Evaluation of Rheumatoid Arthritis Outcome Measures between Users and Non-Users of the Patient Portal
Main Article Content
Abstract
Introduction
Patient engagement has become a growing focus in healthcare, catalyzed with the passage of the HITECH Act in 2009. Stage 2 of Meaningful Use has criteria dependent on a patient portal, however whether electronic patient engagement translates into better clinical outcomes is yet to be determined. To begin an evaluation into this we reviewed outcomes in rheumatoid arthritis patients who had signed up for the patient portal compared to those who did not.
Methods
Data was obtained from a retrospective chart review of rheumatoid patients seen at the Ohio State University Rheumatology Clinics. Outcome measures including the most recent sedimentation rate (ESR), Rapid 3, and swollen joint count were evaluated. Two tailed t tests for these outcomes were done between each the group who had signed up for the patient portal and those that did not.
Results
132 patients were included with 66 having signed up for the patient portal (Users) and 66 not signed up for the patient portal (Non-users). 103 (78.0%) of patients were female, with a mean age of 55 ±13.79 years. Outcome measures between the patients who signed up for the patient portal compared to those who had not 14.77 ±7.57 compared to 13.48 ±7.73 (p=0.33) for Rapid 3 scores, 1.97 ±2.25 compared to 2.86 ±4.06 (p=0.16) for swollen joint count, and 39.88 ±29.76 mm/hour compared to 30.61 ±22.04 mm/hour (p=0.04) for ESR.
Conclusions
This initial study cohort does not demonstrate any clinically significant difference in several key outcome measures in rheumatoid arthritis, particularly Rapid 3 scores and swollen joint counts. However there was a statistical difference between the ESR, with more favorable values in patients using the patient portal. This data suggests further study is needed to better understand if electronic patient engagement does have an effect on clinical outcomes in RA.
Keywords:
rheumatoid arthritis, electronic health record, patient portal
Article Details
How to Cite
MASCARENHAS, Sheryl; ROY, Shuvro.
Evaluation of Rheumatoid Arthritis Outcome Measures between Users and Non-Users of the Patient Portal.
Medical Research Archives, [S.l.], v. 8, n. 5, may 2020.
ISSN 2375-1924.
Available at: <https://esmed.org/MRA/mra/article/view/2117>. Date accessed: 17 nov. 2024.
doi: https://doi.org/10.18103/mra.v8i5.2117.
Section
Research Articles
The Medical Research Archives grants authors the right to publish and reproduce the unrevised contribution in whole or in part at any time and in any form for any scholarly non-commercial purpose with the condition that all publications of the contribution include a full citation to the journal as published by the Medical Research Archives.
References
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24. Prevoo ML, van’t Hof MA, Kuper HH et al. Modified disease activity scores that include twenty-eight-joint counts. Development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum1995;38:44–8.
25. Vander Cruyssen B, Van Looy S, Wyns B, et al. DAS28 best reflects the physician’s clinical judgment of response to infliximab therapy in rheumatoid arthritis patients: validation of the DAS28 score in patients under infliximab treatment. Arthritis Res Ther2005;7:R1063–71.
26. Smolen JS, Breedveld FC, Schiff MH, et al. A simplified disease activity index for rheumatoid arthritis for use in clinical practice. Rheumatology (Oxford) 2003 Feb;42(2):244-57.
27. Pincus T, Yazici Y, Bergman MJ. RAPID3, an index to assess and monitor patients with rheumatoid arthritis, without formal joint counts: similar results to DAS28 and CDAI in clinical trials and clinical care. Rheum Dis Clin North Am 2009 Nov;35(4):773-8.
28. Kvien TK, Uhlig T, Ødegård S, et al. Epidemiological aspects of rheumatoid arthritis: the sex ratio. Ann N Y Acad Sci. 2006 Jun;1069:212-22.
29. Ronald F van Vollenhoven. Sex differences in rheumatoid arthritis: more than meets the eye... BMC Med 2009; 7: 12.
30. Turner AM, Osterhage KP, Taylor JO, et al. A closer look at health information seeking by older adults and involved family and friends: Design considerations for health information technologies. AMIA Annu Symp Proc 2018; 2018: 1036–1045.
31. Vaportzis E, Giatsi Clausen M, and Gow AJ. Older Adults Perceptions of Technology and Barriers to Interacting with Tablet Computers: A Focus Group Study. Front Psychol 2017; 8: 1687.
32. Choi NG, DiNitto DM. Internet Use Among Older Adults: Association With Health Needs, Psychological Capital, and Social Capital. J Med Internet Res 2013 May; 15(5): e97.
33. Korupp SE, Szydlik M. Causes and trends of the digital divide. Eur Sociol Rev. 2005 Jun 06;21(4):409–422.
34. Choi NG, Dinitto DM. The digital divide among low-income homebound older adults: Internet use patterns, eHealth literacy, and attitudes toward computer/Internet use. J Med Internet Res. 2013 May;15(5):e93.
35. Chiu CJ, Liu CW. Understanding Older Adult's Technology Adoption and Withdrawal for Elderly Care and Education: Mixed Method Analysis from National Survey. J Med Internet Res 2017 Nov; 19(11): e374.
36. Zickuhr K. Pew Research Center; Generations 2010. Dec 16, 2010. Available from: http://pewinternet.org/Reports/2010/Generations-2010.aspx.[Accessed February 29, 2020].
37. Fischer SH, David D, Crotty BH, et al. Acceptance and use of health information technology By community-dwelling elders. Int J Med Inform 2014 Sep; 83(9): 624–635.
38. Choi NG, Dinitto DM. The digital divide among low-income homebound older adults: Internet use patterns, eHealth literacy, and attitudes toward computer/Internet use. J Med Internet Res 2013 May;15(5):e93.
39. Korupp SE, Szydlik M. Causes and trends of the digital divide. Eur Sociol Re. 2005 Jun 06;21(4):409–422.
40. Dumitrascu AG, Burton MC, Dawson NL, et al. Patient portal use and hospital outcomes. J Am Med Inform Assoc. 2018 Apr 1;25(4):447-453.
41. Shearn MA, Kang IY. Effect of age and sex on the erythrocyte sedimentation rate. J Rheumatol 1986;13:297–298.
42. Nestel AR. ESR changes with age - a forgotten pearl. BMJ. 2012;344:e1403.
43. Miller A, Green M, Robinson D. Simple rule for calculating normal erythrocyte sedimentation rate. Br Med J (Clin Res Ed) 1983;286:266.
44. Oeser A, Chung CP, Asanuma Y, et al. Obesity is an independent contributor to functional capacity and inflammation in systemic lupus erythematosus. Arthritis Rheum 2005;52:3651–3659.
45. Restrepo JF, del Rincón I, Battafarano DF, et al. Clinical and laboratory factors associated with interstitial lung disease in rheumatoid arthritis. Clin Rheumatol 2015 Sep;34(9):1529-36.
46. Daniels LM, Tosh PK, Fiala JA, et al. Extremely elevated erythrocyte sedimentation rates: Associations with patients' diagnoses, demographic characteristics, and comorbidities. Mayo Clin Proc 2017 Nov;92(11):1636-1643.
47. Innala L, Sjöberg C, Möller B, et al. Co-morbidity in patients with early rheumatoid arthritis - inflammation matters. Arthritis Res Ther. 2016; 18: 33.
48. Centers for Disease Control and Prevention. November 12, 2019. Available from: https://www.cdc.gov/healthliteracy/learn/UnderstandingLiteracy.html [Accessed April 2020].
49. Jhamb M, Cavanaugh KL, Bian A, et al. Disparities in electronic health record patient portal use in nephrology clinics. Clin J Am Soc Nephrol. 2015 Nov 6;10(11):2013–22.
50. Milani RV, Lavie CJ, Bober RM, et al. Improving hypertension control and patient engagement using digital tools. Am J Med. 2017 Jan;130(1):14–20.
51. Toscos T, Daley C, Heral L, Doshi R, et al. Impact of electronic personal health record use on engagement and intermediate health outcomes among cardiac patients: a quasi-experimental study. J Am Med Inform Assoc. 2016 Jan;23(1):119–28.
52. Wagner P, Dias J, Howard S, et al. Personal health records and hypertension control: a randomized trial. J Am Med Inform Assoc. 2012;19(4):626–34.
53. Tang P, Overhage JM, Chan AS, et al. Online disease management of diabetes: engaging and motivating patients online with enhanced resources-diabetes (EMPOWER-D), a randomized controlled trial. J Am Med Inform Assoc. 2013 May 1;20(3):526–34.
54. Lim SS, Conn DL. The use of low-dose prednisone in the management of rheumatoid arthritis. Bull Rheum Dis 2001;50(12):1-4.
55. Paolino S, Cutolo M, and Pizzorni C. Glucocorticoid management in rheumatoid arthritis: morning or night low dose? Reumatologia 2017; 55(4): 189–197.
56. Beltrametti SP, Ianniello A, Ricci C, Chronotherapy with low-dose modified-release prednisone for the management of rheumatoid arthritis: a review. Ther Clin Risk Manag 2016; 12: 1763–1776.
57. Osborn CY, Satterwhite Mayberry L, Wallston KA, et al. Understanding Patient Portal Use: Implications for Medication Management. J Med Internet Res. 2013 Jul; 15(7): e133.
2. Henricks WH. “Meaningful use” of electronic health records and its relevance to laboratories and pathologists. J Pathol Inform 2011;2:7.
3. The Office of the National Coordinator for Health Information. Health information technology for economic Clinical health act United States code 42. 2009. HITECH Act Available from: https://www.healthit.gov/sites/default/files/hitech_act_excerpt_from_arra_with_index.pdf [Accessed February 22, 2020]
4. Angst CM, Agarwal R. Adoption of electronic health records in the presence of privacy concerns: The elaboration likelihood model and individual persuasion. MIS Q 2009;33(2):339–370.
5. Wright A, Feblowitz J, Samal L, et al. The medicare electronic health record incentive program: Provider performance on core and menu measures. Health Services Research 2014;49:325–346.
6. Yu PP. Why Meaningful Use Matters. J Oncol Pract 2011 Jul;7(4):206–209.
7. Department of Health and Human Services. 45 CFR Part 170. Health Information Technology: Initial Set of Standards, Implementation Specifications, and Certification Criteria for Electronic Health Record Technology; Final Rule; July 28, 2010. Available from: http://edocket.access.gpo.gov/2010/pdf/2010-17210.pdf [Accessed February 22, 2020]
8. The Office of the National Coordinator for Health Information Technology. Certified EHR Technology Definition. Oct 23, 2018. Available from: https://www.healthit.gov/topic/certification-ehrs/certified-ehr-technology-definition [Accessed February 22, 2020].
9. Centers for Disease Control. Public Health and Promoting Interoperability Programs (formerly, known as Electronic Health Records Meaningful Use). Sept 9, 2019. Available from: https://www.cdc.gov/ehrmeaningfuluse/introduction.html [Accessed February 22, 2020].
10. Center for Medicare and Medicaid Services. Stage 2 Overview Tipsheet: Last updated August 2012. Available from: https://www.cms.gov/Regulations-and-Guidance/Legislation/EHRIncentivePrograms/Downloads/Stage2Overview_Tipsheet.pdf [Accessed February 22, 2020].
11. Office of the National Coordinator. What is a patient portal? Aug 22, 2014. Available from: http://www.healthit.gov/providers-professionals/faqs/what-patient-portal. [Accessed February 22, 2020].
12. Weingart SN, Rind D, Tofias Z, et al. Who uses the patient internet portal? The patient site experience. J Am Med Inform Assoc 2006;13(1):91–95.
13. Ancker JS, Barrón Y, Rockoff ML, et al. Use of an electronic patient portal among disadvantaged populations. J Gen Intern Med 2011 Oct;26(10):1117–1123.
14. Centers for Medicare and Medicaid Services, Department of Health and Human Services. 42 CFR Parts 412, 413, 422 et al. Medicare and Medicaid Programs; Electronic Health Record Incentive Program; Final Rule; July 28, 2010. Available from: http://edocket.access.gpo.gov/2010/pdf/2010-17207.pdf [Accessed February 29, 2020]
15. Centers for Medicare and Medicaid Services. Stage 2 Eligible Professional Meaningful Use Core and Menu Measures. February 2013. Available from: http://www.cms.gov/Regulations-andGuidance/Legislation/EHRIncentivePrograms/Downloads/Stage2_MeaningfulUseSpecSheet_TableContents_EPs.pdf [Accessed February 29, 2020].
16. Tuil WS, Verhaak CM, Braat DD, et al. Empowering patients undergoing in vitro fertilization by providing internet access to medical data. Fertil Steril 2007 Aug;88(2):361-8. Epub 2007 Apr 9.
17. Earnest MA, Ross SE, Wittevrongel L, et al. Use of a patient-accessible electronic medical record in a practice for congestive heart failure: patient and physician experiences. J Am Med Inform Assoc 2004 Sep-Oct;11(5):410-7. Epub 2004 Jun 7.
18. Bodenheimer T, Lorig K, Holman H, et al. Patient self-management of chronic disease in primary care. JAMA 2002 Nov 20;288(19):2469-75.
19. Ammenwerth E, Schnell-Inderst P, Hoerbst A. The Impact of Electronic Patient Portals on Patient Care: A Systematic Review of Controlled Trials J Med Internet Res 2012 Nov-Dec; 14(6): e162.
20. Grant RW, Wald JS, Schnipper JL, et al. Practice-linked online personal health records for type 2 diabetes mellitus: a randomized controlled trial. Arch Intern Med. 2008 Sep 8;168(16):1776-82.
21. Ross SE, Moore LA, Earnest MA, Wittevrongel L, Lin CT. Providing a web-based online medical record with electronic communication capabilities to patients with congestive heart failure: randomized trial. J Med Internet Res 2004 May 14;6(2):e12.
22. Rigby WFC, Lampl K, Low JM, et al. Review of Routine Laboratory Monitoring for Patients with Rheumatoid Arthritis Receiving Biologic or Nonbiologic DMARDs. Int J Rheumatol 2017; 2017: 9614241.
23. Inoue E, Yamanaka H, Hara M, et al. Comparison of Disease Activity Score (DAS)28- erythrocyte sedimentation rate and DAS28- C-reactive protein threshold values. Ann Rheum Dis. 2007 Mar;66(3):407-9. Epub 2006 Aug 22.
24. Prevoo ML, van’t Hof MA, Kuper HH et al. Modified disease activity scores that include twenty-eight-joint counts. Development and validation in a prospective longitudinal study of patients with rheumatoid arthritis. Arthritis Rheum1995;38:44–8.
25. Vander Cruyssen B, Van Looy S, Wyns B, et al. DAS28 best reflects the physician’s clinical judgment of response to infliximab therapy in rheumatoid arthritis patients: validation of the DAS28 score in patients under infliximab treatment. Arthritis Res Ther2005;7:R1063–71.
26. Smolen JS, Breedveld FC, Schiff MH, et al. A simplified disease activity index for rheumatoid arthritis for use in clinical practice. Rheumatology (Oxford) 2003 Feb;42(2):244-57.
27. Pincus T, Yazici Y, Bergman MJ. RAPID3, an index to assess and monitor patients with rheumatoid arthritis, without formal joint counts: similar results to DAS28 and CDAI in clinical trials and clinical care. Rheum Dis Clin North Am 2009 Nov;35(4):773-8.
28. Kvien TK, Uhlig T, Ødegård S, et al. Epidemiological aspects of rheumatoid arthritis: the sex ratio. Ann N Y Acad Sci. 2006 Jun;1069:212-22.
29. Ronald F van Vollenhoven. Sex differences in rheumatoid arthritis: more than meets the eye... BMC Med 2009; 7: 12.
30. Turner AM, Osterhage KP, Taylor JO, et al. A closer look at health information seeking by older adults and involved family and friends: Design considerations for health information technologies. AMIA Annu Symp Proc 2018; 2018: 1036–1045.
31. Vaportzis E, Giatsi Clausen M, and Gow AJ. Older Adults Perceptions of Technology and Barriers to Interacting with Tablet Computers: A Focus Group Study. Front Psychol 2017; 8: 1687.
32. Choi NG, DiNitto DM. Internet Use Among Older Adults: Association With Health Needs, Psychological Capital, and Social Capital. J Med Internet Res 2013 May; 15(5): e97.
33. Korupp SE, Szydlik M. Causes and trends of the digital divide. Eur Sociol Rev. 2005 Jun 06;21(4):409–422.
34. Choi NG, Dinitto DM. The digital divide among low-income homebound older adults: Internet use patterns, eHealth literacy, and attitudes toward computer/Internet use. J Med Internet Res. 2013 May;15(5):e93.
35. Chiu CJ, Liu CW. Understanding Older Adult's Technology Adoption and Withdrawal for Elderly Care and Education: Mixed Method Analysis from National Survey. J Med Internet Res 2017 Nov; 19(11): e374.
36. Zickuhr K. Pew Research Center; Generations 2010. Dec 16, 2010. Available from: http://pewinternet.org/Reports/2010/Generations-2010.aspx.[Accessed February 29, 2020].
37. Fischer SH, David D, Crotty BH, et al. Acceptance and use of health information technology By community-dwelling elders. Int J Med Inform 2014 Sep; 83(9): 624–635.
38. Choi NG, Dinitto DM. The digital divide among low-income homebound older adults: Internet use patterns, eHealth literacy, and attitudes toward computer/Internet use. J Med Internet Res 2013 May;15(5):e93.
39. Korupp SE, Szydlik M. Causes and trends of the digital divide. Eur Sociol Re. 2005 Jun 06;21(4):409–422.
40. Dumitrascu AG, Burton MC, Dawson NL, et al. Patient portal use and hospital outcomes. J Am Med Inform Assoc. 2018 Apr 1;25(4):447-453.
41. Shearn MA, Kang IY. Effect of age and sex on the erythrocyte sedimentation rate. J Rheumatol 1986;13:297–298.
42. Nestel AR. ESR changes with age - a forgotten pearl. BMJ. 2012;344:e1403.
43. Miller A, Green M, Robinson D. Simple rule for calculating normal erythrocyte sedimentation rate. Br Med J (Clin Res Ed) 1983;286:266.
44. Oeser A, Chung CP, Asanuma Y, et al. Obesity is an independent contributor to functional capacity and inflammation in systemic lupus erythematosus. Arthritis Rheum 2005;52:3651–3659.
45. Restrepo JF, del Rincón I, Battafarano DF, et al. Clinical and laboratory factors associated with interstitial lung disease in rheumatoid arthritis. Clin Rheumatol 2015 Sep;34(9):1529-36.
46. Daniels LM, Tosh PK, Fiala JA, et al. Extremely elevated erythrocyte sedimentation rates: Associations with patients' diagnoses, demographic characteristics, and comorbidities. Mayo Clin Proc 2017 Nov;92(11):1636-1643.
47. Innala L, Sjöberg C, Möller B, et al. Co-morbidity in patients with early rheumatoid arthritis - inflammation matters. Arthritis Res Ther. 2016; 18: 33.
48. Centers for Disease Control and Prevention. November 12, 2019. Available from: https://www.cdc.gov/healthliteracy/learn/UnderstandingLiteracy.html [Accessed April 2020].
49. Jhamb M, Cavanaugh KL, Bian A, et al. Disparities in electronic health record patient portal use in nephrology clinics. Clin J Am Soc Nephrol. 2015 Nov 6;10(11):2013–22.
50. Milani RV, Lavie CJ, Bober RM, et al. Improving hypertension control and patient engagement using digital tools. Am J Med. 2017 Jan;130(1):14–20.
51. Toscos T, Daley C, Heral L, Doshi R, et al. Impact of electronic personal health record use on engagement and intermediate health outcomes among cardiac patients: a quasi-experimental study. J Am Med Inform Assoc. 2016 Jan;23(1):119–28.
52. Wagner P, Dias J, Howard S, et al. Personal health records and hypertension control: a randomized trial. J Am Med Inform Assoc. 2012;19(4):626–34.
53. Tang P, Overhage JM, Chan AS, et al. Online disease management of diabetes: engaging and motivating patients online with enhanced resources-diabetes (EMPOWER-D), a randomized controlled trial. J Am Med Inform Assoc. 2013 May 1;20(3):526–34.
54. Lim SS, Conn DL. The use of low-dose prednisone in the management of rheumatoid arthritis. Bull Rheum Dis 2001;50(12):1-4.
55. Paolino S, Cutolo M, and Pizzorni C. Glucocorticoid management in rheumatoid arthritis: morning or night low dose? Reumatologia 2017; 55(4): 189–197.
56. Beltrametti SP, Ianniello A, Ricci C, Chronotherapy with low-dose modified-release prednisone for the management of rheumatoid arthritis: a review. Ther Clin Risk Manag 2016; 12: 1763–1776.
57. Osborn CY, Satterwhite Mayberry L, Wallston KA, et al. Understanding Patient Portal Use: Implications for Medication Management. J Med Internet Res. 2013 Jul; 15(7): e133.