Using an Automated System to Monitor Response to Calls from the Public Regarding Infectious Diseases

Tuesday, June 6, 2017: 2:30 PM
430B, Boise Centre
Meagan Burns , Massachusetts Department of Public Health, Jamaica Plain, MA
Scott Troppy , Massachusetts Department of Public Health, Jamaica Plain, MA
Monina Klevens , Massachusetts Department of Public Health, Jamaica Plain, MA
Gillian Haney , Massachusetts Department of Public Health, Jamaica Plain, MA

BACKGROUND: The burden of state health department response to calls from providers, local health jurisdictions and the public is not well characterized. In Massachusetts, two epidemiologists are available to answer calls 24/7. Although data on calls to the Massachusetts Department of Public Health (MDPH) epidemiologists have been captured electronically in the Massachusetts Virtual Epidemiologic Network (MAVEN) surveillance system since 2009, in spring 2016, visibility increased when the Governor and MDPH set goals to respond to 60% of calls within 15 minutes of receipt, and 75% within 20 minutes. System enhancements implemented to monitor progress towards these goals included subject, response time, and duration.

METHODS: We analyzed data from March 1 – November 30, 2016. We describe mean frequencies of call response times and duration (defined as the date and time from call receipt to closure). We measured the percentage of calls with responses ≤15 and ≤20 minutes and describe variability by month. Finally, we modeled time to response using linear regression, and stratified response time and duration by disease subject.

RESULTS: From March 1 to November 30 2016, 9,099 calls were documented (mean 1,011 calls/month; range: 813 -1,383 calls/month). The average response time to calls was 20 minutes, and the average duration was 5 minutes. Disease subjects with the highest volume of calls were Zika virus (37.32%, n=3396), rabies (15.38%, n=1399) and mumps (8.45%, n=769).In March, 45% of calls (551/1217) had response times of ≤15 minutes and 60% (733/1217) ≤20 minutes. In November, the percentage increased to 65% of calls (527/813) with response times of ≤15 minutes and 81% (655/813) ≤20 minutes. Preliminary analyses indicate that, accounting for total call volume, the percentage of calls with a response time ≤15 minutes increased by 2.13% per month (p=0.0017), and the percentage of calls with a response time ≤20 minutes increased by 2.46% per month (p<0.0001).

CONCLUSIONS: We found significant improvements in response time and achievement of target goals as monitored by an automated system. Future analyses will include evaluation of call volume by subject, date and time received, and number of epidemiologists involved in the response. These findings can be used to inform staffing and process decisions.