Part I

Physicians and health care workers daily face the task of assessing suffering and the steps to be taken to relieve it for individual patients.

And one of the most important and difficult of the ongoing tasks facing leaders in any country is to formulate a continually updated, humanely cost-effective health care plan for their people. A critical input is the comparative amounts of the associated suffering, potentially preventable and/or relievable, among the given arrays of available resources and feasible options. What follows may be one of the most direct, practical, simplest, tested, and accurate methods to quantify suffering for these purposes. We believe the occasion for their application may be propitious.

The description of a "dukkha-based" assessment of the suffering entailed in individual illness and medicaJ treatment described below is the subject of Part I.

Part II summarizes the products of intensity and duration of suffering, with and without treatment options for the national frequency of selected illnesses and treatments of concern to United States public health. Only after judging the burden of suffering of illness and that additional suffering both imposed and relieved by medical treatment will we factor in in Part II quantitative cost, both for individual treatment options and for collective national health planning.

Health Care Reform and Cost in Dollars

In the continuing process of health care reforms, a system of control was devised that would do away with the former "cost-plus accounting" applied to the ever receding goals of adequate equitable, and possibly even universal health care, in the United States. That there is an insatiable appetite for health in America and that health care imperfectly translates toward that goal has added to the runaway problem recognized now as a crisis in U. S. health care. The largest expenditure for the newest and most innovative health care technology in world history has reaped the least satisfied consumers of that care.

There is one parameter rather easily measured in the crescendo of pressure toward fixing the system–and that is its cost. Whatever its uncertain benefits, we can all run the sums–to a total of a seventh of the world's largest economy. But there is less precise measurement for the purpose of this whole enterprise to begin with: that is, the relief of suffering and the rehabilitation of the disabled–still, presumably, the fundamental reason health care workers go to work each day as professionals.

Attempts at control of the system are data driven and therefore have been directed first at the most reliable–and inevitable–source of numbers, i. e., cost.

To wiggle out of the "necessary but not sufficient" cost-plus game that held some government agencies up to public ridicule, the control system suggested for the huge and fast-growing medical-industrial complex was the "prospective payment scheme." The Health Care Financing Administration contracted an experiment in so-called "Diagnosis Related Groups" (DRG) of Title VI, Section 1886 of Public Law 9821. What DRGs meant is that all public payment for inpaticnt hospital services would be made up front according to the grouped diagnosis that best describes the patient's condition.

Perhaps "a rose is a rose is a rose," but not all cholecystitis is. To reconcile the wide range of patients who might suffer this condition with a single code, a marginal allowance was made for "co-morbid conditions" that factored in the complex of "case mix" (some patients are simply sicker than others, for a variety of reasons, age, reserves, and simultaneous problems), but as long as all agree that the major reason that brought that patient to the hospital at that time is "cholecystitis," that is the principal purpose of treatment, then the patient fits DRG 198–which has a pre-fixed reimbursement. Should the patient have cholecystectomy or medical treatment, and if operation, should that be by an open operation or a laparoscopic technique? One factor the hospital would surely use in tilting toward one treatment option or the other is how fast does the patient get well and leave, and how much resources are consumed in the interval?

DRGs

There is a high stakes gamble in the hospital's interest: it has already received all the money that it will get, predetermined by the patient's DRG code. If recovery is rapid and uneventful, the cost may be less than the prospective reimbursement, and the positive balance is pocketed as black ink in the accounts to be accrued against the inevitable outcomes that could be less favorable. If a patient has a protracted stay, probably by developing some form of complication, more resources are consumed, but these greater-than-expected costs are not compensated. If one form of treatment, or treatment consistently associated with one health care provider, results in expensive untoward outcomes (called "outliers" that fall through "screens" in the "care manager's" reviews), it is the hospital, and not the government that stands to lose. This adds an incentive for internal policing on the part of the hospital staff for which the government is responsible, primarily through the power of the purse.

The data that drive DRG monitoring of health care provided–and are major determinants in options chosen for treatment–are cost data, and these are only indirectly (and often inversely) proxies for patient benefit. No one said hospital managers had to be heartless (but they could be) nor that doctors started out dollar-driven (although that, too, sadly might have been the case), but the data at hand were dollar data when there a movement for control began.

"Outcome" became the new paradigm rather than just the accrual of a number of the newest and fanciest procedure applications, but undeniably those outcomes were fixed in dollars. One perverse twist on this would be that a patient that would benefit the hospitaJ greatly is one with a big-ticket DRG who would die just after admission consuming as little resources as possible rather than lingering under palliative treatment. Is it any wonder some patients feel like pawns in "gaming the system" in which their own perspective of benefit might be an indirect effect of the most measurable one?

It is now ten years after implementation of DRGs and the tenth version shows just under 500 DRGs into which all federally-financed health care can be reduced. More will be forthcoming as new discoveries are made, but the handle is in place for ratcheting down on reimbursemen;s for all health care. But the focus of attention is the "waste" in health care (in which is said to dwell enough dollars to provide universal coverage for ever to all those not now insured, and throw in prescription drugs and mental health in the bargain). Much of this "waste" lies in the "outliers". These are high resource consumers that are not getting better either because of a chronic condition or ineffective treatment. Again, the dilemma is posed in terms of the quantifiable data. The "outliers" will have to be figured in to balance the budget.

Health Care Reform and Reduction of Suffering

The discussion might not have to be couched in terms derived only from the "dismal science." Might it not be feasible to start with the professed fundamental goals of both the patient in seeking help from a health care provider and the professional in practice–to reduce suffering? If this suffering were quantifiable and various treatment options could be expected to accomplish a reduction in the suffering, a humane analysis of the optimum medical treatment options might be possible, and economic cost/benefit considerations would become derivative from it. If a certain reduction in suffering were predictable, resource allocations might be decided by what accomplishes this predetermined goal most efficiently--with some expeditious high-cost options quite probably winners.

There are no magic wands in health care–whether the treatment is a procedure, a drug, or reassurance. Not only is each intervention accompanied by cost but also hazard--and one real risk is that of the iatrogenic infliction of still more suffering. It is quite possible that health care contributes to the sum of human misery in some conditions, and how can that infliction be mitigated or such options be selected against?

There are some agreed upon benefits against trivial infliction–the immunization injection that brings tears to the eyes of a child and lowered risk of communicable disease, for example. There are some procedures for which the balance of inflicted suffering against predictable relief may prohibit the technique as therapy except in terms of Phase II development in clinical research–bone marrow transplantation following radical chemotherapy of metastatic cancer, for example. To analyze the relative success of any medical intervention, then, we would have to consider the sum balance of suffering relieved, and select against all treatments that would cause more suffering to be inflicted than they could reasonably be anticipate to be relieved.

It is particularly timely to redirect attention to first principles in view of the intense debate across the United States on a new trail-blazing national health care plan for the American people. Many options and variations are vigorously advanced. Beyond the humane analysis of a preferred medical treatment option for a given patient, what public good may result from optional health care plans?

It would appear that the version ultimately adopted by the federal government would address the following complex economic types of questions (among others) explicitly and head-on in as clear, direct and firmly grounded a manner as possible:

1. What national health care plan will potentially bring about the largest amount of medical suffering prevented and/or relieved for the population as a whole per million dollars expended?

2. What will be the likely family of curves of the amount of medical suffering sustained by the people at large plotted against time for the period concerned at various levels of funding?

3. What will be the likely corresponding families of curves for various categories of the citizenry calling for speciaJ consideration?

4. How about analogous curves for the various proposals regarding the distributions of resources among categories of illness for various overall levels of approximations?

To the degree that the best available tools for the quantitative estimation of suffering are used, to that degree will the ansvers to the above kinds of questions be more sharply focused and useful. We wish to bring the recently developed quantitative unit of the dukkha and medical dukkha tables to the attention of the responsible policy makers. They might be of some facilitating assistance.

How can such a gauge of suffering be derived? By doing what all clinicians have always done--ask the patient. Describe the pain to me–how bad is it? For how long have you had it? Does it come and go? What scems to make it better? What exacerbates it?" Pain is the experience of the sufferer, but the intensity, duration, and characterization are judged by the clinician, who is always at least ranking it.

lf prevention and reduction of suffering is a fundamental principle in health care, can a new paradigm be constructed using the first principle for decisionmaking among treatment options and national plans?

Quantification of Suffering

The direct quantitative measure of suffering, called the dukkha, is a slight adaptation of the routine intuitive practice followed by physicians and laymen alike for millennia. Among the first questions asked the patient by the doctor is: "How badly do you feel on a scale of ten--ten being the worst possible." And the second is: "For how long have you been feeling so badly?" The dukkha is determined by the standardization of the two steps and a multiplication of the two answers to provide the quantity of suffeing.

The first factor regarding the intensity of suffering is set as an odd-number nine-step range, in order to make it easier for the respondent to find the midpoint of five. The intensity scale in approximately equally spaced ascending de scriptive tcrms is as follows: 1, noticeable; 2, bothersome; 3, moderate; 4, considerable, seeking relief; 5, midpoint, interfering with daily life; 6, quite a lot; 7, miserable, visiting physician or other healer; 8, excruciating; and 9, unbearable, wanting to die.

The second factor of duration is given in days. Thus the number of dukkhas experienscd is (number of persons) x (average intensity of suffering on a 9-step scale) x (duration in days). One dukkha is the suffering borne by one person experiencing an intensity level of one unit for one day.

A person with a moderate toothache for eight hours, for example, endures one dukkha of pain, i. e., (1 person) x (intensity 3) x (8/24 day). A thousand persons with flaring peptic ulcers without medication for a year is estimated as having collectively endurcd approximately a million dukkhas, i. e., (1,000 persons) x (average intensity 6.5) x (10 hours of pain/24 hour day) x (365 days).

At lower levels of suffering, sleep is a possible source of relief with or without hypnotic or sedative agents. At higher levels of suffering, sleep is impossible sometimes even despite analgesics. So, for example, at levels of intensities at 1-3 steps, it is assumed that eight hours of suffering-free sleep may be possible and the average intensity of suffering per day is reduced by a third within a 24hour interval. At the higher levels of intensity of 7-9, sleep is precluded, so no such reduction is made in the estimate of sleepless suffering.

The dukkha is fit to meet the following specifications, which have been advanced for a direct and practical quantitative measurc of suffering for- everyday social usage by laymen:

1. The precision and accuracy should be adequate for the purpose and context at hand.

2. The basic data should be the direct personal estimates by the sufferer. This requirement stems from the very definition of suffcring itself as being subjective.

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3. The manipulation of the basic data to provide the final figure for quantity should be logically sound.

4. The procedure should be sufficiently simple, so that even laymen with minimal education would be capable of using it to estimate their own arnounts of suffering flowing from various sources and causes.

5. No special equipment should be required other than paper and pencil.

6. The method should be universally applicable for all individuals, institutions, governments, kinds of sufferings, conditions, and so on, so that comparative analyses, choices, and judgments can be made.

7. The ease and reliability of eliciting the necessary inputs to the calculations should have been demonstrated in actual use for some time.

The key new input required for the generation of dukkha tables to serve as a useful addition to public health statistics is reliable estimates of the intensitics of suffcring. The rcst of the data arc readily available from existing vital statistics and the medical literature.

Four avenues are at hand for obtaining estimates of the intensities of suffering. The direct method is a statement by the sufferer himself/herself. By the very definition of suffering, this is thc unarguable estimate. The indirect methods derive their validity from an invariable correlation with this subjective reference.

Where direct methods are impractical at the moment, recourse must be made to indirect approximations. Reasonably reliable figures may be forthcoming from attending medical personnel familiar with a large body of cases. This would hold especially if the non-sufferer's estimates had been demonstrated to be highly correlated with the sufferer's statements in other instances.

Another indirect method involves physical instrumentation. Here again, its utility dcpends on the correlation with the patient's estimates. We do not foresee the time when sufficient correlations can be worked out for even a small fraction of the purely physical suffering, not to mention mental ones.

The fourth approach involves social indicators, such as lost labor hours, freedom, and income. These are too gross, indirect, both overlapping and incomplete at the same time, and disparate for logical combination. In the absence of a direct guantitative measure of suffering, they have been the most expcdient under the circumstances. But this no longer is the situation.

We are thus practically left with the first two avenues. While awaiting the day when the ultimately standardized medical dukkha tables would be largely based on direct estimates from the sufferers themselves, we have relied on indirect estimates by a limited number of physicians for the construction of the present illustrative prototype table.

Illustrative Prototype Medical Dukkha

Table

A complete table of the number of dukkhas suffered by the average patient stricken with various illnesses, the probability of prevention and cure with respective costs in dollars and time for the optional treatment regimes now available, and the numbers of patients so afflicted would appear to be necessary as a minimum for a rigorous basis of comparative evaluation of health-care system options. The core information is the number of dukkhas suffered by patients in each case of illness, with and without medical treatments. An illustrative prototype medical dukkha table of this nature is presented below.

The core array can then be amplified with additional relevant columns. Typical would be the number of cases in the United States per year with and without medical treatment, thereby providing the total number of dukkhas of suffcring endured by the American pcople as a whole for thc particular illness (Part II to follow). Econo-panetic information may also be incorporated, such as the cost of treatment, thereby providing estimates of the number of dukkhas relieved per million dollars for the country as a whole for various combinations and permutations of plans, resources, categories of pcople, and systems of treatment.

Other representative tables for finer-grained analysis might include the following: (1) Dukkha tables for the twenty illnesses engendering the greatest amount of suffering for individuals per case, (2) Dukkha tables for the twenty illnesses engendering the greatest amount of suffering for individuals at intensities 8 to 9, (3) Dukkha tables for the twenty illnesses engendering the greatest amount of suffering for the population of the country as a whole, (4) Dukkha tables for the twenty illnesses engendering the greatest amount of suffering at intensities 8 to 9 for the population as a whole, (5) Dukkha tables for the twenty illnesses costing the most for medical treatment per case, (6) Dukkha tables for the twenty illnesses costing the most for the population as a whole, and (7) Dukkha tables for illnesses without known medical treatment.