Medical Care Quotes

“Today, what's normal is being redefined: from vaginal birth to surgical birth; from 'My water broke,' to 'Let's break your water;' from 'It's time' to 'It's time for the induction.' As medical anthropologist Robbie Davis-Floyd writes, 'in the early twenty-first century, we do not know what normal birth is.' Most practicing obstetricians have never witnessed an unplugged birth that wasn't an accident. Women are even beginning to deny normal birth to themselves: if 'normal' means being induced, immobilized by wires and tubes, sped up with drugs, all the while knowing that there's a good chance of surgery, well, might as well just cut to the chase, so to speak. 'Just give me a cesarean,' some are saying. And who can blame them? They want to avoid what they think of as normal birth.”
― Jennifer Block, Pushed: The Painful Truth About Childbirth and Modern Maternity Care

“She looked into the room. So many machines and wires and tubes - a reminder that the human body was an incredible miracle, its countless autonomic functions a gift when they were operating as intended, and a cumbersome nightmare to have to approximate when they were not.”
― J.R. Ward, Consumed

“Your dying was a difficult enterprise.
First, petty things took up your energies,
The small but clustering duties of the sick,
Irritant as the cough’s dry rhetoric.
Those hours of waiting for pills, shot, X-ray
Or test (while you read novels two a day)
Already with a kind of clumsy stealth
Distanced you from the habits of your health.”
― Thom Gunn

“In my over three decades of family practice, I have come to the conclusion that we, as doctors, should provide non-medical people with as much medical information as we can. Not as much as we think they should have, or information just related to the problem at hand, but as much as we can provide. Period.”
― James Hubbard

“Using this technique, Baum et al constructed a forest that contained 1,000 decision trees and looked at 84 co-variates that may have been influencing patients' response or lack of response to the intensive lifestyle modifications program. These variables included a family history of diabetes, muscle cramps in legs and feet, a history of emphysema, kidney disease, amputation, dry skin, loud snoring, marital status, social functioning, hemoglobin A1c, self-reported health, and numerous other characteristics that researchers rarely if ever consider when doing a subgroup analysis. The random forest analysis also allowed the investigators to look at how numerous variables *interact* in multiple combinations to impact clinical outcomes. The Look AHEAD subgroup analyses looked at only 3 possible variables and only one at a time.

In the final analysis, Baum et al. discovered that intensive lifestyle modification averted cardiovascular events for two subgroups, patients with HbA1c 6.8% or higher (poorly managed diabetes) and patients with well-controlled diabetes (Hba1c < 6.8%) and good self-reported health. That finding applied to 85% of the entire patient population studied. On the other hand, the remaining 15% who had controlled diabetes but poor self-reported general health responded negatively to the lifestyle modification regimen. The negative and positive responders cancelled each other out in the initial statistical analysis, falsely concluding that lifestyle modification was useless. The Baum et al. re-analysis lends further support to the belief that a one-size-fits-all approach to medicine is inadequate to address all the individualistic responses that patients have to treatment. ”
― Paul Cerrato, Reinventing Clinical Decision Support: Data Analytics, Artificial Intelligence, and Diagnostic Reasoning

“The US National Institutes of Health states: "There is a lot of overlap between the terms 'precision medicine' and 'personalized medicine.' According to the National Research Council, 'personalized medicine' is an older term with a meaning similar to 'precision medicine.' However, there was concern that the word 'personalized' could be misinterpreted to imply that treatments and preventions are being developed uniquely for each individual; in precision medicine, the focus is on identifying which approaches will be effective for which patients based on genetic, environmental, and lifestyle factors.”
― Paul Cerrato, Reinventing Clinical Decision Support: Data Analytics, Artificial Intelligence, and Diagnostic Reasoning

“When you fund a futile war in a far-off land, something expensive has to be cut at home.”
― Steven Magee