Measuring Health: an Introduction

William P. Fisher, Jr., Ph.D.
Lauren Haygood, R.N., M.S.N.

An Emerging New Era in Measurement Standards
Before the French Revolution, every town in France had its own system of weights and measures. The French were dissatisfied with the many different ways of measuring grain, liquid volume, distance, and land area, and their grievances set the stage for the development of the metric system.

Today, every health care provider has its own system for measuring health, functioning, customer satisfaction, and employee skill levels, just as every school and test publisher has its own system of measures for assessing learning. Much of the general dissatisfaction with the quality of health care and education and with our inability to improve that quality, can be traced to the lack of general measurement standards. Fortunately, measurement quality is improving rapidly in a number of areas of health care.

Quanitites and Amounts
Contrary to what is usually assumed, 75 years of research show that it is possible to measure health, and the capacity to function at work, in school, and at home, just as rigorously and scientifically as height, weight, time, or temperature are measured. Anyone who has ever bought fruits and vegetables in a grocery store can understand how measurement should always work. The basic point follows from the fact that we do not buy apples, for instance, according to the number of apples a shopper puts in a bag. Instead, the purchase price of a bag of a particular kind of apple is set by how much the apples weigh. The individual apples vary in size. A person with seven small apples in a bag would not expect to pay as much as they would for seven large apples, given that the apples are of the same kind and quality.

So we recognize that amounts of apples are not strictly related to numbers of apples. Fair trade depends on finding a way of measuring amounts of apple that stays constant across different groups of apples that naturally vary in size. International standards organizations work with weight scale manufacturers to make sure that the same amount of weight gives the same numeric reading, within an acceptable range of error, no matter which brand scale is used, no matter what is being weighed, and no matter who is using the scale.

Unfortunately, there are no international standards organizations yet working with test and survey publishers to see whether health and learning can be measured so that the same

Unless demand for more convenient and scientific measurement in health care and education grows, the supply of it is not likely to increase. The basic messages we want to convey are that

(1) health and learning outcomes can be quantified in units of measurement as rigorous as units of height, weight, time, and temperature;

(2) health and learning outcome measures can be made as familiar and widely available as measures of height, weight, time, and temperature; and

(3) the LSU Health Sciences Center and its Health Care Services Division are international leaders in the development and use of these measures.

The remainder of this article will address each of these three points in turn.

Measuring Quantities
To measure scientifically, researchers have to show, via experiments, that the variable of interest, such as health, learning, or satisfaction with services, adds up in the same way numbers do. The measurement of length, for instance, can be accomplished by placing a block of wood end-to-end with itself as many times as is needed to span a distance. Because we are counting the repetitions of a single block of wood, we know that every repetition is in fact one more of the same thing. The difference between 1 and 2 repetitions is the same amount of difference as that obtained between 3 and 4, between 112 and 113, or between any other pair of adjacent whole numbers. In order to measure, it is vitally important that researchers establish via experimental tests that the thing to be measured add up the same way the numbers used to represent it do.

Unfortunately, these experimental tests are rarely done. Because experimental evidence is not gathered, we do not really know whether many of the things we want to measure are actually quantitative. We therefore also do not know exactly what many of our tests and surveys actually measure. Finally, the lack of experimentally-calibrated instruments forces us to have different numerical scoring schemes for each different instrument, when what we need are different brand instruments for each different thing we want to measure, and which all measure in a uniform reference standard metric.

Different brand instruments should provide measures that indicate constant amounts of what is measured. It would be okay for the instruments to express those amounts in different numeric units, in the same way that inches and centimeters both indicate the same amount of length. A better system would be to have all instruments measuring one particular variable (physical functioning, for instance) do so in the same numeric unit. Research shows that different existing physical functioning instruments can in fact measure in the same unit even though they each phrase the questions on their instruments in slightly different ways.

Health and learning are not, of course, as easily measured as length, weight, time, or temperature. However, when data are evaluated, on the basis of which responses are most likely to occur (and measurement error is accounted for) health and learning data patterns are often found to meet the mathematical requirements for quite precise measurement. To obtain these kind of data, however, we must pay considerably more attention to both the design of tests, performance assessments, and surveys, as well as to the ways in which they are used.

As mentioned above, we have deeply ingrained cultural assumptions about the appropriate use of instruments, and these assumptions guide us toward producing high quality data in the measurement of height, for instance. Our lack of similar cultural expectations for the appropriate use of tests and surveys prevents us from gathering high quality data on health and learning, and it also prevents us from achieving the same kind of mathematical rigor and practical convenience that we enjoy with other kinds of instruments.

Access to Measures

Over the last 70 years, a wide variety of instruments for measuring health and learning have been shown to meet mathematically rigorous scaling requirements. And when these requirements are met, we see (1) that different brands of instruments intended to measure the same thing often actually do and (2) that the different brands of instruments could measure the same things in the same numeric units.

Now, instead of asking whether the blocks are longer than the distance from the origin to the mark on the ruler, we are asking people to answer questions that will tell us something about the amount of health, daily functionality, or learning they possess. When different brands of instruments are properly calibrated, they will measure constant, invariant amounts of the variable, even if they express those amounts with different numbers.

So why don't we have well known and widely available units of measurement expressing constant amounts of each of the key variables important to better understanding and managing health and learning? The answer to that question lies in another set of deeply ingrained cultural assumptions that we bring to bear when we think about and try to do measurement.

This set of assumptions has to do with the very ancient idea that the world is already quantitative in and of itself before we do anything to measure it. Even though instrument calibration is a very exacting process, and even though billions of dollars are spent on instrument development and maintenance every year, we seem to think that measuring units happen by themselves somehow, that they are so firmly a part of the world around us that we don't have to do anything to make them a part of our lives.

In the last 50 years, these assumptions have been challenged by work in the history, philosophy, and social studies of science, though the challenges have had little impact on measurement practice. The facts remain, however, that measurement, as the science of metrology, begins by calibrating individual instruments and that it progresses toward the quantitative coordination of different brands of instruments, so that users anywhere can tell when they are obtaining reasonable results and when they are not.

It is often said that a field of study is scientific to the extent that it is mathematical, but it is a mistake to think that the use of numbers automatically makes a field mathematical. A better way to think of the matter stems from the realization that a field is mathematical only to the extent that researchers working within it all share a common quantitative language in which they think about and act on the variables of interest. Without rigorously calibrated instruments and widely disseminated units of measurement, the common quantitative language does not exist.

Measurement at LSU Health Sciences Center and its HCSD

The LSU Health Sciences Center and its Health Care Services Division (HCSD) are taking steps toward both rigorously calibrating health surveys and educational tests, and toward coordinating instruments' units of measurement, by bringing together researchers and practitioners in various fields to educate them about the new possibilities and to help them take the first steps toward more rigorous and more convenient measurement.

A variety of tests and surveys intended for use in graduate medical education, hospital management, and health care research have been successfully calibrated over the last seven years. The disciplinary areas involved have included public health, preventive medicine, internal medicine, graduate medical education, pathology, genetics, and nursing. Measures have focused on matters such as chronic disease management (primarily diabetes and asthma), patient satisfaction, general health status, pain, obesity, and calibrating the human genome. The long term goals are to be able to demonstrate that rigorously quantitative units of measurement for each of these variables can be constructed, and to implement these units on a wide scale, putting instruments that provide the needed information into the hands of patients and providers at the point of care.

Diabetes management is one area in which improved measurement is being addressed. In 1994 in Louisiana, there were 115,508 diagnosed diabetes cases. Based on current LSUHSC-HCSD statistics, the HCSD hospitals are caring for about 17% of these cases (or about 20,000 persons). The incidence of diabetes in Louisiana far exceeds that of the rest of the nation. Recent statistics show that there are 33.4 diabetes cases per 100,000 persons in Louisiana, whereas there are about 21.8 cases per 100,000 persons in the U. S. as a whole.

The cost of diabetes accounts for 15% of all US health care expenditures. Based on American Diabetes Association (ADA) data, in 1992, the direct (medical care) and indirect (lost productivity) cost of diabetes in Louisiana was about $1,616,000,000 (1.6 billion dollars). In 1997, approximately 20,000 patients with diabetes were seen in the LSU hospitals and outpatient clinics with about 2,300 admissions for associated conditions. The average length of hospital stay for these 2,300 admissions was 8.8 days with a cost of about $900 per inpatient day.

Our Diabetes Disease Management Program is intended to address several needs. First, we need to help people with diabetes normalize their blood sugars. To do that, we need to implement systematic methods of education and provide the needed tools for glucose monitoring. We also need to continuously improve our diabetes care processes, patient-care giver relationships, use of resources, and clinical outcomes through research and education. Systems for doing so have either been put in place or are being designed.

The diabetes program is a disease management treatment program in which uninsured persons with diabetes are seen by physicians in the LSUHSC hospitals' outpatient clinics, tested and confirmed to have diabetes, placed on standard of care treatment drug therapy in accordance with ADA guidelines, and monitored for short and long term glycemic control and long term end organ complications.

Research suggests that a comprehensive outpatient care program for diabetes, with the institution of clearly defined ADA guidelines, can reduce hospitalization by 47%, reduce length of stay by 71%, reduce amputations by 50%, reduce the incidence of heart disease by 43%, and reduce kidney disease requiring dialysis by 43%.

The ADA has devised a set of recommended diabetes treatment processes and outcomes, with suggestions as to the minimum acceptable percentages of patients receiving the treatments and achieving the outcomes. Hospitals with percentages above the ADA minimums are eligible for certification in a Provider Recognition Program (PRP).

In the year 2000, the HCSD as a whole achieved PRP levels on three out of seven indicators. In a comparison with the performance of hospitals participating in nine different national health plans, the HCSD hospitals and patients achieved the same or better percentages on seven of eight indicators. The quality of diabetes care being provided to Louisiana's uninsured thus can stand comparison with diabetes care being provided anywhere in the nation. As the goals of improved measurement and disease management become better integrated, the quality of life for persons with diabetes will continue to improve.

Anyone interested in learning more about improved measurement or disease management are invited to contact the authors at the addresses below.

Contact Information
William P. Fisher, Jr., Ph.D.
Professor of Research
Public Health & Preventive Medicine
LSU Health Sciences Center
1600 Canal Street, Suite 1123
New Orleans, LA 70112
504-568-8083 (Office)
504-568-6905 (Fax)

Lauren Haygood, R.N., M.S.N., C.N.A.
RN Health Care Program Consultant
8550 United Plaza, suite 400
Baton Rouge, LA 70809
(225) 922-0747 (Office 1)
(337) 262-1849 (Office 2)

How to Learn More
Introductory and advanced courses on measurement theory and practice are taught at LSUHSC regularly. In April 2000, the Tenth International Objective Measurement Workshops (IOMW) were held at the LSU Health Science Center's Medical Education Building, and the Eleventh IOMW was held in New Orleans in April 2002.

Anyone interested in learning more about measurement or disease management is invited to consult the following resources.

A highly readable introduction to the basic measurement issues is provided by the book, Applying the Rasch model: fundamental measurement in the human sciences, by T. Bond and C. Fox (Mahwah, NJ: Lawrence Erlbaum Associates, 2001).

Information on measurement-related books, technical papers, professional associations, scientific journals, videos, software, conferences, seminars, consultants, a discussion list, and the full text of Rasch Measurement Transactions is available at

A comprehensive, general clearinghouse on disease management information is available at

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