For decades medicine’s divide between psychiatrists who cared for the mind and primary care physicians (PCPs), who treated “from the neck down,” worked against both patients and the healthcare system. The arrival of the Affordable Care Act (ACA), coupled with a federal parity law for mental health coverage, offers hope for those with multiple chronic conditions.

Persons with diabetes mellitus, either type 1 (T1DM) or type 2 (T2DM), stand to gain, if the offerings at recent medical meetings are any sign. Both, the May gathering of the American Psychiatric Association (APA) in New York City,

 and the June Scientific Sessions of the American Diabetes Association (ADA) in San Francisco,

 featured sessions on the link between diabetes and depression.

The message at both meetings: coordinating care between PCPs and mental health providers is an idea whose time has come. Not only does this approach work better for patients, but evidence shows it saves money, too. Both meetings and several studies published in recent years have explored the connections between diabetes and depression. Among the observations:

persons with depression account for more healthcare spending on diabetes and cardiovascular disease than those without mental health problems; depression that starts during adolescence causes sufferers to eat poorly, be less active, or smoke and drink, contributing to obesity and other comorbidities; and, managing diabetes over a lifetime is stressful and time-consuming, which wears patients down.

“Depression raises the risk 60% that the patient will develop type 2 diabetes, Wayne J. Katon, MD, of the University of Washington, said in an interview with Evidence-Based Diabetes Management. Once a patient has T2DM, untreated depression can make it hard to follow diets or stick with medication, he said. Many of these connections have been known for years. In 2001, a study in Diabetes Care, the ADA’s flagship journal, concluded that the presence of diabetes doubled the odds of comorbid depression.

 The difference now is the push to coordinate care for the constellation of diseases, rather than treat mental health in a silo.

What’s driving the shift? There are many factors, but the most important one is the ACA, which requires providers and health plans, as well as new entities called accountable care organizations (ACOs), to deliver better care while cutting costs. This has forced the healthcare system to confront how inattention to mental health drives up spending on the medical side. The 2014 report prepared for APA by the actuarial firm Milliman, Inc, got a full airing in New York City, including the finding that better integration of primary and mental health care could save $26 billion a year.

In 2012, 14% of the enrollees on commercial plans had mental health claims, but these patients accounted for 28.7% of the medical spending.

Taxpayers pay for lack of coordination too.

Mental health patients make up 9% and 20% of the enrollees in Medicare and Medicaid, respectively, but these enrollees accounted for 26.3% of the medical spending in those plans.

 At the APA session, “Levering Psychiatric Expertise: Integrated Care and Healthcare Reform,” panelists agreed that psychiatrists and PCPs who fail to embrace integrated delivery models will suffer financial consequences.

The pioneers integrating primary and mental health care, particularly for patients with T2DM, are at the University of Washington, where the TEAMcare design was developed and studied in a clinical trial.

 Patients were randomly assigned to receive usual care or collaborative care; patients in the second group had their care across multiple diseases—including depression, T2DM, and cardiovascular disease, managed by a specially trained nurse who ensured that cases were reviewed at weekly sessions with the care team.

The University of Washington group reported its results in the New England Journal of Medicine in 2010.

 Patients receiving collaborative care for 12 months had 58% improvement in glycated hemoglobin (A1C) levels relative to the control group. Low-density lipoprotein measures and blood pressures improved by wider margins (Table), as did scores on the Symptoms Checklist (SCL-20) depression screen. Patients receiving collaborative care were more likely to have adjustments to insulin or to antihypertensive and antidepressant medications.

Patients who received the intervention also reported higher levels of satisfaction with their care.

 The cost of care for this group was lower—an average of $594 per patient for the year.

 The Washington results have gained notice. Katon, who was the lead author on the NEJM article, took part in both panel discussions at APA and gave a workshop on practical ways to bring collaborative care to a practice.

 Co-author Paul Ciechanowski, MD, MPH, presented the TEAMcare approach at the ADA symposium, “Bending the Curve: Behavioral Health Efforts in Diabetes and Healthcare Reform.”

 Katon and his University of Washington colleagues are now bringing TEAMcare concepts to practices around the country.

As Ciechanowski and others explained at the ADA session, the key ingredient in collaborative care is the weekly case review, where PCPs, mental health professionals, care coordinators, and diabetes educators track who has missed an appointment, whose A1C levels should be taken, and whose unexplained physical symptoms could be a sign of a stress.

Another component is better use of electronic health records, although some state regulations constrain mergers of medical and mental health records.

The need for collaborative approaches to diabetes and mental healthcare seems so obvious—so why has it taken so long?

In an interview, Katon listed many challenges: Acute versus chronic conditions. Primary care has historically meant “acute care,” such as treatment of a symptom or injury, while mental health services work best over time.

 Most patients will show up at a PCP when stress manifests itself as a physical symptom, but the stigma of mental healthcare often means they won’t follow up on a referral to a psychiatrist. It’s easier to get past this when the mental health provider is part of the PCP’s team.

Getting patients to take medications is a problem across chronic conditions, but it’s especially troublesome in the mental health arena. And the divide between primary care and mental health care has often meant that needed adjustments to antidepressants never occur. When medication doesn’t work or side effects appear, patients may stop taking it.

 Historically, the biggest barrier to coordination of primary and mental health care has been the separation of coverage by payers. Limits on mental health visits and restrictions to higher-cost medications have made continuity of care and affordability difficult for many patients. ACA’s enshrinement of mental health parity should help change this, although enforcement is just beginning.

Doctors themselves can be a barrier to better coordination, even in settings like the TEAMcare project in Washington. But if they can be won over, Katon explained at APA, these one-time doubters can be the strongest supporters. He described a colleague, a former athlete-turned-PCP who would not make a mental health referral for 2 years. Then this doctor spent months working to alleviate his patient’s unexplained back pain, without success. Katon, the psychiatrist on the team, interviewed the patient and learned of multiple family problems in the home, including addiction, unemployment, and money woes among the patient’s adult children. Katon treated the woman’s depression and helped her learn to set limits, which rid her of pain. In the process, Katon won over her primary care doctor.

Katon has high hopes for the movement toward the Patient-Centered Medical Home (PCMH), which should mean better coordination of care. Standards revised this spring by the National Committee on Quality Assurance (NCQA), which offers PCMH accreditation, call for better integration of behavioral health services into primary care.

 In June, NCQA took comment on revisions that will boost accountability for antidepressant medication management and proactive assessment of drug and alcohol abuse, as well as numerous measurements in diabetes care.

“The ACO movement, the vertical organization with medical specialty care, and the focus on keeping people out of the hospital will all help,” Katon said. Healthcare reform is forcing practices and health systems to scrutinize where patients with psychiatric disorders are overrepresented in treatment of comorbid conditions. The movement promises to tackle what has been a hurdle in promoting collaborative care: how to pay for the care coordinators or diabetes educators who make these models hum. Too often, Katon said, practices that did the right thing saved money, but the savings flowed to the payer, not to those delivering better care.

The arrival of ACOs and shared savings means “there’s an incentive to get that money back,” he said. He expects that Medicare’s tracking of 30-day hospital readmission rates to be especially powerful in ensuring that mental health patients with comorbid conditions get not only care but also support services upon discharge. Research into the connections is advancing as well, looking beyond the behavioral associations to biochemical roots. An article published last month, based on preclinical work on mice, suggests that decreased serotonin transporter function may be the common thread between depression and insulin resistance.

 Better coordination of care may help doctors distinguish between true depression and “fatigue” from dealing with symptoms. Preliminary results presented in San Francisco found that measures of depression dissipated among many patients who received interventions aimed at helping them manage their disease.

“What’s important about this,” said Lawrence Fisher, PhD, ABPP, of the University of California San Francisco and lead author of the study, “is that many of the depressive symptoms reported by people with type 2 diabetes are really related to their diabetes, and don’t have to be considered psychopathology. So they can be addressed as part of the spectrum of the experience of diabetes and dealt with by their diabetes care team.”

1. American Psychiatric Association. 167th Annual Meeting website. http://annualmeeting.psychiatry. org/. Accessed June 20, 2014.

2. American Diabetes Association. 74th Scientific Sessions website. http://professional.diabetes.org/Congress_Display.aspx?TYP=9&CID=93229.Accessed June 20, 2014.

3. Caffrey MK. Integrated care no longer an afterthought at APA: conference coverage, AJMC.com. http://www.ajmc.com/conferences/APA2014/Integrated-Care-No-Longer-an-Afterthought-at-APA. Published May 4, 2014.Accessed June 24, 2014.

4. Caffrey MK. Behavioral health session tackles diabetic burnout, mental health delivery: conference coverage, AJMC.com. http://www.ajmc.com/conferences/ada-2014/Behavioral-Health-Session-Tackles-Diabetic-Burnout-Mental-Health-Delivery-Published June 15, 2014. Accessed June 24, 2014.

5. Anderson RJ, Freedland KE, Clouse RE, Lustman PJ. The prevalence of comorbid depression in adults with diabetes. Diabetes Care. 2001;24(6):1069-1078.

6. American Psychiatric Association. APA unveils report on cost-effectiveness of integrated care. Psychiatric News Alert. http://alert.psychiatricnews.org/2014/04/apa-unveils-report-on-cost.html.Published April 4, 2014. Accessed June 24, 2014.

7. Katon WJ, Lin EHB, Von Korff M, et al. Collaborative care for patients with depression and chronic illnesses. N Engl J Med. 2010;363:2611-2620.

8. Caffrey MK. Practical ideas for implementing collaborative care: conference coverage, AJMC.com. http://www.ajmc.com/conferences/APA2014/Practical-Ideas-for-Implementing-Collaborative-Care.Published May 4, 2014. Accessed June 24, 2014.

9. TEAMcare website. http://www.teamcarehealth .org/. Accessed June 24, 2014.

10. New NCQA patient-centered medical home standards raise the bar [press release]. Washington, DC: National Committee for Quality Assurance; March 24, 2014. http://www.ncqa.org/Newsroom/NewsArchive/2014NewsArchive/NewsReleaseMarch242014.aspx.

11. Public invited to help shape new measures on physical health, comorbid conditions and care transitions for people with serious mental illness and alcohol or other drug use disorders [press release]. Washington, DC: National Committee for Quality Assurance; June 3, 2014. http://www.ncqa .org/Newsroom/NewsArchive/2014NewsArchive/NewsReleaseJune32014.aspx.

12. Pomytkin IA, Cline BH, Anthony DC, Steinbusch HW, Lesch KP, Strekalova T. Endotoxaemia resulting from serotonin transporter (5-HTT) function: a reciprocal risk factor for depression and insulin resistance [published online May 4, 2014]? Behav Brain Res. doi:10.1016/j.bbr.2014.04.049.

13. Fisher L, Polonsky W, Hessler D. A new validated measure of diabetes distress for adults with type 1 diabetes. Diabetes. 2014;63(suppl 1):Abstract 67-LB.

14. Diabetes distress v. depression: are people with type 2 being misdiagnosed [press release]? San Francisco, CA: American Diabetes Association; June 16, 2014. http://www.diabetes.org/newsroom/press-releases/2014/diabetes-distress-vsdepression. html.

Articles

Evidence-Based Diabetes Management

Integrated Treatment for Diabetes, Depression Gains Notice, With Help from ACA

The association between diabetes and cognition has been known for a while. However, until recently, the primary focus of diabetes-related complications has been on hypertension, renal failure, vision loss, autonomic and peripheral neuropathy, myocardial infarction and cerebrovascular disease, including stroke. Neuropathy, in particular, is responsible for additional comorbidities, resulting in a significantly increased cost of treatment.

 Of late, the effect of hyperglycemia on the cognitive ability of patients has been regaining interest, after research efforts were abandoned in the United States by 1970.

According to the World Health Organization, dementia—a cognitive degeneration syndrome&mdash;affects 35.6 million people globally, with about 7.7 million added every year. Almost 60% to 70% of dementia cases are a result of pathological degeneration caused by Alzheimer’s,

 and recent data suggest that diabetes could be one of the causative factors for the remaining 30% of cases.

In the United States, 16 million people were estimated to be living with cognitive impairment in 2010. With the baby boomers fast approaching and crossing 65 years of age, that number is expected to increase significantly.

 The cost of patient care can be an enormous strain on the healthcare system, both in direct healthcare costs and indirect costs, such as the loss of income for a caregiver within the family. Treating patients with Alzheimer’s and other related dementias were estimated to cost Medicaid nursing facilities an average of $647 million in 2010, which did not include prescription drug costs or home- and community-based care.

 The direct costs of Alzheimer’s alone are estimated at $214 billion in 2014, $150 billion of which would be Medicare and Medicaid expenses. In terms of indirect costs, 15.5 million caregivers provided unpaid care to Alzheimer’s patients in 2013, valued at a whopping $220 billion.

The managed care statistics make it imperative that we try to understand and regulate some of the risk factors of reduced cognition. Based on numerous recent studies, as well as historical evidence, the Alzheimer’s Association has recognized diabetes as a risk factor for cognitive disease.

Persons with type 2 diabetes mellitus (T2DM) experience compromised verbal and nonverbal memory, reduced attention, and reduced processing speed, while type 1 diabetes mellitus patients additionally suffer from an impaired visuospatial performance, psychomotor efficiency, and general intelligence.

 A study conducted in over 800 elderly men and women found that chronic, uncontrolled hyperglycemia can result in slowly progressive functional and structural abnormalities in the brain, with a 65% higher risk of Alzheimer’s disease in those with T2DM.

 A mouse model that evaluated the effect of aging and diabetes on learning and hippocampal synaptic plasticity, observed significant learning impairments in aged diabetic rats compared with controls.

“Older individuals with T2DM are at a higher risk of developing Alzheimer’s than the younger population,” said Gail Musen, PhD, assistant professor of pscychiatry,  Harvard Medical School and assistant investigator in the section on clinical, behavioral, and outcomes research at Joslin, in an interview with 

. Musen’s research is focused on identifying risk factors for Alzheimer’s disease in persons aged 45 to 65 years suffering from T2DM. “T2DM increases the risk of Alzheimer’s disease. Why? We don’t know the reason for that yet, although there are reports of insulin resistance or certain vascular problems being responsible for this.” Musen said that these patients show only a slight decline in their cognitive abilities that emerge as interesting patterns in the brain magnetic resonance imaging (MRI). “However,” she said, “among the older population, those above 65 years of age, a rapid decline in cognitive abilities is observed, highlighting a different etiology between the 2 populations.”

In Alzheimer’s disease, “The default mode network is most susceptible to the build-up of amyloid plaques and hypometabolism,” she said. There are no visible early signs of the disease in 20- to 40-year-old individuals, so awareness of family history of cognitive impairment in T2DM patients would be a good indication. “If T2DM is the primary risk factor, it’s easier to control,” with medication, diet, and exercise. “However, if there are genetic factors involved, that’d be a lot more difficult to regulate.” Musen’s research group is working toward identifying risk factors for early disease intervention. “Unfortunately, we do not as yet have any reliable serum or blood markers available,” she said, although proteins like sirtuin 1 have been projected as early markers of Alzheimer’s.

According to Medha N. Munshi, MD, head of Joslin’s Geriatric Diabetes Clinic and assistant professor of medicine at the Beth Israel Deaconess Medical Center, “Older diabetes patients are usually more compliant with medication adherence and disease management. When they don’t, you wonder why?” Speaking with Evidence-Based Diabetes Management, Munshi explained why she was interested in the phenomenon of cognitive dysfunction in the geriatric diabetic population. Her clinical observations in the older patient population that she treated demonstrated that cognitive dysfunction, depression, and an overall declining functional status were a barrier to achieving good glycemic control.

Munshi’s research group assessed these unrecognized barriers by screening adults over 70 years of age for the presence of depression, functional disabilities, and cognitive dysfunction. The finding: 32% of men and 34% of women reported depressive symptoms, which could influence functional disability. Patients recognized to have cognitive dysfunction had poorer glycemic control, probably due to an incorrect dose or timing of insulin or of their oral medication, omission of meals that can lead to hypoglycemia, etc.

According to Munshi, these patients had a fairly good memory—the problem was with executive dysfunction–so integrating their treatment regimen was an issue, resulting in compromised self-care abilities.

MRI of the brain of 614 diabetic patients observed that a longer duration of high fasting plasma glucose level is associated with lower normal and total gray matter volumes, essentially a reduction in the total brain volume.

 The study found that patients who had been diagnosed for 15 years or more had less gray matter than those who had the disease for 4 years or less. While previous studies had attributed the reduced brain size to a reduction in the blood flow, the authors of this study, conducted at the University of Pennsylvania, observed an accelerated rate of degeneration of the brain tissue in hyperglycemic patients, which they defined as a “neurodegenerative insult on the brain.” Follow-up studies, evaluating the effect of aggressive treatment in slowing down the rapid rapid cognitive decline, are ongoing.

When asked about the efforts being undertaken by treatment institutes and diabetes organizations, like the American Diabetes Association (ADA), in raising awareness about cognitive impairment as a comorbidity of diabetes, Munshi acknowledged that “there is a big gap in the knowledge base—not just among patients and caregivers, but also providers themselves.” She continued, “There are not many programs that address some of the additional comorbidities in the older diabetic patients, such as depression, cognitive dysfunction, and polypharmacy. At Joslin, each patient is screened for cognitive decline, unlike most diabetes care providers.”

Can Overcoming Insulin Resistance Slow Down the Process?

A clinical trial, conducted as a part of the ACCORD Memory in Diabetes (MIND) study, evaluated the potential of intensive glycamic therapy to reduce glycated hemoglobin (A1C) to <6%, compared with standard therapy that would reduce A1C to between 7% and 7.9%. Of the 2977 patients randomized in the study, 1358 patients received intensive therapy and 1416 received standard therapy. Brain MRIs of these patients presented a significantly lower (26%) decline in the total brain volume of patients receiving intensive therapy compared with those receiving standard therapy. Surprisingly, while the cognitive outcomes were no different between the 2 groups, the intensive therapy was associated with increased mortality, an increase in hypoglycemic events, and weight gain, without any cardiovascular benefits, in the main ACCORD trial.

 The results of this particular trial do not support the use of intensive therapy to improve cognitive outcomes.

However, insulin and insulin-mediated signaling pathways are known to regulate normal emotional and cognitive brain functions, and may contribute to memory and learning. Historical data points to an association between glucose metabolism and cognitive impairment.

 Therefore, a different approach might be essential. A recent proof-of-concept clinical trial, that Munshi participated in, did just that—intranasal insulin delivery to the brain was observed to improve cognitive performance in 15 older T2DM patients, without any effect on blood glucose levels.

Binding of insulin, an important neuromodulator, to its corresponding receptors in the brain is regulated by insulin transport through the blood-brain barrier (BBB). Insufficient delivery of this peptide hormone can reduce perfusion and cortical activity, with corresponding effects on cognition (

). Intranasal delivery bypasses the BBB and also avoids systemic effects of insulin. The authors conclude that the shared insulin signaling in vascular and metabolic pathways can provide new therapeutic targets to prevent brain atrophy and consequent cognitive decline in older T2DM patients.

Managing a complex disease like diabetes is extremely difficult and requires the patient to rigorously follow specific disease-management protocols. Impaired cognition could result in cardiovascular effects or severe hypoglycemic events, making it imperative to develop strategies to reduce the risk of cognitive impairment.

A retrospective study conducted by Munshi and her colleagues, evaluating the barriers to glycemic control in the older diabetic population, identified that communication with an educator who is familiar with a patient’s barriers can improve self-care frequency, help maintain functionality, and lower stress in the patients.

The study concluded that telephone follow-up with the patients in-between clinic visits would greatly improve diabetes control in the elderly, cognition-impaired population.

Taken together, there still seems to be a lack of awareness on cognitive impairment as a risk factor for diabetes, and improving the understanding among patients, caregivers, and physicians is essential. Additionally, treatment plans should incorporate therapeutic strategies for brain health, especially among older T2DM patients.

1. Zhao Y, Ye W, Boye KS, Holcombe JH, Hall JA, Swindle R. Prevalence of other diabetes-associated complications and comorbidities and its impact on health care charges among patients with diabetic neuropathy. J Diabetes Complications. 2010;24(1):9-19.

2. Kaidanovich-Beilin O, Cha DS, McIntyre RS. Metabolism and the brain. The Scientist website. http://www.the-scientist.com/?articles.view/articleNo/33338/title/Metabolism-and-the-Brain/. Published December 1, 2012. Accessed June 18, 2014.

3. Dementia. World Health Organization website. http://www.who.int/mediacentre/factsheets/fs362/en/. Accessed June 17, 2014.

4. Cognitive impairment: a call for action now! World Health Organization website. http://www.cdc.gov/aging/pdf/cognitive_impairment/cogimp_poilicy_final.pdf. Accessed June 17, 2014.

5. Alzheimer’s facts and figures. Alzheimer’s Association website. http://www.alz.org/alzheimers_disease_facts_and_figures.asp#cost.Accessed June 17, 2014.

6. Diabetes and cognitive decline. Alzheimer’s Association website. https://www.alz.org/national/documents/topicsheet_diabetes.pdf.Published February 2014. Accessed June 17, 2014.

7. S Roriz-Filho J, Sá-Roriz TM, Rosset I, et al. (Pre)diabetes, brain aging, and cognition. Biochim Biophys Acta. 2009;1792(5):432-443.

8. Diabetes mellitus and risk of Alzheimer disease and decline in cognitive function. Arvanitakis Z, Wilson RS, Bienias JL, Evans DA, Bennett DA. Arch Neurol. 2004;61(5):661-666.

9. Kamal A, Biessels GJ, Duis SE, Gispen WH. Learning and hippocampal synaptic plasticity in streptozotocin-diabetic rats: interaction of diabetes and ageing. Diabetologia. 2000;43(4):500-506.

10. Kumar R, Chaterjee P, Sharma PK, et al. Sirtuin1: a promising serum protein marker for early detection of Alzheimer’s disease. PLoS One. 2013;8(4):e61560.

11. Bryan RN, Bilello M, Davatzikos C, et al. Effect of diabetes on brain structure: the action to control cardiovascular risk in diabetes MR imaging baseline data. Radiology. 2014. http://dx.doi.org/10.1148/radiol.14131494.

12. Park A. Diabetes ages the brain by two years, says study. Time. http://time.com/77874/diabetes-ages-brain-by-two-years/. Published April 29, 2014. Accessed June 17, 2014.

13. Launer LJ, Miller ME, Williamson JD, et al. Effects of intensive glucose lowering on brain structure and function in people with type 2 diabetes (ACCORD MIND): a randomised open-label substudy. Lancet Neurol. 2011;10(11):969-977.

14. Novak V, Milberg W, Hao Y, et al. Enhancement of vasoreactivity and cognition by intranasal insulin in type 2 diabetes. Diabetes Care. 2014;37:751—759.

15. Novak V, Milberg W, Hao Y, et al. Enhancement of vasoreactivity and cognition by intranasal insulin in type 2 diabetes. Diabetes Care. 2014;37:751—759.

16. Munshi MN, Segal AR, Suhl E, et al. Assessment of barriers to improve diabetes management in older adults: a randomized controlled study. Diabetes Care. 2013;36(3):543-549.

Aging and Cognitive Decline in Diabetes

Research and development (R&D) of novel biotherapeutics must be driven by considerations of value to healthcare payers. In an era of cost-constrained health systems, those who make investment decisions in R&D for novel biotherapeutics must closely consider market needs and the necessity to clear market access hurdles.

Even in the United States, developers can no longer assume that the products and services they develop will be adopted and funded; payers may not reimburse innovative technologies at a price sufficient to generate a competitive return on the investment in R&D. It is no longer sufficient for developers to focus on clearing safety and efficacy regulatory hurdles. Meeting these evaluation criteria as technologies progress from preclinical testing through clinical testing is not indicative of whether the resulting technology represents a good investment from either commercial or health-system perspectives. Achieving regulatory approval is only indirectly related to criteria that determine reimbursement and health-system adoption of the therapy.

Here we describe the Value-Engineered Translation (VET) framework that couples development decisions along the translational continuum with the production of a “reimbursable evidence dossier.” It assists technology develop-ers in comprehending the evidence requirements of healthcare payers, both public and private, in different markets. Concomitantly, it supports payers in evaluating a broader range of factors for novel bio-therapeutics that may address unmet healthcare needs. Finally it benefits the public and patients, who require better and more cost-effective therapeutics and diagnostics, by informing decisions on health insurance coverage and out-of-pocket expenses. We illustrate the utility of the framework with real world biotherapeutic development examples, noting that a similar analytical framework is applicable to therapeutics, ‘omics’-based diagnostics, combination therapies, or codependent technologies.

We begin, however, with a brief description of the changing health technology assessment environment. The Case for Health Technology Assessment in Major Markets Health Technology Assessment (HTA) is a process by which the evidence for the safety, effectiveness and value of technologies is systematically identified, critiqued, and synthesized. HTA informs the  reimbursement decisions of payers—should funding for a technology in a particular indication be introduced, maintained, limited, or withdrawn?

HTA dates back to the 1976 United States Congressional Office of Technology Assessment report, “Development of Medical Technologies: Opportunities for Assessment.”

 During the 1980s, HTA continued to develop in the United States, notably in the Blue Cross/Blue Shield Technology Evaluation Center (TEC) and its collaborative relationship with David M. Eddy, MD, PhD, of the Kaiser Permanente Care Management Institute, which began in 1993.

However, from the late 1980s to the present day, the role of HTA in health coverage has grown most rapidly outside the United States. HTA agencies operate at national and state/provincial levels in most countries with publicly funded health systems. Notable examples include the Canadian Agency for Drugs and Technologies in Health (CADTH); Australia, which requires economic evaluations to be included in submissions to its Pharmaceutical Benefits Advisory Scheme; and the United Kingdom National Institute for Health and Care Excellence (NICE), which has pushed the role of HTA in decision making with explicit decision criteria supported by increasingly sophisticated methods. To support technology developers, NICE now offers early scientific advice to companies to help them design studies and develop evidence portfolios that meet the needs of reimbursement agencies.

Similarly, in Europe, licensing authorities host joint HTA/regulatory scientific advice meetings with biopharmaceutical companies. As the European Union represents 27% of the global biopharmaceutical market, planning to meet the needs of HTA organizations, as well as licensing authorities, is an increasingly important component of pharmaceutical R&D and clinical trial planning. The United States has the world’s most expensive health system, with some of the poorest outcomes in terms of average lifespan and infant mortality among developed countries. Healthcare consumed 17.2% of the gross domestic product (GDP) of United States in 2012, and spending outpaced GDP by 2.0% to 2.3% from 1950 to the global recession in 2007, with some slowdown in the rate of growth since. The high rate of increase in healthcare expenditures is due to a combination of factors, many of which are likely to worsen in the coming decades. These include an aging population and the high cost of new technologies that do not necessarily improve health outcomes compared with existing standard of care. The greatest call on federal coffers comes from the Medicare and Medicaid programs. The former covers all citizens aged 65 years and older and some persons with disabilities; the latter covers individuals below an income cutoff. Medicare covered 46 million people in 2009, 33.2 million were enrolled in Medicaid, and an additional 150 million Americans were covered by private insurance, largely through their employers. The remainder of the population was uninsured.

While US law expressly prohibits CMS from considering cost-effectiveness in national coverage determinations (NCDs), its management stresses the importance of cost control. Jacqueline Fox describes an “open secret” in health policy—CMS considers cost when issuing NCDs.

 Indeed, one analysis suggests that coverage decisions are influenced by the availability of cost-effectiveness evidence,

 even though clear evidence of an implicit cost-effectiveness threshold was lacking.

 Fox calls for CMS to be given the power and obligation to develop transparent processes to consider the cost of new medical treatments before covering them,

 a call echoed in a 2014 report for RAND Health.

 This report further called for an alignment in incentives for development of safe and effective health technologies with incentives for the development of technologies that present the greatest value to health systems and patients. Of necessity, value implies considerations of cost-effectiveness.

Several recent developments support our contention that cost will factor increasingly into US healthcare markets. First, in the early part of this century, CMS publicly re-engaged with HTA, implementing Coverage with Evidence Development (CED), where coverage is linked to the collection of additional evidence to inform subsequent reviews of the coverage decision.

 CED was consistent with the development of conditional reimbursement programs in other Western healthcare systems since the mid-1990s.

 Access with Evidence Development is now recognized as the term of art for such systems.

Second, the limitation on CMS to consider only whether a diagnostic or therapy is “reasonable and necessary” is largely restricted to hospital and physician services. Coverage of self-administered therapies, including some biologics, is determined by private sector insurance plans and additional state subsidies. These plans may supplement Medicare/Medicaid, be employer based, or be purely private, but all consider costs and many engage in HTA.

 For example, the TEC may be the most durable HTA program in the world;

 Washington State Health Authority operates an explicit HTA program;

 and the California Blue Shield Foundation has supported the California Technology Assessment Forum since 2003.

 More recently, a group of New England states (Maine, Massachusetts, Connecticut, New Hampshire, Vermont, and Rhode Island) established the Comparative Effectiveness Public Advisory Council (CEPAC) to support clinicians, patients, and policy makers in using comparative effectiveness information.

Third, the Patient Protection and Affordable Care Act (ACA)15 established the Patient- Centered Outcomes Research Institute (PCORI), a nonprofit corporation, to conduct comparative effectiveness research in a manner that does not discriminate on a number of grounds, including against the elderly and the disabled. PCORI provides the secretary of Health and Human Services with information to compare the effectiveness of treatments, and cost may be an “outcome” measure in the information as long as PCORI does not make recommendations based on cost per quality-adjusted life-year (QALY) thresholds. Entities such as CEPAC support clinicians, patients, and policy makers in using comparative effectiveness information.

The ACA has also influenced existing trends toward increased price sensitivity in health insurance.

 These trends include increased deductibles in many private insurance plans and declining prevalence of employer-based plans. Added to these are the ACA’s excise tax that targets generous employer-sponsored insurance plans, and the high cost-sharing rates in lower-premium plans offered on health insurance exchanges instituted by the ACA. With insurers now limited in denying coverage to those with pre-existing conditions, logic would suggest choosing the options of decreased coverage of expensive technologies and/or increased co-payment. The value of HTA and the innovative payment mechanisms developed under the Access with Evidence Development umbrella is that these provide evidence-based and tried-and-tested mechanisms for bearing down on technology costs.

Other initiatives target physicians to weigh the costs of care in their decisions.16 Both the American College of Cardiology and the American Heart Association have stated that they will integrate cost and value information in their guidelines, as has the American Society of Clinical Oncology. The guidelines will incorporate published evidence on the cost-effectiveness of interventions, increasing health price transparency. Finally, the ACA enables groups of providers of hospital and physician services, known as Accountable Care Organizations, to receive a share of efficiency gains if they meet quality performance standards.

In this reimbursement climate, breakthrough technologies such as Vertex Pharmaceutical’s Kalydeco for cystic fibrosis, approved by the FDA in 2012, and Gilead’s Sovaldi for hepatitis C infection, approved by the FDA in late 2013, are experiencing substantial pushback from payers, due to the prices their manufacturers wish to charge. The former is specific to only 4% of individuals with cystic fibrosis with a specific gene mutation, and costs $307,000 a year per patient, well above most reimbursement thresholds. The latter is priced at $84,000 for 12 weeks and $168,000 for 24 weeks of treatment. It is yet to be seen whether new hepatitis C treatments about to enter the market, and discussion of combination therapies, will drive down the price of this drug.

Thus, value assessment is an increasingly real and immediate component of the market access process in the United States, as it has been for many years in other developed countries. The necessary corollary is that value assessment becomes part of the clinical translation process.

The value-engineered translation (VET) framework was designed to evaluate translational candidate biotherapeutics for their potential to clear value-based reimbursement hurdles.

 It comprises 3 distinct steps along the translational continuum—headroom analysis, macro analyses, and micro analyses&mdash;as shown in Figure 1. It provides developers with information at specific points in the process to inform “go-no-go” and research prioritization decisions. For technologies that clear all 3 stages, the framework provides a reimbursement portfolio to incentivize investment in, and inform design of, costly phase 3 clinical trials. The portfolio is a starting point for designing the final evidence package to submit to HTA agencies for reimbursement decisions.

This discussion will focus on the first phase. It comprises a headroom assessment, which integrates considerations of the health and resource impacts of a candidate technology and whether social values might modify our assessments of those impacts. The second and third phases of the VET framework are based on the availability of more specific evidence and comprise increasingly sophisticated economic models to assess the likelihood of clearing market access hurdles, along with the value of alternative R&D investments and their impact on that likelihood.

Headroom analysis evaluates any unmet need for a candidate technology for a specific indication to support a price consistent with an acceptable return on the investment in clinical translation (Figure 2). In other words, it considers the scope for therapeutic or health system benefits of a technology relative to other existing technologies or those expected to be on the market at the time of product launch. This phase may commence as soon as a technology or indication dyad has been specified. It first assesses the maximum health gain that could be achieved if a new therapy restores the affected individual to his or her full health, with consideration for age and gender. However, if existing therapies are successful in restoring a patient’s health, then it will be very difficult for a new therapy to justify a premium price on the basis of health delivered.

Fortunately, in a value-based decision framework, improvements in the cost of care are also valued, as they reflect potential health gain for other people served by the health system. Thus, the second component of the headroom assessment considers whether the candidate technology could achieve savings elsewhere in the system that would be valued by the budget holders, as releasing resources to provide healthcare to others.

The final component of the headroom assessment contemplates whether the characteristics of the technology, the disease, or the affected population would modify the value of the health benefits or resource savings for the decision maker. For example, many jurisdictions incentivize technology development for rare/orphan diseases and for pediatric populations.

The assessment of headroom draws upon insights from clinical landscaping, which maps how the condition is currently managed in target healthcare systems, and technology landscaping, which draws upon patent, clinical trials, and trade and publications databases to identify potential competitor technologies likely to be on the market at the expected time of product launch. The former assessment specifies current headroom and the latter determines the likely headroom at the time of market access. Combined, these analyses determine whether the technology is likely to be a first to market, a fast follower, or a me-too, all of which would influence the ability of a developer to command a premium price.

The final component of the headroom assessment combines the methods of evidence synthesis and Bayesian expert elicitation. It examines the preclinical and early clinical data for evidence of publication bias, which forms the basis for adjusting expectations about the scope of the new technology for “over-confidence” bias.

Why Should Health Technology Developers Consider Headroom?

Here, we present retrospective and prospective examples of how early analysis of headroom may aid in decisions along a translational continuum. The first example illustrates the need for analysis of future market prospects—technologies may fail close to clinical adoption if the expected health benefit shrinks at the time of market entry. Vitravene (fomivirsen), an antisense therapy developed at the National Institutes of Health and licensed by Isis Pharmaceuticals, Inc, was approved by the FDA in August 1998 to treat cytomegalovirus retinitis (CMV-R). During its development in the 1990s, AIDS had transformed CMV-R from a rare disease into one of the most common ocular infections in the United States. When approved for use, Vitravene was a biomedical breakthrough as the first FDA-approved antisense therapy. While Vitravene was in phase 3 clinical trials, Highly Active Anti-retroviral Therapy (HAART) regimen, the “3-drug cocktail”, was developed to suppress HIV replication and allow the immune system to recover. As a consequence, the number of new cases of CMV-R declined by nearly 75%. When Vitravene reached the market, distributed by Novartis Ophthalmics AG, HAART had been standard therapy for about a year. New cases of CMV-R were less common, and many existing cases no longer needed treatment; in other words, the health crisis that Vitravene was designed to address had receded and sales of the product were much lower than predicted. As a result, Novartis no longer markets Vitravene, but Isis Pharmaceuticals still cites Vitravene as evidence of its “ability to meet FDA and European regulatory requirements for safety and efficacy, and for the commercial manufacture of antisense drugs.”

The second example illustrates that delays in evidence development for regulatory approval and legal rights may lead to a loss of headroom if they enable a competitor to enter the market, making a therapy a fast-follower rather than a first-in-class. In 2008, Abbott Laboratories (now AbbVie) began marketing an anti-TNF-alpha human monoclonal antibody, Humira, as a therapeutic for anti-inflammatory disease, including psoriasis. The antibody was derived from a phage display library obtained from Cambridge Antibody Technology (CAT).

 Abbott disputed the royalty payments to CAT on products it developed from antibodies it had licensed. Abbott lost the court case in 2004, resulting in royalty payments to CAT of 5% instead of 2% on net sales.

 At the same time, Abbott was developing another anti-inflammatory therapeutic, anti-IL-12/23 human monoclonal, briakinumab, also obtained from CAT. Despite Abbott’s positive phase 3 results in 2009 for treating psoriasis, the FDA demanded additional data.23 Later that year, Centorcor Ortho Biotech Inc (now Janssen Biotech) received FDA approval for its anti-IL12/23 monoclonal StelaraTM (ustekinumab).

 In 2011, Abbott announced it had withdrawn its application with the FDA and the European Medicines Agency for briakinumab, partly because of a competitor and in part to avoid competing with its existing market for Humira.

The example of 2 FDA-approved recombinant Lyme disease vaccines from the late 1990s illustrates the potential negative impact of social values on headroom for a technology. While social values can lead decision makers to approve technologies that would otherwise not be considered cost-effective, they can also produce a contrary effect. In 1998, FDA approved SmithKlineBeecham’s (now GlaxoSmithKline’s) LYMErix. Pasteur Merieux Connaught (now Sanofi) conducted phase 3 trials of its vaccine ImuLyme at the same time, but never applied for FDA approval. LYMErix trials demonstrated only 76% efficacy and required 3 doses. Additionally, it was approved for a restricted population: persons aged 15 to 70 years who lived in endemic areas and who engaged in activities with frequent exposure to ticks. After 1 year on the market, reports of adverse events began to appear and the media covered stories about “vaccine victims.” A class action lawsuit was filed against the company. While the FDA did not find a higher rate of adverse reactions among a small group who received the vaccine, some studies suggested HLA DR4+ patients who received the vaccine might be at a higher risk for developing chronic treatment-resistant arthritis. The FDA convened a public meeting in 2001 to discuss the risks and benefits of the vaccine. After a highly contentious discussion, the FDA made no changes to the use and labeling of the vaccine, but required the manufacturer to provide data from a phase 4 (postmarketing) trial. With all the negative publicity, sales fell off and GlaxoSmithKline withdrew the vaccine from the market in 2002.

Our work with the regenerative medicine community is leading to greater awareness of cost-effective development of related technologies.

 Two current examples in regenerative medicine are Osiris Therapeutics Inc’s Prochymal, a stem cell therapy to treat steroid-refractory graft-versus-host-disease (GVHD), which was the first off-the-shelf regenerative medicine therapy to gain regulatory approval in Canada in 2012. The conditional approval, requiring ongoing collection of evidence, was only for children with the rare condition. No provincial health plan in Canada has approved reimbursement for the therapy—evidence that regulatory approval is no longer equivalent to market access.

The FDA approved Dendreon Corporation’s Provenge (sipuleucel-T) in 2010 as an autologous cellular immunotherapy for the treatment of asymptomatic or minimally symptomatic metastatic castrate resistant (hormone refractory) prostate cancer. However, Provenge has struggled since its approval due to its administration procedure and the cost. Physicians balk at the $93,000 cost of a course of therapy for an expected 4 month survival benefit for prostate cancer patients. Research found that 57% of physicians indicated a maximum price of $30,000 for this scale of benefit.

 Physicians were concerned with the ability of patients to pay or copay for expensive therapies, the need for preauthorization from insurance companies, and the minimal benefit to patients. At the time Dendreon sought FDA approval, Provenge was a first-in-class immunotherapy. However, the FDA required further evidence of efficacy, which delayed the launch. Now Provenge struggles for market share against rival drugs: Xtandi, from Astellas and Medivation and Zytiga from Johnson & Johnson. The company’s share price and workforce now reflect its decline in fortunes.

From a prospective standpoint, the key lesson for health technology developers is that reimbursement considerations influence all markets. An HTA framework that starts with an analysis of available headroom is valuable from an R&D investment standpoint only when supported by further economic modeling, as the evidence of safety and efficacy mount. For example, a simple plot of disease burden (patient population and potential health impact of the technology) plotted against existing and prospective technologies, is a valuable basis for R&D investments, from both funding and research career perspectives. For example, the headroom for an expensive stem cell therapy for myocardial infarction—with limited benefits for patient survival and quality of life compared to a plethora of existing technologies&mdash;is low when compared with an expensive stem cell therapy for severe sepsis or a treatment for triple-negative breast cancer, which present an increased health gain, especially when alternative therapies are lacking.

In conclusion, it is imperative for stakeholders in translational research—whether funding agencies that invest public moneys in health R&D, researchers who invest their careers, or industry that brings products to market&mdash;to consider uncertainties in clearing increasingly high reimbursement hurdles. A well-structured HTA does not lead to certainty in a changing environment, but it identifies risk factors and promotes investment in technologies with a high likelihood of successful clinical adoption and reimbursement.

 The authors thank Mark Rohrbaugh, PhD, JD, director, Office of Technology Transfer, NIH, for contributing a few case studies of technology discussed in the manuscript and for his comments on the manuscript. The views expressed, however, represent only those of the authors. The authors also thank W. Luth, School of Public Health, University of Alberta, for editing the article.

 Concept and design (TB, CM); drafting of the manuscript (TB, CM); critical revision of the manuscript for important intellectual content (TB, CM); administrative, technical, or logistic support (TB, CM).

 Tania Bubela, PhD, JD, and Christopher McCabe, PhD, report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 This project was supported by the Canadian Stem Cell Network and the PACEOMICS project, funded by Genome Canada, Genome Quebec, Alberta Innovates-Health Solutions and the Canadian Institute for Health Research (CIHR). CM holds the Capital Health Endowed Research Chair in Emergency Medicine Research and TB a McCalla Professorship at the University of Alberta.

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Value-Engineered Translation: Developing Biotherapeutics That Align With Health-System Needs

The enhanced focus on patient outcomes and value for ACOs in general will mean that pharmaceutical companies will have to reshape their relationships with ACOs along these lines. Refocusing these relationships around value will require (1) collaborative measurement of patient outcomes; (2) new commercial models that enable value-based payment; and (3) a broadening of the relationship to develop solutions and services that enhance outcomes independent of the pharmaceutical companies’ products. It is this latter requirement that prompted Merck & Co, Inc, a global pharmaceutical company, and the Heritage Provider Network, Inc (HPN), a Southern California based managed care organization with affiliates in Arizona and New York, and the largest of the Pioneer Model ACOs, to engage in a collaborative process to identify novel solutions in disease areas of considerable shared epidemiological interest: diabetes and heart disease.

During the fall of 2013, Merck and HPN launched an open innovation challenge around care plan adherence for patients with diabetes and heart disease. To our knowledge, this is the first collaboration between a pharmaceutical company and an ACO. This article describes this collaboration, the innovation process, and implications for further collaborations between ACOs and other healthcare stakeholders.

As we transition to a clinically integrated system that incentivizes quality and better health outcomes, care plans are critical patient engagement tools that will be invaluable in helping patients

become informed and educated. Care plans serve as road maps for patients, because they outline diagnosis and treatment, schedules for followup, and vital information and resources

postvisit. Additionally, they serve as a lifeline, allowing providers to monitor their patients and ensure coordination among the healthcare team. But there are significant challenges associated

with creating and delivering successful care plans between the provider and the patient. More than 40% of patients misunderstand, misinterpret, forget, or ignore healthcare advice given by their

 Factors associated with patient compliance to provider-recommended care plans include patients’ knowledge and understanding of treatment and effective communication between

HPN has a long history of providing coordinated care, and both Merck and HPN realized that adherence to care plans for patients with chronic diseases is an underutilized lever for improving

a patient’s quality of life, while also potentially creating cost reductions in healthcare. Together, leadership from the 2 organizations decided to use an open innovation process to identify

and incubate ideas that would advance shared aims around improving adherence to care plans for patients with these conditions.

Many sectors have looked to “the wisdom of the crowd” or the phenomenon that the collective knowledge of the community is greater than the knowledge of the individual

solutions to complicated problems. The use of challenge competitions and an open innovation process to drive breakthrough results has a very long history, going back hundreds of years.

 For example, Charles Lindbergh’s flight across the Atlantic can be traced back to a challenge famously titled The Orteig Prize, a $25,000 reward offered to the first aviator to fly nonstop from New York City to Paris. While this mechanism has been well defined in other sectors, it is relatively new to the healthcare services arena.

Challenge-based competitions have proved to be successful frameworks for addressing fundamental research questions by presenting difficult problems and data to the community and enabling the open exchange of ideas and methodologies. Merck and HPN quickly realized that the long-standing problem of treating chronic diseases could benefit from a community approach, and as a result, the 2 organizations collaborated on devising an open innovation challenge competition that aimed to source and incorporate novel care plan products or services to support providers and patients in the area of chronic disease management.

 (HPN has sponsored a number of other prizes, including prizes related to hospitalization prediction and cancer cell networks, but this is the first nondata, nontechnology challenge in which HPN has participated.) Merck and HPN’s aim was to apply the best practices of open innovation to identify novel solutions for managing patients with chronic diseases. There has been some experimental research indicating that traditional approaches like “winner-take-all” prizes are suboptimal

 We therefore opted for a staged process, with the opportunity for multiple prizes across teams.

 Additionally, other inno-vation processes, such as lean methodology and design thinking, were embedded into the structure of the challenge. Drawing on established principles for open innovation challenges, Merck and HPN designed an innovation challenge with several phases.

Outreach is essential for open innovation challenges. Merck and HPN partnered closely with Luminary Labs, an innovation and strategy consultancy, for the operational components of this challenge, and to ensure that the right community of solvers was involved. Following announcement of the challenge, there was a 1-month open call to the public for submissions. To spread awareness of the challenge and ensure that there would be broad outreach, Luminary Labs notified key media outlets in technology, big data, and healthcare.

Overall, 90 teams submitted solutions for consideration. These submissions spanned from initial concepts to fully mature products or services: 17 in the idea phase, 33 in the early prototype phase, 14 in the full prototype phase, 14 in the beta phase, and 12 that were publicly available. Concepts included hardware, stand-alone care planning solutions, communications platforms, and comprehensive integrated care systems. Eighty-four percent (84%) of submitted solutions were patient-facing; the remaining submissions aimed at multiple segments of the ecosystem. With over 17,000 visits to the challenge website, there was wide-ranging interest and geographic reach. Visitors drew from academic, government, and private-sector spheres that included the Broad Institute, the Bill and Melinda Gates Foundation, Facebook, the Centers for Disease Control and Prevention, and the White House.

Virtual Accelerator and Finalist Selection

An independent panel of judges from the healthcare, innovation, development, and design communities selected 5 teams to proceed on to the virtual accelerator process. Submissions were then evaluated on several dimensions.

The 5 semifinalist teams were composed of clinicians, scientists, patient-entrepreneurs, media producers, and technologists, and the solutions ranged from early prototype to established startup. Accelerators are designed to support .the successful development of entrepreneurial companies and are aimed at increasing the likelihood of success for those companies and iterating their concepts. The 5 semifinalists took part in rigorous design, prototyping, and business modeling sessions tailored to the strengths and weaknesses of each team. The virtual accelerator process consisted of 3 core modeling sessions.

Modeling session 1 focused on an introduction to design thinking also on need-based solution development. These exercises functioned as primers on cultivating empathy, end-user focus, and rapid prototyping. The semifinalists were also exposed to interview-based ethnography, where they simulated exercises in patient engagement and were asked to reconsider care coordination from new angles. The sessions were designed with the patient in mind—and more specifically, how entrepreneurial companies can refocus their solutions to ensure that patient and provider needs are met.

Modeling Session 2 commenced with a stronger emphasis on patient interaction and learning how to complement technology with disease self-management. Semifinalists met with 2 panels of patients living with diabetes and/or heart disease, and gained insights by simulating the complex experience of learning to live with chronic disease from the perspective of a patient and of a caregiver. Clinicians provided their observations from the field, noting best practices and pain points regarding increasing adherence and patient engagement to improve health outcomes.

Modeling Session 3 gave semifinalists the opportunity to access experts in different fields, ranging from business modeling and capital acquisition to design and public speaking. Teams from industry experts and continually crafted their solutions to focus on the problem at hand.

Several insights have emerged from this collaboration. First, by placing a dedicated focus on the challenge announcement and community outreach, Merck and HPN were able to develop a landscape view of the marketplace for care plan adherence solutions. The process also gave both parties proximity to the innovator community, opening up a new opportunity for identifying and harvesting talent from a diverse group of forward thinkers offering fresh ideas and a unique perspective. Second, Merck and HPN were able to successfully source solutions that proactively engage patients to promote lifestyle changes around healthy behaviors and medication management, as well as bridge the communication and coordination gap between patients and providers. This collaboration initiative serves as a model for engaging entrepreneurs and key health stakeholders to work across the care continuum.

As we move toward an increased focus on patient engagement, there is an opportunity for organizations to create dynamic and effective programs that facilitate the exchange of information. Shifting to new models will require an increased focus on identifying clinical gaps to uncover every opportunity and implement patient-centric care plans.

Open innovation, while common in other industries, is still relatively new to the healthcare field. This approach provides a pathway for collaboration, rapid identification of solutions, and access to the broader marketplace. The aim of both Merck and HPN was to apply the best practices of open innovation to identify novel solutions for managing patients with chronic diseases. The quality and quantity of submissions showed notable interest from entrepreneurs to data scientists to clinicians and provided a diverse set of solutions. The challenge allowed both Merck and HPN to look beyond their own walls and gain access to non-traditional partners and products. Additionally, this first-of-its-kind pharmaceutical-ACO collaboration demonstrated how challenge competitions can set in motion communities of innovators to develop sophisticated tools for care management, lay the groundwork for future collaboration, and offer a mechanism for stakeholders like Merck and HPN to collaborate.

 Merck & Co, Whitehouse Station, NJ (AB, AC, SHJ); Luminary Labs, New York, NY (SH); Harvard Medical School, Boston, MA (BP, SHJ); Heritage Provider Network, Inc, Northridge, CA (JG); Boston-VA Medical Center, Boston, MA (SHJ).

 Sachin H. Jain, MD, MBA, 33 Avenue Louis Pasteur, 2-403, Boston, MA 02110. E-mail: sachin.jain@merck.com.

Accountable care is forcing providers to develop new capacities and strategies for managing cost and quality trends. Prospectively managing the health of populations requires shifting the focus of care delivery from episodic interventions to continuous population management. As a result, accountable care organizations (ACOs) are dedicating considerable focus to developing the infrastructure and tools needed to help patients manage their chronic conditions. This is a significant departure from traditional care-delivery models and will require provider organizations to develop new partnerships and embrace new methods.

July 2014

Integrated Treatment for Diabetes, Depression Gains Notice, With Help from ACA

Aging and Cognitive Decline in Diabetes

Value-Engineered Translation: Developing Biotherapeutics That Align With Health-System Needs

A Novel Pharmaceutical-ACO Collaboration: the Merck/Heritage Provider Network Open Innovation Challenge

Challenge Winner Sees Promise in Daily App Check

Pharma-Payer Partnerships Seek to Prove Effectiveness of Care

Can Gastric Bypass Surgery Be a Cure for Diabetes Mellitus?

Environmental Pollutants: A Risk Factor for Obesity and Diabetes

Early Cellular Aging: Salt and the Telomeres

AJMC Peer Exchange: Nationwide, Patient-Centered Strategy Needed to Battle Obesity, T2DM

Benefits, Risks of SGLT2 Inhibitors Explored at Session

Can Early Use of Insulin, GLP-1 Halt Diabetes Progression?

Sessions Highlight Strides in

Results Presented on Motivating Patients With Diabetes

Diabetes Navigator Program Reduces A1C Levels for Patients in Alabama

Afrezza, Inhaled Insulin, Wins FDA Approval