DOI:
https://doi.org/10.64539/sjcs.v2i1.2026.406Keywords:
Chronic disease management, Digital health policy, Health informatics implementation, Internet of Medical Things (IoMT), Medical device validation, Low-and Middle-Income Countries (LMICs)Abstract
The Internet of Medical Things (IoMT) holds promise for chronic disease management, yet evidence from low- and middle-income countries (LMICs) remains scarce, limiting equitable digital health policy development. No previous studies have clinically validated IoMT device performance against electronic health records (EHRs) within Central American public healthcare systems, leaving assumptions about consumer device adequacy untested in resource-constrained settings. This mixed-methods study evaluated IoMT implementation in Costa Rica's Caja Costarricense de Seguro Social (CCSS) system, examining (1) diagnostic accuracy stratification between consumer and clinical-grade devices, (2) healthcare system interoperability challenges, and (3) cost implications of false alerts. Among 50 chronic disease patients, consumer wearables demonstrated 43% sensitivity for cardiac event detection versus 92% for clinical-grade devices (p<0.001). Only 25% of consumer devices integrated with CCSS EHRs versus 100% of clinical-grade devices, requiring 22 minutes of manual data entry per encounter. False positives occurred in 12% of consumer-device alerts, costing an average of $35 per event. Qualitative analysis revealed that 45% of participants overestimated consumer-device diagnostic capabilities. These findings challenge assumptions about universal consumer-technology applicability in LMICs and support tiered implementation frameworks. As Costa Rica prepares for its Digital Health Act 2025, evidence-based device categorization, interoperability investments, and patient education are essential for equitable IoMT integration.
References
[1] A. C. Borges Monteiro, R. P. França, R. Arthur, and Y. Iano, "An overview of the Internet of medical things (IoMT): Applications, benefits, and challenges," Security and Privacy Issues in Internet of Medical Things, pp. 83–98, 2023/01/01/ 2023, https://doi.org/10.1016/B978-0-323-89872-0.00009-5.
[2] J. Jiménez-Montero and M. Villegas-Barakat, "Changes in diabetes mortality rate in Costa Rica 2007–2017," Diabetes Research and Clinical Practice, vol. 174, 2021, https://doi.org/10.1016/j.diabres.2021.108749.
[3] S. Abdulmalek et al., "IoT-based healthcare-monitoring system towards improving quality of life: A review," Healthcare, vol. 10, no. 10, p. 1993, 2022, https://doi.org/10.3390/healthcare10101993.
[4] C. Makri and A. Neely, "Grounded Theory: A Guide for Exploratory Studies in Management Research," International Journal of Qualitative Methods, vol. 20, p. 16094069211013654, 2021, https://doi.org/10.1177/16094069211013654.
[5] I. Rodríguez-Rodríguez, M. Campo-Valera, J.-V. Rodríguez, and W. Lok Woo, "IoMT innovations in diabetes management: Predictive models using wearable data," Expert Systems with Applications, vol. 238, p. 121994, 2024/03/15/ 2024, https://doi.org/10.1016/j.eswa.2023.121994.
[6] A. A. El-Saleh, A. M. Sheikh, M. A. M. Albreem, and M. S. Honnurvali, "The Internet of Medical Things (IoMT): opportunities and challenges," Wireless Networks, vol. 31, no. 1, pp. 327–344, 2025/01/01 2025, https://doi.org/10.1007/s11276-024-03764-8.
[7] M. Baran, "Mixed methods research design," Research Anthology on Innovative Research Methodologies and Utilization Across Multiple Disciplines, vol. 1, pp. 312–333, 2022, https://doi.org/10.4018/978-1-6684-3881-7.
[8] S. Dawadi, S. Shrestha, and R. A. Giri, "Mixed-methods research: A discussion on its types, challenges, and criticisms," Journal of Practical Studies in Education, vol. 2, no. 2, pp. 25–36, 2021, https://doi.org/10.46809/jpse.v2i2.20.
[9] I. Ljevaković-Musladin, "Ensuring the Validity of Results," Handbook of Quality System, Accreditation and Conformity Assessment, pp. 1–54, 2024, https://doi.org/10.1007/978-981-99-4637-2_45-1.
[10] S. R. Taquette and L. M. Borges da Matta Souza, "Ethical Dilemmas in Qualitative Research: A Critical Literature Review," International Journal of Qualitative Methods, vol. 21, p. 16094069221078731, 2022, https://doi.org/10.1177/16094069221078731.
[11] K. Gandy, "How many interviews or focus groups are enough?," Evaluation Journal of Australasia, vol. 24, no. 3, pp. 211–223, 2024, https://doi.org/10.1177/1035719X241266964.
[12] A. B. Hamilton and E. P. Finley, "Qualitative methods in implementation research: An introduction," Psychiatry Research, vol. 280, p. 112516, 2019/10/01/ 2019, https://doi.org/10.1016/j.psychres.2019.112516.
[13] K. Sachathep et al., "Population-Based HIV Impact Assessments Survey Methods, Response, and Quality in Zimbabwe, Malawi, and Zambia," JAIDS Journal of Acquired Immune Deficiency Syndromes, vol. 87, pp. S6–S16, 2021, https://doi.org/10.1097/qai.0000000000002710.
[14] L. N. Kawar, G. B. Dunbar, E. M. Aquino-Maneja, S. L. Flores, V. R. Squier, and K. R. Failla, "Quantitative, qualitative, mixed methods, and triangulation research simplified," The Journal of Continuing Education in Nursing, vol. 55, no. 7, pp. 338–344, 2024, https://doi.org/10.3928/00220124-20240328-03.
[15] D. Mortelmans, "Thematic Coding," Doing Qualitative Data Analysis with NVivo, pp. 57–87, 2025, https://doi.org/10.1007/978-3-031-66014-6_8.
[16] R. H. Adler, "Trustworthiness in Qualitative Research," Journal of Human Lactation, vol. 38, no. 4, pp. 598–602, 2022, https://doi.org/10.1177/08903344221116620.
[17] B. Thakkar, "Chapter 28 - Categorical variable analyses: Chi-square test, Fisher's exact test, Mantel-Haenszel test," Translational Cardiology, pp. 169–170, 2025/01/01/ 2025, https://doi.org/10.1016/B978-0-323-91790-2.00072-1.
[18] Z. T. Haile, "Power Analysis and Exploratory Research," Journal of Human Lactation, vol. 39, no. 4, pp. 579–583, 2023, https://doi.org/10.1177/08903344231195625.
[19] G. Rau and Y.-S. Shih, "Evaluation of Cohen's kappa and other measures of inter-rater agreement for genre analysis and other nominal data," Journal of English for Academic Purposes, vol. 53, p. 101026, 2021/09/01/ 2021, https://doi.org/10.1016/j.jeap.2021.101026.
[20] G. R. Bauer, S. M. Churchill, M. Mahendran, C. Walwyn, D. Lizotte, and A. A. Villa-Rueda, "Intersectionality in quantitative research: A systematic review of its emergence and applications of theory and methods," SSM - Population Health, vol. 14, p. 100798, 2021/06/01/ 2021, https://doi.org/10.1016/j.ssmph.2021.100798.
[21] M. Hennink and B. N. Kaiser, "Sample sizes for saturation in qualitative research: A systematic review of empirical tests," Social Science & Medicine, vol. 292, p. 114523, 2022/01/01/ 2022, https://doi.org/10.1016/j.socscimed.2021.114523.
[22] M. Lazic, E. Woodruff, and J. Jun, "Decoding Subjective Understanding: Using Biometric Signals to Classify Phases of Understanding," AI, vol. 6, no. 1, p. 18, 2025, https://doi.org/10.3390/ai6010018.
[23] S. R. Young et al., "Clinical Validation and Machine Learning Optimization of MyCog: A Self-Administered Cognitive Screener," medRxiv, p. 2025.04.17.25325948, 2025, https://doi.org/10.1101/2025.04.17.25325948.
[24] M. Marín, A. García, O. Muñoz, J. Castellanos, E. Cáceres, and D. Santacruz, "Portable single-lead electrocardiogram device is accurate for QTc evaluation in hospitalized patients," Heart Rhythm O2, vol. 2, 2021, https://doi.org/10.1016/j.hroo.2021.06.005.
[25] A. G. Mohapatra et al., "IoT-driven remote health monitoring system with sensor fusion enhancing immediate medical assistance in distributed settings," Alexandria Engineering Journal, vol. 120, pp. 627–636, 2025/05/01/ 2025, https://doi.org/10.1016/j.aej.2025.02.057.
[26] Á. Verdejo Espinosa, J. Lopez Ruiz, F. Mata Mata, and M. E. Estevez, "Application of IoT in Healthcare: Keys to Implementation of the Sustainable Development Goals," Sensors, vol. 21, no. 7, p. 2330, 2021, https://doi.org/10.3390/s21072330.
[27] WHO. "Digital health for the End TB Strategy: An accountability framework." World Health Organization. https://www.who.int/publications/i/item/WHO-HTM-TB-2015.21 (accessed 2025).
[28] S. F. Ahmed, S. B. Alam, S. Afrin, S. J. Rafa, N. Rafa, and A. H. Gandomi, "Insights into Internet of Medical Things (IoMT): Data fusion, security issues and potential solutions," Information Fusion, vol. 102, p. 102060, 2024/02/01/ 2024, https://doi.org/10.1016/j.inffus.2023.102060.
[29] A. Akundi, D. Euresti, S. Luna, W. Ankobiah, A. Lopes, and I. Edinbarough, "State of Industry 5.0—Analysis and Identification of Current Research Trends," Applied System Innovation, vol. 5, no. 1, p. 27, 2022, https://doi.org/10.3390/asi5010027.
[30] M. S. Kaswan, R. Chaudhary, J. A. Garza-Reyes, and A. Singh, "A review of Industry 5.0: from key facets to a conceptual implementation framework," International Journal of Quality & Reliability Management, vol. ahead-of-print, no. ahead-of-print, 2024, https://doi.org/10.1108/IJQRM-01-2024-0030.
[31] D. Tang, X. Xi, Y. Li, and M. Hu, "Regulatory approaches towards AI Medical Devices: A comparative study of the United States, the European Union and China," Health Policy, vol. 153, p. 105260, 2025/03/01/ 2025, https://doi.org/10.1016/j.healthpol.2025.105260.
