Protecting Privacy and Transforming COVID-19 Case Surveillance Datasets for Public Use.

OBJECTIVES: Federal open-data initiatives that promote increased sharing of federally collected data are important for transparency, data quality, trust, and relationships with the public and state, tribal, local, and territorial partners. These initiatives advance understanding of health conditions and diseases by providing data to researchers, scientists, and policymakers for analysis, collaboration, and use outside the Centers for Disease Control and Prevention (CDC), particularly for emerging conditions such as COVID-19, for which data needs are constantly evolving. Since the beginning of the pandemic, CDC has collected person-level, de-identified data from jurisdictions and currently has more than 8 million records. We describe how CDC designed and produces 2 de-identified public datasets from these collected data. METHODS: We included data elements based on usefulness, public request, and privacy implications; we suppressed some field values to reduce the risk of re-identification and exposure of confidential information. We created datasets and verified them for privacy and confidentiality by using data management platform analytic tools and R scripts. RESULTS: Unrestricted data are available to the public through Data.CDC.gov, and restricted data, with additional fields, are available with a data-use agreement through a private repository on GitHub.com. PRACTICE IMPLICATIONS: Enriched understanding of the available public data, the methods used to create these data, and the algorithms used to protect the privacy of de-identified people allow for improved data use. Automating data-generation procedures improves the volume and timeliness of sharing data.

Emerging issues related to the management of patients in custody during the COVID-19 outbreak in France.

PURPOSE: This paper aims to give an overview of emerging issues relating to the management of patients in custody during the COVID-19 outbreak in France. DESIGN/METHODOLOGY/APPROACH: During custody in France, a medical consultation is provided for any patient who requests it. In the Paris area, this consultation is carried out by a practitioner in forensic medicine, based in a general hospital. Usually, most medical consultations for patients in custody take place directly in police stations. With the COVID-19 outbreak, the authors chose to suspend this activity, asking law enforcement to bring patients directly to their hospitals. Patients presenting with severe infections or indicative symptoms of the severe acute respiratory syndrome Coronavirus 2 infection and a comorbidity are tested for COVID-19. Such patients remain hospitalized until results of the test are received. If the result is positive, they are hospitalized for the length of their custody. If sent to prison, they are transferred to a medical facility in detention. FINDINGS: From the onset of the outbreak, the authors observed increased pressure from law enforcement to obtain medical information. According to the French Code of Medical Ethics, no medical information should be disclosed regarding the authors' patients' medical situations. The authors are also concerned about sending a potentially infected patient back to a police station, to prison or to his/her home. ORIGINALITY/VALUE: This paper provides a snapshot of issues relating to the management of patients in custody during the COVID-19 outbreak in France. Unfortunately, the current situation in France does not permit a wider range of testing for the specified population in this paper.

Guidance for using text, email, and video communication in practices devoted to reproductive medicine.

The prevalence and ease of electronic communication, specifically email through patient portals associated with electronic medical records or via traditional enterprise email clients (e.g., Outlook) and video, have resulted in increased use for rapid communication between practitioners and their patients. Concerns regarding patient privacy and compliance with the regulations of the Health Insurance Portability and Accountability Act (HIPAA) remain a barrier to routine incorporation of electronic communication into practice. Furthermore, capital investment, implementation, and maintenance costs may provide additional barriers. These long-standing concerns have been heightened and tested by the COVID-19 pandemic. Best-practice guidelines for the secure and safe use of electronic communication with reproductive care patients are provided.

The value of federated learning during and post-COVID-19.

Federated learning (FL) as a distributed machine learning (ML) technique has lately attracted increasing attention of healthcare stakeholders as FL is perceived as a promising decentralized approach to address data privacy and security concerns. The FL approach stores and maintains the privacy-sensitive data locally while allows multiple sites to train ML models collaboratively. We aim to describe the most recent real-world cases using the FL in both COVID-19 and non-COVID-19 scenarios and also highlight current limitations and practical challenges of FL.