OBJECTIVE: The aim of this analysis was to assess alternative methods of identification of patients treated with peritoneal dialysis (PD) in health care claims databases for possible use in future analyses of costs of this treatment modality. METHODS: Using a US health insurance claims database spanning January 1, 2004, to December 31, 2006, we identified all patients with renal failure who satisfied a case-finding algorithm for PD anticipated to be highly specific, but not necessarily sensitive-namely, > or =2 claims for PD-related physician services (algorithm 1). All claims from these patients were assessed to identify additional PD-related codes, from which 6 additional algorithms were developed, each of which focused on specific categories of billing codes (eg, diagnostic, procedural/service, equipment). Patient selection was then reimplemented using these alternative algorithms. Concordance between the various algorithms and the extent to which resulting samples were similar in terms of patient characteristics, health care resource utilization, and costs were assessed. RESULTS: We identified a total of 132,274 patients in the database with > or =1 claim for renal failure and valid enrollment data. Among these patients, a total of 2329 satisfied case-selection criteria for algorithm 1, and 4031 patients met criteria for at least 1 of the 7 algorithms for PD. The most sensitive algorithm identified 2859 patients who might have received PD; the least sensitive, 211. Concordance between algorithms was relatively poor. Patients identified using each algorithm were similar, however, with respect to mean age (45-50 years), sex (54%-56% male), and the prevalence of selected comorbidities. Annualized median health care costs were similar across the various algorithms (range, US $80,967-$118,668). CONCLUSIONS: Based on the results from this analysis, it seems that health care providers bill insurers for PD-related care using a variety of codes. Investigators using health insurance claims data for analyses of patients treated with PD need to take this into account.
OBJECTIVE: The aim of this analysis was to assess alternative methods of identification of patients treated with peritoneal dialysis (PD) in health care claims databases for possible use in future analyses of costs of this treatment modality. METHODS: Using a US health insurance claims database spanning January 1, 2004, to December 31, 2006, we identified all patients with renal failure who satisfied a case-finding algorithm for PD anticipated to be highly specific, but not necessarily sensitive-namely, > or =2 claims for PD-related physician services (algorithm 1). All claims from these patients were assessed to identify additional PD-related codes, from which 6 additional algorithms were developed, each of which focused on specific categories of billing codes (eg, diagnostic, procedural/service, equipment). Patient selection was then reimplemented using these alternative algorithms. Concordance between the various algorithms and the extent to which resulting samples were similar in terms of patient characteristics, health care resource utilization, and costs were assessed. RESULTS: We identified a total of 132,274 patients in the database with > or =1 claim for renal failure and valid enrollment data. Among these patients, a total of 2329 satisfied case-selection criteria for algorithm 1, and 4031 patients met criteria for at least 1 of the 7 algorithms for PD. The most sensitive algorithm identified 2859 patients who might have received PD; the least sensitive, 211. Concordance between algorithms was relatively poor. Patients identified using each algorithm were similar, however, with respect to mean age (45-50 years), sex (54%-56% male), and the prevalence of selected comorbidities. Annualized median health care costs were similar across the various algorithms (range, US $80,967-$118,668). CONCLUSIONS: Based on the results from this analysis, it seems that health care providers bill insurers for PD-related care using a variety of codes. Investigators using health insurance claims data for analyses of patients treated with PD need to take this into account.
Authors: Raja Zabaneh; Simon D Roger; Mohamed El-Shahawy; Michael Roppolo; Grant Runyan; Janet O'Neil; Ping Qiu Journal: Perit Dial Int Date: 2014-03-01 Impact factor: 1.756
Authors: Charu Taneja; Ariel Berger; Gary W Inglese; Lois Lamerato; James A Sloand; Greg G Wolff; Michael Sheehan; Gerry Oster Journal: Perit Dial Int Date: 2014-02-04 Impact factor: 1.756