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Designing digital health interventions involves critical "buy or build" decisions for technology components. Careful planning is essential to address common issues like technology mismatches and resource limitations for successful implementation.

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Area of Science:

  • Digital Health
  • Health Informatics
  • Biomedical Engineering

Background:

  • Digital health interventions enhance clinician-patient collaborative care.
  • Developing these interventions necessitates strategic decisions regarding technology component acquisition (buy vs. build).
  • These decisions can introduce unforeseen challenges in implementation.

Purpose of the Study:

  • To document the challenges encountered during the "buy or build" decision-making process for two distinct digital health interventions.
  • To analyze issues arising from technology choices in developing patient-generated health data systems.
  • To inform future digital health intervention design by highlighting common pitfalls.

Main Methods:

  • Two digital health interventions were developed: CONDUIT-HID for hypertension control and USE-MI for HIV medication adherence.
  • CONDUIT-HID (2010-2015) focused on integrating home blood pressure readings into EHRs.
  • USE-MI (2016-2022) incorporated medication reminders, machine learning for ingestion detection, and adherence summaries.

Main Results:

  • Both projects involved extensive "buy or build" decisions across data collection, transfer, analysis, and display.
  • Commercial off-the-shelf technologies often required significant customization.
  • Recurring issues included technology compatibility, novel use cases, stability, longevity, and resource constraints.

Conclusions:

  • Numerous "buy or build" decisions are integral to digital health intervention development.
  • Anticipating and planning for issues stemming from these decisions is crucial.
  • Particular attention is needed for "edge case" applications of commercial systems.