Hydroxycarbamide adherence and cumulative dose associated with hospital readmission in sickle cell disease: a 6‐year population‐based cohort study

Abstract

Sickle cell disease (SCD) is a congenital haemoglobinopathy that causes frequent acute care/emergency room visits and hospital admissions for affected individuals. Evidence from population-based studies demonstrating the role of hydroxycarbamide (HC, also termed hydroxyurea) in reducing hospital readmission rates is limited. Our objective was to describe the use of HC and its association with acute care utilization and readmission rates using a large, nationally-representative US health insurance claims database over a 6-year period between 2009 and 2014. We identified 20 721 SCD-related inpatient and acute care encounters. Patients had been exposed to HC within 6 months prior to admission in 4263 (21%) of SCD-related admission events. HC use was more common among children aged 10-17 years and young adults aged 18-29 years. HC was associated with lower 30-day all-cause readmission rates in adults treated with average daily doses ≥1 g (odds ratio [OR], 0·72, 95% confidence interval [CI] 0·52-0·99) and doses of 0·5-1 g (OR, 0·73, 95% CI 0·57-0·93), compared to HC treatment with average daily doses of <0·5 g; adherence to HC with proportion of days covered of ≥0·80 was also associated with significantly lower 30-day all-cause readmission risks (OR, 0·59, 95% CI 0·41-0·84). Optimal therapeutic dosing and adherence to HC treatment significantly reduces 30-day readmissions among patients with SCD.

<p>Patient-Reported Outcomes and Economic Burden of Adults with Sickle Cell Disease in the United States: A Systematic Review</p>

“…The key characteristics of 15 included studies are presented in Table 3. [30][31][32][33][34][35][36][37][38][39][40][41][42][43][44] Five retrospective studies evaluated electronic medical records (EMRs) [33][34][35]38,42 and nine studies were retrospective database analyses. [30][31][32]36,37,39,40,43,44 One study used data from the Sickle Cell Data Collection Program, a registry collecting data from Georgia and California.…”

“…[30][31][32][33][34][35][36][37][38][39][40][41][42][43][44] Five retrospective studies evaluated electronic medical records (EMRs) [33][34][35]38,42 and nine studies were retrospective database analyses. [30][31][32]36,37,39,40,43,44 One study used data from the Sickle Cell Data Collection Program, a registry collecting data from Georgia and California. 41 Fourteen studies reported on HCRU, 30,[32][33][34][35][36][37][38][39][40][41][42][43][44] while one reported direct medical costs.…”

“…[30][31][32]36,37,39,40,43,44 One study used data from the Sickle Cell Data Collection Program, a registry collecting data from Georgia and California. 41 Fourteen studies reported on HCRU, 30,[32][33][34][35][36][37][38][39][40][41][42][43][44] while one reported direct medical costs. 31 The Impact of SCD on HCRU…”

Administrative data identify sickle cell disease: A critical review of approaches in U.S. health services research

“…Administrative data are often used for population-level assessments of utilization of care or expenditures, especially for conditions with low prevalence. For example, U.S. insurance claims databases, both Medicaid and private insurance, have been used to estimate medical costs, 2,3,32,33 uptake of antibiotic prophylaxis, 19,26,28,31,34,48 documented receipt of immunizations, 31,34,47,57 use of hydroxyurea, 35,37,55,[58][59][60][61][62][63] and receipt of transcranial doppler (TCD) screening among individuals with SCD. 27,31,38,46,47,[64][65][66] Some of those studies, especially ones published in the past 5 years, merged NBS or clinical databases, which were used to identify cases of SCD, with linked claims data that were used to track utilization of services.…”

“…Paulukonis et al proposed the combination of an ICD-9-CM code for SCD in at least two healthcare encounters, independent of setting, and at least one code for an associated treatment, procedure, or complication of SCD, 54 an approach recently adapted by other researchers. 55,56 However, Snyder et al reported that algorithm had a false-negative rate (1 minus sensitivity) of 14.2%, compared with 4.0% for one requiring 3 diagnostic claims. 23…”