Impact of the transition to ICD-10 on Medicare inpatient hospital payments.

OBJECTIVE: On October 1, 2013, the reporting of diagnoses and procedures in the U.S. will transition from the clinical modification of the ninth revision of the International Classification of Diseases (ICD-9-CM) to the tenth revision (ICD-10). We estimate the impact of conversion to ICD-10 on Medicare MS-DRG payments to hospitals using 2009 Medicare data. METHODS: Using the ICD-9-CM MS-DRG v27 (FY 2010), the converted ICD-10 MS-DRG v27, and the ICD-10 to ICD-9-CM Reimbursement Map for fiscal year 2010, we estimate the impact on aggregate payments to hospitals and the distribution of payments across hospitals. RESULTS: Although the transition from the ICD-9-CM to the ICD-10 version of MS-DRGs resulted in 1.68 percent of the patients being assigned to a different MS-DRG, payment increases and decreases due to the changes in MS-DRG assignment essentially netted out, resulting in a minimal impact on aggregate payments to hospitals (+0.05 percent) and on the distribution of payments across hospital types (-0.01 to +0.18 percent). Mapping ICD-10 data back to ICD-9-CM, and using the ICD-9-CM MS-DRGs, resulted in 3.66 percent of patients being assigned to a different MS-DRG, a modest decrease in aggregate payments to hospitals (-0.34 percent), and modest changes in the distribution of payments across hospital types (-0.14 to -0.46 percent). DISCUSSION: As demonstrated by MS-DRGs, a direct conversion of an application to ICD-10 can produce consistent results with the ICD-9-CM version of the application. However, the use of mappings between ICD-10 and ICD-9-CM will produce less consistent results, especially if the mapping is not tailored to the specific application.

Estimating the costs of potentially preventable hospital acquired complications.

California and Maryland hospital data are used to estimate the incremental cost associated with 64 categories of hospital acquired complications. The reason for admission, severity of illness at admission and the presence of hospital acquired complications are used in a linear regression model to predict incremental per patient cost yielding an adjusted R2 of 0.58 for Maryland data and 0.60 for California data. The estimated incremental cost due to each of the 64 categories of complications was consistent across both databases and accounted for an increase in total short term acute inpatient hospital cost of 9.39 percent in the California data and 9.63 percent in the Maryland data.