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Showing posts with label Risk Stratification. Show all posts
Showing posts with label Risk Stratification. Show all posts

Version 1 Care Management to Prevent Hospital Readmission Fails (Unsurprisingly)

Does this high profile randomized study "prove" that telephone follow-up of recently discharged inpatients fails to prevent readmissions? 

Should hospital leaders reconsider care management programs aimed at reducing readmissions?

Hardly, says the Population Health Blog.

Here's how the study was designed:

To be eligible, patients had to be aged 55 or older and without mental illness or serious cancer. They also had to be able to use a telephone. If the patient and their doctor agreed, patients were then randomly assigned to either:

1) "usual" care that consisted of a pre-discharge review of medications, follow up and other instructions plus a 10 day medication supply, or

2) "intervention" care that was comprised of pre-discharge disease-specific education using motivational interviewing, personalized notification of the primary care physician for follow-up, a medication schedule, an in-person follow-up by a registered nurse within 24 hours and follow-up telephone calls on days 1-3 and 6-10 after discharge.

Over 6300 patients were reviewed, 1781 patients were considered and 700 were enrolled in the study. 679 patients completed 30 days, 581 patients completed 90 days and 561 patients completed 180 days of follow-up.  The mean age of the study population was 66 years, 56% had mild cognitive impairment, 33% had visited an emergency room in the prior six months and 62% used English as their primary language. 

In the intervention group, nurses managed to complete their two phone calls 83% of the time.

Results?

"There were no statistically significant differences in the number of ED visits or readmissions between the intervention and usual care groups at 30 days (0.33 vs. 0.26 per person-month; 112 vs. 89 events), 90 days (0.23 vs. 0.20 per person-month; 238 vs. 203 events), or 180 days (0.20 vs. 0.18 per person-month; 392 vs. 370 events)." 

There was also no different in the number of primary care visits between the two groups.

Ouch.

The authors speculate that this patient population already had a high level of support from primary care providers and good access to medications.  In addition, a high prevalence of cognitive impairment may have blunted the nurse interventions.  Last but not least, the authors state that further reductions in ED visits or readmissions may require more in-person home visits in lieu of just telephone calls.

The Population Health Blog offers another thought:  the study was doomed from the start.

Years ago, the Ver. 1.0 "disease management" vendors learned the hard way that aggressively "calling" every patient with did not reduce complications, costs or health care utilization. 

The study described above was a reprise of that long discredited approach. Calling every person being discharged from a hospital may help some patients, but not all. 

Since that time, "population health" vendors have discovered risk stratification. By restricting their in-person and telephonic follow-up to patients discovered to be at greatest risk by advances in"big data" analytics, resources can be better focused on the patients who are most likely to benefit and the likelihood of a return on investment is accordingly increased.

And it's not like this is rocket science.  Surveys and clinical algorithms like this and this respectively can help identify recently discharged patients at high risk of readmission. 

If the study above had incorporated this approach and only enrolled the high risk patients, they might have had a positive study. 

That's the real lesson for hospital leaders and their care management programs.

Image from Wikipedia

Of Risk Stratification, Health System Variation and "Stupid" Decision-Making

A fly in the ointment
Years ago, a middle-aged Population Health Blog patient came in for a routine follow-up appointment.  Since his last visit, he had developed iron deficiency anemia. Since slow blood loss can be a sign of an early and curable cancer in the gastrointestinal tract, the PHB recommended a series of unpleasant tests. After a rather routine explanation of the time, expense and inconvenience of those tests, the patient surprised the PHB with a one-word answer: "No."

He went on to live for decades.

Which brings the PHB to this JAMA article on individually-tailored screening for another type of cancer. While even screening for prostate cancer is controversial, it's possible to stratify a man's risk of the condition with some questions, examination data and test results.  That risk can be portrayed in lay terms (there is a "42-in-100 chance" that cancer is present, but doing a biopsy has a "4-in-100 chance of causing an infection..."). 

The points of the well-written article is that 1) risk-stratification can be used to identify persons at high vs. low risk, 2) the decisions to screen, perform additional testing and embark on treatment can be, based on that risk, "tailored" to maximize a good outcome and 3) patients can use their level of risk to ultimately decide how they want testing and treatment to achieve the outcome they want.

Bravo, says the PHB.  While we're on the cusp of understanding whether a more sophisticated approach to screening ultimately leads to better outcomes than the standard all-or-none guideline (USPSTF "recommends against prostate-specific antigen (PSA)-based screening for prostate cancer"), there is enough face-validity to believe that patients will ultimately benefit.

But there is a fly in the ointment and a monkey in this wrench.

The fly? Variation will not go away. While health system bureaucrats everywhere would prefer that 0% of men undergo prostate screening, that 100% women over 50 get mammograms, and that 0% of us have a body mass index in excess of 25, individuals - after looking as the risk-benefit here, here and here, may choose otherwise.  We don't know what the "right" screening rates are.  In fact, we may not be asking the right questions.

The monkey?  Some "bad" decisions will occur. Once persons truly understand the benefits, risks and alternatives (including not dying prematurely of a preventable illness and side-effect risks that are less than driving in a car), they are allowed to make "stupid" decisions.  Physicians and bureaucrats may not like it when anemic patients, like the one described above, refuse no-brainer recommendations, but in a free country that's the price we pay. Our challenge is to make sure that our patients have all the information they need (which is apparently not the case here) to make a truly informed decision.

Image from Wikipedia
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