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The American Journal of Managed Care May 2004
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Assessing Symptoms, Disease Severity, and Quality of Life in the Clinical Context: A Theoretical Framework
Tracy L. Finlayson, BS; Cheryl A. Moyer, MPH; and Seema S. Sonnad, PhD

Assessing Symptoms, Disease Severity, and Quality of Life in the Clinical Context: A Theoretical Framework

Tracy L. Finlayson, BS; Cheryl A. Moyer, MPH; and Seema S. Sonnad, PhD

Health-related quality-of-life instruments can yield important health information that is often distinct from objective measures of symptoms and disease severity that clinicians are most attuned to. Comprehensive health assessment can be difficult because there are many available measurement instruments that vary in their scope and content. The conceptual boundaries between symptom, disease severity, and health-related quality-of-life instruments are frequently blurred in practice, and what is measured may not coincide with clinical and research goals. The Assessing the Impact of Disease framework aims to clarify the process of selecting appropriate assessment instruments. Three common diseases are discussed in depth to illustrate the applicability of Assessing the Impact of Disease in distinguishing between symptom, severity, and health-related quality-of-life measurements.

(Am J Manag Care. 2004;10:336-344)

Illness affects more than patients' physical functioning: it may also affect their emotional, social, and occupational functioning. Recognizing that objective clinical indicators are not sufficient to assess the overall effect of disease, interest has focused on including patient-reported measures in disease assessment. Instruments that measure health-related quality of life (HRQOL) are increasingly important to clinicians and researchers conducting disease assessment studies.

Nonetheless, disease severity and symptom assessment are important components of assessing the burden of disease, and such assessments often provide information distinct from HRQOL assessment. Yet, HRQOL instruments vary in scope and content and may incorporate symptom and severity assessment to varying degrees, making it challenging to discern the realms each instrument addresses.

Given these issues and the numerous tools to choose from, instrument selection becomes a complex task. Our framework, Assessing the Impact of Disease (AID) assists clinicians in identifying which realm of assessment– symptoms, disease severity, or HRQOL–is of greatest interest for their clinical or research purposes. It also aims to assist clinicians in determining which corresponding instruments might be most appropriate for their clinical and research goals. Without an understanding of the distinctions between these measurement concepts, clinicians may overlook dimensions of assessment that may prove critical in improving patient care. Therefore, the AID framework was developed to help clinicians clarify the dimensions of greatest interest to their research and improve study design by facilitating decisions regarding the most appropriate measurement tools.



Symptoms are experienced deviations from an individual's perception of his or her normal, healthy state of being, yet not necessarily an indicator of illness. A symptom can emerge from sensitivity to certain combinations of biological, social, and environmental processes and vary in magnitude, severity, persistence, and character. Symptoms can be subjectively reported or objectively observed. If patients are subjectively surveyed about their symptoms, the findings can be problematic. For example, at different time points, an individual may not perceive the same aberration in health as a symptom or cause for alarm.1 In addition, symptoms can become integrated into the scope of normal experiences or be ignored for various reasons such as fear of stigmatization, embarrassment, or the expectation of other adverse reactions or consequences from society.2

Objective symptom assessment also has drawbacks. Depending on the disease, the scope, intensity, and duration of symptoms can vary over time. In addition, patients may not report all symptoms to their clinicians or realize that physiological changes may be related to illness. Therefore, the presence, absence, or severity of a symptom may be overlooked or attributed to noncausal factors.

Disease Severity

Disease severity refers to the presence and extensiveness of a disease in the body. It is objectively evaluated through diagnostic testing and physiological examination of the impaired biological organs or tissues, in cases in which disease severity can be distinguished from other realms of health, as in heart disease. The amount of plaque buildup in the heart can be measured, and the corresponding severity level of the disease can be determined. In this example, disease severity information can be contrasted with symptom assessment by considering 2 matched patients with moderate plaque buildup. One patient could complain of chest pains and express symptoms indicative of heart disease, but it would not be unusual if someone else with laboratory results indicating an equally severe disease state to experience a different set of functional limitations and symptoms.

Health-Related Quality of Life

Despite the growing interest in quality of life, debate continues over the appropriate terminology and classification of many quality-of-life concepts and whether they belong under the rubric of HRQOL.3 From the late 1970s to the 1990s, articles that included the concept of quality of life appeared in increasing numbers on MEDLINE from health services researchers using instruments as an outcome measure of medical care and in clinical and population studies. In 1974, there were 40 references, but by 1999, more than 12 000 references were cited and today the number is approaching 40 000.4 In 1987, Ware noted that it had become "fashionable to equate health, defined comprehensively, with quality of life" (emphasis in original).5 Health-related quality of life is elusive, because it can be defined in a way that includes other abstract and concrete aspects of life or quality of life, such as well-being, pain, and happiness.6,7 However, subjective reports of these concepts are not sufficient for generating HRQOL scores or substituting for HRQOL information.

Although there is no gold standard or agreed-on definition for the scope of HRQOL, several prominent HRQOL conceptualizations include the physical, psychological, social, spiritual, role functioning, and general well-being dimensions of health. These conceptualizations are based on the World Health Organization (WHO) definition that "health is complete physical, mental, and social well-being, and not merely the absence of disease and infirmary."8 The WHO definition has become a common starting point for research and discussion of overall health status and HRQOL. Moyer and colleagues9 provide a review of commonly used generic HRQOL instruments, and additional studies10-14 describe some important aspects to consider when choosing HRQOL instruments.

Different conceptualizations of HRQOL may not assess a patient's overall quality of life or yield information about all the dimensions and domains contributing to HRQOL. Schipper et al offer a clinical definition of HRQOL based on physical and occupational function, psychological function, social interaction, and somatic sensation domains: "Quality of life in clinical medicine represents the functional effect of an illness and its consequent therapy upon a patient, as perceived by the patient."15 (p16) In this definition, the functional effect of an illness is important yet difficult to define because it is closely related to the concepts of symptom and disease severity.


Two frequently consulted conceptualizations of HRQOL assessment are the pyramid model by Spilker3 and the model of patient outcomes by Wilson and Cleary.16 However, these models do not address the differences between assessing symptoms, disease severity, and HRQOL, or how to select appropriate instruments once specific measurement goals are identified.

Spilker3 presents the definition and scope of HRQOL in 3 levels of a pyramid. A patient's overall assessment of well-being is at the top of the pyramid (level 1). The middle section (level 2) contains the broad domains that contribute to HRQOL, and the many possible components of each domain comprise the base of the pyramid (level 3). This model was intended to enable researchers or clinicians to include different domains or components of interest in HRQOL assessment, providing the ability to approach HRQOL assessment from a bottom-up or top-down perspective.

However, the pyramid model does not adequately represent the relationships among HRQOL and other related health concepts. According to the model, symptoms and physical functioning measures exist as subsets that contribute to an overall HRQOL score. Spilker notes that, although the number and identity of domains vary, "each cuts the overall pie (level 1) into different pieces of domains (level 2)."3 (p3) The levels are related in a hierarchical fashion, with level 1 including all of the contents of levels 2 and 3. This characterization does not allow for components of different domains to overlap. The model also fails to consider the effects of other health measurements on HRQOL, such as severity of disease. Disease severity can affect health and overall well-being, yet is not included in the pyramid model. Often, disease severity information is useful for contextualizing HRQOL scores and explaining changes over time, and should be part of a comprehensive assessment of the effect of disease. Spilker's pyramid is useful as an educational tool for understanding HRQOL and its component realms, but may not be ideal when applied to all clinical situations.

In the causal pathway of patient outcomes presented by Wilson and Cleary,16 disease severity is accounted for at the first level of the model by biological and physiological variables reflecting health and functioning at the genetic level. The next 4 levels include symptom status, functional status, general health perceptions, and overall quality of life. Each of the 5 outcome levels accounts for various indirect and direct inputs and factors out of the control of clinicians and the health system that affect health outcomes. This model maps causal relationships between patient outcome measures to increase understanding about the pathogenesis of impairment and enable the development of more effective interventions. This model is most useful for examining many health factors and HRQOL, yet it does not offer clinicians guidance in choosing the specific tools to measure each factor.

The AID framework that we propose incorporates the effect of disease severity on HRQOL and offers relevant guidance in disease assessment. Assessing the Impact of Disease presents the relationships among measures of symptoms, disease severity, and HRQOL in a model that allows the measurement of health concepts to overlap (Figure 1). Our figure is symmetrical for simplicity in illustration; however, it does not reflect the relationships among these concepts for every disease. The AID framework recognizes that, in some disease states, symptom measurement cannot be separated in practice from disease severity measurement. We draw attention to the various instruments and underlying health concepts being assessed for different classes of diseases. This information can increase a clinician's understanding of which health domain he or she is measuring and its effect on the individual's overall well-being.

The next section presents case studies of several diseases. Each case study illustrates how the focus of measurement instruments draws on different realms of health, leading to the need for careful instrument selection in clinical practice.


We identify 3 classes of diseases with contrasting degrees of conceptual overlap. We chose urinary incontinence (UI), obstructive sleep apnea (OSA), and gastroesophageal reflux disease (GERD) as examples of the differences between symptom assessment, disease severity, and HRQOL using the AID framework. These case studies were selected to illustrate varying degrees of conceptual overlap, not to describe the clinical scenarios most commonly associated with HRQOL assessment.

Case Study 1: Urinary Incontinence

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