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Sunday, September 26, 2010

Framing issues and informed consent

We are all choice architects, influencing our patients by describing options in different contexts. This is devilishly difficult given the time constraints created by our present payment structure, the imperfect nature of the data we have at our disposal, the varying preferences and educational backgrounds of our patients, and our own biases hidden from our ability to appreciate their influences. This past week there was yet another major study published in the NEJM regarding the effectiveness of screening mammography on prevention of breast cancer. It was another case of looking at the glass and saying whether it was partially full or partially empty.

My sentiments on this align with Gilbert Welch who wrote an accompanying editorial. The basic take home message was that in order to save one life the authors found they needed to screen 2500 fifty year old women for 10 years in order to save one life. These efforts would generate 1000 false positive tests and likely expose 15-20 women falsely diagnosed with breast cancer to various forms of treatment including surgery and chemotherapy. Within a cohort of 1000 women, on average 4.5 would die of breast cancer in 10 years and this would drop to 4 with deployment of mammography. 

My question is, now that this and other studies supporting similar numbers have been completed and published, how many women will be given this data as part of their routine discussions to have mammography?  I suspect next to none. 

Medicine is filled with these types of issues. Basically healthy people with few if any symptoms come to us for some sort of service. They want reassurance. We have become increasingly equipped to offer an array of services to prevent some sort of undesirable future outcome. Unfortunately we as physicians don't understand the numbers particularly well and we are not encouraged to present them in an understandable and transparent format to our patients. 

In Dr. Welch's piece that accompanies the NEJM article, he raises the issue that physicians are being judged on quality metrics that include participation of their patients in various activities such as screening mammography. This gives clinicians a vested interest in getting patients to comply with various, purportedly beneficial activities. However, just how beneficial are these activities and what information should be shared with patients before they commit to any given course of action?

I came across an article by Misselbrook and D Armstrong. 276. British Journal of General Practice, April 2001 where they looked at patient responses to the following scenarios:

The results are quite startling. 

Depending on the data presented and the framing, anywhere from two thirds to less than twenty percent definitely would agree to treatment. Those who likely would decline went from about twenty percent to well over half. 

What are we to do with such information? What is the correct approach to informing patients? I have little doubt that using the NNT or PPB approaches will result in fewer patients electing for certain interventions.  Is that reason enough not to share this information? I do not think so. In fact, it seems to me that the quality of the informed consent process could be directly assessed by the number of patients who actively decide against specific measures. Too high a level of compliance with certain measures might equate with evidence of an inadequate informed consent process and a lower level might be a good measure of the quality of the informed consent. 

Bending the cost curve

Other than those who are admirers of Louis XIV and his philosophy of  "Après moi le déluge", there is widespread agreement that continuing our present path of growth in health care spending is not sustainable. All political posturing and bluster and magical thinking aside, how can this actually happen? 

This does not involve higher math and uses the mathematical tools which I learned in elementary school.  We need to either spend less or increase the pool of resources which can be tapped to pay for health care or a combination of both. However, we need to define which actions would result in either of these two outcomes and then define which entities are empowered to make those decisions. None of this is easy.

First of all, how can we predict that any given action by any given entity will have the expected outcome? In addition, saving money is not the only charge of those whose mission is to remake the health care system. Competing imperatives include increased access, lower out of pocket costs, sufficient payments to guarantee provider participation and availability of services, long term support of health care education, support for research, support for quality initiatives, promotion of innovation, fairness and functionality of the tax code, and limiting the tax burden in order to promote overall growth of the economy. Any action taken by any numbers of parties to further any one of the above goals will have impact on how much is available to be spent on health care and how much will be spent.

Let me simply highlight one interaction between competing imperatives. Despite the huge increases in the total amount spent on health care, the portion of costs which fall upon the medical consumer (patient) has on average fallen since 1960. On one level this is highly desirable in that out of pocket  (OOP) expenses do not create a barrier to accessing what patient need (see chart).

On the other hand, insulating people from the costs of goods and services creates all sorts of moral hazards, the worst of which is the tendency to over consume or utilize more expensive approaches which may bring limited if any additional benefit for the additional dollars spent. In the broader economy, substitution options  create downward price pressures on goods and services. In the medical realm, this mechanism works poorly if at all since substantial portions of the public have historically have not been motivated to cost shop since their insurance insulates them from such cost differentials. This may or may not be changing.

As I see things, the only way this changes is by implementation of some sort of gain sharing mechanisms. The public will not broadly buy into cut backs in their benefits unless the gains are explicitly shared with  them. Short of actually paying patients to use cheaper interventions, which would create all types of perverse incentives, we are left with having patients pay more for more interventions that have lower cost (and perhaps lower quality) alternatives. Otherwise, why stint on your own care when you have nothing to gain from it.

How this can actually come about is another story. None of the parties presently involved is either empowered or incentivized to make the changes which can result in bending the cost curve in the desirable direction.  It is only the rare politician who will be re-elected by promising his constituents that she/he will deliver less. Few people other than those with martyr complexes are driven to pay more to get less from the health care system. Physicians will refuse to play both patient advocate and cost containment agents simultaneously. Insurers will not be capable of being effective agents for cost containment. They will not gradually move their business model to simply collecting a fee for claims adjudication and check cutting and leave the thorny job of saying no to their political masters who will provide more and more of the funds to keep the health care monster alive. 

It brings us back to how can this be managed and I again get back to the best model for scarce resource allocation; markets. There is no question that such a model will remake the health care industry into something very different from what it is today. There will be great resistance to this approach given the bias that markets can not work for health care. Ultimately we will have no choice. The only approach which can bend the curve is for each of us to husband our individual resources and for health care purchases to compete with other individual wants and needs on an even playing field. If those within the health care industry cannot convince the public that their investment in their own health is worth the expense is worth it, the cost of moving that decision making process for resource allocation to another entity will prove to be disastrously expensive in the  long term.    

Saturday, September 25, 2010

A surprise every 15 minutes

Every time I see patients in the typical ambulatory setting, I still marvel at how ridiculous our processes and workflows are. I have a practice which includes new referrals for complex problems and follow up patients, also generally with complex medical issues. For the patients who I see initially, I insist on record review before I will schedule them. Patients and physicians complain about this requirement and this generally impacts my patient satisfaction scores since all parties view this as a barrier to getting in to see me. Few appear to connect the dots that perhaps collection of information before the patient arrives at my office is critical for me making sure they are actually coming to the right place to address whatever problem they have.

The usual triage mechanisms in place involve the patient and someone at the other end of a phone line, generally someone with virtually no medical training. In our institution, the historical measure for productivity of those who received the calls and scheduled appointments was simple. How many calls can you handle per unit of time. Place any caller in any available appointment slot to keep the patients and their manager happy. Whatever information which might have been collected at the time of the call relating to the reason for the appointment was either not recorded anywhere or amounted to an obscure or inaccurate complaint, generally conveyed with tortured and often comical spelling. What the heck of someone drove five hours for a brief encounter with the wrong physician. We use tools which basically guarantee that this will happen.

I have wracked my brain trying to think of other industries with similar business models. There are some parallels with auto repair shops. However, they generally collect much more information regarding the challenge ahead of them than we do and manage time expectations much better than physicians. Imagine that, falling short of the bar set by auto mechanics. Perhaps I am being too hard on the medical profession. People are much more complex than cars and trucks. They cannot leave their body at the office and go on with the rest of their business using a loaner, at least no yet.

However, we are going to go nowhere until there is a broad recognition that we go about our business using a model which is fundamentally flawed. I should not use a process in my office which is based upon being surprised every 15 minutes. When I walk into a room with a follow up patient, I might have a hint of what I will face, but generally not. For my follow up patients with chronic and symptomatic disorders, I usually have implemented some treatment protocol some weeks in the past. Short of me calling each individual patient on a regular basis and asking them how they are doing, we remain blissfully unaware of what has transpired in the intervening periods between appointments. I actually do call patients but it is generally hard to reach people and it is not an efficient use of my time.  In a world of widespread and robust communication tools which allow us to collect all types of information automatically and in structured formats and which have been widely deployed in many industries, health care remains a remarkable exception.

At least part of the lag could be traced back to HIPPA. Perhaps more early adopter types might have tinkered with small scale projects to form the basis for larger and enterprise based tools. This has not happened, at least on any widespread level. I don't see MD/patient communication apps on my Droid phone. I do not think they exist for the iPhone either. The only way we will see the development of such tools  is for each large vendor to develop expensive enterprise patient portal tools which will need to comply with HIPPA, CCHIT, and whatever. These will be applications developed by committee and will likely serve everyone's needs equally badly. I will be surprised if they are robust and adaptive. They need to be both if they are to allow for the type of information exchange which will allow for physicians to recognize and be responsive to patient needs and to collect information is formats which will allow people and systems to review what they are doing and find areas for improvement.

At some point in the not to distant future, substantial numbers of patients will come from generations that have integrated electronic social networking tools into their daily lives and they will look at the way we do business now as some form of madness. Some already do. They are appalled that they cannot communicate effectively with me because they have to run the phone tree gauntlet or hope that I received the fax they sent. We surreptitiously use emails but since they are technically forbidden, the information never makes it into the actual medical record. It amounts to work arounds heaped on work arounds.

So we wait and continue to run our practices using the information tools of the last century and structure our days seeing patients in the context of agenda- less meetings and surprises every 15 minutes. Health care reform was most focused on increasing the number of people who get access to this dysfunctional system and paid scant attention to the barriers already in place which thwart efforts to re-engineer our processes. I am tired of bing surprised every 15 minutes, particularly when the tools exist to fix this problem right now.

Sunday, September 19, 2010

Rethinking Science

There is an excellent piece from The Economist:
Good sense is the most fairly distributed commodity in the world, Descartes once quipped, because nobody thinks he needs any more of it than he already has. 
It is always great when the lead off for an essay has such a pithy quote. The author goes on to write:
No group of believers has more reason to be sure of its own good sense than today’s professional scientists. There is, or should be, no mystery about why it is always more rational to believe in science than in anything else, because this is true merely by definition. What makes a method of enquiry count as scientific is not that it employs microscopes, rats, computers or people in stained white coats, but that it seeks to test itself at every turn. If a method is as rigorous and cautious as it can be, it counts as good science; if it isn’t, it doesn’t. Yet this fact sets a puzzle. If science is careful scepticism writ large, shouldn’t a scientific cast of mind require one to be sceptical of science itself?
 There is no full-blown logical paradox here. If a claim is ambitious, people should indeed tread warily around it, even if it comes from scientists; it does not follow that they should be sceptical of the scientific method itself. But there is an awkward public-relations challenge for any champion of hard-nosed science. When scientists confront the deniers of evolution, or the devotees of homeopathic medicine, or people who believe that childhood vaccinations cause autism—all of whom are as demonstrably mistaken as anyone can be—they understandably fight shy of revealing just how riddled with error and misleading information the everyday business of science actually is. When you paint yourself as a defender of the truth, it helps to keep quiet about how often you are wrong.

Thus, despite having a set of tools unrivaled in regards to identifying truth, science and scientists are wrong more often than begin right. The science is undergoing continuous revision. This is obviously relevant to the practice of medicine. It is cumbersome in a world where patients want to know THE ANSWER or THE DIAGNOSIS to respond with hedging.  It unquestionably cuts into billing to have to deal with the messy world of gray as opposed to black and white.  Furthermore, this may call into question the actual role of science and evidenced based medicine. 

When I see a patient and discuss options to deal with a particular problem, the science and evidence are important but represent only a part of the picture. They may help guide any decision by providing a background as to the likely outcomes. How the patient deals with this information (if actually available) is not a scientific question but a personal question. Science cannot and should not dictate the answers to personal decisions. It is critical that we know when our data is good and revealing of underlying trends. How people use this data and what outcome they decide is desirable should be their call. Only they know what their particular goals are.

The assumption promulgated in policy circles is that what should be delivered (and paid for) in the health care realm can be decided on the basis of science. That is one of  the driving forces behind the EBM movement. However, you need to ask whether patient decisions regarding health interventions are fundamentally scientific questions. While these decisions may be influenced greatly by data and products of scientific inquiry,  I believe the answer they are personal decisions. These decisions are also highly influenced by individual and personal goals which are highly disparate within any given population.      

However, this paradigm is not so simple because there is often another party involved, the payer of the service. The payer generally has some sort of fiduciary responsibility to yet another party (taxpayer, stockholder, business owner). Science is injected into this mix based upon the assumption that we can use science to decide what health care interventions are needed. Perhaps it is reasonable to use scientific and statistical methods to define whether on average a particular intervention and allocation of resources generates a net positive effect in a given population. However, it is a pretty poor tool when it comes to accommodating individual needs. Using scientific algorithms to decide personal questions will almost certainly result in wasteful allocation of resources and  substantial personal disappointment. 

We are all gamblers

I am reading a book by Peter Bernstein entitled "Against the Gods: The remarkable Story of Risk". As those of you who have read my previous blog pieces already know, I am fascinated by concepts of risk and prediction. I believe that understanding these concepts are absolutely essential to the practice of medicine. Unfortunately, the general public as well as the medical profession has a poor grasp of these concepts and it serves as an impediment to best decision making.

What is most intriguing about the history described by Bernstein is that gambling was the driver of gains in the statistical realm which ultimately catalyzed the quantum leaps in expanding the understanding of the statistical tools and concepts required to both understand and predict risks. One the concepts were understood as they related to dice and cards, the mathematical application to other domains outside typical gambling became apparent. The rest is history in the world of finance and insurance.

At the most fundamental "gut" level, I think all of us understand that we are constantly making bets and weighing the odds. I suspect that one of the attractions to the world of overt gambling is the rules are more explicit, the stakes are reasonably well defined, and the outcomes are tightly temporally linked. We do not need to wait a long time to discern whether we are winners or losers. Furthermore, it is easy to tell. The outcomes are not ambiguous. If there is anything we humans like it is certainty and immediate gratification.

The practice of medicine is laced with bets. In contrast to the clarity of the gaming tables, medicine is filled with uncertainty overlaid with ambiguity. Take a population of patients with mild hypertension. Intervene with some sort of medication in thousands of patients, follow for decades, and statistically someone is a winner but no one knows who. Similarly, screen tens of thousands of patients for breast, lung, or prostate cancer using whatever tool which is in vogue. In contrast to patients with hypertension, patients who participate in cancer screening get an almost immediate feedback with what appears to be a result which is as unambiguous as rolling snake eyes. The problem is that virtually no medical tests are that black and white. We would like to be able to predict with certainty the winners and losers (although in the end we are all losers) and most of the public and much of the medical community have virtually no appreciation of the limits of these tests.  They fail to understand that the diagnosis of cancer in many cases is simply a prediction about what might happen in the future with no way of knowing whether the prediction is correct 95%, 50%, 5%, or 0.5% of scenarios.

In my own practice I have solved this problem by focusing on the present as opposed to the future. I deal primarily with patients who are symptomatic and uncomfortable and my measure of success is whether I am able to fix that. I like to say that I deal with present problems as opposed to dealing with things that might happen in the future. I still need to be aware of what might happen in the future, particularly as it relates to what my interventions may cause in the future. When trying to address someone is is in pain, is short of breath, is itching from dermatitis, or is functionally impaired in some way, all possible fixes entail some risk of creating some new or worse problem.

The obvious question which any well informed patient should ask is how likely is that to happen? Alas, there lies the problem with even the most modern medicine. For the most part, we do not know. In the 16th century, gamblers were in similar straits. Men had been playing dice games for literally thousands of years but it was not until the works of Girolamo Cardano, a Renaissance man and inveterate gambler that assessment of risk and odds changed. His work revolutionized how the financial world dealt with risk, moving it from gut and intuition to statistical analysis. With his mathematical tools, he could precisely predict the odds of rolling a two or a seven. The same principles were applied to annuities, insuring commerce,  and finance.

For the most part, risk assessment in the practice of medicine still operates primarily at the gut level. The statistical tools exist but they require actual data to be applied. Absent the availability of relevant data, we are left with a world similar to those throwing dice prior to Cardano. We may understand that we are placing all types of bets but we don't have the tools to understand the odds.

Thursday, September 16, 2010

Rethinking multidisciplinary care

I attended a conference whose sole purpose was to bring together experts with experience in running multidisciplinary clinics. None of my previously conceived notions were altered much. There was a very sobering introduction which highlighted two themes. The first was the accountable care organization concept. What we are facing is the construction of totally new models of care which are to be created based upon top down mandates by organizations poorly equipped to assess how they are doing. The second theme was that the growth in health care spending was simply not sustainable meaning that the ACO construction will need to happen in a world of serious cost constraints.

There was lots of discussion, actually very interesting discussion, but there was a serious disconnect. The consensus was that multidisciplinary care was better for patients but the only way to get it was to spend more, not less money. There were many participants who described their own experience with such clinics, and although there were exceptions, most of these models involved having multiple physicians engaged simultaneously. After the conference, I started to run the math. What would it take in terms of  revenue to simply cover the cost of simply the doctors in the room? For circumstances described where there were three specialists in the room at once, let's make a few simple assumptions. The average specialist salary can be conservatively estimated at $200K/year. Assuming they spend 40 hours/week in direct patient care and 50 weeks of work (likely an overestimate), this amounts to 2000 hours. This means to simply cover their salary you need $100/hr per specialist. For the typical institution, the overhead rate is at least 60% and likely closer to 70%. This means the MD costs of $300/hr will require collections of almost $1000/hr. The overhead may be even higher since there may be particular support needs for these clinics.

Irrespective of whether insurers should or could cover these costs, you need to ask the question, can we accomplish the same outcomes using a much less expensive approach. What other activities require the simultaneous activities of multiple six figure professionals delivery service to people, one at a time? It would be nice if we could all hire the equivalent of Michelangelo to paint our living room but most of us settle for the local contractor who might hire a few undocumented workers to save a few bucks.

Virtually all industries have seen tremendous gains in productivity since WWII and in each of these cases the gains have been made by the use of automation and movement away from manual and people dependent processes. One major exception is health care. Within health care we only partly aware of the spiraling costs but because of how our individual incentives are structured, our individual financial gains are directly linked to how much of the insurer's and patient's money we can spend. Our productivity is measured by how much we generate in billings and collections. It is the only way we can keep such an inefficient system solvent.

Getting back to multidisciplinary care, my question is what can multidisciplinary clinics deliver which is not delivered in our present model? One obvious answer is better communication and coordination of care. However, at what cost is it to use the most expensive people in your system in this way?

 I am sure that MacDonald's could hire and pay for Le Cordon Bleu trained chefs to flip burgers and it might improve their food. Geek Squad could hire nothing but MIT PhD's s to repair computers and they would likely raise their quality parameters to some degree.  If we had fast food and appliance insurance, we might end up with these HR placements but that is not the case in the current world. The party line is health care is different and at an emotional level one can easily make this case. At an economic level this is not he case. If we keep up our present course of action we will go broke.

We can create a system with coordinated multidisciplinary care of complicated disease but we cannot design this around such an inefficient use of such valuable resources. We need to identify where physician expertise actually makes a difference and distinguish these tasks from tasks that be be delegated to people who require less training or to machines. In the former category, other industries which were previously reliant upon rare talent who used intuitive decisions making skills to create unique products or services, make huge productivity gains when they could develop rules based processes to replace intuition. DuPont at one point in time had a virtual monopoly on synthetic fiber development business since they basically employed all of the talent who had the skills to develop new fibers using an intuitive approach. The development of better understanding of 3D chemical structure, powerful desktop computers, and software which allowed for modeling at modest cost  put the tools to develop new fibers in the hands of a vastly broader group. It was not necessarily good news for the highly paid chemists but it was good news for those who benefits from the availability of an abundant variety of inexpensive synthetic fibers.

People are expensive and industries such as the auto industry have replaced expensive people with machines which are in fact better suited to do particular tasks. In health care machines such as computers might be ideal for data collection and tracking, flexible learning and testing, and decision support tools.  If we are to carry out the mandate to improve care while saving money, we will need to borrow heavily from other industries which have made large productivity gains. We have no choice but automate and delegate.

You might ask about the human element to health care. It may sound like the future I paint sounds bleakly sterile and devoid of human interaction. It may move in that direction but I suspect we will be pleasantly surprised. Automation of other industries freed up people to do tasks they were better suited for. In the case of health care, I suspect delegation and automation will free up time for valuable problem solvers to spend their time actually solving problems and communicating with patients and other members of the health care team. True multidisciplinary care will happen much more readily when the individual costs are not so prohibitively expensive that the primary focus of the care giving team is to figure out how they can support themselves and not their patients.

Sunday, September 12, 2010

Politics and bending the health care cost curve

There are two pieces, one published in the New York Times today and another in the NEJM earlier in the week which are well worth reading. In addition, the authors of the respective pieces should read each others writings. I would love to see their comments. The piece in the NYT today is entitled "Is Newer Better? Not Always."

This Op-Ed points out what the author believes is an inherent problem with advances and innovation in treatment; it makes medical care more expensive. Is that me-too drug really worth the cost? Should we use this test on a particular population to screen for a particular disease?  This is by no means a novel question and in fact I have commented in this blog on more than one occasion, most recently I agree with the Op-Ed author that at least one of the challenges is the widespread lack of information to guide patients and physicians as to the outcomes from particular interventions and believe that investment in research to focus on outcomes is absolutely necessary. That is where our agreement ends.

This brings me to the second article, published in the NEJM and entitled "Lessons from the Mammography War".

This article deals with two big questions regarding screening women for breast cancer using memmography. The recommendations from the Preventative Medicine Task force was to change the recommendation for screening of women without risk factors to start at age 50 as opposed to age 40 and to do screening only every other year. Given the relative infrequency of breat cancer in the younger age group and the overwhelming number of false positve screens in the 40-50 year age group, it was not an unreasonable change to advocate. However, the firestorm of controversy generated two responses. First, it prompted all those who were political appointees involved in the process to run for cover. Second, it should make one think twice about the actual usefulness of outcomes data when it comes to allocation decisions.

Let me elaborate. Fast forward to the day when studies from the Institute for Comparative Effectiveness have been completed and you will get an idea of how this information will be treated if you look at the current day response to the mammography recommendations. It is simply not sufficient to do the outcomes research and expect this will be adequate to dictate best practices. It should be noted that the work put into studying mammography took literally decades and required the study of tens of thousands of women to examine the effect of screening. On the upside, these studies used an unambiguous endpoint, death. For many other expensive and prevalent interventions where benefit needs to be studied the endpoints are much more subtle.

Our desire for the product of outcomes research is that we can have THE ANSWER, unambiguous in black and white. Unfortunately, the answers will be much more nuanced and subtle, as evidenced by the results of mammography studies. Which brings us back to the quandary which face. Even with the best and hopefully increasingly better information on hand, who should be empowered to make decisions about allocation of scarce resources? The writers of the NYT Op-Ed piece suggest we are doing the right thing now and that it is simply a matter of sufficient courage and political will. This is nothing more than wishful thinking. Moving decisions regarding resource allocation of any type into the political realm guarantees that resources will be allocated in such a way to further political ends, generally short term political ends meaning the purchase of votes for the next election.

The lesson from the mammography wars is that data and science are not particularly politically compelling, despite the huge investment to garner them. When the primary mechanism for resource allocation is political, those with the largest potential immediate losses will invest substantial resources in the political realm to protect their turf. Hard data is not the fuel of politics, emotion and personal stories are and they will always trump data in the world of politics. Outcomes data will be like all of the items in that great store room pictured at the end of Indiana Jones and the Raiders of the Lost Arc, filed away for safe keeping and promptly foregotten.

The reality is as we move the allocation of resources in health care primarily into the realm of government, these resources will be allocated by increasingly political means. Like the data on mammography, what is hoped to be hard outcomes data will unfortunately come out not so hard and will not sway many (if any) in the predictable political fights over who should get what. It is the nature of politics and will always be the nature of politic. This type of conflict and behavior is inextricably linked to human nature and the desire for power and control.

We need to realize that certain types of problems are made worse when they are moved increasingly into the political realm. Resource allocation problems fall into this category. Allocation of scarce resources in health care will not be improved by making them more and more politically based. Attempts to create independent entities within government to influence or dictate specific health care decisions will always fail if the money spent is allocated through a political process.

Tuesday, September 7, 2010

Science, Skepticism, and Advocacy

I spent part of my Labor Day weekend transporting household goods to and working around our mountain home a few hours from where we live. One of my colleagues, who I have not had much of a chance to hang with, accompanied me and I was pleasantly surprised that he is quite proficient with the chain saw. He calls himself a "chain saw stud" which was just fine since he was able to clear trees which would have taken days to cut with my wimpy handsaw.

One of the treats of the trip was the opportunity to catch up on his science and find potential common areas of interest and scientific collaboration. We also talks about the respective challenges that we face as individual faculty, the challenges of our institution, and the challenges being faced by the research and clinical establishments as a whole. One thing that he voiced great concern about was what he saw as an unhealthy rise in distrust of experts in general. I agree that both the basic scientific community and the medical communities have seen an increase in general skepticism from the public. However, I am not so sure that the present state represents an aberration an I suspect that the period of remarkable trust which was ushered in after WWII is the real aberration.

I see this return to a more "natural" state as being a consequence of human nature. Many of us are simply suspect of authority, and this distrust may serve many useful functions. This is particularly true within the scientific community. Scientists are skeptics since the scientific method is based upon skepticism. The practice of science involves formulating and testing hypotheses, assertions that are potentially falsifiable using reproducible data derived from experimentation. The trust we gained was based upon the public belief that scientists had developed unique tools to ascertain and were beholden to the truth. The assumption was that if we could prove our beliefs wrong we would shed our beliefs. 

Well, not so fast. If science and scientists could maintain a firewall which allowed them to pose their hypotheses and do their experiments cloistered from politics, policy, and money, there would be no problem. Similarly, if clinicians could take care of patients and make their decisions without regard to their own interest and money, health care finance and politics would be much less complex. That is simply fantasy. With information comes authority and with authority comes power and something to lose. Our work, whether clinical or laboratory, tends to be resource intensive and can only be maintained with substantial flows of money. Who can or will guarantee that the resource stream will continue?

Enter the mixture of science, politics, and advocacy. The question is does science and advocacy mix well? Can a scientist be both a scientist and an advocate at the same time? I believe here are the origins of the mistrust which has reappeared. When the public sees a scientist testifying in front of Congress, they see an advocate, much like advocates from the auto industry, Greenpeace, or whatever. They may be providing "scientific" testimony, but are more likely venturing outside of science and skepticism which science requires. For them to advocate, it requires more in the realm of beliefs than what is testable and falsifiable. Scientists and other experts in this context may deserve as much trust and respect as any other person advocating for their strongly held beliefs. 

Sunday, September 5, 2010

Rethinking work on Labor Day

When I was growing up, I cannot recall my father doing anything which resembled his actual "work" when he was away from his work site. It was not that his work days were filled with manual tasks. He was a PhD trained scientist and I suspect that he did many of the same technical and administrative tasks which I do today. It is possible he did some reading in the evenings when I was very young and I was not aware of this since they herded us off to bed very early. However, at this point in time, it was very clear when he was working and when he was not and it tracked very closely to where he was physically located.

In the intervening 50 years monumental changes have taken place in the work place. What is remarkable is not only the actual technical advances (although some may question the use of the term advances), but also the lag of the recognition of how technology has changed how we work. I have previously blogged about the resident duty hours regulation, which has been crafted completely discounting the how technology has altered how medical house officers do their work. It should be noted that these observations apply to increasing numbers of people in the work force.

Why should any of this really matter? There are huge costs associated with bringing people together to do work and we need to ask the question, why do we need to do this? Historically, we brought people together physically because it was required for them to do their jobs and I believe we continue to use this model because we have not given it much thought. As I have written about before, we bring patients to our offices for face to face encounters and this is driven by the payment system as much as anything else. We bring our employees to work in a building in an academic medical center where we pay a premium for space. This requires that the taxpayers pay large sums of money to support a road system that can handle peak traffic where everyone needs to get to work about the same hours and needs to leave about the same hours. We need to find places for them to park their cars. This is very expensive.

I read a story about a traffic jam in Beijing which extended 60 miles. It is obvious the Chinese are trying to play catch up with road building in order to support economic growth which entails people traveling form one place to another to do their jobs. I have my doubts they can actually build fast enough to make a dent in this.

You might be wondering where this blog is going? My point is we are at a cross roads where we need to ask the question, is it really necessary for us to continue doing business this way? I asked one of the people who works for me how much of the work she does could be done from home. Her answer was 85%. I did a mental checklist of other people who work for me, tallying was they do and the "product" they produce and realized, many need not come to physically work.

I think the implications of this observation are quite striking. I do not have the data but I can speculate that even moving modest numbers of people of virtual employees will have huge impacts on the resources needed to build roads, parking structures, and offices where they historically traveled, parked, and worked.  Anyone familiar with economics realizes that where the action is is at the margins where small changes are leveraged to  have huge effects. 

Obviously there are big barriers to widespread deployment of a virtual employment model. There are cultural issues, the most notable being a combination of lack of trust that those who are working will actually be working. This lack of trust is not completely unwarranted since a not insignificant portion of the workforce will game whatever system they operate in. However, robust information systems also allow us to define what we need done and have the potential to transform how we define work accomplished. Physical presence and the ability to define whether people are physically at work has been the standard. You can have workers punch in and punch out.  This still leaves us with the common scenario employees are physically present but accomplish nothing. It is vastly preferable that you can define what needs to be done, track this, and not need to worry about how long it takes them to accomplish this or where they accomplish it from.

Within the realm of health care, this has tremendous ramifications. Obviously we are a ways off from doing surgery remotely. There are circumstances where we need to be in a position where we can examine patients directly to derive particular pieces of information and use intuition to make critical decisions. As far as I know how much of medical decisions making which occurs in this context has not been studied. However, I suspect it represents only a modest fraction of overall encounters. I believe that most of medical decisions are much more pedestrian and assuming the information systems can be built which allow for collection of relevant data,  we can move health care encounters into the virtual realm with little or no loss of quality. I suspect that quality and value will improve.Anything which allows for effectively dealing with patient needs without requiring them to travel and consume their time is almost certainly a winner.

The cost savings will be staggering. My own home institution was considering completely rebuilding our health care campus until the economy turned south. One of the major elements were road improvements and parking enhancements. Simply to create sufficient parking for peak demand required an investment of hundreds of millions of dollars. Eliminate the need for a modest 15% of the visits which can be dealt with in virtual as opposed to real (and expensive) spaces and viola! - you can deploy those funds to build something which really brings value to patients and the health system.

All of this will require that we redefine what work is. It will likely require that we redefine the relationship between employer and employee, how we pay for services, and how we track quality and quantity of work done. It may ultimately blur the distinction between working and leisure, business and consumer, as well as management and labor. Perhaps in the future we will be having our long weekend marking the end of the summer celebrating Management and Labor Day.