Building Data Registries with Privacy and Confidentiality for Patient-Centered Outcomes Research (PCOR) [Methods Study], 2020 (ICPSR 39579)
Researchers can use patient health data to compare treatments. But these data may include information, like names or social security numbers, that could identify patients. Researchers use different methods to remove such information and protect patients' privacy. Some methods work well to protect privacy but may make data less useful for research. Other methods don't protect privacy well enough.
Current methods for protecting privacy don't work well when:
- The number of patients in the data set is smaller than the number of data fields, such as patient traits or health conditions, and data are updated many times
- Patients' health and treatments are measured at more than one point in time
- Data are displayed as a graph to better capture some types of content
In this study, the research team created three new methods. The team wanted to see if the new methods better protect patient privacy but also make sure data remain useful for research.
To access the methods and software, please visit the AIMS Group at Emory University.
Improving Methods for Linking Secondary Data Sources for Comparative Effectiveness Research (CER)/Patient-Centered Outcomes Research (PCOR) [Methods Study], United States, 2008-2019 (ICPSR 39614)
Researchers often combine patient health data from different sources, such as claims and health records. These data contain personal information, such as names and social security numbers.
In this study, the research team wanted to learn patients' views on sharing and combining health data for research. The team surveyed patients about their views on
- Sharing health and personal data, such as social security numbers
- Benefits and risks of data sharing
- Ways to help patients feel comfortable sharing health data
Incremental Privacy-Preserving Record Linkage (iPPRL) to Reduce Barriers to Data Sharing and Improve Data Quality [Methods Study], Colorado, 2011-2022 (ICPSR 39738)
Researchers often have trouble collecting complete information on patient health, as patients may receive care at different places. Linking patient records from different places may help researchers get a more complete picture.
One way to link records is through personal information, such as names and birth dates. But this method increases risks to patient privacy. Another way, known as privacy-preserving record linkage, or PPRL, masks personal information. But current PPRL methods only work when linking entire sets of patient data, including data that have already been shared and linked. Linking entire data sets takes a long time. Also, sharing the same records multiple times increases data privacy risks.
In this study, the research team developed and tested a new PPRL method called incremental PPRL. This method links only new or updated data rather than re-linking entire data sets.