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

The Patient Centered Medical Home PCMH Gets On Base with Increased Quality in the Real World

Getting to first base

Advocates for the Patient Centered Medical Home will probably like what they see in the lead research article in the June 3 Annals of Internal Medicine.

The Population Health Blog likes it too.  But first, let's look at the study itself.

The Taconic Independent Practice Association participated in a multi-commercial insurer medical home program.  For each patient enrolled in an NCQA Level 3 primary care home, the IPA was offered $2 to $10 per patient per month. 

Since not all of the 675 IPA practices created medical homes in the 2008-2010 time frame, researchers were able to compare the quality of care for the approximately 27,000 patients attributed to the medical homes versus the approximately 64,000 patients attributed to usual care settings.  While they were at it, they also evaluated the quality impact of having an electronic health record (all medical home practices had one, but not all users of electronic health records were medical homes) vs. having a paper record. Quality was determined by examining a subset of NCQA-based measures of recommended routine screening tests and care of persons with diabetes, asthma and (for children) pharyngitis.

While the impact of being in a medical home was not a home run, it definitely got on base.

Over the three years of the study, the medical home practices' measures diverged from the other two groups by an average of a 7% vs. paper and 6% vs. EHR.  While none of the practices hit 100%, and not all of the differences were statistically significant, if an EHR-based clinic was able to hit (for example) a "72%" quality measure, the medical home was"79%" (mammogram screening). 

As one more gauge of its impact, as time went on, the spread of the data grew over time as medical homes outpaced the usual care practices.

The authors correctly point out that the study was observational and that there could be hidden factors other than the presence or absence of a medical home that could be biasing the data.  While the authors did everything they could to statistically "neutralize" the impact of unequally distributed patient or practice factors, the study process is not perfect.

This was also in a commercial insurance setting.  We don't know if Medicare patients would gain the same benefit.

The PHB will also point out that the NCQA's one-size-fits-all measures are intermediate in nature and are imperfectly tied to long term outcomes.  They also fail to account for patient preferences.

On the other hand, the PHB likes this because it was a huge "real world" study involving hundreds of clinical practices taking care of tens of thousands of patients over three years. It helps the PHB put things in perspective by showing that the team-based care management of the medical home can have a discernible impact on quality.

Unfortunately, there is nothing on the cost of care. The PCMH is still struggling to prove that it "saves" money; the PHB says health care consumers will get what they pay for and - aside from a selected high-risk subpopulation - the medical home offers high value at a reasonable additional cost.  The commercial insurers got their money's worth from the Taconic IPA.

While the authors don't specifically call it out, there doesn't appear to have been a large impact by the EHR on the quality of care in the real world.  Compared to practices with paper records, the impact of the EHR seemed to be scant.

Maintenance of Certification in Internal Medicine: What the Population Health Community Needs to Know

Since population health provider organizations work closely with physicians, they're aware that "board certification" is an important credential.  Being "boarded" in family practice, pediatrics or internal medicine is widely regarded as evidence of extensive training.

They may not be aware of the controversy brewing over board certification in the internal medicine physician community.

The American Board of Internal Medicine (ABIM) is the certifying Board for the nation's internists.  After meeting training requirements involving years of training after medical school graduation, candidates have to pass an examination.  Once physicians do that, they have the credential that documents their expertise. 

It used to be that once you did the training and passed the test, you were credentialed as a "board certified" internist.... forever.  With increasing recognition that skills can grow stale with time, in 1990 the ABIM decided to require recredentialing on a periodic basis. 

That process has evolved under the umbrella term "maintenance of certification" ("MOC").  You can read more about that here and here, but it basically involves earning "points" through activities such as documentation of learning, participation in quality improvement, chart audits and taking a repeat test.

Unfortunately, MOC and the ABIM have become a focus of physician ire.  While the academics and organized medical societies' leaders believe in the process, many rank and file practicing physicians disagree. 

Among their concerns that are nicely documented here and here:

1. It takes a considerable amount of time, documentation, and paperwork to complete the 10 years' worth of continued training/chart audits and to prepare for the repeat examination.  (That's especially true thanks to the difficulty at extracting electronic records data; it also puts smaller practices at a disadvantage, since they may not have the support personnel to help with all those tasks).

2. It's also expensive.

3. If a physician doesn't pass the test, it needs to be taken again at additional cost.  Over the past five years, the failure rate has increased from 10% to 22%.  Since it's unlikely that the pool of docs entering the MOC process are dumber, that suggests the test is getting unnecessarily harder. Some physicians wonder if ABIM has a financial incentive to increase the failure rate. 

4. Unlike the initial process of board certification, there is little hard evidence that MOC-credentialed physicians  attain better patient outcomes compared to non-MOC physicians.

5. Physicians are unhappy that the MOC process does not recognize the practical wisdom that comes with decades of patient care.  It is "one size fits all" and can't be tailored to account for different practice settings.

6. There is a possibility that MOC could evolve from a voluntary exercise in professionalism to a mandatory condition of licensure, hospital/insurer participation or employment.

7. ABIM not only has a monopoly, it has no oversight. Whatever the merits, the ABIM's MOC actions are seen by some as capricious, arbitrary, disconnected to the real world and only adding to physicians' low morale.  One survey suggests a majority of practicing physicians are skeptical about the MOC.

 The Population Health Blog suspects this is a controversy that is not going away anytime soon.  Population health service providers will always be interested in helping their "orphan" patients without a PCP become engaged with a physician, and may use "board" status as one criterion for referral.  It remains to be seen if "MOC" participation should be part of that calculus.

Stay tuned!

How Does the Office of the National Coordinator for Health Information Technology (ONC) Think About EHR Portals?

EHR portals at work?

The Disease Management Care Blog had this thoughtful reply logged onto its "Follow-Up" post on the topic of EHR patient portals. Logged by Rebecca M Coelius MD, Medical Officer for Innovation at HHS/ONC, the DMCB recognized that this was important enough to warrant its own separate page.

While we wish that the results were more conclusive and positive, the Office of the National Coordinator for Health Information Technology (ONC) applauds the meta-analysis and the recent upswing in articles on patient portals and other patient-facing technologies. The number of patients and caregivers who desire greater participation and transparency in their healthcare makes continued research in this area vital. Yet, in a close read of the full Annals of Internal Medicine meta-analysis article and in many of the studies it cites, there were unquestionably statistically significant positive clinical outcomes, as well as positive patient experiences, associated with certain patient portal functions.

The ONC does not believe that Health IT alone is a panacea, or that meeting the form of Meaningful Use, while not embracing the new functions the technologies it enables, is likely to result in measurable improvements. The study authors caution that it was case management that tipped the utility of portals from unclear or small to more substantial, but it is important to note that the case management activities happened via the portal itself. This is a perfect example of Health IT as an enabler of new ways of reaching and caring for patients; we would not separate the two concepts.

To the study’s described limitations, we offer two significant additions. First, the definition of a patient portal remains loosely specified, so it is difficult to make conclusive statements about the entire category. The meta-analysis did attempt to list which functions were present for each study, but half of the studies that looked at patient outcomes gave only a partial description of portal features, and a deeper assessment of the quality of functions and their relevance to the outcomes measured was not present for any study.

A more illustrative future approach would be to evaluate individual functions of portals for impact on patient participation in their care and specific health outcomes, and then ask what design principles and organizational contexts were necessary to make that function successful. For example, the impressive OpenNotes project demonstrated that patients with access to provider notes had a better understanding of their health and condition, improved recall of their care plan, and increased likelihood of taking medications as prescribed. In a New England Journal of Medicine study on weight loss interventions, over twice the number of patients in the remote support intervention groups (telephone, website access, and e-mail support) lost more than 5% of their weight versus the control group. Secure messaging and the ability to view personal health information are two cornerstones of portal functionality within Meaningful Use.

Second, more than 10% of these studies are ten years old, and over a third were published five or more years ago. We understand the necessity of adequate numbers for meta-analyses, but statistical significance does not necessarily confer relevant insights. Technology, and patient preferences and capabilities for using technology have fundamentally changed over the study time periods included, not to mention the maturation among health-care organizations themselves and the expectations of patients.

The very premise of the patient portal is a rapidly ageing one. As the ONC articulated in a 2013 Health Affairs article, there are shifting attitudes related to the traditional roles of patients and providers, and exploding demand and penetration of smartphones, health and wellness apps, and connected devices. We are moving the conversation from engaging people with our existing healthcare system through “portals”, to using technology to move outside our system to reach them every day where health truly happens. What we need to measure and incentivize in the future is not the value of portals, but the value of delivering the right information and intervention to the right person, at the right time, through the right interface based on an individual user’s context.

Does Diet and Exercise Prevent Diabetes or Help Persons with Diabetes Live Longer?

It's such a no-brainer, right?  If persons at risk for diabetes would only eat right and exercise more, they'd avoid the disease.  And for those who develop diabetes, diet and exercise will reduce death rates and complications.

Yes and no, say Elizabeth Sumamo Schellenberg and colleagues at the University of Alberta.  Their review of the mixed published scientific evidence on the topic appears in the October 15 issue of the Annals of Internal Medicine.  The purpose of their study was to ascertain the impact of diet and exercise on the prevention of "Type 2 diabetes," as well as lowering complications among persons with who had established Type 2 diabetes. 

To be included, studies had to be prospective and compare the outcomes from an intervention versus a randomly selected control group. The study could only be included if it examined the impact of exercise plus diet and "one other component," such as "counseling, smoking cessation and behavior modification."  The outcomes had to include the development of Type 2 diabetes (in the prevention trials) or complications (in the treatment trials).

1289 candidate studies were found but only 20 made the grade. Nine were prevention trials and 11 were treatment trials.

For the prevention trials:

The interventions lasted from 6 to 72 months, with follow-up going for 3 to 20 years for between 39 to 3234 participants.  The counseling varied and included group and/or individual with or without tobacco cessation, telephony, goal setting, cooking classes or pills involving a range of physician and non-physician professionals.

Results?

Seven of the nine studies showed that diabetes can be delayed. When the results were pooled, compared to the control patients, the risk of developing diabetes over 10 years was only a third and the difference was statistically significant.

But, there was no detectable impact on cardiovascular disease events or on eye, kidney or nerve damage. That may have been due to not all the studies including these outcomes as well as the time it takes for these complications to occur once diabetes develops.  With more patients or more time, a difference could have become apparent.
 
For the treatment trials:

The interventions lasted from 6 to 48 months with follow-up for 6 to 93 months. The counseling was as varied as the prevention trials but included glucose and blood pressure monitoring as well as stress management and, in one instance, a three day residential retreat. There was likewise the range of professionals who provided the interventions.

Results? 

Compared to the control patients, there was no statistically significant difference in all-cause mortality.  Some individual studies had beneficial outcomes involving cardiovascular events or diabetes complications, but they included the aggressive use of medications.  There were no sustained impacts on weight or dietary intake.  And if pills were not included, there was also no real improvement in measures of blood glucose control.

The Disease Management Care Blog's take?

The good news is that there is good evidence that exercise and diet can prevent diabetes.  The bad news is that it takes years for that "return on investment" to declare itself and typically involves interventions that fall outside the traditional health care delivery system.  It's unlikely, thinks the DMCB, that current iterations of payment reform (value based purchasing, bundled payments or upside risk) can be marshaled to make this a reality.  That being said, population health management (PHM) companies like Omada Health are making their evidence-based services available to, for example, employers who have a longer term commitment to the well being of their "human capital" outside of the traditional insurance market.

The bad news is that once diabetes declares itself, diet and exercise don't result in life extension, and control of complications as well as overall blood sugar levels is more a function of pills than lifestyle. Accordingly, expectations need to be realisitically shared with patients and PHM should emphasize taking the pills as prescribed.

Image from Wikipedia

Should Patients in Population Health Management Programs Have Access to Lay Care Coaches?

Based on prior posts like this, the Disease Management Care Blog thinks the answer is yes. 

That being said, this hot-off-the-presses research paper shows just much we need to learn about this emerging approach to the care of persons with chronic conditions like diabetes, high blood pressure and chronic heart failure.

Lay Persons Educating Persons With Chronic Conditions in Primary Care Clinics

The paper was just published in the Annals of Internal Medicine. It was a one year randomized study involving the patients at six Allina Health primary care clinics. 

Twelve lay "care guides" had at least 2 years of college education and "strong interpersonal skills." They received two weeks of education that included setting goals, identifying and overcoming care barriers, behavior change techniques, the limits of scope of practice and how to use the electronic records to message physicians.  It was up to the care guides and the patients to decide on how often they needed to meet in face or by telephone. The guides were supervised by two RNs.

Active (i.e. seen in the clinics within 6 months) patients who agreed to be in the study with high blood pressure, diabetes or heart failure were allocated in a 2:1 ratio to either a "care guide" or usual care. Goals were proscribed and were the usual HEDIS-style outcomes, such as achieving blood pressure control, reaching an A1c level, getting an echocardiogram, being on beta-blocker medications or getting a pneumovax immunization.
 
The study was not "blinded," in that they and their providers were aware of the assignment. Recruitment began in July of 2010 and the study was completed in April of 2012. 6168 patients were screened, 2135 patients agreed to participate and 1423 and 702 completed the study from the care guide and usual care study arms.

Results?

One year later, 82.6% of the care guide patients achieved their selected care goals vs. 79.1% of the usual care patients. That 3.5% increase was statistically significant.

Most of that improvement was accounted by a higher rates of tobacco cessation, pneumovax immunization, getting persons with diabetes to get an eye exam as well as urine protein testing, and getting persons with heart failure to go through an echocardiogram.  There were no statistically significant impacts on blood pressure control, diabetes control, cholesterol control or medication prescribing.

The care guides interacted with their patients on average 7 times (2 face-to-face and 5 by telephone).  They messaged physicians an average of 4 times.  There was no difference between the two groups in primary care office visits. Estimated cost was $286 per patient per year.

The Disease Management Care Blog's take:

There is increasing interest in incorporating lay-persons in the outpatient care of persons with chronic conditions.  That makes sense, because much of the educational "payload" may be deliverable using far cheaper and more engaging "peer" members of the community who - literally - speak the patients' language.  This is a nicely done randomized clinical trial done in a real world setting that adds to our understanding of this care option. The bottom line is that this study showed that the care guides had a real impact.

When the DMCB looks at the actual numbers, it is also clear that the study had an uphill climb.  Many of the baseline measures of blood pressure, diabetes and heart failure quality relatively high to begin with. The impact of the care guides may have been much greater in a population with a lower baseline (such as in this study) with more "room" to move.

Problems to think about for the next study.....

Not all outcomes are created equally: Unfortunately, this study was something of a disappointment because the improvements were spotty, relatively small and limited to lightweight "testing" outcomes vs. more -hard-to-achieve disease control outcomes.  It may one thing for a peer patient to talk a patient into a urine test or a heart scan, it's another getting a patient to take more pills.  That may take a professional educator, a pharmacist or nurse.

What do the patients want: In addition, the goals were based on a one-size-fits-all HEDIS approach.  They were not adaptable, negotiable or subject to shared decision-making.  If that had been in the mix, patient engagement may have been an additional ingredient that could have pushed other outcome measures toward statistical significance.

What do the docs think: The DMCB notes that provider office visits did not go down among the care guide patients compared to the usual care patients. This makes the DMCB wonder if there wasn't enough physician buy-in: if there had been higher trust in the care guides' ability to manage these patients, it would have been reflected in less need to see the patients for a separate appointment.

Predictive modeling to the rescue: Finally, there is the problem of treating all chronic illness patients the same. Not all patients with high blood pressure, diabetes or heart failure are as susceptible to behavior change, and not all patients who engage in behavior change achieve better outcomes.  The trick is to use risk stratification to find the patients with the greatest chance at benefit.  This study may have benefited from a more focused approach.