ArticleApplied clinical informatics2019
Evaluation of Secure Messaging Applications for a Health Care System: A Case Study.
Article in Applied clinical informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 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
29 citing papers in PubMed.
- Clinician-Patient Asynchronous Text Messaging Communication in Hospital-at-Home Care: Qualitative Study.Journal of medical Internet research · 2026Article
- Secure Messaging Workload and the Effect of an Enhanced Workflow Intervention Among Hospitalist Clinicians.Journal of general internal medicine · 2026Article
- A scoping review of studies on secure messaging through patient portals: persistent challenges and potential solutions.npj health systems · 2026Article
- When practice outpaces policy: Whatsapp use among nursing and medical staff in Israeli hospitals.Israel journal of health policy research · 2026Article
- Social Network Analysis of Secure Text Messaging Metadata During Clinical Deterioration in an Inpatient Children's Hospital Setting.Journal of medical systems · 2025Article
- Association Between Conversational Multitasking and Clinician Work Behaviors at a Large US Health Care System: Cohort Study.Journal of medical Internet research · 2025Observational
- Association of EHR-Integrated Secure Messaging Use with Clinician Workload and Attention Switching.Journal of general internal medicine · 2025Article
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- The blue tick: WhatsApp as a care tool in pediatric palliative care.BMC palliative care · 2025Article
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- Advancing orthopaedic trauma care through WhatsApp: An analysis of clinical and non-clinical applications, challenges, and future directions.World journal of orthopedics · 2024Review
- Contributors to Electronic Health Record-Integrated Secure Messaging Use: A Study of Over 33,000 Health Care Professionals.Applied clinical informatics · 2024Article
- Privacy and confidentiality of emergency department patient information: Contemporary considerations and challenges.Journal of the American College of Emergency Physicians open · 2024Article
- Adapting Physical Therapy Practice for the "Short-Stay" Total Joint Arthroplasty Patient: A Commentary.HSS journal : the musculoskeletal journal of Hospital for Special Surgery · 2024Article
- Characterizing the Patterns of Electronic Health Record-Integrated Secure Messaging Use: Cross-Sectional Study.Journal of medical Internet research · 2023Observational
- Asynchronous Conferencing Through a Secure Messaging Application Increases Reporting of Medical Errors in a Mature Trauma Center.Journal of patient safety and risk management · 2023Article
- Texting is caring: a content analysis of clinical text messages by hospitalists.BMJ open quality · 2023Article
- Improving Communication in a Large Urban Academic Safety Net Hospital System: Implementation of Secure Messaging.Journal of medical systems · 2023Article
- Management of Onsite and Remote Communication in Oncology Hospitals: Data Protection in an Era of Rapid Technological Advances.Journal of personalized medicine · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe use of text messaging in clinical care has become ubiquitous. Due to security and privacy concerns, many hospital systems are evaluating secure text messaging applications. This paper highlights our evaluation process, and offers an overview of secure messaging functionalities, as well as a framework for how to evaluate such applications.
methodsApplication functionalities were gathered through literature review, Web sites, speaking with representatives, demonstrations, and use cases. Based on similar levels of functionalities, vendors were grouped into three tiers. Essential and secondary functionalities for our health system were defined to help narrow our vendor choices.
resultsWe stratified 19 secure messaging vendors into three tiers: basic secure communication, secure communication within an existing clinical application, and dedicated communication and collaboration systems. Our essential requirements revolved around functionalities to enhance security and communication, while advanced functionalities were mostly considered secondary. We then narrowed our list of 19 vendors to four, then created clinical use cases to rank the final vendors. DISCUSSION: When evaluating a secure messaging application, numerous factors must be considered in parallel. These include: what clinical processes to improve, archiving text messages, mobile device management, bring your own device policy, and Wi-Fi architecture.
conclusionSecure messaging applications provide a Health Insurance Portability and Accountability Act (HIPAA) compliant communication platform, and also include functionality to improve clinical collaboration and workflow. We hope that our evaluation framework can be used by other health systems to find a secure messaging application that meets their needs.
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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.