How might patient data be released in error

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How might patient data be released in error

Facebook had decided, in the wake of the Cambridge Analytica fiasco, to put those plans on hold. Here is the video version of the report, which is definitely worth watching.

I thought this was disappointing, because I know that many patients rely on social media generally, and Facebook in particular to coordinate patient care. Connecting healthcare data with a patients social graph, when done with permission and with limited and intelligent goals could result in real improvements in patient care, especially for our most vulnerable populations.

I tweeted as much: This is tragic, connecting healthcare data to social graph data could be a huge help to the most vulnerable populations, and now because Facebook scandal it may never happen… https: Given this reaction, I thought it wise to more carefully defend my position. I have spent time thinking carefully about the intersection of healthcare information systems, and cybersecurity and privacy.

This has lead me to be frequently at odds with other cybersecurity experts who are legitimately concerned about the dangers of connecting to early. The problem that I see again and again are knee-jerk policy reactions to technology potential and, more generally, a tendency for talking-head histrionics regarding healthcare information privacy.

Probably the most extreme of these, historically, has been my friend Dr. Dr Peel has continued to suggest that all health information exchange halt, until it can be made entirely secure and entirely respect patient privacy and ongoing consent.

The discussion about Facebooks change in policies is a good example such fear-mongering. Let me quote some of the article, highlighting some of the terms that I find concerning.

Facebook sent a doctor on a secret mission to ask hospitals to share patient data Facebook was in talks with top hospitals and other medical groups as recently as last month about a proposal to share data about the social networks of their most vulnerable patients.

The idea was to build profiles of people that included their medical conditions, information that health systems have, as well as social and economic factors gleaned from Facebook. Now, CNBC is not as given as some of the other networks to outright fear-mongering, but I do need to quibble with this type of reporting.

How might patient data be released in error

First, if you read the article closely you will see that the project intended to link data using a two-sided hashing mechanism.

The headline makes it seem like it would be trivial for both the hospital and Facebook to identify these patients. And it is highly unlikely that either Facebook or the hospitals intended to release this merged dataset to the public.

Still, de-identifying a dataset like this is a useful precaution to ensure that researchers are not tempted to violate patient privacy. This type of de-identification strategy would have made the resulting dataset almost useless for Facebooks main profit center: A profile is a kind of an aggregation of multiple people.Errors in the lower tier are issues that might be the focus of voluntary external reporting systems, as well as research projects supported by the Center for Patient Safety and internal patient safety programs of health care organizations.

Case Study 3 Issue: Patient Identification and Demographic Data: Automated Patient Registration Data Elements/Patient Safety Risks.

Failure of an EHR system to provide appropriate safeguards against medication errors, including the wrong patient, the wrong drug, or failure to consider all available data, can contribute to poor quality care. An electronic health record (EHR), or electronic medical record (EMR), is the systematized collection of patient and population electronically-stored health information in a digital format.

These records can be shared across different health care settings. Records are shared through network-connected, enterprise-wide information systems or other information networks and exchanges.

How might patient data be released in error

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Real-world streaming analytics calls for novel algorithms that run online, and corresponding tools for evaluation. • Anomaly detection with Hierarchical Temporal Memory (HTM) is a state-of-the-art, online, unsupervised method.

“In addition, physicians should disclose to patients information about procedural or judgment errors made in the course of care if such information is material to the patient's well-being. Errors do not necessarily constitute improper, negligent, or unethical behavior, but failure to disclose them may.”.

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Hospitals are Getting 'Smart' About Patient Data