Health Insurance Company Response to High Risk Patients

Today’s Managing Health Care Costs Indicator is 25%

Click image to enlarge. Source above

Today’s NY Times has an article focused on high risk patients – who in the under-65 population represent about 1% of patients, and 25% of all medical costs – over $100,000 per year. Full Report Here (Registration Required)

The concentration of the cost of care is an important observation – the bottom 50% of Americans represent about 3% of total medical costs – so interventions to lower the cost of care for these least expensive health plan members are bound to be unsuccessful. This is also why programs to convince Americans to go see the doctor raise costs.   (Good Op-Ed on this topic from Dartmouth University today, too).

The robust and publicly-available Medicare claims database has been studied extensively – but many of the conclusions from the over 65 population are not applicable to the younger cohort insured through employer-based plans

-       Medicare beneficiaries are highly likely to be readmitted to the hospital (almost 20% in 30 days). Readmission rates are much lower  in the non-Medicare population (5-8%) , and many of these readmissions are planned, like followup inpatient chemotherapy.

-       Medicare spends a quarter of its dollars on patients in the last 6 months of life.   Commercial plans actually spend a very small portion of their claims on end of life care, since death is much less common in this population

-       Medicare beneficiaries stay with that insurance plan for the remainder of their lives, while commercial health plans “churn” membership at a rate of 15% or more a year

Care management interventions should not assume that the commercial population is akin to the Medicare populations.

Health plans have hired platoons of nurses to do outbound calls to high-risk beneficiaries– and they charge employers large fees to perform this work.    However, most of the evidence of efficacy of this intervention is highly anecdotal. From Reed Abelson’s article:

When Wendy Meath, a 59-year-old with diabetes, was hospitalized a year ago, she was identified by HealthPartners as someone who needed help to control her disease. She had been admitted for kidney stones, one of many possible complications of diabetes. Although she had insurance through her husband, she was unemployed.

Since leaving the hospital, where she was admitted for 12 days for a series of complications from the surgery to remove the stones, Ms. Meath has been in regular contact with one of HealthPartners’ nurses, who serves as a case manager. The nurse calls at least once a month and checks in after she goes to the doctor for any developments. The health plan also assigned a social worker to help her with the cost of medications and other obstacles that were preventing her from taking better care of herself. “It makes me feel like I’m not alone,” Ms. Meath said.

“They’re trying to prevent the big things from happening, which is great,” she said.

But the iron-clad evidence of the effectiveness of this intervention is still lacking.

Health plans tend to cite compelling anecdotes – but here’s what we should look at to assess efficacy of these programs

Structure 

a. What intervention is in place?    Are the elements evidence-based?  Is there a measurement plan?

Process

a.     How many of the targeted high risk members actually participate?  Many health plan programs have half or more targeted members refuse to participate.   That sharply limits potential effectiveness

 Outcome

a.     Are there changes in clinical course due to the intervention?

b.     Are there beneficial financial outcomes as a result?

There are two major problems with the outcome evaluations I’ve seen – most of which have focused on only program participants.  

The first is regression to the mean.  The likelihood that Wendy Meath will be hospitalized again over the next year is low.  This doesn’t mean that the intervention has been successful – it’s what you’d expect in the year following such an admission.

The second problem is selection bias. The half of patients who eagerly participate in the intervention are fundamentally different than those who refuse.  Even efforts to do “propensity matching,” to try to adjust for known differences between participants and nonparticipants, aren’t effective for adjusting for these differences.

We should only attribute cost savings to these programs if there are cost savings over the entire population.  Further, we should only find claims of success believable if enough members were engaged to credibly lead to the claimed cost savings.

I believe that high risk programs performed in the provider realm are likely to get more patient engagement – and could lead to more success in preventing bad outcomes and lowering costs.    Health plan leverage in the future might have more to do with payment reform than with hiring legions of remote nurses.

Of course, we will have to measure that too!

Asthma Program A Good Idea, but Cost Saving Claims Not Credible

Today’s Managing Health Care Costs Indicator is $1.46

Click image to enlarge.  Source 

Today’s Boston Globe front page rings out with a “top of the fold” headline “Children’s Hospital Reports Asthma Progress.”

Hospitalizations for asthma have been dramatically cut by a program that helps families reduce the conditions that trigger attacks, saving $1.46 in hospital care for every $1 spent on prevention, according to a Children’s Hospital Boston study being released today.

The actual article was e-published by Pediatrics today.  The link to the article is here.  Harvard Link

The truth, as always, is murkier than the headline.

First of all – this study is laudable for many reasons.   It aimed to lower the asthma morbidity in underprivileged communities – which is where asthma has the most devastating impact.   Asthma hospitalization rates are five times higher among Blacks and Hispanics compared to whites – and the study group was largely Black and Hispanic. The researchers sifted through the literature about what works, and developed a multidisciplinary intervention based on this literature.  They measured carefully.  They counted only “hard” savings like decreased hospitalizations and ED visits, and did not attribute monetary value to

Researchers made notable efforts to be culturally sensitive, and offered home community health worker and nursing visits, supplies to help decrease allergens, and even special vacuum cleaners to decrease airborne particulate matter.  When necessary, the program did extermination to help prevent exposure to allergens that could trigger asthma attacks.  

Now, the concerns.

This is a study with 283 patients, who were handpicked by researchers because they appeared to be at highest risk for recurrent emergency department visit or hospitalization based on their recent history.  The study was offered to 562 families; so the take-up rate was about 50%.    The cost savings are comparing these study patients with patients from different zip codes – who were not subject to the same selection process.

Note that the study was designed in 2003 and carried out from 2005-2008. This gives you the sense of how complicated these studies are to complete.

Here are two reasons why this study likely overstates the benefit from this intervention

1.  Regression to the mean.  Those asthmatics who are chosen because they appear very ill today will as a group always have far fewer hospitalizations and ED visits going forward than they had in the recent past.   Here’s a link to a 2004 study where the control group (no intervention) had more than a 30% decrease in cost.   Here’s a link to my letter to the editor, where I pointed out that even this understated the true amount of regression to the mean.
2. Selection bias.   The families that were willing to participate and were able to persist in the intervention likely had more means than those who refused, were unable to be reached, or dropped out during the course of the trial.  The stated control group did not have such selection.

To the Globe’s credit, the last two paragraphs quote a researcher who points out that this was not a randomized controlled trial. 

It’s heartening that it appears that there was some decrease in asthma morbidity that coincided with this intervention.   I would be very cautious about the cost-saving claims from this article.

Two major public health interventions to lower asthma morbidity – decreasing air pollution and decreasing parental and teenage smoking rates, are not mentioned in the article.  We tend to overemphasize interventions in the medical model while we underinvest in effective public health interventions.