Prescription opioid misuse motive latent classes: outcomes from a nationally representative US sample

Prescription opioid misuse (POM) contributes to a larger opioid crisis in the US and Canada, with over 17 000 US POM-related overdose deaths in 2017. Our aims were to (1) identify specific profiles of respondents based on POM motives using the US National Survey on Drug Use and Health (NSDUH) and (2) compare profile respondents on sociodemographics, substance use and mental and physical health outcomes.

Analyses included 2017–18 NSDUH respondents with data on POM motives (n = 4810). POM was defined as prescription opioid use in a way not intended by the prescriber, including use without a prescription, in larger amounts or more frequently. Nine POM motives for the most recent episode were assessed, including ‘to relieve physical pain’ and ‘to get high’. Latent classes, based on POM motives, were estimated. Classes were compared on sociodemographics, substance use and physical and mental health outcomes.

Eight latent classes were identified (in order of prevalence): pain relief only, relaxpain relief, sleep-pain relief, multi-motive, high, experimenter, emotional coping and dependent/hooked. Compared to the pain relief only group, the high and multi-motive classes had higher odds of all substance use outcomes, with the dependent/hooked class having higher odds on all but one outcome. Six of the eight classes had higher odds of past-year mental health treatment and suicidal ideation than the pain relief only class.

Screening for pain, pain conditions, problematic substance use and psychopathology are recommended in those with any POM. While those in the dependent/hooked, multi-motive and emotional coping classes are most likely to have prescription opioid use disorder (OUD), screening for OUD symptoms in all individuals with POM is also warranted.

The full article can be downloaded below.

Combining deep learning with token selection for patient phenotyping from electronic health records

Artificial intelligence provides the opportunity to reveal important information buried in large amounts of complex data. Electronic health records (eHRs) are a source of such big data that provide a multitude of health related clinical information about patients. However, text data from eHRs, e.g., discharge summary notes, are challenging in their analysis because these notes are free-form texts and the writing formats and styles vary considerably between different records. For this reason, in this paper we study deep learning neural networks in combination with natural language processing to analyze text data from clinical discharge summaries. We provide a detail analysis of patient phenotyping, i.e., the automatic prediction of ten patient disorders, by investigating the influence of network architectures, sample sizes and information content of tokens. Importantly, for patients suffering from Chronic Pain, the disorder that is the most diffcult one to classify, we fnd the largest performance gain for a combined word- and sentence-level input convolutional neural network (ws-CNN). As a general result, we fnd that the combination of data quality and data quantity of the text data is playing a crucial role for using more complex network architectures that improve significantly beyond a word-level input CNN model. From our investigations of learning curves and token selection mechanisms, we conclude that for such a transition one requires larger sample sizes because the amount of information per sample is quite small and only carried by few tokens and token categories. Interestingly, we found that the token frequency in the eHRs follow a Zipf law and we utilized this behavior to investigate the information content of tokens by defining a token selection mechanism. The latter addresses also issues of explainable AI.

The full article can be downloaded below.  

Suicide Rate Boosts Health Insurer Efforts To Curb Loneliness

The high U.S. suicide rate could embolden health insurer efforts to curb loneliness and address other social determinants that can lead to poor health outcomes and illnesses.

A new report Thursday from the Commonwealth Fund showed the U.S. having the “highest suicide rate of any wealthy nation.” U.S. suicides account for 14 deaths for every 100,000 people, or double the rate of the United Kingdom as one example, according to the Commonwealth Fund report, which compared the U.S. to 10 other “high-income nations” in the Organization for Economic Cooperation and Development.

The rising suicide rate comes as the U.S. spends a much higher amount on healthcare services per capita than these other wealthy countries. And it’s another sign that the U.S. “can do better, and … should start by assuring everyone can get the care they need, when they need it,” Commonwealth Fund president Dr. David Blumenthal said.

The full Forbes article can be viewed at this link.

U.S. Health Care from a Global Perspective, 2019: Higher Spending, Worse Outcomes?

This analysis is the latest in a series of Commonwealth Fund cross-national comparisons that uses health data from the Organisation for Economic Co-operation and Development (OECD) to assess U.S. health care system spending, outcomes, risk factors and prevention, utilization, and quality, relative to 10 other high-income countries: Australia, Canada, France, Germany, the Netherlands, New Zealand, Norway, Sweden, Switzerland, and the United Kingdom. We also compare U.S. performance to that of the OECD average, comprising 36 high-income member countries.

The full Commonwealth Fund analysis can be viewed at this link.  

Thinking Beyond The Rebate Debate: Strategies To Bring Value To Healthcare

The Trump administration may have dropped the drug rebate rule last year, but the American people haven’t given up their search for security.

Healthcare is a $3.5 trillion industry projected to balloon even more in the next decade and consumers are finally saying “enough is enough.” They’re speaking out against unsustainable costs and directing a sizable portion of their frustration toward the pharmaceutical industry. Eight in ten Americans now say prescription drug prices are “unreasonable,” as pharma scrambles to build a legislative firewall by putting significant sums of money behind candidates who will protect their interests.

As we move closer to the 2020 presidential election, the voices calling for change will only get louder. And as a result, the need to introduce new strategies to lower all healthcare costs will only become more critical.

The full Forbes article can be viewed at this link.  

9 things Americans need to learn from the rest of the world’s health care systems

So the dissatisfying answer to “so what can the US learn from these other countries’ successes?” is: It’s complicated. But my hope for this series is it would speak to the kinds of values and strategies, if less the specific policies, that are necessary to achieve universal health care.

Every health system is different. But all of them, except ours, have figured out a way to make being uninsured or going bankrupt over medical bills a thing of the past. The US can do better.

The full Vox article can be viewed at this link.  

How AI is battling the coronavirus outbreak

When a mysterious illness first pops up, it can be difficult for governments and public health officials to gather information quickly and coordinate a response. But new artificial intelligence technology can automatically mine through news reports and online content from around the world, helping experts recognize anomalies that could lead to a potential epidemic or, worse, a pandemic. In other words, our new AI overlords might actually help us survive the next plague.

These new AI capabilities are on full display with the recent outbreak of COVID-19, which was identified early by a Canadian firm called BlueDot, which is one of a number of companies that use data to evaluate public health risks. The company, which says it conducts “automated infectious disease surveillance,” notified its customers about the new form of coronavirus at the end of December, days before both the US Centers for Disease Control and Prevention (CDC) and the World Health Organization (WHO) sent out official notices, as reported by Wired. Now nearing the end of January, the respiratory virus that’s been linked to the city of Wuhan in China has already claimed the lives of more than 100 people. Cases have also popped up in several other countries, including the United States, and the CDC is warning Americans to avoid non-essential travel to China.

The full Vox article can be viewed at this link.  

Who Are the Key Players in Social Determinants of Health Strategy?

The healthcare industry has come to a consensus that the social determinants of health and population health are essential considerations for delivering on value-based care. But it takes a village, as the adage says, and organizations need to anticipate a number of stakeholders for making these programs a reality.

SDOH programs are inherently multi-stakeholder — they require the medical provider who will identify high-risk patients, fund sources, care coordinators or caseworkers, and the community-based partners that will help carry out interventions. Each of these stakeholders needs to be working in the same direction in order for programs to be successful.

The full Patient Engagement HIT article can be viewed at this link.  

AI: Pharma's Perfect Medicine

AI appears set to be the thing that separates the next generation of business success stories and market dropouts. It has revolutionized the transportation industry by bringing the science fiction dream of autonomous cars into reality, as driverless taxis have already been tested and deployed in the U.S.

Further indicators of its importance come from finance companies like Goldman Sachs, JPMorgan and Morgan Stanley — all of which have aggressively expanded their data and tech teams over the past year — looking to deploy AI projects that will give them the competitive edge against their rivals. The application of this technology ranges from the mundane to the absurd, seemingly with no sector able to escape its influence — and the pharma industry is no different.

The full Forbes article can be viewed at this link.  

When Insurance Won't Cover Drugs, Americans Make 'Tough Choices' About Their Health

The majority of Americans have health insurance that includes coverage for prescription drugs. But unfortunately that doesn't ensure that they can afford the specific drugs their doctors prescribe for them.

In fact, many Americans report that their insurance plans sometimes don't cover a drug they need — and nearly half the people whom this happens to say they simply don't fill the prescription. That's according to a poll released this month on income inequality from NPR, the Robert Wood Johnson Foundation and the Harvard T.H. Chan School of Public Health.

The full NPR article can be viewed at this link.