KYV: Know Your (Healthcare) Visitor

Who is accessing healthcare assets and data?

Healthcare identity verification and authentication is often substandard, as I noted in a prior Bredemarket blog post entitled “Medical Fraudsters: Birthday Party People.” In too many cases, all you need to know is a patient’s name and birthdate to obtain fraudulent access to the patient’s protected health information (PHI).

But healthcare providers need to identify more than just patients. Providers need to identify their own workers, as well as other healthcare workers.

Know Your Visitor

Healthcare providers also need to identify visitors. When a patient is in a hospital, a rehabilitation facility, or a similar place, loved ones often desire to visit them. (So do hated ones, but we won’t go there now.)

I was recently visiting a loved one in a facility that required identification of visitors. The usual identification method was to present a driver’s license at the desk. The staffer would then print out a paper badge showing the visitor’s name and the validity date.

Like this…

John Bederhoft?

So John “Bederhoft” (sic) enjoyed access that day. Whoops.

Oh, and I could have handed my badge to someone else after a shift change, and no one would have been the wiser.

Let’s apply “somewhat you why”

There’s a more critical question: WHY was John “Berdehoft” visiting (REDACTED PHI)? Was I a relative? A friend? A bill collector? 

My proposed sixth factor of identity verification/authentication, “somewhat you why,” would genuinely help here. 

Somewhat you why “applies a test of intent or reasonableness to any identification request.” 

Maybe I should have said “and” instead of “or.”

  • Visiting a relative shows intent AND reasonableness.
  • Visiting a debtor shows intent but (IMHO) does NOT show reasonableness.

Do you need to analyze healthcare identity issues for your healthcare product or service? Or create go-to-market content for the same? Or proposals?

Contact me at Bredemarket’s “CPA” page.

DNA Chain of Custody

(Part of the biometric product marketing expert series)

Gloves can play a big part in a variety of criminal investigations…including the ones that DON’T result in live coverage and international headlines.

The phrase of the day is “chain of custody,” because DNA evidence can be incredibly accurate…until it isn’t.

H/T CSIDDS for this story.

Sydney Criminal Lawyers shared the story of a police officer sent to prison for falsifying evidence.

“A property in Cairnlea, Melbourne, was identified as a safe house for…drugs, with police finding pieces of evidence — including a pair of gloves that had a man’s DNA on them. Despite only having the one source of DNA on the gloves, (former police detective Jye) Symes falsely reported that he found a woman’s DNA on the gloves.”

For the misconduct, Symes received “a full term of 3 years imprisonment with an 18-month non-parole period.”

Don’t mess with the evidence.

Google Does Not Comply With Google

Mystifying error message of the day.

I hadn’t cast from my phone to my TV in a while. 

When I tried to do so recently, I got an error from Google, saying in part that YouTube on TV’s request does not comply with Google’s “Use Secure Browsers” policy.

It’s worth noting:

  • The YouTube app on my phone is from Google.
  • The YouTube on TV app on my TV is from Google.

So if I read the message as stated, Google’s apps don’t meet Google’s standards.

(And for those who are curious, no my wi-fi network is not tied to my consulting e-mail account.)

I was in an impatient mood and didn’t feel like diagnosing the issue, so I didn’t.

“Plug and play” has a way to go in the wi-fi world. 

Survey Says

So Deloitte announced the results of a survey earlier this month.

“The fifth annual Deloitte “Connected Consumer” survey reveals that consumers have a positive perception of their technology experiences and are increasingly embracing GenAI. However, they are determined to seek balance in their digital lives and expect trust, accountability, and transparency from technology providers.”

Deloitte conducted the survey BEFORE the RIBridges hack.

On the RIBridges Benefits System Hack

I originally worked with state benefits systems during my years at Printrak, and have performed analysis of such systems at Bredemarket. These systems store sensitive personal data of many Americans, including myself. And they are therefore a target for hackers.

The hack at RIBridges

A huge benefits system was hacked in Rhode Island, according to the State.

“On December 5, the State was informed by its vendor, Deloitte, that the RIBridges data system was the target of a potential cyberattack….”

That was just the beginning.

“On December 10, the State received confirmation from Deloitte that there had been a breach of the RIBridges system based on a screenshot of file folders sent by the hacker to Deloitte. On December 11, Deloitte confirmed that there is a high probability that the implicated folders contain personally identifiable information from RIBridges. On December 13, Deloitte confirmed there was malicious code present in the system, and the State directed Deloitte to shut RIBridges down to remediate the threat.”

RIBridges is…um…a bridge from Rhode Island residents to various Federally sponsored but State administered benefits programs, including:

  • Medicaid,    
  • Supplemental Nutrition Assistance Program (SNAP),    
  • Temporary Assistance for Needy Families (TANF),    
  • Child Care Assistance Program (CCAP),    
  • Health coverage purchased through HealthSource RI   
  • Rhode Island Works (RIW),    
  • Long-Term Services and Supports (LTSS), and    
  • General Public Assistance (GPA) Program

State benefits systems such as RIBridges are complex and often hosted on old infrastructure that requires modernization. (“Modernization” is a great buzzword to use to toss around when describing aging state computer systems, as I know from my years working with driver’s license and biometric identification systems.) The older and more complex the system, the easier to hack.

The history of RIBridges

This complexity is certainly true of Deloitte’s hacked RIBridges system.

As StateScoop noted in 2021:

“Gov. Daniel McKee…said the state will pay the firm $99 million over the next three years to manage and build out the RIBridges computer system….The firm has been developing the software, which handles the state’s Medicaid, SNAP and other welfare programs, since 2016, though delays and errors during (previous Governor) Raimondo’s administration caused the state to overspend by at least $150 million as of 2019, the last time the state renewed Deloitte’s contract.”

Why is Deloitte’s performance less than ideal? Anthony Kimerv of Biometric Update explains the issues facing RIBridges.

“Federal agencies, including the federal Centers for Medicare and Medicaid Services, had warned Rhode Island before the system’s launch that it was not ready for deployment….RIBridges proceeded despite clear operational risks, leading to immediate and widespread problems. The launch resulted in significant disruptions to benefits distribution, with thousands of residents experiencing delays in receiving critical assistance. Backlogs soared, with more than 20,000 cases piling up due to system malfunctions.”

After much time and effort the backlogs decreased, but the treasure trove of personally identifiable information (PII) remained a target.

“As a central repository for sensitive personal data, including financial information and health records, RIBridges became a potential target for cyberattacks. Security audits revealed vulnerabilities in the system’s defenses….Cybercriminals exploited weaknesses in RIBridges to access sensitive data. The attackers bypassed existing security measures, inserted malicious code, and obtained unauthorized access. The breach exposed flaws in the system’s technical defenses and highlighted issues with its oversight and vendor management.”

The consequences for RIBridges applicants

So now the system is down, applicants are using paper forms, and a cyber criminal is requesting a payout.

(Image by Google Gemini)

If the World is Flat

(Part of the biometric product marketing expert series)

(August 1, 2025: image img_2522-1.jpg and video flat2412a-1_mp4_hd_1080p.original.jpg?h=1378 removed by request)

(also deleted related content on Bluesky, Facebook, LinkedIn, TikTok personal, and YouTube)

If the world is flat…

…there’s no need to look beyond the horizon.

…only the current quarter counts.

If you want to survive…

…think beyond the current quarter.

…invest in the long term.

…invest in product marketing.

…invest in a product marketer.

John E. Bredehoft on LinkedIn: LINK

I’m seeking a Senior Product Marketing Manager role in software (biometrics, government IDs, geolocation, identity and access management, cybersecurity, health) as an individual contributor on a collaborative team.

Key Accomplishments

  • Product launches (Confidential software product, Know Your Business offering, Morpho Video Investigator, MorphoBIS Cloud, Printrak BIS, Omnitrak).
  • Multiple enablement, competitive analysis, and strategy efforts.
  • Exploration of growth markets.

Multiple technologies.

Multiple industries.

Over 22 types of content.

Currently available for full-time employment or consulting work (Bredemarket).

More details on the latter at Bredemarket’s “CPA” page.

Temporary REAL-ity?

Your driver’s license isn’t real forever.

When talking about the validity periods for U.S. driver’s licenses (which vary from state to state) in a February 2024 post, Veriff points out one oft-overlooked part of the REAL ID Act:

“If a document bears the typical Real ID star symbol (or some accepted adaptation of it), meaning it is a Real ID-compliant document, it cannot be valid for longer than 8 years (Section 202(d)(10) of the Real ID Act).”

At the time of Veriff’s post, the REAL ID deadline was due for enforcement on May 7, 2025 after numerous delays. Several months later, in September 2024, the Transportation Security Administration started planning to be flexible about that deadline…

Someday the REAL ID Act will be real…

Musical Chairs, the Mid-December 2024 Edition (So Far)

There are fewer identity companies now.

  • It was just announced that SecureAuth is acquiring SessionGuardian.
  • Before that, LexisNexis Risk Solutions announced that it is acquiring IDVerse.

And that’s just in the last few days. Many more identity companies acquired new subsidiaries themselves, or were acquired.

I have no idea if these mergers and acquisitions will include layoffs of now-redundant staff, but I do know that one established company let some people go last Friday—only the latest round of layoffs in the last several months.

Why? Identity firms are buffeted by the same issues that beset the rest of tech. 

In addition, the “one trick pony” firms in the industry that only support one modality are finding that they cannot provide complete solutions. This is something Steve Craig just addressed on LinkedIn. His key takeaway:

“Document verification has become a feature, not a product”

And if all your company offers is a feature, you’d better broaden your offerings, acquire, be acquired, or die.

We’ve seen this before, when Robert LaPenta acquired a lot of one-trick ponies and forged a multimodal, multi-factor firm that was finally known as L-1 Identity Solutions before it was itself acquired. There were many other acquisitions around the same time, creating a dizzying array of musical chairs.

And in the game of musical chairs, whenever a chair is removed, someone doesn’t have a place to sit.

(Wildebeest musical chairs AI-generated image by Google Gemini)

Hospital-acquired Delirium is Only Temporary

Until recently I had never heard of hospital-acquired delirium before. From UCLA Health:

“(T)he type of confusion you describe isn’t unusual in older adults who have been hospitalized. Sometimes referred to as hospital-acquired delirium, it’s a temporary but severe form of mental impairment that affects up to one-third of patients over the age of 70, particularly those undergoing surgery or those in intensive care. The condition is marked by periods of confused thinking, jumbled memory, difficulty understanding speech, agitation, disorientation and even hallucinations.

“The duration of hospital-acquired delirium can be as brief as a few hours or…can continue for several days.”

The NIST Test You Choose Matters

(Baby smoking image designed by Freepik)

As I’ve mentioned before, when the National Institute of Standards and Technology (NIST) tests biometric modalities such as finger and face, they conduct each test in a bunch of different ways.

One of the ramifications of this is that many entities can claim that they are “the best, according to NIST.”

For example, when NIST released its first version of the age estimation tests, 5 of the 6 participating vendors scored first in SOME category.

But NIST doesn’t do this just to make the vendors happy. NIST does this because biometrics are used in many, many ways.

Let’s look at recent age estimation testing, which currently tests 15 algorithms rather than the original 6.

Governments and private entities can estimate ages for people at the pub, people buying weed, or people gambling. And then there’s the use case that is getting a lot of attention these days—people accessing social media.

Child Online Safety, Ages 13-16 (in my country anyway)

When NIST conceived the age estimation tests, the social media providers generaly required their users to be 13 years of age or older. For this reason, one of NIST’s age estimation tests focused upon whether age estimation algorithms could reliably identify those who were 13 years old vs. those who were not.

By Adrian Pingstone – Transferred from en.wikipedia, Public Domain, https://commons.wikimedia.org/w/index.php?curid=112727.

Which, by the way, basically means that the NIST age estimation tests are useless in Australia. After NIST started age estimation testing, Australia passed a law last month requiring social media users to be 16 years old or older.

Returning to America, NIST actually conducted several different tests for the 13 year old “child online safety” testing. I’m going to focus on one of them:

Age 8-12 – False Positive Rates (FPR) are proportions of subjects aged 8 to 12 but whose age is estimated from 13 to 16 (below 17).

This covers the case in which a social media provider requires people to be 13 years old or older, someone between 8 and 12 tries to sign up for the social media service anyway…AND SUCCESSFULLY DOES SO.

You want the “false positive rate” to be as low as possible in this case, so that’s what NIST measures.

Results as of December 10, 2024

The image below was taken from the NIST Face Analysis Technology Evaluation (FATE) Age Estimation & Verification page on December 10, 2024. Because this is a continuous test, the actual results may be different by the time you read this, so be sure to check the latest results.

From https://pages.nist.gov/frvt/html/frvt_age_estimation.html as of December 10, 2024.

As of December 10, the best performing algorithm of the 15 tested had a false positive rate (FPR) of 0.0467. The second was close at 0.0542, with the third at 0.0828.

The 15th was a distant last at 0.2929.

But the worst-tested algorithm is much better on other tests

But before you conclude that the 15th algorithm in the “8-12” test is a dud, take a look at how that same algorithm performed on some of the OTHER age estimation tests.

  • For the age 17-22 test (“False Positive Rates (FPR) are proportions of subjects aged 17 to 22 but whose age is estimated from 13 to 16 (below 17)”), this algorithm was the second MOST accurate.
  • And the algorithm is pretty good at correctly classifying 13-16 year olds.
  • It also performs well in the “challenge 25” tests (addressing some of the use cases I mentioned above such as alcohol purchases).
I think they’re over 13. By Obscurasky – Own work, Public Domain, https://commons.wikimedia.org/w/index.php?curid=7776157.

So it looks like this particular algorithm doesn’t (currently) do well with kids, but it does VERY well with adults.

So before you use the NIST tests as a starting point to determine if an algorithm is good for you, make sure you evaluate the CORRECT test, including the CORRECT data.