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Science Policy Around the Web – August 5, 2016

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By: Fabrício Kury, MD

Genetic engineering

‘Gene drive’ organisms should be tested in field trials, not widely released, experts say

While the Zika virus shows spread into the US, with mosquito-borne transmission having been reported in Miami, the scientific community is eager to kick-start the use of the new biotechnology called Gene Drive. This technique allows for the creation of genes that cheat the trial of chance and get passed on to nearly 100% of the offspring. This way, it is possible to alter the genome of entire populations of species, for example, by making populations of Aedes mosquitoes unable to transmit the Zika or Malaria viruses — if not plainly kill all the Aedes.

The danger of Gene Drive is our lack of knowledge about the impact of drastic alterations in the behavior or biology of one species, and also the consequences from the quick removal of a pervasive species from an ecosystem. The slow progress of Zika into the U.S. through warmer and wetter edges such as Florida and Puerto Rico seems like a window of opportunity for attacking the spread of the disease while it is still relatively isolated. However, the National Academies of Sciences, Engineering and Medicine call for tightly controlled experiments before wide use of the gene drive. As MIT Media Lab professor Kevin Esvelt put it, “there is a nontrivial chance that [the genes] will spread from a single organism released into a wild population into most or all members of the local population — and very possibly into every population of the target species around the globe.” (Ike Swetlitz, STAT news)

Technology and Healthcare

Why lawmakers are trying to make ransomware a crime in California

Ransomware is a type of malware (a “virus”) that can make money for a hacker very quickly. The ransomware program encrypts files in the target computer, then demands a ransom, usually to be paid in cryptocurrency (the most popular is Bitcoin) which can be hard to track, to release the key that decrypts the files. Hospitals are perfect targets for ransomware attacks because they are often big institutions, are mostly unprepared to defend themselves against cybercrime, and hold precious data in its computers. Most often, ransomware makes the system of computers functionally “locked inside a black box” or completely unable to be used, creating mounting losses and outright risks that outweigh the price of the ransom.

This includes the medical data that is kept private inside those computers and becomes locked behind the ransomware’s military-grade encryption. Other times, the cyberattack consists of “kidnapping the privacy” of the patients. Here the hacker makes a copy of the data and requests a ransom not to release it to the public. In 2015 alone, 113 million patients had some or all of their health records stolen, and the hospital hacks showed increase of 600%. It has been called “The Year of the Hospital Hack.” Moreover, according to the FBI, ransomware as a broader industry is on the rise. In the first three months of 2016, victims of ransomware lost more than $209 million, compared to $25 million in the entire 2015. (Jazmine Ulloa, Los Angeles Times)

Affordable Care Act Effects

How I Was Wrong About ObamaCare

The strategy implemented by the Patient Protection and Affordable Care Act (PPACA, “ObamaCare”) for the purpose of controlling health care costs is one that strives for paying for healthcare by value provided instead of service provided. The promoted understanding, as summarized by former health policy advisor to the Obama administration Dr. Ezekiel Emanuel, 2011, is that such force will pressure the health care industry to undergo vertical consolidation into Integrated Delivery Systems. These systems, whose likes could be named as Kaiser Permanente, Geisinger Health Care System, and Intermountain Healthcare, are consolidations of all types of providers (physician, imaging, therapy, nursing, surgery, home care, specialty care etc.) and strives to be at least internally coordinated to provide the best value per cost, since its payment is not completely tied to the number of procedures or services performed.

Two PPACA-derived value-based reimbursed programs were launched in 2012 — the smaller and more cautious Pioneer Accountable Care Organizations, reserved for groups of providers with more experience in integrated health care delivery, and the larger and more ambitious Shared Savings Program Accountable Care Organizations. Their data has been released along the past year. The data shows that, along the first performance year of the Medicare Shared Savings Program, 58 ACOs generated $705 million in savings, feat which earned them $315 in bonuses as per the program’s workings, leaving net $260 million in savings to CMS. In April this year, the first study of the official CMS claims data indicated that the better savings were among the ACOs classified as small groups of providers. This is understood as evidence against the “Kaiserification” of healthcare as envisioned by Dr. Emmanuel, since the savings come not from having all providers as employees of a big conglomerate, but instead in giving more autonomy and power to the health care provider at the forefront of the contact with the patient. (Bob Kocher, Wall Street Journal)

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August 5, 2016 at 11:00 am

Science Policy Around the Web – July 26, 2016

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By: Ian McWilliams, Ph.D.

photo credit: Newport Geographic via photopin cc

Infectious Diseases

Research charities help marry two major South African HIV/TB institutes

Two institutes, the Wellcome Trust and the Howard Hughes Medical Institute (HHMI), have announced that they are joining efforts in to fund the fight against HIV and Tuberculosis (TB) in South Africa. South Africa has the largest population infected with HIV. Because TB thrives in HIV-infected individuals, South Africa is experiencing a co-epidemic that has been challenging to battle. This collaboration will mark the first time that HHMI and The Wellcome Trust have worked together on a global health institution.

The new Africa Health Research Institute combines the Africa Centre for Population Health’s detailed population data gathered from over 100,000 participants with basic laboratory science and medical research of the KwaZulu-Natal Research Institute TB-HIV (K-RITH). Together the organization will work towards eliminating HIV and TB by training African scientists and will “link clinical and laboratory-based studies with social science, health systems research and population studies to make fundamental discoveries about these killer diseases, as well as demonstrating how best to reduce morbidity and mortality.” Projects funded by the institute include maintaining the longest running population-based HIV treatment as prevention (TasP) trial in Africa and using genomics to study drug resistant TB.

The organization is funded by a $50 million grant from The Wellcome Trust that is renewable over the next five years. Additionally, HHMI has already spent $40 million for the construction of new facilities, including a new biosafety level 3 laboratory that is designed to handle dangerous pathogens. These new efforts aim to apply scientific breakthroughs to directly help the local community. Deenan Pillay, the director of the new institute, has expressed his support of the organization’s mission by stating “There’s been increasing pressure and need for the Africa Centre not just to observe the epidemic but to do something about it. How long can you be producing bloody maps?” (Jon Cohen, ScienceInsider)

Scientific Reproducibility

Dutch agency launches first grants programme dedicate to replication

While a reproducibility crisis is on the minds of many scientists, the Netherlands have launched a new fund to encourage Dutch scientists to test the reproducibility of ‘cornerstone’ scientific findings. The €3 million fund was announced on July 19th by the Netherlands Organisation for Scientific Research (NWO) and will focus on replicating work that “have a large impact on science, government policy or the public debate.”

The Replication Studies pilot program aims to increase transparency, quality, and completeness of reporting of results. Brian Nosek, who led studies to evaluate the reproducibility of over 100 reports from three different psychology journals, hailed the new program and stated “this is an increase of infinity percent of federal funding dedicated to replication studies.” This project is the first program in the world to focus on the replication of previous scientific findings. Dutch scientist Daniel Lakens further stated that “[t]his clearly signals that NWO feels there is imbalance in how much scientists perform replication research, and how much scientists perform novel research.” The NWO has stated that it intends to include replication in all of its research programs.

This pilot program will focus both on the reproduction of findings using datasets from the original study and replication of findings with new datasets gathered using the same research protocol in the original study. The program expects to fund 8-10 projects each year, and importantly, scientists will not be allowed to replicate their own work. The call for proposals will open in September with an expected deadline in mid-December. (Monya Baker, Nature News)

Health Care Insurance

US Sues to block Anthem-Cigna and Aetna-Human mergers

United States Attorney General Loretta Lynch has announced lawsuits to block two mergers that involve four of the largest health insurers. Co-plaintiffs in the suits include eight states, including Delaware, Florida, Georgia, Illinoi, Iowa, Ohio, Pennsylvania, Virginia, California, Colorado, Connecticut, Main, Maryland, and New Hampshire, as well as the District of Columbia. The lawsuits are an attempt by the Justice Department to block Humana’s $37 billion merger with Aetna and Anthem’s $54 billion acquisition of Cigna, the largest merger in the history of health insurers. The Justice Department says that the deals violate antitrust laws and could mean fewer choices and higher premiums for Americans. Antitrust officials also expressed concern that doctors and hospitals could lose bargaining power in these mergers.

Both proposed mergers were announced last year, and if these transactions close, the number of national providers would be reduced from five to three large companies. Furthermore, the government says that Anthem and Cigna control at least 50 percent of the national employer-based insurance market. Lynch further added that “competition would be substantially reduced for hundreds of thousands of families and individuals who buy insurance on the public exchanges established under the Affordable Care Act.” The Affordable Care Act (ACA) aimed to encourage more competition between insurers to improve health insurance options and keep plans affordable. The Obama administration has closely watched the health care industry since the passing of that legislation and has previously blocked the mergers of large hospital systems and stopped the merger of pharmaceutical giants, such as the proposed merger of Pfizer and Allergan.

Health insurers argue that these mergers are necessary to make the health care system more efficient, and would allow doctors and hospitals to better coordinate medical care. In reaction to the announcement by the Justice Department, Aetna and Humana stated that they intend to “vigorously defend” the merger and that this move “is in the best interest of consumers, particularly seniors seeking affordable, high-quality Medicare Advantage plans.” Cigna has said it is evaluating its options. (Leslie Picker and Reed Abelson, New York Times)

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July 26, 2016 at 11:00 am

Science Policy Around the Web – July 15, 2016

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By: Leopold Kong, Ph.D.

Healthcare Policy

United States Health Care Reform – Progress to Date and Next Steps

On Monday, President Obama published a special communication in The Journal of the American Medical Association summarizing the impact of the Affordable Care Act (ACA) during his tenure in office.  The report outlined the president’s initial motivations for health care reform, including his frustration over the relatively low insurance coverage across the US population when he first entered office, even though the U.S. was devoting over 16% of its economy to health care.  The report noted that since the implementation of Medicare and Medicaid in 1965, the uninsured population in the United States had stabilized to around 15% since the early 1990s.  With the creation of the ACA, the uninsured population has dropped 43% from 16% in 2010 to 9.1% in 2015.  Importantly, the health care reform has not decreased employment rates, while it has decreased insurance payment prices in the private sector by improving detection of health care fraud and by increasing insurance provider competition.  President Obama is optimistic that coverage will further expand, considering that many of the reforms that are part of the ACA have not yet reached their maximum effect. Policymakers must be on guard, however, against backtracking in the years ahead, considering there are continued attempts to repeal parts of the ACA. The report notes: “We need to continue to tackle special interest dollars in politics. But we also need to reinforce the sense of mission in health care that brought us an affordable polio vaccine and widely available penicillin.” (Barack Obama, JAMA)

HIV Health Policy

South Africa ushers in a new era for HIV

Next week, the International AIDS Conference returns to Durban, South Africa to discuss research and health care policy challenges in the country with the largest HIV epidemic in the world. Nearly 7 million people in South Africa have HIV, about 15% of the global HIV infected population. Remarkable progress has been made over the last two decades with the advent of more effective antiretroviral therapeutics and their wide dissemination.  South Africa’s average life expectancy has increased from 54.4 years in 2004 to 62.5 in 2015, and mother-to-child transmission has fallen from 30% to 1.5%.  Furthermore, AIDS-related deaths have been cut in half since 2006, from 400 to 200 thousands per year.  It is hopeful that continued gains in therapeutics accessibility would greatly improve the situation in South Africa, though substantial challenges remain. These include maintaining patient compliance in the face of a disease that no longer appears to be immediately life threatening, and dealing with the inevitable development of drug resistance that would require constant and costly patient monitoring.  Surprisingly, in South Africa, but not in Europe, people on therapy appeared to have better quality of life than their HIV-negative peers, highlighting the general benefit of increased interaction with health practitioners. Health policymakers in a country with over 3 million on antiretroviral therapy must also consider the side effects of the drugs, which include increased risk of hypertension, diabetes and obesity for older populations. With continued advances in small molecule and antibody therapeutics, as well as novel vaccine platforms, there is increased hope for millions of people living with HIV. (Linda Nordling, Nature)


First virus-hunter in space will test DNA-decoding device

Earlier this week, virus-hunter turned astronaut Kate Rubins arrived at the International Space Station with a pocket-sized DNA sequencer, the MinION (9.5 x 3.2 x 1.6 centimeters, ~ 120 grams) developed by Oxford Nanopore Technologies.  Unlike conventional sequencers, the MinION “reads” DNA strands by passing them through nanopores on the device that detect changes in electrostatic charge.  The small size of MinION is important to curb expenses, as it costs about $10,000 per pound of equipment flown to the space station. “Altogether, it’s an extremely exciting research package and a great capability on board station,” Rubins said. NASA hopes this project will improve scientific microbial research and disease diagnostics in space.  The MinION technology may also be used to detect extraterrestrial life, though further development may be needed, especially if non-DNA based life forms are expected.  Importantly, the experiments in space could encourage the expansion of genomics-based medicine utilizing MinION technology to more remote and poorer areas on Earth where the use of large, conventional DNA sequencers would not be practical. (Marcia Dunn, Associated Press)

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July 15, 2016 at 1:45 pm

The Debut of Health Care Data Science

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By: Fabrício Kury, M.D.

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It is easy for a millennial – a person born between mid-1980’s to late-90’s – to be unaware of just how young the current methods used in health care research really are. Controlled randomized clinical trials (RCT), dating only from the late 40’s, are probably younger than most millennial’s grandparents. Case-control methodology and Kaplan-Meier curves only originated in the 1950’s, while meta-analyses were only accepted by medical researchers in the late 70’s. Step into the 80’s and early millennials are as old, if not older, than propensity scores and the concept that is today called cost-effectiveness research. The term “Evidence-Based Medicine” is as young as a millennial born in the early 90’s, while the late 90’s and 2000’s saw the explosion of genomics, proteomics, metabolomics, and other -omics research. Finally, the 2010s so far might be credited for when the term Data Science (“the fourth paradigm of science“) gained widespread notoriety, and established its modern meaning as – long story made short – the practice of producing knowledge out of data that had been created for other purposes.

While the second half of the 20th century transformed health care research into an ever more rigorous and technology-driven science, it also saw the cost of the health care sector of the U.S. unrelentingly grow from a comfortable 5% of the Gross Domestic Product in 1960 to a crushing 18% in 2015. Medical bills have become the leading cause of personal bankruptcies in the nation, while life expectancy, as well as other basic health indicators, depicted a country nowhere close to getting a similar bang for each buck as other developed nations. In 2009, the Obama administration prescribed to the health care sector a remedy that had previously brought efficiency and cost savings to every industry it had previously touched: information technology. The Health Information Technology for Economic and Clinical Health (HITECH) Act (part of the American Recovery and Reinvestment Act of 2009) literally gave away as much as $36.5 billion of taxpayers’ money to hospitals and physician practices for them to buy and “meaningfully use” electronic health records (EHRs). This outpouring of money was overseen by the Office of the National Coordinator of Health Information Technology (ONC), which had existed since 2004 as a presidential Executive Order, but became solidified as a legislative mandate via HITECH. This act fiercely transitioned the country from mostly paper-based health care in 2008 to near-universal EHRs adoption by 2015, giving electronic life, and potential reuse for research, to streams of health data previously dormant in paper troves.

Moreover, in March, 2010, the Patient Protection and Affordable Care Act (PPACA, a.k.a. “Obamacare”) was signed into law and, among so many other interventions, secured a few hundred million dollars for the creation of the Patient-Centered Outcomes Research Institute (PCORI). The mission of the PCORI is to do research that responds directly to real-life concerns of patients. For that purpose, among the first initiatives by the PCORI was the creation of PCORnet, a network of institutions capable of providing electronic health data for research. Most recently, in January 2015, President Obama announced the Precision Medicine Initiative (PMI). The PMI seeks to craft a nationwide and representative cohort of 1 million individuals, from whom a wealth of health data will be collected with no definitive goal besides to serve as a multi-purpose prime-quality dataset for observational electronic research. Meanwhile, private sector-led initiatives such as Informatics for Integrating Biology and the Bedside (i2b2) and Observational Health Data Sciences and Informatics (OHDSI) were also launched with the mission to access and do research on health care’s big data, and their publications can be easily found in PubMed.

These initiatives depict a political and societal hope – or hype? – that information technology, among its other roles in health care as whole, can make health care research faster, broader, more transparent, more reproducible, and perhaps also closer to the everyday lives of people. One premise is that by using existing EHRs for research, instead of data collected on-demand for a particular study, the researcher gets closer to the “real world” individuals that ultimately receive the treatments and conclusions produced by the study. In traditional clinical trials and other studies, the patients who participate are highly selected and oftentimes remarkably unrepresentative of the general population. Moreover, in EHR-based research there is also the potential to investigate more individuals than any previous method could possibly attempt. This broader reach makes rare conditions (or combinations of conditions) not so rare that they cannot be readily studied, and allows subtler variations in diseases to become detectable. On top of that, these studies can be done at the speed of thought. De facto, electronic health records-based clinical research has been recently published in the Proceedings of the National Academy of Sciences (PNAS) and evinced to be feasible at international, multi-hundred million patients scale at a breathtakingly swift time span. Altogether, one can sense in this picture that the millions of dollars spent on HITECH, PCORnet, PMI, and the NIH’s Data Science research grants might not have been just unfounded hype.

The relationship of IT and health care must, however, recognize its rather long history of frustrated expectations. In 1968, for example, Dr. Laurence Weed – the father of today’s prevailing paradigm of patient notes – predicted that in the future all text narratives present in electronic health records would be entered in structured form that enables scientific analysis. Today, to say the minimum, we have become less confident about whether such change is feasible or even desirable to begin with. In 1987, Barnett and colleagues believed that “relatively simple computational models” could be used to construct “an effective [diagnostic] assistant to the physician in daily practice” and distributed nationwide, but such assistant is yet to arrive at your physician’s office downtown (although, truth be recognized, it might be around the corner). While presently teaming with excitement and blessed with incentives, the journey of IT into health care and health care research is invariably one of uncertainties and risks. Health information technology has been accused of provoking life-threatening medical errors, as well as – like previous technological breakthroughs along the history of Medicine, including the stethoscope – harming the patient-physician relationship and the quality of care. The editors of the New England Journal of Medicine early this year went as far as to state that data scientists are regarded by some clinical researchers as “research parasites.”

Moreover, the Federal Bureau of Intelligence has investigated that medical information can be sold on the black market for 10 times more than a credit card number, while at the same time cybersecurity experts are stunned by the extreme vulnerability of current U.S. health care facilities. This provides sensible ground for concern about patient privacy violation and identity theft once the health records have moved from papers into computers. Unlike a credit card, your medical and identity information cannot be cancelled over the phone and replaced by a new one. Patient matching, i.e. techniques for recognizing that data produced at separate sites refer to the same person, oftentimes confronts blunt opposition by civil opinion, while the ultimate ideal of a National Patient Identifier in the U.S. is explicitly prohibited by present legislation (HIPAA). Such seamless flow of interoperable health data between providers, however, is the very first recommendation expressed in 2012 by the Institute of Medicine for realizing the Learning Health Care System – one that revolves around the patient and where scientific discovery is a natural outgrowth of patient care.

With or without attaining the ideal of a Learning Health Care System, the U.S. health care system will undergo transformation sooner or later, by intervention or by itself, because the percentage of the GDP that is spent on health care can only continuously increase for so long. Information technology is at minimum a sensible “bet” for improving efficiency – however, the power of IT for improving efficiency lies not in greasing the wheels of existing paradigms, but in outclassing them with novel ones. This might be part of the explanation for the resistance against IT, although there does exist some evidence showing that IT can sometimes do more harm than good in health care, and here the word “harm” sometimes can mean patient harm. The cold truth is that, in spite of decades of scientific interest in using computers for health care, only very recently the health care industry became computerized, so we remain not far from the infancy of health care informatics. Nevertheless, Clinical Informatics has been unanimously approved in 2011 as a board-certified physician subspecialty by the American Board of Medical Specialties, signaling that the medical community sees in IT a permanent and complex duty for health care. Similarly, the NIH has in late 2013 appointed its first Associate Director for Data Science, also signaling that this novel field holds importance for health care research. Finally, there might be little that can be done with the entire -omics enterprise, with its thousands over thousands of measurements multiplied by millions of patients, that does not require data-scientific techniques.

The first cars were slower than horses, and today’s high-speed, road-only automobiles only became feasible after the country was dependably covered with a network of roads and freeways. Such a network was built not by the automobile producers, but by the government upon recognition that it would constitute a public good. The same principle could very well be the case of health care IT’s important issues with privacy, security and interoperability, with the added complication that it is easy for an EHR producer to design a solution but then block its users from having their system interact with software from competing companies. Now that health care records are electronic, we need the government to step in once again and build or coordinate the dependable freeways of health care data and IT standards, which will also constitute a public good and unlock fundamental potentials of the technology. Health care, on top of its humanitarian dimension, is fundamentally intensive in data and information, so it is reasonable to conjecture that information technology can be important, even revolutionizing, for health care. It took one hundred years for Einstein’s gravitational waves to evolve from a conjecture based on theoretical fundaments to a fact demonstrated by experiments. Perhaps in the future – let us hope not a century from today! – some of the data-scientific methods such as Artificial Neural Networks, Support Vector Machines, Naïve Bayes classifiers, Decision Trees, among others, in the hands of the millennials will withstand the trial of time and earn an entry at the standard jargon of medical research. Just like how, in their generations, meta-analyses, case-control studies, Kaplan-Meier curves, propensity scores, and the big grandpa of controlled randomized trial were similarly accepted.

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July 13, 2016 at 11:15 am

Challenges in the Translation of Science into Policy: The Case of Breast Cancer Screening Coverage

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By: Felisa Gonzales, Ph.D.

The appropriate role of science in policy making has been debated for centuries. Most theories of decision-making posit that decisions, including policy decisions, are based on beliefs and values. How best to incorporate scientific knowledge into policymakers’ beliefs and values is unclear, and doing so is particularly difficult when the science is not definitively conclusive. The challenges inherent to the use of science to inform policy were clearly demonstrated when the Patient Protection and Affordable Care Act (ACA) mandated free health insurance coverage for certain preventive services based on the science-based recommendations of the United States Preventive Services Task Force (USPSTF). The USPSTF is an independent, volunteer panel of experts and clinicians from the fields of preventive medicine and primary care charged with evaluating the scientific evidence regarding the benefits and harms of clinical preventive services. The target audience for the USPSTF recommendations is primary care clinicians, not policymakers. Because the use of their recommendations has been codified into law, the scientifically and clinically oriented USPSTF is now occupying a policy role for which it was neither designed nor intended. The scientific conclusions of the USPSTF may not match the beliefs and values of democratically elected policymakers, raising the question: Is USPSTF the appropriate body to be put in the position of determining coverage policy?

The direct linkage of the USPSTF’s science-based recommendations to health insurance coverage came to public attention in 2009 when the panel changed its breast cancer screening recommendation. Based on data from randomized trials of mammography screening, the USPSTF made age-specific recommendations that advised against routine breast cancer screening for women between the ages of 40-49 and called for women to weigh “the potential benefit against the potential harms” before deciding to initiate mammography before the age of 50. Although women older than 40 have long heard messages such as “screening saves lives” and “take the test, not the chance”, researchers had been expressing their uncertainty about the benefits of mammography for women in their 40s since at least 1993. Nevertheless, the 2009 recommendation was criticized as “gender genocide”, “incredibly flawed”, “disastrous for women’s health”, and “callous and poorly conceived”. Despite the backlash, the USPSTF reiterated the same recommendation in January of 2016.

A review of the available evidence in 2016 indicated that for every 10,000 women ages 40-49 screened for breast cancer, approximately 1,212 false-positives will result, 164 biopsies will be conducted, 10 cancers will be missed. With repeat screening over 10 years, only 4 breast cancer deaths among women ages 40-49 will be avoided. Based on this information, the USPSTF gave mammography for women ages 40-49 a grade of “C”, which indicates that “there is at least moderate certainty that the net benefit [i.e., the degree to which the benefits outweigh the harms] is small”. Only clinical preventive services with “A” or “B” grades, which indicate a moderate to high degree of certainty that the benefits outweigh the harms of a procedure by a moderate to substantial margin, are required to be completely covered by health insurers under ACA. The USPSTF grade definitions include assessments of certainty because science is not often absolutely conclusive. Commenting on the role and responsibility of expert bodies, the Organisation for Economic Co-Operation and Development Committee for Scientific and Technological Policy notes, “the policy and societal context for scientific advice is challenging, not only because the stakes are high, but also because the general expectation is that science can provide clear and unambiguous answers. The reality is that the results of scientific research are often provisional and sometimes heavily contested…” The fact that the USPSTF recommendations are based on the best available science and are of superior quality was not enough to convince policymakers that they were sufficient to be the sole determinant of coverage for mammography.

The “C” rating for mammography among women ages 40-49 was not a recommendation against screening or against coverage, but because the ACA linked the USPSTF recommendations to coverage decisions, some incorrectly interpreted it this way. As a “C” rating would result in mammography not being covered as a preventive service under ACA, Senators Barbara Mikulski (D-MD) and David Vitter (R-LA) drafted amendments requiring insurance plans to pay for annual mammograms for women ages 40 and older and not restrict mammography based on USPSTF recommendations. Mikulski’s amendment also included screenings for ovarian and lung cancer screening despite a lack of evidence of any benefit, and concerns about substantial harms, associated with these procedures. Members of the House and Senate have proposed additional actions including eliminating funding for future USPSTF recommendations and requiring people who are not experts in prevention or evidence-based medicine to serve on the panel (for example representatives from patient groups, specialty physicians, and relevant stakeholders from the medical products manufacturing community). Experts are wary of these efforts, noting that “political interference with science can discourage shared decision-making, increase harms from screening, and foster public doubt about the value and integrity of science.” These tensions highlight differences in scientists’ and policymakers’ beliefs and values despite a shared commitment to improved public health.

The USPSTF “is committed to using the best science to identify the most effective preventive services to improve the health of the public,” but carrying out this mission is much more complicated now that their recommendations are used to dictate health insurance coverage. One proposed solution, favored by the USPSTF and its critics, is the creation of a separate independent panel to be charged with reviewing the USPSTF screening recommendations as well as other considerations important for public policy, such as cost, context, and feasibility. As the current chair and members of the USPSTF have noted, “the science on effectiveness – although foundational – is only one factor that needs to be considered in developing policy coverage.” Others closely associated with the USPSTF have warned that “limiting first-dollar coverage to services supported by strong evidence of effectiveness, as determined by one panel, is potentially harmful for public policy and threatens the USPSTF and other independent panels like it.” The linkage of the USPSTF recommendations to health insurance coverage policy reminds us that scientists are not policymakers, and policymakers are not scientists. The development of evidence-based policy requires scientific advice that is “scientifically sound and politically suitable and legitimate at the same time.” In the absence of an independent, intermediate body that can consider both scientific beliefs and prevailing societal values in health insurance coverage decisions, we risk building walls rather than bridges between science and policy.

Written by sciencepolicyforall

May 12, 2016 at 11:00 am

Science Policy Around the Web – February 19, 2016

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By: Fabrício Kury, MD

Affordable Care Act

Obamacare supporters don’t like talking about it — but the individual mandate is working

Among the many goals of the enormous piece of legislation that is the Patient Protection and Affordable Care Act (PPACA), one is to deliver universal health care access in a nation that often ranks no. 1 in the ranking of cost of health care per capita, and without flirting with socialist-minded models such as single-payer health care that would have failed to pass in Congress. Because it is so expensive, health care in the U.S. is largely paid for via health insurances, which act as pools of the risk of needing healthcare and dilute the cost among all insured individuals. However, in a free capitalist market, the health insurances suffer from the fundamental problem of adverse selection, in which only the people who need health care purchase insurance, while those who are mostly healthy opt not to. This becomes a “death spiral” that leads to financial insolvency of insurance companies even despite them going to extreme lengths in denying insurance coverage to individuals expected to be costly. To address this, the PPACA prohibits insurance companies from denying coverage on the basis of pre-existing conditions and at the same time addresses the problem of adverse selection by making it mandatory that everyone (with few exceptions) must have health insurance or otherwise face a financial penalty – the so-called “individual mandate”. Recent statics on enrollment in the ACA show that the financial penalty aspect is working to encourage young, otherwise-healthy people to sign up, exactly as it was intended. (Sarah Kliff, Vox)

Technology and Health Care Policy

When Software Tries to Eat Regulation

In the era of disruptive innovation, billion-dollar unicorns, there-is-an-app-for-that mindset, it is no surprise to hear that ”every smart tech person I know is working in healthcare,” the $3 trillion industry that occupies more than $1 out of every $6 spent in the entire U.S. economy. Underpinning digital revolutions such as Uber, Airbnb, Spotify, even Wikipedia, lies the concept of delivering value in a dramatically rethought manner that longstanding behemoth corporations fail to compete with. Health care, however, cannot be provided by a team of youngsters in a garage because what is at stake is more serious than whether or not you get to find a cab when you need one. Health care is delivered amid walls of regulations that protect patients and assign liability, and health care consumers are not necessarily looking forward to risking security in favor of imaginative, cheaper alternatives. Since 2013, the Food and Drug Administration (FDA) has laid out regulation for responsible innovation in mobile health and followed up final guidance this year, while the HHS Office for Civil Rights offers guidance on adhering to HIPAA for health app developers. In this article, the examples of Zenefits, Theranos and 23andMe demonstrate that the FDA has consistently made clear that the “Ubers” of health care must exist within the same legal framework that safeguard the existing U.S. health care delivery models. (Erin Griffith, Fortune)

Fee-for-Service Heathcare

The Hidden Financial Incentives Behind Your Shorter Hospital Stay

In basically any U.S. market, if you purchase a product and it breaks too soon, you either get a new one or you receive your money back. In U.S. health care, though, up until 2012 if a patient was discharged from a hospital, but soon had to be re-admitted due to a preventable problem such as a poorly disinfected surgical wound, the hospital profited again from the new patient admission. The 2012 Medicare’s Hospital Readmission and Reduction Program, part of the Patient Protection and Affordable Care Act (PPACA), financially penalizes facilities that fail to meet historical measures of what is considered an acceptable rate of re-admissions, but this has been bringing the adverse effect of “workflow gymnastics” to make patients not be re-admitted or at least, not get counted as so. Another approach, the Bundled Payments for Care Improvement initiated in 2013, extends the concept of a single payment per diagnosis to include all care needed by the patient including out-of-hospital care. While these approaches seem to have been successful, they are still built on top of the fee-for-service rationale, where health care is paid for by the number (volume) of treatments provided. The American Hospital Association (AHA) affirms there exists considerable agreement that fee-for-service is one of the major culprits in the decades-old unrelenting upward trend in the percentage of the U.S. gross domestic product that is spent on health care. The opposite model of fee-for-service is capitation, where providers are paid a fixed price to provide all care to a group of individuals regardless of the volume of the care provided. The ACA has made capitation a possible alternative for some types of Accountable Care Organizations, however it is not mandatory, the programs are still temporary, and their details must evolve from the failed capitation models of the 1990s. (Austin Frakt, The New York Times)

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Written by sciencepolicyforall

February 19, 2016 at 9:00 am

Science Policy Around the Web – December 7, 2015

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By: Fabrício Kury, MD

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Patient Privacy

Would You Trust a Hospital to Scan Your Fingerprint?

Biometrics, such as fingerprints and iris scans, that are unique to each person might not be ready or even a good idea for use as personal identifiers in health care. The concept of a Universal Patient Identifier (UPI) is an idea that has gained new momentum since 2009 when billions of dollars were spent by the federal government to digitize the nation’s health records via the HITECH Act. However, being able to identify that two pieces of data from two different sources (for example, from an imaging center and an outpatient clinic) belong to the same patient can enable have serious consequences in terms of keeping patient data private and unidentifiable. In addition, health care settings are extremely vulnerable to hacking, making it more likely that patient data could be released. The Patient Privacy Rights group has detailed their case arguing that due to such vulnerabilities, fingerprints ought not to be the way forward. The FDA has started to take action to secure hospital systems and equipment from intrusion, however, once a cyberattack has happened (such as the recent one at the federal Office of Personnel Management) you cannot request to change your fingerprints because the ones you had got stolen. (Christina Farr, KQED Science)

Healthcare Industry

Cerner, Leidos and Accenture win massive Defense contract for EHR system

This year saw the one of the biggest, if not the biggest, deal in the history of all Health Information Technology. The U.S. Department of Defense (DOD) signed an $11-billion contract spanning 18 years with Cerner-Leidos-Accenture to deliver health information systems to the DOD’s 55 hospitals, 600 clinics, and 9.5 million covered personnel and their families. The contract had centered around developing a replacement electronic health record (EHR) system for the very large Military Health System. The Defense Department had issued draft requests for proposals back in January 2014, with the final successful bid determined in July 2015. This decision was a large blow for two other teams that were bidding on the same contract: Cerner’s principal market share rivals Epic (which had partnered with IBM) and Allscripts (which had partnered with Hewlett-Packard).  (Joseph Conn,


Health Information Technology in the United States, 2015: Transition to a Post-HITECH World

In 2009, as part of the American Recovery and Reinvestment (ARRA) Act, President Obama signed into law the HITECH Act — Health Information Technology For Economic and Clinical Health Act — which sent $25.9 billion dollars from federal coffers into paying hospitals and physicians to implement and successfully report Meaningful Use of Electronic Health Records (EHR). This report, published by the Robert Wood Johnson Foundation, is the latest one in the series since 2009, and reviews the impact of the still ongoing Meaningful Use program. Highlights from this report include the vertiginous increase, starting in 2009, in the percentage of both hospitals and physicians that use EHRs: currently 75% of hospitals and 82% of physicians, and the overall failure of the program in promoting health data exchange, which remains as a major challenge to the envisioned Learning Health Care System. (Mathematica Policy Research, and Harvard School of Public Health)

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Written by sciencepolicyforall

December 7, 2015 at 9:00 am