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Why a Majority of Readmission Risk Tools Fail in Practice

Apr 28, 2014• 8

By Eric Heil

Potentially preventable readmissions are a scourge on the US healthcare system.

Each year millions of patients are discharged from the hospital, only to return within 30, 60, or 90 days.

Not only do patients, their families, and their caregivers suffer as a result, but hospitals, insurers, and the government waste billions of dollars that could be spent on other public health priorities. Many if not most of these readmissions could have been avoided if clinicians had effective, scalable, and timely methods for identifying not only which patients were the highest risk, but what steps should have been taken to mitigate that risk.

In recent years there has been a proliferation of readmission risk assessment models, yet readmission rates have barely budged. Fundamental flaws exist in most approaches in the areas of Data, Model Adaptability and Clinical Workflow Integration.

Many tools rely solely on historical patient data mined from the EHR or are disease-specific models that cannot be scaled to address all readmissions challenges. Models that rely on data collected at discharge are not timely enough to enable clinicians to take meaningful action, and ones that are not well-integrated into clinical workflow are not easily adopted.

For a readmission risk assessment tool to achieve a meaningful and long-lasting impact, these common pitfalls must be avoided at all costs. Today, I’m going to address some of the many data challenges faced when trying to risk assess patients.

Historical Data does not Predict Future Readmissions

Anybody who has ever invested in the stock market, rooted for a local sports team, or stuck with a television show past its tenth season knows that past performance gives you no guarantee on future returns. Factors beyond our control and beyond our ability to predict may cause our fortunes to turn on a dime.

Consider the Dow Jones Industrial Average: Those who had any investments around July of 2007 remember the feelings of unabashed optimism and certainty inspired by the great bull run of the early 2000s. Unfortunately, those same investors also most assuredly remember what happened shortly thereafter, when the financial crisis of 2008 erased trillions of dollars’ worth of wealth.

A recent systematic review of readmission risk models concluded that many hospitals still model their approach to identifying high-risk patients based on historical admissions, claims data, and outdated information on patient populations [1].

Using these old data to model and predict readmissions is dangerous. And with increasing pressure on hospitals to reduce readmissions, this approach also runs the risk of becoming extremely costly. Just ask the guy who splurged on Brooklyn Dodgers tickets in 1958, or the guy who put all his money into 8-track cassettes in 1979, or the guy who started a Hummer dealership in 2005.

Any of these folks will tell you that past performance data can not only betray you, but it may also prevent you from recognizing the obsolescence of your sources. As a result, this data may cost you a fortune.

Health Reform and the Mission of Nonprofit Hospitals

Apr 28, 2014• 1

By Mary Crossley

Ever since 1969, when the IRS established the “community benefit” standard for hospital tax exemption, nonprofit hospitals have been able to achieve federal tax exemption without any precise accountability for the benefits they provided.

The ACA’s passage, however, ushered in significant changes to federal tax-exemption standards for hospitals.

The new § 501(r) of the Internal Revenue Code requires hospitals to take numerous measures, including establishing written financial assistance policies, limiting the amount charged to patients eligible for financial assistance, and limiting their use of “extraordinary collection actions” against patients.

These requirements responded to concerns about how some purportedly “charitable” hospitals treated uninsured patients and, more generally, hospitals’ lack of transparency regarding indigent care.

They stop well short, however, of requiring hospitals to provide any particular quantum of free care to patients unable to pay.

Section 501(r) also incorporates a different tack, requiring that at least once every three years, a hospital conduct a “community health needs assessment” (CHNA) and adopt an “implementation strategy” to respond to the needs identified by the assessment.

The needs assessment requirement is novel as a matter of federal tax policy, but is similar to mandates previously existing in a number of states.

As announced in the statute and fleshed out in Proposed Regulations issued by the IRS in April 2013, the CHNA requirement entails a series of steps.

In identifying and prioritizing community health needs, a hospital must take into account “input from persons who represent the broad interests of the community served by the hospital facility, including those with special knowledge of or expertise in public health.”

Once the assessment is completed, the hospital must make a report on it “widely available to the public” and adopt an “implementation strategy” to meet the community health needs it identified.

Doctors Should Be Paid for Outcomes. But Which Outcomes?

Apr 28, 2014• 7

By Hans Duvefelt, MD

Should we be paid for outcomes?

This is often proposed, but I have trouble understanding it. Real outcomes are not blood pressure or blood sugar numbers; they are deaths, strokes, heart attacks, amputations, hospital-acquired infections and the like.

In today’s medicine-as-manufacturing paradigm, such events are seen as preventable and punishable.

Ironically, the U.S. insurance industry has no trouble recognizing “Acts of God” or “force majeure” as events beyond human control in spheres other than healthcare.

There is too little discussion about patients’ free choice or responsibility. Both in medical malpractice cases and in the healthcare debate, it appears that it is the doctor’s fault if the patient doesn’t get well.

If my diabetic patient doesn’t follow my advice, I must not have tried hard enough, the logic goes, so I should be penalized with a smaller paycheck.

The dark side of such a system is that doctors might cull such patients from their practices in self defense and not accept new ones.

I read about some practices not accepting new patients taking more than three medications. In the example I read, the explanation was not having time for complicated patients, but such a policy would also reduce the number of patients exposing the doctor to the risk of bad outcomes.

A few comparisons illustrate the dilemma of paying for outcomes:

Do firefighters not get paid if the house they’re dousing to the best of their ability still burns down?

Does the detective investigating a homicide not get a paycheck if the crime remains unsolved?

Does the military get less money if we lose a war?

Even if we were to accept and embrace outcomes-based reimbursement in health care, how would we measure outcomes?

What We’ve Learned from Horizontal and Vertical Integration of Physicians

Apr 25, 2014• 10

By Lawton R. Burns & Aditi Sen

As health care reform rolls out, there is a growing focus on restructuring the health service delivery system in the hope of improving health care quality and “bending the cost curve.”

A key part of this focus has been on physician organization and, in particular, moving toward large, multispecialty physician groups or hospital-physician systems that can provide integrated, coordinated patient care (e.g., through “Accountable Care Organizations”).

In a recent chapter in Advances in Health Care Management’s Annual Review of Health Care Management, however, we and our co-author Jeff Goldsmith find that there is little evidence for the superiority of these integrated models in terms of patient care quality or cost-savings, and that the trends toward physician consolidation has been much less dramatic than is often thought.

Using data from a variety of sources, we find there are two separate phenomena at work in physician organization. At one end of the spectrum (bottom tail of the size distribution of physician groups), the majority of physicians continue to practice in small groups, although there has been some movement from really small practices (one to three or four physicians) to slightly larger groups (five to nine physicians).

Still, nearly two-thirds of office-based physicians continue to practice in solo settings, two-person partnerships, and small (usually single specialty) groups with five or fewer physicians.

At the other end of the spectrum (upper tail of the distribution), however, is a smaller number of very large and rapidly growing multispecialty physician groups, which are often owned by hospitals, health plans, private equity firms, or other non-physician sponsors.

These two stories of what is happening in the distribution of physician group size are described as “a tale of two tails.”

The Medical Chart: Ground Zero for the Deterioration of Patient Care

Apr 25, 2014• 32

By Val Jones, MD

EMR Alert – Featuring radiologist note in illegible font color

For the past couple of years I’ve been working as a traveling physician in 13 states across the U.S.

I chose to adopt the “locum tenens lifestyle” because I enjoy the challenge of working with diverse teams of peers and patient populations.

I believe that this kind of work makes me a better doctor, as I am exposed to the widest possible array of technology, specialist experience, and diagnostic (and logistical) conundrums. During my down times I like to think about what I’ve learned so that I can try to make things better for my next group of patients.

This week I’ve been considering how in-patient doctoring has changed since I was in medical school. Unfortunately, my experience is that most of the changes have been for the worse.

While we may have a larger variety of treatment options and better diagnostic capabilities, it seems that we have pursued them at the expense of the fundamentals of good patient care.

What use is a radio-isotope-tagged red blood cell nuclear scan if we forget to stop giving aspirin to someone with a gastrointestinal bleed?

Why Are Al Lewis and Vik Khanna Such Jerks?

Apr 24, 2014• 16

By Al Lewis & Vik Khanna

Recently, The Health Care Blog published a post by Robert Sutton asking why there were so many jerks in medicine.

That posting made the underlying assumption that being a jerk is a bad thing. In response, we are posting today a defense — really more an explanation of the features and benefits — of jerkdom, at least in our segment of healthcare, wellness and outcomes measurement.

In 1976 an obscure graduate student named Laura Ulrich (now a Pulitzer Prize-winning professor) wrote: “History is seldom made by well-behaved women.” That statement could be applied much more broadly. In any field governed by voluntary consensus – especially where the consensus specifically and financially benefits the people making the consensus – radical change does not happen jerklessly.

The best current example might be the critique of Choosing Wisely in the New England Journal of Medicine in which it was pointed out that only three specialty societies blacklisted controversial procedures still performed in significant enough quantity to affect that specialty’s economics.

(Another example of financially fueled consensus gone awry is the RUC, also frequently and justifiably excoriated in The Health Care Blog and elsewhere.)

Specifically, there are three reasons we act like jerks. (Four reasons if you include selling our book, but we acted like jerks well before our book came out.)

First, as Upton Sinclair said, “You can’t prove something to someone whose salary depends on believing the opposite.” Hence, making nice rarely works and may backfire when you are pointing out a total waste that also happens to be someone else’s income.

After Community Care of North Carolina (CCNC) sponsored an outcomes study by Mercer finding massive savings through their patient-centered medical home (PCMH) in an age cohort (children under one year of age) in which no utilization reduction took place and which, as luck would have it, was not enrolled in the PCMH anyway, we kindly wrote to them and offered to show them the error of their ways, privately.

We didn’t get a response. We repeated the offer when they put out another RFP for even more validation, pointing out that using the HCUP database meant no RFP was needed — we would be able to give them an answer in less time than it would take them to evaluate the RFP responses, and save them close to $500,000 in taxpayer money too.

Placing Diagnosis Errors on the Policy Agenda

Apr 24, 2014• 19

By Robert Berenson, MD

“Not everything that counts can be counted, and not everything that can be counted counts.”

This aphorism has been deliciously, but, alas, incorrectly attributed to Albert Einstein (the saying actually has mixed origins, but credit properly might be given to sociologist William Bruce Cameron, writing in 1963).

But, whatever its provenance, the saying is particularly appropriate in describing the woeful lack of attention paid to the long-standing problem of diagnosis errors in the provision of health care services.

Last week academic researchers from Baylor and the University of Texas published important research estimating that one in 20 adults in the U.S., or roughly 12 million people every year, receive an error of diagnosis—a wrong, missed or delayed diagnosis—in ambulatory care.

This likely represents a conservative estimate of the incidence of such errors in ambulatory care and does not attempt to include inpatient hospital care or care provided in nursing homes and post-acute care facilities, such as rehab hospitals.

The news media correctly decided that this peer-reviewed finding deserved prominent attention—it was a lead story on “NBC Nightly News” and other national news programs.

It seems that attaching a large number to the prevalence of such errors provided the needed news hook to give the problem the attention it has long deserved. Surveys reveal that the public is worried as much about a misdiagnosis or missed diagnosis as any other quality and safety issue in health care.

Autopsy studies performed over time find that unacceptably high rates of diagnosis errors persist; similarly, diagnosis errors continue to represent a leading cause of medical malpractice suits.

But even without newsworthy body counts, the problem of diagnosis errors has been known to clinicians for decades, if largely ignored by stakeholders and policy-makers as a major quality and safety problem.

The ICD-10 Extension: For Whatever Reasons, Congress Did the Right Thing.

Apr 23, 2014• 13

By Edmund Billings, MD

Did you hear the one about the CMS administrator who was asked what it would take to delay the 2014 ICD-10 implementation deadline? An act of Congress, he smugly replied, according to unverified reports.

Good thing he didn’t say an act of God.

So, now that CMS has been overruled by Congress, who wins and who loses? Who’s happy and who’s not?

The answers to those questions illustrate the resource disparity that prevails in healthcare and, mirroring the broader economy, threatens to get worse. The disappointed Have-a-lot hospitals are equipped with the resources to meet ICD-10 deadlines and always felt pretty confident of a positive outcome; the Have-not facilities were never all that sure they would make it and are breathing a collective sigh of relief.

First off, it is necessary to recognize that ICD-10 is far superior to ICD-9 for expressing clinical diagnoses and procedures. Yes, some of the codes seem ridiculous … “pecked by chickens,” for example. But people do get pecked by chickens, or plowed into by sea lions, so I believe the intent is positive, as will be the results.

An example: I saw my physician this past week at a Have-a-lot health system in San Francisco and I asked what she thinks of the ICD-10 extension.

“We’re already using (ICD-10) in our EHR and it is much better than ICD-9,” she said. “When I want to code for right flank pain, it’s right there. I don’t have to go with back pain or abdominal pain and fudge flank in. It’s easier and more accurate.”

“If I was still on paper and not our EHR, which I like,” she added, “my superbill would go from 1 page to 10. SNOMED works.”

Moore’s Law in Healthcare – Three Predictions

Apr 23, 2014• 32

By Nick Dawson

Je n’ai fait celle-ci plus longue que parce que je n’ai pas eu le loisir de la faire plus courte. —Blaise Pascal

Translation: I have made this longer than usual because I have not had time to make it shorter.

As Appley as it gets.

A while ago I was challenged to write about what an Apple-like approach to healthcare might look like.

That challenge has been weighing on me.

For starters, we’re all over Appled aren’t we? Maligned anecdotes about Steve Jobs and the iPhone make their way into almost every presentation remotely related to innovation or technology. Triteness aside, I’ve been stalled because Apple is really a philosophy, not a series of steps or lessons learned. (Although, they are nonetheless methodical.)

Instead, what I’ve been kicking around in the ole noggin are three notional predictions, which I’ll assert are inevitabilities which will fundamentally disrupt healthcare delivery as we know it today.

What follows is about as Appley as I’m likely to get. Despite big-bang product launches, Apple actually plays the long game. They introduce small features into products to affect user behavior years before a flagship product takes advantage of those reprogramed behaviors.

That’s how they disrupt.

I believe there are three meaningful, unstoppable trends, in our current world which will significantly alter healthcare. The steps taken towards these inevitabilities, along the way, are what will define the innovators and leaders. They are the ones who see this future and know how to drive towards it.

The three trends are:

Tools and culture which favor individual empowerment
The commoditization and automation of diagnosis
Accelerated globalization of treatment options

But wait, there’s Moore.

Don’t worry, I’m not going to leave you hanging. I’ll attempt to rationalize each of these points and explain why, particularly when considered as a bundle, they are a powerful force for disruption. And to prime that pump, we have to talk about Gordon Moore.

Obamacare Observations from the Marketplace

Apr 23, 2014• 4

By Robert Laszewski

A few observations from my travels and conversations in the marketplace:

About half of the enrollments are coming from people who were previously insured and half are not. When I try to gauge this, I go to carriers who had high market share before Obamacare and have maintained that through the first open enrollment. Some carriers have said only a small percentage of their enrollments had coverage before but health plans only would know who they insured before.

By sticking to the high market share carriers who have maintained a stable market share and knowing how many of their customers are repeat buyers, it’s possible to get a better sense for the overall market. Other conventional polls have suggested the repeat buyers are closer to two-thirds of the exchange enrollees.

The number of those in the key 18-34 demographic group improved only slightly during the last month of open enrollment so the average age is still high. The actuaries I talk to think this issue of average age is made to be far more important than it should be. It is better to have a young group than an old group. But remember, the youngest people pay one-third of the premium that older people pay.

The real issue is are we getting a large enough group to get the proper cross section of healthy and sick?

The bigger concern continues to be the relatively small number of previously uninsured people who have signed up compared to the size of the eligible group. The recent report released by Express Scripts reporting on very costly pharmacy claim experience from January and February enrollees is far more concerning than the average age.