By SAURABH JHA, MD

Halfway through the “Bell Curve,” which is an analysis of differences in intelligence between races, I realized what had been bothering me about Charles Murray’s thesis. It wasn’t the accuracy of his analysis, which concerned me, too. It was that he analyzed. The truth, I used to believe, was always beautiful, whether it was what happened in the multiverse at T equals zero, or the historical counterfactual if Neville Chamberlain hadn’t signed the peace accord with Adolph Hitler. After reading Murray’s book, I realized that the truth can be irrelevant, ugly, and utterly useless. Even if the average intelligence of races was truly different, so what? Surely, civilized people must judge each other as individuals, regardless of the veracity of the statistical baggage of their ethnicities.

Murray was castigated, deservedly, for swallowing the bell curve uncritically. But his detractors missed one point. Murray wasn’t just wrong because he was factually wrong or for inquiring. In fact, it was worse, because Murray, it turned out, was wronger than wrong.

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By ASHISH JHA, MD

About a year ago, Yusuke Tsugawa – then a doctoral student in the Harvard health policy PhD program – and I were discussing the evidence around the quality of care delivered by female and male doctors. The data suggested that women practice medicine a little differently than men do. It appeared that practice patterns of female physicians were a little more evidence-based, sticking more closely to clinical guidelines.  There was also some evidence that patients reported better experience when their physician was a woman.  This is certainly important, but the evidence here was limited to a few specific settings or in subgroups of patients. And we had no idea whether these differences translated into what patients care the most about: better outcomes. We decided to tackle this question – do female physicians achieve different outcomes than male physicians. The result of that work is out today in JAMA Internal Medicine.

Our approach

First, we examined differences in patient outcomes for female and male physicians across all medical conditions. Then, we adjusted for patient and physician characteristics. Next, we threw in a hospital “fixed-effect” – a statistical technique that ensures that we only compare male and female physicians within the same hospital. Finally, we did a series of additional analyses to check if our results held across more specific conditions.

We found that female physicians had lower 30-day mortality rates compared to male physicians. Holding patient, physician, and hospital characteristics constant narrowed that gap a little, but not much. After throwing everything into the model that we could, we were still left with a difference of about 0.43 percentage points (see table), a modest but clinically important difference (more on this below).Continue reading…

By DAN ORENSTEIN

On December 7, 2016, the United States Senate approved the 21st Century Cures Act by an overwhelming margin. Having already passed the House with similarly broad bipartisan support, it now goes to President Obama for signature. Several years in the making, the Cures Act is broad and sweeping legislation that covers many topics, mostly on streamlining and accelerating the discovery of new drugs and medical devices. It includes provisions to improve mental health and substance abuse treatment, and to improve patient access to new therapies, among many other areas covered by the Act.

The Act also includes several provisions that will help accelerate the work of health information technology (HIT) companies and providers working to use healthcare data and information to improve outcomes, reduce variations in care, and better coordinate care delivery. These provisions establish programs and oversight to promote health information interoperability and prohibit information blocking practices.

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By LEONARD D’AVOLIO

Recently, a great op-ed published in The Wall Street Journal called “Turn Off the Computer and Listen to the Patient” brought a critical healthcare issue to the forefront of the national discussion. The physician authors, Caleb Gardner, MD and John Levinson, MD, describe the frustrations physicians experience with poor design, federal incentives, and the “one-size-fits-all rules for medical practice” implemented in today’s electronic medical records (EMRs).

From the start, the counter to any criticism of the EMR was that the collection of digital health data will finally make it possible to discover opportunities to improve the quality of care, prevent error, and steer resources to where they are needed most. This is, after all, the story of nearly every other industry post-digitization.

However, many organizations are learning the hard way that the business intelligence tools that were so successful in helping other industries learn from their quantified and reliable sales, inventory, and finance data can be limited in trying to make sense of healthcare’s unstructured, sparse, and often inaccurate clinical data.

Data warehouses and reporting tools — the foundation for understanding quantified and reliable sales, inventory, and finance data of other industries – are useful for required reporting of process measures for CMS, ACO, AQC, and who knows what mandates are next. However, it should be made clear that these multi-year, multi-million dollar investments are designed to address the concerns of fee-for-service care: what happened, to whom, and when. They will not begin to answer the questions most critical to value-based care: what is likely to happen, to whom, and what should be done about it.

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By ART CAPLAN

I just finished my required training about the protection of patient privacy.  Every employee of New York University Langone Medical Center must take an online course and pass an admittedly not very difficult quiz as to our duties regarding patient privacy.  All other American medical centers have the same requirement.  I passed my quiz.  But, despite my certification, I think the effort to protect privacy in health care is a lost cause.  It is time to admit that privacy in health care is dead.  Confessing that privacy has passed on, while reporting a death is often very sad, has many benefits.  Not only is the continued effort to ensure privacy protection futile, it costs a lot of time and money, undermines trust in the health care system, causes confusion that interferes with family needs and, most importantly, likely gets in the way of giving greater benefit to the sick, soon to be sick and those who are not yet born but who will also become ill.

Much of the required teaching in the United States about privacy involves learning a bit about the Health Insurance Portability and Accountability Act of 1996 (HIPAA).  The Federal Office for Civil Rights of the Department of Health and Human Services enforces the law that protects the privacy of health information that could identify a particular patient such as addresses, phone numbers, email address and medical record numbers.  I know from my training that hospitals and health care institutions must report any breach of information going to someone not providing care to a patient or paying for that care. 

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By JIM PURCELL

It has happened.  For the first time, consumers are purchasing more on line than in stores.  Even Black Friday 2016 with its emphasis on traditional shopping saw more people buying on line than in stores (44% compared to 40%).  Mobile phone sales on Cyber Monday, at $1.07 Billion, were up 34% over last year, and Cyber Monday sales exceeded Black Friday’s sales according to Adobe Digital.  Personally, I would rather chew off my right pinkie than venture to a mall on Black Friday, but I did shop online taking me two minutes, without moving from my desk.

The traditional consumer shopping world is changing at light speed, and this dramatic sea change is turning shopping malls inside out, literally and figuratively.  In the process, Amazon has eaten the collective lunches of Macy’s, Penny’s, Kohl’s, and even Wal-Mart.

By way of example, Amazon offers a purchasing experience that makes use by smart phone an obvious choice for Millennials who must be served if businesses are to survive the next two decades. On line price shopping is quick and incredibly convenient; price comparisons are easy; customer service is superb; and such things as Amazon Prime are eliminating shipping costs and speeding delivery.  Returns are easy, requiring only some scotch tape and a stop at a UPS drop box.  What’s not to like in this age of little spare time?

Consequently, brick and mortar stores are in serious jeopardy and are like deer in headlights, reminiscent of companies such as Blockbuster, Kodak, and Xerox, which fell prey to disruptive technologies, products, and trends.  Only time will tell if traditional stores will survive, but the smart money is not investing in malls these days.Continue reading…

By DAVID KENDALL

It’s very possible that the pejorative “Obamacare” could become the even more pejorative “Trumpcare” in a very short period of time. That is because Trump’s and the GOP’s promise to repeal Obamacare — the Affordable Care Act (ACA) — has already hit a snag called reality.

Reports are now circulating that the much-promised repeal of the health care law (60 plus House and Senate votes since 2010) won’t take effect until at least 2019, after the mid-term elections. The excuse is that it’ll take that long to figure out an alternative and get it into place. But congressional calendars and political expedience have nothing to do with the health care market. And without action early in 2017, the health insurance exchanges could collapse in 2018 or sooner — leaving millions without insurance, millions more without protections from pre-existing conditions, and possibly millions more cursing Trumpcare. The only constructive solution is to repair the ACA before, ironically, repealing it and then replacing it with a brand new, untested experiment in 2019.

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By SAM OSBORN

As organizations in every industry invest heavily in business intelligence and analytics to transform their business models, healthcare providers are looking for opportunities to catch up. The challenges to digital transformation in the healthcare industry are significant, but the opportunities are tremendous as applying modern analytics can dramatically speed and improve quality of care while also creating opportunities for new revenue streams and customer retention.

Take, for example, the transformational opportunities presented by applying analytics to Electronic Health Records (EHRs). By applying a layer of advanced analytics to EHRs, providers can identify areas for improvement and opportunity, which is especially important when you consider that these insights can anticipate outcomes and inform actions that can directly affect (and improve) the standard of care.

Analytics aren’t just improving the quality of patient care; they are creating entirely new revenue opportunities in the healthcare industry. MediGain for example, which provides revenue cycle management services to medical practices, hospitals and other care providers, was able to harness advanced analytics to combine data from 300+ sources to deliver on-demand revenue management analytics to their clients. As a result, reporting time was reduced from weeks to near real-time, greatly improving client performance while earning MediGain 1044 percent ROI.

These are just a few examples of healthcare companies leveraging their data and analytics to transform their businesses. These services are no longer optional offerings; Nucleus Research confirms that customers are demanding accessibility to analytics in their daily workflow, meaning that organizations need adapt and offer these solutions in order to remain competitive.

GoodData recently partnered with Anne Moxie, Sr. Analyst of Nucleus Research and Ian Maurer, CIO at MediGain to create a webinar that features the latest strategies and tactics that healthcare companies are using to turn their data and analytics into a profit center, click this link to view on-demand session.

Sam Osborn is head of content at GoodData. This is post is published in conjunction with GoodData‘s sponsorship of the Health 2.0 Conference