Transition From Pediatric To Adult Care Of High Cost Patients In a Medicaid Population With Sickle Cell Disease
Bibliographic record
Abstract
Abstract Introduction Though healthcare costs associated with the management of sickle cell disease (SCD) can be high, costs are not evenly distributed both across patients and across age groups; a small fraction of SCD patients incur a large share of healthcare costs and costs tend to increase as patients transition from pediatric to adult care setting. The aim of this study was to identify high cost SCD patients (HCSPs) and analyze cost patterns throughout lifetime and as they transition from pediatric to adult care. Method State Medicaid data from FL (1998-2009), NJ (1996-2009), MO (1997-2010), IA (1998-2010), and KS (2001-2009) were used for this study. Patients with ≥2 SCD diagnoses (ICD-9 282.6x) and ≥1 blood transfusion were included in the analysis. Patients were followed for as long as they were enrolled in Medicaid. HCSPs were defined as the fraction of most expensive patients accounting for 50% of the total average yearly cost. The share of the average total yearly cost represented by HCSPs was analyzed by age group and by type of setting (inpatient [IP], outpatient [OP], emergency department [ED], and other). Understanding that periodic events associated with high costs are likely to be responsible for high total costs, high cost events (HCEs), defined as quarters with costs ≥$33,095, corresponding to the amount separating the top 5% most expensive quarters observed in the sample, were analyzed. A longitudinal logistic regression model was used to assess associations between HCEs and transition age (16-20 years old), transfusions, hydroxyurea use, and SCD complications (pain, stroke, leg ulcers, avascular necrosis, infections, as well as pulmonary, renal, and cardiovascular events). Other covariates included transfusions during the previous quarter, other relevant medications (e.g.: pain medication, diuretics, anticoagulants), comorbidities (e.g.: hypertension, myocardial infarction, liver disease), and, serving as proxies for overall health status, the frequency of OP, IP, and ED visits during the previous quarter. Results From the cohort of 3,208 SCD patients (FL: 1,550, NJ: 992, MO: 489, KS: 121, IA: 56) who were eligible, 449 (14%) accounted for 50% of the total average yearly cost and were classified as HCSPs. HCSPs were observed on average (standard deviation [SD]) 6.39 (3.30) years, compared to 6.57 (3.24) years for other patients (p=0.2697). The average (SD) yearly total costs of HCSPs was statistically significantly higher at $108,524 ($52,900) per year compared to $17,683 ($15,037) per year for other patients (p<.0001). The share of the total yearly costs of HCSPs increased from 34.4% to 46.3% between age groups 11-15 and 16-20, reaching its maximum at 65.2% in the 26-30 age group. Average (SD) yearly hospitalization costs were $56,669 ($67,287) for HCSPs aged 11-15, accounting for 61.9% of their average total yearly costs. Average (SD) hospitalization costs increased sharply in transitioning HCSPs to reach $81,918 ($87,919), representing 74.9% of their average total yearly costs. Accordingly, the frequency of HCEs increased by 122.6% in the transitioning group from 0.110 HCE/year among patients aged 11-15 to 0.244 HCE/year among patients aged 16-20. The regression analysis indicated that patients were more likely to have a HCE during the post-transition period (age group 16-20, odds ratio [OR]: 1.41, p=.0046; age group >20, OR: 1.62, p=.0024) and when experiencing an SCD complication (OR: 3.79, p<.0001). Blood transfusions received during the previous quarter were associated with a lower likelihood of HCEs (OR: 0.87, p=.0080). Conclusion In this sample of Medicaid patients with SCD, 14% of patients were responsible for 50% of total yearly healthcare costs. Inpatient services accounted for the largest share of costs and this share increased in parallel with the frequency of high cost events in patients transitioning from pediatric to adult care, consistent with the increasing rate of SCD-related complications and inpatient admissions during that period reported in previous studies. Directing appropriate and targeted interventions including prophylaxis blood transfusion when indicated can help assist providers improve outcomes and lower healthcare costs in this patient population. Disclosures: Blinder: Novartis Pharmaceuticals: Consultancy, Research Funding. Sasane:Novartis Pharmaceuticals: Employment. Fortier:Novartis Pharmaceuticals: Research Funding. Paley:Novartis Pharmaceuticals: Employment. Duh:Novartis Pharmaceuticals: Research Funding. Vekeman:Novartis Pharmaceuticals: Research Funding.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".