Next Lesson - Health Economics
Core
Most chronic illnesses are disabling in some way, but they do not always cause the patient to become disabled. Disability is a complex and personal topic to many and this article only attempts to explore some of the established models on the subject.
Models of disability
There are 2 key models of disability:
- Medical model: Disability is caused by deviation from the medical norm and as a result interventions should aim to return the patient as close as possible to the medical norm. The limitations and disadvantages of disability stem from the existence of an impairment. Therefore the aim of treatment is to fix the impairment itself.
- Social model: There is an intrinsic failure of society to adjust to those with differing needs. This lack of consideration and adjustment leads to the creation of disability. Disability is therefore a form of social oppression and social change is required to prevent disability occurring.
The social model acknowledges the role of disabling environments; an individual is only seen as being disabled as a result of the demands of the environment. For example, dyslexia is only seen as a learning difficulty in a society that values the ability to read, write or spell.
There are pros and cons of both models and the best approach likely lies somewhere between the two.
The WHO has published a number of classifications on disability. Their initial classification was the ICIDH (international classification of impairments, disabilities and handicaps). This classification defined:
- Impairment - the physical abnormality in structure, or an abnormality in function of the body.
- Disability - difficulty performing certain tasks due to an impairment.
- Handicap - the broader social and psychological consequences of living with an impairment or disability.
The ICIDH has been superseded by the ICF (international classification of functioning, disability and health). This is as the ICIDH implied definite progression from each definition to the next i.e. impairment will lead to disability which will lead to handicap. The ICIDH’s use of the term handicap is also seen by some as problematic and outdated.
The ICF defined 3 components:
- Body structure and function.
- Activity.
- Participation in life situations.
Each of the 3 component is roughly analogous to the previous ICIDH definitions respectively but act to describe the individual as well as their environment rather than boxing individuals into problematic classifications.
Lay beliefs of health stem from what health means to the average person who has no medical training (the ‘lay-person’ or ‘man on the street’). Lay beliefs can be socially embedded and can influence behaviour regarding health. This can be detrimental because there can often be discrepancies between medical knowledge and lay beliefs. This can lead to varying acceptance of medical advice and can influence concordance to treatment.
Lay beliefs develop naturally as a community seeks to understand health conditions. This is further hampered by the fact that medical concepts can sometimes be difficult to understand, and lay beliefs can exist as a simplified although possibly distorted version.
There are three important behaviours that patients may partake in:
- Health behaviour - activity undertaken to maintain health and prevent illness. This could include eating healthily and taking regular exercise.
- Illness behaviour - activity undertaken by a patient who feels ill to define the problem and seek treatment. This could include seeing a doctor to get a diagnosis and negotiating an agreed treatment plan.
- Sick role behaviour - activity performed by a patient who is ill to actively make themselves better. This includes taking medications prescribed.
Illness behaviour can be affected by many factors because it involves the patient admitting there is a problem and seeking help, which can be difficult for some patients. It therefore depends on the following things:
- Culture - some cultures believe that seeking help from an external source is a bad thing, for example, men who are encouraged to "man up" instead of seeking counselling for mental health problems.
- Visibility of symptoms - it can be easier to delay illness behaviour if the symptoms are easy to hide.
- Extent of disruption - illness behaviour often occurs more quickly if the illness interferes with daily life or work.
- Information available - if the patient is worried about their health due to a prospective diagnosis of cancer (even if this is unlikely) they might be less likely to perform illness behaviour because they don’t want to receive the bad news.
- Lay referral - this is when someone close to the patient recommends certain services to the patient. This is important because it often explains delays to seeking professional help and why some patients present ‘now’ e.g. ‘my partner told me to come in to get seen,’ the patient has first talked to their partner (another lay person) who has ‘referred’ the patient to the doctor.
There are three main categories that patients may fall into with regards to concordance to treatment:
- Deniers - individuals who don’t believe they have the disease, so don’t follow the treatment plan as that would mean accepting the condition. This is related to distancers patients who downplay their condition and symptoms as not needing treatment and non-serious.
- Accepters - these people accept that they have the condition and view it as vital that they adhere to the treatment plan, so they can achieve normal life.
- Pragmatists - individuals who only seek help on deterioration, when the condition becomes practically bothersome.
Health promotion is the process of enabling people to increase control over and improve their own health. There are five different parts of it:
- Medical interventions to protect from risk - e.g. statins to reduce cardiovascular disease risk, gastric band surgery to reduce obesity.
- Behaviour change - e.g. campaigns on TV encourage positive behaviour changes, like the Change4Life program run in the UK.
- Educational - campaigns run in education, e.g. healthy eating classes in primary schools.
- Empowerment - making the public aware and able to access the services that they need to help improve their health.
- Social change - often through regulations, e.g. the sugar tax on sugary drinks, the public smoking ban in the UK.
PROMs
A patient reported outcome measure (or PROM) is a tool used to measure the outcomes of interactions that patients have with healthcare from their own perspective. It is distinct from a patient reported outcome (PRO) which is feedback directly from the patient with no tool in between.
PROMs can be generic (for any patient population) or disease specific (for a particular condition); unidimensional (focussed on symptoms) or multidimensional (global health related quality of life).
PROMs are important because they assess:
- Symptom burden and psychological impact that are often under-recognised in patient populations.
- Place more emphasis on quality of life rather than simply length of life.
- They are helpful in improving and guiding patient clinician decision making.
- Provide the patient’s perspective which the clinician may otherwise have missed.
Clinical trials often use PROMs as part of their structure. This is because they provide quantifiable data which is clinically meaningful so can help with monitoring progression of a condition and efficacy of treatment. They can also be used to monitor adherence, assess adverse effects and calculate QALYs (see our article on healthcare economics) by providing information on survival and adverse effects.
When evaluating PROMs to use, certain characteristics must be considered:
- Appropriateness - are the questions asked going to get the desired information?
- Acceptability - will it be acceptable to patients? i.e. will they be able to fill it out, understand the questions, be willing to complete it.
- Feasibility - is it easy to administer and process?
- Interpretability - are the results easy to interpret and do they produce meaningful information?
- Reliability - are the results reproducible?
- Validity - does it measure what it claims to?
- Responsiveness - does it detect changes that matter to patients?
There are three levels of prevention that can be put into place to help prevent adverse effects on health:
These interventions prevent the onset of disease by reducing exposure to risk factors. This can be done by four main methods:
- Immunisations
- Prevention of contact with environmental risk factors - for example, using bug spray to protect against mosquito bites.
- Taking precautions regarding communicable disease - for example, wearing condoms to prevent against sexually transmitted diseases.
- Reducing health-related behaviour risk factors - for example, stopping people smoking.
These interventions aim to detect and treat a disease (or the risk factors) at an early stage to prevent future complications. Examples include: screening programmes for cervical cancer and monitoring and treating hypertension.
These interventions aim to minimise the effects of established disease. Examples include: giving steroids to treat asthma and giving renal transplants in renal failure.
A screening programme is a form of secondary prevention that acts to detect early stages of a disease in order to treat it before it becomes an issue. It must have many qualities to become a nationwide screening programme in Britain, which are based on the Wilson-Jungner Criteria:
- The condition for which it screens must be frequent and severe - this article will use the example of the cervical cancer screening programme.
- Primary prevention methods should have been considered - for example, HPV vaccination.
- The test must be simple, safe, precise and inexpensive - smear tests fit all of these.
- There must be an agreed target population - all women 25-49 in Britain are invited every three years, and all women 50-64 are invited every five years.
- There must be evidence that intervention at this pre-symptomatic stage is beneficial - in cervical screening, pre-cancerous cells (called Cervical Intra-epithelial Neoplasia or CIN) can be detected and successfully treated to prevent disease progression.
- The opportunity cost must be acceptable (opportunity cost is the amount that it would cost to perform the service, and the amount of benefit that you could get from that money if it was invested elsewhere).
- The screening programme must be possible to implement - a smear test can be performed by a trained nurse.
There are a number of types of screening programmes:
- Mass screening screens every individual for diseases. An example of this is the newborn blood spot tests, that screen every baby for genetic conditions such as cystic fibrosis.
- Selective screening involves offering the screening test for only at-risk populations. An example of this is the cervical screening programme in the UK, where cervical smear tests are offered every 3 years to women between 25 and 49, and every 5 years between 50 and 64.
- Opportunistic screening is a screening programme implemented only when the opportunity arises. An example of this is a GP checking the blood pressure of anyone over 60 years old who presents to them in general practice; no one is called in for this, it is done because they are already there.
Screening tests are indicative of the risk a person has of having the disease. They are not diagnostic.
True Positive - individuals with a disease who receive a positive screening test result. This means that it indicates they have a high chance of having the disease, and so are referred for further testing. This is good because it means that the people with the disease are caught early, diagnosed and treated.
True Negative - healthy individuals who receive a negative screening test result. This means that the screening test indicates they have a low chance of having the disease, which is good because they’re healthy. This means that further testing or treatment which may in itself be harmful is avoided.
However, it is possible to get results out of the screening test that are incorrect.
False Positive - healthy people getting a positive screening test result. This means the test indicated they have a high chance of having the disease, but they don’t in reality and are referred for further testing. The result of this is expensive and possibly harmful further testing that reveals they are healthy.
False Negative - diseased people getting a negative screening test result. This means the test indicated they have a low chance of having the disease, but they really do have it, and are not referred for further screening. The result of this is a patient with the early stages of a disease not being diagnosed, so they are left to go on and develop the disease. This causes a delay in diagnosis and may lead the patient coming to harm from the worse outcomes from the more progressed disease
Diagram - The process a patient will go through if they have a screening test performed in secondary prevention. A screening test shows the likelihood of the person having the disease, and is not a complete diagnostic test. It is still important to remember that patients who screen negative could still have the disease, they are just not investigated any further
SimpleMed original by Dr. Maddie Swannack
Table - The relationship between the screening result and the true state of the patient
SimpleMed original by Dr. Maddie Swannack
Key Terms
There are several key terms regarding screening tests that relate to the values shown in the table above.
Sensitivity - proportion of people with the disease who test positive (number of true positives).
- High sensitivity = good at picking up the disease.
- Sensitivity = a / (a+c)
- This is the number of true positives divided by total number of patients with the disease.
Specificity - proportion of people without the disease who test negative (true negatives).
- High specificity = good at ruling out healthy people.
- Specificity = d / (b+d)
- This is the number of true negatives divided by total number of healthy patients.
It is important to remember that when a test is applied in the exact same way to a different population, specificity and sensitivity will stay the same because they are features of the test rather than of the population.
Positive Predictive Value (PPV) - probability that someone who tested positive actually has the disease.
- Higher positive predictive value = more accurate at indicating disease state.
- PPV = a / (a+b)
- This is true positives divided by number of people who tested positive.
Negative Predictive Value (NPV) - probability that someone who tested negative is actually healthy.
- Higher negative predictive value = more accurate at indicating healthy state
- NPV = d / (c+d)
- This is the true negatives divided by the number of people who tested negative.
Sensitivity and specificity describe a test at a chosen threshold, but they do not by themselves show how much an individual result changes the probability of disease. Continue with likelihood ratios and ROC curves to connect pre-test probability with post-test probability and to see how changing a threshold trades sensitivity against specificity.
Evaluating Screening Programmes
Screening programmes can be difficult to evaluate because they have a number of intrinsic biases.
Lead time bias
The early diagnosis caused by screening programmes can falsely appear to prolong the survival.
For example; a patient once developing this condition will die within 10 years regardless of intervention. When not screened the patient presents 8 years after initially developing the condition which is now in its late stages and has been noticed by its symptoms. As a result the survival of the patient is 2 years post diagnosis.
If screened the patient is diagnosed with the disease after 5 years as the test picks up the condition in its early stages before the patient notices any symptoms. However the patient still dies 5 years later. When screened the patient has a survival of 5 years.
This means that it appears that screening adds 3 years to survival when in fact the patient dies at the same time and is simply diagnosed earlier.
Length time bias
Screening programmes can cause otherwise benign conditions that would not cause harm in the long term to be picked up. This means that potentially harmful, painful and expensive treatment may be given to a patient that would not have been needed if a harmless disease state had not been picked up by screening. This is true of prostate cancer which a large proportion of elderly men die with rather than die from. Treatment in all of these cases would of course be unsuitable as it would only cause preventable expenditure and most importantly preventable suffering.
Selection bias
Those members of the public who attend screenings could also be the ones who are likely to do other things that are protective to their health, making the disease less likely in this group to begin with.
Edited by: Dr. Ben Appleby
Reviewed by: Dr. Thomas Burnell
In this article
Most chronic illnesses are disabling, but not all patients with chronic illnesses are disabled.
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