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Health Care Policy
Emergency room patients treated by physicians who prescribe opioids more often are at greater risk for long-term opioid use even after a single prescription than those who see less-frequent prescribers, according to the findings of a study from Harvard Medical School and Harvard T.H. Chan School of Public Health.
The research, believed to be the first to measure variation in provider prescribing practices and their impact on long-term opioid use, will be published Feb. 16 in the New England Journal of Medicine.
Long-term opioid use increases the danger of misuse, addiction and even overdose, fueling what public health experts have called a national epidemic of opioid overuse. In 2015, more than 15,000 people in the United States died from an overdose involving prescription opioids, according to the Centers for Disease Control and Prevention.
The findings, the researchers add, underscore an acute need to educate clinicians on judicious prescribing practices and reduce wide variation in prescribing patterns for similar patients.
“These are sobering results,” said lead study author Michael Barnett, assistant professor of health policy and management at the Harvard Chan School and an HMS instructor of medicine at Brigham and Women’s Hospital. “Our analysis suggests that one out of every 48 people newly prescribed an opioid will become a long-term user. That’s a big risk for such a common therapy.”
Specifically, the study found that patients who saw frequent, or so-called high-intensity, opioid prescribers were three times as likely to receive a prescription for opioids as patients seen by infrequent, or low-intensity, prescribers in the same hospital.
Individuals treated by the most frequent prescribers were 30 percent more likely to become long-term opioid users—defined as receiving six months worth of pills in the 12 months following the initial encounter—and were also more likely to have an adverse outcome related to the drugs, such as a fall, a fracture, respiratory failure or constipation.
The study also showed that patients treated by low-frequency prescribers were no more likely to return to the hospital overall or with the same complaints—findings that suggest these people were not under-treated for their symptoms.
“Who treats you matters. Our findings lend support to the narrative that we often hear—a patient happened to be prescribed an opioid by a dentist or in the emergency room and unwittingly became a long-term user,” said study author Anupam Jena, the Ruth L. Newhouse Associate Professor of Health Care Policy at HMS and an HMS associate professor of medicine and physician at Massachusetts General Hospital. “A physician who prescribes an opioid needs to be conscious that there is a significant risk that the patient could continue to be on an opioid for the long term, even from a single, short, initial prescription.”
In their analysis, the researchers compared opioid use during 12 months following an initial emergency department encounter among more than 375,000 Medicare beneficiaries treated by more than 14,000 physicians between 2008 and 2011.
Although the physicians saw patients with similar complaints, they treated them differently. On the low end of the spectrum, one quarter of providers gave opioid prescriptions to just 7 percent of the patients they saw. At the other extreme, the top quarter of prescribers gave opioids to 24 percent of their patients.
"That’s an enormous amount of variation just from walking through a door and getting assigned to one doctor instead of another," said Barnett.
This research was funded by National Institutes of Health Director’s Early Independence Award number 1DP5OD017897-01.
The Affordable Care Act instituted financial penalties against hospitals with high rates of readmissions for Medicare patients with certain health conditions. A new analysis led by researchers at Harvard Medical School, Beth Israel Deaconess Medical Center, Harvard T.H. Chan School of Public Health and Massachusetts General Hospital has found that the penalties levied under the law’s Hospital Readmissions Reduction Program were associated with reduced readmissions rates, and that the poorest performing hospitals achieved the greatest reductions.
The research appears online in Annals of Internal Medicine on Dec. 27.
The Hospital Readmissions Reduction Program was enacted into law in 2010 and implemented in 2012 in response to the high numbers of patients who were readmitted within 30 days of their initial discharge from the hospital after treatment for several common conditions—including heart failure, pneumonia and acute myocardial infarction (heart attack).
While some readmissions may be unavoidable, there was evidence of wide variation in hospitals’ readmission rates before the ACA, suggesting that patients admitted to certain hospitals were more likely to experience readmissions compared to other hospitals.
“Paying hospitals not just for what they do, but for how well they do—that’s still a relatively new way of reimbursing hospitals, and it looks to be effective,” — Robert Yeh
“Hospital readmissions represent a significant portion of potentially preventable medical expenditures, and they can take a physical and emotional toll on patients and their families,” said co-senior author , associate professor of medicine and director of the Richard A. and Susan F. Smith Center for Outcomes Research in Cardiology at Beth Israel Deaconess.
“The Affordable Care Act sought to introduce financial incentives to motivate hospitals, especially the poorest performing ones, to reduce their readmission rates, and only the data could tell us if and how well it worked,” Yeh said.
“We know that the national hospital readmissions rate has been declining since passage of the Affordable Care Act, and our team wanted to assess whether this improvement was driven by the best-performing hospitals alone or if all groups improved,” said first author , instructor in medicine at HMS and director of quality and analytics at the Mass General Corrigan Minehan Heart Center.
The researchers examined Medicare fee-for-service hospitalization data from more than 2,800 hospitals across the country between 2000 and 2013. Based on 30-day readmission rates after initial hospitalization for acute myocardial infarction, congestive heart failure or pneumonia, the researchers categorized hospitals into one of four groups based on the penalties they had incurred under the Hospital Readmission Reduction Program: highest performance (0% penalty), average performance (greater than 0% but less than 0.5% penalty), low performance (equal to or greater than 0.5% but less than 0.99% penalty), and lowest performance (equal to or greater than 0.99% penalty).
"We analyzed data from more than 15 million Medicare discharges,” said co-senior author Francesca Dominici, professor of biostatistics and senior associate dean for research at the Harvard Chan School.
“We implemented Bayesian hierarchical models to estimate readmission rates for each hospital, accounting for differences in each hospital’s patient population. We then used pre-post analysis methods to assess whether there were accelerated reductions in readmission rates within each group after the passage of the reform. It turned out that all groups of hospitals improved to some degree. Notably, we found that it was the hospitals that were the lowest performers before passage of the Affordable Care Act that went on to improve the most after being penalized financially,” Dominici said.
“For every 10,000 patients discharged per year, the worst performing hospitals—which were penalized the most—avoided 95 readmissions they would have had if they’d continued along their current trajectory before the implementation of the law,” added Dominici.
“It’s a testament to the fact that hospitals do respond to financial penalties, in particular when these penalties are also tied to publicly reported performance goals,” she said.
“Paying hospitals not just for what they do, but for how well they do—that’s still a relatively new way of reimbursing hospitals, and it looks to be effective,” Yeh added.
This work was funded, in part, by grants from the National Institutes of Health (P01 CA 134294, R01 GM111339, R01 ES024332 and K23 HL 118138-01) as well as support from the Mass General Cardiology Division’s Hassenfeld Scholars Program.
Adapted from a Beth Israel Deaconess news release.
Patients who choose primary care doctors with low office visit prices can rack up considerable savings on overall health care costs according to new research from Harvard Medical School.
The report, published Dec. 5 in the December issue of the journal Health Affairs, suggests that office visit costs may be a reliable indicator of what a patient will pay for a wide range of services and procedures.
The analysis shows that a relatively small difference in office visit price—$26—translated into hundreds of dollars in savings over the course of a year. The study found that when patients received care from primary care doctors with lower-than-average office visit prices, they spent, on average, $690 less per year, compared with patients who saw higher-priced physicians.
The savings, the researchers note, were not driven by fewer services or less care. Indeed, there was no significant difference in the kind and amount of services received by the two groups of patients. Rather, patients whose physicians charged lower prices for office visits also paid less for almost every other outpatient service they received.
In the past decade, patients have had to pay more for health care, due to higher deductibles. Many states and private insurers now offer price transparency tools in the hope that access to such information could help people make better-informed decisions on how much they will pay per visit or for a given procedure.
Would picking a provider based on low-priced office visits translate into overall savings including procedures and other follow-up care? The study suggests so.
“Because of the tremendous growth in high-deductible health plans, Americans are being forced to think about prices when they choose where to get care,” said study lead author Ateev Mehrotra, associate professor of health care policy at Harvard Medical School and a hospitalist at Beth Israel Deaconess Medical Center. “Our data suggest that looking at the price of your doctor’s office visit is a good place to start. Choosing a lower-priced primary care doctor could save someone a lot of money.”
Using the 2010 Ingenix insurance database, which contains data from 27 national employers, the researchers grouped primary care doctors into high, average and low price tiers based on the cost of an office visit. From there, they examined the spending of those doctors’ patients, looking at how many services such as drugs and emergency care visits patients used and how much the services cost.
Other investigators on the research included Peter Huckfeldt, assistant professor in the Division of Health Policy and Management at the University of Minnesota School of Public Health; Amelia Haviland, Anna Loomis McCandless Professor of Statistics and Public Policy at the H. John Heinz III College of Public Policy and Management at Carnegie Mellon University; Laura Gascue, programmer and quantitative analyst at the Leonard D. Schaeffer Center for Health Policy and Economics at the University of Southern California, Los Angeles; and Neeraj Sood, professor of public policy at the Leonard D. Schaeffer Center for Health Policy and Economics at the University of Southern California.
The work was funded by the Common Fund of the National Institutes of Health (Grant No. R01 AG043850-01).
Premiums for marketplace plans in the Affordable Care Act will increase by an average of 25 percent nationwide from 2016 to 2017, new reports from the federal government say.
Opponents of the politically contested health care reform law, sometimes referred to as Obamacare, have reacted by saying that the latest increases are proof that the ACA is a failure.
But some states are saying that the law has proven successful.
Peter Lee, executive director of Covered California, the California ACA insurance marketplace, said that states that have taken advantage of all of the tools provided by the ACA, such as California, have been able to make great progress in providing affordable care for consumers.
Lee was the featured speaker at this year’s 16th Annual Marshall J. Seidman Lecture on Oct. 25.
“We keep hearing a lot about the exchanges failing,” Joseph Newhouse, HMS professor of health care policy, said. “But our speaker may be able to tell you, ‘It ain’t necessarily so.’”
California has had the best performance in the health exchanges of any state on many measures.
“We're at a pretty good time to pause and look at how the ACA and the exchanges are doing,” Lee said. “With any large-scale policy, at five or six years in you need to pause and do a tune-up.”
From 2013 to 2015 the share of California residents without health insurance fell from 17 percent to 8.1 percent, according to federal calculations.
Covered California’s data show that most people who have left their plans either entered an employer-provided plan or became eligible for Medicaid, with very few leaving to become uninsured.
One reason that California has had such success is that the state started with the healthiest mix of residents of any state. The state government also wholeheartedly embraced the provisions of the ACA, Lee said.
Step one was to increase participation in Medicare, Lee said. This move served both to increase the portion of the population with health care coverage and to decrease the number of unhealthy people in the population who would be eligible for exchange-based individual insurance.
Covered California also actively sought to market and sell its insurance plans, which allowed the program to reach healthier consumers who might not have sought out insurance on their own, Lee said.
“Many of the exchanges that are struggling are in states that have been politically hostile to the ACA," Lee said.
In states that did not increase Medicare participation or invest in marketing the exchange plans, Lee said, many of the consumers who sought to purchase plans were already in poor health and therefore expensive to cover.
On average, exchange plan premiums in California will rise 13 percent in the new year, compared to states like Arizona, where rates will more than double, Lee said.
In contrast to some states, where insurers have lost money and struggled to set sustainable prices, leaving both consumers and health plans unhappy, Lee noted that insurers are eager to participate in the California exchange because they can sell products that make a profit.
Covered California is using that as leverage to require improved benefits for consumers and to prune low-quality and high-cost hospitals and provider groups from insurers’ networks, Lee said.
“We can push changes in the delivery system to improve the quality of care," he added.
Noting that much of the research that guided the design and implementation of the ACA came from HMS and colleagues throughout Harvard University, Lee said that researchers have an important role to play in evaluating the reform effort and guiding improvements in the future.
“Credit and blame lies on your doorstep,” Lee said, challenging researchers in the audience to “help the new Congress and the new president build on what we've got, which is actually working pretty well."
In 2000, on the occasion of the 50th reunion of his Harvard Law School class, Marshall J. Seidman provided endowment support to the Harvard Medical School Department of Health Care Policy to support research related to health care costs and quality and to host an annual meeting by a leading policymaker on issues related to costs and quality of health care with a particular emphasis on activities that are most likely to impact federal and state approaches to these problems. The department has sponsored the lectures yearly since 2001.
More than 2.6 million servicemen and women have deployed to Iraq or Afghanistan since September 11, 2001. Many veterans return home from their service with symptoms of posttraumatic stress, depression, chronic pain and traumatic brain injury. These symptoms are also common among civilian trauma survivors.
The National Institutes of Health, in response to an executive order from President Obama to initiate major research efforts to better understand and treat these disorders, has just provided $21 million for the most comprehensive longitudinal study of trauma survivors ever performed. The five-year-long project, which will be known as the Aurora study, is funded by the National Institute of Mental Health.
The research will utilize the efforts of 19 institutions and more than 40 scientists. Three of the four Aurora principal investigators are Harvard faculty: Ronald Kessler, the McNeil Family Professor of Health Care Policy at Harvard Medical School, who will be responsible for the social epidemiological aspects of the study; Karestan Koenan, professor of psychiatric epidemiology at the Harvard T.H. Chan School of Public Health, who will be responsible for the genetic epidemiological aspects of the study; and Kerry Ressler, professor of psychiatry at HMS and the James and Patricia Poitras Chair in Psychiatry and chief scientific officer at McLean Hospital, who will be responsible for the neurophysiology and neuroimaging aspects of the study.
Trauma survivors will be enrolled in the study in the immediate aftermath of trauma and followed longitudinally for one year using sophisticated adaptive sampling methods to perform a comprehensive, state-of-the-art assessment of genomic, neuroimaging, physiologic, neurocognitive, psychophysical, behavioral and self-report markers.
In addition to its unparalleled scope, the study differs from previous studies in that it will assess neuropsychiatric effects of trauma broadly rather than focus on only one or a few diseases.
“We want to be patient-centered and not diagnosis-centered,” said Samuel McLean, lead principal investigator of the study and an emergency medical physician at the University of North Carolina at Chapel Hill.
“We also recognize that a trauma survivor with depression, who also has a lot of posttraumatic stress symptoms and traumatic brain injury symptoms, is likely to be a lot different in terms of underlying biology than a trauma survivor with depression alone. We believe that only by looking at an individual globally can we achieve great advances in treatment,” McLean said.
The study will use a wealth of biologic data collected during the critical time after trauma exposure to chart onset and progress of disorders and to search for treatment intervention targets. Psychosocial specifiers will also be examined in an effort to determine ways in which behavioral or environmental interventions might be useful in prevention and treatment.
Another major goal of the study is to develop predictive analytic tools that clinicians in emergency departments, military hospitals and military aid stations can use at the bedside to identify trauma survivors at high risk of persistent sufferings.
“We need these tools urgently so that trauma survivors at high risk can be identified for early preventive treatments,” Kessler said.
Study investigators are currently pursuing additional foundation and philanthropic support to expand the study in ways that would allow targeted models to be developed for important trauma subtypes, including sexual assault, physical assault and motor vehicle collisions involving the death of a loved one.
This story is adapted from a news release from the University of North Carolina.
Increasingly powerful computers using ever-more sophisticated programs are challenging human supremacy in areas as diverse as playing chess and making emotionally compelling music. But can digital diagnosticians match, or even outperform, human physicians?
The answer, according to a new study led by researchers at Harvard Medical School, is “not quite.”
The findings, published Oct. 10 in JAMA Internal Medicine, show that physicians’ performance is vastly superior and that doctors make a correct diagnosis more than twice as often as 23 commonly used symptom-checker apps. The analysis is believed to provide the first direct comparison between human-made and computer-based diagnoses.
Diagnostic errors stem from failure to recognize a disease or to do so in a timely manner. Physicians make such errors roughly 10 to 15 percent of the time, researchers say.
Over the last two decades, computer-based checklists and other fail-safe digital apps have been increasingly used to reduce medication errors or streamline infection-prevention protocols. Lately, experts have wondered whether computers might also help improve clinical diagnoses and reduce diagnostic errors. Each year, hundreds of millions of people use Internet programs or apps to check their symptoms or to self-diagnose. Yet how these computerized symptom-checkers fare against physicians has not been well studied.
In the study, 234 internal medicine physicians were asked to evaluate 45 clinical cases, involving both common and uncommon conditions with varying degrees of severity. For each scenario, physicians had to identify the most likely diagnosis along with two additional possible diagnoses. Each clinical vignette was solved by at least 20 physicians.
The physicians outperformed the symptom-checker apps, listing the correct diagnosis first 72 percent of the time, compared with 34 percent of the time for the digital platforms. Eighty-four percent of clinicians listed the correct diagnosis in the top three possibilities, compared with 51 percent for the digital symptom-checkers.
The difference between physician and computer performance was most dramatic in more severe and less common conditions. It was smaller for less acute and more common illnesses.
“While the computer programs were clearly inferior to physicians in terms of diagnostic accuracy, it will be critical to study future generations of computer programs that may be more accurate,” said senior investigator Ateev Mehrotra, an associate professor of health care policy at HMS.
Despite outperforming the machines, physicians still made errors in about 15 percent of cases. Researchers say developing computer-based algorithms to be used in conjunction with human decision-making may help further reduce diagnostic errors.
“Clinical diagnosis is currently as much art as it is science, but there is great promise for technology to help augment clinical diagnoses,” Mehrotra said. “That is the true value proposition of these tools.”
As waves of hospitals move from older methods of record keeping to new digital electronic health record (EHR) systems, many medical professionals express fears that implementing an EHR system in their hospital will have dire results, including more errors and higher patient mortality.
But these fears are largely unfounded, researchers from Harvard Medical School and the Harvard T.H. Chan School of Public Health have found after studying a diverse group of U.S. hospitals that implemented new EHR systems during 2011 and 2012.
Better technology and monetary incentives from the federal government promoting more advanced record keeping have meant that EHR adoption has accelerated, both in the U.S. and abroad.
However, implementing a new EHR system can be one of the most disruptive events a hospital can experience. Workflow disruptions can create numerous frustrations and distractions as providers learn new systems, potentially leading to errors. Many providers fear that patient care could suffer as a result.
One prior study on a hospital’s EHR implementation even reported increases in mortality in the months following activation of the new system.
In the current study, led by Michael Barnett, assistant professor at the Harvard Chan School, researchers sought to address this concern by studying the short-term impact of implementing EHR systems nationally. They identified 17 hospitals that implemented a new EHR system in a single day, known as “going live.” Then, using Medicare data from 2010 to 2012, they compared patient outcomes before and after EHR implementation to the same trends in other nearby hospitals.
Because these hospitals implemented their systems in a single day, this created a “natural experiment” to study the effect of EHR implementation in similar groups of patients admitted before and after activation of a new system.
The researchers found that there was no difference in the rates of inpatient mortality, adverse safety events and readmissions in hospitals implementing EHR systems before and after going live, compared to the control group.
There was also no change when examining groups of patients and hospitals that might have been at higher risk for problems, such as sicker patients or hospitals who transitioned from paper to electronic charts, versus those just switching from one electronic system to another.
“Physicians’ tremendous frustration in switching to new electronic health records can spill over into concerns that patient care is actually worse because of these systems,” said Barnett, who is also a primary care physician at Brigham and Women’s hospital. “Happily, our results suggest that switching to a new system is a challenge that hospitals are prepared to handle safely.”
This should be encouraging to doctors, practices and hospitals planning their own implementations, the researchers said.
“Having recently witnessed firsthand how disruptive an EHR implementation can be, it is reassuring to know that hospital safeguards prevent patients from being harmed,” said Anupam Jena, senior author of the study and the Ruth L. Newhouse Associate Professor of Health Care Policy at HMS.
This research was supported by grants from the Office of the Director at the National Institutes of Health (NIH early independence award 1DP5OD017897-01 and Health Resources and Services Administration T32-HP10251).
Women physicians earn an average of $20,000 per year less than men even after adjusting for factors likely to influence income, according to what is probably the largest study of salary differences between male and female medical school faculty members.
The study, which analyzed data for physicians employed at 24 public medical schools, appears online in JAMA Internal Medicine.
“More than raising attention to salary sex differences in medicine, our findings highlight the fact that these differences persist even when we account for detailed factors that influence income and reflect academic productivity,” said Anupam Jena, the HMS Ruth L. Newhouse Associate Professor of Health Care Policy, and an internist at Massachusetts General Hospital.
“The fact that we observed these income differences among physicians who are public employees raises issues that may have state regulatory implications,” he said.
While several previous studies have documented salary differences between male and female physicians working in academic medicine, those investigations have been relatively small, restricted to specific specialties or depended on participants’ responses to survey questions.
The current study started with employee information—including names, titles and salaries—from public medical schools in 12 states that make such information available online. The researchers merged that data on physician faculty salaries with information from the Doximity database of more than 700,000 U.S. physicians.
That database includes demographic and professional factors including age, gender, faculty rank, university affiliation, specialty, year of residency completion, type of clinical practice (based on receiving Medicare payments) and several indicators of research activity.
Among their final sample of almost 10,250 physician faculty members—35 percent of whom were women—the unadjusted average annual salaries of women were almost 20 percent lower ($206,641 versus $257,947) than those of male physicians.
After adjusting for the factors mentioned above, female physician faculty members still received salaries 8 percent lower than those of comparable male physicians ($227,783 versus $247,661).
Adjusted salary disparities were greatest for orthopedic surgery, obstetrics/gynecology (one of the specialties female physicians were most likely to enter), other surgical subspecialties and cardiology, and lowest for family medicine and emergency medicine.
Adjusted average salaries for women in radiology were slightly higher than for men.
Disparities also varied among medical schools, with adjusted average salaries for male physicians being significantly higher at nine schools—the greatest disparities occurring at schools in the western U.S.
“Our findings also highlight how non-traditional data sets like Doximity and public employee salary information can be used to investigate questions that historically have been difficult to evaluate due to lack of access to large-scale data,” said co-author Daniel Blumenthal, HMS research fellow in medicine and clinical fellow in the Mass General Division of Cardiology.
The study was supported by National Institutes of Health Early Independence Award 1DP P50D017897-01.
Adapted from a Mass General news release.
Early studies have suggested that paying doctors bonuses for meeting targets for certain health care measures would lead to improved health outcomes for patients, but the findings were not repeated in later, more rigorous studies, according to new research.
In a paper published June 23 in Preventing Chronic Disease, Stephen Soumerai, Harvard Medical School professor of population medicine at Harvard Pilgrim Health Care Institute, and Huseyin Naci at the London School of Economics analyzed the latest results.
This study is the latest in a series of papers from Soumerai and colleagues exploring how uncorrected bias and unreliable study design may contribute to flip-flops in health care recommendations and policies, and offering recommendations on what researchers, educators and journalists might do to address these issues.
Soumerai discussed the paper and the challenges of research design with Harvard Medicine News.
HMN: Why are the promising conclusions from early studies of pay-for-performance so different from the findings of later studies?
When the initial national programs in pay-for-performance were rolled out, many early studies suggested that the policies were contributing to improved health outcomes, including findings which suggested that giving physicians cash incentives to take patient blood pressure contributed to improved patient mortality rates.
The problem was that these studies didn’t correct for other changes that were taking place in medicine at the same time. Failing to account for these ongoing baseline changes is called history bias. Uncorrected, these biases led to false, optimistic conclusions because the policies were taking credit for improvements in medical care that were already occurring.
Subsequent, stronger research—including quasi-experimental studies, randomized control trials and systematic reviews that can control for these biases—consistently overturned the early, optimistic findings.
One international systematic review found that not only was there little evidence to support pay-for-performance’s effects on quality of medical care but some studies found that it sometimes had the unintended consequence of discouraging doctors from treating the sickest patients.
HMN: What happened next?
Unfortunately, that initial, weak research on the supposed success of pay-for-performance in health care was published in top medical journals and hastened the adoption of these policies around the world.
Despite its unfulfilled promise and discouraging evidence, this costly and ineffective approach to improving health care is a widespread component of current national and international health care policies. It is entrenched in many policies created by the Affordable Care Act. This has led to billions of dollars in wasted resources around the world.
Remarkably, most of these initiatives were started after the evidence of failure or very weak effects were published.
HMN: How common is this?
This isn’t an isolated incident; it’s a pattern that repeats itself throughout health care effectiveness research. Weak research designs are the most common reason for biased health care effectiveness research.
This paper continues a line of research we’ve been pursuing that shows how stronger research designs can avoid these costly mistakes.
HMN: What’s the solution?
Science can be a useful tool for designing and implementing effective, efficient health care, but only if we use reliable research methods such as randomized, controlled trials; interrupted time-series designs; and systematic reviews—and if we conduct rigorous pilot tests of expensive policies.
Investments of private and taxpayer funds should be based on solid evidence of safety and efficacy. The alternative—the present system—relies on weak and uncontrolled research designs, misleads policy makers and the public, and will ultimately lead to unsustainable costs, unhappy clinicians and policies that may damage—rather than improve—the quality of medical care.
Everyone involved in the process that brings this information to light—the researchers who design the studies, the journal editors who accept and reject papers and the mainstream journalists who cover health care and policy—all have a responsibility to get this work right.
Nearly 15 percent of opioid-naïve patients hospitalized under Medicare are discharged with a new prescription for opioids, according to a study published today in JAMA Internal Medicine.
Among those patients who received a prescription, 40 percent were still taking opioids 90 days after discharge. The rate of prescription varied almost twofold between hospitals, with some hospitals discharging as many as 20 percent of patients with a prescription for opioids.
Despite growing concern about the public health costs of long-term opioid use, little has been known about how often the painkillers are prescribed. Even appropriate short-term prescriptions can lead to long-term use and, potentially, abuse.
“Every day, 44 people in the United States die from prescription drug overdoses, especially opioid overdose,” said Anupam Jena, lead author of the study, the Ruth L. Newhouse Associate Professor of Health Care Policy at Harvard Medical School, and a physician at Massachusetts General Hospital. “It’s critical that we understand hospital prescribing patterns so that we can make sure we are prescribing these medications safely and effectively without fueling this deadly crisis.”
Jena said that the researchers were especially interested to see whether there was a relationship between Medicare incentives to encourage hospital pain management and the rate of opioid prescriptions by hospitals.
Currently, hospitals that score well on patient–reported pain metrics receive cash bonuses. Could this policy encourage hospitals to overprescribe opioids?
While the study, which analyzed hospitalizations under Medicare in 2011, did find that the hospitals that scored highest on pain control measures also had the highest rates of opioid prescribing, the link was quite modest and did not explain most of the variation between hospitals.
While the study did adjust for differences in patient mix, diagnosis and other clinical factors, Jena said, it was possible that some hospitals had a high percentage of patients with more severe pain. However, he said it was more likely that the observed differences in prescribing rates were related to differences in how individual doctors prescribe or to differences in the prescribing culture of different hospitals or geographic regions.
Short-term prescriptions for opioids, while well-intentioned, can lead to long-term use. “Opioids have an important role to play in specific forms of acute pain, but the high risks of long-term use mean that adherence to proper prescribing guidelines is critical,” said study co-author Pinar Karaca-Mandic, associate professor at the University of Minnesota’s School of Public Health Division of Health Policy and Management.
Dana Goldman, professor and the Leonard D. Schaeffer Chair and Director of the Schaeffer Center for Health Policy and Economics at the University of Southern California also contributed to the study.