A Two-Way Interactive Text Messaging Application for Low-Income Patients with Chronic Medical Conditions: Design-Thinking Development Approach

Monika Marko-Holguin; Stephanie Luz Cordel; Benjamin William Van Voorhees; Joshua Fogel; Emily Sykes; Marian Fitzgibbon; Anne Elizabeth Glassgow

doi:10.2196/11833

A Two-Way Interactive Text Messaging Application for Low-Income Patients with Chronic Medical Conditions: Design-Thinking Development Approach (Preprint)

10.2196/preprints.11833 ◽

2018 ◽

Author(s):

Monika Marko-Holguin ◽

Stephanie Luz Cordel ◽

Benjamin William Van Voorhees ◽

Joshua Fogel ◽

Emily Sykes ◽

...

Keyword(s):

Health Care ◽

Text Messaging ◽

Design Thinking ◽

Care Staff ◽

Health Care Staff ◽

Chronic Medical Conditions ◽

Medical Conditions ◽

Interactive Text ◽

Sms Text Messaging ◽

User Centered

BACKGROUND Two-way interactive text messaging between patient and community health workers (CHWs) through mobile phone SMS (short message service) text messaging is a form of digital health that can potentially enhance patient engagement in young adults and families that have a child with chronic medical conditions such as diabetes mellitus, sickle cell disease, and asthma. These patients have complex needs, and a user-centered way can be useful for designing a tool to address their needs. OBJECTIVE The aim of this study was to utilize the user-centered approach of design thinking to develop a two-way interactive communication SMS text messaging tool for communication between patients or caregivers and CHWs. METHODS We applied a design thinking methodology for development of the SMS text messaging tool. We collected qualitative data from 127 patients/caregivers and 13 CHWs, health care professionals, and experts. In total, 4 iterative phases were used to design the final prototype. RESULTS The design thinking process led to the final SMS text messaging tool that was transformed from a one-dimensional, template-driven prototype (phases 1 and 2) into a dynamic, interactive, and individually tailored tool (phases 3 and 4). The individualized components consider social factors that influence patients’ ability to engage such as transportation issues and appointment reminders. SMS text messaging components also include operational factors to support staff such as patient contact lists, SMS text messaging templates, and technology chat support. CONCLUSIONS Design thinking can develop a tool to meet the engagement needs of patients with complex health care needs and be user-friendly for health care staff.

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REVISÃO DE FORMA SISTEMÁTICA DO DESIGN THINKING APLICADO EM DISPOSITIVOS MÉDICOS

International Journal of Knowledge Engineering and Management ◽

10.47916/ijkem-vol9n25-2020-84852 ◽

2021 ◽

Vol 9 (25) ◽

pp. 165-180

Author(s):

Mariana Ribeiro Brandao ◽

Maria Collier de Mendonça ◽

Renato Garcia Ojeda ◽

Richard Perassi ◽

Francisco Fialho

Keyword(s):

Public Health ◽

Low Income ◽

Text Messaging ◽

Design Education ◽

Design Thinking ◽

Pilot Project ◽

Harvard Business Review ◽

Clinical Engineering ◽

Innovation Ecosystem ◽

Development Approach

Objetivo: Analisar estudos baseados na aplicação do Design Thinking envolvendo dispositivos médicos para discutir a importância das necessidades dos usuários na resolução de problemas relacionados às tecnologias em saúde. Design⏐Metodologia⏐Abordagem: Neste artigo é apresentada uma revisão de forma sistemática da literatura, através do método Systematic Search Flow (SSF), por meio de uma pesquisa nas bases de dados Scopus, IEEE, Pubmed e Scielo. Foram encontradas 161 publicações segundo os critérios de busca e as palavras-chaves definidas. Por fim, foram selecionados seis artigos para a análise dos resultados. Resultados: Os resultados da revisão de forma sistemática mostraram diversas possibilidades de aplicação do Design Thinking no desenvolvimento de dispositivos médicos, desde em dispositivos de classe de risco mais elevado, até mesmo em equipamentos menos complexos, para uso domiciliar, e software para aporte clínico para melhorar a experiência de recém-nascidos, crianças, quanto também para auxiliar o envelhecimento saudável de idosos. Originalidade⏐Valor: O desenvolvimento de novas soluções tecnológicas centradas nos usuários e voltadas para a saúde permitem a aplicação do Design Thinking; especialmente aquelas que envolvem dispositivos médicos para melhorar a segurança e a qualidade das tecnologias de saúde para os usuários, proporcionando melhor usabilidade e compreensão do contexto atual dessas tecnologias na perspectiva dos usuários. Referências Abookire, S., Plover, C., Frasso, R., & Ku, B. (2020). Health Design Thinking: An Innovative Approach in Public Health to Defining Problems and Finding Solutions. Front Public Health, 8(459). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7484480/ Altman, M., Huang, T. T., & Breland, J. Y. (2018). Design Thinking in Health Care. Prev Chronic Dis. Ayah, R., Ong'ech, J., Mbugua, E. M., Kosgei, R. C., Waller, K., & Gathara, D. (2020). Responding to maternal, neonatal and child health equipment needs in Kenya: a model for an innovation ecosystem leveraging on collaborations and partnerships. BMJ Innov, 6. https://doi.org/10.1136/bmjinnov-2019-000391 Brown, T. (2008). Design Thinking. Harvard Business Review. Brown, T. (2010). Design Thinking - Uma metodologia poderosa para decretar o fim das velhas ideias (Traduzida - 2017 ed.). Starlin Alta. Ferenhof, H. A., & Fernandes, R. F. (2016). Desmistificando a revisão de literatura como base para redação científica: método SFF. Revista ACB, 21(3). https://revista.acbsc.org.br/racb/article/view/1194 Flewwelling, C., Easty, A., Vicente, K., & Cafazzo, J. (2014). The use of fault reporting of medical equipment to identify latent design flaws. J Biomed Inform. Jiang, J., Liu, T., Zhang, Y., Song, Y., Zhou, M., Zheng, X., & Yan, Z. (2017). Design and development of an intelligent nursing bed - a pilot project of "joint assignment". Annu Int Conf IEEE Eng Med Biol Soc, 38–41. https://doi.org/10.1109/EMBC.2017.8036757 Marko-Holguin, M., Cordel, S. L., Voorhees, B., Fogel, J., Sykes, E., Fitzgibbon, M., & Glassgow, A. (2019). A Two-Way Interactive Text Messaging Application for Low-Income Patients with Chronic Medical Conditions: Design-Thinking Development Approach. JMIR Mhealth Uhealth, 7. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6658312/ Organização Mundial da Saúde. (2020). Dispositivo Médico - Definição Completa. Organização Mundial da Saúde. https://www.who.int/medical_devices/full_deffinition/en/ Poncette, A.-S., Spies, C., Mosch, L., Schieler, M., Weber-Carstens, S., Krampe, H., & Balzer, F. (2019). Clinical Requirements of Future Patient Monitoring in the Intensive Care Unit: Qualitative Study. JMIR Med Inform, 7. https://doi.org/10.2196/13064 Rodziewicz, T. L., Houseman, B., & Hipskind, J. E. (2020). Medical Error Prevention. StatPearls. https://www.ncbi.nlm.nih.gov/books/NBK499956/ Shepherd, M. (2004). Clinical Engineering Handbook (1st ed.). Elsevier Academic. Sherman, J., Lee, H. C., Weiss, M. E., & Kristensen-Cabrera, A. (2018). Medical Device Design Education: Identifying Problems Through Observation and Hands-On Training. Des Technol Educ, 23, 154-174. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6759072/ Tosi, F., & Rinaldi, A. (2017). Design and Usability of the Next Medical Devices for the Home Care. The Design Journal. https://doi.org/10.1080/14606925.2017.1352722 Van der Cammen, T. J., Albayrak, A., Voûte, E., & Molenbroek, J. F. (2016). New horizons in design for autonomous ageing. Oxford Academic, 46, 11-17. https://doi.org/10.1093/ageing/afw181

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Effect of Electronic Health Record Reminders for Routine Immunizations and Immunizations Needed for Chronic Medical Conditions

Applied Clinical Informatics ◽

10.1055/s-0041-1739516 ◽

2021 ◽

Vol 12 (05) ◽

pp. 1101-1109

Author(s):

Ashley B. Stephens ◽

Chelsea S. Wynn ◽

Annika M. Hofstetter ◽

Chelsea Kolff ◽

Oscar Pena ◽

...

Keyword(s):

New York ◽

Low Income ◽

Age Groups ◽

Clinical Decision ◽

Chronic Medical Conditions ◽

Medical Conditions ◽

Chi Square ◽

Control And Prevention ◽

Electronic Health ◽

The Impact

Abstract Background Immunization reminders in electronic health records (EHR) provide clinical decision support (CDS) that can reduce missed immunization opportunities. Little is known about using CDS rules from a regional immunization information system (IIS) to power local EHR immunization reminders. Objective This study aimed to assess the impact of EHR reminders using regional IIS CDS-provided rules on receipt of immunizations in a low-income, urban population for both routine immunizations and those recommended for patients with chronic medical conditions (CMCs). Methods We built an EHR-based immunization reminder using the open-source resource used by the New York City IIS in which we overlaid logic regarding immunizations needed for CMCs. Using a randomized cluster-cross-over pragmatic clinical trial in four academic-affiliated clinics, we compared captured immunization opportunities during patient visits when the reminder was “on” versus “off” for the primary immunization series, school-age boosters, and adolescents. We also assessed coverage of CMC-specific immunizations. Up-to-date immunization was measured by end of quarter. Rates were compared using chi square tests. Results Overall, 15,343 unique patients were seen for 26,647 visits. The alert significantly impacted captured opportunities to complete the primary series in both well-child and acute care visits (57.6% on vs. 54.3% off, p = 0.001, and 15.3% on vs. 10.1% off, p = 0.02, respectively), among most age groups, and several immunization types. Captured opportunities for CMC-specific immunizations remained low regardless of alert status. The alert did not have an effect on up-to-date immunization overall (89.1 vs. 88.3%). Conclusion CDS in this population improved captured immunization opportunities. Baseline high rates may have blunted an up-to-date population effect. Converting Centers for Disease Control and Prevention (CDC) rules to generate sufficiently sensitive and specific alerts for CMC-specific immunizations proved challenging, and the alert did not have an impact on CMC-specific immunizations, potentially highlighting need for more work in this area.

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Habit Strength, Medication Adherence, and Habit-Based Mobile Health Interventions Across Chronic Medical Conditions: Systematic Review

Journal of Medical Internet Research ◽

10.2196/17883 ◽

2020 ◽

Vol 22 (4) ◽

pp. e17883 ◽

Cited By ~ 1

Author(s):

Sherif M Badawy ◽

Richa Shah ◽

Usman Beg ◽

Mallorie B Heneghan

Keyword(s):

Medication Adherence ◽

Theoretical Model ◽

Mobile Health ◽

Text Messaging ◽

Keyword Search ◽

Habit Strength ◽

Self Report ◽

Chronic Medical Conditions ◽

Medical Conditions ◽

Pubmed Database

Background Unintentional medication nonadherence is common and has been associated with poor health outcomes and increased health care costs. Earlier research demonstrated a relationship between habit strength and medication adherence. Previous research also examined a habit’s direct effect on adherence and how habit interacts with more conscious factors to influence or overrule them. However, the relationship between habit and adherence and the role of habit-based mobile health (mHealth) interventions remain unclear. Objective This review aimed to systematically evaluate the most recent evidence for habit strength, medication adherence, and habit-based mHealth interventions across chronic medical conditions. Methods A keyword search with combinations of the terms habit, habit strength, habit index, medication adherence, and medication compliance was conducted on the PubMed database. After duplicates were removed, two authors conducted independent abstract and full-text screening. The guidelines for the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were followed when reporting evidence across the included and reviewed studies. Results Of the 687 records examined, 11 met the predefined inclusion criteria and were finalized for data extraction, grading, and synthesis. Most included studies (6/11, 55%) were cross-sectional and used a theoretical model (8/11, 73%). The majority of studies measured habit strength using the self-report habit index and self-report behavioral automaticity index (9/11, 82%). Habit strength was positively correlated with medication adherence in most studies (10/11, 91%). Habit mediated the effects of self-efficacy on medication adherence (1/11, 9%), and social norms moderated the effects of habit strength on medication adherence (1/11, 9%). Habit strength also moderated the effects of poor mental health symptoms and medication adherence (1/11, 9%). None of the included studies reported on using or proposing a habit-based mHealth behavioral intervention to promote medication adherence. Conclusions Habit strength was strongly correlated with medication adherence, and stronger habit was associated with higher medication adherence rates, regardless of the theoretical model and/or guiding framework. Habit-based interventions should be used to increase medication adherence, and these interventions could leverage widely available mobile technology tools such as mobile apps or text messaging, and existing routines.

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