Jose F Florez-Arango MD MSc PhD

Yes, informatics can help to humanize health

Research Agenda

 

Humanizing Clinical Encounters and Personalized Care through Information and Communication Technologies (ICTs)

 

Introduction

Personalized medicine holds the promise of revolutionizing healthcare by tailoring treatments to the individual needs of patients. However, the integration of Information and Communication Technologies (ICTs) into clinical encounters often creates challenges, with many patients and providers perceiving these technologies as cold, intrusive, and a source of triangulation that detracts from human connection. Additionally, healthcare providers face dehumanizing pressures such as heavy workloads, stress, and diminished personal satisfaction.

Factors contributing to these challenges include cognitive overload, physical strain, and emotional demands on providers, which affect their ability to deliver optimal care. Evidence suggests that ICTs have the potential to address these issues by supporting both patients and providers, enhancing their experiences through cognitive and decision support, reducing physical burdens, and fostering emotional, psychological, and social well-being (1–9).

This research agenda emphasizes mental health as a critical case use but is applicable to other clinical conditions. It focuses on how personalized medicine, knowledge engineering, and user-centric interface design can converge to improve provider-patient interactions, promote therapeutic adherence, and ultimately lead to better clinical outcomes.

 

 

Research Objectives

  • Develop an ICT Implementation Framework
    Create a framework for implementing ICTs that enhances healthcare providers' cognitive and perceived performance. The framework should aim to:

    • Reduce mental, physical, and temporal demands.
    • Minimize frustration experienced by providers during clinical encounters.
    • Support healthcare providers in maintaining high levels of empathy and patient engagement.

  • Streamline Knowledge Engineering Processes
    Optimize the workflow for acquiring, summarizing, modeling, encoding, and deploying medical knowledge to:

    • Create collaborative decision-making tools that integrate seamlessly into clinical workflows.
    • Develop personalized health interventions that are safe, usable, and widely accepted by both patients and providers.

  • Enhance Patient-Provider Interaction
    Use ICTs to humanize clinical encounters by:

    • Fostering meaningful communication and shared decision-making between patients and providers.
    • Designing user-centric interfaces that facilitate the delivery of personalized interventions in a way that aligns with patient needs and preferences.
    • Innovating in the use of technology in the encounter

  • Improve Patient Adherence and Clinical Outcomes
    Leverage ICT-enabled personalized care to promote therapeutic adherence by:

    • Providing patients with intuitive tools to track progress, understand treatment plans, and stay engaged in their care.
    • Enhancing the delivery of targeted interventions that address not just physical health but also emotional and psychological well-being.

Mental Health as a Case Use

Mental health care exemplifies the need for humanized, personalized care, where ICTs can play a pivotal role in addressing complex challenges:

  • Jointly with Universidad de Antioquia’s School of Public and Center for innovation in Mental Health at CUNY I’m exploring the use of information and communication technologies in the triad student-teacher-parent to identify internalizing and externalizing mental health symptoms, that inform school interventions and provide parental guidance in the context of victims of violence and the resilience building.
  • With Center of Innovation of Mental Health at CUNY, we are exploring alternatives to educate community health workers in mental health screening and referrals, including online education for knowledge development and extended reality tools for communication skills development.
  • In collaboration with Cornell Center for Research on End-of-Life Care we are exploring information and communication technologies to personalize care of grief and bereavement on cancer patients and their families, with emphasis in self-care and self-management.
  • With Lienzotú in Colombia we are exploring art-therapy as strategy to deliver support to teenagers with social network support.

 

Expected Outcomes

  • Humanized Technology: ICTs designed to promote empathy, trust, and effective communication during clinical encounters.
  • Improved Provider Performance: Tools that reduce cognitive and physical demands while supporting clinical decision-making.
  • Personalized Care at Scale: Safe, user-friendly interventions tailored to individual patient needs, improving adherence and satisfaction.
  • Enhanced Mental Health Outcomes: Demonstrated impact in mental health care as a model for how ICTs can improve other clinical areas.
  • Automation of development cycle: Tools that facilitate the construction and deployment of ICTs that incorporate human factors, improves performance, personalize care and enhance health outcomes.

Conclusion

This research agenda advocates for the development and implementation of ICTs that humanize personalized care. By focusing on improving provider performance, facilitating collaborative decision-making, and enhancing patient engagement, these technologies can transform clinical encounters into meaningful, human-centered interactions. The goal is to streamline the delivery of personalized interventions that improve adherence and lead to better clinical outcomes while preserving the humanity of healthcare delivery.

References

  1. Torres Silva EA, Luna Gomez IF, Florez Arango JF, Smith JW, Ocampo SU, Hidalgo JE. Evaluation of satisfaction and usability of a Clinical Decision Support System (CDSS) targeted for early obstetric risk assessment and patient follow-up. In: MCCSIS 2018 - Multi Conference on Computer Science and Information Systems; Proceedings of the International Conferences on e-Health 2018, ICT, Society, and Human Beings 2018 and Web Based Communities and Social Media 2018. IADIS; 2018. p. 3–11.
  2. Hsueh PYS, Florez-Arango JF, Kuziemsky CE, Nøhr C, Patel VL, Zhu X. New Care Delivery Models for Critical Responses: Case Studies of E-enabled Patient-Provider Communication in Context. In: AMIA. 2020.
  3. Kuziemsky Craig E.and Nohr C and FAJF and PVL. E-enabled Patient-Provider Communication in Context. In: Hsueh Pei-Yun Sabrinaand Wetter T and ZX, editor. Personal Health Informatics: Patient Participation in Precision Health [Internet]. Cham: Springer International Publishing; 2022. p. 3–24. Available from: https://doi.org/10.1007/978-3-031-07696-1_1
  4. Iyengar MS, Rogith D, Florez-Arango JF. Measuring Workload Demand of Informatics Systems with the Clinical Case Demand Index. In: AMIA Annual Symposium Proceedings. American Medical Informatics Association; 2017. p. 985.
  5. Florez-Arango JF, Patiño-Giraldo S, Iyengar MS, Smith JW. Performance Evaluation Clinical Task Ontology ( PECTO ) on health worker performance. In: Meier A, editor. Joint International Conference on Biological Ontology and BioCreative 2016 [Internet]. CEUR Workshop Proceedings; 2016. Available from: http://ceur-ws.org/Vol-1747/IP26_ICBO2016.pdf
  6. Florez-Arango JF. Workload and performance factors associated with multimedia job aids for community health workers [Internet] [PhD Thesis]. The University of Texas School of Health Information Sciences at Houston; 2009. Available from: https://digitalcommons.library.tmc.edu/uthshis_dissertations/22/
  7. Florez-Arango JF, Iyengar MS, Dunn K, Zhang J, Sriram Iyengar M, Dunn K, et al. Performance factors of mobile rich media job aids for community health workers. J Am Med Inform Assoc [Internet]. 2011 Jan 1 [cited 2012 Mar 14];18(2):131–7. Available from: http://jamia.bmj.com/content/18/2/131.full
  8. Iyengar MS, Chang O, Florez-Arango JF, Taria M, Patel VL. Development and usability of a mobile tool for identification of depression and suicide risk in Fiji. Technol Health Care. 2021;29(1).
  9. Silva EAT, Gomez IFL, Arango JFF, Smith JW, Ocampo SU, Hidalgo JE. Evaluation of satisfaction and usability of a clinical decision support system (CDSS) targeted for early obstetric risk assessment and patient follow-up. Health (N Y). 2018;3.