrating that patients with a history of psychiatric disease are prescribed more symptomatic MS medications, is concerning—particularly in light of no demonstrable interaction with portal user status. These findings may indicate that our staff prescribes medications ‘sight unseen’ more frequently for these patients than those without psychiatric history. As this is a retrospective cross-sectional study, we are not able to test this hypothesis directly. Such findings may also represent an association of increased prescribing for these patients in the clinics, with subsequent communication regarding the medication and side effects via PatientSite. From a broader perspective, an important question raised by the increased medication prescribing to portal users is whether selective use of an internet portal in a chronic-disease population requiring expert multidisciplinary management facilitates and possibly accentuates the use of drugs in situations where counseling, education, or non-pharmacological management may be more appropriate. Future prospective study of portal utilization by physician and patient should test this hypothesis in order to establish appropriate limits for portal use.

Our retrospective chart review has several limitations. First, our sample size is small and may not capture all the behaviors and attitudes of patients within our clinic. Moreover, our patient population reflects that of an academic tertiary referral center largely from Massachusetts which has mandated, near universal health insurance coverage²³ and, therefore, may not be generalizable to other MS Centers or neurology practices. Our patient population at an academic tertiary referral center may over-represent complex patients requiring advanced multidisciplinary care in contrast to that provided through a general neurology practice—which may influence how the portal is used by patient and physician in these different settings. While possession of health insurance is likely a surrogate marker of socio-economic status, every patient in our cohort was insured. Despite this peculiarity of our cohort compared to other patient populations within the US where healthcare is not mandated, socio-economic status can be inferred in our sample through stratifying private versus public insurance. Although portal users were largely privately insured, whereas a comparatively larger proportion of non-users were publically insured (table 1), patient insurance type was not found to be an independent predictor of portal use (table 3). Our intent for this pilot study is to describe PatientSite use among our MS cohort and generate hypotheses to test with future prospective investigations.

Conclusion

A larger proportion of patients with MS use the internet compared to the general US adult population.⁹ Over the past decade, there has been increasing interest within the MS community for internet portals that allow patients to access electronic medical records, search trusted resources of multiple sclerosis information, and communicate directly and in a timely manner with their physician. While PatientSite addresses these interests, our pilot study identified areas where further research is needed, including identifying barriers to portal access among disadvantaged populations and the influence of a patient's psychiatric history on prescribing habits among physicians.

Future directions for portal research should investigate the influence of this technology on healthcare resource utilization and cost. Moreover, future investigation should leverage current interest in e-homecare monitoring services²⁴ and patient-reported outcomes research.²⁵ Recently, the Mellen Center published on the feasibility of conducting a prospective randomized controlled trial where patient self-management tools were linked to the electronic personal health record.²⁶ In June 2009, Biogen Idec and Elan Corporation announced the launch of mymshealth.org, a patient-reported outcomes research program that is currently being piloted among natalizumab-treated individuals with MS.^{27 28} This project allows patients to complete self-assessment surveys on the internet over time and track validated quality of life metrics. Integration of PatientSite with a feature that follows various aspects of the disease course from the patient's perspective has value to physicians from a disease-management standpoint. In addition, patients may derive substantial benefit by becoming more engaged in monitoring their chronic disease and discussing this with their physician.²⁹