Evidence map›Paper›PMID 33435704›Full record

ArticleJournal of diabetes science and technology2022

Smart Insulin Pens: Advancing Digital Transformation and a Connected Diabetes Care Ecosystem.

Tejaswi Kompala, Aaron B Neinstein

Abstract read
In one paragraph

Article in Journal of diabetes science and technology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Connected Insulin Pens and Pen Caps: Expanding Diabetes Technology Access and Adoption.Diabetes spectrum : a publication of the American Diabetes Association · 2025
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. STYLCONNECT Study: An Assessment of Automatic Data Collection Devices by People Living with Diabetes and Using an Insulin Pen.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2023
    Article
  12. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Tejaswi KompalaDepartment of Medicine, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0002-4492-5035
Aaron B NeinsteinDepartment of Medicine, University of California, San Francisco, San Francisco, CA, USA.ORCID 0000-0002-9774-7180

Funding

DIABETES, ENDOCRINOLOGY &METABOLISM TRAINING PROGRAMT32DK007418 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI EDWARD C HSIAO · 1986 to 2026
$14.3M
NIDDK NIH HHS T32 DK007418
6 · The paper itself

Abstract

With the first commercially available smart insulin pens, the predominant insulin delivery device for millions of people living with diabetes is now coming into the digital age. Smart insulin pens (SIPs) have the potential to reshape a connected diabetes care ecosystem for patients, providers, and health systems. Existing SIPs are enhanced with real-time wireless connectivity, digital dose capture, and integration with personalized dosing decision support. Automatic dose capture can promote effective retrospective review of insulin dose data, particularly when paired with glucose data. Patients, providers, and diabetes care teams will be able to make increasingly data-driven decisions and recommendations, in real time, during scheduled visits, and in a more continuous, asynchronous care model. As SIPs continue to progress along the path of digital transformation, we can expect additional benefits: iteratively improving software, machine learning, and advanced decision support. Both these technological advances, and future care delivery models with asynchronous interactions, will depend on easy, open, and continuous data exchange between the growing number of diabetes devices. SIPs have a key role in modernizing diabetes care for a large population of people living with diabetes.

Indexed as

Diabetes MellitusEcosystemHumansInsulinInsulin Infusion SystemsMachine LearningInsulindiabetes mellitusdigital healthinsulin deliverytelehealth

Identifiers

PMID33435704
PMCPMC9294591

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.