Quality of life (healthcare)

In general, quality of life (QoL or QOL) is the perceived quality of an individual's daily life, that is, an assessment of their well-being or lack thereof. This includes all emotional, social, and physical aspects of the individual's liPfe. In health care, health-related quality of life (HRQoL) is an assessment of how the individual's well-being may be affected over time by a disease, disability, or disorder.

Measurement
Early versions of healthcare-related quality of life measures referred to simple assessments of physical abilities by an external rater (for example, the patient is able to get up, eat and drink, and take care of personal hygiene without any help from others) or even to a single measurement (for example, the angle to which a limb could be flexed).

The current concept of health-related quality of life acknowledges that subjects put their actual situation in relation to their personal expectation. The latter can vary over time, and react to external influences such as length and severity of illness, family support, etc. As with any situation involving multiple perspectives, patients' and physicians' rating of the same objective situation have been found to differ significantly. Consequently, health-related quality of life is now usually assessed using patient questionnaires. These are often multidimensional and cover physical, social, emotional, cognitive, work- or role-related, and possibly spiritual aspects as well as a wide variety of disease related symptoms, therapy induced side effects, and even the financial impact of medical conditions. Although often used interchangeably with the measurement of health status, both health-related quality of life and health status measure different concepts.

Similar to other psychometric assessment tools, health-related quality of life questionnaires should meet certain quality criteria, most importantly with regard to their reliability and validity. As such, hundreds of validated health-related quality of life questionnaires have been developed to suit the needs of various illnesses. The questionnaires can be generalized into two categories:
 * 1) Generic instruments (e.g. SF-36, Short-Form with 36 questions)
 * 2) Disease, disorder or condition specific instruments (e.g. the King's Health Questionnaire (KHQ) or the International Consultation on Incontinence Questionnaire-Short Form (ICIQ-SF) in urinary incontinence, the LC -13 Lung Cancer module from the EORTC Quality of Life questionnaire library, or the Hospital Anxiety and Depression Scale (HADS) ).

Activities of daily living
Because health problems can interfere with even the most basic aspects of daily living (for example, breathing comfortably, sleeping comfortably, eliminating wastes, feeding oneself, dressing, and others), the health care professions have codified the concepts of activities of daily living (ADLs) and instrumental activities of daily living (IADLs). Such analysis and classification helps to at least partially objectify quality of life. It cannot eliminate all subjectivity, but it can help improve measurement and communication by quantifying and by reducing ineffability.

Examples
Here are some examples of frequently used health-related quality of life questionnaires:
 * quality of life/health-related quality of life14_measure.htm Healthy Day Measures: A questionnaire with four base questions and ten optional questions used by the Center for Disease Control and Prevention (CDC).
 * ECOG, most commonly used to evaluate the impact of cancer on sufferers.
 * NYHA scale, most commonly used to evaluate the impact of heart disease on individuals.
 * Short-Form Health Survey: One example of a widely used questionnaire assessing physical, social, and mental health-related quality of life, used in clinical trials. Suitable for pharmacoeconomic analysis, benefiting healthcare rationing.
 * Manchester Short Assessment of Quality of Life: 16-item questionnaire for use in psychiatric populations.
 * EQ-5D a simple quality of life questionnaire.
 * WHO-Quality of life BREF: A general Quality of life survey validated for several countries.

Utility
A variety of validated surveys exist for healthcare providers to use for measuring a patient’s health-related quality of life. The results are then used to help determine treatment options for the patient based on past results from other patients.

When it is used as a longitudinal study device that surveys patients before, during, and after treatment, it can help health care providers determine which treatment plan is the best option, thereby improving healthcare through an evolutionary process.

Importance
There is a growing field of research concerned with developing, evaluating, and applying quality of life measures within health related research (e.g. within randomized controlled studies), especially in relation to Health Services Research. Well-executed health-related quality of life research informs those tasked with health rationing or anyone involved in the decision-making process of agencies such as the Food and Drug Administration, European Medicines Agency or National Institute for Clinical Excellence. Additionally, health-related quality of life research may be used as the final step in clinical trials of experimental therapies.

The understanding of Quality of Life is recognized as an increasingly important healthcare topic because the relationship between cost and value raises complex problems, often with high emotional attachment because of the potential impact on human life. For instance, healthcare providers must refer to cost-benefit analysis to make economic decisions about access to expensive drugs that may prolong life by short amount of time and/or provide a minimal increase to quality of life. Additionally, these treatment drugs must be weighed against the cost of alternative treatments or preventative medicine. In the case of chronic and/or terminal illness where no effective cure is available, an emphasis is placed on improving health-related quality of life through interventions such as symptom management, adaptive technology, and palliative care.

Research
Research revolving around Health Related Quality of Life is extremely important because of the implications that it can have on current and future treatments and health protocols. Thereby, validated health-related quality of life questionnaires can become an integral part of clinical trials in determining the trial drugs' value in a cost-benefit analysis. For example, the Center for Disease Control and Prevention (CDC) is using their health-related quality of life survey, quality of life/health-related quality of life14_measure.htm Healthy Day Measures, as part of research to identify health disparities, track population trends, and build broad coalitions around a measure of population health. This information can then be used by multiple levels of government or other officials to "increase quality and years of life" and to "eliminate health disparaties" for equal opportunity.

Ethics
The quality of life ethic refers to an ethical principle that uses assessments of the quality of life that a person could potentially experience as a foundation for making decisions about the continuation or termination of life. It is often used in contrast to or in opposition to the sanctity of life ethic.

Statistical biases
It is not considered uncommon for there to be some statistical anomalies during data analysis. Some of the more frequently seen in health-related quality of life analysis are the ceiling effect, the floor effect, and response shift bias.

The ceiling effect refers to how patients who start with a higher quality of life than the average patient do not have much room for improvement when treated. The opposite of this is the floor effect, where patients with a lower quality of life average have much more room for improvement. Consequentially, if the spectrum of quality of life before treatment is too unbalanced, there is a greater potential for skewing the end results, creating the possibility for incorrectly portraying a treatment's effectiveness or lack thereof.

Response Shift Bias
Response shift bias is an increasing problem within longitudinal studies that rely on patient reported outcomes. It refers to the potential of a subject’s views, values, or expectations changing over the course of a study, thereby adding an additional factor of change on the end results. Clinicians and healthcare providers must recalibrate surveys over the course of a study to account for Response Shift Bias. The degree of recalibration varies due to factors based on the individual area of investigation and length of study.

Statistical variation
In a study by Norman et al. about health-related quality of life surveys, it was found that most survey results were within a half standard deviation. Norman et al. theorized that this is due to the limited human discrimination ability as identified by George A. Miller in 1956. Utilizing the Magic Number of 7 ± 2, Miller theorized that when the scale on a survey extends beyond 7 ± 2, humans fail to be consistent and lose ability to differentiate individual steps on the scale because of channel capacity.

Norman et al. proposed health-related quality of life surveys use a half standard deviation as the statistically significant benefit of a treatment instead of calculating survey-specific “minimally important differences", which are the supposed real-life improvements reported by the subjects. In other words, Norman et al. proposed all health-related quality of life survey scales be set to a half standard deviation instead of calculating a scale for each survey validation study where the steps are referred to as "minimally important differences".