Breaking News
December 13, 2018 - Drug repositioning strategy identifies potential new treatments for epilepsy
December 13, 2018 - Chronic rhinitis associated with hospital readmissions for asthma and COPD patients
December 13, 2018 - Food poisoning discovery could save lives
December 13, 2018 - Cloned antibodies show potential to treat, diagnose life-threatening fungal infections
December 13, 2018 - Exercise may reduce colorectal cancer risk after weight loss
December 13, 2018 - Russian scientists create hardware-information system for brain disorders treatment
December 13, 2018 - Moderate alcohol consumption linked with lower risk of hospitalization
December 13, 2018 - Nurturing Healthy Neighborhoods | NIH News in Health
December 13, 2018 - Rise in meth and opioid use during pregnancy
December 13, 2018 - Researchers gain new insights into pediatric tumors
December 13, 2018 - FSU study finds racial disparity among adolescents receiving flu vaccine
December 13, 2018 - Drug cocktail induces cancer cell death by switching off energy supply
December 13, 2018 - Baculovirus virion completely eliminates liver-stage parasites in mouse model
December 13, 2018 - Researchers create noninvasive technology that detects when nerve cells fire
December 13, 2018 - Treating patients with hypertension induced albuminuria
December 13, 2018 - New substance could improve efficacy of established breast cancer treatments
December 13, 2018 - Scientists develop new stem cell line to study conversion of stem cells into muscle
December 13, 2018 - Re-programming the body’s energy pathway boosts kidney self-repair
December 13, 2018 - Research findings could help improve treatment of anxiety and post-traumatic stress disorders
December 13, 2018 - The Microbiome Movement announce Microbiotica as official industry partner
December 13, 2018 - New study reveals potential benefits of cEEG monitoring for infant ICU patients
December 13, 2018 - Whole-body imaging PET/MRI offers information to guide treatment options for prostate cancer
December 13, 2018 - International investigators fight against the negative campaign on benzodiazepines
December 13, 2018 - Targeting biochemical pathway may lead to new therapies for alleviating symptoms of anxiety disorders
December 13, 2018 - FDA Approves Tolsura (SUBA®-itraconazole capsules) for the Treatment of Certain Fungal Infections
December 13, 2018 - Are scientists studying the wrong kind of mice?
December 13, 2018 - Computer memory: A scientific team builds a virtual model of a key brain region
December 13, 2018 - Visual inspection alone is insufficient to diagnose skin cancer
December 13, 2018 - Paternal grandfather’s access to food associated with grandson’s mortality risk
December 13, 2018 - Our brain senses angry voices in a flash, study shows
December 13, 2018 - PM2.5 Exposure Linked to Asthma Rescue Medication Use
December 13, 2018 - Can’t exercise? A hot bath may help improve inflammation, metabolism, study suggests
December 13, 2018 - Can artificial intelligence help doctors with the human side of medicine?
December 13, 2018 - Virginia Tech and UC San Diego researchers team up to develop nonopioid drug for chronic pain
December 13, 2018 - NIH offers support for HIV care and prevention research in the southern United States
December 12, 2018 - Activating brain region could revive the urge to socialize among opioid addicts
December 12, 2018 - Relationship impairment appears to interfere with seeking mental health treatment in men
December 12, 2018 - Sleep, Don’t Cram, Before Finals for Better Grades
December 12, 2018 - Effective treatments for urticarial vasculitis
December 12, 2018 - Gun violence is a public health issue: One physician’s story
December 12, 2018 - The Science of Healthy Aging
December 12, 2018 - Yes to yoghurt and cheese: New improved Mediterranean diet
December 12, 2018 - Researchers uncover a number of previously unknown insecticide resistance mechanisms
December 12, 2018 - Regulating the immune system’s ‘regulator’
December 12, 2018 - In breaking bad news, the comfort of silence
December 12, 2018 - Study finds upward link between alcohol consumption and physical activity in college students
December 12, 2018 - FDA issues warning letter to Zhejiang Huahai Pharmaceutical involved in valsartan recall
December 12, 2018 - Weight history at ages 20 and 40 could help predict patients’ future risk of heart failure
December 12, 2018 - Presence of antiphospholipid antibodies tied to first-time MI
December 12, 2018 - DNA analysis finds that stethoscopes are teaming with bacteria
December 12, 2018 - New study could help inform research on preventing falls
December 12, 2018 - Women and men with heart attack symptoms receive different care from EMS
December 12, 2018 - Disrupted biological clock can contribute to onset of diseases, USC study shows
December 12, 2018 - New publications generate controversy over the value of reducing salt consumption in populations
December 12, 2018 - New data from TAILORx trial confirms lack of chemo benefit regardless of race or ethnicity
December 12, 2018 - Specific class of biomarkers can accurately indicate the severity of cancer
December 12, 2018 - Meds Taken Do Not Vary With ADL Impairment in Heart Failure
December 12, 2018 - Long-term study shows that HIV-2 is deadlier than previously thought
December 12, 2018 - People living near oil and gas wells show early signs of cardiovascular disease
December 12, 2018 - IONTAS founder and pioneer in phage display technology attends Nobel Prize Award Ceremony
December 12, 2018 - People who eat red meat have high levels of chemical associated with heart disease, study finds
December 12, 2018 - New method uses water molecules to unlock neurons’ secrets
December 12, 2018 - Genetics study offers hope for new acne treatment
December 12, 2018 - New computer model predicts prostate cancer progression
December 12, 2018 - Nobel Laureates lecture about immune checkpoint therapy for cancer treatment
December 12, 2018 - More Illnesses From Tainted Romaine Lettuce Reported
December 12, 2018 - Aspirin could reduce HIV infections in women
December 12, 2018 - The EORTC Brain Tumor Group and Protagen AG collaborate to study immuno-competence of long-term glioblastoma survivors
December 12, 2018 - Insights into magnetotactic bacteria could guide development of biological nanorobots
December 12, 2018 - Sacrificial immune cells alert body to infection
December 12, 2018 - Low-salt diet may be more beneficial for females than males
December 12, 2018 - Major soil organic matter compound battles chronic wasting disease
December 12, 2018 - Findings may open up new ways to treat dwarfism and other ER-stress-related conditions
December 12, 2018 - New computational model provides clearer picture of shape-changing cells’ structure and mechanics
December 12, 2018 - 10 Facts on Patient Safety
December 12, 2018 - Poorest dying nearly 10 years younger than the rich in ‘deeply worrying’ trend for UK
December 12, 2018 - Innovative care model for children with ASD reduces use of behavioral drugs in ED
December 12, 2018 - Spending time in and around Hong Kong’s waters linked to better health and wellbeing
December 12, 2018 - Simple measures to prevent weight gain over Christmas
December 12, 2018 - Research advances offer hope for patient-tailored AML treatment
How should an algorithm generate recommendations for patient care?

How should an algorithm generate recommendations for patient care?

image_pdfDownload PDFimage_print

Say you’re a doctor. You’d like guidance on how to treat a particular patient, and you have the opportunity to query a group of physicians about what they’d do next.

Who do you include in that group? All doctors who have seen similar patients? A smaller number of doctors who are considered the best?

These questions are at the root of recent Stanford research.

The study, published in the Journal of Biomedical Informatics, examines a key aspect of medical artificial intelligence: If machines are to provide advice for patient care, who should those machines be learning from?

Jonathan Chen, MD, PhD, tackled this question as the latest step in his quest to build OrderRex, a tool that will mine data from electronic health records to inform medical decisions. In a prototype, an algorithm that works like Amazon’s recommendation feature supplied information to doctors on how their peers managed similar patient cases — i.e., it tells users that other doctors in this situation ordered this medication or this test.

Now, Chen and his colleagues are working through logistics of how the computer decides what to recommend. Research assistant Jason K. Wang is the study’s lead author. Chen, the senior author, told me,

The distinguishing question was, if you had to learn medical practices, should you just try to get everybody’s data and learn from everybody? Or should you try to find the ‘good’ doctors? Then that evokes some really deep follow-up questions, such as, what is a preferred doctor or a good expert? What does that mean? How would we define that?

He asked multiple doctors a simplified version of these questions — if you had to grade each doctor by a number, how would you come by that number? — and tumbled into the usual thicket surrounding physician evaluations. Which outcomes should be considered? What if you see sicker patients? What about hospital readmission, length of stay, and patient satisfaction?

Ultimately, Chen and his colleagues settled on the measure of 30-day patient mortality rate: actual number of deaths compared to expected deaths, as reliably calculated by a computer using three years of electronic health record data.

“We tried a couple of things, but found they were correlated enough that it basically didn’t matter. The doctors who rose to the top of the list versus the bottom — it was a pretty stable list,” Chen said. “Plus, you can’t really game mortality: it’s the most patient-centered outcome there is.”

With “expert” doctors identified as those with low patient mortality rates, the researchers turned to defining “optimal” care to compare with recommendations that the algorithm would produce. They decided to try two different options. One was care that followed standards from clinical practice guidelines based on literature available through such venues as the National Guideline Clearinghouse. The second was care reflecting patterns that typically led to better-than-expected patient outcomes — calculated by the computer from data in the electronic patient records.

With this established, they tested the algorithm to see how its recommendations for care for a condition such as pneumonia compared to both standard clinical practice guidelines and to computer-generated above-average patient care. First, they fed the algorithm information from patients seen by expert doctors. Then, separately, the algorithm looked at patients seen by all doctors.

The result? Not much difference between recommendations derived from care in the expert group versus all of the doctors.

Essentially, Chen said, outlier behavior from specific doctors was neutralized. And without significant differences in the results, the findings argue for building machine-learning models around data from more physicians rather than a curated bunch. The logic is similar to calculating an average: with more numbers in the equation, each number carries less weight and the average is less influenced by individual numbers — including anomalies.

Chen summed it up:

As a human, it’s not feasible to interview thousands of people to help learn medical practice, so I’m going to seek out a few key mentors and experts. What large datasets and computational algorithms enable us to do is to essentially learn from ‘everybody,’ rather than being constrained to learn from a small number of “experts.”

With this question resolved, Chen and his colleagues have now built a prototype user interface incorporating the suggestion system, and they plan to bring in doctors to test it with simulated patient cases.

“The next big challenge to closing the loop on a learning health care system,” he said, “is… where we don’t just learn interesting things from clinical data, but we design, study, and evaluate how to deliver that information back to clinicians and patients.”

Photo by Markus Spiske

Tagged with:

About author

Related Articles