Mitesh S Patel1,2,3,4,5, Neha Patel6,7, Dylan S Small8, Roy Rosin9, Jeffrey I Rohrbach7, Nathaniel Stromberg7, C William Hanson6,7, David A Asch9,6,8,10,7. 1. Penn Medicine Center for Health Care Innovation, Philadelphia, PA, USA. mpatel@upenn.edu. 2. Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. mpatel@upenn.edu. 3. The Wharton School, University of Pennsylvania, Philadelphia, PA, USA. mpatel@upenn.edu. 4. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA. mpatel@upenn.edu. 5. University of Pennsylvania Health System, Philadelphia, PA, USA. mpatel@upenn.edu. 6. Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. 7. University of Pennsylvania Health System, Philadelphia, PA, USA. 8. The Wharton School, University of Pennsylvania, Philadelphia, PA, USA. 9. Penn Medicine Center for Health Care Innovation, Philadelphia, PA, USA. 10. Crescenz Veterans Affairs Medical Center, Philadelphia, PA, USA.
Abstract
BACKGROUND: Changes in the medium of communication from paging to mobile secure text messaging may change clinical care, but the effects of these changes on patient outcomes have not been well examined. OBJECTIVE: To evaluate the association between inpatient medicine service adoption of mobile secure text messaging and patient length of stay and readmissions. DESIGN: Observational study. PARTICIPANTS: Patients admitted to medicine services at the Hospital of the University of Pennsylvania (intervention site; n = 8995 admissions of 6484 patients) and Penn Presbyterian Medical Center (control site; n = 6799 admissions of 4977 patients) between May 1, 2012, and April 30, 2014. INTERVENTION: Mobile secure text messaging. MAIN MEASURES: Change in length of stay and 30-day readmissions, comparing patients at the intervention site to the control site before (May 1, 2012 to April 30, 2013) and after (May 1, 2013 to April 30, 2014) the intervention, adjusting for time trends and patient demographics, comorbidities, insurance, and disposition. KEY RESULTS: During the pre-intervention period, the mean length of stay ranged from 4.0 to 5.0 days at the control site and from 5.2 to 6.7 days at the intervention site, but trends were similar. In the first month after the intervention, the mean length of stay was unchanged at the control site (4.7 to 4.7 days) but declined at the intervention site (6.0 to 5.4 days). Trends were mostly similar during the rest of the post-intervention period, ranging from 4.4 to 5.6 days at the control site and from 5.4 to 6.5 days at the intervention site. Readmission rates varied significantly within sites before and after the intervention, but overall trends were similar. In adjusted analyses, there was a significant decrease in length of stay for the intervention site relative to the control site during the post-intervention period compared to the pre-intervention period (-0.77 days ; 95 % CI, -1.14, -0.40; P < 0.001). There was no significant difference in the odds of readmission (OR, 0.97; 95 % CI: 0.81, 1.17; P = 0.77). These findings were supported by multiple sensitivity analyses. CONCLUSIONS: Compared to a control group over time, hospitalized medical patients on inpatient services whose care providers and staff were offered mobile secure text messaging showed a relative decrease in length of stay and no change in readmissions.
BACKGROUND: Changes in the medium of communication from paging to mobile secure text messaging may change clinical care, but the effects of these changes on patient outcomes have not been well examined. OBJECTIVE: To evaluate the association between inpatient medicine service adoption of mobile secure text messaging and patient length of stay and readmissions. DESIGN: Observational study. PARTICIPANTS: Patients admitted to medicine services at the Hospital of the University of Pennsylvania (intervention site; n = 8995 admissions of 6484 patients) and Penn Presbyterian Medical Center (control site; n = 6799 admissions of 4977 patients) between May 1, 2012, and April 30, 2014. INTERVENTION: Mobile secure text messaging. MAIN MEASURES: Change in length of stay and 30-day readmissions, comparing patients at the intervention site to the control site before (May 1, 2012 to April 30, 2013) and after (May 1, 2013 to April 30, 2014) the intervention, adjusting for time trends and patient demographics, comorbidities, insurance, and disposition. KEY RESULTS: During the pre-intervention period, the mean length of stay ranged from 4.0 to 5.0 days at the control site and from 5.2 to 6.7 days at the intervention site, but trends were similar. In the first month after the intervention, the mean length of stay was unchanged at the control site (4.7 to 4.7 days) but declined at the intervention site (6.0 to 5.4 days). Trends were mostly similar during the rest of the post-intervention period, ranging from 4.4 to 5.6 days at the control site and from 5.4 to 6.5 days at the intervention site. Readmission rates varied significantly within sites before and after the intervention, but overall trends were similar. In adjusted analyses, there was a significant decrease in length of stay for the intervention site relative to the control site during the post-intervention period compared to the pre-intervention period (-0.77 days ; 95 % CI, -1.14, -0.40; P < 0.001). There was no significant difference in the odds of readmission (OR, 0.97; 95 % CI: 0.81, 1.17; P = 0.77). These findings were supported by multiple sensitivity analyses. CONCLUSIONS: Compared to a control group over time, hospitalized medical patients on inpatient services whose care providers and staff were offered mobile secure text messaging showed a relative decrease in length of stay and no change in readmissions.
Entities:
Keywords:
communication; inpatient; length of stay; medical patients; mobile secure text messaging; patient outcomes; readmissions; residents; smartphone; teaching hospital
Authors: Mitesh S Patel; Susan Day; Dylan S Small; John T Howell; Gillian L Lautenbach; Eliot H Nierman; Kevin G Volpp Journal: Ann Intern Med Date: 2014-11-18 Impact factor: 25.391
Authors: Mitesh S Patel; Kevin G Volpp; Dylan S Small; Alexander S Hill; Orit Even-Shoshan; Lisa Rosenbaum; Richard N Ross; Lisa Bellini; Jingsan Zhu; Jeffrey H Silber Journal: JAMA Date: 2014-12-10 Impact factor: 56.272
Authors: Kathlyn E Fletcher; Alexis M Visotcky; Jason M Slagle; Sergey Tarima; Matthew B Weinger; Marilyn M Schapira Journal: J Gen Intern Med Date: 2012-06-27 Impact factor: 5.128
Authors: Kim Tran; Dante Morra; Vivian Lo; Sherman D Quan; Howard Abrams; Robert C Wu Journal: J Med Internet Res Date: 2014-05-22 Impact factor: 5.428
Authors: Jennifer A Przybylo; Ange Wang; Pooja Loftus; Kambria H Evans; Isabella Chu; Lisa Shieh Journal: J Hosp Med Date: 2014-08-11 Impact factor: 2.960
Authors: Xinran Liu; Paul R Sutton; Rory McKenna; Mika N Sinanan; B Jane Fellner; Michael G Leu; Cris Ewell Journal: Appl Clin Inform Date: 2019-02-27 Impact factor: 2.342
Authors: Mitesh S Patel; Kevin G Volpp; Dylan S Small; Craig Wynn; Jingsan Zhu; Lin Yang; Steven Honeywell; Susan C Day Journal: Healthc (Amst) Date: 2016-05-11
Authors: Mitesh S Patel; Kevin G Volpp; Dylan S Small; Craig Wynne; Jingsan Zhu; Lin Yang; Steven Honeywell; Susan C Day Journal: J Gen Intern Med Date: 2017-03-23 Impact factor: 5.128
Authors: Matthew M Symer; Jonathan S Abelson; Jeffrey Milsom; Bridget McClure; Heather L Yeo Journal: J Gastrointest Surg Date: 2017-07-06 Impact factor: 3.452
Authors: Joy L Lee; Areeba Kara; Monica Huffman; Marianne S Matthias; Bethany Radecki; April Savoy; Jason T Schaffer; Michael Weiner Journal: Appl Clin Inform Date: 2022-03-16 Impact factor: 2.342