The accuracy and completeness for receipt of colorectal cancer care using Veterans Health Administration administrative data.

BACKGROUND: The National Comprehensive Cancer Network and the American Society of Clinical Oncology have established guidelines for the treatment and surveillance of colorectal cancer (CRC), respectively. Considering these guidelines, an accurate and efficient method is needed to measure receipt of care. METHODS: The accuracy and completeness of Veterans Health Administration (VA) administrative data were assessed by comparing them with data manually abstracted during the Colorectal Cancer Care Collaborative (C4) quality improvement initiative for 618 patients with stage I-III CRC. RESULTS: The VA administrative data contained gender, marital, and birth information for all patients but race information was missing for 62.1% of patients. The percent agreement for demographic variables ranged from 98.1-100%. The kappa statistic for receipt of treatments ranged from 0.21 to 0.60 and there was a 96.9% agreement for the date of surgical resection. The percentage of post-diagnosis surveillance events in C4 also in VA administrative data were 76.0% for colonoscopy, 84.6% for physician visit, and 26.3% for carcinoembryonic antigen (CEA) test. CONCLUSIONS: VA administrative data are accurate and complete for non-race demographic variables, receipt of CRC treatment, colonoscopy, and physician visits; but alternative data sources may be necessary to capture patient race and receipt of CEA tests.

Practice-Level Variation in Outpatient Cardiac Care and Association With Outcomes.

BACKGROUND: Utilization of cardiac services varies across regions and hospitals, yet little is known regarding variation in the intensity of outpatient cardiac care across cardiology physician practices or the association with clinical endpoints, an area of potential importance to promote efficient care. METHODS AND RESULTS: We included 7 160 732 Medicare beneficiaries who received services from 5635 cardiology practices in 2012. Beneficiaries were assigned to practices providing the plurality of office visits, and practices were ranked and assigned to quartiles using the ratio of observed to predicted annual payments per beneficiary for common cardiac services (outpatient intensity index). The median (interquartile range) outpatient intensity index was 1.00 (0.81-1.24). Mean payments for beneficiaries attributed to practices in the highest (Q4) and lowest (Q1) quartile of outpatient intensity were: all cardiac payments (Q4 $1272 vs Q1 $581; ratio, 2.2); cardiac catheterization (Q4 $215 vs Q1 $64; ratio, 3.4); myocardial perfusion imaging (Q4 $253 vs Q1 $83; ratio, 3.0); and electrophysiology device procedures (Q4 $353 vs Q1 $142; ratio, 2.5). The adjusted odds ratios (95% CI) for 1 incremental quartile of outpatient intensity for each outcome was: cardiac surgical/procedural hospitalization (1.09 [1.09, 1.10]); cardiac medical hospitalization (1.00 [0.99, 1.00]); noncardiac hospitalization (0.99 [0.99, 0.99]); and death at 1 year (1.00 [0.99, 1.00]). CONCLUSION: Substantial variation in the intensity of outpatient care exists at the cardiology practice level, and higher intensity is not associated with reduced mortality or hospitalizations. Outpatient cardiac care is a potentially important target for efforts to improve efficiency in the Medicare population.

Experimental measurement of preferences in health care using best-worst scaling (BWS): theoretical and statistical issues.

For optimal solutions in health care, decision makers inevitably must evaluate trade-offs, which call for multi-attribute valuation methods. Researchers have proposed using best-worst scaling (BWS) methods which seek to extract information from respondents by asking them to identify the best and worst items in each choice set. While a companion paper describes the different types of BWS, application and their advantages and downsides, this contribution expounds their relationships with microeconomic theory, which also have implications for statistical inference. This article devotes to the microeconomic foundations of preference measurement, also addressing issues such as scale invariance and scale heterogeneity. Furthermore the paper discusses the basics of preference measurement using rating, ranking and stated choice data in the light of the findings of the preceding section. Moreover the paper gives an introduction to the use of stated choice data and juxtaposes BWS with the microeconomic foundations.