Clara E Dismuke1. 1. Center for Health Economic and Policy Studies and Department of Health Administration and Policy, Medical University of South Carolina, Charleston 29425, USA. dismuke@musc.edu
Abstract
BACKGROUND: ICD-9-CM procedure codes in inpatient claims data are used for a wide range of purposes, such as monitoring utilization, costs, and quality, and adjusting for patient risk. However, many procedures may be underreported because they are not required for reimbursement via Diagnosis-Related Group (DRG) assignment (non-DRG procedures). OBJECTIVES: This study examined the extent and variability of ICD-9-CM procedure code reporting for 2 commonly employed non-DRG imaging procedures, computerized tomography (CT) and magnetic resonance imaging (MRI). RESEARCH DESIGN: Using nonfederal hospital inpatient claims (n = 56,091) from Washington State Inpatient Data for 1997, ICD-9-CM procedure and Universal Billing revenue codes for CT and MRI were compared by payer and hospital characteristics. RESULTS: When compared with revenue codes, ICD-9-CM procedure coding was found to be considerably underreported and variable, with only 33% of CT and 43% of MRI procedures being recorded. Moreover, the frequency of underreporting of both procedures did not appear to be random, with 31 of 72 hospitals that reported revenue codes for the CT not recording any ICD-9-CM codes for the procedure. Of the 48 hospitals that reported revenue codes for the MRI, 15 failed to record any ICD-9-CM codes that indicated its use. Statistically significant differences in median coding frequencies by teaching and rural status were found for both procedures, while ownership was an important factor in CT reporting variability. CONCLUSIONS: This nonrandom variability in reporting can potentially bias utilization studies as well as risk-adjustment outcome estimates of techniques that rely on reporting of these procedures (eg, APR-DRG and AHRQ CCS). An effort to define a universally agreed upon list of non-DRG procedures to be coded in all US hospitals would greatly improve the capacity of health services researchers to conduct important utilization, outcome and policy studies.
BACKGROUND: ICD-9-CM procedure codes in inpatient claims data are used for a wide range of purposes, such as monitoring utilization, costs, and quality, and adjusting for patient risk. However, many procedures may be underreported because they are not required for reimbursement via Diagnosis-Related Group (DRG) assignment (non-DRG procedures). OBJECTIVES: This study examined the extent and variability of ICD-9-CM procedure code reporting for 2 commonly employed non-DRG imaging procedures, computerized tomography (CT) and magnetic resonance imaging (MRI). RESEARCH DESIGN: Using nonfederal hospital inpatient claims (n = 56,091) from Washington State Inpatient Data for 1997, ICD-9-CM procedure and Universal Billing revenue codes for CT and MRI were compared by payer and hospital characteristics. RESULTS: When compared with revenue codes, ICD-9-CM procedure coding was found to be considerably underreported and variable, with only 33% of CT and 43% of MRI procedures being recorded. Moreover, the frequency of underreporting of both procedures did not appear to be random, with 31 of 72 hospitals that reported revenue codes for the CT not recording any ICD-9-CM codes for the procedure. Of the 48 hospitals that reported revenue codes for the MRI, 15 failed to record any ICD-9-CM codes that indicated its use. Statistically significant differences in median coding frequencies by teaching and rural status were found for both procedures, while ownership was an important factor in CT reporting variability. CONCLUSIONS: This nonrandom variability in reporting can potentially bias utilization studies as well as risk-adjustment outcome estimates of techniques that rely on reporting of these procedures (eg, APR-DRG and AHRQ CCS). An effort to define a universally agreed upon list of non-DRG procedures to be coded in all US hospitals would greatly improve the capacity of health services researchers to conduct important utilization, outcome and policy studies.
Authors: Steven T Fleming; Heath B Mackley; Fabian Camacho; Eric E Seiber; Niraj J Gusani; Stephen A Matthews; Jason Liao; Tse-Chuan Yang; Wenke Hwang; Nengliang Yao Journal: J Rural Health Date: 2013-06-26 Impact factor: 4.333
Authors: Steven T Fleming; Ann S Hamilton; Susan A Sabatino; Gretchen G Kimmick; Xiao-Cheng Wu; Jean B Owen; Bin Huang; Wenke Hwang Journal: Med Care Date: 2014-09 Impact factor: 2.983