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Tag: Quality

On Teaching Hospitals and Conflict of Interest and Other Politically Charged Topics

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By ASHISH JHA, MD

How much does it matter which hospital you go to? Of course, it matters a lot – hospitals vary enormously on quality of care, and choosing the right hospital can mean the difference between life and death. The problem is that it’s hard for most people to know how to choose. Useful data on patient outcomes remain hard to find, and even though Medicare provides data on patient mortality for select conditions on their Hospital Compare website, those mortality rates are calculated and reported in ways that make nearly every hospital look average.

Some people select to receive their care at teaching hospitals. Studies in the 1990s and early 2000s found that teaching hospitals performed better, but there was also evidence that they were more expensive. As “quality” metrics exploded, teaching hospitals often found themselves on the wrong end of the performance stick with more hospital-acquired conditions and more readmissions. In nearly every national pay-for-performance scheme, they seemed to be doing worse than average, not better. In an era focused on high-value care, the narrative has increasingly become that teaching hospitals are not any better – just more expensive.

But is this true? On the one measure that matters most to patients when it comes to hospital care – whether you live or die – are teaching hospitals truly no better or possibly worse? About a year ago, that was the conversation I had with a brilliant junior colleague, Laura Burke. When we scoured the literature, we found that there had been no recent, broad-based examination of patient outcomes at teaching versus non-teaching hospitals. So we decided to take this on.

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MACRA and the New Quality Payment Program: Most Frequently Asked Questions

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November 2 | 2-3 PM EST      / With THCB 

On Oct. 14 the Centers for Medicare and Medicaid Services (CMS) released detailed regulations for implementation of the Medicare Access and CHIP Reauthorization Act (MACRA). With so many changes to the Merit-Based Incentive Payment System (MIPS) and the Advanced Alternative Payment Model (APM) track, we at Health Catalyst have heard many questions and comments. This is understandable, as the substantial 962-page proposal has grown to the 2,398-page final rule. Also, since nearly all providers will be subject to the new Quality Payment Program (QPP), understanding MACRA and what it means for providers is imperative.

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The ACA: We Got Quantity but What About Quality?

By ABRAAR KARAN, MD

flying cadeuciiOne of the main goals of the Affordable Care Act (ACA), perhaps second only to improving access, was to improve the quality of care in our health system. Now several years out, we are at a point where we can ask some difficult questions as they relate to value and equity. Did the ACA improve quality of care in the ways it intended to? Did it do so for some people, or hospitals, more than others?

How did the ACA Attempt to Improve Quality?

Three particular programs created by the ACA are worthy to note in this regard. The Hospital Acquired Condition Reduction Program (HACRP) took effect on October 1, 2014 and was created to penalize hospitals scoring in the worst quartile for rates of hospital-acquired conditions outlined by the CMS. The Hospital Readmissions Reduction Program (HRRP), which began for patients discharged on October 1, 2012, required CMS to reduce payments to short-term, acute-care hospitals for readmissions within 30 days for specific conditions, including acute myocardial infarction, pneumonia, and heart failure. The Medicare Hospital Value-Based Purchasing Program (HVBP) started in FY2013, was built to improve quality of care for Medicare patients by rewarding acute-care hospitals with incentive payments for improvements on a number of established quality measures related to clinical processes and outcomes, efficiency, safety, and patient experience.

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Building Better Metrics: Invest in “Good” Primary Care and Get What You Pay For

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By NIRAN Al-AGBA, MD

flying cadeuciiIn 1978, the Institute of Medicine published A Manpower Policy for Primary Health Care: Report of a Study (IOM, 1978) where they defined primary care as “integrated, accessible services by clinicians accountable for addressing a majority of heath care needs, developing a sustained partnership with patients, and practicing in the context of family and community.” The four main features of “good” primary care based on this definition are: 1. First-contact access for new medical issues, 2. Long-term and patient (not disease)-focused care, 3. Comprehensive in scope for most medical issues, and 4. Care coordination when specialty referral is required.  These metrics ring as true today as they did many years ago.

Estimates suggest that a primary care physician would spend 21.7 hours per day to provide all recommended acute, chronic, and preventive care for a panel of 2,500 patients.  An average workday of 8 hours extrapolates to an ideal panel of 909 patients; let us make it an even 1000 to simplify.  A primary care physician could easily meet acute, chronic, and preventative needs of 1000 patients, thereby improving access.  Our panels are much larger due to the shortage of available primary care physicians and poor reimbursement which keeps us enslaved.  Pay us what we are worth and then utilize this “first-access” metric to judge our “quality.”

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Quality v. Quantity

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By MICHEL ACCAD, MD

A few weeks ago, the medical community received unexpected good news from the government about a “simplification of quality measures:”

Strictly speaking, and contrary to what Mr. Slavitt’s tweet would lead us to believe, the agreement to the new rules was primarily between commercial insurers and CMS, the Center for Medicare and Medicaid Services. Physicians were not actually party to the deal.

Nevertheless, doctors were expected to greet the news with cheers. As Rich Duszak reported, Adam Slavitt, acting administrator for CMS, also declared that “patients and care providers deserve a uniform approach to measure [sic] quality.”

Indeed, we all deserve uniform quality measures. Equality in quality!

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Cost, Value & Tools

By PETER PRONOVOST, MD

Peter PronovostLike a pro golfer swears by a certain brand of clubs or a marathon runner has a chosen make of shoes, surgeons can form strong loyalties to the tools of their craft. Preferences for these items — such as artificial hips and knees, surgical screws, stents, pacemakers and other implants — develop over time, perhaps out of habit or acquired during their training.

Of course, surgeons should have what they need to be at the top of their trade. But the downside of too much variation is that it can drive up the costs of procedures for hospitals, insurers and even patients. When a hospital carries seven brands of the same type of product instead of one or two, it’s not as likely to get volume discounts. Moreover, if hospitals within a health system negotiate independently of one another, they may pay drastically different prices for the exact same item.

Carrying many brands of a given item may also increase risks for error and patient harm. Staff members need to be trained and competent in a variety of tools; the greater the number of tools, the greater the risk for error.

These physician preference items are no small contributor to health care costs. Around the year 2020, medical supplies are expected to eclipse labor as the biggest expense for hospitals, according to the Association for Healthcare Resource and Materials Management. Higher costs for physician preference items are major drivers of this increase.Continue reading…

A Proposal to Increase the Transparency and Quality of Electronic Health Records

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By HAYWARD ZWERLING, MD

flying cadeucii The electronic health record (EHR) is now used by the majority of physicians during every patient encounter. The EHR has become the most important tool in our “black bag” and precisely for that reason, the EHR must be highly accurate and free of bias. As our most heavily utilized tool, the EHR must also be flexible and highly optimized so as to ensure it does not adversely impact the delivery of healthcare. Unfortunately, numerous surveys have found widespread physician dissatisfaction with EHR design.

The fact that EHR programming code is shielded from objective scrutiny by independent evaluators increases the risk that the EHR will contain errors and bias which could adversely impact our patient’s health, hinder our ability to deliver healthcare, “warp” the design of the healthcare system and drain financial resources from our patients and society.

EHR “errors” are well documented in the literature and are referred to as “e-iatrogenesis” or “technology induced” errors. “Bias” in EHR programming code is not discussed in the literature.

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Why Data Governance Needs a Henry Kissinger

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By DALE SANDERS

Dale SandersThe number of mergers, acquisitions, and collaborative partnerships in healthcare continues to skyrocket. That’s not going to change for the next few years unless the FTC decides to be more restrictive. In all of these activities, older generation executives (I can say that because I’m older) have underestimated the importance and difficulties—technically and culturally—of integrating data and data governance in these new organizations, and the difficulties are exponentially more complicated in partnerships and collaboratives that have no formal overarching governance body. In 2014, 100 percent of Pioneer ACOs reported that they had underestimated the challenges of data integration and how the lack of data integration has had a major and negative impact on the performance of the ACOs.

Seamless Data Governance

After 33 years of professional observations and being buried up to my neck in this topic, especially the last two years as the topic finally matures in healthcare, I’m convinced that the role model organizations in data governance practice it seamlessly. That is, it’s difficult to point a finger directly at a thing called “Data Governance” in these organizations, because it’s completely engrained, everywhere. As I’ll state below, it reminds me of the U.S. transition in the early 1980s when organizations finally realized that product quality was not something that you could put in an oversight-driven Quality Department, operating as a separate function. Quality must be culturally embedded in every teammates’ DNA. Data governance is the same, especially data quality.Continue reading…

Blood Clots Show Limits of Quality Care Penalties

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By ELLIOTT R. HAUT, MD

Iflying cadeuciin the world of medicine, blood clots during hospitalization have become synonymous with imperfect care. As many as 600,000 patients per year experience a blood clot, and more than 100,000 die as a result, accounting for between 5 and 10 percent of hospital deaths. Regulatory agencies have taken clots as signals that safety and quality have been compromised, and have instituted significant financial penalties on physicians and hospitals for these “preventable events.”

In reality, clots aren’t always as preventable in real-world practice as they are in theory. Blood clots happen even under conditions of perfect, best-practice patient care, which should be seen as testimony to the limits of penalty schemes aiming to improve the quality of care. These penalties should be re-examined.

In a study recently published in JAMA Surgery of 128 blood clot or venous thromboembolism (VTE) cases, my team found that nearly 50 percent of the cases reviewed at The Johns Hopkins Hospital were not actually preventable. In fact, these patients received perfect care by all objective measures — all appropriate preventive measures were taken, including the prescription of the ideal medication and assuring that every dose of medicine was administered. Yet the blood clots still occurred, and the hospital was still financially penalized.

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Why Health Care Performance Measures Need Their Own Grades

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By MATT AUSTIN

Screen Shot 2015-07-13 at 7.04.54 PM

Some measures of health care quality and patient safety should be taken with a grain of salt. A few need a spoonful.

In April, a team of Johns Hopkins researchers published an article examining how well a state of Maryland pay-for-performance program measure for dangerous blood clots identified cases that were potentially preventable. In reviewing the clinical records of 157 hospital patients deemed by the state program to have developed these clots — known as deep vein thrombosis and pulmonary embolism — they found that more than 40 percent had been misclassified. The vast majority of these patients had clots that were not truly preventable, such as those associated with central catheters, for which the efficacy of prophylaxis remains unproven.

These misclassified cases of blood clots resulted in potentially $200,000 in lost reimbursement from the state, which penalizes hospitals when the additional treatment costs related to more than 60 preventable harms exceeds established benchmarks.

Why the discrepancies? The state identified cases of these clots using billing data, which utilize the diagnosis codes that medical billing specialists enter on claims. These data, also known as administrative data, lack the detail that would be available in the actual clinical record, considered by many to be the most trusted source for safety and quality measures.

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