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Objectives: To estimate the annual prevalence of opioid use disorder (OUD) in Massachusetts from 2011 to 2015., Methods: We performed a multisample stratified capture-recapture analysis to estimate OUD prevalence in Massachusetts. Individuals identified from 6 administrative databases for 2011 to 2012 and 7 databases for 2013 to 2015 were linked at the individual level and included in the analysis. Individuals were stratified by age group, sex, and county of residence., Results: The OUD prevalence in Massachusetts among people aged 11 years or older was 2.72% in 2011 and 2.87% in 2012. Between 2013 and 2015, the prevalence increased from 3.87% to 4.60%. The greatest increase in prevalence was observed among those in the youngest age group (11-25 years), a 76% increase from 2011 to 2012 and a 42% increase from 2013 to 2015., Conclusions: In Massachusetts, the OUD prevalence was 4.6% among people 11 years or older in 2015. The number of individuals with OUD is likely increasing, particularly among young people.

Objectives: To assess the feasibility of chronic disease surveillance using distributed analysis of electronic health records and to compare results with Behavioral Risk Factor Surveillance System (BRFSS) state and small-area estimates., Methods: We queried the electronic health records of 3 independent Massachusetts-based practice groups using a distributed analysis tool called MDPHnet to measure the prevalence of diabetes, asthma, smoking, hypertension, and obesity in adults for the state and 13 cities. We adjusted observed rates for age, gender, and race/ethnicity relative to census data and compared them with BRFSS state and small-area estimates., Results: The MDPHnet population under surveillance included 1 073 545 adults (21.8% of the state adult population). MDPHnet and BRFSS state-level estimates were similar: 9.4% versus 9.7% for diabetes, 10.0% versus 12.0% for asthma, 13.5% versus 14.7% for smoking, 26.3% versus 29.6% for hypertension, and 22.8% versus 23.8% for obesity. Correlation coefficients for MDPHnet versus BRFSS small-area estimates ranged from 0.890 for diabetes to 0.646 for obesity., Conclusions: Chronic disease surveillance using electronic health record data is feasible and generates estimates comparable with BRFSS state and small-area estimates.

Electronic health record systems contain clinically detailed data from large populations of patients that could significantly enrich public health surveillance. Clinical practices' security, privacy, and proprietary concerns, however, have limited their willingness to share these data with public health agencies. We describe a novel distributed network for public health surveillance called MDPHnet. The system allows the Massachusetts Department of Public Health (MDPH) to initiate custom queries against participating practices' electronic health records while the data remain behind each practice's firewall. Practices can review proposed queries before execution and approve query results before releasing them to the health department. MDPH is using the system for routine surveillance for priority conditions and to evaluate the impact of public health interventions.