Evaluating the effect of data standardization and validation on patient matching accuracy

Objective This study evaluated the degree to which recommendations for demographic data standardization improve patient matching accuracy using real-world datasets. Materials and Methods We used 4 manually reviewed datasets, containing a random selection of matches and nonmatches. Matching datasets included health information exchange (HIE) records, public health registry records, Social Security Death Master File records, and newborn screening records. Standardized fields including last name, telephone number, social security number, date of birth, and address. Matching performance was evaluated using 4 metrics: sensitivity, specificity, positive predictive value, and accuracy. Results Standardizing address was independently associated with improved matching sensitivities for both the public health and HIE datasets of approximately 0.6% and 4.5%. Overall accuracy was unchanged for both datasets due to reduced match specificity. We observed no similar impact for address standardization in the death master file dataset. Standardizing last name yielded improved matching sensitivity of 0.6% for the HIE dataset, while overall accuracy remained the same due to a decrease in match specificity. We noted no similar impact for other datasets. Standardizing other individual fields (telephone, date of birth, or social security number) showed no matching improvements. As standardizing address and last name improved matching sensitivity, we examined the combined effect of address and last name standardization, which showed that standardization improved sensitivity from 81.3% to 91.6% for the HIE dataset. Conclusions Data standardization can improve match rates, thus ensuring that patients and clinicians have better data on which to make decisions to enhance care quality and safety

Testing and Nonpharmaceutical Interventions for Prevention of SARS-CoV-2 in 20 US Overnight Camps in Summer 2021

OBJECTIVES: Overnight camps are a setting where COVID-19 can easily spread without the diligent use of layered public health interventions. We evaluated 20 camps in the United States to examine COVID-19 transmission and mitigation strategies during summer 2021. METHODS: For this descriptive cross-sectional study, we examined self-reported information from 20 camps in 6 predominantly northeastern states on geographic information, tests and testing cadences, vaccination rates, and number of COVID-19 cases during summer 2021. Because the camps had hired public health consultants to guide them on reducing COVID-19 introduction and spread, all camps implemented similar interventions, including encouraging behaviors that lower the risk of COVID-19 transmission prior to camp arrival, use of cohorts, testing before and after arrival, and strong encouragement of vaccination among eligible campers and staff members. RESULTS: A total of 9474 attendees at the 20 camps came from geographically diverse regions. Camps generally tested before and at arrival, as well as once or twice after arrival. Rates of vaccination were high among staff members (84.6%) and campers (76.2%). Camps identified 27 COVID-19 cases, with 17 (63.0%) detected after arrival, 3 (7.4%) detected on arrival, and 8 (29.6%) detected prior to arrival. CONCLUSIONS: The spread of cases detected after arrival to overnight camps was limited by the use of 3 key interventions: (1) high vaccination rates, (2) a rigorous and responsive testing strategy, and (3) ongoing use of public health interventions. These findings have implications for successful operation of overnight camps, residential schools and colleges, and other similar settings