Objective

To identify an approach to summarizing publicly reported hospital performance data for acute myocardial infarction (AMI) or heart failure (HF) that best predicts current year hospital mortality rates.

Setting

A total of 1,868 U.S. hospitals reporting process and outcome measures for AMI and HF to the Centers for Medicare and Medicaid Services (CMS) from July 2005 to June 2006 (Year 0) and July 2006 to June 2007 (Year 1).

Design

Observational cohort study measuring the percentage variation in Year 1 hospital 30-day risk-adjusted mortality rate explained by denominator-based weighted composite scores summarizing hospital Year 0 performance.

Data collection

Data were prospectively collected from hospitalcompare.gov.

Results

Percentage variation in Year 1 mortality was best explained by mortality rate alone in Year 0 over other composites including process performance. If only Year 0 mortality rates were reported, and consumers using hospitals in the highest decile of mortality instead chose hospitals in the lowest decile of mortality rate, the number of deaths at 30 days that potentially could have been avoided was 1.31 per 100 patients for AMI and 2.12 for HF (p < .001).

Conclusion

Public reports focused on 30-day risk-adjusted mortality rate may more directly address policymakers' goals of facilitating consumer identification of hospitals with better outcomes.

Objective

To determine whether Internet search volume for kidney stones has seasonal and geographic distributions similar to known kidney stone incidence.

Material and methods

Google Insights for Search analyzes a portion of Google web searches from all Google domains to compute how many searches are performed for a given term relative to the total number of searches done over a specific time interval and geographic region. Selected terms related to kidney stones were examined to determine which most closely tracked kidney stone incidence. Google Insights for Search data were correlated with hospital admissions for the emergent treatment of nephrolithiasis found through the Nationwide Inpatient Sample. Ambient temperature in Seattle and New York were compared with search volume for these regions to display qualitative relationships.

Results

The term "kidney stones" had the highest seasonal correlation of terms examined (r = .81, P = .0014). Google Insights for Search output and national Inpatient Sample admissions also correlated when regions were compared (r = .90, P = .005). Qualitative relationships between ambient temperatures and kidney stone search volume do exist.

Conclusions

Internet search volume activity for kidney stones correlates with temporal and regional kidney stone insurance claims data. In the future, with improved modeling of search detection algorithms and increased Internet usage, search volume has the potential to serve as a surrogate for kidney stone incidence.