Archive for Proactive health management
by KDunn
April 21, 2008 at 6:07 pm · Filed under Proactive health management, Women's Health
I’m a HR person, so you know that contraception is the last thing I want to talk about… Don’t get in an employee’s personal business, etc…
Ray Brusca, VP of Benefits at Black and Decker, would tell me (and you, if you’re like me) that contraception is something you need to talk more about, given the costs of unplanned pregnancy.
Still don’t buy it? Consider Ray’s data that 50% of all pregnancies are unplanned, and you might change your mind…
Brusca’s presentation in Track Six on Monday (Employee-Centric Benefits for Prevention and Improve Care Management) started with the assumption that 50% of all pregnancies aren’t desired. That fact alone suggests that more education on contraception is employee-centric. The problem, according to Brusca, is that the U.S. culture prefers means of contraception that are unreliable. For that reason, Black and Decker actively promotes education on Long Acting Reversible Contraception (LARC), the best example of which is the IUD.
Use of forms of LARC is strong in Europe, weak in the U.S. So Black and Decker communicates the pro’s of contraception, specially LARC’s often.
Still not convinced of the business case? Brusca points to Black and Decker’s own experience with a catastrophic claim, in which a woman who had just given birth became pregnant six weeks later. Due to limitations of the human body, she was forced to give birth to a premature child at the 23 week mark, and the birth resulted in 1.8 million in claims toward the Black and Decker medical plan.
That’s worth a second look…
by Fred Fortin
April 6, 2008 at 9:49 pm · Filed under Policy Makers, Consumer Engagement, Health IT, Proactive health management
In a soon-to-be-published article, Ruth Gardiner argues,
we are seeing a shift from the ‘informed patient’ which has resulted from improved access to healthcare information, primarily from the Web, to the ‘participative patient’ as we move into Web 2.0 territory.
This is a “major turning point” according to Gardiner, “that could present greater challenges for healthcare professionals, organizations and the patient or client.” How will providers adapt? What impact will Google et al. have in their attempts to “own” the health care consumer? And how will even newer information technologies — such as digital video change the healthcare landscape, she asks.
The distinction Gardiner makes is an important one. The first notion is almost universally perfunctory now: the ‘informed patient’ is either the product of the patient’s own initiative, or a point in the patient care process where he or she gets to sign the consent and waiver form. In short, a tolerated but necessary legal exercise.
But the second notion implies that attention to the patient’s awareness of the relevant information and risks at the proper time is an essential and critical component of the total care experience; a mindfulness and respect for the patient exhibited at every point, by every care provider.
Gardiner puts to question the impact of information technologies on this aspect of medical care. And to a certain extent she is right to ask, since, in many ways, the push of information technology has brought us to a place where it is now possible to serve the “participant patient” in ways that could not have been conceived only a few decades ago.
by Scott MacStravic
September 17, 2007 at 9:31 am · Filed under Health Plan/Payer CEOs, Group Practice CEOs, Prevention and Health Promotion, Employee Health Management, Proactive health management, Health Management
Deselecting prospects for HM interventions can occur before they are invited to participate, by simply deciding that particular people who are eligible for a given intervention do not promise sufficient potential risk/reward ROI for the cost of the intervention considered. This is really no more than careful selection of whom to invite in the first place. The more serious de-selection challenge arises with people who have enrolled, but do not participate, cooperate or change their behaviors/lifestyles enough to deliver the predicted value.
Many such participants will de-select themselves, by simply not responding to invitations to participate, or dropping out once they are enrolled in a particular HM intervention. Many will drop out if they do not participate, or make no changes that would deliver any benefit to them anyway. But when there are incentives for participation, some may continue to do the minimum needed to qualify for incentives, but not make the changes needed to either gain personal health benefits, or deliver any value to HM sponsors or providers.
When participants choose not to enroll, or when they de-select themselves, sponsors and providers may decide to seek to “recapture” them through new persuasive communications, incentives or both, assuming their predicted value is great enough to warrant added effort and expense. If participants do not show any signs of achieving close to their predicted value, such as not participating with coaches, not opening e-mail, making website visits, and particularly if not making the kinds of lifestyle/behavior changes needed to deliver value to sponsors, then the sponsor or provider may choose to “fire” them.
This should obviously be done carefully and politely, with reasons for doing so made clear, along with the fact that their dropping out will save them time and save the sponsor effort that is now being wasted. Such a notice may be enough to spur some to re-energize their participation, but many will probably be happy to drop out if they are not gaining any incentives. It is for this reason that incentives should be linked to clear demonstration of behavior changes, rather than merely going through the motions to qualify.
For members of insured populations, insurers will clearly worry about losing the members who are “fired” from an HM intervention. They may prefer that members who do not respond well to one HM intervention be offered another they might respond to better. With employee participants, the potential of a loss of an employee over being dropped from an HM intervention may not be pretty low, but employers may object to the idea, or prefer offering non-responders other options as well.
Since the average participant in an HM intervention will have five or more health risk behaviors, risk conditions or chronic diseases, the option of offering another option might make sense anyway. It may be that the behavior changes for one risk are significantly more difficult for a given participant to make than the changes required in another. Non-responsive participants may be offered the option of selecting from among as many HM options they are eligible for, in which case, their act of making a choice, rather than being “recruited” to the one the sponsor/provider prefers may also help engage them better in the new intervention.
De-selecting or switching non-responsive participants is at least a logical option to consider when trying to optimize the overall ROI from a given HM intervention and overall investment. Of course, when incentives are based on behavior changes, or even better health improvements, the lack of any gain by non-responsive participants in one HM intervention may make them more likely to drop out, or even request another option. When incentives are based on improved productivity and performance by employees, the prospect of added pay for performance can be the most powerful incentive for enrollment, cooperation, and behavior change.
There are also intrinsic benefits to participants that may affect both their willingness to enroll in HM interventions, and their persistence therein. By calling participants’ attention to behavior changes they have succeeded in making, health improvements that have resulted, etc. HM providers and sponsors may increase participant retention as well as cooperation, and thereby decrease reliance on extrinsic and expensive incentives. Intrinsic benefits also do not tend to diminish in impact over time the way extrinsic ones do. Personal health and life quality benefits often arise so gradually that participants may not notice them, or be aware of how significant they are unless asked about them, reminded of progress and their significance.
The combination of selection of HM targets based on predicted risk/reward potential, graduating HM interventions based on such potential, and careful de-selection or intervention modification among those who are not responding can significantly improve providers’ and sponsors’ success rates and ROI. This requires additional investment in predictive modeling, and planned adjustments during participation. It also requires tracking specific behaviors, health status, and cost/productivity/performance changes that may risk violating HIPAA regulations, as well as added costs, but careful use of selection and de-selection or offering options should more than cover such costs.
by Scott MacStravic
September 17, 2007 at 9:25 am · Filed under Health Plan/Payer CEOs, Prevention and Health Promotion, Proactive health management, Health Management
In low-cost health management (HM) interventions, mainly those that use computer-generated health risk feedback, online or web-based “self-service” coaching for all participants, it is generally the case that the more participants the better. In such cases, costs to HM providers are fixed, and fees to their clients are usually set on a flat fee/per population basis. So adding participants does not add to costs for clients, while adding to at least the potential for added benefits.
In such cases, the only basis for selecting HM participants is the match between a particular intervention and the targeted persons identified as potentially benefiting themselves and their employer or insurer by participating. Many may benefit from participating in more than one HM intervention, since the average person typically has more than one health risk, chronic condition, or productivity/performance factor affecting each.
But when costs to HM providers and charges to clients vary significantly by the number of participants in a given intervention, careful selection of targets and of the most cost-effective/efficient ways to secure their enrollment, participation, cooperation and completion of the intervention can be essential. If the intervention is the same across all participants, selection should focus on ensuring that as many of those targeted for participation as possible have predicted risk/reward levels greater then the costs they add to the intervention.
This is good practice for both HM providers and their clients. If costs increase per participant, the best way to ensure that the overall ROI ratio and net economic gain or ROI amount of each intervention are acceptable or admirable is to ensure that as many participants as possible have individual ROI ratios and amounts that are at least positive. This is true whether the type of intervention is the same for all participants or varies by their predicted risk/reward potential.
Individual customers of any business tend to include “most valuables” that generate great profit, “profitables” that at least contribute some profit, “marginals” that cover the fixed costs of serving them but no profit, and “losers” that detract from profits. Individual employees can be arrayed across a similar scale of value to their employers. And HM eligibles should be identifiable in terms of the same varying levels of risk/reward potential using predictive analytics.
When those eligible for particular HM interventions are identified through claims analysis or medical records, or through screening tests alone, the risk/reward potential is likely to be based solely on their past costs to insurers or employers. But if health risk assessments (HRAs) are used, they can add far more information about individuals’ probability of responding well to HM interventions, plus their potential for improving their value to employers, when they are employees.
The key is to identify existing and validated HRAs that determine individuals’ attitudes and perceptions, as well as risks and past and current costs or productivity/performance impairment levels. These may assessments should identify their levels of concern about and motivation to change their health behaviors and risks, or manage their chronic conditions and the behaviors that can accomplish that. They may also identify where people are in stages of readiness to change, in internal vs. external locus of control perceptions, perceived barriers to change, etc. – whatever individual characteristics have been shown to affect their probability of responding well to HM interventions.
The combination of individuals’ past and present costs and impairment levels with their probability of changing these in the immediate future will determine their risk/reward potential. This potential can then be used to:
- select targets for a one-size-fits-all intervention
- determine what sponsors or providers can afford to spend on incentives and efforts to promote their participation
- graduate interventions to match the risk/reward potential of different cohorts or individuals among those eligible
Since the efforts expended by HM providers or sponsors, as well as any incentives used to entice their participation, cooperation and completion of interventions add to the costs of such interventions, these costs have to be factored into both selection and graduation processes, to ensure that the risk/reward potential of participants exceeds their predicted costs. And when a combination of general health/wellness promotion, risk behavior, risk condition, and disease management interventions are planned, the potential per individual will vary widely across those eligible.
General health/wellness promotion tends to have the lowest potential in terms of healthcare/insurance costs, though it can reduce worker injuries, for example. And it can include focused efforts to reduce productivity/performance impairment factors, such as lack of sleep, hydration at work, poor nutrition, etc. that may also add to healthcare costs. And it can improve employee morale, energy levels and other health and motivation dimensions that may move participants into the range of “positive presenteeism”, where they go beyond expected and “normal” productivity/performance levels and value to employers.
One of the challenges in this type of intervention, aimed at preventing people from getting any risks, or increasing the numbers they already have, is that there is no change to use as the basis for predicting risk/return benefits. Only the non-emergence of risks represents the source of benefit and ROI. Fortunately, there is plenty of experience with populations and their tendency to add risks if left “unattended”. The value of keeping people from moving to a higher risk category should always be added to the value of reducing them to a lower risk category.
For example, in one study, the proportion of people in a low-risk category (having 0-2 risks) who moved to the medium-risk (3-4 risks) level in the following year was 13.7%, while 2.2% moved to high risk (5+ risks). The added cost of moving from low to medium risk was an increase of 26% in healthcare costs alone, while the added cost of moving to high risk was a 65% increase. Moving from medium to high risk meant an increase of 31%, adjusted for inflation in overall costs. [D. Eddington & S. Musich “The Case for Low-Risk Maintenance” Absolute Advantage 2:5 2003 22-25 (www.welcoa.com)
The benefit of reducing risks from a high to a low level was a 37% reduction in healthcare costs, while remaining at high risks meant a 21% increase. So the total benefit of reducing a person’s risk from high to low amounted to avoiding an 88% increase in costs altogether, counting inflation of costs. The University of Michigan Health Management Research Center is an excellent source of information on the financial benefits of reducing health risks in employed populations. (www.hmrc.umich.edu)
This Center has also examined the productivity impact of risk reduction and increase. In one of its studies, it found that the addition or reduction of a single risk was an average of 1.9% loss or gain in productivity due to presenteeism, or impairment among those at work. [W. Burton, et al. “The Association Between Health Risk Change and Presenteeism Change” JOEM 48:3 2006 252-263] By multiplying such an effect by the average annual compensation of workers, roughly $50,000 nationally among employers who engage in health management, HM providers and clients can gauge the value, e.g. 1.9% of $50,000 = $950.
The value of disease management varies dramatically by the disease in question, in addition to across the individuals who have such a disease. Congestive heart failure patients, for example, can often have their healthcare costs alone reduced by 30-50%, while diabetes patients may save only 5-10%. People with depression rarely save on healthcare costs, but can save dramatically in reduced productivity/performance impairment, from 10-25% in many cases. This kind of potential value can often cover DM costs of hundreds of dollars a month, since 25% of $50,000 = $12,500 a year.
Careful selection of individuals to target for HM interventions, together with prediction of the risk/reward potential of each can make a dramatic difference in the ROI ratios and amounts achieved by such interventions. The prediction of such potential should be an inherent feature of HM strategies and programs, though it is most important when the costs of such programs vary significantly by the number of participants. Such prediction also enables informed decisions on incentives and graduated interventions, to make ROI even more likely to be gained.
by Nick Jacobs
September 7, 2007 at 10:52 am · Filed under Prevention and Health Promotion, Disease Management, Proactive health management
Following up on Tony’s post the other day…
Remember the politically insensitive Vaudeville lines where the first comedian says, “You’re fat,” and the second comedian responds, “Yes, but you’re ugly, and I can lose weight . . . “ Well, the truth came out a few weeks ago when the President’s Panel on Cancer very strongly pointed out in a politically insensitive manner that we have done nothing of substance to alter the obesity and smoking problems in the United States.
In the past I have written about the incredible insensitivity that this administration has demonstrated toward children’s health care needs in this country. President Bush has been quoted as saying that he would never support a major increase in the tax on cigarettes . . . even if it was to provide additional care for our children. He also continues to dig in against any legislation that Congress is proposing to further regulate tobacco.
In a recent Op/Ed by Todd Sloane in Newsweek, he discusses figures that create a gripping picture of decimation. Cancer cases in the next fifteen years are projected to go from about 12 million to nearly 18 million and obesity is seen to be one of the significant contributors to these figures. Sloane goes on to quote that nearly half of the two thirds of American adults who are overweight are obese and that obesity contributed to about 112,000 deaths. At the same time, about 440,000 Americans die from tobacco related illnesses.
The most startling figure presented was that, since 1950, lung cancer deaths among women have increased by 600%.
The report went on to delineate the fact that there is a “lack of political will” to fight either of these horrendous trends.
So, if preventative medicine is not rewarded, fruits and vegetables are not subsidized (remember Reagan ketchup in school lunches), and tobacco taxes are ignored, life as we know it will continue to end prematurely for tens of thousands of us . Vending machines are still stocked with junk, schools are not changing menus and physical education continues to be missing in action.
Come on. Someone needs to stand up and be counted here.
by Scott MacStravic
August 15, 2007 at 2:55 pm · Filed under Policy Makers, Health IT, Prevention and Health Promotion, Proactive health management
I was struck by what I assume was an unintended connection between two recent posts to this blog – one by Nick Jacobs on “Change the World”, and the other by Fred Fortin on “Miscellany, Messiness and Medicine”. To these I add an article noting a plan for fixing health care, published in WIRED in May [K. Philipkoski “Intel’ Andy Grove Pitches a Plan for Fixing Health Care” Wired.com May 2, 2007]
Andy Grove sees information technology as having a huge potential in fixing health care, along with efforts to “shift left” such care by moving it toward care that is not expensive, does not require hospitals and other institutions, but empowers consumers and innovative approaches to serving them such as retail clinics to take on otherwise highly expensive care. High-tech gadgets can be used to monitor and manage the care of chronic disease and elderly patients at home, keeping them out of institutions.
Retail clinics can provide care in inexpensive “kiosks” or inexpensive retail and drug store space, and keep people out of hospital emergency rooms. His other suggestion is the use of information technology in the form of electronic medical records which could be made portable all consumers carry their own with them at all times, making access to them when needed universally available, to ensure the quickest and best diagnosis and treatment of patients possible when they need hospital or physician care.
For some reason, however, Mr. Grove has little good to say about “prevention” as a way to fix healthcare, despite wide agreement among both health gurus and presidential candidates that prevention is an essential element for both reducing healthcare costs and enabling universal insurance coverage. His objection to prevention is that it requires changing individuals’ behaviors, and he doesn’t think we have the capacity to do this yet in a cost-effective manner, although it is, theoretically, at least, in his view “…absolutely the right answer…”.
I can only conclude that Mr. Grove, as CEO of Intel, has not yet encountered the applications of information and communications technologies to prevention, rather than traditional physicians’ annual checkups, immunizations, and usually unsuccessful or overly expensive coaching for patients. The search for cost-effective prevention has already concluded that technology innovations are essential to its realization.
Fortunately, such innovation is well under way and already in use. While I know of no healthcare organization, in the traditional sense, that uses such innovations, the new brand of organizations usually deemed wellness, risk and disease management vendors are well underway. Examples such as HealthMedia, Inc. and Thomson Healthcare, both in Ann Arbor Michigan, are already using online health risk assessments (HRAs) and customized online feedback therefrom to promote wellness, prevent or reduce risks, and manage chronic diseases.
They have also recognized that commercial or government insurance plans are not the best customers for such innovations. Employers are, because they gain dramatically more positive impact from having healthier employees than do insurance plans from having healthier members or beneficiaries. Employer gains include the full range of insurance costs combining healthcare, workers compensation and disability. Moreover, healthier employers are absent less, produce more output and perform better across the balanced scorecard of business performance, realizing many multiples of sickness care cost reductions.
Instead of or augmented by physical examinations and screenings, online HRAs can be inputted directly into computers and automatically translated into individualized feedback, recommendations and continuous coaching, for a few dollars per employee per month in many cases. These same HRAs can be used to estimate the productivity and performance value, as well as the extent of employee behavior changes and health status improvements.
The technologies used by most vendors, as well as most traditional healthcare organizations, have tended to emphasize, if not be exclusively devoted to professionals interacting one-on-one with patients in managing disease. This is often cost effective, when the right patients, diseases and professionals are involved, but usually quite expensive. Witness the costs of fifteen vendors and healthcare organizations involved in a Medicare DM demonstration project whose costs per participant ranged from $80 to $440 per month! and whose effects were generally negative in terms of savings vs. costs.
As far as I know, none of the new-technology-enabled approaches to affordable prevention have been tried with commercial insurance plans and either Medicare or Medicaid beneficiaries. It may be that vendors who employ such technologies are focusing on employer clients whose pockets can be more generous, given their already demonstrated significant savings, even without counting the full economic benefits of employee health.
In any case, it would be a shame to characterize the entire armamentarium of “prevention” as not yet cost effective. The new information and communications technologies available include many that are indeed “messy”, including consumer-directed communications with each other in support groups, and by the full array of wireless technologies, not merely the ones most providers seem to have tried. And this approach to prevention still does have the capacity to “change the world”, since it can be used world wide as even underdeveloped countries are finding at least some of its technologies affordable.
by Nick Jacobs
August 15, 2007 at 9:09 am · Filed under Policy Makers, Prevention and Health Promotion, Population health management, Proactive health management
Thanks to the Associated Press, our national egos can rest uncomfortably knowing that our health score as a nation continues to plummet. You’d think that at over $2 trillion in health care expenditures nationally or nearly $6000 per capita, the score card would be better, but we have now dropped to 42nd in life expectancy worldwide.
Drunk drivers took the lives of almost 17,000 on the roads, and an estimated 510,00 are injured annually from alcohol related accidents. That works out to about one person per minute. Another part of the problem may be because we have so many guns. Every year it is estimated that more than 30,000 people are shot to death in murders, suicides, and accidents while another 65,000 suffer from gun injuries in the United States. Defective automobile tires may have killed about 103 people over a number of years, but firearms kill about 85 people every day in this country. How about obesity? The AMA estimates that nearly 300,000 people are dying annually due to obesity.
We may also rank 42nd because we have not used enough sun screen, have had too many household accidents and because the vast majority of medical centers are not dealing with their infection rates. (The national average is a 9% infection rate, our medical center has been below 1% for nearly a decade. They can be controlled.)
The bottom three spenders in healthcare dollars annually are the United Kingdom, Japan and Finland and Finland, Luxembourg and the U. K. are at the bottom as a percentage of GDP. Guess what countries are included in the list that do better than the United States? Remember, 41 countries are helping their citizens live longer than us and a few include: Finland, Luxembourg, Japan, the United Kingdom and Cuba?
The AP article pointed out that the country with the longest life span was Andorra? Andorra is a tiny country between France and Spain where the people live nearly seven years longer than us. Of course, the contrast to Andorra is Swaziland where the average person lives to be about 34.
Interestingly enough, after having spent time in Europe recently, It seems relatively apparent to me that the reason we are under performing so dramatically is that we don’t invest in preventative care, don’t really embrace public health and have never had a health policy for this nation. Only about 4% of our trillions goes to prevention in this country.
Please forward this blog to our public officials.
by Scott MacStravic
August 15, 2007 at 8:58 am · Filed under Health Plan/Payer CEOs, Hospital and Health System CEOs, Pay-for-Performance, Proactive health management
The majority of pay-for-performance systems offer bonuses for healthcare providers that adhere to treatment guidelines and best practices. In many cases, there are specific outcomes included, such as patient satisfaction, cost reduction, and reduced infections. This “carrot” approach is intended to reward providers that improve or maintain high quality and efficiency, as defined and measured by specified criteria.
But just as is the case with P4P systems that apply to individual behaviors and health status, there are a growing number of “sticks” being added to systems that apply to providers. Medicare, for example, has frequently included “budget neutral” policies in its P4P programs, where the extra payments for high-performing providers comes out of the payments for low-performers, in order to keep the total payments the same as usual.
Payers are also beginning to refuse to pay for the care required to address “never events” in medical care, such as wrong-site surgeries. They argue that when providers cause costs to increase, often dramatically, by making serious errors in patient care, they should not be rewarded for such errors by getting increased payment over what would have been paid had there not been such an error. While this makes eminently good sense, and will generally not harm providers dramatically, given the rarity of “never events”, this policy could end up having dramatic impact, as the definition of such events changes.
If payors decide that providers should not be paid for what amounts to careless or unsafe practices, for example, rather than egregious mistakes such as wrong-site surgery, they could save significant amounts, while providers could be severely affected. Already lists of non-payable problems have been created that include quality failures such as decubitus ulcers in inpatients, for example. The case can certainly be made that such conditions should not occur, since good care should prevent them among bedridden patients, but the effects of non-payment would be far greater than for truly egregious errors.
A recent study, for example, found that hospital-based or “nosocomial” infections have cost between $200 million and $473 million in the state of Massachusetts alone. This includes extended inpatient stays, and additional costs of treatment for such infections. While the recommendation accompanying the report calls only for hospitals to publicize their infection rates, it would take little for payors to decide to include them among the events for which they will no longer pay. In such a case, payors could save hundreds of millions of dollars in dozens of states, and hospitals could be seriously hurt as a result. [“Infections Acquired at Massachusetts Hospitals Cost up to $473M Annually, Report Finds” Kaiser Daily Health Policy Report Aug 10, 2007 (www.kaisernetwork.org)]
Even publishing the different performance levels achieved by providers could severely damage low-performers, by causing patients, providers, and payors alike to avoid doing business with them. This has been one of the expectations of the “Buy Right” concept originated in the 1970s, though the effects of publishing performance data has, thus far, been minimal. With more costs and responsibility for sickness care use management being shifted to consumers, and easy Internet access to performance data, the effects of publishing comparative performance may become significant in the current and future system.
Any “punishment” of providers for poor performance will have at least two effects: 1) making it that much more essential for them to correct mistakes and improve poor performance; and 2) depriving them of resources that may be needed to do so. With many hospitals and physician practices operating at or below minimal survival levels in terms of revenue vs. expense, significant cuts in payment could easily drive them out of business before they are able to improve.
For those who favor a “free market” approach to healthcare reform, this would be a consummation devoutly to be wished, rather than a negative effect. But when poor performers are the only available or accessible source of care for particular communities or sub-populations, their going out of business would not always be an overall improvement in their healthcare system. With individuals, “capital punishment” is reserved for relatively rare and truly egregious behavior, not merely lower than average performance, but with healthcare organizations, there could be a far higher percentage of providers so “punished”.
There is also the risk that payors could find the refusal to pay for “never” events could become overly attractive, since it reduces their costs and improves their profits. In such a situation, the free market may favor payors too much, and cause overly aggressive definitions of such events, and even greater reductions in payment levels, since payors are competing with each other to keep their costs down. It will always be a temptation for payors to choose not to pay enough for providers to survive, witness the severe underpayment compared to providers’ operating costs that is already the case for Medicare and Medicaid, where these payors can simply dictate how much they will pay.
While carrots and sticks are often effective combinations in achieving improvements in individuals’ behavior and organizations’ performance, the stick carries with it some side effects that should warrant extreme care in its use. While there may well be a number of hospitals, as well as physicians and other practitioners that should not continue to deliver care, the potential that “No Pay for No Performance” could do significant harm, as well as good, should not be ignored in either public policy or private payment.
by Scott MacStravic
August 9, 2007 at 9:10 pm · Filed under Hospital and Health System CEOs, Business of Health, Hospital Administration, Proactive health management
The three earlier challenges for traditional healthcare providers in health management (HM) pale beside the greatest challenge facing both providers and customers thereof, namely counting the benefits, as well as the costs of HM investments. While sickness care has devised thousands of metrics for what is accepted as good practice and outcomes for its efforts, the same is nowhere near the case for HM. Its history has included a lot of over-counting and under-counting of benefits, in particular, though costs are occasionally overlooked as well, particularly costs to HM participants.
The challenge is greatly complicated by the sheer number of consequences that HM can have, the complex “causal chain between particular HM interventions and such effects, and the difficulties in measuring many of these effects, particularly the beneficial ones. It is no wonder that early HM efforts focused almost entirely on reducing sickness care costs, since these were readily measured, and it seemed thoroughly logical and credible to attribute reductions therein to HM interventions.
But while sickness care, along with workers compensation and disability costs of “unhealth” for insurers and employers have long been counted, even the simple out-of-pocket financial cost savings that HM participants gain have more often been overlooked. Smokers who quit can save as much as a thousand dollars a year by not purchasing tobacco products, for example, to say nothing of the out-of-pocket savings for those able to overcome substance abuse problems.
Since the first objective of all HM initiatives is to change the current behavior of individuals and families, the first counting problem arises because there are few reliable, simple, and inexpensive ways of monitoring such changes. When participants have financial incentives to make such changes, there is usually the risk that they will report them as made, rather than make them, or al least exaggerate the extent of the changes they make. Aside from some chemical checks on behaviors such as alcohol, drug and tobacco use, all of which cost money for testing, there are few objective measures of behavior changes.
Monitoring objective health status changes are also likely to require testing, though this may involve no more than simple monitoring devices, from scales to check weight to simple blood pressure monitors, blood sugar meters, etc. Many other metrics are routinely part of annual lab tests that measure twenty or more indicators at relatively low costs, but still add to overall intervention costs. At the other extreme, some continuous monitoring devices can add hundreds of dollars a year to HM efforts dealing with chronic diseases, though such frequent monitoring is also good for managing and evaluating results.
It is when counting attempts to include workplace productivity and performance effects that it becomes really challenging. Except for a minority of industries and jobs where individual employee output quantity and quality are routinely measured as part of management and compensation, most counting of these effects involves estimation. Estimates may be based on team objective measures, or individual self-reports, but both are suspect. Team measures may accurately reflect total output, while missing the contributions of individuals outrageously. Self-reports, of either current health-related impairment or improvement may be “honestly” biased by low levels of self-awareness, or by the desire to look good, get rewards, etc.
When workers in jobs where their output could be objectively measured, in one example, they reported themselves as having been impaired by an average of 20% due to migraine headaches, far greater than the objectively measured effect, which was only 8%. [G. Pransky, et al. “Performance Decrements Resulting from Illness in the Workplace” JOEM 47:1 Jan 2005 34-40] In any case, it would be a strange coincidence if self-reported impairment levels were identical with actual objective measures.
This means that self-reported declines in individual productivity or performance have to be converted from their estimates to whatever objective checking shows corresponded to self-reports. For the call center representatives in the preceding example, the “conversion ratio”, from self-reported to actual impairment is 0.40 to 1.00. Unfortunately, while the average conversion ration works well, once it is determined, for each employer or team where such a conversion is used, for individuals in pay-for-performance (P4P) situations, an individual conversion rate would be needed to apply in individual-based P4P compensation.
Fortunately, healthcare providers already have a strong motivation to develop the best gauges for individual, or at least team productivity and performance, thanks to the growing number of P4P systems that apply to them, and the growing amount of bonus or other performance-based revenue to which they are subject. Since performance has to be measured in order to be managed, the measurement system that is used for management should be applicable to monitoring and evaluating HM interventions, as well as other efforts intended to improve workforce performance.
In fact, once healthcare providers master performance measurement for P4P reasons, they will be in an excellent position to integrate all employee-focused investments, including all benefits, aimed at improving their performance. This should make HM efforts more efficient and effective, when they are combined with employee training and development, EAP programs, and other efforts aimed at improving the performance and retention of employees.
Moreover, healthcare providers may be able to become leaders in performance measurement, management, and integrated benefits strategies, which could be added to their HM expertise as a competitive distinction relative to specialized HM suppliers. In most cases, such suppliers have to rely on either HM participant self-reporting, or on their employer clients’ own systems for measuring performance, while healthcare providers can afford to develop their own affordable and effective measurement systems.
We are only at the beginning of addressing the counting challenge, particularly when it comes to positive market and revenue impacts, such as improved product and service quality, customer satisfaction and loyalty, new business and similar effects that have been traced to HM efforts by at least some employers. And if healthcare providers master the art and science of counting the full range of HM effects, they will not only be able to rise to the top in terms of their own internal HM applications, but in their marketing of HM programs to other employers, as well.
by Nick Jacobs
July 5, 2007 at 2:56 pm · Filed under Proactive health management
Why do national statistics indicate that thousands of people are killed each year due to medication errors in hospitals? Because they are. If pharmacists are careful, you might ask, how does this possibly happen?
Well, there are pharmacy techs and pharmacy aids, and there are poorly written prescription orders, and busy RN’s, and LPN’s. There are inappropriately registered patients with similar names. There are emergency room techs or nurses or physicians that sometimes miss or misunderstand what the patient is saying about the drugs they take at home. There are patients who don’t tell us the entire story, i.e., like the recreational drugs that they take, just for fun, or are clueless about their drug list. |
The story doesn’t end here. There are exhausted employees who misread or misinterpret the prescriptions. Then there are just intellectually challenged employees who don’t bother to pronounce what they read, don’t pick up what was ordered from the drug cart, and don’t check the patient to see if they are giving the correct drug to the correct patient.
Don’t forget the hassled administrator who has to find a way to keep the hospital open and running. They have a committee that adopts a formulary of permitted drugs for his or her facility based on price. Are they always the same drugs that the patient has taken at home? No. Are they sometimes-similar yet different drugs? Yes. Do they interact differently with the patients other drugs? Sometimes. Do the patients sneak in their herbal medicines and laxatives and antacids? Yes.
Do you get the picture? It is common knowledge that if you take five or more drugs per day the chance that they will interact with each other in your body is 100 percent.
What Can You Do?
For goodness sake, don’t be afraid to ask. Don’t be afraid to challenge. Don’t be afraid to question. In fact, ask, challenge, and question. You need more people caring for your personal health than your doctor. You must be a player. Your family members must be players. Your loved ones and even your enemies can help. Don’t just accept everything you hear or see. Sometimes top notch, seasoned veterans make mistakes, too. In fact, they all do. Mistakes do happen.
So, ask questions. Ask for verification. Ask to speak to a pharmacist. Ask for an explanation. Explain that the drug being given to you because of some hospital formulary didn’t work the time you tried it at home, or that it made you sick, or that it was the one that interacted with your fish oil that made you break out in hives.
Challenge and challenge again.
It is, after all, your life.
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