Futurism88%

US Hospitals Are Outsourcing In-Person Nursing to Remote Health Workers in the Philippines 81%

By Joe Wilkins84%

7/18/2026, 10:00:00 AM

BS Summary: This article contains 23 faulty reasoning types, including Negativity Bias, Hasty Generalization, and Appeal to Emotion, with Biased Writer Voice as the most egregious example at 41.8% saturation with 238 hits. Analysis detected 1,669 faulty-reasoning hits from 570 analyzed words, generating a BS Score of 72.9% and a BS Rank of 81% (4,044 of 21,175 articles). This article is worse (more manipulative) than 80.90% of the article peer group.

The next time you’re checking into a hospital, it’s possible that your nurse may actually be 8,000 miles away. 
That’s the reality at a growing number of hospitals throughout the US and the world, which are turning to low-paid telehealth workers in the Philippines to help fill in the duty roster. 
As it is for remote driving and AI data labeling , the Philippines has become a wellspring of cheap labor for transnational healthcare companies, which are more than happy to exploit a country where millions of people live in poverty. 
Stunning reporting by Rest of World detailed the lives of some of the 210,000 full-time Filipino workers employed in remote healthcare. 
This new class of workers makes up for a massive shortage of almost 80,000 registered nurses in the US. 
One of the workers, Alice, is a licensed nurse working in Quezon City, a city of three million people in the Philippines. 
In 2019, she signed on with a telehealth company providing mental health and substance abuse treatment to US-based patients in California and New Mexico. 
Alice told RoW she earns $5 an hour, five times as much as the hospital job she left behind. 
“We have this virtual clinic that functions like a lobby where patients check in,” Alice explained, “and then we traffic or triage them and send them to each of the providers’ personal Zoom room.” 
To get a job communing with US patients through a screen, a Filipino worker simply needs to have a medical degree  it doesn’t matter what kind. 
While it’s likely that many telehealth recruits come from healthcare administration backgrounds, RoW notes that about 30 percent of the people employed in these jobs are trained nurses or other medical professionals. 
The result is a scenario where tens of thousands of healthcare workers are physically present in their communities, but spend their days caring for patients half a world away in a desperate bid to pay the bills. 
Already facing a mounting shortage of trained healthcare professionals, the Filipino people have watched as telehealth corporations court the remaining hospital workers to oversee care for patients in the US. 
“If they can’t go abroad, remote nursing is the next best thing because local wages are so low,” Nico Uba, secretary general of the group Filipino Nurses United told RoW . 
“Then local hospitals are left understaffed and overworked.” 
The companies running this insidious scheme prey on two sets of healthcare workers on opposite ends of the world: the underpaid Filipino, for whom a wage of $5 an hour is much higher than the national average , and the overworked American, for whom a 50-hour work week is practically a vacation. 
The remote healthcare industry is well aware of this tension, and is happy to take advantage. 
As JL Botor, president of the Healthcare Information Management Association of the Philippines told RoW , US hospitals can save up to 70 percent of their overhead costs by hiring Filipino workers instead. 
In all, Botor notes that the country is a “clinical process outsourcing powerhouse,” as well as “a premier global hub for supporting overstressed international healthcare systems.” 
More on healthcare: Lawsuit Claims the Mayo Clinic’s Use of AI Is Butchering Patient Care 
The post US Hospitals Are Outsourcing In-Person Nursing to Remote Health Workers in the Philippines appeared first on Futurism . 
Article reasoning-pattern comparisonThis article: 0.0%Joe Wilkins: 6.6%Futurism: 6.0%Confirmation Bias0.0%This article: 9.1%Joe Wilkins: 1.6%Futurism: 1.6%Anchoring Bias9.1%This article: 15.3%Joe Wilkins: 6.3%Futurism: 6.2%Availability Heuristic15.3%This article: 8.9%Joe Wilkins: 1.6%Futurism: 1.5%Representativeness Heuristic8.9%This article: 0.0%Joe Wilkins: 0.3%Futurism: 0.6%Hindsight Bias0.0%This article: 0.0%Joe Wilkins: 3.7%Futurism: 2.6%Overconfidence Bias0.0%This article: 18.4%Joe Wilkins: 13.2%Futurism: 11.5%Framing Effect18.4%This article: 0.0%Joe Wilkins: 1.1%Futurism: 1.2%Loss Aversion0.0%This article: 0.0%Joe Wilkins: 0.7%Futurism: 0.6%Status Quo Bias0.0%This article: 0.0%Joe Wilkins: 0.1%Futurism: 0.2%Sunk Cost Effect0.0%This article: 0.0%Joe Wilkins: 2.0%Futurism: 2.2%Optimism Bias0.0%This article: 5.6%Joe Wilkins: 4.5%Futurism: 4.3%Pessimism Bias5.6%This article: 40.4%Joe Wilkins: 25.5%Futurism: 22.6%Negativity Bias40.4%This article: 0.0%Joe Wilkins: 1.6%Futurism: 1.6%Self-Serving Bias0.0%This article: 0.0%Joe Wilkins: 1.4%Futurism: 1.1%Fundamental Attribution Error0.0%This article: 0.0%Joe Wilkins: 0.2%Futurism: 0.2%Actor-Observer Bias0.0%This article: 0.0%Joe Wilkins: 1.2%Futurism: 0.6%In-Group Bias0.0%This article: 0.0%Joe Wilkins: 0.4%Futurism: 0.3%Out-Group Homogeneity Bias0.0%This article: 8.2%Joe Wilkins: 1.3%Futurism: 1.1%Halo Effect8.2%This article: 0.0%Joe Wilkins: 0.7%Futurism: 0.6%Horn Effect0.0%This article: 0.0%Joe Wilkins: 0.1%Futurism: 0.1%Dunning-Kruger Effect0.0%This article: 0.0%Joe Wilkins: 2.2%Futurism: 2.2%Recency Bias0.0%This article: 0.0%Joe Wilkins: 0.2%Futurism: 0.5%Primacy Effect0.0%This article: 0.0%Joe Wilkins: 0.1%Futurism: 0.1%Blind-Spot Bias0.0%This article: 0.0%Joe Wilkins: 1.4%Futurism: 1.3%Ad Hominem0.0%This article: 0.0%Joe Wilkins: 1.1%Futurism: 0.6%Straw Man0.0%This article: 11.2%Joe Wilkins: 5.6%Futurism: 6.8%Appeal to Authority11.2%This article: 5.4%Joe Wilkins: 2.5%Futurism: 2.5%False Dilemma5.4%This article: 7.0%Joe Wilkins: 2.9%Futurism: 2.6%Slippery Slope7.0%This article: 0.0%Joe Wilkins: 0.3%Futurism: 0.2%Circular Reasoning0.0%This article: 30.5%Joe Wilkins: 12.8%Futurism: 10.5%Hasty Generalization30.5%This article: 0.0%Joe Wilkins: 1.0%Futurism: 0.9%Red Herring0.0%This article: 0.0%Joe Wilkins: 1.5%Futurism: 1.2%Bandwagon0.0%This article: 21.9%Joe Wilkins: 11.4%Futurism: 9.3%Appeal to Emotion21.9%This article: 0.0%Joe Wilkins: 1.6%Futurism: 1.5%Begging the Question0.0%This article: 4.7%Joe Wilkins: 3.0%Futurism: 3.9%Post Hoc (False Cause)4.7%This article: 0.0%Joe Wilkins: 0.1%Futurism: 0.2%Tu Quoque0.0%This article: 0.0%Joe Wilkins: 1.2%Futurism: 1.1%Burden of Proof0.0%This article: 0.0%Joe Wilkins: 0.2%Futurism: 0.3%Appeal to Nature0.0%This article: 9.1%Joe Wilkins: 0.2%Futurism: 0.3%Composition/Division9.1%This article: 7.9%Joe Wilkins: 4.3%Futurism: 4.3%Anecdotal7.9%This article: 0.0%Joe Wilkins: 0.0%Futurism: 0.1%No True Scotsman0.0%This article: 5.6%Joe Wilkins: 2.3%Futurism: 2.7%Ambiguity (Equivocation)5.6%This article: 0.0%Joe Wilkins: 0.0%Futurism: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Joe Wilkins: 0.2%Futurism: 0.2%Middle Ground0.0%This article: 0.0%Joe Wilkins: 0.2%Futurism: 0.1%Personal Incredulity0.0%This article: 0.0%Joe Wilkins: 0.4%Futurism: 0.2%Special Pleading0.0%This article: 7.0%Joe Wilkins: 0.6%Futurism: 0.3%Genetic Fallacy7.0%This article: 6.0%Joe Wilkins: 3.4%Futurism: 3.9%Unattributed Quote6.0%This article: 4.6%Joe Wilkins: 2.8%Futurism: 2.6%Quote-first Misdirection4.6%This article: 41.8%Joe Wilkins: 27.1%Futurism: 20.8%Biased Writer Voice41.8%This article: 9.1%Joe Wilkins: 1.7%Futurism: 2.1%Indoctrination9.1%This article: 12.3%Joe Wilkins: 5.2%Futurism: 2.4%Politically Left Leaning Bias12.3%This article: 0.0%Joe Wilkins: 0.4%Futurism: 0.3%Politically Right Leaning Bias0.0%This article: 2.6%Joe Wilkins: 1.5%Futurism: 1.6%Attempt to Sell a Product or S…2.6%

570 words analyzed.

Speakers

4speakers32%attributed speech387writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 13 words • 100.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 32 words • 100.0% coverageWriter's voice • 40 words • 100.0% coverageWriter's voice • 21 words • 100.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageAlice • 19 words • 0.0% coverageAlice • 34 words • 100.0% coverageWriter's voice • 27 words • 100.0% coverageRest of World • 32 words • 0.0% coverageWriter's voice • 37 words • 100.0% coverageWriter's voice • 30 words • 100.0% coverageNico Uba • 31 words • 0.0% coverageNico Uba • 8 words • 0.0% coverageWriter's voice • 52 words • 100.0% coverageWriter's voice • 16 words • 100.0% coverageJL Botor • 33 words • 0.0% coverageJL Botor • 26 words • 100.0% coverageWriter's voice • 15 words • 100.0% coverageWriter's voice • 20 words • 0.0% coverage
Selected voice

JL Botor

100%flagged-word coverage
59 attributed words32% of attributed speech83% writer coverage
0%32.5%65.0%Biased Writer Voice-61.5 ptsWriter: 61.5%JL Botor: 0.0%0.0%Quote-first Misdirection+44.1 ptsWriter: 0.0%JL Botor: 44.1%44.1%Politically Left Leaning B-18.1 ptsWriter: 18.1%JL Botor: 0.0%0.0%Indoctrination-13.4 ptsWriter: 13.4%JL Botor: 0.0%0.0%Attempt to Sell a Product -3.9 ptsWriter: 3.9%JL Botor: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.