ArticleJournal of the American Medical Informatics Association : JAMIA2019
A smart decision: smartphone use for operative data collection in arthroscopic shoulder instability surgery.
Article in Journal of the American Medical Informatics Association : JAMIA, 2019. 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, 4 citations in OpenAlex.
- Validation of a Smartphone-Based Institutional Electronic Data Capture System for Thumb Carpometacarpal Joint Arthroplasty.Hand (New York, N.Y.) · 2023Article
- Validation of a Novel Smartphone-Based Electronic Data Capture System Following Surgical Fixation of Distal Radial Fractures.Hand (New York, N.Y.) · 2023Article
- Associations of preoperative patient mental health status and sociodemographic and clinical characteristics with baseline pain, function, and satisfaction in patients undergoing primary shoulder arthroplasty.Journal of shoulder and elbow surgery · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveThis study tested validity, accuracy, and efficiency of the Orthopaedic Minimal Data Set Episode of Care (OME) compared with traditional operative report in arthroscopic surgery for shoulder instability. As of November 2017, OME had successfully captured baseline data on 97% of 18 700 eligible cases. MATERIALS AND
methodsThis study analyzes 100 cases entered into OME through smartphones by 12 surgeons at an institution from February to October 2015. A blinded reviewer extracted the same variables from operative report into a separate database. Completion rates and agreement were compared. They were assessed using raw percentages and McNemar's test (with continuity correction). Agreement between nominal variables was assessed by unweighted Cohen's kappa and a concordance correlation coefficient measured agreement between continuous variables. Efficiency was assessed by median time to complete.
resultsOf 37 variables, OME demonstrated equal or higher completion rates for all but 1 and had significantly higher capture rates for 49% (n = 18; P < .05). Of 33 nominal variables, raw proportional agreement was ≥0.90 for 76% (n = 25). Raw proportional agreement was perfect for 15% (n = 5); no agreement statistic could be calculated due to a single variable in operative note and OME. Calculated agreement statistic was substantial or better (κ > 0.61) for 51% (n = 17) for the 33 nominal variables. All continuous variables assessed (n = 4) demonstrated poor agreement (concordance correlation coefficient <0.90). Median time for completing OME was 103.5 (interquartile range, 80.5-151) seconds.
conclusionsThe OME smartphone data capture system routinely captured more data than operative report and demonstrated acceptable agreement for nearly all nominal variables, yet took <2 minutes to complete on average.
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.