Thursday, October 16, 2014

Health Worker Nonchalance About Ebola?

The Ebola virus
Recent reports of two nurses becoming infected with Ebola begs the question of whether they were lax in following infection-control protocols. Even if that's true (and it may not be) the bigger mystery is healthcare community's apparent nonchalance. TV's talking heads are generally not alarmed. NBC medical correspondent Nancy Snyderman reportedly snuck out to get some take-out food. Experts at the CDC apparently okayed one mildly feverish nurse's request that she be allowed to travel.

What gives?

First off, how does Ebola spread?

 Ebola is "filovirus" (so named because it has a uniquely filamentous appearance) that, once introduced into the body, can attach to and invade numerous types of human cells. Getting into the human body occurs from the injection of infected blood (such as a inadvertent needle stick from a person with Ebola) or hand-borne "self-inoculation" of a patient's body fluids into the mucus membranes. That's typically the mouth, nose or eyes. 

"Self-inoculation" of a virus by rubbing the eyes or touching the nose/mouth has been a long-known means of spreading infection. Because humans unconsciously touch their facial mucous membranes frequently during the course of a day, eye goggles and facemasks are not only a barrier to airborne virus (such as regular cold viruses), but also act as a reminder to keep your fingers away from your face and eyes (which is more important with the Ebola virus, which is not airborne). 

After the inoculation and during the initial stages of invasion and replication, there aren't enough viral particles to pose a significant person-to-person transmission risk. It's only when the infection becomes overwhelming (which is heralded by a fever) that the virus makes its appearance in body fluids, including blood, tears, saliva, sweat, diarrhea and vomit. Healthcare workers cannot avoid handling the sick patient or their bedclothes, and that's when accidental needle sticks and unconscious touching of their face - i.e. mucus membranes - leads to transmission of the virus to a new victim.

What are healthcare workers' attitudes about infections?

Getting health care workers to pay attention to the inadvertent spread of infection in the course of patient care has been a topic of research for decades.  It's not like they don't know how viruses move from person to person.  Rather, failure to act on that knowledge is a result of poor adherence, insufficient resources, staffing problems, lack of culture change, no impetus to change, and issues related to staff and patient education.  Even with intense education, attitudes may shift by a only a few percentage points. It's not uncommon for up to a quarter of health care workers to not follow basic infection control protocols after a teaching intervention.

How well do health care workers educate lay-persons?

Even when patients are in contact isolation for other reasons, healthcare workers do a bad job of dealing with the concerns of family members or educating their patients about its importance. And it doesn't help that nurse "burnout" can be an independent risk factor for the inadvertent transmission of infection to patients.

While reports like this portray the importance of public education, it's fair to say that the gap between the "stay calm" Ebola expertise of organizations like the CDC and the growing alarm of the lay public is significant.

The Population Health Blog's take?

Healthcare providers have cared for patients with other serious infectious diseases, and their attitudes to dealing with Ebola are not new. While the PHB is unaware of the details of how the two nurses described above contracted the disease, it was just a matter of time until someone got infected. 

If more primary Ebola cases occur in the U.S., we can expect more healthcare workers to contract the disease. A nonchalance toward infectious disease has been a part of the medical landscape for decades.  While the risks associated with Ebola are higher (a purported mortality rate as high as 70%), this is another virus bumping into decades-long patterns of imperfect human behaviors.

While the public is extremely concerned about the specter of Ebola, expert infectious disease talking-heads are well-acquainted with the above data.  They are not surprised that nurses are coming down with Ebola.  Unfortunately, that unsurprised expertise combined with a legacy of poor lay-public education is coming across as incompetence. That's especially true when clinical judgment about a fever leads to a plane-load of passengers being exposed to a sick patient's body fluids. The public deserves better.

Wednesday, October 15, 2014

Associations. Correlations. Inferences. Signals. Yes, That's Big Data

America's corporate Directors
celebrate big data
The Population Health Blog's recent travels recently included a speaking gig at the just concluded National Association of Corporate Directors ("NACD") annual conference meeting.  It was part of a panel discussion focusing on health care innovation that was ably moderated by tech guru John Hotta.

The PHB's educational mission was to enable the persons who serve on Boards of Directors understand how "big data" is going to change health care.  After giving its standard definition (the use of large, disparate and unrelated data sets to find correlations and draw inferences that are actionable at the individual level), it turned to the following example:

"Imagine standing at the top of the Empire State Building and analyzing the noise from below to find out what's most likely happening down on Fifth Avenue."

In other words, its the use of computational analytics to separate the noise from the signals, and using those signals to ascertain a probability.

An informed guess.  Or, a probabilistic choice.

Folks in the audience seemed to get it, especially when the PHB noted that insurance (ICD-9 250), electronic record ("diabetes") pharmacy (insulin), public health (obesity prevalence data by zip code), survey ("have you ever been told you have diabetes?"), government (car registration; overweight persons prefer minivans), web-usage (recent interest in low calorie foods?) and purchasing (grocery purchases) data could be marshalled to assign a risk that diabetes is present, and if it's present, the risk of complications, and if there is a high risk, whether it's actionable.

The value proposition? 

By understanding the risk and being able to array it from high to low, precious health care resources can be scaled to the burden of illness in the population.  So, instead of "carpet bombing" all persons with a diagnosis of diabetes with one-size-fits-all reminders to see their doctor along with mass mailings of educational materials, personalized outreach can be targeted on those persons most likely to be hospitalized (and there are big data signals that can predict it) in the next year.

Bottom line: it can save money by rationalizing health care.

The PHB wanted to point out some other need-to-knows, which it did with variable success:

1. Quantum jumps in processing power and server capacity have put this within reach of desk-top personal computers.  As an added bonus, you don't need an army of mathematicians.

2. "Actionable" also means that the information is meaningfully available at the point of care, i.e. in the doctor's office where 80% of the decisions that drive health care spending occur.

3. Big data can also point to way toward more accurate diagnoses (imagine if all the risk factors for an Ebola infection had been rolled up into a single score in that Texas ER) as well as treatment (deciding on the "best" cancer treatment program after knowing the relative influences of genetics, lifestyle and past medical history).

Wednesday, October 8, 2014

Version 1 Care Management to Prevent Hospital Readmission Fails (Unsurprisingly)

Does this high profile randomized study "prove" that telephone follow-up of recently discharged inpatients fails to prevent readmissions? 

Should hospital leaders reconsider care management programs aimed at reducing readmissions?

Hardly, says the Population Health Blog.

Here's how the study was designed:

To be eligible, patients had to be aged 55 or older and without mental illness or serious cancer. They also had to be able to use a telephone. If the patient and their doctor agreed, patients were then randomly assigned to either:

1) "usual" care that consisted of a pre-discharge review of medications, follow up and other instructions plus a 10 day medication supply, or

2) "intervention" care that was comprised of pre-discharge disease-specific education using motivational interviewing, personalized notification of the primary care physician for follow-up, a medication schedule, an in-person follow-up by a registered nurse within 24 hours and follow-up telephone calls on days 1-3 and 6-10 after discharge.

Over 6300 patients were reviewed, 1781 patients were considered and 700 were enrolled in the study. 679 patients completed 30 days, 581 patients completed 90 days and 561 patients completed 180 days of follow-up.  The mean age of the study population was 66 years, 56% had mild cognitive impairment, 33% had visited an emergency room in the prior six months and 62% used English as their primary language. 

In the intervention group, nurses managed to complete their two phone calls 83% of the time.

Results?

"There were no statistically significant differences in the number of ED visits or readmissions between the intervention and usual care groups at 30 days (0.33 vs. 0.26 per person-month; 112 vs. 89 events), 90 days (0.23 vs. 0.20 per person-month; 238 vs. 203 events), or 180 days (0.20 vs. 0.18 per person-month; 392 vs. 370 events)." 

There was also no different in the number of primary care visits between the two groups.

Ouch.

The authors speculate that this patient population already had a high level of support from primary care providers and good access to medications.  In addition, a high prevalence of cognitive impairment may have blunted the nurse interventions.  Last but not least, the authors state that further reductions in ED visits or readmissions may require more in-person home visits in lieu of just telephone calls.

The Population Health Blog offers another thought:  the study was doomed from the start.

Years ago, the Ver. 1.0 "disease management" vendors learned the hard way that aggressively "calling" every patient with did not reduce complications, costs or health care utilization

The study described above was a reprise of that long discredited approach. Calling every person being discharged from a hospital may help some patients, but not all

Since that time, "population health" vendors have discovered risk stratification. By restricting their in-person and telephonic follow-up to patients discovered to be at greatest risk by advances in"big data" analytics, resources can be better focused on the patients who are most likely to benefit and the likelihood of a return on investment is accordingly increased.

And it's not like this is rocket science.  Surveys and clinical algorithms like this and this respectively can help identify recently discharged patients at high risk of readmission. 

If the study above had incorporated this approach and only enrolled the high risk patients, they might have had a positive study. 

That's the real lesson for hospital leaders and their care management programs.

Image from Wikipedia

Thursday, October 2, 2014

Two Additional Reasons Why Health App Adoption is Bound to Grow

The Population Health Blog is avidly learning about health apps for patients

As described here, half of U.S adults now own a smartphone, half of them use them to obtain health information and approximately a fifth have at least one health app loaded on their device. 

Regular PHB readers are well aware of the potential for health apps, including lay-person education, the promotion of consumer behavior change, increased consumer-provider connectivity with greater access to care, better medication compliance as well as medication reconciliation, increased self-care, greater quality and lower costs.

But as the PHB's e-health experience grows, it's encountered two under-recognized features of apps that - in its opinion -  are sure to also drive their adoption:

1. The Provider App Arms Race:  As  competition for loyal patients grows, health systems, care organizations, insurers, buyers and provider networks are going to expect their apps to create greater consumer "stickiness."  For example, offering a tablet with a pre-configured app may enable hospitals to not only reduce readmissions, but enhance their brand recognition.

2. The App Is the Outcome: It will take years for science to prove that apps cause better outcomes. While lingering skepticism will prove to be another bonanza for outfits like this, the luster of smart-device gadgetry will be too much to resist. As a result, it's only a matter of time until Boards and their CEOs pressure their management teams to launch their own app.  While the electronic record and big data are important advances, let's face it: they're in the background. There's nothing like a patient-facing app to remind customers, families and providers of the organization's health tech chops.

Image from Wikipedia

Tuesday, September 30, 2014

The Most Interesting Man In the World Teaches the PHB about the Medical Home

The Population Health Blog isn't sure why its Twitter account was targeted by the Dos Equis ads about the exploits of "the world's most interesting man." Tweets on how "His grandmother uses his family recipes!" and "Fish fight for his bait!" tempted the PHB succumb to Twitter followership.

Which naturally prompted the debonair PHB to ponder the exploits of the Patient Centered Medical Home (PCMH).

To wit:

The White House wants to throw the bus under the PCMH.

Health insurers like it when the PCMH loses money.

The PCMH sues malpractice attorneys.

Ezekiel Emanuel wants be enrolled in a PCMH after he turns 75.

Biker pediatricians have tattoos that say "PCMH."

When they encounter a PCMH, actuaries stop counting.

PCMH jargon about smart device apps has led to the creation of a PMCH jargon app.

"PCMH" is how "ACO" is successfully spelled.

The most interesting man in the world is enrolled in a PCMH

The PHB invites other exploits.

Stay healthy, my friends.

Thursday, September 25, 2014

Dr. Emanuel Hopes He Dies Before He Gets Old

Poor judgment.

The Population Health Blog can't discern another explanation for Ezekiel Emanuel's Why I Hope to Die at 75 article in The Atlantic.  Since leaving Washington DC, Dr. Emanuel has become safely ensconced at the University of Pennsylvania, where he can disclose what he was really thinking while he was helping to stand up the Affordable Care Act.

The Population Health Blog appreciates Dr. Emanuel's recycled nostrums on the quality vs. quantity of elder-years, Americans' unrealistic yearnings for immortality and medical over-testing. And, if the essay prompts patients and families talk to their doctors about end-of-life care, even better.

But those good points are far outweighed by four intellectual blunders:

1) The watershed age of "75" that is used by Dr. Emanuel is an averageMany individual patients suffer declines in quality of living and life expectancy before as well as after that particular age. The PHB has been privileged to care for healthy persons aged 85 who have been correctly looking forward to additional years of rich and rewarding activity.

2) The "value" of a "poor quality" life is in the eye of the beholder. The PHB has also been privileged to care for very unhealthy persons over the age of 75 who remarkably treasure every day they are alive. Who is Dr. Emanuel to disagree with their decision-making?

3) While The Atlantic piece is about the writer's very personal views, they're not only arguably ageist, they're confirming the worst fears of the "death-panel" loonies.

4) Last but not least, real doctors know that healthcare preferences can change. That's especially true for end-of-life care, where yesterday's kitchen-table decisions routinely fail to account for today's emergency room realities. While Dr. Emanuel may hope he dies before he gets old, he should think on how the lyricists behind My Generation continue to rock decades later. He may live to regret his words.


Tuesday, September 23, 2014

The Antifragile VA: Lessons from the NFL

Unacceptable behavior. Tone deaf sanctions. Superficial investigations blaming a few bad apples. Contrite leadership promising change.

Population Health Blog readers might think that this is about the National Football League (NFL), but it's also about the Veterans Administration (VA) whitewash.

But, in reality, this is about something much bigger: the unpredictably predictable dysfunction that happens to large and complex organizations. Mix insular leadership (Commissioner or Secretary), an unaccountable bureaucracy (owners or appointees), huge budgets (as in very huge) with hidebound government oversight, and something very big and very bad is bound to happen. Sooner rather than later.

That something often remote (an elevator or a Phoenix clinic), is only obvious in retrospect (atrocious male violence or gaming outcomes), signals a deeper problem (player recruitment or leadership integrity) and results in a loss of reputation that lasts for years

Think baseball and steroids, NASA and shuttles, GM and starters, Presidents and red lines.

This is classic antifragility.  As we continue to concentrate economic and social power into large organizations, logarithmic jumps in complexity will lead to rare, contagious, catastrophic and unpredictable crack-ups. Naturally, our response will be to layer in more systems complexity.

Assuming large and complex ACOs prove they can really conjure money out of providing fewer health services, the PHB believes their next biggest threat is a black swan event. A huge patient data breach.  Withholding care.  Cutting corners.  Something else. You read it here first.

In the meantime, smart PHB readers will discern that there are some important differences between the NFL and the VA:

                                  VA                                            NFL
    
Problem:               Waiting lists.                      Switches and fists.

Involving:                   Docs                                     Jocks

Result:          Congressional indignation.       Sponsor consternation

Solution:             Budget Conference                    Press conference.

The Media:     Monday morning quarterbacking   Monday Night Football

So the chief gets:          Replaced                         Breathing space

The real problem:        A monopoly                         A monopoly

Tuesday, September 16, 2014

Telehealth Helps!

... and have you taken your pills today?
Are you in the "telehealth" business? 

Do you sell, buy, broker or provide remote monitoring, telephonic follow-up, internet-based patient management, handheld health apps, video-support or home-based medical devices? 

Then you'll probably want to download this 32 page paper.

Bashur and colleagues set out to review every good (defined as any controlled study with a valid concurrent comparison group with at least 150 study subjects) research paper on the impact of telehealth on three conditions: heart failure, stroke and chronic obstructive pulmonary disease.

177 references later, their conclusion is that telehealth - over a broad range of patient types (age, illness severity and co-morbidities), level and intensity of patient participation, provider types (nurses vs. physicians with or without an explicit protocol) - increases quality of care and reduces unnecessary utilization. 

In other words, telehealth is substitutive.  It doesn't add to inefficient services, it replaces them with something cheaper.

The Population Health Blog already knew that, of course, but it's handy to have an authoritative text that catalogs every published study.

What the PHB didn't quite know:

The official definition:

Telehealth (e-health, mobile health, m-health), connected health) is the delivery of healthcare via information and communication technology.

Telehealth jargon: when you launch it, make sure you have:

1. Fidelity (use in an appropriate setting with optimal strength and integrity),

2. Maturation (the technology may not have fully integrated personnel, other technology and patients to achieve maximum efficiency) and

3. Bundling (where the technology is vulnerable to how other concomitant supporting services are configured.

Monday, September 15, 2014

Is One DIet Program Better Than Another for Weight Loss?

As a doctor, the Population Health Blog was often asked by overnourished patients to help find a "best" diet.  Its advice to simply eat less and skip desert, however, was insufficient to overcome the commercial programs' allure of word-of-mouth, dubious advertising and fanciful on-line marketing . As a result, many desperate PHB patients fell into closed loops of pseudoscience, anecdotal testimonials and expertly crafted statements "not evaluated by the FDA."

As a population-health skeptic, the outcomes-focused PHB was never convinced that one commercial diet plan was "better" than any other.  Not only are excess calories very efficiently turned into corpulence by a very efficient human metabolism, it didn't make sense that that persons could eat their way to weight loss with more [insert one of the following: protein, fat, fiber, pre-packaged meals or vitamins].  Last but not least, if all these commercial weight loss outfits spent a tenth of their marketing budget on real science, the PHB may have had the evidence it needed to make a recommendation.

Well, a meta-analysis of "Named" (you'd recognize the brands) diet program outcomes has been published in JAMA and the results are decidedly unimpressive.  The good news is that all of the household-name programs result in modest weight loss compared to no diet.  The bad news is that the loss of two to six pounds for each program was no better or worse compared to the others.

The PHB's take?  It's up to the consumer to weigh their personal preferences for one type of diet plan vs. another.  In addition, out-of-pocket costs may also play a role in helping sustain the dieter's motivation in getting their money' worth. 

Beyond those two considerations, however, it's just a matter of eating less calories, not more of the latest nutritional fad.

Friday, September 12, 2014

Of Risk Stratification, Health System Variation and "Stupid" Decision-Making

A fly in the ointment
Years ago, a middle-aged Population Health Blog patient came in for a routine follow-up appointment.  Since his last visit, he had developed iron deficiency anemia. Since slow blood loss can be a sign of an early and curable cancer in the gastrointestinal tract, the PHB recommended a series of unpleasant tests. After a rather routine explanation of the time, expense and inconvenience of those tests, the patient surprised the PHB with a one-word answer: "No."

He went on to live for decades.

Which brings the PHB to this JAMA article on individually-tailored screening for another type of cancer. While even screening for prostate cancer is controversial, it's possible to stratify a man's risk of the condition with some questions, examination data and test results.  That risk can be portrayed in lay terms (there is a "42-in-100 chance" that cancer is present, but doing a biopsy has a "4-in-100 chance of causing an infection..."). 

The points of the well-written article is that 1) risk-stratification can be used to identify persons at high vs. low risk, 2) the decisions to screen, perform additional testing and embark on treatment can be, based on that risk, "tailored" to maximize a good outcome and 3) patients can use their level of risk to ultimately decide how they want testing and treatment to achieve the outcome they want.

Bravo, says the PHB.  While we're on the cusp of understanding whether a more sophisticated approach to screening ultimately leads to better outcomes than the standard all-or-none guideline (USPSTF "recommends against prostate-specific antigen (PSA)-based screening for prostate cancer"), there is enough face-validity to believe that patients will ultimately benefit.

But there is a fly in the ointment and a monkey in this wrench.

The fly? Variation will not go away. While health system bureaucrats everywhere would prefer that 0% of men undergo prostate screening, that 100% women over 50 get mammograms, and that 0% of us have a body mass index in excess of 25, individuals - after looking as the risk-benefit here, here and here, may choose otherwise.  We don't know what the "right" screening rates are.  In fact, we may not be asking the right questions.

The monkey?  Some "bad" decisions will occur. Once persons truly understand the benefits, risks and alternatives (including not dying prematurely of a preventable illness and side-effect risks that are less than driving in a car), they are allowed to make "stupid" decisions.  Physicians and bureaucrats may not like it when anemic patients, like the one described above, refuse no-brainer recommendations, but in a free country that's the price we pay. Our challenge is to make sure that our patients have all the information they need (which is apparently not the case here) to make a truly informed decision.

Image from Wikipedia