Month: October 2023

Measures of Disease Frequency: Incidence and Prevalence

In this post, I will discuss methods used to measure the frequency of disease: incidence and prevalence. These are essential tools for governments, health care planners, doctors, public health specialists, and epidemiologists in their efforts to protect the health of the public.

Incidence is the rate at which new cases of a disease occur in a population during a specified time period. It is calculated by dividing the number of new cases by the population at risk during that time period.

Incidence Rate =  Number of new cases / Person-time at risk  × N

Where N is a number such as 1,000 or 100,000.

For example, if there were 100,000 myocardial infarctions in England each year, the annual incidence would be 1.75 per 10,000 people (100,000 / 57,000,000 x 10,000).

Prevalence is the proportion of individuals in a population who have a disease or other health outcome of interest at a specified point in time (point prevalence) or during a specified period of time (period prevalence). It is calculated by dividing the number of people with the disease by the total population.

Point Prevalence: The number of cases at a specific point in time.

Point Prevalence = Number of cases at a point in time / Total population at that time x N

For example, if there are 4,000,000 people with diabetes in England, the point prevalence of diabetes is 7.0 per 100 people of 7.0% (4,000,000 / 57,000,000 x 100).

Period Prevalence: The number of cases over a specific period.

Period Prevalence = Number of cases during a time period / Average population during the period x N

What methods are used to provide the data needed to measure incidence and prevalence?

There are a range of methods used to measure incidence and prevalence, depending on the specific disease or health outcome being studied and the available resources. Some common methods include:

Surveillance systems: Surveillance systems are used to collect data on the occurrence of disease or other health events on an ongoing basis. This data can be used to calculate incidence and prevalence rates, as well as to track trends over time.

Cohort studies are observational studies that follow a group of people over time to track the occurrence of disease or other health outcomes. Cohort studies can be used to calculate incidence rates, as well as to identify risk factors for disease.

Cross-sectional studies are observational studies that collect data on a group of people at a single point in time. Cross-sectional studies can be used to calculate prevalence rates, but they cannot be used to calculate incidence rates (unless they are repeated over time: serial cross-sectional studies).

With the greater use of electronic health records by the NHS and other health systems, these are now increasingly used to calculate measure of disease frequency such as incidence and prevalence. But these data do have limitations. For example, some problems may not be well-recorded in electronic health records as they rely on patients presenting to health services; and errors an omissions in the coding of clinical data are also common.

How do we interpret incidence and prevalence?

Incidence and prevalence rates can be influenced by a variety of factors, including the following:

Age: Incidence and prevalence rates often vary by age. For example, some diseases are more common in children, while others are more common in adults.

Sex: Incidence and prevalence rates also vary by sex. For example, some diseases are more common in men, while others are more common in women.

Race and ethnicity: Incidence and prevalence rates can also vary by race and ethnicity. For example, some diseases are more common in certain racial and ethnic groups.

Geography: Incidence and prevalence rates can also vary by geographic location. For example, some diseases are more common in certain countries or regions.

All of these factors must be considered when interpreting incidence and prevalence data. For example, if comparing the incidence of a disease in two different countries, it is important to make sure that the populations being compared are similar in terms of age, sex, race and ethnicity, and other relevant factors.

How are incidence and prevalence used?

Disease surveillance: Incidence and prevalence data can be used to track the occurrence of disease or other health events over time and to identify areas where there may be increased risk.

Research: Incidence and prevalence data can be used to identify risk factors for disease, to develop new diagnostic tests and treatments, and to evaluate the effectiveness of public health interventions.

Healthcare programme planning and evaluation: Incidence and prevalence data can be used to plan and evaluate health services and public health programmes, such as vaccination programmes and screening programmes.

Conclusions: Incidence and prevalence are two important measures of disease frequency. These measures can be used to track health trends over time, to identify risk factors for disease, and to plan and evaluate public health and healthcare interventions. It is important to interpret incidence and prevalence data carefully, considering all of the factors that can influence these rates.

New Awareness Campaign to Help Reduce Hospital Admissions for Urinary Tract Infections

A new campaign from NHS England and the UKHSA aims to raise awareness about the prevalence and risks of urinary tract infections (UTIs), particularly among older people and carers, and to reduce hospital admissions related to UTIs.

The campaign offers advice on preventive measures. It emphasizes the importance of staying hydrated, going to the toilet as soon as the need arises, and maintaining hygiene in the genital area. Resources, including posters, are being made available to healthcare services, charities, royal colleges, and care homes to disseminate this information as widely as possible.

The guidance comes ahead of a potentially busy winter season for the NHS, a time when the health service is usually under increased pressure. As part of a larger effort to manage healthcare resources, the campaign encourages the use of alternative services like NHS 111, community pharmacists, and urgent care walk-in centres for less critical cases. This is in line with the broader NHS plan of expanding out-of-hospital care options, including “hospital at home” services and urgent community response teams.

UTIs are particularly dangerous for older adults. Prompt action and early treatment are stressed as critical for managing UTIs and preventing severe outcomes like sepsis or death.

The campaign is part of a larger effort to prepare for increased demand during the winter months and aims to improve public awareness and self-care measures to reduce the need for hospital admissions.

What issues do NHS clinicians need to consider in using this guidance?

1. It is more difficult to diagnose UTIs in older people. Younger people (who will nearly all be women) will usually present with the “classical” symptoms of  UTI – such as frequency, dysuria, urgency and haematuria. Older people can have these symptoms but they can also present with problems such as confusion, agitation, functional decline or lethargy where there is a large overlap with other conditions; making diagnosis more challenging.

2. Another challenge in older people is that some will have asymptomatic bacteriuria (i.e. bacteria in the urine that are not causing problems). When the bacteria are detected, doctors will often treat the patient with antibiotics when the medication may not be needed.

3. Spotting infections early requires knowledge of the symptoms and signs and how these differ in younger and older people. There is also a need to be aware of the complications of UTIs such as sepsis or pyelonephritis and to treat these early.

4. Doctors and patients need to balance the benefits of early diagnosis treatment with the risks of overtreatment with antibiotics. Not all UTIs need antibiotic treatment and some may resolve without it. Overuse of antibiotics contributes to antibiotic resistance as well as putting patients at risk of side effects.

5. Finally, these kind of single issue campaigns will be of limited value unless there is adequate capacity in the NHS for patients to be assessed promptly. Otherwise, patients will end up waiting a long time for appointments with the risk their condition may worsen while waiting for treatment.

Making Sense of Sensitivity, Specificity and Predictive Value: A Guide for Patients, Clinicians and Policymakers

In this post, I will discuss sensitivity, specificity and positive predictive value in relation to diagnostic and screening tests. Many more people have become aware of these measures during the Covid-19 pandemic with the increased use of lateral flow and PCR tests.

In clinical practice and public health, sensitivity, specificity, and predictive value are important measures of the performance of diagnostic and screening tests. These measures can help clinicians, public health specialists and the public to understand the accuracy of a test and to make informed decisions about its use in patient care.

Sensitivity: The proportion of people with a disease who test positive on a diagnostic or screening test.

Sensitivity = True Positives / (True Positives + False Negatives)

Specificity: The proportion of people without a disease who test negative on a diagnostic or screening test.

Specificity = True Negatives / (True Negatives + False Positives)

Positive predictive value (PPV): The proportion of people who test positive on a diagnostic test who actually have the disease.

Positive Predictive Value = True Positives / (True Positives + False Positives)

Negative predictive value (NPV): The proportion of people who test negative on a diagnostic test who actually do not have the disease.

Negative Predictive Value = True Negatives / (True Negatives + False Negatives)

How do we Interpret sensitivity, specificity, and predictive value?

Sensitivity and specificity are linked measures. A test with high sensitivity is good at identifying people with a disease, but it may also produce false positives in people who do not have the disease. A test with high specificity is good at identifying people who do not have a disease, but it may also produce false negatives in people who do have the disease. In general, as sensitivity increases, specificity decreases; and vice versa.

Positive Predictive Value (PPV) depends on the prevalence of the disease in the population being tested. In a population with a high prevalence of disease, a positive test result is more likely to be a true positive. Conversely, in a population with a low prevalence of disease, a positive test result is more likely to be a false positive.

In clinical and public health practice this means that a test can have a high sensitivity and specificity but if it is being carried out in a population with a low prevalence, most positive tests are false positives; thereby limiting the value of a positive test. This is why a test can vary in its performance in primary care (where prevalence of a condition is often low) and in hospital care (where prevalence will generally be higher).

The Covid-19 pandemic brought global attention to the importance of diagnostic test parameters such as sensitivity, specificity and positive predictive value. Initial Covid-19 tests often prioritised sensitivity to capture as many positive cases as possible. However, as the pandemic progressed, the need for more specific tests became clear to minimise false positives that could distort public health strategies. For example, a false positive test could result in a person isolating or staying off work or school unnecessarily.

A test with a high Negative Predictive Value means that it is good at ruling out disease in people who test negative. This is important for public health interventions, such as contact tracing, where it is important to identify people who are unlikely to be infected with a disease so that they can be excluded from further monitoring and isolation.

The pandemic underscored that no single measure—sensitivity, specificity, or predictive value—could offer a complete picture of a test’s effectiveness.

Example of a diagnostic test: A Covid-19 test has a sensitivity of 90%, meaning that 90% of people with a Covid-19 infection will test positive on the test. The test has a specificity of 98%, meaning that 98% of people without Covid-19 will test negative on the test.

The PPV of the test will vary depending on the prevalence of Covid-19 in the population being tested. For example, if 5% of people in a population have Covid-19, then the PPV of the test will be 70%. This means that 70% of people who test positive on the test will actually have Covid-19.

If the prevalence of Covid-19 is 1%, then the PPV will be 31%. This means that 31% of people who test positive on the test will actually have Covid-19. Hence, at times of low prevalence, many positive Covid-19 tests will be wrong.

You can use a Positive Predictive Value Calculator to see how changing sensitivity, specificity and prevalence alters the result.

Screening tests have also become more important as health systems across the world try to detect conditions such as cancer earlier in their clinical course in an attempt to improve health outcomes survival.

Example of a screening test: A mammogram is a screening test for breast cancer. It has a sensitivity of 85%, meaning that 85% of women with breast cancer will have a positive mammogram. The mammogram has a specificity of 90%, meaning that 90% of women without breast cancer will have a negative mammogram. The PPV of the mammogram will vary depending on the prevalence of breast cancer in the population being screened. For example, if the prevalence of breast cancer in a population is 1%, then the PPV of the mammogram will be 8%. This means that 8% of women who have a positive mammogram will actually have breast cancer. Hence, many women who don’t have breast cancer will need investigation to confirm the result of their screening test.

Conclusion: Sensitivity, specificity, and predictive value are important concepts in the evaluation of diagnostic and screening tests. Clinicians, public health specialists and the public should understand the performance of a test before using it in patient care.

In addition to sensitivity, specificity, and predictive value, there are other factors that clinicians should consider when choosing a diagnostic or screening test, such as the cost of the test, the risks and benefits of the test, and the availability of alternative tests.

No diagnostic or screening test is perfect. All tests have the potential to produce false positives and false negatives. Clinicians, the public and policy-makers should use judgment to interpret the results of any test; and to make decisions about patient care, screening programmes and public health policy.

Evaluating the Uptake of the NHS App in England

Our new study published in the British Journal of General Practice examines uptake of the NHS App in England. The NHS App was launched in January 2019 as a “front door” to digitally enabled health services, allowing patients to access their personal health information online. With the advent of the COVID-19 pandemic, the app saw a significant increase in downloads, especially with the introduction of the COVID Pass feature. However, the uptake of the app has revealed some important trends and inequalities that need to be addressed.

The Study

A comprehensive observational study used monthly NHS App user data at general-practice level in England from January 2019 to May 2021. Different statistical models were applied to assess changes in the level and trend of use of various functionalities of the app, particularly before and after the first COVID-19 lockdown.

Key Findings

Between January 2019 and May 2021, the NHS App was downloaded 8,524,882 times and registered 4,449,869 users. Intriguingly, the app experienced a 4-fold increase in downloads after the introduction of the COVID Pass feature, which allows users to prove their COVID-19 vaccination status. However, the data also revealed disparities in app registration based on sociodemographic factors:

  • There were 25% fewer registrations in the most deprived practices.
  • Largest-sized practices had 44% more registrations.
  • Registration rates were 36% higher in practices with the highest proportion of registered White patients.
  • Practices with a larger proportion of 15–34-year-olds saw 23% more registrations.
  • Surprisingly, practices with the highest proportion of people with long-term care needs saw 2% fewer registrations.

What This Means

The findings indicate that while the NHS App has proven to be an useful tool, especially in the times of the Covid-19 pandemic, its usage is not uniform across various sociodemographic groups. This raises questions about accessibility and the digital divide, which could ultimately impact the quality of patient care and health outcomes.

Further Steps

While the app has clearly benefited a significant number of people, it’s crucial to understand the reasons behind these patterns of inequalities. Further research is essential to delve deeper into these trends and how they may affect the patient experience.

Understanding these dynamics can guide improvements to the app, making it more inclusive and effective for all users. Policymakers, developers, and healthcare providers need to work together to ensure that digital health services like the NHS App are accessible and beneficial to everyone, regardless of their socio-economic status or demographic background.

Conclusion

The NHS App has seen a considerable increase in usage since the onset of the Covid-19 pandemic, highlighting its essential role in modern healthcare. However, the unequal patterns in its uptake call for a focused approach to ensure it serves as an inclusive platform for all. Further research is crucial to uncover the underlying reasons for these disparities and to work towards a more equitable healthcare system.

Guidance for NHS staff on writing support letters for patients for applications for PIP or ESA.

Doctors and other NHS professionals in England are often asked to write in support of patients applying for benefits such as Personal Independence Payments (PIP) or Employment Support Allowance (ESA); which support people with disabilities and long-term health conditions.

These benefits are vital for people suffering from long-term health conditions and disabilities, offering them financial help that can significantly improve their wellbeing and quality of life. Given the critical nature of these benefits and the stringent criteria often applied during the assessment process, the letters we write can play an essential role in securing this much-needed support for our patients.

Here is some guidance on how to write a more effective and relevant letter of support based on my long experience as an NHS doctor in writing such letters.

1. Introduce yourself and describe your relationship to the patient, including how long you have known them and in what capacity. This will help establish your credibility as a reliable source of information in support of their application for a personal independence payment or another state benefit.

2. Provide a detailed description of the patient’s medical conditions, including any diagnoses they have received, how their medical conditions affect their daily life, and any symptoms they experience. Focus on the most relevant conditions to their application first. For example, if the patient is applying for PIP due to mobility problems, you should focus on their mobility impairments and how they affect their daily life and ability to work. Also include any medication they are taking and any past medical or surgical interventions.

3. If the patient is applying for Employment & Support Allowance (ESA), explain how their medical condition affects their ability to work. Describe any physical or cognitive limitations they have, or how their symptoms interfere with their ability to perform tasks required for their job. Aim to give precise descriptions of their conditions; for example if they have heart failure, what is the severity?

4. When describing how the patient’s condition impacts their daily life, focus on the activities of daily living that they have difficulty with. For example, you could mention if they have difficulty dressing, bathing, cooking, shopping, cleaning, or managing their finances. Also describe any problems the patients has in managing their health and their medical conditions.

5. Use specific examples to illustrate how the patient’s condition affects their daily life and ability to work. For example, you might describe a time when the patient experienced a symptom flare-up that prevented them from completing a task at home or attending work.

6. Emphasize the patient’s need for financial support through benefits such as PIP or ESA. Explain how this support would help them manage their condition and improve their quality of life. With the cost of living crisis, these benefits are now essential for many people.

7. Remember to keep the letter factual, polite, concise and to the point, and to focus on the patient’s medical conditions (both physical and mental health problems) and how they impact their ability to work and carry out essential daily activities.

Some doctors argue they should not be writing such letters as they detract from the time available from providing core medical services. But obtaining support from a PIP or ESA can improve a patient’s well-being, which ultimately is also beneficial for the NHS and society.

In England, the NHS is funding social prescribers to work with general practices and writing such letters of support is often delegated to these social prescribers who can take over this task from health professionals such as general practitioners and therapists.

Financial problems will have a big impact on people’ health and well-being and it is important that NHS staff do their best to support patients who have difficult financial circumstances because of their health problems.

Understanding and Managing Sport-Related Concussion in Primary Care

The importance of the global emphasis on physical activity for health cannot be understated. However, it is crucial to address one of the adverse effects of contact sports—specifically, sport-related concussions. Sport-Related Concussion is a traumatic brain injury caused by a direct blow to the head, neck, or body resulting in an impulsive force being transmitted to the brain.

Sport-Related Concussion can present with a wide range of signs and symptoms, and can affect a person’s thinking, concentration, memory, mood, and behaviour. These incidents are common and account for a significant number of emergency department visits. They also have some long-term risks, including cognitive and neurological problems.

Recent publications, like the consensus statement from the Concussion In Sport Group and the UK Government’s landmark concussion guidance, offer valuable insights in the management of Sport-Related Concussion. This blog – based on our recent article in the British Journal of General Practice – aims to provide guidance on recognising, diagnosing, and managing Sport-Related Concussion within the context of primary care.

 The Changing Landscape of Sport-Related Concussion

In 2016, over 1% of emergency department visits in England and Wales were attributed to concussions. Up to 60% of these involved children and adolescents. A 2021 UK House of Commons report criticised the current awareness level about Sport-Related Concussion in the UK’s NHS, indicating a need for better recording and treatment procedures.

 Recognising Sport-Related Concussion

Symptoms of Sport-Related Concussion can range from cognitive issues to mood changes. Anyone with a suspected concussion should be immediately removed from the field of play and assessed by an appropriate healthcare professional within 24 hours of the injury. Those working in sport will be aware of specialist assessment tools pertaining to individual sports that aid clinicians when diagnosing concussion. The UK Government guidance provides a list of ‘red flags’ that require immediate assessment.

Once Sport-Related Concussion has been recognised or diagnosed, a short period (24–48 hours) of relative rest is advised, where only light-intensity physical activity that does not, or only minimally, exacerbates symptoms is undertaken. Subsequently, a logical graduated return to school/work and then sport can be started, where progression through stages is dependent on minimal and transient (the CSIG advise <1 hour) exacerbation of symptoms.

Sport-specific assessment tools exist for diagnosing concussion, such as the Sport Concussion Assessment Tool (SCAT6). These tools are most effective within 72 hours of the injury and evaluate symptoms, cognitive function, and coordination.

 Managing Sport-Related Concussion in Primary Care

Primary care doctors play an essential role in managing Sport-Related Concussion. Initial management includes:

– Advising a short period of relative rest (24-48 hours)

– Reducing screen time and cognitive load

– No alcohol, solitary time, or driving within the first 24 hours

Patients with persistent symptoms beyond 28 days should be referred for a more comprehensive assessment. Gradual return to normal activities is advised, strictly adhering to symptom-dependent progress.

Challenges and Future Directions

The NHS’s limited specialist services for treating complex or prolonged sport-related concussion symptoms create a care gap. This could be bridged by experts in sports medicine or primary care doctors with extended roles in sports medicine. Emerging technologies like Inertial Measurement Units (IMUs) in mouthguards and salivary micro-RNA samples show promise for better recognition and understanding of sport-related concussion.

Conclusions

Sport-Related Concussion is important. Effective recognition and management by general practitioners can significantly contribute to an individual’s immediate and long-term health. It is also vital for local commissioners to implement appropriate care pathways for managing this condition. By acknowledging the complexities in management and investing in ongoing research, we can create a healthcare system that supports both the benefits of physical activity and the challenges it can sometimes bring.