Modifying DRG-PPS to include only diagnoses present on admission: financial implications and challenges.
ABSTRACT The inability to distinguish complications acquired in hospital from comorbid conditions that are present on admission (POA) has long hampered the use of claims data in quality and safety research. Now pay-for-performance initiatives and legislation requiring Medicare to reduce payment for acquired infections add imperative for POA coding. This study used data from 2 states currently coding POA to assess the financial impact if Medicare pays based on POA conditions only and to examine the challenges in implementing POA coding.
Medicare payments were calculated based first on all diagnoses and then on POA diagnoses in the Medicare discharge abstracts from California and New York in 2003, using the Diagnosis Related Group (DRG)-based Prospective Payment System (PPS) formula. The potential savings that result from excluding non-POA diagnoses were calculated. Patterns of POA coding were explored.
Medicare could have saved $56 million in California, $51 million in New York, and $800 million nationwide in 2003 had it paid hospital claims based only on POA diagnoses. Approximately 15% of the claims had non-POA codes, but only 1.4% of the claims were reassigned to lower-cost DRGs after excluding non-POA diagnoses. Excluding non-POA diagnoses resulted in reduced payment for operating costs, but increased outlier payments because some of the claims were designated as "unusually high cost" in the lower-cost DRGs. POA coding patterns suggest some problems in current POA coding.
To be consistent with pay-for-performance principles and make claims data more useful for quality assurance, incorporating POA coding into DRG-PPS could produce sizable savings for Medicare.
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ABSTRACT: The Department of Veterans Affairs (DVA) National Surgical Quality Improvement Program (NSQIP) employs trained nurse data collectors to prospectively gather preoperative patient characteristics and 30-day postoperative outcomes for most major operations in 123 DVA hospitals to provide risk-adjusted outcomes to centers as quality indicators. It has been suggested that routine hospital discharge abstracts contain the same information and would provide accurate and complete data at much lower cost. With preoperative risks and 30-day outcomes recorded by trained data collectors as criteria standards, ICD-9-CM hospital discharge diagnosis codes in the Patient Treatment File (PTF) were tested for sensitivity and positive predictive value. ICD-9-CM codes for 61 preoperative patient characteristics and 21 postoperative adverse events were identified. Moderately good ICD-9-CM matches of descriptions were found for 37 NSQIP preoperative patient characteristics (61%); good data were available from other automated sources for another 15 (25%). ICD-9-CM coding was available for only 13 (45%) of the top 29 predictor variables. In only three (23%) was sensitivity and in only four (31%) was positive predictive value greater than 0.500. There were ICD-9-CM matches for all 21 NSQIP postoperative adverse events; multiple matches were appropriate for most. Postoperative occurrence was implied in only 41%; same breadth of clinical description in only 23%. In only four (7%) was sensitivity and only two (4%) was positive predictive value greater than 0.500. Sensitivity and positive predictive value of administrative data in comparison to NSQIP data were poor. We cannot recommend substitution of administrative data for NSQIP data methods.Journal of the American College of Surgeons 04/2002; 194(3):257-66. · 4.50 Impact Factor
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ABSTRACT: This study examined the validity of the Complications Screening Program (CSP) by testing whether (1) ICD-9-CM codes used to identify a complication are coded completely and accurately and (2) the CSP algorithm successfully separates conditions present on admission from those occurring in the hospital. We compared diagnosis and procedure codes contained in the Medicare claim with codes abstracted from an independent re-review of more than 1,200 medical records from Connecticut and California. Eighty-nine percent of the surgical cases and 84% of the medical cases had their CSP trigger codes corroborated by re-review of the medical record. For 13% of the surgical cases and 58% of the medical cases, the condition represented by the code was judged to be present on admission rather than occurring in-hospital. The positive predictive value of the claim was greater than 80% for the surgical risk pool, suggesting the value of the CSP as a screening tool. The CSP has validity as a screen for most surgical complications but only for 1 medical complication. The CSP does not have validity as a "stand-alone" tool to identify more than a few in-hospital surgery-related events. The addition of an indicator to the Medicare claim to capture the timing of secondary diagnoses would improve the validity of the CSP for identifying both surgical and medical in-hospital events.Medical Care 09/2000; 38(8):785-95. · 3.23 Impact Factor
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ABSTRACT: Comorbidity measures are designed to exclude complications when they map International Classification of Diseases (ICD-9-CM) codes to diagnostic categories. The use of data fields that indicates whether each secondary diagnosis was present at the time of hospital admission may lead to the more accurate identification of preexisting conditions. To examine the rate of misclassification of ICD-9-CM codes into diagnostic categories by the Dartmouth-Manitoba adaptation of the Charlson index and by the Elixhauser comorbidity algorithm. Analysis of 178,838 patients in the California State Inpatient Database (CA SID) admitted in 2000 for one of seven major medical and surgical conditions. The CA SID includes a condition present at admission (CPAA) modifier for each ICD-9-CM code. The Dartmouth/Charlson index and the Elixhauser comorbidity measure were used to map the ICD-9-CM codes into diagnostic categories for patients in each study population. We calculated the misclassification rate for each mapping algorithm, using information from the CPAA as the "gold standard." The Dartmouth/Charlson index underestimated the prevalence of hemiplegia/paraplegia by 70 percent, cerebrovascular disease by 70 percent, myocardial infarction by 65 percent, congestive heart failure (CHF) by 45 percent, and peptic ulcer disease by 34 percent. The Elixhauser algorithm misclassified complications as preexisting conditions for 43 percent of the coagulopathies, 25 percent of the fluid and electrolyte disorders, 18 percent of the cardiac arrhythmias, 18 percent of the cardiac arrhythmias, and 9 percent of the cases of CHF. Adding the CPAA modifier to administrative data would significantly enhance the ability of the Dartmouth/Charlson index and of the Elixhauser algorithm to map ICD-9-CM codes to diagnostic categories accurately.Health Services Research 03/2006; 41(1):231-51. · 2.29 Impact Factor