Using internet searches for influenza surveillance.

The Internet is an important source of health information. Thus, the frequency of Internet searches may provide information regarding infectious disease activity. As an example, we examined the relationship between searches for influenza and actual influenza occurrence. Using search queries from the Yahoo! search engine ( http://search.yahoo.com ) from March 2004 through May 2008, we counted daily unique queries originating in the United States that contained influenza-related search terms. Counts were divided by the total number of searches, and the resulting daily fraction of searches was averaged over the week. We estimated linear models, using searches with 1-10-week lead times as explanatory variables to predict the percentage of cultures positive for influenza and deaths attributable to pneumonia and influenza in the United States. With use of the frequency of searches, our models predicted an increase in cultures positive for influenza 1-3 weeks in advance of when they occurred (P < .001), and similar models predicted an increase in mortality attributable to pneumonia and influenza up to 5 weeks in advance (P < .001). Search-term surveillance may provide an additional tool for disease surveillance.

Use of prediction markets to forecast infectious disease activity.

Prediction markets have accurately forecasted the outcomes of a wide range of future events, including sales of computer printers, elections, and the Federal Reserve's decisions about interest rates. We propose that prediction markets may be useful for tracking and forecasting emerging infectious diseases, such as severe acute respiratory syndrome and avian influenza, by aggregating expert opinion quickly, accurately, and inexpensively. Data from a pilot study in the state of Iowa suggest that these markets can accurately predict statewide seasonal influenza activity 2-4 weeks in advance by using clinical data volunteered from participating health care workers. Information revealed by prediction markets may help to inform treatment, prevention, and policy decisions. Also, these markets could help to refine existing surveillance systems.

A cost analysis of the Iowa Medicaid primary care case management program.

OBJECTIVE: To determine the cost savings attributable to the implementation and expansion of a primary care case management (PCCM) program on Medicaid costs per member in Iowa from 1989 to 1997. DATA SOURCES: Medicaid administrative data from Iowa aggregated at the county level. STUDY DESIGN: Longitudinal analysis of costs per member per month, analyzed by category of medical expense using weighted least squares. We compared the actual costs with the expected costs (in the absence of the PCCM program) to estimate cost savings attributable to the PCCM program. PRINCIPAL FINDINGS: We estimated that the PCCM program was associated with a savings of US dollars 66 million to the state of Iowa over the study period. Medicaid expenses were 3.8 percent less than what they would have been in the absence of the PCCM program. Effects of the PCCM program appeared to grow stronger over time. Use of the PCCM program was associated with increases in outpatient care and pharmaceutical expenses, but a decrease in hospital and physician expenses. CONCLUSIONS: Use of a Medicaid PCCM program was associated with substantial aggregate cost savings over an 8-year period, and this effect became stronger over time. Cost reductions appear to have been mediated by substituting outpatient care for inpatient care.