Abstract
Objective
To develop and test the accuracy of administrative claims method for identifying children with sickle cell disease (SCD) to enable quality of care assessments among children enrolled in Medicaid.
Methods
All administrative claims with a SCD diagnosis were obtained from Michigan Medicaid from 2008–2011 for children =>18 years, representing 1,828 individuals. All Medicaid claims were obtained for these children and classified into categories based on SCD care; these classifications were used to develop 37 alternative case definitions for identifying children with SCD. Children with ≥1 SCD claim in 2010 or 2011 were identified as confirmed SCD or not SCD using the gold standard of Michigan Newborn Screening (NBS) administrative records. Measures of performance were calculated for each case definition for eligible children in 2010. Further validation of the case definitions was performed among eligible children in 2011.
Results
In 2010, 938 children met eligibility criteria and were linked to NBS records; 605 (59%) were confirmed SCD, 333 (32%) were not SCD. Measures of performance varied among the 37 case definitions, and the 4 best case definitions based on the sensitivity and specificity were validated among 924 children meeting eligibility criteria in 2011. The case definition of 3 SCD claims in any position identified children with SCD with the most accuracy.
Conclusions
This definition can be used to facilitate a more accurate identification of children with SCD in future studies. Further investigation is necessary to determine if this method translates to other populations besides Michigan Medicaid.
Keywords: Sickle Cell Disease, Administrative Claims, Case Identification, Medicaid, children, Newborn Screening
Background
Sickle cell disease (SCD) is a chronic disease affecting mainly minority populations and is characterized by significant morbidity and mortality. SCD is estimated to currently affect 90,000–100,000 Americans (approximately 1 in 500 African American births); although variation exists among prevalence estimates.1–4 SCD has multiple clinically significant forms, further complicating estimates of the true burden of disease. There are six sickle cell genotypes; however, the most common variants are sickle cell anemia (Hemoglobin SS), Hemoglobin (Hb) SC, Hb S/Beta0 Thalassemia and Hb S/Beta+ Thalassemia.5 Children with SCD are at risk for chronic symptoms which can seriously impact quality of life, including pain episodes, severe anemia, and pulmonary complications.6,7 SCD can have devastating consequences among children if uncontrolled and can lead to potentially life-threatening complications. Children with SCD are 7–30 times more likely to be hospitalized, 2–6 times more likely to visit the emergency department, 300 times more likely to have a stroke, 100 times more likely to develop pneumococcal infection and have over 8 times the healthcare expenditures than their counterparts without SCD.8–11
Given these risks, it is essential that children with SCD have effective follow up immediately following birth and preventive services are obtained throughout childhood.7,12–14 At birth, all children are screened for SCD through statewide newborn screening (NBS) programs; however, many states may not have the technical capacity to link these results on an ongoing basis with Medicaid administrative claims. As accurate identification of the study population of children with SCD is integral for appropriate assessment of these quality of care measures, a claims-based definition is necessary Although quality of care assessments using administrative claims data have been previously developed for conditions such as asthma and diabetes,19,20,21–23 a mechanism to identify SCD cases using claims has not been validated. If successful, a claims-based method would offer important opportunities to evaluate population-based quality of care among children with SCD without requiring linkages to external data sources such as those maintained by state newborn screening programs. With that in mind, our objective was to develop and test the feasibility and accuracy of an administrative claims method for identifying children with SCD to enable quality of care assessments among children enrolled in Medicaid.
Methods
We developed and tested alternative methods for identifying children with SCD using Medicaid administrative claims data. We used a five step process which included: 1) acquisition of all Medicaid administrative claims for any child with at least one SCD claim; 2) classification of claims into meaningful groups relevant to SCD care; 3) development of alternative case definitions using these variables; 4) identification of the testing population to validate the accuracy of the alternative case definitions; and 5) testing the accuracy of the alternative case definitions to identify children with SCD.
Acquisition of claims
In partnership with the Michigan Department of Community Health (MDCH), we obtained all Medicaid administrative claims with a SCD ICD-9 diagnosis code for children 18 years or younger (all children included regardless of Medicaid enrollment status) during the period 2008 to 2011. Consistent with other studies and AHRQ Healthcare Cost and Utilization Project Single-Level Clinical Classification Software (HCUP CCS), we included claims with ICD-9 diagnosis codes for Hb SS (282.60, 282.61, 282.62), Hb SC (282.63, 282.64), Hb SD (282.68, 282.69), and Hb S beta thalassemia (282.41 and 282.42); we did not include sickle cell trait (282.5) or other hemoglobinopathies.24–27
A total of 66,274 SCD claims containing 304,289 revenue and/or procedure codes, representing 1,828 unique individuals were identified from 2008 to 2011. All Michigan Medicaid administrative claims were acquired for these 1,828 individuals for each year, including detailed enrollment (containing demographics and program eligibility information), provider, and claims. These data were linked to provide a comprehensive overview of paid services rendered to any child with a SCD claim. The claims tables included codes from all major healthcare coding schemes used to track patients and obtain reimbursement, including ICD-9-CM diagnoses codes, diagnosis related groups (DRGs), Uniform Billing (UB-92) codes, ICD-9-CM surgical codes, Current Procedural Terminology (CPT) codes, Healthcare Common Procedure Coding System (HCPCS), and national drug codes (NDC). A de-duplication process was implemented and claims were grouped together into events based on dates of service.
Classification of Claims
As a precursor to creating alternative case definitions, we classified individuals based on claims history relevant to SCD care using the extracted SCD claims. Our classification approaches were derived from methodologies published by AHRQ, NCQA Healthcare Effectiveness Data and Information Set (HEDIS), and Centers for Medicare and Medicaid Services (CMS).24,28,29 We started the process with a complete extraction of all SCD claims to maximize the likelihood that even diagnosis and procedure codes that were infrequently used would be given consideration in our approach. Interim results were share among the team of investigators that included substantial expertise in Medicaid claims data analyses, chronic disease epidemiology, newborn screening and statistical programming. Team members reviewed candidate case definitions based solely on one coding system (e.g., an outpatient definition using CPT codes) and evaluated the incremental advantages or disadvantages of including other coding schemas (e.g., an outpatient definition using both CPT and Revenue codes). These considerations were aided by tabular frequency counts of the number of unique individuals and event counts for each code as well as visual representations (e.g., Venn Diagrams). These methods were jointly reviewed by team members to evaluate the degree of overlap between code groups and the unique contribution of each code group in capturing distinct individuals with SCD. Using an iterative approach, we determine the degree to which each child had specific groups of claims representing meaningful categories of SCD care. We subsequently classified each child’s claims from several perspectives, ranging from simple counts of SCD claims to claim counts based on combinations of different SCD services.”
Development of Alternative Case Definitions
From our analysis of SCD claims groupings, we identified seven mutually exclusive claims categories: inpatient, outpatient, home health care, emergency department, blood transfusion, antibiotic prophylaxis, and hydroxyurea. In addition, two composite groups were formed: evaluation/consultation claims and an overall count of SCD claims (irrespective of type of service); Table 1 illustrates these categories as well as a listing of several additional categories that were considered but not included in the final case definitions. These nine categories served as the basis for the development of alternative case definitions to identify children with SCD from administrative claims. Table 2 illustrates the resultant 37 case definitions considered; the definitions reflect alternatives aimed at balancing inclusion of cases to maximize sensitivity with the addition of increasingly restrictive criteria to gain specificity. Alternative definitions were also considered based on whether the diagnosis code for SCD was reported as the primary diagnosis or any mention of SCD for ED and inpatient claims.
Table 1.
Claims Classifications included in Case Defintions
| Category | Definitions |
|---|---|
| Sickle Cell Disease Claim Count | Healthcare Cost and Utilization Clinical Classification Software (HCUP CCS) #61 for ICD-9-CM Codes (trait excluded) |
| Evaluation/Consultation | HCUP CCS #227 for Procedure Codes |
| Outpatient* | 99201–99205, 99211–99215, 99241–99245 |
| Emergency Department** | HCUP Emergency Department (ED) Utilization Flag |
| Inpatient Hospitalization*** | HCUP Cost-Center Clusters: RBU, SCU, NUR where facility type is outpatient- or inpatient-hospital. |
| Home Health Care | HCUP CCS #236 for Procedure Codes |
| Blood Transfusion | HCUP CCS #222 and Centers for Medicare and Medicaid Services (CMS) Cost-Center Cluster Blood Processing/Transfusion |
| Antibiotic Prophylaxis | Aminopenicillins, Beta-lactamase inhibitors, Macrolides, Miscellaneous antibiotics, Natural penicillins |
| Hydroxyurea | Hydroxyurea |
Codes for clinic care and preventive medicine were dropped due to low additional yield (1.1%) among the SCD cases.
CPT codes for ED were dropped due to low additional yield (6.9%) among the SCD cases, difficulty of processing claims lacking admission dates, discharge dates, and primary diagnosis.
CPT codes for Inpatient Hospitalization were dropped due to low additional yield (8.7%) among the SCD cases, difficulty of processing claims lacking admission dates, discharge dates, and primary diagnosis. (RBU=Routine Bed Units, SCU=Special Care Units, NUR=Nursery)
Other categories created but not used in case definition: Observation Stays, SCD Screening and Confirmatory Testing, Chemistry/Hematology Lab Claims, and Transracial Doppler.
Table 2.
Description of Case Definitions Developed for Identification of Children with Sickle Cell Disease (SCD)*
| Definition Number | All SCD Claims | Interview, Evaluation and Consultation Claims | Outpatient SCD Claims | Emergency Department SCD Claims | Inpatient SCD Claims | Combination of SCD Claims |
|---|---|---|---|---|---|---|
| 1 | 2 claims, any position | |||||
| 2 | 3 claims, any position | |||||
| 3 | 4 claims, any position | |||||
| 4 | 5 claims, any position | |||||
| 5 | 1 claim, any position | |||||
| 6 | 2 claims, any position | |||||
| 7 | 3 claims, any position | |||||
| 8 | 4 claims, any position | |||||
| 9 | 5 claims, any position | |||||
| 10 | 1 claim, any position | |||||
| 11 | 2 claims, any position | |||||
| 12 | 3 claims, any position | |||||
| 13 | 4 claims, any position | |||||
| 14 | 1 claim, any position | |||||
| 15 | 2 claims, any position | |||||
| 16 | 3 claims, any position | |||||
| 17 | 4 claims, any position | |||||
| 18 | 1 claim, primary position | |||||
| 19 | 2 claims, primary position | |||||
| 20 | 3 claims, primary position | |||||
| 21 | 4 claims, primary position | |||||
| 22 | 1 claim, any position | |||||
| 23 | 2 claims, any position | |||||
| 24 | 3 claims, any position | |||||
| 25 | 4 claims, any position | |||||
| 26 | 1 claim, primary position | |||||
| 27 | 2 claims, primary position | |||||
| 28 | 3 claims, primary position | |||||
| 29 | 4 claims, primary position | |||||
| 30 | At Least 1 Inpatient claim, primary position | |||||
| OR At Least 1 ED claim, primary position | ||||||
| OR At Least 4 outpaitent claims, any position | ||||||
| 31 | At Least 1 Inpatient claim, any position | |||||
| OR At Least 1 ED claim, any position | ||||||
| 32 | At Least 1 Inpatient claim, any position | |||||
| OR At Least 1 ED claim, any position | ||||||
| OR 4 SCD Outpatient claims, any position | ||||||
| 33 | At Least 1 Inpatient claim, any position | |||||
| OR At Least 1 ED claim, any position | ||||||
| OR 3 SCD Outpatient claims, any position | ||||||
| 34 | At Least 1 Inpatient claim, any position | |||||
| OR At Least 1 ED claim, any position | ||||||
| OR 2 SCD Outpatient claims, any position | ||||||
| 35 | At Least 1 Inpatient claim, any position | |||||
| OR At Least 1 ED claim, any position | ||||||
| OR 1 SCD Outpatient claim any position | ||||||
| 36 | At Least 1 Inpatient claim, any position | |||||
| OR At Least 1 ED claim, any position | ||||||
| OR At Least 1 outpatient claim, any position | ||||||
| OR At Least 1 home health care claim, any position | ||||||
| OR At Least 5 Blood Transfusions with a SCD Diagnosis | ||||||
| OR Had At Least 300 Days of Antibiotics (age 0–5 years) | ||||||
| 37 | At Least 1 Inpatient claim, any position | |||||
| OR 2 claims for either Outpatient or ED, any position | ||||||
All definitions list minimum number of required claims. For example, 2claims, any position corresponds to at least 2claims, any position.
Identification of Testing Population
We selected a subset of individuals initially identified in our SCD claims database to test the accuracy of the alternative case definitions. Our testing subset included children in 2010–2011 who were 1 to 18 years whohad at least one Medicaid SCD claim in either year, and had a Michigan NBS result available (requiring birth in the state of Michigan). Use of NBS records allowed children born 1987 and beyond who met inclusion criteria to be part of the testing population. In addition, we required continuous enrollment in Michigan Medicaid with no other forms of health insurance during the year of the SCD claim. Eligible children were linked to Michigan birth certificates using child’s name, birth date, and gender. Unlinked records were manually reviewed to attempt to locate a birth record. Birth records were subsequently linked to newborn screening (NBS) records maintained by MDCH using common variables.30 Records that were not automatically linked were reviewed manually to identify additional matches. Using NBS records, children were classified as confirmed SCD (Hb SS, Hb S/beta-thalassemia, Hb SC, and other variants), not SCD, or unknown status. Infants in Michigan with an abnormal hemoglobin result on their NBS are referred to a hematologist for confirmatory testing and medical management, if needed. A child is classified as confirmed SCD after receipt of disease confirmation by the NBS Follow-up Program.31 Children with normal hemoglobin results or abnormal hemoglobin results on their NBS but not SCD (e.g., sickle cell trait, Hb H disease, etc.) were classified as not SCD. Children without a documented NBS in Michigan were classified as unknown status and excluded from further analysis.
Testing of Alternative Case Definitions
We tested alternative case definitions in two phases. The initial phase of testing occurred among children meeting eligibility criteria in 2010 who had Medicaid claims that reported an SCD diagnosis code. These children were linked to NBS results and included individuals with confirmed SCD as well as others who had been confirmed as not SCD cases. Measures of performance were calculated for each of the 37 candidate case definitions including: sensitivity, specificity, positive predictive value, and the area under the receiver operating characteristic (ROC) curve; we used the confirmed SCD diagnosis from Michigan NBS administrative records as the gold standard. Based on the results of these measures of performance, we identified four case definitions as the strongest candidates for additional investigation. In the second phase of testing, we conducted a subsequent validation of these four case definitions using a set of candidate SCD cases identified independently in 2011. Once again, we calculated performance measures to identify which case definitions provided the most accurate identification of children with SCD. In addition, we explored the changes in the predictive values of this final case definition by adding a more labor-intensive measure of SCD-related medications to the definition: 1) had hydroxyurea and/or 2) had 300+ days of antibiotics from ages 0 to 5 years.
Results
Initial case definition testing was conducted among the subset of children continuously enrolled in Michigan Medicaid in 2010 who met eligibility criteria (n=1,033). After linkage to NBS records, 605 (59%) were confirmed SCD, 333 (32%) were confirmed not SCD, and 95 (9%) were unknown (and subsequently excluded). Among children with confirmed SCD (n=605), 49% were male, 87% were black, 61% were HbSS and the average age was 9.7 years (SD=5.5) (Table 3).
Table 3.
Characteristics of Children with an SCD in 2010 or 2011*
| 2010 | 2011 | ||
|---|---|---|---|
| SCD** n = 605 | Not SCD** n = 333 | SCD** n = 609 | Not SCD** n = 315 |
| 299 (49%) | 180 (54%) | 301 (49%) | 160 (51%) |
| 306 (51%) | 153 (46%) | 308 (51%) | 155 (49%) |
| 527 (87%) | 216 (65%) | 521 (86%) | 194 (61%) |
| 7 (1%) | 71 (21%) | 8 (1%) | 65 (21%) |
| 70 (12%) | 16 (5%) | 78 (13%) | 25 (8%) |
| 1 (<1%) | 30 (9%) | 2 (<1%) | 31 (10%) |
| 372 (61%) | -- | 357 (59%) | -- |
| 176 (29%) | -- | 199 (33%) | -- |
| 56 (9%) | -- | 52 (9%) | -- |
| 1 (<1%) | -- | 1 (<1%) | -- |
| 9.68 (5.47) | 7.11 (4.92) | 9.78 (5.52) | 6.77 (5.23) |
at least 1 Medicaid claim for SCD
determined from newborn screening
age is reported as mean age (years) and standard deviation
Measures of performance varied widely among the 37 case definitions (Table 4). Sensitivity ranged from 6.3% (definition 29) to 99.2% (definition 36, 5), specificity from 52% (definition 36) to 99.7% (definitions 20, 21, 24, 27, 28), positive predictive value from 79% (definition 36) to 99.3% (definitions 26, 27), and area under the ROC curve from 0.53 (definition 29) to 0.92 (definition 6). The top four case definitions based on the measures of performance were definitions 1, 2, 6 and 37 (Figure 1).
Table 4.
Measures of Performance for Case Definitions*
| Definition Number | Area Under the ROC Curve (95% Confidence Interval) | Sensitivity (%) | Specificity (%) | PPV (%) |
|---|---|---|---|---|
| 0.90 (0.88, 0.92) | 96.5 | 83.8 | ||
| 0.91 (0.89, 0.93) | 90.7 | 91.3 | ||
| 0.87 (0.85, 0.88) | 85.1 | 93.7 | ||
| 0.87 (0.85, 0.89) | 79 | 95.2 | ||
| 0.77 (0.74, 0.79) | 99.2 | 54.1 | ||
| 0.92 (0.90, 0.94) | 93.7 | 89.5 | ||
| 0.91 (0.89, 0.93) | 86.3 | 95.2 | ||
| 0.87 (0.85, 0.89) | 77.5 | 95.5 | ||
| 0.83 (0.81, 0.85) | 69.1 | 97.6 | ||
| 0.80 (0.77, 0.82) | 92.1 | 67 | ||
| 0.85 (0.83, 0.87) | 75.2 | 94.9 | ||
| 0.77 (0.75, 0.79) | 55.7 | 97.9 | ||
| 0.69 (0.67, 0.71) | 40 | 98.8 | ||
| 0.77 (0.74, 0.79) | 69.8 | 83.5 | ||
| 0.70 (0.68, 0.73) | 42.6 | 98.2 | ||
| 0.63 (0.62, 0.65) | 27.8 | 99.1 | ||
| 0.59 (0.57, 0.60) | 18 | 99.4 | ||
| 0.75 (0.73, 0.77) | 51.7 | 98.5 | ||
| 0.64 (0.62, 0.66) | 28.3 | 99.4 | ||
| 0.58 (0.57, 0.60) | 16.9 | 99.7 | ||
| 0.54 (0.53, 0.55) | 8.4 | 99.7 | ||
| 0.74 (0.72, 0.77) | 52.6 | 96.1 | ||
| 0.64 (0.63, 0.66) | 29.8 | 99.1 | ||
| 0.59 (0.57, 0.60) | 17.5 | 99.7 | ||
| 0.55 (0.54, 0.56) | 9.6 | ** | ||
| 0.72 (0.70, 0.74) | 44.3 | 99.4 | ||
| 0.61 (0.60, 0.63) | 22.8 | 99.7 | ||
| 0.56 (0.55, 0.57) | 12.6 | 99.7 | ||
| 0.53 (0.52, 0.54) | 6.3 | ** | ||
| 0.83 (0.81, 0.85) | 67.9 | 97.6 | ||
| 0.77 (0.75, 0.80) | 71.7 | 82.9 | ||
| 0.81 (0.79, 0.84) | 80 | 82.3 | ||
| 0.83 (0.80, 0.85) | 84.5 | 81.4 | ||
| 0.86 (0.83, 0.88) | 92.1 | 79.3 | ||
| 0.76 (0.73, 0.79) | 99.2 | 52.6 | ||
| 0.76 (0.73, 0.78) | 99.3 | 52 | ||
| 0.91 (0.89, 0.92) | 90.2 | 90.4 |
Children continuously enrolled in Michigan Medicaid in 2010 with either confirmed SCD or not SCD as identified by Newborn Screening records
Zero false positives cases
Figure 1.
Receiver Operating Characteristic (ROC) Curve of Alternative Case Definitions to Identify Children with Sickle Cell Disease using Administrative Claims, 2010*
* sensitivity and specificity determined using Michigan newborn screening results for Children Continuously Enrolled in Michigan Medicaid in 2010
Further validation of these 4 case definitions was conducted among 997 children meeting eligibility criteria in 2011. In this second phase of validation, a total of 609 children (61%) were confirmed SCD, 315 (32%) were confirmed not SCD, and 73 (7%) were unknown. Testing of these case definitions provided similar results to 2010, with case definition 2 (3 SCD-claims in any position) emerging as the most accurate identification of children with SCD when compared to the gold standard of NBS (Table 5). The addition of SCD-related medications to this case definition showed no improvement in accuracy beyond case definition 2’s original conception and was not considered further.
Table 5.
Measures of Performance for Top Four Performing Case Definitions*
| Definition Number | Description | Area Under the ROC Curve (95% Confidence Interval) |
Sensitivity (%) | Specificity (%) | PPV (%) |
|---|---|---|---|---|---|
| Had 2 SCD Claims in any position | 0.88 (0.86, 0.90) | 94.9 | 81.0 | ||
| Had 3 SCD Claims in any position | 0.91 (0.89, 0.93) | 89.7 | 92.4 | ||
| Had 2 Other Diagnostic Procedures in any position | 0.90 (0.88, 0.92) | 92.6 | 87.9 | ||
| Had at least 1 Inpatient Hospitalization with a SCD Diagnosis, OR | 0.90 (0.88, 0.92) | 90.2 | 90.4 | ||
| Had 2 visits in either an Outpatient or ED setting with a SCD Diagnosis |
Children continuously enrolled in Michigan Medicaid in 2011 with either confirmed SCD or not SCD as identified by Newborn Screening records, n = 924
Discussion
In this study, we successfully developed and tested an administrative claims-based method to accurately identify children with SCD. To date, no such method has systematically been tested for the identification of SCD cases at the population level. We found that a count of three paid SCD claims in a year – irrespective of type of service – is the most accurate administrative claims-based case definition to identify children with SCD. Although we also evaluated numerous other case definitions that were increasingly complex, none were superior in terms of accuracy. Although the confidence intervals for several of the final case definitions overlap, in contrast with the other alternatives, the SCD case definition identified as the most accurate identification of children with SCD through our analysis is straightforward to implement; SCD cases can be identified with a high degree of accuracy by finding individuals with three or more SCD claims annually. Notably, the selected case definition does not require the use of pharmacy claims, which are substantially more labor intensive and for which we observed no additional improvements in accuracy. The simplicity and accuracy of this approach suggests a high degree of feasibility for health plan quality of care assessments based solely on administrative claims data.
Our findings are novel for the identification of SCD cases, building upon similar approaches that have been used to validate claims-based case definitions for other chronic and acute conditions. Incident cases of breast cancer have previously been identified using a cancer registry as a gold standard; multiple logistic regression models which included claims-based predictors were investigated to estimate the probability of each model capturing a case.34 Similarly for pneumonia cases, claims based definitions have been compared to medical charts in several different settings to identify the most appropriate algorithms for identification of cases.35–37 Although our study is similar to these in the development of claims-based case definitions and their comparison to an assumed gold standard, the gold standard we employed may provide a more accurate mechanism to identify true cases. In this study, we used a genetic testing gold standard to validate our cases. In contrast, the gold standard source used in other studies has oftentimes involved medical record review or cases included in a disease registry; both of these methods are subject to incomplete case capture.
Although a claims-driven investigation of the accuracy of alternative SCD case definitions has not previously been performed, a prior study did compare the accuracy of one claims-based SCD case definition to cases identified through NBS.17 Additional studies have used different administrative claims methods to identify children SCD in the study population. Several studies have employed various combinations of administrative claims; one was based on combinations of hospitalizations and outpatient visits,17,18,32 while another study required only a single SCD-related claim.10,33 Such methods may introduce bias; our findings indicate that SCD case definitions such as these may lack sensitivity and miss cases while other case definitions may not be sufficiently specific and include children without SCD.
This study has several limitations. The case definitions considered in our study were examined using administrative claims for one state’s (Michigan) Medicaid program. Although differences exist between states’ administrative claims systems, the coding methods employed in as the basis for this study are widely used and are common to most claims extracts such as the Medicaid Analytic eXtract (MAX) files.38 Additionally, the incidence of SCD in Michigan (HbSS: 0.24 per 1,000 births; HbSC: 0.16 per 1,000 births; HbBeta Thalassemia: 0.04 per 1,000 births) is comparable to the national rate of SCD (HbSS:0.26 per 1,000 births; HbSC: 0.14 per 1,000 births; HbBeta Thalassemia: 0.03 per 1,000 births), indicating that the population of children with SCD in state of Michigan may be an appropriate reflection of SCD rates across the country. Our study was limited to children insured by Medicaid with no other forms of health insurance. Although 70% of children born in Michigan with SCD (1987–2008) have a Medicaid ID, it is possible that healthcare utilization among children not fully insured by Medicaid may differ from those with private insurance. Importantly, the methods explored in this study is predicated upon the completeness and accuracy administrative claims paid for SCD-related health services; children who do not have SCD-related healthcare encounters or claims that are not accurately coded may reduce the sensitivity of this method. Furthermore, this method does not reflect potential differences in the accuracy of administrative claims to identify genetic variants of SCD.Finally, although the case definition developed in our study was shown to be accurate among children in Michigan Medicaid, the effectiveness for identification of cases of SCD over the age of 18 remains untested.
The claims-based method for identifying children with SCD serves as an important foundation for studying multiple aspects of health among the population of children with SCD. The simplicity and accuracy of the method for SCD case identification developed in this study has multiple opportunities for application within the Pediatric Quality Measures Program (PQMP) as well as state Medicaid programs. The PQMP is aimed at expanding existing pediatric quality of care measures currently available for use by public and private health care purchasers through the Children’s Health Insurance Program Reauthorization Act (CHIPRA). The methods explored in our study will enable several important quality of care measure aimed at key aspects of care for children with SCD, including appropriate use of antibiotics and annual Transcranial Doppler (TCD) screening. Absent NBS data, we found that Medicaid administrative claims can be used to accurately identify SCD casesIt is important to note that the claims-based method developed in this study may be of value even in states where Medicaid claims for SCD cases can be identified by linkages with NBS data. Administrative claims-based case definitions can be used to identify SCD cases without a NBS result in state databases due to circumstances such as a child being born in a different state. In these cases, claims can accurately identify resident SCD cases that are enrolled in Medicaid, irrespective of the geographic location of their birth. Consequently, we believe that the administrative simplicity and accuracy of this approach will not only support SCD quality of care assessments, it can also be instrumental in assessing the comparative effectiveness of SCD treatments regimens, or supporting ongoing surveillance of state SCD populations.
What’s new.
We developed an administrative claims method for identifying children with sickle cell disease and demonstrated its accuracy using Newborn Screening data.
Project Support:
Agency for Healthcare Research and Quality (AHRQ) Cooperative Agreement, U18HS020516.
Footnotes
Potential conflicts of interest: None
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