Generic but ambitious...
January can be restorative following the chaos of the holidays but often equal parts annoying and cloying as well. You can't swing a pencil without hitting tomes about how to boost your sales in 2020, new books abound that expand the listicle mindset, or other distractions to separate you from your money.
I am going to whisper a little secret, it won't work. What works is hard work. Really hard work. You must consume more than you create. Read, listen, and watch everything. Jerry Saltz described the ordinary brilliantly--"generic but ambitious". I follow Jerry for many reasons--most importantly are his lessons on observation. Yes, I could read the stacks of books falling like manna from the heavens about data visualization. But that is too narrow of a focus. I like edges from other perspectives. I subscribe to ARTFORUM to learn how to consume information. My reality will never be yours, what worked for me will never work the same way for you, but the hard work will.
I recommend listening to Jerry's interview on the Longform Podcast. He became an art critic in his 40s from a career as a truck driver...his humility and cleverness is and should be industry agnostic. Let me know what you think.
A poem by Wallace Stevens describes my thoughts exactly. This excerpt shares the awareness that 20 men will have 20 unique experiences and will perceive the bridge AND the village uniquely. Read the poem in its entirety here.
Metaphors of a Magnifico by Wallace Stevens (1879-1955)
Twenty men crossing a bridge,
Into a village,
Are twenty men crossing twenty bridges,
Into twenty villages...
A recent article in the New England Journal of Medicine, and reported by the New York Times reminded me of those vapid real-estate reality shows. A couple looks at a perfectly serviceable home in need of a bit of sweat equity but declare the house a failure--"Oh I could not live with that wallpaper, can you show us something else?".
​In the case of the medical literature I don't know whom to blame first, the shoddy media coverage or the confusing study design. The wallpaper can be changed folks.
The article in the New York Times doesn't seem to like the wallpaper and can't see beyond the hype to actually look at the merits or opportunities to query the data in a way that might be meaningful.
I am not blaming the brilliant author because let's face it--he didn't create the headline. But I am blaming the metric--avoiding repeat hospitalization or hospital readmission rates. Maybe we should look earnestly into better measures for this highly edited study population.
The study has quite robust inclusion/exclusion criteria for starters.
Inclusion criteria:
at least one hospital admission at any of four Camden-area hospital systems in the 6 months before the index admission,
at least two chronic conditions;
and at least two of the following traits or conditions:
use of at least five active outpatient medications,
difficulty accessing services,
lack of social support,
coexisting mental health condition
active drug habit, and homelessness.
Exclusion criteria:
uninsured
cognitive impairment
oncologic care or had been admitted for a surgical procedure for an acute health problem, for mental health care (with no coexisting physical health conditions), or for complications of a progressive chronic disease for which limited treatments were available.
Assuming that most readers of the article are simply going to think the program was unsuccessful, here are a few tools (below) I am pulling into the data literacy workshop so we can continue to question questions while also questioning answers. Follow along for insights from the workshop. I don't want to reveal to much here as discovery and discussion will be in "real time."
CMS defines readmission rates within the 30 day time-frame in order to capture events most likely associated with the independent admission. I am assuming then that a 180 day time-frame is a bit noisier.
"Readmission and death rates are measured within 30 days, because readmissions and deaths after a longer time period may have less to do with the care gotten in the hospital and more to do with other complicating illnesses, patients’ own behavior, or care provided to patients after hospital discharge."--Medicare.gov
Dissecting racial bias in an algorithm used to manage the health of populations
​What does race have to do with it (link to discussion of bias)
Graphical presentation of confounding in directed acyclic graphs
Health Care Hotspotting--A Randomized, Controlled Trial
Supplement to: Finkelstein A, Zhou A, Taubman S, Doyle J. Health care hotspotting — a randomized, controlled trial. N Engl J Med 2020;382:152-62. DOI: 10.1056/NEJMsa1906848
Trouble accessing clinical research articles? Try Sci-Hub...
A recent study, Dissecting racial bias in an algorithm used to manage the health of populations sheds some light on how to reform how we evaluate interventions targeted toward social determinants of health.
​The bias introduced in an algorithm widely used in hospital systems revealed that black patients were considerably sicker when compared to white patients at the 97th percentile metric--a qualifier for being referred for additional supports. Although the use of healthcare costs appears to be an effective measure to indicate interventions successful in managing patient outcomes--the racial biases are evident.
When the algorithm score is replaces by number of comorbid conditions vs. medical expenditure a more equitable referral pattern is observed at the 97th percentile.
I have reviewed the supplemental data from the "Hot-spotting" article and will be reviewing in more detail in future posts. I don't want to "spoil" the end for folks enrolled in the workshop! But stay-tuned...
​The authors are planning additional analyses and I anticipate insights regarding improvements in a wider variety of patient populations. Often being ambitious is not the only goal--we need to be curious--not generic.
Future data workshop "buckets" to highlight Envision2030
