Data Analytics: Silver Lining in a Big Black Cloud

Good economic news is almost impossible to find these days. Employment is not improving, and historically low interest rates are not promoting investments that will restore lost jobs any time soon. The political process is deadlocked, incapable of producing coherent changes in economic policy. The real estate market is so battered that experts doubt housing will be a sound investment for at least a decade. The birth rate has declined for the second straight year—one of the surest signs that consumers of childbearing age are not confident in the future. Even Wall Street’s occasional gains are seen as blips in a downward cycle. The share prices of health care stocks are falling, and the bond ratings for most non-profit hospitals have been downgraded in the past few months.


However, the value of one health care asset—information—is rising fast. Companies that store and analyze data are the hot commodity in today’s medical marketplace. Competitive bidding for several health data companies has doubled or tripled their share prices in the past few months. Major payers, IT companies, and private investors are all betting that information is a critical success factor in health care. Access to key data and appropriate analysis of the numbers is increasingly viewed as the coming differentiator between winners and losers in health care.

Is this data frenzy creating the next unsustainable bubble? No; it has sound economic foundations. I cannot think of another industry that has collected so much information and used it so poorly. Health care’s inefficiency and ineffectiveness are due in no small measure to mismanagement of its data. Conversely, state-of-the-art information systems and analytics were common attributes of health systems identified as models for reform (e.g., accountable care organizations, medical homes). We simply cannot reduce costs of acceptable health care without good numbers and intelligent analysis. Wall Street gets it.

My bullish view is not an unconditional endorsement of data and analytics. Some companies in the business will perform highly sophisticated manipulations of bad numbers, ignoring a lesson of the latest crash in the stock market (e.g., “quants” who failed to realize that collateralized debt obligations included a lot of mortgages that would not be repaid). Others will collect good numbers but analyze them with flawed statistical techniques.

Nevertheless, companies that mine accurate, meaningful, and timely numbers with the right analytical tools will strike gold. They have the opportunity to shape successful health reform in local marketplaces—faster and better than complicated federal laws with uncertain political futures in bad economic times. What do you think? Is health reform possible without good data and sound analysis? Are data stocks a good buy…or the next market bust?

Is Meaningful Use Always a Step Forward?

Recent hoopla over “meaningful use” (MU) is obscuring the compelling reason to adopt electronic health records (EHR). Digital transformation of medical care delivery is an economic imperative to reduce the costs of producing acceptable care—doing things right all the time, as inexpensively as possible. Digital transformation is a means to an end. The end is not “meaningful use.” Rather, it is identifying wasted resources and reallocating them to productive use.

I fear that MU rules for the first two years of HITECH will actually increase production costs for many providers seeking the incentive payments. By lowering the bar so more providers might qualify, the final rules fail to discourage simultaneous use of electronic and paper records for all data-gathering functions. In my experience, maintaining two identical systems increases costs—that is, MU-qualified providers with duplicative paper and digital information systems will incur higher overall costs than providers that continue to use only paper records.

I have seen this waste first-hand on three recent family experiences with a highly rated health system. Several paper forms were filled in by hand (by the patient, nurses, and physicians), and then the information on the forms was typed into the EHR before care could proceed to the next step. Labor costs were doubled, and data transcription mistakes could easily have occurred as data were keyboarded into the computer. Ironically, I believe that this duplicative and error-prone process could conceivably qualify for “meaningful use” payments, even though it certainly raises costs and potentially lowers quality.

I started working in health care 40 years ago as a medical records clerk. I have extensive experience with paper records, especially during my academic career as a researcher. I have subsequently devoted most of the past 20 years to promoting efficiency and effectiveness through digital transformation. Nevertheless, I have come to the conclusion that paper records should not be completely eliminated. Some data, such as a history and physical or background information provided by the patient, can be recorded more efficiently on a paper form. An intelligent scanner can then transfer the information to an EHR. On the other hand, many data entries (e.g., test results, medication orders, caregivers’ notes not made in the patient’s presence) should never exist on paper.

Today’s real challenge is to design and build integrated, intelligent record systems where data originate in the most cost-effective form but quickly migrate into interoperative electronic files. So far, I haven’t seen how the MU rules necessarily move us in this direction. Please educate me with your comments if you have figured it out; I need to know what I am missing in HITECH. Above all, I solicit your thoughts on optimal relationships between paper and electronic data collection.

Absorptive Capacity: Are We Doing Too Much?

Do you remember studying absorptive capacity in economics courses?  I didn’t encounter the concept until graduate school, yet I have found it to be an essential foundation of operations analysis.  Considering absorptive capacity is a key to efficiency and effectiveness—especially in a recession when accustomed growth has come to a halt.  (You can quit reading this post if your organization has sufficient revenue and personnel to do everything that needs to be done…)

Absorptive capacity is a measure of an individual’s or an organization’s ability to take on a new task.  As individuals, we effectively recognize the concept when we say—as we so often do these days—that we have no “bandwidth” for a new assignment because we cannot keep up with the work we’ve already got.  However, we probably don’t give due recognition to organizational capacity to do one more thing. 

Based on my frequent interactions with providers and payers around the country, I think health care executives need to assess absorptive capacity at the organizational level.  The number of operational demands is unprecedented and growing.  As if HIPAA 5010 and ICD-10 mandates aren’t enough to stretch resources to the limit, along come challenges to become Meaningful Users and Accountable Care Organizations while trying to understand the Affordable Care Act!  Any one of these new demands can quickly become the “straw that breaks the camel’s back,” resulting in inefficiencies that can then break the bank (not to mention employee morale).

Health care executives need to evaluate two possibilities from the perspective of absorptive capacity: 

• First, some things that seemingly must be done are not worth doing.  (Decision-makers should also remember that anything not worth doing is not worth doing well.)  My August 3^rd blog post on the marginal utility of meaningful use illustrated negative economic consequences when economic costs exceed financial incentives.  Additional consideration of absorptive capacity will suggest that some projects are not worth the human costs, even if the projects show a positive ROI on the balance sheet.  
• Second, some “must do” tasks that cannot be done by one organization acting alone can be accomplished successfully by several organizations working together.  Many health care delivery systems do not have available resources to own and manage today’s essential infrastructure of health information technologies.  To use HIT productively, they need to assemble partnerships with an absorptive capacity that can be shared by all the stakeholders (including payers and vendors/outsourcers). 

Health care’s “do-it-yourself” tradition is poorly suited to the new medical marketplace.  Industry leaders need to realize that they simply to not have the economic or human capacity to do everything.  Some “opportunities” need to be skipped or pursued with others.  What do you think?  Has your organization reached its absorptive capacity?     

Medicare Solvency Extended?

Last week’s report that the Medicare hospital trust fund will not run out of money until 2029 is perplexing.  The system’s trustees said last year that insolvency would occur in 2017, so the 12-year extension of Medicare’s viability comes as quite a surprise.  The only major change since the previous annual reports was passage of two convoluted laws that are uniformly criticized for their failure to “bend the cost curve.” 

Yes, the reform legislation of 2010 includes dramatic cuts in future federal payments for Medicare services, but it does not meaningfully address the numerous market failures that generate wasteful increases in the volume and costs of care.  These structural problems are succinctly and cogently presented in the Statement of Actuarial Opinion at the end (http://www.cms.gov/ReportsTrustFunds/downloads/tr2010.pdf, pp. 281-283).  Even the Trustees’ commentary includes appropriate caveats.  Nevertheless, their overall message conveys an optimistic outlook that I do not share. 

The report’s positive spin is based on a possibility “that providers can improve their productivity, reduce wasteful expenditures, and take other steps to keep their costs within the bounds imposed by Medicare price limitations.” (p. 2)  I’ve argued for years that improving productivity and reducing waste are imperatives for providers and payers, for economic and professional reasons independent of Medicare.  I fear that the new reform laws will actually thwart the private sector’s efforts to become efficient and effective (i.e., to do things right all the time, as inexpensively as possible).  Time and money that should be dedicated to improving operations will be diverted to trying to understand the complicated laws and complying with an exploding array of cumbersome regulations.

As a medical economist focused on building a world-class health care system by incorporating information technologies and performance improvement techniques into daily operations, I am particularly bothered by reform provisions prohibiting providers and payers from using comparative data to reallocate resources toward the least-expensive clinical interventions that provide acceptable outcomes.  Economic analysis shows that trade-offs must be made when an economic system hits the limit of its resources.  Consequently, providers and payers will increasingly find themselves in an economic Catch-22—better data will support making “discriminatory” coverage decisions that are not allowed under the reform laws of 2010.     

All other things being equal, cutting Medicare expenditures would extend the solvency of the trust fund.  However, other things are not equal, and Medicare’s gain will create pain elsewhere, sooner rather than later.  We still have a broken health system that desperately needs to be fixed.  Hence, last week’s report on the trust fund’s extended future does not give me any reason to breathe a sigh of relief.  What do you think?  Is there a silver lining in the dark cloud of Medicare cuts?  

Marginal Utility of Meaningful Use (MU of MU)?

To anyone with basic training in economics, MU designated a very important concept long before “meaningful use” co-opted the abbreviation under HITECH.  The original MU, marginal utility, is part of the foundation of microeconomic theory—marginal analysis.   It ought to be a key consideration in every provider’s approach to deciding if meaningful user designation under the federal incentive program is worth the time and money.  (Don’t forget that providers must make the investment before pursuing incentive payments.  HITECH does not provide up-front seed money.)           

Marginal analysis embodies two steps for answering such questions.  First, it looks solely at the relationship between additional expenditures and additional utility (i.e., value in use at the margin) of a possible activity.  If the marginal utility exceeds the marginal cost, the analysis proceeds to the second step.  The second, essential step in marginal analysis is comparing any investment with a positive marginal utility to other ways that the same resources might be spent. 

A new activity with marginal value greater than marginal costs is not economically justified until additional analysis shows that its returns are greater than the returns from other ways that the same limited resources could be expended.  In other words, positive MU is not a solely sufficient reason for making an investment when resources are scarce—clearly the situation facing all providers in today’s unforgiving economy.  Marginal analysis ultimately supports the investment with the highest MU when investment capital is limited.  (If your organization has unlimited funds, you can ignore the point of this blog post.) 

As a medical economist focused on information technology for more than a decade, I do not believe that providers should automatically seek MU designation just because the value of the incentives is expected to exceed the costs of making the necessary investments in HIT.  The key decision factor is the potential returns of other ways the same money could be spent.  All other things being equal, providers will discover that investments in HIT can reasonably be expected to yield the best returns to the bottom line.  Digital transformation of health care is a precondition to better, less-expensive health care for all Americans.

Becoming a government-qualified meaningful user will make the most economic sense for some providers, but none should blindly assume that HITECH is the only option.  The rational approach is comparing all feasible HIT investments that will improve efficiency and effectiveness, and then choosing the best one.  Given the narrow focus and uncertainty of “meaningful use” as being defined under the HITECH Act, I think that comprehensive marginal analysis will cause many providers to decide that the best returns are likely to come from HIT investments not eligible for the federal incentives.  What do you think?