The next imperatives for US healthcare
Two steps—increasing healthcare-sector productivity and improving healthcare-market functioning to better balance the supply of and demand for health services—would likely produce sufficient savings to lower medical cost inflation to the rate of GDP growth.
Since 2010, the US uninsured rate has dropped from 17% to 11% of the population.1 Some of the new episode- and population-based payment models are achieving savings,2 and some categories of healthcare utilization have declined.3 However, medical inflation still rises faster than GDP growth. There is little transparency into pricing, and, in many regions, the price dispersion for similar services exceeds 100%. All too frequently, the correlation between cost and quality is weak. Regulatory constraints often inhibit much-needed innovations. The health status of the population remains below that of most other peer countries.
Moreover, the average healthcare consumer now faces far greater financial exposure to medical costs. Between 2010 and 2015, employees’ contributions to health insurance grew almost three times faster than wages.4 Middle-class Americans are feeling this burden the most—their healthcare spending as a percentage of household income has increased 60% over the past 30 years, and their healthcare costs are now almost half of a typical mortgage payment.5
In other words, the US healthcare system is delivering less (through declining utilization) for more (higher spending), a phenomenon that runs counter to basic economic principles.
Within this context, there are three imperatives for improving the US health system’s financial sustainability and value it delivers:
- Achieve rapid—and dramatic—productivity improvements in the delivery of health services
- Improve the functioning of healthcare markets
- Improve population health
The third imperative may arguably be the most important for long-term sustainability, but it requires tackling social determinants of health (e.g., inadequate housing, food insecurity) and changing many people’s attitudes about responsibility for their health,6 factors largely outside the scope of health services companies, including insurers and providers. However, these organizations can and should take the lead on the first two imperatives, and thus our emphasis in this article is on them.
Our conservative estimates suggest that addressing these two imperatives through broad adoption of best practices could lower national healthcare expenditures by a minimum of $284 billion to $532 billion per year and reduce the annual growth of those expenditures by about 30%.7 Achieving a reduction of this magnitude will not be easy, but the impact would be significant—medical cost inflation would likely fall and be roughly equivalent to GDP growth,8 and the financial stress on individual Americans would be reduced. In addition, innovation beyond current best practices and the application of digital technologies have the potential to deliver substantially greater improvement.
Achieve productivity improvements
Productivity improvements are the lifeblood of any industry, enabling them to deliver better products and services while reducing or carefully controlling prices. In the past few decades, for example, innovation enabled manufacturers to drop the average prices of laptop computers and cell phones by a substantial amount (Exhibit 1).9 In both cases, the sharp drops in price occurred despite dramatic technological advances that gave consumers significantly enhanced functionality.
Productivity improvements have also helped a wide range of other industries—from airlines to wealth management services—lower prices. Between 2001 and 2014, for example, the average fee for wealth management advisory services decreased 13%.10 If the healthcare industry had been able to achieve comparable productivity improvements, prices for consumers would often be much lower, while payors and providers would be able to maintain wages and margins. For example, if health insurerance premiums had followed the same trajectory that wealth management advisory fees did between 2001 and 2014, the average annual premium for a family of four would have been $6,155, instead of $16,834, in 2014. In reality, very few areas in healthcare have seen costs decrease to any real degree.11 Innovation in healthcare has created a range of new treatments, services, and technologies, but often at high prices not always commensurate with the benefits delivered.
In short, healthcare innovation has not led to the types of productivity improvements that have enabled other industries to deliver “more for less.” Between 1999 and 2014, labor productivity (defined as real value added per worker) increased by only 6% in healthcare—but by 18% in other service industries and 78% in manufacturing.12 In most years during this period, productivity in the healthcare industry actually declined at the national level. Only in 2008 did the industry experience a comparatively large (2.9%) year-on-year increase in productivity. (The slowdown in hiring during the Great Recession may have led to a temporary boost as output grew faster than employment in the sector. Our experience suggests that in some regions of the country, 2008 was the only year between 1999 and 2014 that saw an increase in healthcare productivity.)
Calculating productivity changes in healthcare requires agreement on how the intended “output” should be defined and how the underlying costs needed to produce it are measured—two formidable yet surmountable obstacles.13 Thus, comparisons of productivity gains between healthcare and other industries are inexact. Nevertheless, our experience indicates that healthcare is far behind other industries—and indeed its own potential. Healthcare organizations that develop the ability to define and measure both their target output and associated costs will likely have a distinct advantage over competitors, because these are the first steps to improving value for consumers while minimizing costs.
If healthcare productivity is to rise—even if only to the level achieved by other service industries—two things need to happen: both payors and providers need to radically alter their business models, and we, as a society, will want to consider adopting “smart” regulations.
Business model changes
Too often today, healthcare delivery is based on outdated approaches that rely heavily on overly expensive labor and care venues. Alternative approaches are possible, though. For example, ambulatory surgery centers (ASCs) have radically redesigned the provider business model for operations by using a smaller capital footprint, better asset utilization, and higher labor productivity. ASCs capitalize on the fact that when surgeons and facilities perform a high volume of specific procedures, care quality improves and productivity increases. ASCs have prices that are, in many cases, close to half those at most health systems,14 and for consumers, the benefit is clear: more for less.
Diagnostic laboratory chains, retail health clinics, and dialysis companies offer other examples of how the provider business model can be redesigned. We have found, for example, that the lab chains are able to provide most tests at about half of what a typical hospital charges. (We recognize that some of this variation is a result of differences in the complexity of the diagnostics.) They do so by offering consumers convenient, local collection centers and by shipping the samples to much larger centers for analysis. The larger centers gain the benefit of scale and are better able to balance fluctuations in demand, thereby enabling not only better labor capacity utilization but also more efficient use of capital.15 There is no reason to believe other new entrants will not find ways to offer other traditional hospital services in outpatient settings—at a much more attractive price point and, potentially, with increased convenience for consumers.
The provider business model can also be radically redesigned without abandoning the hospital footprint. In India, the Narayana Health System uses what has been described in news stories as a “Walmart-like” approach, based on heavy use of technology, to continuously improve its cost management and efficiency without jeopardizing patient care.16 For example, it has standardized its procedures and schedules operations to ensure its surgical suites—and surgical teams—are maximally utilized. The result: excellent outcomes at a price only one-third of that charged by other Indian hospitals. A new entrant introducing a “Walmart-like” approach in the United States could disrupt the provider landscape.
Payors also should consider redesigning their business models. By fully digitizing the consumer decision journey, payors can significantly decrease their administrative costs and, by association, their premiums. Our analyses have shown, for example, that the average cost to payors for an individual-market member acquisition is $125 through online sales, but $500 through traditional sales channels. In addition, digitization can lower back-office costs for account and membership administration by more than 20%. Digitizing claims processing also makes possible the advanced analytics that can significantly reduce fraud and abuse rates.
Payors could also build on the broader market migration toward value-based payment as a way to aggressively shift medical management activities to providers that accept risk-based arrangements. Rather than offering disease management, case management, or wellness programs themselves, payors could use value-based contracting to encourage providers to deliver these programs. This move could potentially cut payors’ medical management-driven administrative spending almost in half.
Payors and providers could take other steps that hold the promise of significantly improving productivity. For example, transaction costs could be lowered by streamlining quality reporting or by redesigning the claims and payment transaction system to a “hub-and-spoke” model, with large-scale clearinghouse utilities similar to those used by credit card companies or in financial securities settlements. Artificial intelligence could improve the speed and accuracy of diagnosis. Other new technologies (e.g., at-home remote monitoring, online physician consultations) could reduce the need for in-person medical care.17,18 However, empirical evidence is not yet sufficient to establish the savings these technologies might achieve, and thus we did not include them in our calculations of financial impact.
Making the needed changes to improve productivity is not easy, especially for providers, given their fixed assets and labor force restrictions. Change is possible, though—and necessary. The incumbents first to achieve significant productivity gains will create a material competitive advantage for themselves through growth and margin. They will also be better positioned to defend themselves against attackers.
Although regulations serve an important role in ensuring patient protection and safety, many current regulations are outdated, unclear, or inconsistent. Stark and anti-kickback laws have slowed the spread of some payment and delivery innovations—for example, the Department of Health and Human Services (DHHS) issued waivers for some new payment models, but excluded commercial models.19 At times, the payment and delivery innovations encouraged by DHHS and the Centers for Medicare and Medicaid Services have run afoul of Internal Revenue Service regulations.20 State laws and federal policies governing telehealth services vary on such points as where the services can be delivered, what types of clinicians can deliver the services, and where the clinicians must be licensed.21 The regulations specifying what services nurse practitioners and other ancillary clinicians can offer without direct physician supervision differ widely across states.22
Outdated, unclear, or inconsistent regulations such as these can, at times, inhibit innovation, and in many cases it may be possible to streamline them or replace them with “smart” regulations that stimulate productivity improvements while protecting patient safety, fostering competition, and achieving equity aims.23 Smart regulations use enforceable standards to achieve desired goals, but carefully balance those goals against the cost of compliance and permit a degree of flexibility that enables innovation. Smart regulations can also be used to establish enabling mechanisms that would not be feasible for an individual organization to develop (e.g., the creation of data standards and requirements for easy interchange of data across organizations24).
Improve Market functioning
In well-functioning markets, demand-side and supply-side incentives are balanced. Think again of consumer electronics: the combination of engaged consumers making informed choices and a competitive market of providers has led to a steady stream of product innovations and frequent price reductions. However, balanced incentives are rare in healthcare. Instead, misaligned incentives—between patients and providers, providers and payors, and among different providers—all too often result in increased costs without any related benefit to consumers.
On their own, both demand-side and supply-side incentives can be effective in healthcare. Considerable evidence shows, for example, that utilization decreases when consumers pay more out of pocket. Even a 10% increase in consumers’ share of costs (a 10% reduction in actuarial value) decreases utilization by 15% (Exhibit 2). Similarly, the pressure of engaged consumers paying full costs in a price-transparent market has led to declining prices for elective procedures, in some cases by double digits (Exhibit 3).
Episodes payments and other bundled payment approaches that reward providers for outcomes rather than volume have also been shown to lower prices and reduce the delivery of unnecessary services, including emergency room visits and excessively long hospital stays.25 The State of Arkansas, for example, launched episode payment for attention deficit/hyperactivity disorder and found that the average episode cost fell by 29% in the first year. It also saw reductions in average episode cost for other conditions, although in a few cases its spending remained flat.26 Another payor has found that the use of episode payments for hip replacements significantly decreased the average cost of that procedure while substantially reducing the postsurgical readmission rate.27
However, both demand-side and supply-side incentives have limitations. When cost-sharing levels are high, some consumers may opt to forego appropriate care. Yet in the absence of consumer cost sharing, attempts to reduce the over-delivery of services may have little impact.
Our experience suggests that the best way to balance the two sets of incentives at scale is to take the level and nature of medical risk into consideration.28 Simply put, medical problems vary in severity and frequency, the number of times treatment will be needed (acute vs. chronic care), and the extent to which consumers can both control the services received and absorb the cost of those services. (For a fuller explanation of medical risk, see the sidebar below.)
Understanding medical risk
The fundamental nature of medical risk in the United States has changed over the past few decades. In most cases, medical risk no longer results from random, infrequent events driven by accidents, genetic predisposition, or contagious disease but from chronic conditions related to behavioral, environmental, or other factors. Treating chronic conditions, and the serious medical events they commonly induce, now costs more than treating the random, catastrophic events that health insurance was originally designed to cover.
Although our country’s approach to health insurance—and to paying for healthcare more generally—is changing, it has still not sufficiently adapted to the change in medical risk. As a consequence, consumers still have little incentive to forego unnecessary, inexpensive services yet are ill protected from the cost of very expensive care. The incentives for providers are only starting to change to encourage them to deliver preventive services and discourage them from offering unnecessary or poor-quality care.
Medical risk is not uniform, however. We analyzed US healthcare spending and broke it down into separate risk categories, each of which has unique characteristics.1 We then matched the incentives offered to consumers and providers to the characteristics of each category.
How we did the analysis
Our analysis looked at total annual US healthcare spending (excluding government administrative expenses, private insurers’ profits, research expenses, and the cost of equipment, software, and public health activities). We evaluated expenditures using four major factors:
Severity. The magnitude of the medical expense to treat a specific condition.
Frequency. How often the condition occurs.
Level of consumer discretion. The degree to which consumers can control costs.
Temporal dependency. The amount of time a patient is likely to be afflicted with the condition.
We then considered a number of other issues. For example, we reviewed evidence-based guidelines and evaluated the inherent value of preventive medicine. In addition, we investigated the primary mechanisms used to pay for services delivered:
Out-of-pocket. Expenses paid by consumers other than insurance premium payments (e.g., copays, coinsurance, and deductibles).
Insurance. Expenses covered by individual insurance, government insurance, and employer-sponsored insurance (including the employee portion of premiums).
Subsidies. Expenses covered by federal and state subsidy programs (e.g., Medicaid and the State Children’s Health Insurance Program), as well as charity care.
What we found
The analysis yielded the eight categories of medical risk shown in Exhibits 4 and 5. When we looked at how each of these categories was primarily paid for, we discovered there was often a disconnect between the value the services provided and where the funding came from. For example, insurance often covered a greater proportion of the costs of discretionary care than of preventive care. Similarly, we found a disconnect between the share of costs consumers were expected to pay and their ability to influence the need for that care. (Consumers were often responsible for more of the cost of uncontrollable catastrophic events than of catastrophic events related to chronic disease.) And we saw little or no relationship between the amount consumers were expected to pay in each category and their ability to absorb those costs.
Our findings led us to believe that a one-size-fits-all approach to either consumer cost-sharing or payment innovation will not be effective in controlling healthcare costs or improving care quality. Only by matching the extent of cost sharing and the primary reimbursement mechanism to the characteristics of each category of medical risk will it be possible to achieve those goals.
Admittedly, the approach outlined here is somewhat simplified. Patients are not homogenous, and what is an appropriate treatment for one patient may be discretionary or even inappropriate for another. Thus, models designed to encourage high-value care and discourage low-value care through variable cost sharing must be more nuanced to take these differences into account. Payors should rely on clinical evidence when developing smart cost sharing models to move beyond blunt instruments such as high deductibles and uniform copayments or coinsurance rates. And they should re-examine the models periodically to minimize the risk that either patients or providers can game the results.
1. Singhal S, Pellathy T, Adigozel O. Why understanding medical risk is the key to US health reform. McKinsey Quarterly. June 2009.
Each category of medical risk has a potentially optimal financing and reimbursement approach. Compare, for example, preventive services and routine outpatient care for mild conditions, such as influenza in adults (Exhibit 4). In both cases, consumers have considerable discretion over which services they receive and can generally afford to absorb the expense. However, many preventive services reduce the long-term cost of care and thus should be offered free or near-free, as is currently done in plans offered through the public exchanges. In contrast, outpatient care for mild conditions is frequently unnecessary; having consumers bear the full cost of such care would lower utilization rates and/or encourage the growth of lower-cost, more convenient sites of care (e.g., retail clinics). Discretionary procedures (e.g., back surgery when not clinically necessary) are also candidates for full cost sharing.
Catastrophic care falls squarely within the intent of insurance, given that most consumers have little ability to absorb the total costs. However, coverage details should depend on whether the need for care results from a chronic condition that is within a patient’s ability to control. Low cost sharing makes sense when it does not (e.g., accidents, unexpected cardiac events). For catastrophic events resulting from controllable chronic conditions, cost-sharing levels should be higher, but patients should be offered incentives to improve their management of those conditions. In other words, the level of cost sharing should vary based on how well patients engage and take responsibility to manage their conditions.29
Under this model of “smart cost sharing,” subsidies may be needed to help lower-income individuals afford appropriate routine and elective care. Furthermore, this redefinition of covered benefits does not match most people’s current conception of health insurance, and it is not fully consistent with existing mandatory or essential health benefits. Employers and payors would need to work through mandated benefits requirements, depending on the applicable federal and state regulations. However, the impact of adopting this approach could be profound. Our research has shown that almost 30% of the medical costs covered by commercial plans result from routine, discretionary, or purely elective care (Exhibit 5). If a payor curtailed coverage for these types of care, the premium reductions it could pass on to consumers could be significant (Exhibit 6).
Furthermore, if the cost of routine, discretionary, and purely elective care were transferred to consumers, utilization of that care would likely decrease substantially or be shifted to lower-cost, more convenient sites of care. This would lower overall healthcare spending. Payors could achieve additional cost savings through innovation around narrowed networks, chronic care management, and bundled payment models. For example, by using bundled payments to cover catastrophic and end-of-life care, payors would protect consumers from the extremely high costs associated with those types of care while discouraging providers from delivering unnecessary services. In addition, payors could design population health models to ensure that providers are well rewarded for delivering appropriate preventive services and thereby reducing future costs.
Some providers could also benefit from this redefinition of health insurance coverage. Productive providers, for example, could gain market share by offering consumers more attractive pricing, added convenience, and perhaps higher-end amenities, for routine, discretionary, and elective care. In addition, the providers could partner with payors on outcomes-based payment models for catastrophic and chronic care to earn higher revenues and margins for their more efficient, lower-cost care.
For this redefinition of insurance coverage to succeed, however, certain supportive elements must be in place. Consumers must have effective mechanisms to help them absorb the costs—health savings accounts do not yet meet this standard. Consumers would also need tools to help them understand the benefits and risks of the types of care they are considering, and to enable them to compare quality and prices at different providers. Transparency tools have a long way to go, but evidence is already emerging that when consumers do have access to cost data, they use it. For example, a high proportion of consumers on the public exchanges are comparison shopping for insurance coverage, with many purchasing lower-priced plans.30
Our economic analyses are based on the assumption that the current best practices we have observed among certain players could be applied in the industry more broadly—a change that may not be easy to accomplish in an industry as entrenched as healthcare, but is also not impossible. For example, if all providers were to follow best practices, they could achieve savings of 9% to 16%, our analyses indicate (Exhibit 7). These conservative estimates suggest that improving healthcare productivity and market functioning has the potential to substantially reduce near-term spending and slow medical cost inflation. We estimate, for example, that initiatives targeting productivity and market distortions could achieve a savings of $284 billion to $532 billion over the course of the next ten years (Exhibit 8).31 Achieving these savings equates to a 30% decrease in the average annual increase in national health expenditures. Such a decrease could bring medical cost inflation to about the rate of GDP growth for the next several years—something that has not happened in more than half a century.32
The actual impact could be much higher, however. Our analyses did not take into account a range of forward-looking levers, such as regulatory reforms, simplified quality reporting, fraud/abuse reductions, and digital technologies. Yet these levers have the potential to produce considerable savings. Remote monitoring, as one example, could eventually lower the cost of delivering primary care services by $25 billion to $40 billion annually.33
In sum, the near-term, practical opportunity for reducing healthcare costs presents the possibility that medical cost inflation could be lowered to match GDP growth. Over the longer term, the added potential innovation could make possible would enable the healthcare industry to continually deliver “more for less.”
Implications for incumbents
The healthcare industry is ripe for disruption, and incumbents must be prepared to respond. New entrants have already demonstrated the effectiveness of radically rethinking healthcare business models, and there is no reason to think others will not follow. Incumbents that want to avoid being overtaken by these new entrants must pivot quickly to act like attackers themselves (as Charles Schwab did following the advent of online brokerages—it was able to stave off attackers and maintain margins by radically lowering its prices, introducing online trading, and improving customer support).
As payors and providers rethink their business models, improving productivity drastically and quickly must be uppermost in their minds. The first incumbents that can do this will gain a significant competitive advantage. Thus, radical new ideas should be strongly considered—minor tweaks will not be sufficient in a world where an Amazon- or Walmart-like attacker could materialize.
Some of the changes payors and providers need to make are quite different. Payors, for example, should focus not just on back-office services but also on front-office operations. As we have noted, digital sales are significantly less expensive than traditional sales. Providers could start with supply chain optimization and better clinical workforce management, but they should not forget the other levers available to them. Both groups should be aggressive in their efforts—in our experience, many of them do not pull these levers hard enough.
There is also a real opportunity for collaboration between payors and providers to reduce complexity, and increase transparency and the use of payment for value. In addition, incumbents could collaborate with appropriate public agencies to update the regulatory framework. Smart regulations can ensure that both consumers and medical standards remain protected while enabling the innovations needed to increase productivity and improve market functioning. Collaboration between payors, providers, and public agencies could also help rebalance incentives in the healthcare market, enabling that market to operate more efficiently. For example, redefining what constitutes essential health benefits has the potential to benefit all three groups—without adverse impact on consumers, who may, over time, see an improvement (i.e., more cost-effective and/or convenient choices).
Finally, payors and providers should remain alert for innovations that advance best practices, as well as for emerging evidence about the value digital technologies can bring. Both of these have the potential to deliver substantially greater improvement than we have estimated in this article.
The time for incumbents to act is now. Simply put, traditional approaches to delivering and paying for healthcare are no longer adequate.
The authors would like to thank Matt Carey and Nina Jacobi for their contributions to this article.
- Marken S. US uninsured rate at 11.0%, lowest in eight-year trend. Gallup. April 7, 2016.
- Evidence for the success of these programs is mixed. For example, of the 333 accountable care organizations (ACOs) that participated in the Medicare Shared Savings Program in year 2, 86 earned payments because their claims costs were below their financial benchmarks. (Introcaso D, Berger G. MSSP year two: Medicare ACOs show muted success. Health Affairs Blog. September 24, 2015.)
- Health Care Cost Institute. 2014 Health Care Cost and Utilization Report. October 2015.
- Kaiser Family Foundation, Health Research & Education Trust. Employer Health Benefits: 2015 Annual Survey. September 2015.
- Schanzenbach DW et al. Where Does All the Money Go? Shifts in Household Spending over the Past 30 Years. Brookings/Hamilton Project Report. June 2, 2016.
- See, for example, Dobbs R, Sawers R, Thompson F, et al. How the world could better fight obesity. McKinsey Global Institute Report. November 2014.
- The actual impact could be much higher, because our calculations did not include anything for which we could not establish a reasonably accurate assessment of economic effect.
- Between 1995 and 2014, medical cost inflation exceeded GDP growth by an average of 1.45%. (CMS. NHE summary including share of GDP, CY 1960–2014.)
- US Department of Labor. Long-term price trends for computers, TVs, and related items. October 13, 2015.
- The Cerulli Report. US Retail Investor Advice Relationships 2014.
- One area in which decreases have been seen is the cost of elective procedures, a reflection of consumerism’s power, as we discuss later in this article.
- McKinsey analysis of data from the US Bureau of Labor Statistics and US Bureau of Economic Analysis. Note: Some researchers have argued that provider productivity improvements are understated in these reports because they do not take changes in patients’ average severity of illness into consideration. However, even when that factor is taken into account, labor productivity improvements are far lower in healthcare than in most other industries.
- See the article by Dunn et al, Introducing the New BEA Health Care Satellite Account (Bureau of Labor Statistics. January 2015), for further discussion on the measurement of output and productivity in healthcare.
- Medicare Payment Advisory Committee. Report to Congress 2016: Medicare Payment Policy. Chapter 5: Ambulatory Surgery Center Services. March 2016.
- The importance of capital utilization as a driver of healthcare value is starting to gain wider recognition. See, for example, Klein DJ et al. Investing wisely in health care capital. JAMA. Published online September 29, 2016.
- Salter C. Narayana Hrudayalaya Hospitals. FastCompany.com. February 7, 2013.
- Atluri V, Cordina J, Mango P, Rao S, Velamoor S. How tech-enabled consumers are reordering the healthcare landscape. McKinsey white paper. September 2016.
- Aue G, Biesdorf S, Hencke N. How healthcare systems can become digital health leaders. McKinsey white paper. January 2016.
- Department of Health and Human Services. Medicare program; final waivers in connection with the shared savings program; interim final rule. November 2, 2011.
- National Law Review. IRS denial of section 501(c)(3) status for commercial ACO – accountable care organization. May 10, 2016.
- For example, the federal Medicare program limits reimbursement for telehealth services to rural or medically underserved areas. Many state Medicaid programs do not impose this restriction but may include various other limits on reimbursement. (Center for Connected Health Policy. August 2016.
- For example, 21 states and the District of Columbia permit nurse practitioners to deliver care independently; 30 states require them to work under the supervision of a physician. American Association of Nurse Practitioners.
- Using smart regulations becomes even more difficult when state laws vary.
- Greene C et al. Costs and benefits of building faster payment systems: The UK experience and its implications for the United States. Federal Reserve Bank of Boston Current Policy Perspectives. February 24, 2015.
- In a sense, these payment approaches also reduce demand, since they can inhibit referrals to other providers for unnecessary healthcare services.
- Arkansas Health Care Payment Improvement Initiative. Building a Healthier Future for All Arkansans. April 28, 2014.
- Brillstein L. Episodes of care: A value-based model for specialty care. Presented at the Second Annual Bundled Payment Implementation Forum. January 25, 2016.
- Singhal S, Pellathy T, Adigozel O. Why understanding medical risk is the key to US health reform. McKinsey Quarterly. June 2009.
- Admittedly, this categorization of healthcare spending is a simplification. In reality, insurers will need to identify high- and low-value services at a more refined level, focusing not only on particular procedures or medications but also on specific patient populations. See the sidebar “Understanding medical risk” for more detail.
- Health insurance marketplaces 2015 open enrollment period: March enrollment report. ASPE Issue Brief. March 10, 2015.
- The savings are calculated in 2014 dollars.
- CMS. NHE summary including share of GDP, CY 1960–2014.
- Atluri V, Cordina J, Mango P, Rao S, Velamoor S. How tech-enabled consumers are reordering the healthcare landscape. McKinsey white paper. August 2016.