BS Summary: This article contains 27 faulty reasoning types, including Representativeness Heuristic, Confirmation Bias, and Appeal to Authority, with Halo Effect as the most egregious example at 21.9% saturation with 114 hits. Analysis detected 1,028 faulty-reasoning hits from 520 analyzed words, generating a BS Score of 40.1% and a BS Rank of 42% (15,454 of 26,447 articles). This article is better (less manipulative) than 58.40% of the article peer group.

Wisconsin ranks among the best in the country for high-quality hospitals based on federal data. 
Of the 86 Wisconsin hospitals rated by the Centers for Medicare and Medicaid Services, 64 percent received a four- or five-star rating for overall hospital quality. 
Compared to other states, it’s the fourth-highest percentage of top-rated hospitals, and the highest percentage reported among states with 50 or more hospitals, according to the Wisconsin Hospital Association . 
The quality ratings are based on metrics across five categories including re-admissions, patient experience and mortality. 
Nadine Allen , WHA’s chief quality officer, said the ratings are meant to help patients make informed decisions about where they want to receive care. 
She said for many Wisconsin residents, a four- or five-star choice may not be far away. 
“This is not just a couple of our larger systems or larger hospitals,” Allen said. 
“It’s not just in urban areas, but anywhere you go in Wisconsin, you can see the consistent message.” 
Six of the 21 Wisconsin hospitals that received a perfect rating are critical access hospitals , or rural locations that are more than 35 miles from another hospital and have 25 or fewer inpatient beds. 
Another eight critical access hospitals received a four-star rating, out of the 34 total hospitals with that rating. 
“There are some thoughts on critical access hospitals that smaller doesn’t always mean better,” said Kayla Mobley , director of quality services at Tomah Health, a critical access hospital in Monroe County that received a five-star rating this year. 
But Mobley said she sees Tomah Health’s small size as a strength for providing a positive patient experience. 
“We know that they are members of our community,” she said. 
“They’re not just a number when they come here. 
They’re very well our neighbors or our coworkers, and so we want to make sure that we are providing exceptional care for them.” 
Tomah Health, a 25-bed hospital in rural Monroe County, is one of six critical access hospitals in Wisconsin that received a five-star rating from the Centers for Medicare and Medicaid Services this year. 
Photo courtesy of Tomah Health 
Mobley said comparing the quality of care across health systems of different sizes and with different services is complex, and the star rating system doesn’t always capture the nuances. 
That’s in part because not every hospital receives a star rating. 
Allen said the federal agency requires data from a certain number and variety of Medicare and Medicaid patients. 
In Wisconsin, two out of five hospitals in the state did not receive a star rating, according to the Centers for Medicare and Medicaid Services data. 
That includes just over half of the state’s critical access hospitals. 
This year was the first in several years that Tomah Health met the requirements for a rating, according to Mobley. 
She said it reaffirms what the health system has already seen through monitoring patient outcomes and feedback. 
“It was nice to see the five-star recognition,” she said. 
Nearly two-thirds of Wisconsin hospitals receive top federal quality ratings was originally published by Wisconsin Public Radio. 
Article reasoning-pattern comparisonThis article: 16.3%Hope Kirwan: 2.5%Urban Milwaukee: 1.5%Confirmation Bias16.3%This article: 0.0%Hope Kirwan: 1.7%Urban Milwaukee: 0.4%Anchoring Bias0.0%This article: 2.1%Hope Kirwan: 2.8%Urban Milwaukee: 1.3%Availability Heuristic2.1%This article: 17.5%Hope Kirwan: 1.9%Urban Milwaukee: 0.7%Representativeness Heuristic17.5%This article: 0.0%Hope Kirwan: 0.6%Urban Milwaukee: 0.3%Hindsight Bias0.0%This article: 3.5%Hope Kirwan: 0.4%Urban Milwaukee: 0.4%Overconfidence Bias3.5%This article: 1.7%Hope Kirwan: 3.8%Urban Milwaukee: 2.8%Framing Effect1.7%This article: 0.0%Hope Kirwan: 1.2%Urban Milwaukee: 0.3%Loss Aversion0.0%This article: 7.5%Hope Kirwan: 0.5%Urban Milwaukee: 0.5%Status Quo Bias7.5%This article: 0.0%Hope Kirwan: 0.5%Urban Milwaukee: 0.1%Sunk Cost Effect0.0%This article: 11.2%Hope Kirwan: 4.3%Urban Milwaukee: 1.8%Optimism Bias11.2%This article: 0.0%Hope Kirwan: 4.1%Urban Milwaukee: 1.0%Pessimism Bias0.0%This article: 1.9%Hope Kirwan: 3.7%Urban Milwaukee: 4.9%Negativity Bias1.9%This article: 3.3%Hope Kirwan: 0.3%Urban Milwaukee: 1.4%Self-Serving Bias3.3%This article: 3.5%Hope Kirwan: 0.7%Urban Milwaukee: 0.6%Fundamental Attribution Error3.5%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.0%Actor-Observer Bias0.0%This article: 4.4%Hope Kirwan: 0.5%Urban Milwaukee: 0.4%In-Group Bias4.4%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.0%Out-Group Homogeneity Bias0.0%This article: 21.9%Hope Kirwan: 1.2%Urban Milwaukee: 1.4%Halo Effect21.9%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.1%Horn Effect0.0%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.0%Dunning-Kruger Effect0.0%This article: 7.1%Hope Kirwan: 1.7%Urban Milwaukee: 0.9%Recency Bias7.1%This article: 5.8%Hope Kirwan: 0.3%Urban Milwaukee: 0.2%Primacy Effect5.8%This article: 5.6%Hope Kirwan: 0.3%Urban Milwaukee: 0.2%Blind-Spot Bias5.6%This article: 0.0%Hope Kirwan: 0.6%Urban Milwaukee: 0.4%Ad Hominem0.0%This article: 0.0%Hope Kirwan: 0.4%Urban Milwaukee: 0.2%Straw Man0.0%This article: 14.4%Hope Kirwan: 3.5%Urban Milwaukee: 1.4%Appeal to Authority14.4%This article: 0.0%Hope Kirwan: 1.1%Urban Milwaukee: 0.6%False Dilemma0.0%This article: 0.0%Hope Kirwan: 0.5%Urban Milwaukee: 0.5%Slippery Slope0.0%This article: 3.3%Hope Kirwan: 0.2%Urban Milwaukee: 0.1%Circular Reasoning3.3%This article: 8.5%Hope Kirwan: 3.7%Urban Milwaukee: 2.0%Hasty Generalization8.5%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.1%Red Herring0.0%This article: 3.3%Hope Kirwan: 0.2%Urban Milwaukee: 0.6%Bandwagon3.3%This article: 8.1%Hope Kirwan: 2.4%Urban Milwaukee: 3.5%Appeal to Emotion8.1%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.3%Begging the Question0.0%This article: 5.6%Hope Kirwan: 4.3%Urban Milwaukee: 0.9%Post Hoc (False Cause)5.6%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.2%Tu Quoque0.0%This article: 0.0%Hope Kirwan: 0.3%Urban Milwaukee: 0.4%Burden of Proof0.0%This article: 0.0%Hope Kirwan: 0.5%Urban Milwaukee: 0.0%Appeal to Nature0.0%This article: 6.7%Hope Kirwan: 0.4%Urban Milwaukee: 0.1%Composition/Division6.7%This article: 6.2%Hope Kirwan: 2.9%Urban Milwaukee: 1.2%Anecdotal6.2%This article: 7.5%Hope Kirwan: 0.4%Urban Milwaukee: 0.2%No True Scotsman7.5%This article: 11.3%Hope Kirwan: 1.4%Urban Milwaukee: 0.7%Ambiguity (Equivocation)11.3%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Hope Kirwan: 0.1%Urban Milwaukee: 0.2%Middle Ground0.0%This article: 0.0%Hope Kirwan: 0.3%Urban Milwaukee: 0.0%Personal Incredulity0.0%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.0%Special Pleading0.0%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.0%Genetic Fallacy0.0%This article: 0.0%Hope Kirwan: 0.3%Urban Milwaukee: 0.7%Unattributed Quote0.0%This article: 0.0%Hope Kirwan: 0.3%Urban Milwaukee: 1.2%Quote-first Misdirection0.0%This article: 0.0%Hope Kirwan: 0.5%Urban Milwaukee: 0.8%Biased Writer Voice0.0%This article: 4.8%Hope Kirwan: 0.2%Urban Milwaukee: 0.5%Indoctrination4.8%This article: 0.0%Hope Kirwan: 0.1%Urban Milwaukee: 0.6%Politically Left Leaning Bias0.0%This article: 0.0%Hope Kirwan: 0.0%Urban Milwaukee: 0.1%Politically Right Leaning Bias0.0%This article: 4.8%Hope Kirwan: 0.2%Urban Milwaukee: 0.5%Attempt to Sell a Product or S…4.8%

520 words analyzed.

Speakers

2speakers52%attributed speech252writer words
Selected voice

Kayla Mobley

100%flagged-word coverage
176 attributed words66% of attributed speech98% writer coverage

No manipulation-pattern hits were found in this speaker's attributed words or the writer's voice.

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.