• Disclosing drug and alcohol related data

    I’ve heard from trustworthy sources that in its Medicare and Medicaid research data files, CMS is no longer including claims for patients with certain alcohol and drug use disorder related diagnoses and procedures. I have not found anything online that documents this more fully. I will update this post should anything come to my attention.

    Here’s an email from ResDAC:

    email ResDAC

    Suffice it to say, lack of access to such data for research is harmful to work on these specific populations, but also any other work, since it imposes a systematic bias on the sample. It messes up risk adjustment too.

    Think about it. Think about the precedent it sets as well.

    For this reason, I reviewed this entry in the code of federal regulations. At the time I accessed that link, the page said the information was current as of December 3, 2014. I’m having trouble assessing if it was published earlier than that date. I’ve excerpted some key passages below. I’ve added bold to some text. With regard to the issue at hand, I think it speaks for itself. (Update: Maybe they don’t speak for themselves as clearly as I thought. You should read this Nicholas Bagley post for an interpretation of the regulations. All posts on this issue are under the CMS-SUD tag.)

    From section 2.1, subsection (a):

    Records of the identity, diagnosis, prognosis, or treatment of any patient which are maintained in connection with the performance of any drug abuse prevention function conducted, regulated, or directly or indirectly assisted by any department or agency of the United States shall, except as provided in subsection (e) of this section, be confidential and be disclosed only for the purposes and under the circumstances expressly authorized under subsection (b) of this section.

    Subsection (b) includes:

    (2) Whether or not the patient, with respect to whom any given record referred to in subsection (a) of this section is maintained, gives his written consent, the content of such record may be disclosed as follows: […]

    (B) To qualified personnel for the purpose of conducting scientific research, management audits, financial audits, or program evaluation, but such personnel may not identify, directly or indirectly, any individual patient in any report of such research, audit, or evaluation, or otherwise disclose patient identities in any manner.

    Further on, it reads, in subsection (e):

    The prohibitions of this section do not apply to any interchange of records—

    (1) within the Armed Forces or within those components of the Veterans’ Administration furnishing health care to veterans

    Section 2.2, as near as I can tell, has identical language to 2.1 but pertaining to “alcoholism or alcohol abuse education, training, treatment, rehabilitation, or research.”

    Section 2.3 includes

    (2) These regulations are not intended to direct the manner in which substantive functions such as research, treatment, and evaluation are carried out. They are intended to insure that an alcohol or drug abuse patient in a federally assisted alcohol or drug abuse program is not made more vulnerable by reason of the availability of his or her patient record than an individual who has an alcohol or drug problem and who does not seek treatment.

    From section 2.52:

    (a) Patient identifying information may be disclosed for the purpose of conducting scientific research if the program director makes a determination that the recipient of the patient identifying information:

    (1) Is qualified to conduct the research;

    (2) Has a research protocol under which the patient identifying information:

    (i) Will be maintained in accordance with the security requirements of §2.16 of these regulations (or more stringent requirements); and

    (ii) Will not be redisclosed except as permitted under paragraph (b) of this section; and

    (3) Has provided a satisfactory written statement that a group of three or more individuals who are independent of the research project has reviewed the protocol and determined that:

    (i) The rights and welfare of patients will be adequately protected; and

    (ii) The risks in disclosing patient identifying information are outweighed by the potential benefits of the research.

    (b) A person conducting research may disclose patient identifying information obtained under paragraph (a) of this section only back to the program from which that information was obtained and may not identify any individual patient in any report of that research or otherwise disclose patient identities.

    Finally, if you’re interested, section 2.16 says, in its entirety:

    (a) Written records which are subject to these regulations must be maintained in a secure room, locked file cabinet, safe or other similar container when not in use; and

    (b) Each program shall adopt in writing procedures which regulate and control access to and use of written records which are subject to these regulations.

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  • Medicaid’s return on investment

    It’s time to face the fact that I’m not going to be able read, let alone write a full post on every interesting looking paper in my pile. But you’re hungry for content and want to know what’s potentially worth reading, right? So, expect a few posts that are little more than abstracts of papers I’ve at most skimmed. Maybe they contain a fatal flaw. Maybe they’re awesome. I just don’t have time to find out. Take with a grain of salt.

    Medicaid as an Investment in Children: What is the Long-Term Impact on Tax Receipts?” by David Brown, Amanda Kowalski, and Ithai Lurie:

    We examine the long-term impact of expansions to Medicaid and the State Children’s Health Insurance Program that occurred in the 1980’s and 1990’s. With administrative data from the IRS, we calculate longitudinal health insurance eligibility from birth to age 18 for children in cohorts affected by these expansions, and we observe their longitudinal outcomes as adults. Using a simulated instrument that relies on variation in eligibility by cohort and state, we find that children whose eligibility increased paid more in cumulative taxes by age 28. These children collected less in EITC payments, and the women had higher cumulative wages by age 28. Incorporating additional data from the Medicaid Statistical Information System (MSIS), we find that the government spent $872 in 2011 dollars for each additional year of Medicaid eligibility induced by the expansions. Putting this together with the estimated increase in tax payments discounted at a 3% rate, assuming that tax impacts are persistent in percentage terms, the government will recoup 56 cents of each dollar spent on childhood Medicaid by the time these children reach age 60. This return on investment does not take into account other benefits that accrue directly to the children, including estimated decreases in mortality and increases in college attendance. Moreover, using the MSIS data, we find that each additional year of Medicaid eligibility from birth to age 18 results in approximately 0.58 additional years of Medicaid receipt. Therefore, if we scale our results by the ratio of beneficiaries to eligibles, then all of our results are twice as large.

    So maybe, all in, Medicaid could be break even. Maybe. (Yes, this is the pure economist point of view, as if lives and quality thereof can be easily, unambiguously converted to dollars. And, yes, the framing here suggests — though does not demand — that things are worth doing only if they pay for themselves, which is ridiculous. Good things are worth spending money on.)

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  • Geographic variation tells us less than we think

    On Monday, J. Michael McWilliams and a team of colleagues, including me, published an article in Annals of Internal Medicine that compares geographic variation in cancer-related imaging in the VA to Medicare. The article was editorialized by Michaela Dinan and Kevin Schulman for AnnalsKate Madden Yee wrote a good, brief summary for AuntMinnie.com.

    Rather than write my own, I’m going to suggest you go read Yee’s. She quotes Michael with the one sentence takeaway:

    While geographic comparisons can be useful for understanding trends in provider behavior, our study demonstrates that geographic variation is not necessarily a reliable indicator of the extent of overuse in a healthcare system.

    Our finding that greater average efficiency isn’t associated with less variation is consistent with that of other studies across a variety of settings, which we cite: VA vs. Medicare in medication use (Gellad et al.), HMOs vs. unmanaged care (Baker et al.), Medicare Advantage vs. traditional Medicare (Matlock et al.). If it’s not a reliable signal of efficiency, perhaps it’s time to move beyond studies that simply demonstrate geographic variation.

    UPDATE: In light of some emails, I thought it worth clarifying that our article doesn’t rebut the idea that there is more waste in higher spending areas. That there is variation in the VA system and in Medicare means there could be more waste in some areas than others, as we and others have found. But as the IOM report notes, targeting areas for policy doesn’t make sense even if that is so. It would be better to target provider organizations/facilities within a system and measure performance at an organizational or facility level rather than at an area level. What our article does rebut is the idea that knowing how much variation there is tells you how much waste there is. Greater variation could exist at a lower level of waste or vice versa.

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  • Workplace wellness programs don’t save money

    We’ve said it before, many times and in many ways: workplace wellness programs don’t save money.

    Last week, on the Health Affairs blog, Al Lewis, Vik Khanna, and Shana Montrose said so too, adding some nuance we have not included in our posts on TIE. You should read the whole thing. Here are a few of my favorite passages:

    It is beyond the scope of this posting to question non-peer-reviewed vendor savings claims that do not use any recognized study design.

    I just love this phrasing of “we’re not reviewing crap.” Next, here’s a difference-in-differences blooper (or, really, a failure to do a real diff-in-diff analysis):

    As an example of overstated savings, consider one study conducted by the Health Fitness Corporation (HFC) about the impact of the wellness program it ran for Eastman Chemical’s more than 8,000 eligible employees. […]

    [F]igure 1 below shows that despite the fact that no wellness program was offered until 2006, after separation of the population into participants and non-participants in 2004, would-be participants spent 8 percent less on medical care in 2005 than would-be non-participants, even before the program started in 2006. In subsequent presentations about the program, HFC included the 8 percent 2005 savings as part of 24 percent cumulative savings attributed to the program through 2008, even though the program did not yet exist.

    Lewis-Figure-1

    Finally, for workplace wellness programs to save money, they have to save more than the cost of implementing such programs. Lewis, Khanna, and Montrose say exactly why this is hard:

    Data compiled by the Health care Cost and Utilization Project (HCUP) shows that only 8 percent of hospitalizations are primary-coded for the wellness-sensitive medical event diagnoses used in the BJC study. To determine whether it is possible to save money, an employer would have to tally its spending on wellness-sensitive events just like HCUP and BJC did. That represents the theoretical savings when multiplied by cost per admissions. The analysis would compare that figure to the incentive cost (now averaging $594) and the cost of the wellness program, screenings, doctor visits, follow-ups recommended by the doctor, benefits consultant fees, and program management time. For example, if spending per covered person were $6,000 and hospitalizations were half of a company’s cost ($3,000), potential savings per person from eliminating 8 percent of hospitalizations would be $240, not enough to cover a typical incentive payment even if every relevant hospitalization were eliminated.

    Now maybe Lewis et al. and TIE bloggers are wrong about wellness programs. Maybe they can save money. That’d be fine, if true. What we want, though, is evidence, not claims from industry studies based on study designs that cannot produce valid causal estimates without heroic assumptions. Show us the credible evidence and we’ll sing a different tune. Until then, so far, wellness programs look like a cost loser.

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  • A new entrant in the battle over drug prices: Hospital systems

    Not that it isn’t obvious to wonks, but I’m proud to have predicted this years ago, when I thought about the incentives of ACOs and vertical integration. I’ll let Jaimy Lee explain:

    All drugs [at  Christiana Care Health System in Wilmington, Del.] that cost more than $10,000 for a course of treatment—about 5% of the medications dispensed through the system’s inpatient and outpatient settings—are now assessed by the medication value subcommittee, which includes 12 physicians, administrators, nurses, pharmacists and finance executives.

    The subcommittee looks at a wide range of factors, including the drug’s efficacy and risk and the financial impact on the patient and the healthcare system. A group of five community leaders, including a local high school teacher, a pastor and a community activist, also evaluate factors such as a drug’s tolerability, cost and safety to provide input on quality-of-life issues. Of 27 drugs assessed by the subcommittee, 17 ended up on the system’s formulary list. […]

    Hospitals traditionally have been less concerned with drug costs in the outpatient setting. But the move away from a fee-for-service model, the broader push to improve value for patients, and the potential for health systems to end up shouldering all or part of the cost of some pricey medications is driving more interest in controlling the costs of outpatient drugs. […]

    “In light of healthcare reform, hospitals have no choice but to select drugs that are effective and have value,” a group of Christiana Care leaders wrote in a 2012 study looking at its cost-scoring system for pricey new drugs. […]

    In 2012, oncologists at Memorial Sloan Kettering Cancer Center in New York pulled cancer drug Zaltrap from the hospital’s formulary, arguing in a New York Times op-ed that the drug wasn’t worth its monthly treatment cost of $11,000. The manufacturer Sanofi eventually halved the price of the drug.

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  • Facility fees

    Reader David States sent me two articles on facility fees, a topic I’ve not given much attention (yet).

    Liz Kowalczyk reported in January 2013:

    [T]he Burlington hospital to charge patients an overhead fee when they are treated by doctors it employs — even when their offices are not located in the hospital but in a medical building 1½ miles away.

    This practice is common and has become more widespread in the past several years as hospitals across the United States buy up physician practices in the community. […]

    The federal Medicare program, which covers 47 million people and is under pressure to cut costs, is taking a look at the practice. An independent agency that advises Congress concluded last year that the charging of facility fees at hospital-owned medical practices is costing Medicare millions of dollars a year. For a 15-minute office visit, for example, the federal health insurance program paid $44 more at a hospital-owned office in 2011 than at an independent office. Medicare patients pay more too: Their share of the bill for this standard visit was $11 more when they went to a hospital-owned office. […]

    Erik Rasmussen, a senior associate director at the American Hospital Association, said the extra fees are a way to have patients served at all of a hospital’s locations cover overhead costs unique to hospitals, such as having emergency room staff available 24 hours a day.

    Fred Schulte reported in December 2012:

    The root of these increases are controversial charges known as “facility fees,” and they are routinely tacked on to patients’ bills not just for services actually provided in hospitals, but also by outpatient care centers and doctors’ offices simply because they’ve been purchased by hospital-based health care systems. Hospitals argue they can’t afford to keep the doors open without facility fees.

    Hospitals have billed them at least since 2000 when Medicare set billing standards for doctors employed by hospitals, and private insurers went along. Since then, the fees have grown increasingly common, costly and controversial. […]

    The fees date back to April 2000, when Medicare clarified its policy for billing by health groups that hired physicians. […]

    The issue popped up last year when the House passed legislation that extended the payroll tax holiday and unemployment compensation benefits. Tucked into the “Middle Class Tax Relief and Job Creation Act” was a provision to cut about $6.8 billion in Medicare costs by targeting doctor services in hospital-owned offices.

    The hospital industry fought back hard — and ultimately successfully. The cuts never passed the Senate and were not in the final conference committee bill signed by President Obama in February. […]

    The Medicare Payment Advisory Commission, or MedPAC, which advises Congress, stirred up the debate in January when it recommended that the health plan for seniors pay for visits with doctors at the same rate, no matter where they occurred, and regardless  of whether the doctor practices independently or is employed by a hospital.

    MedPAC also made this recommendation in subsequent reports, according to the article. I have not chased down the MedPAC reports yet. The article also discusses efforts to force hospitals to disclose facility fees in advance and challenges to removing facility fees from provider organizations.

    Facility fees also arise in this New York Times article by Elizabeth Rosenthal.

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  • Hierarchy of human needs

    Via Veris:

    human needs

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  • When health coverage expansion means longer waits for a doctor

    The following originally appeared on The Upshot (copyright 2014, The New York Times Company). I thank Daniel Liebman for his assistance tracking down some evidence for an early draft of this post.

    One concern about the Affordable Care Act is that as more Americans get health insurance and start using it, those who already have coverage will have to wait longer for care.

    Recent research with a focus on Massachusetts suggests this may actually happen, but may not last long. Several years after the coverage expansion in that state, access to care for other, previously covered residents appears to be no worse than before the expansion.

    Coverage expansion would present this potential trade-off if the supply of care (the number of doctors or their productivity) does not expand to meet the greater demand for it from the newly insured.

    Increasing coverage is likely to increase demand for care. A longstanding finding in the research literature is that uninsured people avoid and delay care more than insured people do, and that this can harm health. According to Gallup, uninsured Americans are about twice as likely as insured Americans to delay care, and about 30 percent have put off care because of costs. A large body of research on the effects of the coverage expansion in Massachusetts found that it increased access to care for previously uninsured residents. For example, residents in that state were almost 5 percent less likely to forgo care, compared with the expected rate without the expansion.

    But improving access to care for the uninsured doesn’t necessarily reduce access for everyone else, according to a new study published in the journal Health Services Research and led by Dr. Karen Joynt of Harvard. The authors found that neither receipt of outpatient services nor quality of care suffered when coverage expanded under the state’s health overhaul, which started in 2007. The findings, which are consistent with previous work by the same authors, are based on analysis of changes in receipt of outpatient care from 2006 to 2009 for elderly Medicare beneficiaries with chronic illnesses in Massachusetts, as compared with those in other New England states.

    However, other work seems to conflict with Dr. Joynt’s analysis. In an article also published in Health Services Research, Amelia Bond and Chapin White examined changes in primary care visits from 2005 to 2007 by Medicare beneficiaries in Massachusetts ZIP codes with different rates of the uninsured in 2005. They compared these differences with those from ZIP codes in surrounding states with similar characteristics. Massachusetts showed a larger gap in primary care visits by Medicare beneficiaries, suggesting that the coverage expansion came at the cost of reduced access for those Medicare beneficiaries, and presumably others who also already had insurance.

    Historically, large expansions of health insurance for some tends to reduce access to care for others. Just after universal health insurance was introduced in England and Wales in 1948, receipt of care increased for most of the population, but it decreased for people with high incomes, precisely those who probably had good access before universal coverage. A similar thing happened in Quebec after Canada introduced universal coverage. Physician visits increased in general, but decreased for higher-income residents. Waiting times also increased, and more so for higher-income groups.

    I am unaware of any similar research pertaining to Medicare. When it was introduced in the United States in 1965, access to care for those 65 and older improved, but we don’t know whether access to care suffered for the rest of the population. Medicare payments at that time were generous, and that may have helped spur the expansion of supply to meet the new demand.

    The same cannot be said of the Affordable Care Act, in general. Indeed, it is financed in part by cuts to Medicare. However, the law does include an increase in funding for primary care training and in fees paid for primary care visits under Medicaid, albeit only through this year (Congress is considering extensions).

    A potential explanation for the disparate results of the two Massachusetts studies also suggests why the Massachusetts experience may not generalize to other states. The study by Drs. Bond and White included data through 2007, while that of Dr. Joynt and colleagues included data through 2009, two years later. Perhaps health providers in Massachusetts were stretched thin in 2007, just as the new health measures were taking effect in the state. But by 2009, maybe they managed to increase their capacity, either by increasing their numbers or enhancing their productivity to meet additional demand from a larger insured population, perhaps.

    For this reason, delays in care should be expected in states that are less able to increase capacity to meet additional demand from a larger insured population, perhaps because they’re not as well supplied with medical schools as Massachusetts, or because providers may not be able to increase their productivity as much as those in Massachusetts may have. Already, the Health Resources and Services Administration judges that there are regions where demand for care outstrips supply. By the organization’s estimate, 20 percent of Americans live in regions where there are not enough primary care doctors; 16 percent where there are not enough dental care providers; and 30 percent in areas where mental health providers are in short supply.

    What can be done? Two approaches come immediately to mind. First, it’s generally believed that a substantial fraction (10 percent or more) of health care delivered is wasteful, unnecessary overtreatment. By reducing that waste, we would free up resources to deliver beneficial care to those who would otherwise wait longer for it. Reductions in access to care need not be harmful if they’re purely reductions in care that isn’t of benefit anyway.

    Second, we could increase primary-care capacity, for example by increasing the wages primary-care physicians earn (e.g., by increasing what Medicare pays them). Another capacity-building policy would be to allow nurses to do more of the functions that are reserved for primary-care doctors.

    That delays in care in Massachusetts didn’t seem to persist beyond a year or two after coverage expansion is comforting. But other states may be able to follow Massachusetts’ lead only if they can develop sufficient capacity to meet the greater demand that the Affordable Care Act is likely to create.

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  • Targeting drug development

    Muthiah Vaduganathan and Vinay Prasad in a JAMA Viewpoint:

    From a pragmatic standpoint, drug development programs conducted in broad populations poorly prioritize which patients should start therapy first. If provided regardless of risk, expensive new first-in-class agents may overwhelm health care budgets. In hepatitis C management, novel drug therapies broadly indicated for most patients with chronic hepatitis C, such as sofosbuvir, cost approximately $1000 per pill, presenting major cost challenges to drug implementation and distribution. In an effort to balance access and affordability, recent hepatitis C clinical practice guidelines have encouraged use of these agents primarily in the sickest subgroup of patients. In the current financial environment, emerging clinical trials should consider selecting the groups at highest risk to guide an economically viable and practical approach to drug utilization.

    This gets at the point that even a very cost-effectiveness therapy can overwhelm budgets. The allocative efficiency problem still needs to be addressed.

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  • The formulary wars

    Robert Langreth reports:

    Unless more is done about a wave of new and expensive drugs, some priced at as much as $50,000 a month, Miller [the chief medical officer at Scripts Express] says that health plans are going to be swamped as costs double to half a trillion dollars as soon as 2020. […]

    Drug companies that “think they can charge whatever they want” in competitive categories “run the risk of being excluded,” said Glen Stettin, 50, Miller’s colleague responsible for clinical products, including formularies.

    An Express Scripts competitor, CVS will keep 95 drugs off its main formulary. More at the link. A related story is here.

    Correction: In my first draft, I had written that CVS will keep 95% of drugs, not 95 drugs, off its main formulary. My bad.

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