Archive for Variability in PHM Series
by Scott MacStravic
May 12, 2008 at 11:08 am · Filed under Employer CEOs, Health Plan/Payer CEOs, Business of Health, Variability in PHM Series
Given the large number of PHM suppliers already available, and growing numbers of hospitals, physicians, and other suppliers joining still, the number of options across the seven elements of PHM is enormous. If there were as few as five options available for each element, to say nothing of different mixes of elements for the same purpose, there would be 75 = 16,807 different mixes of the options to consider. In practice, of course, insurers and employers, like consumers when faced with too many choices, first strive to limit the number to a manageable few, perhaps no more than five sets.
This may be accomplished by looking for particular vendors, as outsource suppliers or at least basic models for a DIY option. ON the other hand, some PHM investors have divided up the strategy, and even particular interventions among multiple suppliers, using one for the assessment element, and others for interventions, or one for interventions, and another for evaluation. If each different supplier offers different options for each element, that could greatly increase the mix of options available, even if only a few suppliers are considered. Moreover, suppliers are increasingly adding numbers and types of interventions, in order to be able to offer options graduated in cost and effectiveness to the risk/reward potential of different programs and participants.
One development should reduce the difficulty of making choices in this “overstocked” world. Predictive modeling is improving in its accuracy all the time relative to the risk/reward issue. And since different element options, as well as different suppliers, bring with them different charges and typical costs for their clients, these may more accurately be compared to the risk/reward of the population under consideration, and for targeting prospective participants, thereby improving the chances of investments turning out well.
But the biggest boon to payers will come only when sufficient studies are made of the relative cost and returns on investment of the methods available in the market. It may take decades to do this for each option in each element, but it should not take more than a few years of concerted effort to compare different suppliers, along with more successful DIY efforts. The key is to retain a focus on results and returns, rather than be satisfied with thinking that investing in PHM is a good idea for its own sake.
Employers are probably somewhat more averse to “rigorous evaluation”, when it adds significantly to costs, than are insurers, at least as regards PHM investments. Managers spend relatively little time measuring things, as long as the key items in their balanced scorecard are going well. And if they are not going well, they may have to conserve their funds anyway, so would be unable to invest in measurement. Insurance, with its core competencies of underwriting and risk management, are at least more engaged in measuring things.
One study, for example, has found that only a small minority of employers even measure employee absences, much less presenteeism, despite the fact that both cost them a lot and can be reduced, with presenteeism many times more expensive and potentially rewarding than health-related absence alone. [W. Lynch & H. Gardner “Our People Are Our Greatest Asset… But No, We Don’t Track Their Performance or Attendance” Health as Human Capital, Dec 17, 2006]
Another found that only 38% of employers surveyed in 2007 measured the ROI at all from their PHM investments, though this was up from 23% in 2006. Many seem satisfied that it is an inherently good thing to do, or are confident that it is yielding a positive ROI, at least in the long run, and don’t wish to waste money proving it. [Wellness: Saving Lives and Money” 2007 Willis Survey (Willis America Employee Benefits North America (request: willisebsurvey@willis.com)]
Investing on faith alone will certainly not last long. Finance executives and governing bodies are sure to begin questioning at least any large investment in PHM, so CEOs and whoever else champions PHM should be prepared to prove the business case. In all the cases where efforts have been applied, the business case has been proven, and usually based on the most conservative figures, such as not including full productivity and performance benefits, or not including healthcare cost reductions. [S. Nicholson, et al. “How to Present The Business Case for Health Care Quality to Employers” Applied Health Economics and Health Policy, 4:4 2005 209-218]
Many results have no doubt seriously understated the full economic value of their PHM efforts because they neither counted productivity impairment or its “non-disease/risk” causes nor invested in interventions related thereto. There is ample evidence, for example, that conditions rarely included in disease management programs, including emotional disorders, allergies, arthritis, and chronic pain cause far more productivity impairment than to the most managed diseases. Moreover, poor nutrition, fitness/activity levels, stress, lack of sleep, poor hydration, for example, have been found to be far more valuable when corrected to productivity benefits than to reduced disease and healthcare costs.
We have a long way to go, and far too many choices of how to get there at the moment. What is needed is a concerted and coordinated effort — funded by governments, insurers, and employers – to evaluate the hundreds of options available, or at least screen for the most probably good ones, then rigorously evaluate these to identify and publish information on what are truly best practices. This may begin with what is already being done in sickness care, measuring and reporting who is best, or least bad in this far too expensive side of “health care”. It would make far more sense for it to be done where health can be improved, along with the quality of life for all people, as well as money can be saved by everyone who now pays for sickness care.
And one thing that is certainly clear, given the enormous variations in how PHM is designed, delivered, and evaluated, is that there is no way on earth to determine scientifically if “PHM works”. The definitions and applications of “PHM” are so variable, and of “works” equally so, making any attempt to arrive at a single conclusion about it ridiculous and impossible to begin with. The same has always been true of its separate components – disease management, health/wellness promotion, risk behavior and condition prevention and correction – in addition to whatever combination of these is included in PHM. It may be understandable that academic institutions and governments strive to “test the hypothesis” of whether PHM works, but any such attempt is doomed by the extreme degree of variation in what “PHM” is, and how “works” is measured.
by Scott MacStravic
May 12, 2008 at 11:06 am · Filed under Business of Health, Variability in PHM Series
To a great degree, the evaluation element in PHM comprises repetition of one or more of the assessments done for the initial baseline analysis. Ideally, this repetition, whenever it is repeated, will identify the changes of concern to payers, at least, while any added tracking of results used to sustain participants in their efforts and changes will do the same for the changes of interest to participants. But saying this, there will inevitably be the complication of making a “business case” that credibly demonstrates that the PHM strategy overall, and its individual interventions, have been the causes of the changes discovered.
Because the value dimensions addressed in EHM efforts and evaluations are major concerns of insurers and employers all the time, it is likely that they are doing something else to reduce costs or improve productivity and performance, beyond the effects of PHM interventions. And rarely would insurers, much less employers be willing to devote an entire year’s financial performance to the effects of a PHM investment alone. So generally speaking, the PHM evaluation should include some effort, at least, to separate out what changes in the evaluation dimensions it addresses that were probably affected by other efforts as well.
One of the best ways to track the effects of PHM is to analyze the tracking data that connects PHM efforts, such as HRA, screenings, and other information that was shared with individual participants in the HRA, coaching interventions used with participants in particular PHM interventions, and participant-reported behavior changes, health status biometrics of self-reports, etc. If this “value chain” of causes and effects can be shown to be connected as expected, that will make a strong case for attributing much at least of measured improvements to the PHM effort rather than “extraneous” causes.
Results such as “yes/no” behavior changes, (smoking, alcohol/drug abuse cessation) or “degree” changes, (increased physical activity, improved nutrition, longer average time slept per night, lower stress, etc.) should correlate with the amount and intensity of interventions, together with participant participation measures. In other words, the more the inputs by coaches and participants, the more the outputs in terms of behavior change, either a higher rate of yes/no changes, or a greater degree of change in continuous metrics.
In turn, the more the changes or progress achieved in behavior, the greater should be the improvements in biometrics, risk/impairment factor status, etc. that are supposed to be affected by each. This should also appear as a correlation between the different kinds of measures. And the measured biometrics, health/risk/impairment factor status should be well correlated with changes in healthcare cost, disability, and workers compensation costs, plus productivity and performance metrics or estimates.
The higher the degree of correlation across these changes, the more likely and credible the causal connection between them is. Only randomized and limited intervention clinical trials will meet academic standards, but demonstrated correlation should provide stronger evidence than simply records of changes in the outcome value, and certainly be better than the most popular approach, which among employers, at least, is not to measure ROI at all.
To determine ROI, of course, it is essential to factor in all costs as well as financial gains discovered in the evaluation. These will include all internal costs for payers who do it themselves, and is likely to include internal costs – for staff efforts, incentives paid, internal promotion of participation, team contests, etc.—as well. The costs imposed in the form of PHM supplier charges should be the easiest to identify, since they involve direct payments. When all financial benefits are compared to all costs, the ROI ratios and net earnings can be calculated.
There is a further complication in PHM, however, because, as is the case with some marketing expenditures, some portion of PHM costs should probably be treated as longer-term investments, rather than this year’s costs. While the published cases of long-term PHM results are few, they strongly suggest that when most of the participants in one year’s PHM efforts remain beneficiaries, members, or employees, the second-year results tend to be better than the first, and the third better than the second. The only case I know of where results were tracked for longer than three years found the fourth-year results essentially flat compared to the third.
This case, however, involved a cohort of employees, roughly 6000, who were continually employed and continuously participating in the PHM program for all four years. The pattern they produced, which was savings of $233 per participant in the first year, $375 in the second, $944 in the third, and $950 in the fourth, counted both medical care and disability/workers compensation expense savings, but not the productivity losses most likely associated. [G. Stave, et al. “Quantifiable Impact of the Contract for Health and Wellness” JOEM, 45:2 2003 109-117]
But chances are, when there are high turnover rates among health plan members or employees, the degree of improvement in that case would not be replicated. “Veteran” participants would too often be gone, instead of in their third or fourth year of improvement. And “novice” participants would have to replicate lower first-year results when it is their first year, even if the fifth or tenth for the payer in terms of PHM program investment. But as long as there is less than 100% turnover in the participant population, there seems likely to be improvement in annual results for successive years, at least up to three or four.
Improvements usually occur both because it takes time for participants to gain confidence in the own abilities. It also may take time for health status effects to occur. Fortunately for employers, many improvements in productivity occur quickly, so this should bolster clients’ confidence. One of the factors that take time is the influence that successful participants have on their peers who chose not to participate when first offered. The examples of successful peers, and the word-of-mouth reports spread by them, can be the most effective, and certainly least expensive approach to promoting future participation and improved results.
In general, it may be the third or fourth year until positive or at least desired ROI levels are achieved. Marathon Health, for example, a PHM supplier in Vermont, guarantees a 2:1 ROI, and often achieves 3:1, though not until the third year. The huge increase in the third year cited above may have meant no significant ROI was achBy contrast, HealthMedia is willing to guarantee the results it measures, though not ROI, for whatever period it uses in measuring them should its clients desire (per e-mail from Ted Dacko, CEO). HealthMedia only has two years* history with any of its results, and less than that for interventions introduced more recently, has not yet reported long-term results, but it makes employers who want quick results happy.
Whatever method for evaluation is used, it should meet at least standards for accuracy, reliability and validity, and avoid at least the most common errors due to self-selection bias and regression to the mean. Measuring ROI is clearly superior to pure credence that PHM works, or even relying on results others evaluate and report. The huge variety of methods currently in use, particularly in what is measured, together with the unavoidable costs of measuring many important sources of value from PHM investments, as well as the need to be able to take a long-term view of such investments, makes choosing an approach difficult, but definitely worthwhile.
by Scott MacStravic
May 6, 2008 at 8:14 am · Filed under Business of Health, Variability in PHM Series
Once targets are enrolled, i.e. as many choose to opt in or fail to opt out, there remains the next challenge of sustaining their participation, in terms of frequency and duration of interactions, cooperation in pursuing the intervention goal, and making behavior changes – and completing or continuing in the intervention, depending on which applies. There may also be a separate challenge to sustain the changes in behavior, health status, and economic benefit delivered, since relapses relative to the behavior change targeted, or “slipping” into risk levels of some other behavior or condition is common.
PHM suppliers and sponsors seem generally to rely on the same approaches for sustaining participation and behavior changes as they do in achieving them. Of course, the least expensive course may be simply to ignore those who succeed, and even those who do not, rather than attempt to enroll them in the same intervention again. Re-enrollment efforts may help for those who failed to succeed or still have plenty of room for improvement, or they may be offered a different intervention, linked by assessment to a comparable or at least appreciable level of risk/reward potential.
For those who have succeeded already, some kind of “maintenance” intervention may work, with a lower intensity and cost to sponsors. Or, since almost every member of the population is likely to have many more than one cost factor present, those who succeed in one may be invited to enroll in another, assuming there remains plenty of room for reducing one or more of the costs involved. It may easily be possible to enroll “succeeders” in both one maintenance-level and one new intervention, without reducing the effects of either.
The most powerful approach to promoting sustained and continuous participation, however, is likely to be paying significant attention to what the participant has gained through past and current efforts. When the PHM intervention involves personal coaching, by phone or in person, it should be an automatically included part of each interaction to check what progress each participant has made in changing behavior, improving health status, reducing healthcare use, or improving productivity/performance, as each perceives such changes.
Their perceptions, at a minimum, can be used to reinforce their confidence in success, and thereby their motivation to persist. If, in addition, an effort is made, such as by asking participants to track for themselves, the health-related quality of life, and perhaps “life asset” impact of their participation so far, and their success once achieved, this should reinforce their persistence even more. Progress and success in changing behavior, health status, and productivity or performance, for example, when participants have their recognition of these prompted or reinforced, should add to their self-esteem as well as self-confidence.
Moreover, such changes may well have measurable impact on their life asset of “wealth” as well as “health”. Quitting smoking can save literally thousands of dollars a year in costs of tobacco, for example. Enabling and reminding participants to track how much they are “wasting” while they still smoke, and “earning” while they remain abstinent, can reinforce their commitment. It has been difficult to get smokers to recognize how much their productivity and performance have been impaired by their addiction, but measured improvement in both can add to their sense of “talent” or performance asset as well. And if productivity/performance improvements have come with increased compensation, reminding them of that should help as well.
Participants, themselves, are most likely to be at least potentially aware of many life benefits they are gaining through participation, if they are asked about them, or encouraged to record them in a personal health log or diary. This may be kept private for the participant’s personal use, or shared with the PHM supplier, as each participant chooses. Those that the supplier knows about can be used to provide periodic summaries to participants, to remind them of their achievements.
For PHM suppliers or programs that include frequent assessments, and I know of one that performs assessments at 30, 90 and 180 days, for example, for some clients, at least, can use these assessments to provide reinforcement effects to sustain participation, if it is intended to be longer than 30 or 90 days for example, or sustain change if repeated again after a year. Having three opportunities for participants to report their progress means they will be reminding themselves every time they are asked. If they also keep a shared log of results, the supplier can add its own summaries to these reminders.
Others, including incentaHEALTH and Virgin Health, use self-service kiosks that employees can use to “check in” with weight and other biometric measures whenever they choose. Each participant registers a confidential ID when using the kiosk, so that each’s efforts and biometrics can be tracked, making periodic reporting of progress and achievement easy for PHM providers.
Of course, like so many of the elements of PHM, supplying extra reminders, even asking separately about participant progress and achievement, may add some costs, so balancing the positive effects or sustaining efforts with their costs will be necessary. I know of no PHM supplier that has separated out such costs and effects, so there is no experience that I know of to look at. But research has clearly indicated that the prospect of future benefits is an even more powerful stimulant for continuing relationships than is recognition of past benefits, so reinforcing both seems likely to help. [K. Lemon et al. “Dynamic Customer Relationship Management: Incorporating Future Considerations into the Service Retention Decision” Journal of Marketing, 66:1 Jan 2002 1-14]
With so little known about how suppliers and clients have sustained participation and success in the past, it is difficult to say how much variations in this element add to the overall variability of PHM strategies and interventions. But when efforts are used, or even if they become only gradually added to PHM efforts, they will likely add to the overall variability, since there is no evidence at all, as far as I know, of which methods work best.
by Scott MacStravic
May 6, 2008 at 8:13 am · Filed under Business of Health, Variability in PHM Series
The range of interventions that DIY payers and PHM suppliers have adopted in seeking desired behavior, health status, healthcare/WC/disability cost reductions, and improvements in productivity or performance is vast – as is the range of costs and charges for such interventions. The least intense, expensive, and unfortunately effective method of which I am aware, used by a vast number of single-problem suppliers, and ranging on costs from free to a few dollars per month per participant, is the automated, standardized e-mail prompt/invited website visit combination.
Since visits to websites cost sponsors little or nothing, and online e-mails reminding participant to make such visits add only a little more, these types of interventions can be marketed to consumers for self-paid efforts. I don’t know if any payers use them, though there is one fitness/weight loss intervention I know of that is sold to employer and insurer clients, for undisclosed fees. It is also marketed to consumers through their primary physicians, for as little as $19.95 per month.
At the opposite end of the spectrum are PHM interventions that rely on face visits for screening assessments and coaching interactions, which often include biometric measurements to track how well the participant is progressing, and supply evidence for incentives that are based on biometric improvements, such as weight, blood pressure, sugar, cholesterol, etc. Such visits can also be used to verify smoking, drugs or alcohol abstinence by checking for traces in the blood or urine.
The cost to participants in time to make visits to individual practitioners, or for practitioners to go to worksites for interactions, tends to make this method the most expensive.
When physician-practice-based interventions were used in one Medicare disease management demonstration project, they came with costs that ranged from $80 to $444 per month for each participant = $960 to $5328 per year! It is little wonder that out of the fifteen providers participating in this project, only two have been able thus far to produce results meeting Medicare expectations, and warranting a bonus to the providers for their efforts. [R. Brown, et al. “The Evaluation of the Medicare Coordinated Care Demonstration: Findings for the First Two Years” Mathematica Policy Research, Inc. 2007.
This example is likely to be an “outlier” in PHM generally, particularly for employers, since it reflects only medical care cost reductions, and high-cost elderly chronic disease patients. Another physician practice has reported offering diabetes DM services that only added $104 in costs to normal patient visits, for example, though it lost money by doing so, because only a minority of patients had insurance plans that paid anything at all for the services. [P. Mohler & N. Mohler “Improving Chronic Illness Care in a Private Practice” Family Practice Management, 12:10 Nov/Dec 2005 50-56]
Visit-based PHM programs are not necessarily the most expensive, however. In many cases, visits to physicians’ offices or retail medical clinics for other purposes can substitute for special trips for PHM interactions. And some retail clinics offer PHM services, at either low fee-for-service prices each, or in relatively low-priced (< $100) packages to patients who use them for sickness care as well, or may even come exclusively for PHM services. Kiosks used to monitor biometrics such as weight, blood pressure/glucose and cholesterol can be offered in retail clinics, enabling practitioners to monitor progress and coach at modest costs.
Many PHM suppliers rely on phone coaching, but both the frequency and duration of interactions can vary, as will the costs, as is the case for visit-based interactions. Phone coaches have to rely on participant self-measurement and reporting when tracking cooperation, behavior change, and biometric improvements, of course, unless participants have remote monitoring devices that automatically upload measures to practitioners, or medications adherence devices that monitor when and how often participants take them. And such devices are expensive in themselves, and normally only used in high-risk chronic disease(s) management.
Pretty close to the low-end website-based interventions are the wide range (ten at last count) of interventions offered by HealthMedia, Inc. (Ann Arbor, Michigan). It offers each of the ten at separate costs per population, but the costs tend to be quite low, particularly for large employers with thousands of employees. It also offers “book of business” data on as many as half a million employees who have participated in one or more of these interventions, so payers can get an idea of what results have been achieved in the past over a very large population. It collects only productivity data, combining absenteeism and presenteeism, but individual employers can supply or analyze their direct costs as well to complete savings calculations.
Its intervention relies on online or paper health risk assessments, which include risk/reward psychographics and productivity impairment questions. The answers to its 30-50-question assessments enable virtually total individualization of both the HRA analysis and feedback to HRA participants, and ongoing communications to each one that chooses to enroll in one of their intervention programs. And since even a question with only two possible answers, when there are 50 questions in the assessment, yield a possible 250 = 1 quintillion (fifteen zeros) possible combinations, so it is unlikely that many if any individual participants get the same communications.
The PHM market, generally, is moving away from the one-size fits all approach, toward customization in both content and cost of interventions. Graduating prospective participants into low, medium, and high risk/reward categories is common, with accompanying graduation in the intensity and costs of interventions tailored to each. Formerly high-end suppliers have merged with or acquired lower-cost suppliers, or developed their own lower-cost options, in order to compete effectively with the vast number of rival choices available. Lower-cost suppliers may create or buy capabilities that have better results, but require more intensive and costly interventions to achieve, to accompany their basic methods.
There is no way of saying what is the best choice for any payer newly entering the PHM market, since the problems and potential for each will likely be unique, as well the economic impact of particular solutions with their populations. The plethora of choices available is reflected in a generally dispersed market, where no one supplier is dominant, particularly since many employers and insurers are in the DIY category. In a recent study of employer-sponsored EHM efforts, for example, out of 96 employers who were investing in such efforts, no one supplier had been selected by more than three of the employers, counting those who were operating their own programs. [Wellness: Saving Lives and Money” 2007 Willis Survey (Willis America Employee Benefits North America)]
But the wide range of choices relative to how PHM services are delivered probably adds the most to the enormous variation in PHM choices, when all seven elements are combined.
by Scott MacStravic
May 5, 2008 at 2:33 pm · Filed under Population health management, Variability in PHM Series
Once members of the population have been targeted for participation in particular PHM interventions, the next step is to recruit as many as possible, or at least as many as will contributable value per participant, to each intervention. Such recruitment may actually be part of the assessment process, when members of the population have to be persuaded to engage in a health risk assessment or biometric screening process, for example. In any case, this element is yet another in which there is wide variability across the methods used by different DIY payers or the suppliers they hire.
One of the simplest is the “opt-out” strategy, in which every member of the population targeted is automatically enrolled without their involvement, once the targeting process is complete. They are usually individually notified of their enrollment, and invited to take whatever the first step in actual participation is. In some cases, they are automatically assigned a coach who will call them, or are automatically sent online or mailed information that is part of the intervention process.
This method often results in 90-95% enrollment, since only those who explicitly opt out are deemed non-participants. But the significance of their being enrolled lies in their active participation, cooperation, and changes in behavior, and the rates of each may be quite a bit lower than when other enrollment strategies are followed. The major two options with “opt-in” interventions are: 1) targeting each for a particular intervention based on the identified most promising PHM intervention for each; or less common 2) asking each target to choose among a number of options based on recommendations customized to each.
The enrollment process has to balance two considerations: 1) which intervention promises the greatest return to the investor; and 2) which has the greatest likelihood of delivering on that promise. The opt-out approach probably is strongest on the first criterion, and weakest on the second. Inviting targets to enroll in an intervention pre-selected for each is probably medium on the first and on the second criteria. The “self-determination” approach would probably be weakest on the first and strongest on the second. So it is a balancing act to select the best approach, and one or two may be tried before the best is identified in each case.
The “style” of the intervention and enrollment effort may also make a major difference to the numbers who enroll, participate effectively, and succeed. Early PHM interventions were mostly “one-size-fits-all designed and implemented by the sponsor or supplier. Increasingly, however, interventions are either partly or totally individualized, by either the person who contacts the target, or the automated online/mail communications based on analysis of assessment information. And the customized approaches tend to work far better.
Enrollment is also influenced by whether or not financial or other incentives are offered – for enrollment, participation, or success. Incentives paid for enrollment should achieve the highest enrollment, but not necessarily the highest levels of enthusiastic participation. Incentives paid for participation in or completion of an intervention may achieve high levels of participation, but not necessarily of success. Incentives paid for success may promote both enrollment and participation, particularly among those with the greatest confidence in their probability of succeeding.
Of course, people often delude themselves. Repeated studies have found, for example, that those with the highest levels of capabilities tend to underrate themselves, while those with the lowest levels overrate themselves. If the assessment process identifies targets based on predicted probability of success, it should be safer to pay incentives for participation, since those with low probability, despite confidence therein, would not be targeted. Those with high probability, but perhaps less confidence, would be encouraged to participate by the incentive, where they might not be as encouraged by a reward only for success.
Since incentives add to the costs incurred by insurers or employers, they have to be used carefully. PHM suppliers or peers who have used incentives, if they share their experience, may provide a basis for choosing which type and amount of incentive may work best, though each population is likely to be unique enough to make actual experience with it the best guide in the long run. The combination of customization and the right incentives is likely to work best, judging by experience in PHM so far.
by Scott MacStravic
May 5, 2008 at 2:33 pm · Filed under Employer CEOs, Population health management, Variability in PHM Series
The first purpose of the assessment process is to determine the size of the PHM challenge and of potential gains from implementing a PHM strategy. The assessment process is then also used in the evaluation process, to identify changes in measured “success” dimensions against the baseline data. But another key use of the data is to identify and select which members of the population make the most promising targets for participation in which PHM intervention, together with how many available interventions will likely justify their investment.
This step begins with identifying the baseline costs, both direct and indirect when applied to employee populations, linked to individuals and the health-related factors each has been found to have. Usually, without extensive multivariate analysis and predictive modeling, the “potential” is estimated based solely on the baseline costs. But the real predictor of potential economic gains lies in the particular PHM interventions that will be applied on a DIY or outsourced basis. And this information is peculiar to each PHM strategy, intervention, and supplier, rather than any generalizable average for PHM as a whole.
Moreover, when measurement problems such as side-by-side comparison “self-selection bias” and before/after “regression to the mean” effects have been overcome, there remains the inherent difficulty of predicting realistic potential cost impacts or other benefits based on past data. While past data may accurately describe the past of the very population to be addressed by PHM, it does not translate easily into predictions of the future. And while a given PHM supplier’s own past performance may be “statistically valid and reliable”, it may not be a sound basis for accurate prediction of results in a new population.
Within these limits, PHM investors and suppliers will want to determine which and how many population members represent the best risk/reward potential for which particular PHM interventions. Some suppliers and employers have employed a completely customized approach to PHM, where each individual either chooses each’s own goals or is assigned a coach who will customize the intervention to the individual’s mix of challenges, and address as many of each’s individual problems as possible. Experience suggests that individuals can handle more than one, but rarely more than two or three, so the number of problems to be addressed is normally small.
In many cases, there is one specific problem that is the basis for the PHM intervention to which members of the population will be invited. This does not mean that the intervention will have a very narrow focus, however, though it may. A smoking cessation program normally focuses exclusively on enabling participants to quit, but may have to address a wide range of perceived barriers and related issues, including stress and weight management along with the smoking behavior, per se. And diabetes disease management interventions routinely include attention to blood pressure and cholesterol levels, in addition to blood glucose.
While the baseline costs linked to individuals may guide targeting to some extent, the psychographic data indicating the probability that each will make a needed change and achieve success thereby, together with PHM suppliers’ demonstrated performance will add significantly to how “informed” the choice of targets can become. In many cases, the supplier may guarantee results for particular population segments, interventions, or success dimensions, making the targeting that much better informed.
Targeting necessarily includes consideration of how PHM suppliers charge, and what additional costs may be incurred by targeting more and particular segments or individuals for interventions. When the supplier charges on a “per population” of flat fee basis, it will not add fee costs to include as many members of the population in any given intervention, though most charge a fee for each separate intervention, which will multiply costs by the number of interventions selected, rather than the number of members participating.
When the supplier charges per participant, perhaps with graduated fees based on the risk/reward potential it determines for each and the different intensity/expense for the graduated interventions, it is the number of members targeted for each intervention that will represent the upper limit on fees. Moreover, payers will likely incur additional costs, per member, per participant, or even per successful participant (e.g. when incentives are offered for success rather than participation alone), which have to be considered as well. And while payers may recommend steps their clients should take that incur costs, the client will have the last word on which kinds of support it provides and what it will pay for what.
There will always be the unknown costs of participation or success incentives that will have to be paid, but this will typically be substantially less than the economic gains associated therewith. The past performance of the supplier applied to the baseline costs and economic value of members of the actual population to be addressed should help in ensuring that the client’s total costs are kept lower than the client’s benefits. Controlling the number of members targeted and number of interventions invested in based on risk/reward vs. predicted or controllable costs, is the best overall approach to take.
by Scott MacStravic
May 2, 2008 at 12:33 pm · Filed under Business of Health, Population health management, Variability in PHM Series
The sheer number of dimensions of the PHM challenge that are to be measured partly determines the relative difficulty, uncertainty, and costs involved, but the types of dimensions makes an even greater difference. One fairly common practice, however, is to count only the numbers of health risks, chronic conditions, or impairment causes, and link the number of such “factors” to the amounts of sickness care, disability and workers compensation (‘direct”) costs, and productivity or performance impairment (“indirect”) costs, for each individual in the population. This greatly simplifies the measurement challenge, but it may also mislead it.
The difficulty with assessing the specific factors of concern in PHM is that it is normally only possible to identify the overall direct and indirect costs that apply to each individual, together with the presence/absence or degree of the separate factors for each. This means that there is no basis for determining how much each individual factor contributes to the total costs for each, nor predicting how much might be saved through a particular PHM intervention addressing each. In practice, PHM interventions are customized to individuals, at least by what is usually one particular factor affecting each, though potentially for a number of such factors simultaneously, depending on the types of interventions available.
There are four common approaches to gauging individuals’ and populations’ risk/reward levels in terms of costs and economic gains: 1) past claims analysis, 2) health risk assessments); 3) biometric screenings; and 4) “psychographic” surveys. Champions for each tend to think theirs is the best approach, though there is likely to be added value in each of them that is not available in the others. The trouble is, however, that adding more methods adds to costs for insurers and employers, and to participating employees as well, which can directly threaten payers’ return on investment (ROI) by increasing the cost denominator. It can also indirectly threaten ROI by making participation either lower in numbers of people involved, reducing the economic gains achieved, or more expensive to achieve by requiring incentives to be paid, which will affect both numerator and denominator.
Claims analysis is often easiest, because the data already exist, in insurance plans or the employers’ own operational data. This will only apply to direct costs, unless the employer has a P4P system that involves already measuring employee productivity or performance in a way that can be applied to gauging their health-related impairment. Otherwise, only direct costs will be gauged by using existing data, and this will greatly understate the size of the problem and extent of economic benefit for employers, regardless of how much they pay their employees. The degree of understatement will be directly related to the amount of average compensation, with or without team/peer effect or value-based multipliers.
Claims analysis also carries with it the greatest risk of overestimating potential and actual economic gains. This is particularly true when individuals with high/outlier levels of sickness care expense in the baseline year will greatly influence the estimate of potential. Since such individuals are more likely to have lower costs in the following year, thanks to what is called “regression to the mean” than to have the same or higher costs in the next year, a major portion of the potential savings in the assessment, as well as the actual savings in the evaluation, will not be linked to the PHM intervention, but to unrelated “natural” causes.
There are half a dozen validated measures for employee productivity, which should also be fairly good estimates for performance, though I know of none validated for this added dimension of employee value. The book — R. Kessler & P. Stang (Eds), “Health & Work Productivity “, U. Chicago Press 2006 — offers the best compilation of these methods that I know of, and any one might be chosen for PHM use with some confidence. The trouble is that different methods tend to produce different results. Moreover, where comparisons have been made between employees’ self-reported impairment and objectively measured output, it has been found that employees often overstate their degree of impairment. So whichever method is used, there should be sound data available for converting employee reports into most probable reality.
In practice, many PHM suppliers use psychographic measures, along with, or even instead of the others. A few rely totally on individual’s self-reported perceptions and attitudes to predict their future costs, and the same may be used to predict their impairment. This can be inexpensive, where the survey is administered online, for example, and responses are automatically analyzed by computers. But the proof of all such assessments will be in the degree to which they lead to positive ROI based upon them. No merely “scientific” superiority should overcome pragmatic advantages.
Most suppliers who use employee surveys, whether health risk assessments or productivity/impairment questionnaires, can and usually do combine these with psychographic questions to gauge things such as employee motivation, commitment to change, confidence and self-efficacy in self-governance, for example. Answers to such questions, combined with the costs linked to each, can be used to identify and target the most promising individuals for inclusion in PHM interventions. Or they may be used to determine risk/reward segments, whose members will be assigned different levels of intensity and cost for the interventions they get.
There are equally wide variations on how identified risks are defined. “Depression”, for example, may be defined as a diagnosis, with only a small portion of the population identified as having a diagnosed “disease”, or as a “disorder” where a far larger portion is affected, or as an “emotional state” where an even larger portion would be identified as having it. It may even be defined as a general catchall covering all emotional problems and “down” feelings, including anxiety and stress, making it likely to affect the majority of the population.
The variety across internal PHM programs, as well as outsource suppliers, in the methods they employ to assess the baseline situation, which are typically repeated in the evaluation process, add greatly to the overall variability across the large numbers of options available to employers and insurers. We can hope that in the future, there will be improved identification of which are truly the “best practices” in PHM, though there is likely to be constant experimentation with new methods that will compete with even those proven best in the past.
by Scott MacStravic
May 2, 2008 at 12:31 pm · Filed under Business of Health, Population health management, Variability in PHM Series
The first basic split among PHM clients in terms of which dimensions of economic impact will be used in assessing problems and evaluating gains is that between commercial and government insurers on the one hand, and employers on the other. Insurers focus mainly, though not exclusively, on reductions in sickness care costs as the economic gains they are after, with many true “health” care costs part of the PHM intervention. They may also look at member/beneficiary health status and satisfaction with their PHM experience, as well as the duration of their “membership” in specific insurance plans.
Employers tend to look at a far greater number of dimensions, though these include the same ones that insurers look at, since they pay for such insurance, or if self-insured, pay the costs directly. But in addition to sickness care costs, employers worry about workers compensation and short- plus long-term disability (STD and LTD) insurance or direct costs as well. These may be as great as are insured sickness care costs, with some employees, though they are normally far less overall.
The really large economic benefits sought in PHM by employers tend to be that derived from reductions in absences and both productivity and performance impairment while at work (“presenteeism”). Economic losses from lost productivity/performance has been measured at levels two to five times as great as the sickness care costs associated with the many health-related problems that cause impairment. Moreover, employers may achieve economic gains through “positive presenteeism”, the potential that healthy and happy employees will contribute significantly more economic value than is “normal”, not merely “impaired” levels.
While productivity, per se, is the more frequently included dimension, compared to performance, there have been a few cases where specific benefits of improved performance have been addressed by employers. These include employee impact on customer satisfaction and loyalty, word-of-mouth impact on new business, and similar revenue-related benefits, in addition to labor cost reductions. And many employers have examined improvements in employee retention as adding value in the balanced scorecard dimension of “organizational knowledge” as well as reducing costs of replacing employees who leave.
The determination of which dimensions to include affects the complexity and costs of the PHM effort, whenever measuring these dimensions requires going beyond information already being collected as part of normal operations. This is less often the case for insurers, since claims data is frequently all they look at, though if they also consider member health status, satisfaction, and retention, for example, special efforts and added expense may arise in collecting such information.
With employers, complexity and costs of measuring dimensions of the PHM problem and progress in its solution are likely to be significantly greater than for insurers (though insurers may have to address these when they provide PHM services for their employer clients). Measuring workers compensation and disability expenditures is normally routine, already being tracked overall, though there may be added effort used in analyzing collected data so that it serves better to guide and evaluate the PHM effort, itself.
The biggest challenges will be in gauging productivity and especially performance impairment levels and their reduction, i.e. the economic benefits of improving either or both. While productivity is susceptible to both objective measurement in some cases, and validated estimates via surveys that collect employees’ and sometimes team supervisors’ perceptions of output, performance includes multiple dimensions of its own.
Of course, some dimensions of performance, such as customer satisfaction, retention, market share, new business revenue, etc. are likely to be routinely measured. But they are normally measured on an overall or market/segment-specific basis, rather than linked to individual or segments of employees, except for sales results linked to specific sales staff members. Customer satisfaction may be linked to the specific employees known to have served them, where this is likely to be the same individual or team over time, but market share and new business increases may have to be credited more widely, perhaps to the PHM effort overall.
There are probably a half dozen commonly used methods for estimating productivity based on employee self-reported data. These may directly ask employees to recall how many hours of lost productivity they have had in a recent period, perhaps a week, two weeks or a month, where their memory may be reliable. Or it may ask for an estimate of the percentage of their full potential they have been able to deliver, considering their health and any problems identified, that may affect their output.
Similar surveys may be used to gauge the levels of performance employees have been able to deliver, since both absence and presenteeism will likely affect performance as much as they do productivity. And the impairment found in individuals may be “multiplied” by their estimated “team/peer impact”, which has been measured at between 1.25 and 1.35 times the impact of the individual’s absence on average. [“Multiplier Effect: The Financial Consequences of Worker Absences” Knowledge@Wharton Dec 14, 2005 (knowledge.wharton.upenn.edu)]
The economic impact of absent or impaired employees may also be based on the economic value of employees in terms of their overall contribution to the employers’ performance. When employees are paid on a “pay-for-performance” basis, their performance will naturally be measured, though it may prove difficult to determine the extent to which any individual is impaired by their health problems, as opposed to other non-health-related limitations. Fortunately, once performance improvements have been linked to PHM interventions, the measured performance may be more easily translated into economic benefit.
By far the most common approach currently used in evaluating the economic impact of employees’ health-related impairment is to multiply their degree of impairment times their annual compensation levels. This means the different employees will have different costs of lost productivity, whenever they have different levels of compensation. It also fails to take into account any team/peer impact or the likelihood that employees are worth more than they are paid. One study, for example, found employees worth an average of 3.28 times their annual compensation, though the median was only 1.92 times. [P. Strassman “How Much Is an Employee Worth?”, Jan 14, 2006]
While insurers have relatively few and commonly used dimensions when measuring their PHM problem/challenge and the results of their PHM investments, employers have far more complex and potentially costly choices. Fortunately, employers can use the same relatively simple and inexpensive-to-measure dimensions as do insurers, and when they go beyond those, they should also be gaining many times the cost of doing so in the added value they discover across the full range of benefits in having a healthier/happier workforce.
by Scott MacStravic
May 2, 2008 at 12:30 pm · Filed under Business of Health, Population health management, Variability in PHM Series
Population Health Management (PHM) has become a major market for insurers, governments, and employers to invest in – and for a wide range of organizations, from traditional healthcare providers to specialized PHM suppliers to insurers to deliver to that market. The numbers of suppliers keeps growing as the number of payer clients does also. The market is beginning to look like the early stages of many new markets, from automobiles to radios to TV sets, cell phones, and electronic gadgets in general – it offers a vast number of options to purchasers, including the “do-it-yourself” (DIY) alternative to purchasing PHM.
Many traditional healthcare organizations (HCOs), from physician practices to hospitals to integrated health systems (IHSs) have entered this market, as DIY providers to their own workforces, or as competitors in marketing PHM services to payers, mainly to employers. They may do so in order to support their sickness care services marketing strategy by creating and sustaining stronger and more lasting relationships with employers as influencers of both insurance plan decisions on provider networks, and employees’ choices of providers. Or they may see the PHM market as one they would rather join than merely suffer its sought-after effects in reducing sickness care use and expenditures and thereby their sickness care revenue.
Employers have been involved in a “toe-in-the-water” approach to PHM since the 1970s at least. Many began with some kind of DIY “worksite wellness” program for their employees, and a growing number are offering onsite medical clinics that engage in PHM along with traditional sickness care. But most appear to be outsourcing the PHM function to specialized suppliers or HCOs, since there are so many complications in their knowing about their individual employees’ health problems — and most have no great competence in PHM.
Insurers have often been influenced by their own interests or their employer clients’ demands to become PHM DIY suppliers, as well as insurers, to employers, at least. Both Aetna and CIGNA, for example, offer PHM services to employers other than those to which they provide health insurance plans. Since insurers can gain substantial experience, and with large populations, by delivering PHM services to their own insured populations, they can gain both the competence and track record needed to become viable suppliers in the overall market, as well as capable DIY providers for their own health plan members.
Specialized PHM suppliers have been in the PHM market, as operators of worksite medical care clinics for employers, or suppliers of PHM services for commercial and government insurers, for a few decades. There has been a significant movement toward merger and acquisition among such suppliers, resulting in consolidation of their numbers, but many new ones keep entering the market, so the overall numbers of suppliers is still huge. And while some have captured large market shares, there appears to be no single supplier who could be called dominant.
One of the reasons for this is the vast degree of variability among PHM suppliers, due to both their large numbers and the fact that there is nothing close to agreement on what are the “best practices”, the most cost-effective approaches to PHM in any one of its essential elements. These elements include:
- Determination of what dimensions of economic impact will be included in the PHM planning, management, and evaluation
- Assessment of the PHM current state of these dimensions in whatever population (insured plan members, employees, dependents, retirees) is to be involved
- Targeting of which individuals shall be sought as participants in either standardized or differentiated PHM approaches to particular problems, risks, or potential gains are to be addressed
- Recruiting targeted individuals and segments to become active, engaged, and enthusiastic participants
- Sustaining participants throughout the PHM intervention program, at least long enough to achieve some desired effects, if not to the end of a limited intervention, or on a continuous basis if there is no intended end.
- Carrying out the intervention process on those participating, using a wide range of interaction and communications technologies and methods
- Evaluating the effects of interventions over whichever time frame(s) clients wish
Not only are there vastly different approaches to each of these elements being used by different PHM suppliers, but clients may engage different suppliers for two or more of such elements, including doing one or more themselves, or at least sharing the responsibility with outsource suppliers. As a consequence of the numbers of and variations among suppliers, the overall PHM market contains far more variation than is true for almost any other example in the business-to-business (B2B) or business to consumer (B2C) markets.
In subsequent postings, I will describe and discuss the seven separable elements in PHM that are subject to such variations. The combination of this number of basic elements, and the variability in how they are carried out by different suppliers, even within the same supplier for different clients, is what makes the PHM market so replete with variability.
