Unfulfilled Promises


A team of RAND researchers in 2005 published a widely cited analysis that the projected widespread adoption of health information technology could eventually save the United States more than $81 billion annually by improving the delivery and efficiency of health care

Seven years later, the evidence about the safety and efficiency of health information technology is mixed and annual health care spending has grown by $800 billion annually.


  • Health information stored in one IT system must be retrievable by others, including doctors and hospitals that are a part of other health systems. This is particularly important in emergency situations.
  • Patients should have ready access to their electronic health information, much as consumers now have access to their bank accounts.Patients should be able to view their own records and share them with health care providers of their choice.
  • Health information technology systems must be engineered to
    • aid the work of clinicians, not hinder it;
    • be intuitive, so they can be used by busy health care providers without extensive training;
    • be able to easily use systems across different health care settings, much as consumers easily drive various makes and models of automobiles.

Health Affairs

Fully interoperable, patient-centered, and easy-to-use systems are necessary but insufficient to unlock the potential of health IT. Ultimately, there is only so much that the government and vendors can do. Providers must do their part by reengineering existing processes of care to take full advantage of the efficiencies offered by health IT. This revamping of health care delivery is unlikely to happen before payment models are realigned to favor value over volume.

Differential Privacy

Privacy by the Numbers: A New Approach to Safeguarding Data

In 1997, when Massachusetts began making health records of state employees available to medical researchers…William Weld, then the governor, assured the public that identifying individual patients in the records would be impossible.

Within days, an envelope from a graduate student at the Massachusetts Institute of Technology arrived at Weld’s office…[Latanya Sweeney](http://latanyasweeney.org/work/index.html) was able to pinpoint Weld’s records.

Differential privacy focuses on information-releasing algorithms, which take in questions about a database and spit out answers—not exact answers, but answers that have been randomly altered in a prescribed way. When the same question is asked of a pair of databases (A and B) that differ only with regard to a single individual (Person X), the algorithm should spit out essentially the same answers.

Privacy is a nonrenewable resource [] once it gets consumed, it is gone.

The question of [] acceptable privacy loss is ultimately a problem for society, not for computer scientists—and each person may give a different answer. And although the prospect of putting a price on something as intangible as privacy may seem daunting, a relevant analog exists.

There’s another resource that has the same property—the hours of your life [] — once you use them, they’re gone. Yet because we have a currency and a market for labor, as a society we have figured out how to price people’s time. [I]magine the same thing happening for privacy.

Downfield Imperatives

Higher-Complexity ED Billing Codes — Sicker Patients, More Intensive Practice, or Improper Payments? — NEJM

The ED has also been affected by another major trend: hospitals’ reduced inpatient capacity has led to widespread boarding of inpatients in ED hallways. This trend contributes to shifting of work formerly done in inpatient wards to the ED, encouraging EDs to discharge patients with borderline health status (who might have been admitted in the past) in order to reduce crowding and prolonged waits.

The result of these changes is an increasingly interventionist ED practice style, illustrated not only by increased imaging, but also by increased laboratory testing and initiation of IV fluids.

While the ED has remained the social safety net, it has also gradually inherited roles previously handled by office-based physicians. EDs have become a central staging area for acutely ill patients, for the use of diagnostic technology, and for decisions about hospital admission, all of which makes ED care increasingly complex.

The imperative has changed from too well to be in the ED or too ill to go home, to these are the “exact” reasons for admission. Swapping sensitivity for specificity moves the complexity and cost balls downfield to the ED.

The article misses another significant cost-driver where sensitivity and specificity are swapped. When time metrics in the ED are performance metrics for incentive-based benefits or penalties, then time becomes another enemy to slay. The time for ordering diagnostic testing with sensitivity is significantly less than the time required to order with specificity.

Swiftness and accuracy are costly.

The EHR is one reason behind increased ED billing, and fraud may be facilitated by these new systems.

The irony of the association (not causation) of EHR adoption with increased ED billing is that both “swiftness and accuracy” (as more causal than EHR adoption) is what CMS is pushing.

Mystery is Why, Not Who

Ordering of CT by Emergency Department Provider Type: Analysis of a Nationally Representative Sample

Objective Given the growing concern about CT overutilization, we provide a descriptive trend analysis of CT studies ordered in U.S. emergency departments by nonphysician health care providers and examine whether there is a significant difference in ordering patterns between nonphysicians and physicians.

Conclusion [N]onphysician health care providers are less likely to order CT compared with physicians. The types of ordering providers and their differing practices should become part of the discourse regarding appropriate CT utilization.

Mystery MD: Who is the gatekeeper of CT in the ED?

Nonphysicians increasingly turned to CT during the study period. In 2008, patient visits without a physician involved resulted in at least one CT exam 5.6 percent of the time. However, visits with a physician involved resulted in a CT exam 14.6 percent of the time. The researchers calculated that patients managed by nonphysicians had 0.38 times the odds of undergoing CT compared with those managed by physicians.

The findings suggest nonphysician providers are less likely to order a CT scan than physicians, but Lee and colleagues could not identify the reason. “It may be,” they wrote, “that nonphysician health care providers follow protocol-driven practices regarding CT ordering more strictly whereas physicians may be subjectively influenced by a strong concern for malpractice liability (given that ultimate legal responsibility for patient care belongs to supervising physicians.)”

Too obvious? Physicians and nonphysician providers in the ED see different patient populations based upon acuity. What studies are ordered is a function of how much time is spent in the triage process. Where an ED is front–loading the triage process, the goal is to drop the time patients spend in triage to both increase the triage throughput and drop the provider–to–patient time for patient satisfaction and hospital marketing purposes. Time is not sufficient to be precise, but it is sufficient to “shotgun” the studies to minimize the triage time, and also the downstream deposition time.

The mystery isn’t who does the ordering, but rather why the ordering is being done—is it always exclusively patient–centric?

Loyalty Apps

Data-Gathering via Apps Presents a Gray Legal Area

What is going on…is [] applications []…are collecting personal information, usually the user‘s location and sex and the unique identification number of a smartphone. But in some cases, they cull information from contact lists and pictures from photo libraries.

As the Internet goes mobile, privacy issues surrounding phone apps have moved to the front lines of the debate over what information can be collected, when and by whom.

Apps are the smartphone equivalent of loyalty programs. You join the program to gain a discount, coupons, contests, etc. You use the app because it conveys something similarly beneficial. But the benefits are always both ways obvious and subtle. Your uniqueness, when aggregated, is perhaps more valuable the cost of the app.

Codependent Coaddictions

Why Doctors Prescribe Opioids to Known Opioid Abusers

Throughout the 19th century, doctors spoke out against the use of pain remedies. Pain, they argued, was a good thing, a sign of physical vitality and important to the healing process.

[T]he patient’s subjective experience of pain now takes precedence over other, potentially competing, considerations. In contemporary medical culture, self-reports of pain are above question, and the treatment of pain is held up as the holy grail of compassionate medical care.

The prioritization of the subjective experience of pain has been reinforced by the modern practice of regularly assessing patient satisfaction. Patients fill out surveys about the care they receive, which commonly include questions about how adequately their providers have addressed their pain. Doctors’ clinical skills may also be evaluated on for-profit doctor-grading websites for the world to see. Doctors who refuse to prescribe opioids to certain patients out of concern about abuse are likely to get a poor rating from those patients. In some institutions, patient-survey ratings can affect physicians’ reimbursement and job security.

A cultural change contributing to physicians’ dilemma is the “all suffering is avoidable” ethos that pervades many aspects of modern life. Many Americans today believe that any kind of pain, physical or mental, is indicative of pathology and therefore amenable to treatment.

Health care providers have become de facto hostages[.]


Codependency is defined as a psychological condition or a relationship in which a person is controlled or manipulated by another who is affected with a pathological condition (as in an addiction to alcohol or heroin); and in broader terms, it refers to the dependence on the needs of or control of another. It also often involves placing a lower priority on one’s own needs, while being excessively preoccupied with the needs of others. Codependency can occur in any type of relationship[.]

Seems there are two addictions at play here: the addiction to opioids and the addiction to satisfaction. Healthcare providers are not hostages, but codependents, discarding common sense and propriety for a pathologic encumbrance.

Magic Mirror Moore Melding

Magic Mirror on the wall, who is the fairest one of all?

Mirrors That Double as Computers

Unlike the magic mirror that upset the evil queen in “Snow White,” a wave of new mirrors are relying not on hocus-pocus but on sensors, cameras, and flat-panel displays to transform the time-tested looking glass.

These “smart” mirrors are melding with digital components to act as health-monitoring devices that measure vital signs, in-shop equipment to try on clothes virtually and displays to keep track of news and information.

Facebook wants you to snitch on friends that aren’t using real names

Facebook is attempting to collect the data to gain a “better understanding of our ecosystem” according to a Facebook representative. [T]he data could eventually be used to identify specific accounts[.]

[A]pproximately 8.7 percent of the 955 million user accounts are fake. Nearly 46 million are duplicate accounts, 23 million are classified incorrectly and about 14 million have been created by “undesirable” people[.]

Facebook’s Gen Y Nightmare

Spending about 30 hours a month on the social network, she has become as transparent as a looking glass…impact[ing] the cost of her health insurance, her ability to get a loan and to find a job.

Regarding the “de-anonymizing” the web…[e]ven if the person buys a cell phone with a fake ID and uses it with great care, based on past behavior, his/her real ID will be recovered in a matter of weeks.

Expanding such capabilities is only a matter of refining algorithms, setting up the right data hoses and lining up the processing power required to deal with petabytes of unstructured data. Not an issue anymore. Moore’s Law is definitely on the Inquisitors’ side.

Augmenting reality for the “viewer,” more big data for the “viewee.” Big data has your images, has your subjective droppings, and will have your objective descriptors—begs a revision:

Magic mirrors on all the walls, who is the most quantifiable one of all?