Improving discharge data fidelity for use in large administrative databases

Abstract

<jats:sec> <jats:title>Object</jats:title> <jats:p>Large administrative databases have assumed a major role in population-based studies examining health care delivery. Lumbar fusion surgeries specifically have been scrutinized for rising rates coupled with ill-defined indications for fusion such as stenosis and spondylosis. Administrative databases classify cases with the <jats:italic>International Classification of Diseases, Ninth Revision, Clinical Modification</jats:italic> (ICD-9-CM). The ICD-9-CM discharge codes are not designated by surgeons, but rather are assigned by trained hospital medical coders. It is unclear how accurately they capture the surgeon's indication for fusion. The authors first sought to compare the ICD-9-CM code(s) assigned by the medical coder according to the surgeon's indication based on a review of the medical chart, and then to elucidate barriers to data fidelity.</jats:p></jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>A retrospective review was undertaken of all lumbar fusions performed in the Department of Neurosurgery at the authors' institution between August 1, 2011, and August 31, 2013. Based on this review, the indication for fusion in each case was categorized as follows: spondylolisthesis, deformity, tumor, infection, nonpathological fracture, pseudarthrosis, adjacent-level degeneration, stenosis, degenerative disc disease, or disc herniation. These surgeon diagnoses were compared with the primary ICD-9-CM codes that were generated by the medical coders and submitted to administrative databases. A follow-up interview with the hospital's coders and coding manager was undertaken to review causes of error and suggestions for future improvement in data fidelity.</jats:p></jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>There were 178 lumbar fusion operations performed in the course of 170 hospital admissions. There were 44 hospitalizations in which fusion was performed for tumor, infection, or nonpathological fracture. Of these, the primary diagnosis matched the surgical indication for fusion in 98% of cases. The remaining 126 hospitalizations were for degenerative diseases, and of these, the primary ICD-9-CM diagnosis matched the surgeon's diagnosis in only 61 (48%) of 126 cases of degenerative disease. When both the primary and all secondary ICD-9-CM diagnoses were considered, the indication for fusion was identified in 100 (79%) of 126 cases. Still, in 21% of hospitalizations, the coder did not identify the surgical diagnosis, which was in fact present in the chart. There are many different causes of coding inaccuracy and data corruption. They include factors related to the quality of documentation by the physicians, coder training and experience, and ICD code ambiguity.</jats:p></jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>Researchers, policymakers, payers, and physicians should note these limitations when reviewing studies in which hospital claims data are used. Advanced domain-specific coder training, increased attention to detail and utilization of ICD-9-CM diagnoses by the surgeon, and improved direction from the surgeon to the coder may augment data fidelity and minimize coding errors. By understanding sources of error, users of these large databases can evaluate their limitations and make more useful decisions based on them.</jats:p></jats:sec>

Trends in hospitalization of preterm infants with intraventricular hemorrhage and hydrocephalus in the United States, 2000–2010

“…The potential for recording bias results in estimates of coding accuracy of approximately 80%. 4,6 This bias can affect not only coding of diagnoses but also covariates and complications. In addition, even though we used previously published methods of preventing double counting, 3 we cannot completely eliminate it, because of the lack of individual identifiers.…”

Adolescent idiopathic scoliosis: risk factors for complications and the effect of hospital volume on outcomes

“…21,31 First, the clinical characteristics coded in the NIS for individual records are based on ICD-9-CM coding defi- nitions. Although individual facilities employ certified medical coders for billing purposes, the possibility of the analyzed discharge records being subject to errors in coding and omissions cannot be ruled out.…”

Coder perspectives on physician-related barriers to producing high-quality administrative data: a qualitative study

“…3 High-quality administrative data, with accurate, specific, comprehensive and precise diagnostic codes, are therefore important for both research and decision-making. 5 However, known quality issues exist, especially with nonspecificity and imprecision. 3,[6][7][8][9][10] Most studies on barriers to coding that result in highquality administrative data have focused on coder-related barriers concerning their training, knowledge and evaluation standards.…”