Evidence map›Paper›PMID 24319621›Full record

ArticleGeriatric orthopaedic surgery & rehabilitation2013

Patients' response toward an automated orthopedic osteoporosis intervention program.

Matthew A Varacallo, Edward J Fox, Emmanuel M Paul, Susan E Hassenbein, Pamela M Warlow

Open access · goldAbstract read
In one paragraph

Article in Geriatric orthopaedic surgery & rehabilitation, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 27% of its field
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 citations in OpenAlex.

  1. Pooled it
  2. Review
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  4. Article
  5. Review
  6. Deep learning for osteoporosis screening using an anteroposterior hip radiograph image.European journal of orthopaedic surgery & traumatology : orthopedie traumatologie · 2024
    Article
  7. Article
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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

5 authors at 1 institution in 1 country.

Matthew A VaracalloDepartment of Orthopaedics and Rehabilitation, Penn State Hershey Medical Center, Hershey, PA, USA.
Edward J Fox
Emmanuel M Paul
Susan E Hassenbein
Pamela M Warlow
Penn State Milton S. Hershey Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Osteoporosis is overshadowed in an era of chronic illnesses, and a care gap exists between physicians and patients. The aim of this study was to determine the effectiveness of implementing an automated system for identifying and sending a letter to patients at high risk for osteoporosis. Patients 50 years of age and older were tagged with an International Classification of Diseases, Ninth Revision, diagnostic code upon initial visit to the emergency department (ED), identifying potential fragility fractures. Automatically generated letters were sent via our osteoporosis database system to each patient 3 months after the initial visit to the ED. The letter indicated that he or she was at risk for osteoporosis and suggested that the patient schedule a follow-up appointment with a physician. Patients were subsequently telephoned 3 months after receiving the letter and asked about their current plan for follow-up. The control group did not receive a letter after departure from the ED. In the control group, 84 (85.71%) individuals of the total 98 did not have any follow-up but the remaining 14 (14.29%) sought a follow-up. In the intervention group, 62 (60.19%) individuals of 103 did schedule a follow-up, while the remaining 41 (39.81%) did not seek a follow-up. Thus, the patient follow-up response rate after fracture treatment improved with intervention (P < .0001). Current literature has demonstrated the low rate of follow-up care addressing osteoporosis in patients experiencing fragility fractures (1%-25% without intervention). Research has shown the effectiveness of various types of intervention programs for improving the continuum of care for these high-risk patients. Nonautomated intervention programs can have a multitude of human-related system failures in identifying these patients. Our study successfully implements an automated system that is able to be applied to most hospitals with minimal cost and resources.

Indexed as

economics of medicinefragility fracturesgeriatric medicinegeriatric traumaosteoporosissystems of caretrauma surgery

Identifiers

PMID24319621
PMCPMC3848331
OpenAlexW2163115675

What Socratic 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 Socratic graph.