I read the report of a phase 3 RCT of a “new” breast cancer drug but I had the feeling that I had already read this before. Later I realized that this was indeed a new trial of a new drug, but that I had read a very similar report of a very similar drug with very similar results and conclusions. This new drug is a PARP inhibitor called talazoparib and the deja vu was related to another PARP inhibitor drug called olaparib tested in the same patient population of advanced breast cancer patients with a BRCA mutation. The control arms were the same: physician choice of drug, except that physicians couldn’t choose the one drug that is probably most effective in this patient population (carboplatin). The results were nearly the same: these drugs improved progression-free survival, but didn’t improve overall survival. In another commentary, I had raised some questions on the choice of control arm, endpoint and quality of data about the olaparib trial when it was published last year. This current talazoparib trial is so similar to the olaparib trial that you can literally replace the word “olaparib” with “talazoparib” in that commentary and all statements will stay valid.
The oncology version of half-full, half-empty glass
The PARP inhibitors olaparib and niraparib are also approved in ovarian cancer based on improvement in progression-free survival (PFS), without improving overall survival (OS). If a drug doesn’t improve OS but improves only PFS, it should also improve quality of life to justify its use. According to two new reports, these drugs do not appear to improve quality of life. The niraparibtrial reported that the patients were able to “maintain” their quality of life during treatment while the olaparib trial reported that olaparib did not have a “significant detrimental effect” on quality of life. I find it remarkable that a drug that isn’t proven to improve survival is lauded for not significantly worsening quality of life … at $10,000 a month!
It is also important to recognize that these drugs were tested as maintenance therapy against placebos. For “maintenance therapies,” as explained in this paper, improving PFS alone is not an important endpoint. That’s why I am also not excited about this new trial of sorafenib maintenance in ovarian cancer. A drug has to be very ineffective to fail to improve even PFS as a maintenance therapy against placebo. Continue reading…
In the run-up up to this month’s mid-term elections, health care appears to be just one of many burning political issues that will be influencing Americans’ votes. But delve into nearly any issue—the economy, the environment, immigration, civil rights, gun control—and you’ll find circumstances and events influencing human health, often resulting in profound physical, emotional and financial distress.
Evidence suggests that separating immigrant children from their families could cause lasting emotional trauma. Gun violence and adverse weather events destroy lives and property, and create hazardous living conditions. Structural racism has been linked to health inequities, for instance where housing discrimination leads to segregation of black buyers and renters in neighborhoods with poor living conditions. The list goes on, and through every such experience, affected individuals, their loved ones, and their communities learn implicitly what health care providers have long known: that health status depends on much more than access to, or quality of, health care.
Some of the most influential factors are called social determinants of health, and they include education, immigration status, access to safe drinking water, and others. Society and industry must collaborate to address them if we are to reduce the extraordinary human and economic costs of poor health in our nation. Fortunately, many providers have embraced the challenge, and are tackling it in myriad, innovative ways. Continue reading…
Hardly a day goes by that I don’t read the term “Disruptive Innovation” cited in relation to health care delivery. This might seem like a good thing, given that our expensive, wasteful, and in some cases frightfully ineffective traditional delivery model is in dire need of transformation. However, the term is frequently misunderstood to refer to any innovation representing a radical departure from an industry’s prior best offerings. In fact, it actually has a very specific definition.
Disruptive Innovation is the phenomenon by which an innovation transforms an existing market or sector by introducing simplicity, convenience, accessibility, and affordability where complication and high cost have become the status quo—eventually completely redefining the industry. It has played out in markets from home entertainment to teeth whitening, and it could make health care delivery more effective by making providers’ care processes, as well as individuals’ own self-care regimes easier and less costly. This, in turn, would reduce the need for both more, and more expensive, interventions over time.
Unfortunately, disruption has been slow to emerge in the health care sector. It’s been thwarted by the broader health care industry’s unique structure, which tends to prioritize the needs of commercial insurers and large employers (who pay the most for consumercare) over those of health care consumers themselves. It also stacks the deck against disruptive entrepreneurs, since established providers effectively control professional licensing requirements, and (along with insurers) access to patients & key delivery partners.
A few weeks ago, I saw a young patient who was suffering from an ear infection. It was his fourth visit in eight weeks, as the infection had proven resistant to an escalating series of antibiotics prescribed so far. It was time to bring out a heavier hitter. I prescribed Ciprofloxacin, an antibiotic rarely used in pediatrics, yet effective for some drug-resistant pediatric infections.
The patient was on the state Medicaid insurance and required a so-called prior authorization, or PA, for Ciprofloxacin. Consisting of additional paperwork that physicians are required to fill out before pharmacists can fill prescriptions for certain drugs, PAs boil down to yet another cost-cutting measure implemented by insurers to stand between patients and certain costly drugs.
The PA process usually takes from 48-72 hours, and it’s not infrequent for requests to be denied, even when the physician has demonstrated an undeniable medical need for the drug in question.
Everyone agrees that health care is bankrupting the nation. The prevailing winds have carried the argument that a system that pays per unit of health care delivered and thus favors volume over value is responsible. The problem, you see, was the doctors. They were just incentivized to do too much. This incontrovertible fact was the basis for changes in the healthcare system that favored hospital employment and have made the salaried physician the new normal. Yet, health care costs remain ascendant.
It turns out overutilization in the US healthcare system isn’t what its cracked up to be.
Figure 1. Utilization rates in different health care systems
A recent analysis (Figure 1) by Papanicolas et al., in JAMA demonstrates that while the United States is no slouch with regards to volume of imaging and procedures in a variety of different categories, it does not explain a health care system twice as expensive as its nearest competitor. The problem turns out not to be volume, rather its the unit price of healthcare in the United States.
Health Care Costs and Glass Houses
There are many stones cast by all the various players in healthcare when it comes to cost, and of course, everyone bears some degree of responsibility, but it’s also clear that some folks live in larger glass houses than others. The most beautiful of all the glass houses are those built by hospitals. From 1996 to 2013, it was not population growth, health status, doctors visits, or prescription drugs that drove spending increases. Sixty-three percent of the increase in cost over an almost 20-year time span can be attributed to hospital stays and testing during doctor visits. Consider that the average hospital stay in the US costs $18,142, and lasts 4.9 days compared to other industrialized countries where average hospital stays last 7.7 days, and cost $6,222. But despite these exorbitant prices hospital systems in the United States complain they barely stay afloat.
The highly anticipated unveiling of the Apple Watch Series 4 caused a news and social media sensation. Apple coined the iconic timepiece as the “guardian of your health”, with health tracking functionalities such as the ability to detect atrial fibrillation (AFib) by a self-performed electrocardiogram (ECG). But from patients’ and carepartners’ perspectives, there is a long road to a universally accessible, seamlessly implemented, mass-adoption, and meaningful use for this wearable technology.
Many experts, such as Dr. Eric Topol a cardiologist at the Scripps Research Institute, and other reports, were quick to highlight concerns about the consequences of false positives. The Apple Watch was criticized as a source for unnecessary anxiety. A letter from the Center for Devices and Radiological Health (CDRH) of the FDA, which cleared the ECG app as a class II over-the-counter (OTC) device, highlighted the risks to health and potential mitigation measures that the Apple Watch posed. Unfortunately, the vast majority of concerns in the public domain haven’t emphasized the risks to health due to poor implementation, integration, and adoption strategies of digital tools and wearables.
The current health care system needs to be significantly refreshed as it is not positioned to simply drop in advancements, such as those offered by the Apple Watch Series 4, into everyday patient care. Having Dr. Ivor Benjamin, president of the American Heart Association (AHA), endorse the Apple Watch at the Apple Keynote Event did wonders for the mass marketing appeal. It would’ve have been more credible and demonstrated more value if he stated that the AHA devised a strategic clinical practice implementation guide for cardiologists, created patient education materials for using the Apple Watch, partnered with payers to incentivize doctors to adopt the technology, and reimburse for virtual consults to support remote patient monitoring (RPM).
If your heart throbs with desire for the new Apple Watch, the Series 4 itself can track that pitter-pat through its much-publicized ability to provide continuous heart rate readings.
On the other hand, if you’re depressed that you didn’t buy Apple stock years ago, your iPhone’s Face ID might be able to discover your dismay and connect you to a therapist.
In its recent rollout of the Apple Watch, company chief operating officer Jeff Williams enthused that the device could become “an intelligent guardian for your health.” Apple watching over your health, however, might involve much more than a watch.
As doctors, we all took an oath when we graduated from medical school to “do no harm” to patients. It is, therefore, our duty to speak up and take action when there is an opportunity to prevent harm and improve patient care, safety and well-being. On average, the opioid crisis is killing more Americans on a monthly basis than traumatic injuries. It is time for the medical community to raise its voice even more loudly in support of proven technology that helps curb this crisis.
This month, California Governor Jerry Brown became the latest state lawmaker to embrace electronic prescribing for controlled substances (EPCS) — joining nearly a dozen other states that have passed legislation mandating that health care providers and pharmacies use the technology. The Golden State law was signed at the same time the U.S. Senate passed a bill requiring e-prescriptions for any reimbursement under Medicare Part D.
Clearly, EPCS is emerging as a key tool in the fight against opioid abuse. And legislators aren’t alone in driving the trend — corporations are playing a key role as well. Walmart, one of the nation’s largest pharmacy chains, is requiring EPCS by January 1, 2020. In their press release, it was noted that “E-prescriptions are proven to be less prone to errors, they cannot be altered or copied and are electronically trackable.”
You’ve probably heard of Bitcoin, but we doubt you’ve heard of Dentacoin, MedTokens, or Curecoin.
These are healthcare specific cryptocurrencies born from Initial Coin Offerings or ICOs. In this article, we’ll briefly recap the trend of ICOs (aka token offerings) and provide you with a summary financial analysis of how this trend has played out among 138 healthcare ICOs. The results to-date are enlightening, but disappointing. We believe there’s still potential for some projects to be successful.
What’s an ICO? Here’s a quick take from Wikipedia and we’ll point you to an Appendix that will guide you to additional resources:
An ICO is a type of funding using cryptocurrencies…In an ICO, a quantity of cryptocurrency is sold in the form of “tokens” (“coins”) to speculators or investors, in exchange for legal tender or other cryptocurrencies. The tokens sold are promoted as future functional units of currency if or when the ICO’s funding goal is met and the project launches.
Autonomous Research found that ICOs raised over $7 billion in 2017 and are slated to raise $12 billion in 2018, with some mega projects raising billions of dollars each.
Apologies on the hiatus for posting on THCB. As many of you know, I was running around getting Health 2.0 in order this past weekend. Today we are featuring a piece on understanding how machine learning can actually work in health care today-Matthew Holt
By LEONARD D’ AVOLIO, PhD
There’s plenty of coverage on what machine learning may do for healthcare and when. Painfully little has been written for non-technical healthcare leaders whose job it is to successfully execute in the real world with real returns. It’s time to address that gap for two reasons.
First, if you are responsible for improving care, operations, and/or the bottom line in a value-based environment, you will soon be forced to make decisions related to machine learning. Second, the way this stuff actually works is incredibly inconsistent with the way it’s being sold and the way we’re used to using data/information technology in healthcare.
I’ve been fortunate to have spent the past dozen years designing machine learning-powered solutions for healthcare across hundreds of academic medical centers, international public health projects, and health plans as a researcher, consultant, director, and CEO. Here’s a list of what I wish I had known years ago.