Medco’s ‘gaps in care’ approach saves $900 million by targeting 15 chronic conditions
Its costs exceed $177 billion annually. It results in 125,000 deaths, nationwide. Nonadherence to medication is so prevalent that about half of the 3.2 billion prescriptions issued in the United States are not taken as directed.
To encourage compliance, Medco Health Solutions tried an innovative approach. The result? “For people nonadherent at any point in time, we can get 75 percent of them back on therapy in about 12 weeks,” reports Glen Stettin, MD, chief medical officer. Read more »
When an employer group shifts from one health plan to another, why not allow them to take their claims data to the next health plan? That way, the new plan would gain immediate knowledge of the specific disease burden faced by its new members and be able to act accordingly vis-à-vis care management programs and other interventions. As it stands now, the new plan would have to wait many months and even then would lack the history that the earlier plan no longer needs. And when the new plan “finds out” about a member’s condition, it might be due to a claim for an event that could have been prevented had the carrier had access to the earlier data.
Here’s how the system would work. When a group signs up with a carrier, it could reserve the right to have its data transferred if it changes carriers. Obviously, it wouldn’t be able to “see” its own patient-identified data any more than it does now, but the data would accompany the change of carriers.
This can certainly be done without an Act of Congress. It might need to be safe-harbored by a brief regulation or administrative ruling under the Health Insurance Portability and Accountability Act, but I think one could argue that there is no prohibition against doing this now.
My question to the group is, what am I missing? Why aren’t we already doing this? Why wouldn’t a health plan offer this to an employer, for a fee, once it is clear that the employer is leaving for another carrier anyway?
Health insurance plans need only bolster the following accepted guidelines to see a return on a very little bit of investment
Heart failure results in substantial morbidity, mortality, and health care expenditures. There are 5.8 million people in the United States with heart failure, and this condition has one of the highest rates of hospitalization and rehospitalization. There are, fortunately, several therapies that are based on evidence and recommended by professional societies and that can reduce morbidity, mortality, and costs.
For example, a 2009 study in the Journal of the American Medical Association of 12,565 patients with HF investigated whether guidelines were being adhered to. It found that fewer than one third of patients who were eligible for aldosterone antagonist therapy were actually given these guideline-recommended drugs. At discharge, some hospitals prescribed them to no patients at all. Meanwhile, the rate of documented contraindication in the medical record was only 0.5 percent.
Yet for heart failure patients these drugs are proven to lower mortality, hospitalization, and rehospitalization rates. Read more »
The disease has risen quickly to become the third-leading cause of death in the world — getting there much faster than anyone expected
The 2003 National Health Interview Survey found that chronic obstructive pulmonary disease would ascend from the fourth- to the third-leading cause of death in the United States by 2020. It was off by a mile.
COPD has already taken third place on the list, according to the U.S. Centers for Disease Control and Prevention (CDC).
It affects as many as 24 million Americans. There was an 18-percent increase in patients hospitalized for acute COPD exacerbations between 1998 and 2008, says Richard A. Mularski, MD, chairman of the American Thoracic Society’s quality improvement committee. He is also an investigator at the Kaiser Permanente Center for Health Research.
More than 822,000 patients are hospitalized annually for COPD. Among patients 64 years of age and younger, there were more than 230,000 hospitalizations in which COPD was the first-listed diagnosis, and many more in which COPD was involved.
COPD has an average length of stay of 4.8 days, Mularski points out, with direct costs for caring for patients coming to about $40 billion per year.
Meanwhile, our understanding of the disease has been changing. What was once thought of as a pulmonary problem is now considered a larger systemic disease that may involve many comorbidities. In this article, we use the definition of comorbid from Dorland’s Illustrated Medical Dictionary, 2007, “pertaining to a disease or other pathologic process that occurs simultaneously with another.”
COPD is now understood to involve inflammation, and inflammation is unwilling to remain neatly parked in the lungs. Rather, COPD-associated inflammation affects many organ systems, and recent studies have demonstrated a set of nonpulmonary morbidities associated with COPD.
“These are all intertwined,” says Brian Carlin, MD, chairman of the COPD Alliance — a multisociety organization that includes the American College of Chest Physicians. Carlin is an assistant professor of medicine at Drexel University College of Medicine, among other appointments.
As these are patients with complex conditions, “they require complex interventions” to keep them healthy and reduce hospitalization expenses, he says.
“We now understand that COPD is a systemic disease with synergistic interactions with other systemic diseases,” says Mularski. “You cannot succeed with these patients with just single interventions.”
According to a recent study by Bartolome Celli and colleagues in the American Journal of Respiratory and Critical Care Medicine, COPD “is a complex disease at the clinical, cellular, and molecular levels.” Currently “diagnosis, assessment, and therapeutic management are based almost exclusively on the severity of airflow limitation,” even while this measure “fails to adequately express this complexity.”
As each patient’s comorbidities differ, “a holistic approach makes sense,” says William M. Vollmer, PhD, a biostatistician and senior investigator at the Kaiser Permanente Center for Health Research.
“It is almost impossible to disentangle the comorbidities,” he says. “Look at what is going on overall with each patient.”
Costs far from trivial
As is so often the case, complexity does not bring easy answers. But answers are needed, as the costs are far from trivial.
No one truly knows the full extent of these costs, even though this subject has been studied numerous times. Several of the experts interviewed for this article noted that all existing economic analyses of COPD underestimate the actual costs greatly, in that these analyses focus on COPD as a pulmonary condition and do not count expenses associated with the comorbidities.
Hospitalizations and rehospitalizations are costly and, in COPD, the second is usually longer than the first, Carlin says.
Moreover, hospitals would be prudent to improve their treatment of COPD patients now, rather than be vulnerable once new Medicare rules on readmissions go into effect, he says. “Lack of payment for readmissions will be a strong motivator,” he says.
At the present time, approximately 1 in 4 COPD patients is re-hospitalized within 30 days of discharge, Mularski says, summarizing the findings of several studies.
It is in the interest of managed care “to invest up front to keep patients healthy and keep them out of the hospital,” says Carlin.
“Health plan medical directors should educate providers to have a checklist of some type, both for the initial diagnosis and for follow-up visits,” Carlin says. They should be considering such comorbidities as heart failure, arterial stiffness, right ventricular dysfunction, left ventricular diastolic dysfunction, metabolic syndrome, osteoporosis, peripheral skeletal muscle dysfunction, nutritional abnormalities, or cancer. Furthermore, diabetes and metabolic abnormalities should be considered, particularly for patients receiving steroids.
Also, there is some evidence that COPD is associated with increased risk of long-term mortality in patients with peripheral arterial disease and those with chronic kidney disease.
Further, “between 40 percent and 50 percent of patients with COPD suffer from depression,” Carlin points out. It is well-known that depression is associated with noncompliance with physician recommendations.
Informational e-mails from medical directors alerting providers to these issues might be beneficial by improving patient health and reducing hospitalizations and rehospitalizations. “The provider should be thinking of these conditions and rule them out in the outpatient arena,” Carlin says. Thus, in terms of an established comorbidity such as osteoporosis, the provider should be pursuing the following question: “Does this patient have osteoporosis and, if so, how should that be managed to avoid a hospitalization for fracture?” At that point, he says, it is not necessary to decide precisely how much of the patient’s osteoporosis or heart failure relates to inflammation generated by COPD and how much all these conditions relate to a history of smoking or other factors.
“It is essential with these patients to search out comorbidities,” Carlin says. “Too frequently, these patients are siloed into one diagnosis” which neither protects their overall health nor effectively keeps them out of the hospital.
Vollmer points out that inadequacies in the literature are a problem. The National Institutes of Health itself is focused primarily on individual diseases, he explains, and, thus, research is lacking on diseases that manifest as multiple comorbidities. “Research tends not to cut across outcomes,” he says.
Meanwhile, a great deal is being spent on ineffective treatments. A study of 69,820 patients hospitalized for acute exacerbations of COPD, reported by Peter Lindenauer and colleagues in the Annals of Internal Medicine, found that 45 percent of these patients received at least one nonrecommended test or treatment.
What is managed care doing now?
Using claims data and computerized programs to search out possible comorbidities and then alerting physicians to them “is the essence of the care considerations,” says Haydee Muse, MD, MBA, senior medical director at Aetna.
Aetna’s Care Engine constantly scans Aetna’s system to look for potential gaps. This is a proprietary technology platform, continuously analyzing claims and other data with reference to evidenced-based best practices and alerting the members and their physicians about possible care gaps and such inconsistencies as drug-drug interactions, missing preventive exams, or needed screening tests. If a member’s records, for example, indicate he has COPD but there is no evidence of spirometry testing, the member’s physician would then be informed.
For patients with COPD, Aetna supplements physician visits with “personalized outreach interventions for members,” with nurse case managers more likely to intervene during times of hospitalization or medical crisis and the disease management team to engage them at other times to help close gaps in care, says Muse.
Both case managers and the disease management nurses work one-on-one with members, educating them on their COPD action plans, she says. “For instance, they review the warning signs that symptoms might be getting worse and require treatment — such as recognizing when [patients are] getting shorter on breath, or paying attention to increased mucous, swollen ankles, fevers, and chills.”
Aetna’s National Clinical Improvement Work Group, which develops interventional quality programs for specific patient subpopulations, develops programs targeting patients with acute COPD exacerbations leading to hospitalization. The workgroup sends information to both providers and patients — such as the importance of avoiding metformin in COPD patients who have acidosis, or the need to address sleep apnea in patients with COPD.
Aetna’s Health Media furnishes highly personalized, self-paced online coaching sessions, she says, permitting members to chose between live and online smoking cessation programs.
Cigna is using claims data to attempt to tease out information on comorbidities. “We calculate a risk score that helps prioritize customers for outreach. The presence of comorbidities will often raise the risk score,” says Scott Josephs, MD, vice president and national medical officer for total health management.
“We also identify gaps in care through our Well Informed program,” Josephs says. “This program uses algorithms to combine medical, pharmacy, and laboratory findings to determine, for example, whether the patient is overdue for a blood test to monitor a particular medication.”
In approaching each patient, Cigna takes into account such factors as the patient’s ability to read and to comprehend medical terms, socioeconomic position, and “any financial or health barriers that might affect their ability to understand and manage their condition,” Josephs says. “We try to meet them where they are.”
The goals are preventing exacerbations and maintaining level of function, restoring the level of health whenever the patient becomes ill, and preventing complications of illness and of treatment.
Personal contact by health advocates is the key, he says. These advocates, mostly nurses, are provided with more than 40 hours of behavior-change theory training at Cigna and enrolled in a form of continuing education thereafter. They focus on educational, social, and functional barriers.
Smoking cessation is, of course, a prime concern with many COPD patients, and nicotine replacement therapy is provided free to appropriate patients. An example of another focus would be whether arthritis is interfering with inhaler use.
Cigna’s Well Aware Chronic Obstructive Pulmonary Disease program was developed using nationally recognized guidelines and the recommendations of such organizations as the American Thoracic Society and the Veterans Health Administration.
“Only by improving outcomes will you reduce costs,” Josephs says. “COPD is a problem that is increasing faster than was predicted and that needs attention.”
Several experts say that the cost of COPD treatment has been underestimated in many studies.
Many problems attributed to outcomes measurement result from poor planning before a program is initiated. A DM expert lays down some ‘must-do’ rules for success in this excerpt from Disease Management and Wellness in the Post-Reform Era, published by Atlantic Information Services Inc.
Perhaps no issue in disease management (DM) is more controversial than outcomes measurement. As for wellness, that field is five years behind DM in the ability to measure outcomes validly. Being five years behind DM in measurement is like being five years behind Iraq in democracy.
Many — if not most — reported results are wrong, infected by either obvious or insidious regression to the mean and distortions due to faulty trend calculations. How do you know if your results are among those so infected? Three simple tests will tell you whether your results are infected by regression to the mean:
(1) Did you see cost or utilization declines in categories which do not normally decline in DM, such as physician visits or drugs?
(2) Did drug costs decline (a reduction attributed to the program) while the quality indicators showed an improvement in adherence to drug therapy?
(3) Is the stated decline in admissions of a much greater proportion than the improvement in quality indicators?
If the answer to any one of these questions is positive, your results are infected and hence invalid at worst and controversial at best. But help is on the way. We are already seeing a glimpse of the future in measurement, and the good news is that “regression to the mean” specifically — and complex, invalid, expensive actuarial methodologies generally — are being banished to what Leon Trotsky once called “the dustbin of history.”
What follows are the emerging insights which, taken into consideration when you measure, will remove most of the controversy around measurement and produce generally valid results … and will save both time and money in the process. That’s because validity of outcomes and complexity of the process used to generate those outcomes turn out to be inversely correlated.
Though generally not practical for health plans, the only truly valid methodology is randomized controlled trials (RCTs). Any other methodology needs to be confirmed with plausibility checking before being accepted.
Randomized control group trials were used by the Centers for Medicare & Medicaid Services (CMS) in their Medicare Health Support project. Whatever other mistakes made by CMS that perhaps caused the contracted vendors to miss their targets (and there were many), there was no issue about measuring in this manner, the closest approximation to a double-blind study there could be in a field where placebos aren’t possible. Of course, in a “real” RCT, the doctors don’t have patients in both the control and study groups, the way they did in this situation. That is just one example of mistakes made in the CMS study design.
Before embarking on your own RCT or accepting a study provided by a vendor, keep in mind that all RCTs are not created equal. In particular, there are a number of comparisons between the two groups which must be checked, and rarely are, in RCTs:
What was the previous hospitalization rate of the two groups? Often, the groups look like a match on demographics and illness burden, but had a much different rate of hospitalizations in the six months prior to the start of the trial.
Could the difference in results have been caused by the intervention? It’s not enough to just accept differing results between the control group and the intervention group in the study period. Some changes are not due to DM, including large percentage differences of any type; differences between the groups in categories like radiology or post-acute care, which simply do not get noticeably affected by DM; and differences which are larger in lower-acuity members than high-acuity members.
Even within the “expectable” categories such as hospitalizations, did the researchers rule out other possible causes for differing results? Once one focuses on knowing that only certain categories are affected by DM, one must go a step further to determine whether the differences — even if in the “expectable” categories like hospitalizations — were in fact due to the program. Was a differential decline in hospitalizations due to fewer hospitalizations for the conditions actually being managed? Was a differential decline in surgeries concentrated in the surgeries where patient preference can make a difference? Or was it across the board?
Did you achieve cost reductions in most or all categories? Keep in mind that it is not possible to reduce costs in most or all categories — the cost has to go somewhere. It might move from inpatient to outpatient, or inpatient to drugs, or ER to physician office visits. But it doesn’t go away.
Does the reported savings change when the outlier cutoff point is changed? If so, the savings are not likely caused by the program, since a few phone calls can’t prevent a six-figure hospitalization. A good way to check this: Does the vendor, who is touting the RCT, tell you what the outlier cutoff is, and whether changing it changed the savings? If not, chances are that they picked the cutoff which resulted in the greatest savings.
Assuming these paragraphs above are taken into account, the RCT is the best comparison available. That is why it is used in drug trials. However, the major disadvantage is that only rarely does a health plan or any other entity find itself in a position to conduct an RCT. Occasionally a program is offered to the insured population but many self-insured groups don’t buy it, as was the case where Blue Shield of California offered a catastrophic case management program to its own members and used the California Public Employees Retirement System as a control. It had several hundred thousand people in each group, with essentially no migration between groups. The outcomes, peer-reviewed and published in the February 2007 American Journal of Managed Care, appeared to be valid.
RCTs provide a far more accurate analysis than a “pre-post” study, in which a single population is used as both the control and study group over two periods of time. In a pre-post study, generally it is assumed that the baseline cohort’s costs would stay the same adjusted for trend (as measured by the nondiseased population’s cost change) absent the DM intervention. Therefore, any change in costs (adjusted for the change in costs of the nondiseased population) is attributed to the program.
Among the many problems with this methodology, the most obvious is that the baseline does not include the entire population, only the population sick enough to have claims. Hence the “planes on the ground” (as explained in Rule Five, below) are not included and the calculated average cost of everyone with claims for the condition is higher than the underlying average cost of everyone with the condition.
Pre-post methodologies can be divided into two types: “prospective identification,” in which anyone who ever had a claim for a condition is counted in all future periods, and “annual requalification,” in which only people with claims in any period are counted going forward.
Rules #2 and #3
Before initiating a program, you need to know which conditions are most out of control and are creating the most unnecessary admissions.
To know which conditions are out of control, you need to know basic facts. For instance, if you are managing or considering managing heart disease, you need to know your rate per 1,000 for heart attacks, angina attacks, and other cardiac events.
These two rules can be considered together. Today, too many health plans and employers say, “Let’s do DM.” Too many employers say, “Let’s do wellness.” Dollars are committed and spent and measured by actuaries … and yet, basic questions don’t get asked or answered. Let us use the example of heart disease. Health plans and employers are spending millions to manage this category, to reduce heart attacks and other ischemic events. But almost no one can answer basic questions like:
What is our rate per 1,000 patients for heart attacks, angina attacks and other cardiac events?
How has it been trending since we started this program?
How does it compare to other similar populations? Are we out of control or in control?
That set of epidemiological questions begs another set of managerial questions: How can you manage something if you don’t know what you are managing? How do you know where to focus your DM efforts if you don’t know whether and where your adverse event rates are out of control?
These event-rate tests are very simple, and avoid all the actuarial data-crunching and what-if scenarios found in the typical benefits consultant analysis. You divide the number of ER and inpatient events primary-coded for the condition in question by the total plan membership, just as if you were calculating a birth rate.
For instance, if you count 3,000 asthma attacks overall, and you have 1 million members in your plan, your asthma attack rate is 3 per 1,000.
It is vastly more actionable to know one’s out-of-control event rate, which is a known, valid, replicable figure, than it is to know the prevalence rate. Prevalence is a term of art whose parameters vary according to the “claims-extraction algorithm” used to find members. Suppose you are satisfied with the prevalence-rate algorithm and find that the prevalence is high. Does that mean you should “do DM?” Not necessarily. Perhaps usual care is quite good — that means there are few events left to avoid. The Boston area, for example, is a hotbed of asthma. Yet in the commercial population, the health plan which has the best event avoidance in the entire U.S. pulls its membership largely from greater Boston. How can they have such a low event rate in a high-asthma-prevalence environment? Because usual care is quite good thanks to years of physician education and disease management, so this plan is trying to move its customers into other care management programs.
There are two examples of what health plans can learn by looking at their event rate trend over time, and by comparing their trend to national averages.
For instance, a Southeast health plan implemented programs but never asked whether the program was actually doing what it was intended to do — reduce adverse events in the conditions being managed. An observation of condition-specific event rates showed that there was no program impact on utilization (and hence cost), notwithstanding the actuarial calculations of large savings using its modeling system.
Comparing oneself to historical performance yields some insight, but one can’t be certain that the lack of decline isn’t reflective of excellent initial performance, and therefore the expectation of improvement could be unrealistic. In that particular case, it turned out that the Southeast health plan’s performance was average and therefore should have improved.
How is it possible to know that it was “average”? The results from 29 commercial health plans and employers (but not Medicare health plans or Medicaid health plans, which would have different event rates) were combined into one average. This allows a health plan to compare itself to a benchmark and see how it is performing over time. Another case is Harvard Pilgrim Health Care Inc. Harvard Pilgrim has the best outcomes in the country, roughly tied with Providence Health Plans in Oregon.
The trend lines suggest that Harvard Pilgrim had been improving both in absolute terms and versus the national averages, and — unlike the Southeast health plan above — was already much better than average before implementing its DM programs. Even so, its performance has improved since DM implementation.
The broader question: Why doesn’t everyone look ahead of time at adverse events by condition before deciding which programs to do? The goal of chronic DM is to reduce adverse events, so it would seem very logical to see ahead of time if — and in which conditions — there are enough to merit an attempt to reduce them.
In addition to looking at these event rates — the so-called “plausibility test” — biostatisticians also recommend a “number needed to decrease” (NND) analysis to confirm whether the ROI you believe you have achieved actually was achieved.
An NND test tells you how many of these events you need to avoid in order to hit your ROI targets, given inputs for program costs and emergency and inpatient care expenses. Then, you input an explicit, transparent assumption about the likelihood of comorbidities being reduced as well, if admissions for the specific primary morbidity are avoided. For instance, in asthma most of the event avoidance will take place in asthma itself. But in diabetes, good DM could avoid events across many related comorbidities.
In addition to the basic assumption that a DM program should reduce events in the disease being managed, there are two other assumptions implicit in an NND test. The second critical assumption is that events associated with those related comorbidities are falling at the same rate that the events coded to the primary morbidity are falling. The third is that it is plausible to say that related comorbidities could fall only if there appears to have been an impact on the primary morbidity.
For this last assumption, an analogy could be made to, yes, sports. If you watch a player hit a bunch of slow balls down the middle for home runs, and the player tells you he can also hit sliders on the corners, you might believe him. However, if he misses the slow balls down the middle, that very same statement about being able to hit sliders on the corners is simply not plausible. That’s why both the straight plausibility test and the NND analysis are so concerned with success or lack thereof in the primary morbidity. While easily measurable on its own, that success would also certainly correlate with much less easily measurable results across a range of comorbidities.
A very simple example of an NND analysis might be as follows. Assume you are spending $1 million on asthma, and that avoiding an average event — the weight-average of the costs of an admission and an ER visit — saves $1,000. If you are targeting a 2:1 ROI, and you assume that whatever minor comorbidity reduction you might achieve is offset by higher drug costs, you must therefore avoid 2,000 asthma events to save $2 million.
Is that achievable? Go back to the event-rate chart. There are about three asthma events for every 1,000 plan members. Recall that this is not diagnosed members or members participating in the DM program — this is just a raw rate of event incidence. Since asthma attacks can occur in anyone, since the health plan pays claims for everyone, and since it’s the program’s job to save money by avoiding events, the raw rate of incidence is the correct rate to measure.
As one example from an event-rate chart, 1 million members would yield about 3,000 asthma events in total. This would make avoidance of 2,000 events extraordinarily unlikely — it would be a 67 percent reduction, would generate a very sharp decline in the event-rate line, and would run into the reality that about a third of asthmatics are simply unknown to a health plan in the first place. Either they themselves don’t know, or they received their diagnosis while belonging to another health plan.
However, if you have 10 million members generating 30,000 events, it would indeed be possible to avoid 2,000 of them. You would just track events the following year using the event-rate test above to see if indeed you avoided 2,000 events — 6.7 percent of the total. An event-rate chart database would reveal multiple instances of a 6.7 percent decline in events.
Adding comorbidities creates another layer of complexity in search of more validity. Vary the asthma example above to substitute heart failure for asthma. For heart failure, the value of an avoided event is much greater than for asthma, because a much higher percentage of patients presenting in the ER get admitted, and the lengths of stay are much longer. By looking at the composition of the event rate as between ER and inpatient, and applying your costs for hospital use, you can figure that perhaps the average avoidable heart failure event saved $10,000, rather than $1,000 as in asthma.
Event rates for heart failure fluid overload in the commercial population are about 0.5 per 1,000 members. So assuming the same 1 million people as in the asthma example and the same $1 million in spending, you would have to avoid 200 events to get a 2:1 ROI.
But with an event rate of just 0.5 per 1,000, there are only 500 such events to begin with, making avoidance of 200 — a 40 percent reduction — a difficult challenge. This is where the comorbidity assumption comes in. Suppose that instead of virtually no comorbidity impact from a DM program, as in asthma, you assume that for every fluid overload case your disease managers avoid, they avoid four cases of other medically-related complications or comorbidities. These are nowhere near as measurable because they are spread out over many ICD-9 codes. That assumption significantly reduces the number of avoidable, measured fluid-overload cases needed to decrease to reach the target ROI.
Specifically, to avoid 200 total events in members with congestive heart failure, one has to measure only 40 avoided cases specifically of fluid overload, or about 8 percent of the 500 expected. This is enough to show up on the event-rate charts as a noticeable decline in all but the smallest health plans.
While it is, of course, true that the “comorbidity multiplier” is clearly an assumption, the NND analysis has two huge advantages over actuarial pre-post analysis. Measurement of comorbidities is explicit and transparent, and the “comorbidity multiplier” can easily be varied. In actuarial methodologies, the sources of savings, by condition, are totally implicit, as results are presented in dollars. The best example: A public presentation by a William M. Mercer consultant showed savings of $6 million in asthma, without even checking to see if asthma admissions and ER visits changed. Had he done that, he would have noted that his client, a large retailer, didn’t even incur enough asthma events to spend $6 million on them in the first place, let alone save $6 million by avoiding them.
The “once chronic, always chronic” methodology will invariably overstate savings.
A popular methodology among health plans, vendors and especially benefits consultants is the “once chronic, always chronic” approach, a form of pre-post analysis. The Care Continuum Alliance refers to it formally as the “prospective identification” methodology, in which they find the same flaws as described in this section. In this methodology, any member who is identified in any period as having a chronic condition is assumed to continue to have that chronic condition in future periods. The assumption is based on the logic that chronic conditions, by definition, don’t go away and therefore everyone who has them, even if they are totally under control, should be tracked.
The flaw in this logic is that only members who have high enough claims to be identified through a claims algorithm are counted in the baseline. As is well known by now, tracking members with high claims forward will always yield a decline in costs, through regression to the mean.
The classic analogy, well-known to veterans of the DM field, is to aviation. Radar measures the altitude of all the flights it tracks. One could use that data to measure the altitude of planes actually in the air. This measurement will overstate the altitude of the average plane, because many planes are on the ground at any given time. So the “baseline” measurement of altitude will overstate the actual average altitude of all planes because planes on the ground are not captured in the initial average. Over time they will be, because the radar will “know” which planes have landed. So over time, the average will migrate from an average of flights in the air, to an average of all planes including the planes on the ground, thus showing a decline in measured altitude even if there is no change in actual average altitude in the U.S. aviation system.
Now assume that the radar is a claims-extraction algorithm and that the different times of the reading are years of the program. One can see, by analogy, that measured claims will decline as more people with the disease who didn’t happen to have claims in the baseline — metaphorical “planes on the ground” — are included in the measurement.
If indeed everyone with a chronic condition had claims in every period, a “prospective identification” methodology would work. However, as long as there are any “planes on the ground,” the average “altitude” (cost per disease-eligible member) noted by claims-extraction algorithms will overstate the true average cost per disease-eligible member.
The “annual requalification” methodology should prevent overstatement of savings, but often doesn’t, due to the correlation between higher compliance and recent events.
In theory, the problems noted above should be avoided by a methodology, recommended by the DMAA, which is essentially the same as the “prospective identification” methodology except that it does not count “planes on the ground” in any period, thus canceling out the bias by creating seemingly symmetrical measurement periods. It is a vastly preferable methodology, but still should not be taken as valid unless checked via an event-rate-based “plausibility test.”
Table 1 shows a hypothetical example illustrating how the “annual requalification” methodology gives a much more valid result than does the prospective identification methodology. Assume that there are only two asthmatics in the health plan, and one baseline and one program year. Further assume that inflation/trend have already been taken into account.
|TABLE 1 Cost per person with asthma in both periods using both methodologies (scenario 1)|
|2005 (baseline year)||2006 (contract year)|
|Cost per patient with asthma: $1,000 in both methodologies
$500 in prospective, $1,000 in annual requalification
In the baseline, both methodologies yield the same result — $1,000 is the average cost per asthmatic because the second asthmatic, a classic “plane on the ground,” doesn’t show up in the measurement. In the contract period, however, the methodologies yield dramatically different results. The “annual requalification” shows a $1,000 cost per asthmatic because #1 is not counted since he had no asthma-identifiable claims. The prospective methodology, though, counts him because he had asthma in the baseline so he certainly still has it, even if it’s under control enough not to generate claims.
Even though the total costs to the plan have not changed, the “prospective” methodology shows a 50 percent reduction in cost per member just by counting both members, while the annual requalification methodology shows the correct result, that costs did not decline. Curiously, even though the annual requalification methodology finds the correct mathematical answer in this case and “prospective” does not, most epidemiologists would argue the opposite — that prospective identification truly captures the right population because actual chronic disease itself does not go away. Hence, people who have shown that they have it should be counted in all future periods, even without claims. The proponents of the “annual requalification” methodology would respond that the large majority of those who do not requalify represented false positives in the baseline, and so eliminating them is epidemiologically correct as well as mathematically correct.
Yet even the annual reconciliation methodology must be plausibility-checked with an event-rate measurement, because it too can be flawed. Assume the previous example, but in this scenario, assume that #1 takes drugs for a while, having had a “scare” (see Table 2).
|TABLE 2 Cost per person with asthma in both periods using both methodologies (scenario 2)|
|2005 (baseline year)||2006 (contract year)|
|Cost per person with asthma||$1,000||$550|
Both methodologies identify the member in the contract period and both would then show a 45 percent decline in costs, even though the costs actually increased. Note, below, how a simple application of an event-based plausibility test highlights the flaw in the measurement. Having seen this red flag, the actuaries can now go back and remeasure to get the right answer (Table 3).
|TABLE 3 Asthma events in the payer as a whole|
|2005 (baseline year)||2006 (contract year)|
|Cost per person with asthma||$1,000||$550|
|Event per person with asthma||1||1|
One might say, “That’s not fair — you added the drugs to 2006 to create an artificial scenario where annual requalification wouldn’t work.” However, there is nothing “artificial” about this scenario. It is actually the most common scenario imaginable — that people are much more likely to take their drugs after they have a “scare” than before they do. If indeed it were the case that taking drugs was not more likely after a scare, then a “$100” would also consistently show up in the quadrant of baseline per patient #2, and the average in both years would be $550. However, who among us isn’t much more careful after just having had a “scare” of any kind than after the memory of the scare has faded?
Rules #7 and #8
There are only two significant sources of savings: a reduction in inpatient admissions for the condition(s) and emergency room (ER) avoidance for the specific conditions being managed and their closely related comorbidities. No other savings of significance can be attributed to DM, so there is no reason to complicate measurement with claims from other cost categories.
There is no unit-cost change possible in DM and, therefore, no reason to measure inflation, or “trend.” Doing so just increases the cost and complexity of measurement, while reducing the validity.
These two facts can be grouped because they both point in the same direction: Keep the calculation simple and population-based.
If the answer is so simple and these facts are so incontrovertible, why did reconciliations develop into the complex, expensive, invalid methodologies that have been, until recently, so widely used?
There are three reasons:
(1) The industry evolved based on savings guarantees. Guarantees had to be financially based. So methodologies were developed which were totally based on financial results, and usually never even considered whether the underlying utilization declines necessary to support that analysis were even possible. To this day, one national health plan routinely presents financial savings which, according to its own data, are impossible, and no one notices.
(2) Even without guarantees, the program sponsors within a health plan felt that they needed to present “a number” to senior management. It did not matter that the “number” was no more relevant to the program’s success than the North Vietnamese “body count” was to the Vietnam War’s success. People felt that they needed “a number.”
(3) Most health plans rely on their actuaries, as employers rely on their actuarial consultants, for financial calculations. So the actuarial departments were either given responsibility or took responsibility for this function. And actuaries are clearly the authorities when it comes to answering questions like, “How will a three-tier drug program affect medical spending?” That is an actuarial question and should be given an actuarial answer.
However, DM is not an actuarial science, involving the application of numerical models to a set of assumptions. It is a biostatistical science requiring knowledge and inferences about dose-response relationships for behavior change and event avoidance. It is all about the avoidance of exacerbations and complications, either currently (as noted in the event-rate calculations) or in the future, through favorable changes in quality indicators which presage the avoidance of future events. It is not about unrelated hospitalizations. It is not about lab tests, radiology, home care or any other element of cost which gets included in savings calculations.
And it is not about where one sets the “outlier filter.” By the time people get anywhere near the six-figure claims level, they have long since surpassed a point where events can be prevented by phone calls. Yet, changes in outlier filters can dramatically change the savings “number” despite the lack of impact of DM on those very high-cost members. It’s all about luck, at that point: Did there happen to be more outliers in the baseline or in the study period?
Likewise, pricing has nothing to do with it. DM vendors do not affect contract pricing. So why include inflation in the calculations? Small changes in inflationary trend assumptions can create massive changes in perceived savings, when inflation has nothing to do with it.
Mercer’s lead actuary, Seth Serxner, graciously and candidly acknowledges this fatal flaw in actuarial methodologies in a 2008 article when he writes:
“We can conclude, however, that the choice [emphasis added] of trend has a large impact on estimates of financial savings. Evaluators may be wise, therefore, to conduct their analyses with more than one trend in mind in order to attain a range.”
In other words, there is no way of knowing what the underlying savings actually are since it is all dependent on one’s “choice” of inflation trend. A methodology which does not need to be adjusted for inflation avoids that fatal flaw.
Speaking of “trend,” there is no evidence that the trend for the nonchronic conditions can be used as a proxy for what the chronic-disease trend would have been absent the intervention.
Contrary to what actuaries will tell you, the nonchronically ill population typically differs from the diseased population on nearly all demographic or economic variables. Using a noncomparable group to determine expected trends in cost will introduce measurement bias and limit the ability to draw accurate conclusions about the results. Only if many serial observations of cost are determined to be equivalent between the populations can some degree of confidence be achieved in using the nonchronic trend as a comparator for the chronic population.
These concerns are illustrated by the National Hospital Discharge Survey (NHDS) data presented in Figure 3. Three major chronic disease categories (circulatory, endocrine, and respiratory) are compared to “all other” discharges. As shown, those categories in which the majority of conditions are chronic have been flat, while nonchronic discharges have gone up by 7.5 percent over the observed five-year period. The assumption can also be made that the “all other” category of discharges is more costly than the chronic conditions because many of the diagnoses require surgeries (i.e., injuries, deliveries, and complications), as opposed to less costly medical stays. While these data do not represent chronic versus nonchronic populations per se and some degree of overlap is inevitable, these data do demonstrate that both the level and trend of discharges for nonchronic conditions are significantly higher from those categories considered chronic. These findings suggest that applying a nonchronic “trend” to the diseased population will bias the results in favor of the DM program.
There is also the problem that the two populations aren’t static. The “planes on the ground” will show up in the nonchronic population in the baseline. Then suppose some of them have an event. That event will show up in the nonchronic trend line, causing it to rise even though the person had the condition. In the next period, those people will be shifted into the chronic population. And, like many people with an event, they will then regress to the mean and not have another event. Thus their spike in costs will be counted as part of the nonchronic trend and their subsequent regression to the mean will be part of the chronic trend. As a result, the calculation might favor the diseased population.
Or, some actuaries might do it the other way around to avoid this, and recalculate the trend for both the chronic and nonchronic populations retrospectively, once it is learned that some of the people in the baseline were really “planes on the ground” and not nonchronic, and should have been in the chronic population to begin with. How many years would one do this for, retrospectively? How many times would one recalculate?
No matter which way one looks at it, finding an answer is cumbersome and the answer is probably invalid anyway. One can see why simply counting how many events are avoided is becoming the preferred approach.
A population selected based on “risk scores” of any type — including members selected on the basis of predictive modeling — will also regress to the mean.
One of the most common fallacies of the actuarial approach is that starting not with a population based on claims identification, but rather with a population based on its risk score, will avoid regression to the mean. However, all risk-scoring methodologies weigh either last year’s claims or some proxy for last year’s claims. Why? For the simple reason that last year’s claims are a good predictor of this year’s claims. Many people who are high-cost last year will stay high-cost, though some will move to low-cost.
Likewise, most of the people who were low-cost last year will remain so, though some will move to high-cost. If predictive models or risk scoring could predict those two moves, then indeed “risk scores” would avoid regression to the mean. But they can’t. If your doctor can’t predict when you will have a heart attack, how can a software claims algorithm?
A major risk-bearing health system once tested the ability of predictive algorithms to truly “predict,” meaning to determine which low-cost people would transition to become high-cost. What they found was, ironically, in itself quite predictable but also disappointing. Only a few low-cost members were correctly predicted to become high-cost.
In one exercise, predictive modeling vendors were asked to, well, predict. They were given a two-year-old data set and asked to predict the low-cost people who would become high-cost in the following year. “Low cost” was defined as having had claims of $4,000 or less in the base year, while high cost was defined as $10,000 or more. The results were that very few members were predicted to transition in this manner, with only Vendor A predicting more than a handful. The line, representing the percentage of those predicted who actually became high-cost, tells a story too. Even Vendor D, which tried to be most specific in this prediction and basically predicted less than 20, was right about only one of them.
In reality, several thousand people transitioned in this manner. Most were a surprise to the predictive modeling vendors, and were probably also surprises to themselves and their physician.
Conclusion: While risk scoring and its predictive-modeling cousin may have a role in identifying members for DM, they cannot be relied upon as a tool to predict a cohort’s claims cost, nor can they be used as a study design when trying to select a population whose future claims will be immune to regression to the mean.
The good news is that you can measure validly using “ingredients you have around the kitchen,” without the need for expensive actuarial consulting.
The preferred methodologies that have been described in this chapter can be easily measured by any health plan or large employer using just ICD-9 codes. There is no reason to spend large sums of money on actuarial modeling when you can get greater validity and transparency simply by determining whether you have avoided events and complications closely associated with the conditions which you are managing specifically in order to avoid events and complications.
Taking the advice in this chapter will improve your measurement dramatically. Too many reports are accepted which contain too many unnoticed mistakes, mistakes which would be caught if these simple rules and observations are followed. You may think you can spot these mistakes already. But you probably didn’t even notice that this chapter on “10 Things You Need To Know about Measuring Outcomes” actually contained a list of eleven.
For further reading
- Linden A. What will it take for disease management to demonstrate a return on investment? New perspectives on an old theme. Am J Manage Care 2006 12(4):217-222.
- Linden A. Use of the total population approach to measure U.S. disease management industry’s cost savings: issues and implications. Dis Manage and Healt Outc. 2007;15(1):13-18.
- Linden A, Biuso TJ, Gopal A, Barker AF, Cigarroa J, Haranath SP, Rinkevich D, Stajduhar K. Consensus development and application of ICD-9 codes for defining chronic illnesses and their complications. Dis Manage and Healt Outc. 2007;15(5):315-322.
- Serxner et al., Testing the DMAA’s recommendation for disease management program evaluation. Journal of Population Health Management. 11(5): September-October 2008.
Copyright ©2011 by Atlantic Information Services Inc. (AIS). This is an excerpt from Disease Management and Wellness in the Post-Reform Era, published by Atlantic Information Services Inc. (www.AISHealth.com). It is reprinted with permission from AIS. For more information on this book, visit http://aishealth.com/marketplace/disease-management-and-wellness-post-reform-era
Health plans can offer several kinds of assistance to physicians who are having trouble caring for these patients
It is not for every illness that the FDA recommends massage and emotional support. But fibromyalgia is not like most other illnesses. First, it should be said that there is no longer any question about whether fibromyalgia syndrome is a specific illness — the FDA itself states that these are patients who have gone through a change in the way their brains perceive pain.
And emotional support forms an essential element in management of this syndrome, according to the FDA. “Medication is just one part of the treatment approach” and the FDA also mentions walking, jogging, biking, gently stretching muscles, water therapy, massage, yoga, and other exercises.
Lyrica and Cymbalta and other pain relievers are not the only medications that the FDA considers relevant to fibromyalgia patients. Because comorbidities play a significant role, the FDA also considers sleep medications, antidepressants, muscle relaxants, and antiseizure medications.
But fibromyalgia patients should be approached with the assumption that no single modality alone is sufficient to address the syndrome, says Michael Siegel, MD, corporate vice president and medical director for utilization management and quality improvement at Molina Healthcare. Doctors, he says, should review the several approaches appropriate for the patient, explain each, and guide while at the same time empowering the patient.
Many patients who are managing their illness effectively achieve a moderating of symptoms, says Connie Luedtke, RN, assistant professor of nursing at the Mayo Clinic Pain Rehabilitation Center and nursing supervisor of the Fibromyalgia & Chronic Fatigue Clinic at Mayo Clinic.
Speaking directly to the interests of health plan medical directors, Luedtke urges an attempt to achieve diagnosis at earlier stages of the illness and before patients respond to their symptoms by decreasing exercise and activities and become deconditioned. In her experience it takes an average of five years for primary care doctors to complete this diagnosis. The American College of Rheumatology says fibromyalgia develops in between 2 and 4 percent of the population, predominantly in women. So, prevalence is considerable and providers should be alert to the presence of the illness. Luedtke has treated patients who had to be started on a daily exercise regimen that lasted no more than two minutes!
Fibromyalgia remains challenging for clinicians because it generates tremendous amounts of friction between providers and patients. With fibromyalgia, as with similar conditions, “the biggest problem confronting the interaction between medical providers and patients is that patients fully expect that it will be more or less obvious what the problem is, and that modern medical science will have a way to fix it. And physicians, trapped in the same paradigm, feel they should be able to provide a discrete diagnosis and prescribe a discrete cure,” says Bill Clark, MD, past president of the American Academy on Communication in Healthcare and a lecturer in medicine at Harvard Medical School.
There are no simple answers. Providers have to work carefully to build trust and respect. What is important here is that how to do this can be learned. “Communication and interactional skills can be taught and learned,” says Clark. Modules 26 and 27 of the AACH’s “doc.com” project (http://www.aachonline.org) help physicians provide self-management support.
In most situations, giving emotional support is simple, Clark says. It amounts to actively noticing patients’ emotions and letting patients know you see or hear what they are experiencing, and that their uneasy and negative feelings about fibromyalgia are normal.
To convey emotional support, the academy advises:
- Make partnership statements. Make empathetic statements, naming patients’ emotions and communicating understanding and compassion.
- Make an apology, as this communicates concern for patients — for example, “I’m sorry I’m late,” “I’m sorry I offended / annoyed / ignored you,” or even, “I’m sorry you are ill, and I wish things were different,” Clark suggests.
- Show respect by validating in your own words patients’ choices, traits, and behaviors, even if you have to look for these. For example, you may respect actions patients have taken to manage the illness even if you consider them misguided. Patients’ persistence can be praised even as you provide correct information.
- Legitimize patients’ feelings and let them know it is pretty normal to be angry, worried, or sad about their fibromyalgia.
- Express support by conveying the message that “I will not abandon you. Even though I am referring you to see a specialist, I’m still going to be your doctor.”
Clark says to “Listen carefully and ask the patient to tell you more about what worries him and about how the fibromyalgia has been affecting daily life.” Interrupt if the patient goes on and on; patients want not only your attention, but also your expertise, Clark says. One study found physicians tend to interrupt patients’ opening statement after an average of 18 seconds; a more recent repeat study found that they did so after 23 seconds.
Molina Healthcare educates providers to use a shared decision-making model, says Siegel. Rather than saying, “This is what you should do,” the physician reviews the findings of the examination and test results with the patient and informs the patient about options. After a full discussion about what treatments might be used, the patient and physician decide together what the next steps are. “Often patients will choose the less aggressive option,” says Siegel.
There is a very high comorbidity of serious depression in fibromyalgia patients, points out Michael Golinkoff, PhD, MBA, chief clinical officer at Aetna Behavioral Health. He says that Aetna routinely screens for depression in these patients.
“Even with patients who do not meet diagnostic criteria for depression, we often find that there are many psychological symptoms present,” says Golinkoff. As fibromyalgia is “very stressing, very debilitating, addressing this suffering is an important part of the treatment plan.” Thus it is critical to refer patients as appropriate to psychotherapy and other associated treatments, Golinkoff says.
Golinkoff recommends the meta-analysis of psychological treatments for fibromyalgia by Julia A. Glombiewski et al in the journal Pain (2010; 151: 280-295), both the text and the incorporated references. This study found cognitive-behavioral therapy was associated with the greatest effect sizes and reports that “meta-analytic integration resulted in a significant but small effect size for short-term pain reduction (Hedges’s g = 0.37, 95 percent confidence interval (CI): 0.27-0.48) and a small-to-medium effect size for long-term pain reduction over an average follow-up phase of 7.4 months (Hedges’s g = 0.47, 95 percent CI: 0.3-0.49). Psychological treatments also proved effective in reducing sleep problems (Hedges’s g = 0.46, 95 percent CI: 0.28-0.64), depression (Hedges’s g = 0.33, 95 percent CI: 0.20-0.45), functional status (Hedges’s g = 0.42, 95 percent CI: 0.25-0.58), and catastrophizing (Hedges’s g = 0.33, 95 percent CI: 0.17-0.49).”
Notably these results are “comparable to those reported for other pain and drug treatments used for this disorder.”
Of course, this meta-analysis provides no statistics on the degree to which psychological treatments helped empower patients for self-management or how increased capacity for self-management affects patients’ frequency of physician visits and use of other expensive resources. However, the possibility that such relationships do exist might be kept in mind.
Group therapy as well as individual therapy has been shown to be effective, Golinkoff says. Siegel also emphasized the value of group sessions “if at all possible,” both because they help patients feel they’re not alone and because they provide an opportunity for them to learn from the experience of other fibromyalgia patients.
When patients receive individual or group therapy, “we find symptoms not necessarily associated with depression but associated directly with fibromyalgia improve,” Golinkoff says.
With some patients with fibromyalgia, biofeedback is extremely useful in helping them relax and become aware of when they are relaxed, Luedtke says. “Patients seem to love that.”
At Mayo Clinic, a 2.5-day program introduces fibromyalgia patients to the syndrome, although staffing is not large enough to enroll any but patients referred internally.
Some patients’ employers provide employee assistance programs and, if this is the case, Golinkoff says, it is often beneficial to integrate the resources of such a program into the care of this patient.
In selecting medications for these patients, it may be prudent to monitor carefully or avoid entirely medications that cause musculoskeletal pain, Siegel says, mentioning statins in particular.
What about fibromyalgia patients who look to unconventional approaches to manage their illness? Aetna offers eligible members who are interested in natural and complementary health care services access to many complementary health care services.
Even more important may be how providers address a patient’s wish to embark on some entirely unscientific activities — avoiding all sugar, for example. Too often the doctor’s stance is: I know the right answer, Clark says, although other approaches may be more productive in the long run. Keep in mind that the situation is not urgent. Focus on staying in a relationship with the patient and building a reserve of trust for the future. Understand the patient’s perspective. Support the patient’s determination to make the best decisions for herself, whether or not this perspective is very helpful — the physician has the expertise to explain there are other options.
Strengthening the physician-patient relationship is not only more effective for the patient but also may be more rewarding — and less frustrating — for the physician over the long run as well, Clark says. “Every patient wants a miracle cure and every doctor wants to prescribe it,” says Clark. “It is one thing to take out an appendix; it is another to wrestle with the symptoms and the mystery of fibromyalgia, an illness that is endlessly distressing for patients.”
Group therapy has been shown to improve even nonpsychological symptoms.
The communication and interactional skills needed to deal with patients who have fibromyalgia can be taught and learned.
In-person and Internet group programs such as the Stanford model are now available to millions, and research indicates that they work
It’s an American epidemic — 70 percent of all U.S. deaths are related to a chronic disease. Half the adults here endure at least two ever-present illnesses, according to the National Council on Aging (NCOA).
Traditionally, the focus has been on medical treatment of each condition, but the growth of the affected population calls for innovative strategies to delay disease progression, improve function, and tackle the daily problems of life with a chronic ailment.
However, a highly-respected alternative approach has been shown to save enough through reduction in health care expenditures to pay for itself — even within the first year.
It originated in the late 1970s, when Stanford University Medical School set out to create an education program to build patients’ skills and confidence in managing their own health and maintaining active, fulfilling lives. Its arthritis self-management program was designed as a participatory group workshop for people with any type of rheumatic disease. After several years of thorough evaluation and testing, it was made available to other health care organizations.
The self-management approach
Today, Stanford’s arthritis program is offered throughout the United States and in Canada, the United Kingdom, Australia, China, New Zealand, South Africa, Scandinavia, and Saint Lucia. By 1990, it was the prototype for a suite of successful self-management programs developed at the Stanford Patient Education Research Center, led by Professor Kate Lorig, RN, DrPH.
The NCOA reports that 75 percent of health care costs stem from chronic conditions. “Most health plans focus on the 2 to 3 percent of members who they believe are their highest risks, with multiple hospitalizations, for instance,” says Jay Greenberg, NCOA senior vice president for social enterprise. “Stanford self-management workshops provide a cost-effective way to reach the 20 percent to 30 percent of members with multiple chronic conditions who are not yet sick enough to be heavy utilizers. Self-management could avoid or postpone many members’ worsening so much that it’s hard to help them improve their health care. This group is where we’re convinced that we can bend the cost curve with secondary prevention. Proper self-management can bring them a much healthier life, lower utilization, improved pain tolerance, and greater functionality.”
In Stanford’s programs, a group of participants meets six times in weekly two-hour sessions in a community setting such as a library or senior center. The workshop is led by two trained lay leaders who often have a chronic condition themselves. By now, many of these facilitators are “graduates” of a self-management program.
Sessions explore a broad spectrum of crucial topics. Participants discover how to deal with specific physical problems like pain or fatigue, and with emotional problems such as frustration and depression. They learn effective exercises to maintain and improve strength, flexibility, balance, and endurance. Appropriate medication use, better sleep techniques, healthy eating, and effective communication (with family, friends, and health care providers) are covered. By the sixth week, participants have the tools and encouragement to lessen disease-related problems and make better-informed treatment decisions. At each session’s end, every participant sets an individual realistic goal, then shares progress with the other group members at the next session. Stanford now offers specific self-management curricula for diabetes, arthritis, HIV, and chronic pain. Its Chronic Disease Self-Management Program is for people with any type of chronic illness or their caregivers. Stanford has developed an on-line version of this program, called Better Choices, Better Health, which NCOA is bringing to health plans and other payers.
The Stanford program has been translated into Arabic, French, Chinese, Vietnamese, Dutch, Norwegian, Somali, Italian, Bengali, German, Hindi, Korean, and Welsh. Several Stanford programs are available in Spanish versions that are geared to Hispanic culture. Nutritional information, for instance, is tailored to resonate with Latin Americans.
The chronic disease program is currently licensed by approximately 650 U.S. organizations.
Evidence of effectiveness
NCOA considers the Stanford program “the only self-care program in the marketplace that has data to demonstrate its effectiveness at reducing medical care utilization.”
In the oft-cited landmark study, published in The Permanente Journal (Spring 2002), six months after completing the program, 952 participants averaged 0.22 fewer hospitalizations and spent 0.8 fewer nights in a hospital than the control group. With a per-capita program cost of about $70 and 2002 hospital costs of $1,000 per day, the savings for each participant was approximately $750. After two years, participants reported 2.5 fewer annual visits to physicians.
Another major study, of 831 participants over age 40, found that two years after program completion, savings from fewer hospitalizations averaged $490 per person; fewer outpatient visits saved another $100 per participant. The Chronic Disease Self-Management program cost was $70 to $200 per person (Medical Care, 2001, Volume 3).
According to a study of 568 participants in England’s self-management program for people with long-term conditions, “The peer-led on-line programme conditions appears [cq]to decrease symptoms, improve health behaviours, self-efficacy, and satisfaction with the health-care system.”
Stanford’s own review of 13 U.S. or United Kingdom studies, each with 171 to 1,140 participants, cites the cost-effectiveness of chronic-disease self-management. Reviewers reported that for patients, the program “consistently results in greater energy, reduced fatigue, more exercise, fewer social role limitations, better psychological well-being, enhanced partnerships with physicians, greater self-efficacy, and is generally associated with a reduction in pain symptoms.” Remarkably, after program completion, participants “do not experience greater health care utilization when their disability worsens. The program is effective across chronic disease, socioeconomic, and education levels.”
As part of a research pilot program in 2008, Sanford (not Stanford) Health in Fargo N.D. used Stanford University’s questionnaire. Six months after completing the workshops, the 100 respondents reported measurable improvement in fatigue, shortness of breath, health distress, quality of life, and communication with physicians.
People who decide to try self-management usually “have several chronic conditions and are really struggling to get started on healthy changes,” says Rich Preussler, Sanford’s chronic disease self-management coordinator. “The strength of our Living Well program is its context for people to make small changes that they want to make, to gain confidence, and feel more control.”
What characterizes self-management program participants? For on-line programs at Group Health Cooperative, a Seattle-based not-for-profit health care system, their median age is 54. Nearly two thirds are married. They average 15 years of education, and 83 percent are white. More than half have two or three chronic conditions; 11 percent have four or more. Their most common illnesses are arthritis (39 percent), hypertension (36 percent), diabetes (29 percent), and asthma (18 percent).
With self-management workshops, “one size doesn’t fit all,” says Greenberg. Some people won’t attend a group meeting, while others don’t use the Internet. “One facilitator, who has led both on-line and in-person groups, told me that by the third week, people are posting things they’d never share face-to-face.”
Anonymity is complete; even e-mail addresses are not posted. On-line programs, Greenberg expects, will appeal far more to men than will in-person workshops.
Around-the-clock availability is especially valuable to time-pressed full-time workers and caregivers, and to rural residents without access to distant in-person workshops. Severe weather also reduces attendance at in-person group meetings.
“Participants say the on-line program is especially helpful around holiday time,” notes David McCulloch, MD, FRCP, medical director for clinical improvement at Group Health. “They tell us the support of their peers helps them stick to their diet and exercise choices over the holidays.”
“A big challenge to health plans,” suspects Mike Thompson, a principal in the human resource services group at PricewaterhouseCoopers, “may be winning over the trust of members about programs like this, getting them to see self-management as a good part of their health. A huge upside is creating brand loyalty.”
To recruit participants, Sanford Health keeps its own doctors and nurses informed about “Living Well” programs. Its community partners, including churches and disease-specific groups, spread the word. So do local news releases about upcoming groups and announcements in Sanford Health newsletters. An average group has 10 to 15 participants, for a total of 3,500 since 1998. Sanford will launch the online version in 2011.
Through targeted communication and presentations, Group Health staffers encourage clinicians to refer patients to the program, and the program is available to community residents who are not members of Group Health. According to Group Health surveys, on-line participants learned of the program through:
- Information posted on a Group Health Web site (47 percent)
- Their doctor (11 percent)
- Group Health’s employee wellness program (6 percent)
- Targeted recruitment letters (19 percent)
- Other sources (17 percent)
Each on-line group has about 25 participants. Nearly 300 Group Health members had enrolled by December 2010, with another 200 expected by June 2011. The on-line completion rate (participants logging in for four of the six sessions) is 74 percent. Group Health offers $2 incentives for taking 6-month and 12-month follow-up study surveys.
After six weeks, participants often want to maintain contact and continuing support. Some decide to form their own Google or Facebook group.
Thompson sees a growing national trend toward health care organizations finding more ways to serve people with chronic conditions. “Are disease management programs delivering value to the client?” asks Thompson, who looks carefully at ROI as well as effects on individual behavior. “For managed care providers, a big goal is bending the curve — decreasing the increases. If costs have been rising 8 to 10 percent, the hope is that they will rise only 5 to 7 percent, or less. Some companies have almost flattened the curve.” Others are beginning to ask how they can contain increases.
Group participants are more likely to ask questions and discuss medications with their doctors, observes Dan Kent, PharmD, clinical specialty coordinator at Group Health. “If they set realistic personal goals, they can sometimes reduce the dosage, or even come off medication. If they make changes to food choices — by reading [nutrition] labels and controlling portion size — and increase any [physical] activity, they can lower their blood pressure. When they’re at the point of diabetes, most patients, if they don’t already have hypertension or cardiovascular disease, are at very high risk.”
Kent appreciates the “self-driven, self-activated” aspect of the self-management program. “They come up with an idea about what to do and how much they think they can improve. For example, a patient with Type 2 diabetes who [follows all the recommendations] and loses weight can sometimes get off insulin. That’s a goal that an individual can choose. The self-management program’s support really broadens the perspective of what can happen, through taking baby steps.”
“This is a relatively inexpensive program for Group Health,” says McCulloch. “Patients who participate seem to be satisfied, and probably come in slightly less often, and are less likely to be hospitalized. It empowers people with chronic conditions.” He finds it very suitable for diabetic patients. “Anything you can do to empower [them] to feel better about themselves, understand their disease more, and see their doctor less often makes them more likely to take their meds and stabilize a bit.”
Greenberg at the NCOA concurs. “When diabetics’ blood sugar is so out of control that they face amputation or blindness, throwing a lot of treatment at them won’t change the trajectory very much. But giving them access before that point to self-management programs with proven efficacy offers a chance [to improve their condition]. That’s the big payoff.”
What’s involved in launching a Stanford Chronic Disease Self-Management program? Every organization offering an in-person Stanford program must purchase a license, good for three years. A yearly report about each program is required. For one program in one language, the basic fee is only $500. To offer more than one self-management program, fees begin at $1,000.
The Internet version, Better Choices, Better Health, is licensed exclusively through NCOA. Cost per participant ranges from $40 to $175, depending on the program’s scale and the health plan’s role in program delivery.
Having supervised Sanford Health’s Living Well program since 2006, Preussler says he has learned that it is necessary to have an infrastructure — “a coordinator, even part-time, and centralized registration system so [participants] don’t call the church or library, and so we can follow up. Someone has to handle logistics, supplies, and promotion, too.” Some community groups charge modest fees for meeting rooms.
Group Health, NCOA’s first partner in testing the on-line chronic disease program, received a two-year grant ($127,720) from the Group Health Community Foundation. Start-up took about nine months — considerably longer than anticipated. The main challenge: Developing a simple sign-in to the program through the Group Health member Web site. The study’s data collection involves substantial staff time. Group Health expects that once the pilot program concludes, far less staff time will be needed to administer these programs.
When NCOA surveyed health care organizations about why they offer chronic disease self-management, the most common answer was, “They deliver results.”
Greenberg says, “The primary cause of poor health behaviors among people with serious chronic conditions is not lack of knowledge. It’s depression and lack of confidence, often undiagnosed in this population. Sometimes the health system gives so much information that many people feel inadequate to the task and give up. Group support builds confidence and helps ease depression.”
Like Kent, Greenberg values the small, realistic action plans central to Stanford’s program. “A patient may say, ‘My grandson is coming to visit next week. I want to be able to walk around the block with him. So I need to walk 100 steps by Thursday.’” Posting a goal for the whole group to see brings accountability and encouragement.
“It’s well understood,” Thompson observes, “that if people with chronic diseases take better care of themselves, they stay out of the hospital and costs go down. Becoming more involved in their health is good for patients and for the bottom line. It’s a win-win.”
McCulloch calls self-management “a wonderful resource for patients to get support from each other. It probably builds patient loyalty to Group Health. Given that it’s largely lay-led, it helps people feel less isolated as they learn from and problem-solve with each other. The fact that it can [also] be done on-line is just fantastic,” says Group Health’s medical director. “The patients love it, and so do we.”
“Patients seem to be satisfied, probably come in slightly less often, and are less likely to be hospitalized,” says David McCulloch, MD, a medical director at Group Health in Seattle.
CFS is one of a number of diseases with an uncertain etiology and a substantial effect on patients but with few or no verified treatments
According to the Centers for Disease Control and Prevention, chronic fatigue syndrome affects between 1 and 4 million Americans. At least one fourth of these are unemployed or on disability because of CFS. Yet according to the CDC, only about half of those thought to suffer from CFS have consulted a physician for their condition.
Primary symptoms include unexplained fatigue for six months or more, in addition to any number of the following: cognitive dysfunction, postexertional malaise lasting more than 24 hours, unrefreshing sleep, joint pain without redness or swelling, persistent muscle pain, headaches of a new type or severity, tender lymph nodes, and sore throat. There are more than a dozen other less common symptoms.
Health plan medical directors find the situation vexing. “Like all managed care organizations, Independence Blue Cross struggles with establishing appropriate coverage policies and clinical programs to address conditions in which there is considerable clinical controversy,” says Donald Liss, MD, the plan’s senior medical director of clinical programs and policy. “Conditions such as chronic fatigue syndrome are particularly challenging because of the nonspecific nature of the diagnostic criteria, the lack of objective studies to confirm a diagnosis, and the wide spectrum of therapies prescribed.”
Clinical executives aren’t the only ones frustrated, says Robert McDonough, MD, the head of clinical policy research and development at Aetna. “Treating physicians are struggling to come up with cures,” says McDonough.
In addition, medical directors must consider the role medication should play. “Many of these people have concurrent psychiatric disorders such as anxiety and depression,” says McDonough. “It’s not that chronic fatigue syndrome is caused by depression or anxiety, but depression and anxiety frequency coexist, and treatment of these psychiatric problems will better enable the patient to cope with the chronic fatigue syndrome.”
CFS in the literature
It has been estimated that more than 800,000 adults suffer from CFS in the United States. The annual direct cost could be more than $8,000 per patient, with the total direct cost to society as high as $7 billion.
According to Charles W. Lapp, MD, at Hunter-Hopkins Center in Charlotte, N.C., most people who complained of the symptoms of CFS before it was officially defined in the late 1980s “were considered to be hypochondriacs or crazy, because there are so many symptoms and so many systems involved.” Lapp specializes in treating CFS.
What got people interested in it again were several outbreaks in the early 1980s, including one in Lake Tahoe that got a lot of attention. “It was written up in Rolling Stone magazine and labeled the ‘yuppie flu.’” This was right after AIDS was identified. “As a result, the CDC became very interested, wondering if it was ‘AIDS Minor.’”
McDonough says that, as of right now, CFS is a “diagnosis of exclusion,” meaning that it can be made only after other medical and psychiatric causes of chronic fatigue have been excluded.
“The CDC recommends performing a thorough history and physical and some basic laboratory tests to rule out other common causes of chronic fatigue,” he says. “These include a blood count with differential, an erythrocyte sedimentation rate, a chemistry screen, and a thyroid stimulating hormone level. Additional testing may be necessary based on the history and physical and basic laboratory tests. It is only after a negative workup for other common causes of chronic fatigue that you would come to the conclusion that someone has chronic fatigue syndrome.”
While there are no formal diagnostic methods, there are criteria that are based on subjective symptoms, according to Tanya Edwards, MD, medical director of the Center for Integrative Medicine at the Cleveland Clinic. The primary symptom is unexplained, persistent, or relapsing fatigue for at least six months. Then, four or more of eight additional symptoms must persist or recur during six or more consecutive months and not predate the disease. These are:
- Impairment in short-term memory or concentration
- Sore throat
- Tender lymph nodes in the neck or armpits
- Muscle pain
- Joint pain without redness or swelling
- Headaches of a new pattern or severity
- Unrefreshing sleep
- Post-exertional malaise lasting more than 24 hours
McDonough says that, “They usually have been very highly functioning individuals, and then something happens, sometimes an infection, and they’re suddenly wiped out. It’s like they’re struck down.”
According to Edwards, before making a CFS diagnosis, physicians should first check for an untreated low-grade infection, which can have similar symptoms. There is also significant overlap with fibromyalgia.
Health plan perspectives
At Capital District Physicians’ Health Plan (CDPHP), the thinking is that CFS, as defined in the scientific medical literature, is a real syndrome, and the plan does cover evidence-based care. “We treat this the way we would any other condition, in that we make sure the diagnosis has been appropriately made and that the proposed treatments fall within the scope of what the scientific literature supports,” explains Clifford R. Waldman, MD, senior medical director.
There have been some studies of medications specific to CFS. Currently, though, the plan pays for drugs that are designed to treat the symptoms, such as antidepressants, pain medications, and sleep medications. “One thing we realize is that because a drug is labeled an antidepressant doesn’t mean that it only treats depression,” he continues. “For example, antidepressants will alter sleep patterns. As a result, they have functionality in treating a number of different things, including a number of different chronic pain syndromes.” Thus, he notes, even though it isn’t fully understood how they work, there are some studies showing the effectiveness of antidepressants for CFS.
Waldman says it is important to be sure that the people treating CFS be qualified and use scientifically-based treatments. “It is always important to identify instances of either the use of treatments that are not scientifically supported or overuse of treatments that are scientifically supported.”
In fact, he says, this is an area that can be subject to abuse. “One concern we have is that it is very easy for a provider to treat CFS with alternative treatments, without scientific evidence, and to end up with anecdotal evidence that they are working,” he states. “After that, they continue these treatments, claim expertise in the field, and encourage people to come to them, even though they don’t have any studies to show that what they are doing is effective.”
It’s crucial for clinical executives to follow an evidence-based approach, says McDonough. “We’re continuing to follow the medical literature on chronic fatigue syndrome. The hope is to better elucidate the cause of this condition, whether it is infectious, immunologic, neurologic, psychological, or of some other etiology. Knowledge of the cause of chronic fatigue syndrome will lead to more effective treatments.”
For Health New England, though, CFS coverage is a bit more sticky. Is CFS a legitimate diagnosis? “Sort of,” replies Thomas Ebert, MD, vice president and chief medical officer. “It is a legitimate condition from the perspective that it is a diagnosis, and that there are codes,” he explains. “It is also linked to fibromyalgia and certain chronic viral conditions.”
Unlike diseases that have very specific laboratory or clinical descriptors that can be used to make a diagnosis, it is more difficult with CFS, where there are fewer of these kinds of markers, Ebert says. “This is one reason these patients are difficult to treat, and it is difficult to affect the course of the illness,” he adds.
As a result, there has been a lot of epidemiologic work done on patients with CFS, who often have gone from doctor to doctor and had relatively high use of the health care system.
“Because of the chronic nature of CFS, this is usually not the kind of patient that does well seeing primary care physicians who are scheduled to see patients every 10 to 15 minutes,” Ebert explains. “As a result, these patients often end up going to specialists, and often lend themselves to receiving a team approach to care, including clinical medicine and behavioral health.” In some cases, though, Ebert says, the patients just learn to live with what they have.
So does Health New England consider CFS a legitimate diagnosis? “It is less important for us to consider it than it is for our network providers to consider it a legitimate diagnosis,” he replies. “It usually doesn’t rise to the level of a disease state where we dedicate a lot of resources, so there won’t be a disease management program, as there would be for people with chronic diseases.” However, he adds, some patients with CFS may end up using some of the health plan’s case management services intermittently.
In Ebert’s experience, some patients may also want to see physicians who are not in the health plan’s network. “My experience is that they don’t have any more success when they go outside the network than when they stay in the network.”
The condition is probably legitimate, he adds, but with caveats, because there are people who have many symptoms or complaints, not all fitting CFS. “However, let’s say that we have a cohort of people who meet these conditions for the long term. This subset seems to be real. These are people who have symptoms that clearly interfere with their lives, families, and work.”
These people do tend to use a fair amount of medical services for a while. “After that, though, they tend not to, because they don’t get cured, so they just try to learn to get along,” he continues. “This is what drives them to seek providers outside of the network, including alternative care providers.”
In such cases, Health New England denies coverage, except in cases where a primary care physician or specialist in the network advocates sending the person outside the network. “If this is the case, we generally support it,” he states. “If the care they receive outside the network isn’t any more helpful than the care they got inside the network, they probably aren’t going to use much of that out-of-network care anyway.”
Some question disease management’s cost-effectiveness, but major insurers have seen enough to induce them to expand programs
We’ve grown accustomed in the last year and half to seeing seemingly invincible corporations and even entire industries suddenly find themselves wishing that the government would slap a “too big to fail” label on them. Most companies, however, still swim or sink in Darwinian waters where only the fittest survive.
There is no doubt that the approximately $2.5 billion disease management industry shoots the rapids these days. Skeptics are everywhere, even though some of the best health plans in the country tout their success at managing diabetes, congestive heart failure (CHF), coronary artery disease (CAD), and chronic obstructive pulmonary disease (COPD) and are branching into other areas. (There is serious debate about how cost-effectively asthma can be managed. See “Value of Asthma DM Disputed,” below.)
A direct hit in a February 4 Business Week article titled “Take Your Meds, Exercise — and Spend Billions” asserted that the cost-cutting advantages of DM have been, to put it tactfully, overstated. Then there was the little matter of the eight Medicare DM pilot programs that were supposed to measure how much money can be saved. They were launched under the Medicare Modernization Act of 2003, but last year the Centers for Medicare & Medicaid Services pulled the plug on them because the agency failed to see any positive results.
Medicare pilot programs
Ariel Linden, DrPH, MS, president of Linden Consulting Group and a widely published researcher of DM outcomes, recalls: “Medicare said, ‘All right, we don’t know if it works or not; the literature doesn’t say you work. We’ll create these randomized control trials. We’ll give you 20,000 patients. And we’ll have 10,000 controls. We’ll let you guys run with it.’ And guess what? None of them were effective. Some of them dropped out early when they saw they weren’t working. The rest just fell flat on their faces.”
Al Lewis, JD, president of the Disease Management Purchasing Consortium, who for the most part represents the employer purchasers of DM, not the providers, agrees that DM faces a perception problem. “It’s not enough that GM makes good cars now,” Lewis observes. “For a quarter of a century they made lousy cars. So you can’t just say, oh our cars are good, and expect people to start buying them.”
Gordon K. Norman, MD, is the chairman of the board of DMAA: The Care Continuum Alliance, formerly the Disease Management Association of America. He says that there may have been too much emphasis in the past on the industry’s cost-saving value as opposed to how it improves outcomes.
“I mean no one goes to a doctor to save money,” says Norman. “No one goes to a hospital to save money. Health plans don’t invest in the things they pay for to save money. But when it comes to health management services or DM, suddenly the amount of health improvement seems to go out the window and the amount of savings becomes the only thing focused on.”
To underscore how difficult things have become, it need only be noted that Linden, Lewis, and Norman are three of DM’s biggest boosters.
Still, don’t start looking for obituaries of DM providers. Patients with chronic disease account for 75 percent of overall health spending, according to the Centers for Disease Control and Prevention, and 99 percent of Medicare spending, according to Johns Hopkins University. Many plans still consider DM one of the best methods for taking on those daunting numbers, certainly in terms of the clinical processes it employs. But does it save money?
Norman offers a clue. “The fact is that it is a two-and-a-half billion dollar industry of outsourced health management programs and I don’t think that would be the case with all the steely-eyed, green-shaded CFOs and actuaries of corporate America looking on.”
There are two reasons to want DM programs for CHF, CAD, diabetes, and COPD, Lewis says. First, the cost-avoidance benefit is great, compared to how much it costs to control the condition. Second, these conditions, by and large, are not well-controlled outside of DM programs.
“Generally speaking, for disease management to work, there have to be many avoidable admissions — admissions that are avoidable by better outpatient management, where you don’t throw money at the outpatient management, ” says Lewis. “That can happen with these four and with some of the suite of rare diseases.”
Those four diseases are the ones that are “with the patient for a longer period,” says Burton I. Orland, RPh, a consultant and member of MANAGED CARE’s Editorial Advisory Board. Managing them won’t be “an overnight success, so the HMO sees improvements over a longer period. Patients tend to stay with their MCO because of a successful DM program, so there is a value to having the MCO’s nurse case managers also follow up with the patients.”
So if DM successfully manages those four, can that success be replicated with other diseases?
A study in the December 2007 issue of the American Journal of Managed Care (see “For Further Reading,”) suggests that many in the DM industry believe that it can. The study says that “although disease management programs have traditionally focused on more severely ill patients with common chronic conditions such as diabetes mellitus … and congestive heart failure (CHF), more recently the scope of disease management has expanded to include programs aimed at all patients with a condition regardless of severity (commonly referred to as population-based disease management) and at patients with rare and costly conditions (e.g., hemophilia and autoimmune disorders).”
Judith Frampton, RN, MBA, vice president for medical management at Harvard Pilgrim Health Care, says that in some ways, DM is a victim of its own success. “Why is it that diabetes disease management programs or cardiac disease management programs aren’t creating the return on investment yield that they once did? The reason is that doctors who weren’t practicing evidence-based medicine and patients who didn’t understand self-management skills 15 years ago are practicing them now.
“Other factors have also contributed,” she says. “One example is that the kinds of drugs people have today that can help them lead active and healthy lives even though they have congestive heart failure just weren’t available 10 or 15 years ago. Pharmaceuticals and other kinds of procedures and technology have changed the face of the old DM, but the model of somebody taking the time to talk to people about what they may not know, and what they may not know about how to avoid complications, is really the approach.”
Lewis agrees with Frampton’s assertion about DM being a victim of its own success in regions where people have good access to medical care, where the health plans are conscientious, and where there is a culture of health, as in eastern Massachusetts.
“There have been reductions in events for CAD because of better-than-usual care and prevention,” says Lewis. For the other conditions, the technology is improving, but more people are being diagnosed with some of these conditions. “Diabetes, for instance. What is actually pretty impressive is that the prevalence of diabetes is actually way up in the last 10 years, but the incidence rate for people going to the hospital for diabetes is actually about flat. So technology is making an impact.”
Lewis adds that good DM involves more than just making “a ton of outbound calls,” a phrase that draws a reaction from Linden akin to how a lion responds to a rare steak being waved before its eyes.
“We Americans love simple fixes, but this isn’t a simple thing,” says Linden. “The truth of the matter is that these patients are usually very complex cases and they have got five different chronic illnesses.”
Harvard Pilgrim’s Frampton disagrees, saying that “one outbound call is not the same as another. Our nurses are clinical specialists in the area that they are working in. They are not generalist nurses, though most of them are adequately trained [for that]. But to get the nuances of the drugs, to understand the specificity of the condition, you need a specialist.”
Further, Harvard Pilgrim’s nurses do motivational interviewing. “Our outbound callers are trained in behavioral change techniques, and that makes a difference. We measure whether or not the interaction has resulted in a care plan. The care plan has to have goals that the nurse would perceive as goals, but it also has to have goals that the patient would see as goals. All of that makes it a more effective interaction.”
By way of anecdotal evidence, Frampton has hundreds of e-mails, letters, and phone calls from satisfied members. “All health care is local,” says Frampton. “Our nurses are from the area. They know Dr. Smith; they know the drugstore on the corner. Some of the call centers from some of the disease management programs are nowhere near the people that they are calling. I’m not saying it is impossible to do it from a call center, but our nurses have accents like they are from Boston or they are from Maine. It makes a difference.”
Prochaska change model
Marla Tobin, MD, medical director for Aetna’s Mid-America Region, says that Aetna’s nurse callers use the Prochaska change model in trying to determine when someone is ready to adopt a healthy lifestyle. “Our nurses are taught the Ask-Me-3 technique — What three questions should I ask my doctor today when I go in to visit? So the patient has a pertinent agenda that he goes to his doctor with. He understands his medication and diagnosis. He understands what he must do next and to take charge of his life.
“There are disease-specific things that we want people to understand as well,” adds Tobin. “We want a person with congestive heart failure to weigh himself, to understand the importance of salt in his diet, to know how to get a blood pressure reading, either taking his own or having a nurse do it. We want the coronary artery disease patient to understand what the symptoms of heart disease are.”
This saves money, according to Aetna’s in-house ROI studies. A 2008 study compares members in the Aetna Health Connections disease management program with members with similar conditions who were not enrolled in the program. Company officials say that patients in the Health Connections program had 26 percent fewer inpatient admissions for diabetes, coronary artery disease, congestive heart failure, and stroke. Overall, the medical costs were 10 percent lower — $5,452 vs. $6,040 per patient per year.
Some of this comes down to helping patients follow their prescribed pharmacy treatment. Sure, more people taking more medications can actually cost the members, the employers, and the health plan money up front, but it winds up reducing hospital admissions in the long run, says Tobin.
She calls DM programs for diabetes, asthma, CAD, CHF, and COPD the anchors of the industry. “If you want to talk volume of patients, you talk about those,” says Tobin.
There are other conditions and diseases that are ripe for the sort of intense member assistance that DM provides. In fact, the plan manages 36 diseases through Health Connections. (See “Aetna Goes Whole-Hog for DM,” below.)
“Depression is huge if you look at the cost of treatment and the number of comorbid situations,” says Tobin. “We integrate our behavioral health with our medical just for that reason. The data support that 70 percent of heart attack patients have depression before, after, or during the time of their heart attack. There are high incidences of depression for people who are off work for a long time with a disability like back pain.”
Aetna’s DM effort is not only incorporating more diseases, it is also expanding demographically. “We have DM for both adults and children,” says Tobin, “because asthma, weight management, and sickle cell are the kinds of diseases that can affect kids and really change their lives.” While debate continues about DM’s effectiveness, the commonsense connections it makes have long been evident. “If you don’t deal with the depression as well as the back pain, you are not going to get the person back to work,” Tobin continues. “We manage to where the patient is today.”
Let’s say that somebody is more concerned with getting to her daughter’s wedding in May than in talking about diabetes today. “We talk to her about things she can do to be healthier between now and May,” says Tobin. “That may be a healthier lifestyle and may be controlling her lung disease or kidney disease or some other disease. As we win her confidence and get her toward that goal, then she is willing to let us help improve her diabetes.”
Doing DM in-house allows Aetna to coordinate medical and pharmaceutical treatments more easily. For instance, patients with rheumatoid arthritis — another condition that has become a recent candidate for DM — might use injected anti-TNF agents.
“For appropriate use of such specialty pharmacy drugs, we want the member to really understand the right way to use the medication and how to control the disease,” says Tobin. “Those agents cost a lot of money and you want to use them wisely to make sure that the patient is doing the right thing for his rheumatoid arthritis to get the most benefit from the expensive drugs you are using.
“Same thing with some of the cancer treatments. Same thing with some of the kidney diseases. You want to make sure that lifestyle, exercise, other medical conditions, and drug use programs are dovetailed and the information is exchanged between them.”
Time is the ingredient that will decide whether diseases and conditions not traditionally managed by DM could be managed, says Jodi Aronson Prohofsky, PhD, senior vice president for health management operations at Cigna.
“You want to impact people while they are still healthy — before they become ill, especially chronically ill,” says Prohofsky, citing the work undertaken by Dee W. Edington, PhD, the director of the University of Michigan Health Management Research Center. “We know that the rewards that employers will see might be five to ten years out.”
Cigna has been working on a depression DM program for about four years.
“We’re not just asking people whether they are depressed while we’re working with them on other diseases,” says Prohofsky. “We already know that depression is comorbid with a whole host of other diseases. We are combing our data, utilizing our analytics to identify people who are depressed who may have bipolar disorder, who may have an anxiety disorder, and we are proactively reaching out to them to engage them in a full-fledged DM program.”
Traditional DM puts a lot of stock in behavioral change. The same approach should apply to depression — things like medication or other treatment plan compliance, for instance.
“Or planning for the relapse, for the time when you are not going to be as healthy,” says Prohofsky.
Talking to Prohofsky about depression DM creates the impression that she could be talking about any DM program, which is the point, she says.
“There are conditions that you want to give priority because we know there is potentially a good return on investment, such as heart disease and COPD. But there is an expanding list of diagnoses we should be looking at, such as weight complications, because of morbid obesity, depression, and a whole host of other diseases.”
Those might be conditions that Cigna reaches out to beneficiaries about because patients may not know that they have them. “Maybe they don’t realize the risks associated with it. Maybe they have a track record of just not managing it very well. What if we just said, if you need any help with any illness whatsoever or, frankly, just to retain your health, what if you were free to call in to us and we will provide you the same resources to help you manage your health? That’s where we are today.
“Things like migraine headache, chronic stress, musculoskeletal pain, or other chronic pain syndromes,” Prohofsky continues. “Depression belongs in that category as well. Those are conditions that arguably are driving higher indirect health costs for many employers because of their prevalence more than the rare individual with heart failure who might be in that employer’s workforce. But for many employers, even non-Fortune 500 employers, some of these more prevalent, less severe conditions are nonetheless robbing them of productivity in a way that they are finding it cost-effective to invest in programs that help with these conditions.”
Lewis says that as DM begins to take on rare diseases, it is not so much a question of making people change their behavior as it is a question of making sure people have all the information.
“At this point if you are a health plan and you can’t answer a simple question like What is my heart attack rate per thousand today and what was it like five years ago, then you are not doing your job,” says Lewis. “All the valid methodology is based on measuring events.”
Tobin agrees. “I’ve worked for three managed care companies and there have been considerable differences between their programs,” she says. “The differences that you see in the literature may be the fact that you’ve got apples and oranges comparisons of what works and what doesn’t work. If it is done correctly in a well-run program integrated into your health plan, it does work well.”
Many focus on DM’s savings while concern for health improvement “seems to go out the window,” says Gordon K. Norman, MD, of DMAA: The Care Continuum Alliance.
Management of rare diseases bright spot as DM industry’s growth slows
DM vendors continue to make money, but the rate of revenue growth has slowed in recent years, according to the study “Leading Disease Management Organizations: Fall 2009,” by Health Industry Research Companies.
“DM industry revenue growth appeared to flat-line in 2009, making last year the first time in five consecutive years that DMO revenues did not grow at a double-digit pace,” says Al Lewis, JD, president of the Disease Management Purchasing Consortium. The slowdown is attributed to the recession and to lower growth rates in DM programs managing cardiovascular and respiratory diseases. One positive: “Many of the nontraditional disease states for DM, including cancer, rare diseases, and maternity, experienced strong revenue growth.”
Growth in DMO revenue by disease state
Source: Health Industry Research Companies, Summer 2009.
|Plans said to do DM best are expanding programs|
|Health plan||Major diseases or conditions historically managed||DM categories created in 2009|
|Blue Cross of Alabama||Common chronic, wellness, pain||Oncology|
|Blue Cross of Delaware||Common chronic||Wellness|
|Blue Cross Blue Shield of Florida||Common chronic, rare diseases||None reported|
|Blue Cross Blue Shield of Massachusetts||Common chronic, ESRD, rare diseases, asthma||Wellness, oncology|
|Blue Cross of Nebraska||Common chronic, wellness||None reported|
|Blue Cross Blue Shield of Rhode Island||Common chronic, health and wellness||Low back pain|
|Blue Cross of Vermont||Common chronic, plus “At Risk Suite” including hyperlipidemia, obesity, metabolic syndrome||Wellness|
|Boston Medical Center Health Net Plan||Common chronic||Depression|
|Capital District Physicians’ Health Plan||Common chronic||None reported|
|CareFirst||Common chronic plus ESRD, wellness, health coaching, lifestyle management||None reported|
|ConnectiCare||Common chronic, high-risk maternity, ESRD, complex case management, transplant case management||Wellness — HRA, health coaching outsourced to WebMD|
|Harvard Pilgrim Health Care||Cardiac, common chronic, oncology, rare diseases||High risk pregnancy|
|HealthPartners||Common chronic, rare diseases, complex case management, cancer, high-risk maternity, low back pain||Low back pain|
|EmblemHealth||Common chronic, ESRD, complex case management, high-risk maternity, rare diseases, pediatric diseases, NICU, HIV||None reported|
|Providence Health Plan||Common chronic, ESRD, cancer, inflammatory bowel disease, rare diseases, maternity, complex case management including transplant||None|
|Summacare||Diabetes, asthma, CHF||None reported|
|Source: “Leading Disease Management Organizations: Fall 2009.” Eighth annual report. Health Industries Research Companies, 2009.|
Disease management should be a function of primary care, some industry proponents argue. Did someone say patient-centered medical home?
Nothing bolsters the reputation of a consultant more than making a prediction that turns out to be true. Under the Medicare Modernization Act of 2003, the Centers for Medicare & Medicaid Services launched eight disease management pilot programs throughout the country. Ariel Linden, DrPH, MS, president of Linden Consulting Group and a widely published researcher of DM outcomes, published a white paper in the spring of 2008 that explained why those pilot programs would fail.
“And shortly thereafter — guess what? — Medicare pulled the plug on them,” says Linden.
In that peer-reviewed article, titled “Medicare Disease Management in Policy Context,” Linden touted an approach by which “the primary care physician leads a team of specialists, nurses, dieticians, pharmacists, and health educators to provide and coordinate care for the ill population.”
An intensive approach emanating from a physician’s office is the only way that DM will work, Linden argues. “I mean there is nothing here that adds up unless you have this entire infrastructure and you are firing on all of your spark plugs.
“You need to have the medical group; you need to have the hospital associated with it; you need to have this whole infrastructure built around it; you need the information technology that will allow health information to be transferred between all the providers and participants. (For more about DM, see our cover story.)
“There must also be someone manning the phones reaching out to patients. There should be a pharmacist available to explain medications. A behavioral change expert and social worker must be involved also.”
Jodi Aronson Prohofsky, PhD, senior vice president for health management operations at Cigna, sees value in the push to make DM a function of the provider. She notes that Cigna is participating in several medical home pilot programs, including multipayer programs in Colorado, Pennsylvania, and Vermont, and it has a Cigna-only program in New Hampshire. She says that the pilot programs have yet to generate enough information about how worthwhile it may be to rely more on primary care.
“We completely agree with the concept,” says Prohofsky. “But I don’t know that the whole of the system we live with today is ready. We truly believe it should be the individual’s preference. I should be able to engage in the health care system any way I prefer. One option may be through my practitioner.”
Harvard Pilgrim Health Care strives to maintain good ties with physicians, ties that help with something as complex as DM, says Judith Frampton, RN, MBA, the plan’s vice president for medical management.
“We try to understand what would be most helpful to them,” says Frampton. “Some of them want online registries; some want things faxed to their office. So we’ll send, for example, something like, ‘Here are your diabetics. I use diabetics as an example, but it is the same for any condition. Here are the people who are overdue for X, Y, and Z. If we’ve got that data wrong, just correct it. And please put a check-mark if there is somebody you really want us to call.’”
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Paul Lendner ist ein praktizierender Experte im Bereich Gesundheit, Medizin und Fitness. Er schreibt bereits seit über 5 Jahren für das Managed Care Mag. Mit seinen Artikeln, die einen einzigartigen Expertenstatus nachweisen, liefert er unseren Lesern nicht nur Mehrwert, sondern auch Hilfestellung bei ihren Problemen.