Streamlining Healthcare: How Technology can Further Enhance the NHS

Credit: Ben Hope on Unsplash.com

“I am scared about my daughter’s future thinking about what you guys might do to the NHS and what that means in exact terms for the length of her life”. Those were the words uttered by a mother to the UK Minister of Health who paid a visit to a London hospital in December 2022. She was raising her concerns that enough was not being done by the government to tackle the current crisis in the National Health Service (NHS).

The NHS is the publicly funded healthcare system in the United Kingdom. It is widely considered to be one of the country’s most valued and cherished institutions, providing free healthcare to all UK residents. The NHS is not only central to the UK economy, but also to the well-being and livelihood of the British population.

One of the main reasons the NHS is so central to the UK economy is that it is one of the country’s largest employers. With over 1.7 million staff members, the NHS is one of the largest employers in the world and makes a significant contribution to the UK’s economy through the employment and wages of its staff. Additionally, the NHS also makes a significant contribution to the UK economy through the goods and services it purchases, such as medical equipment and drugs.

In recent years, the NHS has faced several challenges that have affected its ability to provide high-quality care to patients. One of the biggest challenges has been the increasing demand for healthcare services due to an aging population and an increase in chronic diseases. This has placed a strain on the NHS, with hospitals and GP practices often oversubscribed and struggling to meet the needs of patients.

Another major challenge the NHS has faced in recent years is the ongoing funding crisis. Despite being one of the largest employers in the country, the NHS has been facing budget constraints for many years, and this has led to a lack of funding for necessary resources and staff.

Brexit also brought new challenges for the NHS, as it relies heavily on the movement of healthcare professionals and goods across the EU. The uncertainty of the UK’s withdrawal from the EU has created challenges with regard to staffing and medicines, potentially affecting patient care.

Digital health technologies, such as telemedicine, remote monitoring, and patient portals, are increasingly being deployed to improve the delivery of healthcare and the patient experience. However, there are still challenges to be addressed in terms of data security and interoperability, as well as the need to ensure that these technologies are accessible to all. Additionally, there is a need to ensure that these technologies are not only effective but also cost-effective.

Here are some of the key areas where improvements can be made by leveraging technology to improve the efficiency of the NHS.

Population Health Management

Population health management (PHM) is a strategy that utilizes technology and data analytics to enhance the overall well-being of a population. This approach involves gathering information about the population’s demographics, medical background, and other relevant factors, to uncover trends and patterns in health.

By identifying areas that require attention, population health management can help to implement targeted interventions, such as health screenings, preventative care, or increased access to healthcare services. Ongoing monitoring and assessment of these interventions allow for necessary adjustments to be made and to evaluate their success. Furthermore, population health management can help in identifying potential risks and working towards improving health outcomes.

Population health is one of the core strategic aims of the NHS’ integrated care systems (ICSs) which is to improve physical and mental health outcomes, promote wellbeing and reduce health inequalities across the entire population, with a specific focus on the wider determinants of health (things like housing, employment, education).

In 2018, the NHS Long-Term Plan outlined the expectation that Integrated Care Systems (ICSs) would bring together NHS, local authorities, and community groups to deliver population health approaches. The Health and Care Act 2022 further establishes ICSs as statutory bodies with the responsibility to improve population health and imposes new obligations on the NHS to address health disparities.

In Surrey, a PHM approach was used to identify and better coordinate care for nearly 3,000 patients aged 65 or older who were on multiple elective waiting or follow-up lists. These patients had complex health and care needs, and the estimated cost of their care was £19 million per year.

The local NHS Trust established an integrated care hub to offer a wide range of services, including virtual consultations with multiple specialists and social prescribers, special interest GPs, and geriatricians, reducing the need for multiple hospital visits, improving patient experience, and reducing the risk of infections and workload for the NHS. They also used technology to help patients recognize when their condition is worsening and follow-up promptly.

While in East Milton Keynes, PHM analysis identified poor diabetes management and increased risk of cardiovascular disease among South Asian communities and individuals in unskilled jobs or unemployment.

To address this, the primary care network implemented an initiative led by a Wellbeing Team, which provided advice on diet, nutrition, and exercise, including cultural cooking classes, free gym memberships, and access to community facilities such as local allotments. Patients were also encouraged to track their weight and diet by inputting information directly into their medical records using a health app.

These examples demonstrate the benefits of PHM for the NHS which include improved access to care, better integration of services, improved patient outcomes, reduced costs, and increased efficiency. By identifying health trends and patterns in the population, it is possible to target areas where health interventions may be needed, monitor the progress of interventions, and improve health outcomes.

Additionally, population health management can be used to identify risk factors and develop targeted interventions to improve the health of specific groups. Finally, population health management can help to reduce costs, as it can help to reduce the amount of time and resources needed to provide care.

Despite its huge benefits, there are however challenges with the widespread adoption of this approach including those around the quality of the data being collected and those around privacy and security. There are also issues around accessibility as not all individuals have equal access to technology or the Internet, this could mean that some populations might not be reached by population health management strategies and interventions.

According to The King’s Fund, a 125-year health advocacy dedicated to improving health and care in England, effective population health management requires strong leadership at the local level, as much of the shaping, prioritization, and delivery of population health goals takes place within regional and local systems.

Different local structures, such as Integrated Care Systems (ICSs), local authorities, community groups, and political leaders, such as elected mayors, all have important roles to play. The delivery of an effective population health approach will require sustained, systematic, and coherent efforts over several years. While new structures within the health and care system can provide a foundation for this, change will primarily be driven by local and regional teams.

Elderly Care

The UK’s population is aging, with the number of people aged 65 and over projected to rise from 14.9 million in 2014 to 19.8 million in 2039. This increase is caused by factors such as longer life expectancy, lower birth rates, and increased immigration of older people.

This poses a challenge to the UK’s economy and labour force as the number of working-age people decreases and the number of people needing support increases. This aging population is putting a strain on the UK’s health and social care systems as the need for medical care and social services increases.

The NHS offers a variety of elderly care services, including in-home care, nursing homes, and assisted living facilities. In-home care can include help with daily tasks such as personal care, mobility, and meal preparation.

Nursing homes offer round-the-clock nursing care and help with daily activities. Assisted living facilities offer a more independent lifestyle with assistance available as required. The NHS also offers social activities for the elderly, such as day trips and leisure activities, to help them stay connected to their community.

According to Age UK, one of the leading charities dedicated to the elderly, some of the top problems people and their family carers face include:

• Lack of continuity and rushed visits: Many complain about rushed home care visits from professional carers and a lack of continuity, preventing them from building a relationship and proper communication leading to poor person-centered care and sometimes not getting care at all. The system was generally blamed for this rather than the carers themselves.
• Poor quality of care: Many people complain about the poor quality of care received by themselves or their family members, some even resorting to reminders for basic needs, and feeling that with more money, a better care standard could have been acquired.
• High cost of social care: The high cost of social care is causing financial strain for older people and their families, with some being surprised by the high prices, and even when entitled to free care, it was often of poor quality and required additional payment. Those not eligible for support felt they had no other options.
• Family carers feeling unsupported: Family caregivers have expressed a desire to provide the best care for their loved ones but emphasized the need for support from the council or NHS. Caregivers of those with dementia felt unsupported, lacking basic help and specialist dementia support.
• Confusion and difficulties navigating the social care system: Many people had difficulty understanding how to access care, and confusion about what types of care are available, who provides it, and how it is financed. Many mistakenly believed that care would be provided for free by the NHS.

Technology, specifically telehealth and remote monitoring, can be used to improve elderly care by enabling remote communication and check-ins with healthcare providers, sharing patient information for continuity of care, and early detection of potential health issues.

Telehealth can be used to connect patients with healthcare providers remotely, using video conferencing or phone calls, reducing the need for in-person visits. Remote monitoring technology can be used to track patient outcomes, such as vital signs, medication adherence, and mobility, and can also be used to monitor the effectiveness of treatment plans and adjust them as needed.

Artificial intelligence (AI) can be then used to analyze patient data and identify patterns for additional care or support. One example of this is using AI to analyze electronic health records (EHRs) of elderly patients to identify those at risk of falling.

The AI system can analyze data such as the patient’s age, medical history, and current medications to identify patterns and predict the risk of falling. The system can then alert healthcare providers to this risk, allowing them to take preventative measures such as adjusting medication regimens, conducting balance assessments, or providing fall-prevention education to the patient.

Additionally, remote monitoring devices such as wearable sensors can be used to track the patient’s activity levels and alert healthcare providers to any changes that may indicate a fall risk. By combining the data from these devices with the patient’s EHR, the AI system can provide a more comprehensive picture of the patient’s health, allowing healthcare providers to make more informed decisions about their care.

A caregiver portal can be used to provide patients and their carers with easy access to information about available care services, including cost and eligibility requirements. It can also provide resources such as educational materials and support groups for carers. The portal can also be used to facilitate communication between patients, carers, and healthcare providers, allowing for more efficient coordination of care.

An AI-powered chatbot or virtual assistant can assist patients and carers in navigating the healthcare system by answering questions and providing information about care services, such as how to access them and what to expect. For example, a chatbot could help an elderly patient understand the process of scheduling a telehealth appointment or provide a carer with information on how to access respite care services.

Furthermore, an AI-powered chatbot can also help patients and carers with symptom management, providing personalized recommendations and guidance on self-care.

Both the caregiver portal and AI-powered chatbots can be integrated with telehealth and remote monitoring technologies, allowing for more efficient and coordinated care. For example, the portal can be used to schedule telehealth appointments, and the chatbot can provide real-time support during remote monitoring sessions.

They could also provide easy access to information about local support groups, such as those for caregivers, people with specific health conditions, or those who are socially isolated. The portal or chatbot can also provide information about how to access these groups, and can also provide information about other community resources, such as libraries and leisure centers, that can help older people to stay engaged and active.

The data collected via the solution can be used to inform and improve social care services. For example, the caregiver portal or AI-powered chatbot can be used to connect patients and their caregivers with community resources and support services.

Moreover, the data collected from remote monitoring devices can be used to identify patterns and trends in patient health, which can inform the development of social care programs and interventions. For example, if data shows that a high number of patients in a certain area have mobility issues, a social care program could be developed to provide more accessible transportation options.

Overall, the combined solution can provide elderly patients and their carers with more convenient, efficient, and personalized care, improve communication and coordination among healthcare providers, and support patients and carers to navigate the healthcare system more effectively.

Just as importantly, this approach helps in improving efficiency while driving down costs for both the patients in terms of reduction of inpatient costly visits, as well as the providers themselves by being more proactive in negating the need to provide care for cases that could easily have been prevented.

There are several potential drawbacks which include:

• Accessibility: Not all older adults have access to or are comfortable with technology, which can limit their ability to take advantage of telehealth and remote monitoring services.
• Cost: Implementing and maintaining telehealth and remote monitoring technology can be expensive, which may be a challenge for some healthcare organizations.
• Training: Healthcare providers and older adults may need training in how to use the technology, which can be time-consuming and costly.
• Privacy and security: Protecting patient data and ensuring privacy and security is crucial, but with telehealth and remote monitoring, there is a higher risk of data breaches.
• Limited access to technology: Not all individuals have equal access to technology or the internet, this could mean that some populations might not be reached by telehealth and remote monitoring technology.
• Limited engagement and buy-in: Telehealth and remote monitoring require the participation of patients, providers, and community partners. Without engagement and buy-in, it may be difficult to implement and sustain these programs.

Early Intervention

Early identification and intervention can improve patient outcomes by allowing for prompt treatment and management of conditions before they become more severe. This can also reduce costs for the NHS by preventing the need for more extensive and expensive interventions later on. For example, early identification and management of chronic conditions such as diabetes and heart disease can reduce the risk of complications and hospitalizations, ultimately lowering healthcare costs.

Furthermore, early intervention for mental health conditions can prevent the development of more serious conditions and reduce the need for more intensive treatments. Overall, early identification and intervention can improve patient outcomes while also reducing costs for the NHS.

Predictive modeling and AI-powered diagnostic tools can be used alongside data collected from population health management systems and telehealth solutions to improve early intervention in the NHS in three main ways:

Risk stratification: Predictive modeling can be used to analyze data from population health management systems and telehealth solutions to identify individuals at high risk of developing chronic conditions or experiencing complications. This can enable targeted interventions to prevent or delay the onset of these conditions.

It can also be used to identify patients at high risk of hospitalization or readmission based on their demographic, clinical, and claims data. This information can then be used to target interventions to those patients through population health management platforms, such as care coordination and case management, to prevent complications and reduce costs.

Predictive diagnosis: AI-powered diagnostic tools can be used to analyze data from telehealth solutions such as remote monitoring devices and mobile apps to identify early signs of conditions such as heart disease or diabetes. This can allow for earlier intervention and management of these conditions.

AI-powered diagnostic tools can also be integrated with EMR systems to analyze patients’ medical history and alert healthcare providers to potential health issues, such as deterioration of chronic conditions, allowing for earlier intervention and treatment.

For example, image analysis of medical images, such as X-rays and CT scans, using machine learning algorithms can aid in the early diagnosis of conditions such as lung cancer and heart disease.

Personalized care: By integrating data from population health management systems, telehealth solutions, and AI-powered diagnostic tools, healthcare providers can gain a more comprehensive understanding of an individual’s health status and risk factors, allowing for personalized care plans that are tailored to their specific needs.

Overall, by leveraging the data and capabilities of predictive modeling, AI-powered diagnostic tools, population health management systems, and telehealth solutions, the NHS can improve early intervention and ultimately improve patient outcomes. There are also potential drawbacks to consider:

• Bias: Predictive models and AI-powered diagnostic tools can perpetuate bias if they are trained on data that is not representative of the population they are meant to serve. This can lead to inaccurate predictions and inappropriate interventions for certain groups of patients.
• Data quality: Predictive models and AI-powered diagnostic tools rely on high-quality data to function effectively. If the data used to train these models is incomplete, inaccurate, or not properly validated, it can lead to inaccurate predictions and poor performance of the models.
• Privacy concerns: Predictive modeling and AI-powered diagnostic tools rely on large amounts of patient data to function. This can raise concerns about patient privacy, and it’s important to ensure that patient data is protected and used in compliance with relevant regulations.
• Limited human oversight: Predictive models and AI-powered diagnostic tools can automate certain aspects of care, but they are not a substitute for human expertise and judgement. It’s important to ensure that healthcare providers are involved in the decision-making process and that the results of these models are interpreted in the context of a patient’s overall clinical presentation.
• Lack of understanding: Predictive models and AI-powered diagnostic tools can be complex and difficult to understand, which can make it difficult for healthcare providers to explain the results to patients and gain their trust.

It’s important to consider these potential drawbacks when implementing predictive modeling and AI-powered diagnostic tools in the NHS and take steps to mitigate them, such as regularly monitoring and evaluating the performance of the models, ensuring data quality and security, and involving healthcare providers in the decision-making process.