Accuracy of Administrative Coding for Sickle Cell Disease

Background

Administrative data are increasingly used in sickle cell disease (SCD) research to study large numbers of patients at low cost.  However, the validity of research with these data depends on the accuracy of administrative coding, which has been understudied in SCD.  In particular, the validity of ICD-9CM coding for SCD’s clinical hallmark, vaso-occlusive crisis (VOC), has not been reported.  Therefore, we aim to describe the accuracy of ICD-9CM coding for VOC, acute chest syndrome (ACS), and acute splenic sequestration crisis (ASSC) in addition to SCD genotypes.

Methods

Administrative coding for all acute care visits (emergency department [ED], inpatient observation, and inpatient hospitalization) in SCD patients was captured for the 2013 calendar year at Children’s Medical Center Dallas (CMCD) by query of administrative records.  SCD visits were identified using the ICD-9CM codes 282.4x and 282.6x in the primary or any of 14 secondary code positions.  From the administrative data, VOC was defined by the use of the “in crisis” codes (282.42, 282.62, 282.64, or 282.69). ACS was defined by 517.3 and ASSC by 289.52.  Genotypes were defined as HbSS – 282.61 or 282.62; HbSC – 282.63 or 282.64; and HbS-BetaThal – 282.41 or 282.42.

For the chart review, all visits were independently evaluated by two reviewers with the senior author settling disagreements.  Previously-published consensus definitions were used for the complications of interest:  VOC was defined as new onset of pain lasting at last 4 hours for which there is no other explanation; ACS was defined by new pulmonary infiltrate on chest X-ray with associated fever or respiratory symptoms; and ASSC was defined as splenic enlargement leading to anemia (hemoglobin >2g/dL under baseline), typically with thrombocytopenia.  The primary reviewers and senior author evaluated 10 cases for the purpose of consensus-building before beginning data abstraction.

Data capture included demographics and cause of the visit.  The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+), and negative likelihood ratio (LR-) of ICD-9CM coding for VOC, ACS, ASSC, and the SCD genotype were calculated.  The LR+ and LR- were prevalence-weighted.

Results

From 448 patients, 1107 acute care visits were identified at CMCD in 2013. Patients had a median age of 8.2 years (range 0.1 – 33.9 years).  Females accounted for 53% of visits.  Inpatient hospitalization accounted for 374 visits (34%) whereas ED-only visits accounted for 681(61%) and inpatient observation 52 (5%).  The prevalence of SCD genotypes included 69% HbSS, 19% HbSC, and 7% HbS-BetaThal.  VOC, ACS, and ASSC were the “true cause” for 36% (n=402), 6% (n=68), and 1% (n=13) of acute care visits, respectively.

The results of the primary analyses are displayed in the table.  Agreement between reviewers for VOC and ACS was 91% (kappa = 0.80) and 99% (kappa = 0.92), respectively.  When VOC was falsely coded (n=176), the most common true diagnoses were ACS (26%), fever (24%), chronic pain exacerbation (14%), and abdominal pain (10%).  When ACS was falsely coded (n=21), VOC was the most common true diagnosis (71%).  Of 25 (2.2%) patients incorrectly coded for SCD, 14 had sickle trait.

Conclusions

ICD-9CM coding for VOC demonstrated poor accuracy; however, coding for ACS and ASSC was remarkably sensitive and specific.  Genotype coding lacked sensitivity with otherwise variable results.  Unfortunately, coding for SCD in ICD-10 differs minimally from ICD-9CM.  Therefore, these data provide an impetus to restructure ICD coding for SCD.

TABLE

	Sensitivity (95% CI)	Specificity (95% CI)	PPV (95% CI)	NPV (95% CI)	Postive Likelihood Ratio (95% CI)	Negative Likelihood Ratio (95% CI)
VOC	91.8 (88.6-94.2)	75.0 (71.6-78.2)	67.7 (63.6-71.6)	94.1 (91.8-95.9)	2.1 (1.8-2.4)	0.06 (0.04-0.08)
ACS	92.6 (83.0-97.3)	98.0 (96.9-98.7)	75.0 (64.1-83.5)	99.5 (98.8-99.8)	3.0 (2.0-4.4)	0.004 (0.002-0.01)
ASSC	92.3 (62.1-99.6)	99.8 (99.3-100.0)	85.7 (56.2-97.5)	99.9 (99.4-100.0)	6.0 (1.6-22.0)	0.0009 (0.0001-0.006)
HbSS genotype	74.2 (70.9-77.2)	67.7 (62.5-72.6)	83.8 (80.7-86.4)	53.8 (49.0-58.6)	5.1 (4.2-6.1)	0.9 (0.8-1.0)
HbSC genotype	31.0 (24.9-37.7)	99.6 (98.8-99.9)	94.3 (85.3-98.2)	85.8 (83.5-87.9)	16.5 (6.4-42.8)	0.16 (0.14-0.19)
HbS-BetaThal genotype	57.1 (45.4-68.2)	99.6 (98.9-99.9)	91.7 (79.1-97.3)	96.9 (95.6-97.8)	11 (4.3-28.2)	0.03 (0.02-0.05)