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Assembling the Puzzle: Exploring Collaboration and Data Sensemaking in Nursing Practices for Remote Patient Monitoring

Mihnea Calota, Janet Yi-Ching Huang, Lin-Lin Chen, Mathias Funk

TL;DR

This study investigates how remote patient monitoring (RPM) reshapes nursing workflows through data work and sensemaking. Using qualitative field observations and interviews with six participants from two Dutch hospitals, the authors map daily practices, collaboration patterns, and the friction induced by data-centric tasks. Key findings show that RPM scale-up drives asynchronous collaboration, with data sensemaking—interpreting dispersed data across EHRs, patient data, and communications—being central yet hampered by current technologies and workflow design. The authors advocate foregrounding data sensemaking as a distinct nursing practice and call for tool design that supports asynchronous knowledge transfer, aiming to improve nurse experience and the scalability of RPM programs.

Abstract

Remote patient monitoring (RPM) involves the remote collection and transmission of patient health data, serving as a notable application of data-driven healthcare. This technology facilitates clinical monitoring and decision-making, offering benefits like reduced healthcare costs and improved patient outcomes. However, RPM also introduces challenges common to data-driven healthcare, such as additional data work that can disrupt clinician's workflow. This study explores the daily practices, collaboration mechanisms, and sensemaking processes of nurses in RPM through field observations and interviews with six stakeholders. Preliminary results indicate that RPM's scale-up pushes clinicians toward asynchronous collaboration. Data sensemaking is crucial for this type of collaboration, but existing technologies often create friction rather than support. This work provides empirical insights into clinical workflow in nursing practice, especially RPM. We suggest recognizing data sensemaking as a distinct nursing practice within data work and recommend further investigation into its role in the workflow of nurses in RPM.

Assembling the Puzzle: Exploring Collaboration and Data Sensemaking in Nursing Practices for Remote Patient Monitoring

TL;DR

This study investigates how remote patient monitoring (RPM) reshapes nursing workflows through data work and sensemaking. Using qualitative field observations and interviews with six participants from two Dutch hospitals, the authors map daily practices, collaboration patterns, and the friction induced by data-centric tasks. Key findings show that RPM scale-up drives asynchronous collaboration, with data sensemaking—interpreting dispersed data across EHRs, patient data, and communications—being central yet hampered by current technologies and workflow design. The authors advocate foregrounding data sensemaking as a distinct nursing practice and call for tool design that supports asynchronous knowledge transfer, aiming to improve nurse experience and the scalability of RPM programs.

Abstract

Remote patient monitoring (RPM) involves the remote collection and transmission of patient health data, serving as a notable application of data-driven healthcare. This technology facilitates clinical monitoring and decision-making, offering benefits like reduced healthcare costs and improved patient outcomes. However, RPM also introduces challenges common to data-driven healthcare, such as additional data work that can disrupt clinician's workflow. This study explores the daily practices, collaboration mechanisms, and sensemaking processes of nurses in RPM through field observations and interviews with six stakeholders. Preliminary results indicate that RPM's scale-up pushes clinicians toward asynchronous collaboration. Data sensemaking is crucial for this type of collaboration, but existing technologies often create friction rather than support. This work provides empirical insights into clinical workflow in nursing practice, especially RPM. We suggest recognizing data sensemaking as a distinct nursing practice within data work and recommend further investigation into its role in the workflow of nurses in RPM.
Paper Structure (15 sections, 1 figure, 1 table)

This paper contains 15 sections, 1 figure, 1 table.

Table of Contents

  1. Introduction
  2. The interplay of human and technological factors in RPM
  3. Data work for RPM
  4. (Data) sensemaking
  5. Method
  6. Results
  7. The role of the monitoring nurse
  8. The asynchronous nature of remote care
  9. The role of data sensemaking in collaboration
  10. Discussion
  11. The humans in the RPM workflows
  12. The burden of synchronizing asynchronous data and collaboration in RPM
  13. Foregrounding and unpacking data sensemaking in RPM
  14. Future Work
  15. Conclusion

Figures (1)

  • Figure 1: In the daily workflow, a monitoring nurse mainly deals with three types of activities related to sensemaking: calling patients for additionally information (yellow), interacting with the data records (red) and cognitive processes of data sensemaking (green). In a majority of cases, high intensity data sensemaking is correlated with the need to browse or forage for information in the data records.