Amy M J O'Shea1,2, Adam Batten3,4, Elaine Y Hu5, Matthew R Augustine6, Timothy P Hogan7,8, Peter J Kaboli9,10. 1. Veterans Rural Health Resource Center-Iowa City, VA Office of Rural Health, and Center for Access and Delivery Research and Evaluation (CADRE) at the Iowa City VA Healthcare System, Iowa City, IA, USA. 2. The Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, IA, USA. 3. A/B Analytics L.L.C, San Diego, CA, USA. 4. San Francisco VA Health Care System, University of California San Francisco Department of Psychiatry, San Francisco, CA, USA. 5. Seattle Epidemiologic Research & Information Center (ERIC) | VA Cooperative Studies Program (CSP), VA Puget Sound Health Care System, Seattle, WA, USA. 6. Geriatric Research Education and Clinical Center, James J Peters VA Medical Center, Bronx, NY, USA. 7. Center for Healthcare Organization and Implementation Research, VA Bedford Healthcare System, Bedford, MA, USA. 8. Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA. 9. Veterans Rural Health Resource Center-Iowa City, VA Office of Rural Health, and Center for Access and Delivery Research and Evaluation (CADRE) at the Iowa City VA Healthcare System, Iowa City, IA, USA. peter.kaboli@va.gov. 10. The Department of Internal Medicine, University of Iowa Carver College of Medicine, Iowa City, IA, USA. peter.kaboli@va.gov.
Abstract
BACKGROUND: Secure messaging (SM) between patients and primary care teams has expanded care access but may impact other clinical encounters. OBJECTIVE: To study associations between SM use and primary care in-person and telephone visits in the Veterans Health Administration (VHA). DESIGN: The SM feature of VHA's patient portal, MyHealtheVet, supports asynchronous communication between patients and primary care teams. To study the impact of SM on in-person and telephone visits, two analyses were performed: (1) a retrospective pre-/post-analysis comparing changes after initiating SM use and (2) a difference-in-difference comparison among SM users and non-users 1 year before and after index SM use. Matching to non-users was by primary care team, demographics, and predicted propensity of SM use by Nosos comorbidity score and drive time to clinic. PATIENTS: In 2016, 154,053 Veterans initiated SM from all primary care patients (N = 5,891,893); 25,683 were propensity-matched to controls (N = 49,266) from the same primary care team not using SM. MAIN MEASURES: Primary care provider in-person visits and telephone contacts between patients and their primary care team were assessed 1 year prior and post index SM. KEY RESULTS: Overall, primary care in-person visits decreased 13.3% (p < 0.0001); telephone visits increased 13.5% (p < 0.0001). In the matched analysis, in-person primary care visits decreased by 16.0% (p < 0.0001) by SM users and 9.9% (p < 0.0001) among controls, resulting in a across-group decrease of 6.1% in-person visits after SM initiation. Telephone visits increased by 11.0% (p < 0.0001) for SM users and 4.5% for controls (p < 0.0001) resulting in an across-group increase of 6.5% telephone visits after SM initiation. CONCLUSIONS: Use of SM was associated with decreased in-person visits and increased telephone visits. This may improve clinic appointment availability, while increasing time commitments for providers for non-traditional forms of access.
BACKGROUND: Secure messaging (SM) between patients and primary care teams has expanded care access but may impact other clinical encounters. OBJECTIVE: To study associations between SM use and primary care in-person and telephone visits in the Veterans Health Administration (VHA). DESIGN: The SM feature of VHA's patient portal, MyHealtheVet, supports asynchronous communication between patients and primary care teams. To study the impact of SM on in-person and telephone visits, two analyses were performed: (1) a retrospective pre-/post-analysis comparing changes after initiating SM use and (2) a difference-in-difference comparison among SM users and non-users 1 year before and after index SM use. Matching to non-users was by primary care team, demographics, and predicted propensity of SM use by Nosos comorbidity score and drive time to clinic. PATIENTS: In 2016, 154,053 Veterans initiated SM from all primary care patients (N = 5,891,893); 25,683 were propensity-matched to controls (N = 49,266) from the same primary care team not using SM. MAIN MEASURES: Primary care provider in-person visits and telephone contacts between patients and their primary care team were assessed 1 year prior and post index SM. KEY RESULTS: Overall, primary care in-person visits decreased 13.3% (p < 0.0001); telephone visits increased 13.5% (p < 0.0001). In the matched analysis, in-person primary care visits decreased by 16.0% (p < 0.0001) by SM users and 9.9% (p < 0.0001) among controls, resulting in a across-group decrease of 6.1% in-person visits after SM initiation. Telephone visits increased by 11.0% (p < 0.0001) for SM users and 4.5% for controls (p < 0.0001) resulting in an across-group increase of 6.5% telephone visits after SM initiation. CONCLUSIONS: Use of SM was associated with decreased in-person visits and increased telephone visits. This may improve clinic appointment availability, while increasing time commitments for providers for non-traditional forms of access.
Authors: Todd H Wagner; Anjali Upadhyay; Elizabeth Cowgill; Theodore Stefos; Eileen Moran; Steven M Asch; Peter Almenoff Journal: Health Serv Res Date: 2016-02-03 Impact factor: 3.402
Authors: Tait D Shanafelt; Grace Gorringe; Ronald Menaker; Kristin A Storz; David Reeves; Steven J Buskirk; Jeff A Sloan; Stephen J Swensen Journal: Mayo Clin Proc Date: 2015-03-18 Impact factor: 7.616
Authors: Jolie N Haun; Wendy Hathaway; Margeaux Chavez; Nicole Antinori; Brian Vetter; Brian K Miller; Tracey L Martin; Lisa Kendziora; Kim M Nazi; Christine Melillo Journal: Appl Clin Inform Date: 2017-12-14 Impact factor: 2.342
Authors: Stephanie L Shimada; Timothy P Hogan; Sowmya R Rao; Jeroan J Allison; Ann L Quill; Hua Feng; Barrett D Phillips; Kim M Nazi; Susan T Haidary; Thomas K Houston Journal: Med Care Date: 2013-03 Impact factor: 2.983
Authors: Samuel T Edwards; Christian D Helfrich; David Grembowski; Elizabeth Hulen; Walter L Clinton; Gordon B Wood; Linda Kim; Danielle E Rose; Greg Stewart Journal: J Am Board Fam Med Date: 2018 Jan-Feb Impact factor: 2.657
Authors: John C Fortney; James F Burgess; Hayden B Bosworth; Brenda M Booth; Peter J Kaboli Journal: J Gen Intern Med Date: 2011-11 Impact factor: 5.128
Authors: Jolie N Haun; Jason D Lind; Stephanie L Shimada; Tracey L Martin; Robert M Gosline; Nicole Antinori; Max Stewart; Steven R Simon Journal: J Med Internet Res Date: 2014-03-06 Impact factor: 5.428
Authors: Stephanie L Shimada; Beth Ann Petrakis; James A Rothendler; Maryan Zirkle; Shibei Zhao; Hua Feng; Gemmae M Fix; Mustafa Ozkaynak; Tracey Martin; Sharon A Johnson; Bengisu Tulu; Howard S Gordon; Steven R Simon; Susan S Woods Journal: J Am Med Inform Assoc Date: 2017-09-01 Impact factor: 4.497