Prescriptions (either filled or presented to pharmacists) are often included in lists of data with potential value in biosurveillance. There have been studies of the use of prescriptions to detect cases of disease (especially tuberculosis), and one study of the effect of a public health intervention for a pertussis outbreak on Medicaid claims for macrolide antibiotics, but none of outbreaks.
It is anecdotally reported that at the time that AIDS was first uncovered in 1981, the CDC's investigation drug unit was receiving unusual numbers of requests for the drug pentamidine for treatment of young men (CDC, 2001). The CDC's investigation drug unit was the sole distributor of pentamidine at the time, so these still rare requests were funneled to a single entity and the increase therefore noticeable. This experience nevertheless suggests the potential of prescription monitoring.
Maggini et al. (1991) studied the use of Italy's National Health Service pharmacy dispensing information to identify TB cases in Rome. They found that pharmacy screening detected seven times more new TB cases than routine public health reporting.
Yokoe et al. (1999) studied simple case-detection logic that defined a screening criteria for a new case of tuberculosis as two or more antituberculosis drugs. This simple rule identified 43 incident cases of TB from analysis of electronic records. Of these, seven (16%) had not been identified by the health department.
Chen et al. (2004) used the detection algorithm method to study retrospectively the sales of prescription macrolide antibiotics during an outbreak of pertussis.The New York State Syndromic Surveillance Project receives daily summaries from the New York State Medicaid program, which provides healthcare coverage for 4-20% of the non-NYC regions of the state, of claims for prescription medications in 18 medication groups. The summary counts are reported by zip code, age, and gender. The retrospective analysis used the CUSUM statistic on data aggregated at the county level. The reference date for the outbreak was July 21, 2004. CUSUM signaled on the county-wide counts for the affected county on July 23, which was the day of treatment/prophylaxis of the first case and its contacts.
Approximately 300 individuals received prophylactic antibiotics. The total number of excess macrolide prescriptions (over baseline) received by the New York State Syndromic Surveillance Project over baseline was approximately 110 (estimated from graphs in the paper).
The increased prescriptions detected in this study were the result of a public health intervention after an outbreak was detected, so this study is not directly informative about detection of an outbreak. However, this case study illustrates the sensitivity of prescription monitoring to increases in prescription medications. This sensitivity, coupled with the fact that the researchers estimated that approximately 95% of the records that New York State system receives are for prescriptions filled within the preceding 48 hours, suggest the potential of prescription monitoring for outbreak detection and need for additional research (Table 28.6).
3 Doroshenko and collegues also measured the correlation using a second method, in which they first removed seasonal and other trends from both time series by fitting ARIMA models to the data and then computed the Pearson correlation coefficient (because the modeling yielded normally distributed data) at different time lags. Correlations at zero to four week lags were statistically significant, but small. The maximum correlation of 0.224 occurred at a lag of one week. The lack of strong correlation is not surprising since the ARIMA modeling removed influenza effect.
4 This system's detection performance from ambulatory care data (not call data) has been reported for influenza and outbreaks of gastrointestinal disease. We discuss these results in Chapter 23.
table 28.6 Medicaid Prescription Drug Categories Included in New York State's Syndromic Surveillance System
Analgesics (narcotic) Analgesics (non-narcotic) Antacids
Antiasthmatic medications Antibiotics
Cephalosporins, first and second generation
Cephalosporins, third and fourth generation
Penicillin G and ampicillins
Penicillinase-resistant, extended spectrum, and penicillin combinations Tetracyclines Antidiarrheal medications Antihistamines
From Chen, J.-H., Schmit, K., Chang, H., et al. (2004). Use of medicaid prescription data for syndromic surveillance—New York. MMWR Morb Mortal Wkly Rep 54(Suppl):31-4, with permission.
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