Appl Clin Inform 2017; 08(04): 1031-1043
DOI: 10.4338/ACI-2017-06-RA-0096
Research Article
Schattauer GmbH Stuttgart

Core Components for a Clinically Integrated mHealth App for Asthma Symptom Monitoring

Robert S. Rudin
,
Christopher H. Fanta
,
Zachary Predmore
,
Kevin Kron
,
Maria O. Edelen
,
Adam B. Landman
,
Eyal Zimlichman
,
David W. Bates
Further Information

Publication History

14 June 2017

30 August 2017

Publication Date:
14 December 2017 (online)

Abstract

Background mHealth apps may be useful tools for supporting chronic disease management.

Objective Our aim was to apply user-centered design principles to efficiently identify core components for an mHealth-based asthma symptom–monitoring intervention using patient-reported outcomes (PROs).

Methods We iteratively combined principles of qualitative research, user-centered design, and “gamification” to understand patients' and providers' needs, develop and refine intervention components, develop prototypes, and create a usable mobile app to integrate with clinical workflows. We identified anticipated benefits and burdens for stakeholders.

Results We conducted 19 individual design sessions with nine adult patients and seven clinicians from an academic medical center (some were included multiple times). We identified four core intervention components: (1) Invitation—patients are invited by their physicians. (2) Symptom checks—patients receive weekly five-item questionnaires via the app with 48 hours to respond. Depending on symptoms, patients may be given the option to request a call from a nurse or receive one automatically. (3) Patient review—in the app, patients can view their self-reported data graphically. (4) In-person visit—physicians have access to patient-reported symptoms in the electronic health record (EHR) where they can review them before in-person visits. As there is currently no location in the EHR where physicians would consistently notice these data, recording a recent note was the best option. Benefits to patients may include helping decide when to call their provider and facilitating shared decision making. Benefits to providers may include saving time discussing symptoms. Provider organizations may need to pay nurses extra, but those costs may be offset by reduced visits and hospitalizations.

Conclusion Recent systematic reviews show inconsistent outcomes and little insight into functionalities required for mHealth asthma interventions, highlighting the need for systematic intervention design. We identified specific features for adoption and engagement that meet the stated needs of users for asthma symptom monitoring.

Protection of Human and Animal Subjects

This study was reviewed by RAND and Partners Healthcare Institutional Review Board.


 
  • References

  • 1 Singh K, Drouin K, Newmark LP. , et al. Many mobile health apps target high-need, high-cost populations, but gaps remain. Health Aff (Millwood) 2016; 35 (12) 2310-2318
  • 2 Smith A. Record Shares of Americans Now Own Smartphones, Have Home Broadband. Pew Research Center; 2017
  • 3 Laing BY, Mangione CM, Tseng CH. , et al. Effectiveness of a smartphone application for weight loss compared with usual care in overweight primary care patients: a randomized, controlled trial. Ann Intern Med 2014; 161 (10, Suppl): S5-S12
  • 4 Centers for Disease Control and Prevention. Asthma in the US. CDC Vital Signs, [cited May 2011]; Available at: http://www.cdc.gov/vitalsigns/asthma
  • 5 World Health Organization. Asthma fact sheet No. 307. Updated November 2013. [cited 2008]; Available at: http://www.who.int/topics/asthma/en
  • 6 Wang T, Srebotnjak T, Brownell J, Hsia RY. Emergency department charges for asthma-related outpatient visits by insurance status. J Health Care Poor Underserved 2014; 25 (01) 396-405
  • 7 Lang DM. New asthma guidelines emphasize control, regular monitoring. Cleve Clin J Med 2008; 75 (09) 641-653
  • 8 van der Meer V, van Stel HF, Bakker MJ. , et al; SMASHING (Self-Management of Asthma Supported by Hospitals, ICT, Nurses and General practitioners) Study Group. Weekly self-monitoring and treatment adjustment benefit patients with partly controlled and uncontrolled asthma: an analysis of the SMASHING study. Respir Res 2010; 11 (01) 74
  • 9 Braido F. Failure in asthma control: reasons and consequences. Scientifica (Cairo) 2013; 2013: 549252
  • 10 Okelo SO, Butz AM, Sharma R. , et al. Interventions to modify health care provider adherence to asthma guidelines: a systematic review. Pediatrics 2013; 132 (03) 517-534
  • 11 Wisnivesky JP, Lorenzo J, Lyn-Cook R. , et al. Barriers to adherence to asthma management guidelines among inner-city primary care providers. Ann Allergy Asthma Immunol 2008; 101 (03) 264-270
  • 12 Marcano Belisario JS, Huckvale K, Greenfield G, Car J, Gunn LH. Smartphone and tablet self management apps for asthma. Cochrane Database Syst Rev 2013; ;( (11) CD010013
  • 13 Hui CY, Walton R, McKinstry B, Jackson T, Parker R, Pinnock H. The use of mobile applications to support self-management for people with asthma: a systematic review of controlled studies to identify features associated with clinical effectiveness and adherence. J Am Med Inform Assoc 2017; 24 (03) 619-632
  • 14 Wiecha JM, Adams WG, Rybin D, Rizzodepaoli M, Keller J, Clay JM. Evaluation of a web-based asthma self-management system: a randomised controlled pilot trial. BMC Pulm Med 2015; 15 (01) 17
  • 15 Vasbinder EC, Janssens HM, Rutten-van Mölken MP. , et al; e-MATIC Study Group. e-Monitoring of asthma therapy to improve compliance in children using a real-time medication monitoring system (RTMM): the e-MATIC study protocol. BMC Med Inform Decis Mak 2013; 13 (01) 38
  • 16 Rasmussen LM, Phanareth K, Nolte H, Backer V. Internet-based monitoring of asthma: a long-term, randomized clinical study of 300 asthmatic subjects. J Allergy Clin Immunol 2005; 115 (06) 1137-1142
  • 17 Ries E. The Lean Startup: How Today's Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses. New York: Crown Business; 2011
  • 18 Risso NA, Neyem A, Benedetto JI. , et al. A cloud-based mobile system to improve respiratory therapy services at home. J Biomed Inform 2016; 63: 45-53
  • 19 Lara M, Edelen MO, Eberhart NK, Stucky BD, Sherbourne CD. Development and validation of the RAND Asthma Control Measure. Eur Respir J 2014; 44 (05) 1243-1252
  • 20 Schatz M, Sorkness CA, Li JT. , et al. Asthma Control Test: reliability, validity, and responsiveness in patients not previously followed by asthma specialists. J Allergy Clin Immunol 2006; 117 (03) 549-556
  • 21 Becker MH, Maiman LA. Sociobehavioral determinants of compliance with health and medical care recommendations. Med Care 1975; 13 (01) 10-24
  • 22 Becker MH, Radius SM, Rosenstock IM, Drachman RH, Schuberth KC, Teets KC. Compliance with a medical regimen for asthma: a test of the health belief model. Public Health Rep 1978; 93 (03) 268-277
  • 23 Lau AY, Arguel A, Dennis S, Liaw ST, Coiera E. “Why Didn't it Work?” Lessons from a randomized controlled trial of a web-based personally controlled health management system for adults with asthma. J Med Internet Res 2015; 17 (12) e283
  • 24 Deterding S, Dixon D, Khaled R, Nacke L. From game design elements to gamefulness: defining gamification. Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments; 2011:9–15
  • 25 Mekler ED, Brühlmann F, Opwis K, Tuch AN. Disassembling gamification: the effects of points and meaning on user motivation and performance. CHI'13 Extended Abstracts on Human Factors in Computing Systems; 2013:1137–1142
  • 26 Nicholson S. A User-Centered Theoretical Framework for Meaningful Gamification. Madison, WI: Games+Learning+Society 8.0; 2012
  • 27 Steele Gray C, Khan AI, Kuluski K. , et al. Improving patient experience and primary care quality for patients with complex chronic disease using the electronic patient-reported outcomes tool: adopting qualitative methods into a user-centered design approach. JMIR Res Protoc 2016; 5 (01) e28
  • 28 Jones SS, Heaton PS, Rudin RS, Schneider EC. Unraveling the IT productivity paradox--lessons for health care. N Engl J Med 2012; 366 (24) 2243-2245
  • 29 Rudin RS, Bates DW, MacRae C. Accelerating innovation in health IT. N Engl J Med 2016; 375 (09) 815-817
  • 30 Nielsen J. 10 Usability Heuristics for User Interface Design. 1995 [cited May 18, 2017]; Available at: http://www.nngroup.com/articles/ten-usability-heuristics/
  • 31 Glaser BG, Strauss AL. The Discovery of Grounded Theory: Strategies for Qualitative Research. Transaction publishers; 2009
  • 32 Lewis C. Using the “Thinking-Aloud” Method in Cognitive Interface Design. Yorktown Heights, NY: IBM TJ Watson Research Center; 1982
  • 33 Harle CA, Listhaus A, Covarrubias CM. , et al. Overcoming barriers to implementing patient-reported outcomes in an electronic health record: a case report. J Am Med Inform Assoc 2016; 23 (01) 74-79
  • 34 Asch DA, Rosin R. Innovation as Discipline, not fad. N Engl J Med 2015; 373 (07) 592-594
  • 35 Bella M, Hanington B. Universal Methods of design. America: Rockport; 2012
  • 36 Klemmer SR, Sinha AK, Chen J, Landay JA, Aboobaker N, Wang A. Suede: a Wizard of Oz prototyping tool for speech user interfaces. Proceedings of the 13th Annual ACM Symposium on User Interface Software and Technology;2000:1–10
  • 37 van Gaalen JL, van Bodegom-Vos L, Bakker MJ, Snoeck-Stroband JB, Sont JK. Internet-based self-management support for adults with asthma: a qualitative study among patients, general practitioners and practice nurses on barriers to implementation. BMJ Open 2016; 6 (08) e010809
  • 38 Rodriguez D. 8 Apps That Make Asthma Management Easier. 2016 [cited 2016 August 14]; Available at: http://www.everydayhealth.com/hs/adult-asthma/asthma-management-apps/
  • 39 Basch E, Deal AM, Kris MG. , et al. Symptom monitoring with patient-reported outcomes during routine cancer treatment: a randomized controlled trial. J Clin Oncol 2016; 34 (06) 557-565
  • 40 Rotenstein LS, Agarwal A, O'Neil K. , et al. Implementing patient-reported outcome surveys as part of routine care: lessons from an academic radiation oncology department. J Am Med Inform Assoc 2017; 24 (05) 964-968
  • 41 Slover JD, Karia RJ, Hauer C, Gelber Z, Band PA, Graham J. Feasibility of integrating standardized patient-reported outcomes in orthopedic care. Am J Manag Care 2015; 21 (08) e494-e500
  • 42 Ring N, Jepson R, Hoskins G. , et al. Understanding what helps or hinders asthma action plan use: a systematic review and synthesis of the qualitative literature. Patient Educ Couns 2011; 85 (02) e131-e143
  • 43 Ring N, Jepson R, Pinnock H. , et al. Developing novel evidence-based interventions to promote asthma action plan use: a cross-study synthesis of evidence from randomised controlled trials and qualitative studies. Trials 2012; 13 (01) 216
  • 44 Ring N, Malcolm C, Wyke S. , et al. Promoting the use of personal asthma action plans: a systematic review. Prim Care Respir J 2007; 16 (05) 271-283
  • 45 Do Q, Tran S, Robinson K. Big Data and mHealth Drive Asthma Self-Management. 2015 International Conference on Computational Science and Computational Intelligence (CSCI); IEEE; 2015:806–809
  • 46 Morrison D, Wyke S, Agur K. , et al. Digital asthma self-management interventions: a systematic review. J Med Internet Res 2014; 16 (02) e51