ArticleApplied clinical informatics2023
Buy or Build: Challenges Developing Consumer Digital Health Interventions.
Article in Applied clinical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 3 citations in OpenAlex.
- Review
- Early viability assessment of a Business-to-Consumer (B2C) model for digital diabetes screening in Switzerland.BMC health services research · 2026Article
- Consumer Involvement in the Co-Design of Diabetes Self-Management Smartphone Apps: A Scoping Review.Applied clinical informatics · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 5 institutions in 1 country.
Funding
Abstract
backgroundDigital health interventions offer opportunities to improve collaborative care between clinicians and patients. Designing and implementing digital health interventions requires decisions about buying or building each technology-related component, all of which can lead to unanticipated issues.
objectivesThis study aimed to describe issues encountered from our "buy or build" decisions developing two digital health interventions over different timeframes, designed to use patient-generated health data to: (1) improve hypertension control and (2) measure and improve adherence to HIV-related medications.
methodsCONDUIT-HID (CONtrolling Disease Using Information Technology-Hypertension In Diabetes) was developed during 2010 to 2015 to allow patients receiving care from a multispecialty group practice to easily upload home blood pressure readings into their electronic health record and trigger clinician action if mean blood pressure values indicated inadequate control. USE-MI (Unobtrusive SEnsing of Medication Intake) was developed from 2016 to 2022 to allow entry of patients' HIV-related medication regimens, send reminders if patients had not taken their medications by the scheduled time(s), attempt to detect medication ingestion through machine learning analysis of smartwatch motion data, and present graphical adherence summaries to patients and clinicians.
resultsBoth projects required multiple "buy or build" decisions across all system components, including data collection, transfer, analysis, and display. We used commercial, off-the-shelf technology where possible, but virtually all of these components still required substantial custom development. We found that, even though our projects spanned years, issues related to our "buy or build" decisions stemmed from several common themes, including mismatches between existing and new technologies, our use case being new or unanticipated, technology stability, technology longevity, and resource limitations.
conclusionThose designing and implementing digital health interventions need to make numerous "buy or build" decisions as they create the technologies that underpin their intervention. These "buy or build" decisions, and the ensuing issues that will arise because of them, require careful planning, particularly if they represent an "edge case" use of existing commercial systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.