Lowering Developmental Screening Thresholds and Raising Quality Improvement for Preterm Children
Bibliographic record
Abstract
OBJECTIVES: To determine: 1) if preterm children were referred, identified and received early intervention (EI)/ early childhood special education (ECSE) services at rates equivalent to term children after implementation of a universal, periodic Ages and Stages Questionnaire (ASQ) surveillance and screening system; 2) if pediatricians sufficiently lowered their screening thresholds with preterm children;and 3) if quality improvement opportunities exist. PATIENT AND METHODS: Secondary analysis was performed on 64 lower-risk, mostly late-preterm and 1363 term children who originally presented to their 12- or 24-month well- visits. Higher-risk preemies already involved with an EI agency/ identified with a delay were excluded. Board-certified pediatricians (N=18), and nurse practitioners (N = 2), blind to the ASQ results, were secondary participants. Differences between preterm and term developmental agency referrals were examined comparing Pediatric Developmental Impression to the ASQ under natural clinic conditions using a combined in-office or mail-back data collection protocol. Medical record and county EI/ECSE follow-up outcomes were conducted at 36 to 60 months. RESULTS: At 12 and 24 months, preterm (versus term) referral rates were 9.5%(versus 5.6%) with Pediatric Developmental Impression and 26.2% (versus 8.1%) with the ASQ. By 36 to 60 months, 37.5% of preterm (20.8% term) children were referred to EI/ECSE; of which, 50.0% of preterm (42.4% term) children were eligible for services, 54.2%of preterm children were identified with a developmental-behavioral disorder and 29.2% of preterm (20.8% term) children did not follow-up. For ASQ-only preterm referrals,55.6% were subsequently diagnosed with a developmental delay and/or disorder.Preterm children were 2 times more likely to be eligible than term children [corrected]. CONCLUSIONS: Combined referral, quality improvement and outcome data suggests that clinicians should lower their threshold for administering a psychometrically sound developmental screen when providing surveillance for ex-preemies. Quality improvement opportunities exist with diligent developmental surveillance and a more collaborative, standardized, reliable and interpersonal referral process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".