Closing the osteoporosis care gap – Increased osteoporosis awareness among geriatrics and rehabilitation teams
Bibliographic record
Abstract
BACKGROUND: A care gap exists between recommendations and practice regarding the diagnosis and treatment of osteoporosis in fracture patients. The current study was designed to determine rates and predictors of in-hospital diagnosis and treatment of osteoporosis in patients admitted with fragility hip fractures, and to assess differences in these rates since the outset of the multipronged "Fracture? Think Osteoporosis" (FTOP) Program, which includes education of geriatrics and rehabilitation teams. METHODS: This is a retrospective cohort study conducted with data from two Hamilton, Ontario, university-based tertiary-care hospitals, and represents a follow-up to a previous study conducted 8 years earlier. Data pertaining to all 354 patients, age > or = 50, admitted between March 2003 and April 2004, inclusive, with a diagnosis of fragility hip fracture were evaluated. Twelve patients were excluded leaving 342 patients for analysis, with 75% female, mean age 81.Outcomes included: Primary -- In-hospital diagnosis of osteoporosis and/or initiation of anti-resorptive treatment ("new osteoporosis diagnosis/treatment"). Secondary -- In-hospital mortality, BMD referrals, pre-admission osteoporosis diagnosis and treatment. RESULTS: At admission, 27.8% of patients had a pre-existing diagnosis of osteoporosis and/or were taking anti-resorptive treatment. Among patients with no previous osteoporosis diagnosis/treatment: 35.7% received a new diagnosis of osteoporosis, 21% were initiated on anti-resorptive treatment, and 14.3% received a BMD referral. The greatest predictor of new osteoporosis diagnosis/treatment was transfer to a rehabilitation or geriatrics unit: 79.5% of rehabilitation/geriatrics versus 18.5% of patients receiving only orthopedics care met this outcome (p < 0.001). CONCLUSION: New diagnosis of osteoporosis among patients admitted with hip fracture has improved from 1.8% in the mid 1990's to 35.7%. Initiation of bisphosphonate therapy has likewise improved from 0% to 21%. Although multiple factors have likely contributed, the differential response between rehabilitation/geriatrics versus orthopedics patients suggests that education of the geriatric and rehabilitation teams, including one-on-one and group-based sessions, implemented as part of the FTOP Program, has played a role in this improvement. A significant care gap still exists for patients discharged directly from orthopedic units. The application of targeted inpatient and post-discharge initiatives, such as those that comprise the entire FTOP Program, may be of particular value in this setting.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".