Top 10 current trends expected to transform healthcare in 2024

Top 10 current trends expected to transform healthcare in 2024 Rachel Marley

Quick Takes

• As groundbreaking technologies reshape health systems, healthcare leaders must strategize on integrating these innovations within their organizations
• Technologies expected to see strong growth in 2024 include generative artificial intelligence and mass spectrometry applications within clinical laboratories
• Strategic investments in solutions targeting women’s health, data monetization, and population health can serve as key differentiators for leaders in the competitive landscape

Recent advancements in technology are promising automated and cost-effective healthcare solutions that could reshape the ways in which research, diagnostics, and treatment pathways are determined and delivered.

We have compiled a list of 10 pivotal trends anticipated to play a crucial role in the healthcare sector in 2024. Find out what we think healthcare leaders should be focusing on as they seek to remain at the forefront of innovation in terms of services provided and healthcare delivered.

1. Moving care into homes

The COVID-19 pandemic changed the way health systems provided care to patients. Today, patients are increasingly open to receiving medical care in their homes rather than in the clinic. From online pharmacies to telehealth to wearable devices, it is becoming ever easier for patients to access diagnostics and therapies outside the traditional medical office and hospital setting.

Advanced technologies and mobile apps are revolutionizing the industry with services that remotely monitor symptoms, like heart rate, temperature, or blood glucose levels. This tech can also connect patients quickly and directly to specialized providers that can help with a variety of needs, including mental health support.

Studies show that shifting care into homes can potentially reduce staff burden, decrease savings, and simultaneously improve clinical outcomes.^1,2

By 2030, current trends predict the home healthcare market is expected to grow to almost US$ 670 billion, compared with the current estimate of US$ 362.1 billion in 2022.³ Healthcare leaders need to evaluate home care’s impact on their organizations.

2. Integrating generative artificial intelligence (AI) and large language models (LLMs) in healthcare

LLMs are a type of AI that leverage large data sets to understand, summarize, and generate new content, typically in conversational form. One such example is ChatGPT, which was launched in 2022 and is being evaluated for applicability in healthcare. While AI has become an integral part of medicine, especially for diagnostics, stakeholders can leverage simplified machine learning tools without the need for specialists. This could impact the care patients receive. 

For example, LLMs could help manage diseases and provide daily recommendations for heart disease or diabetes.⁴ Additionally, other areas where LLMs can be used include:⁵

• Patient education
• Patient triage
• Reimbursement claims
• Appointment scheduling
• Care recommendations
• Medical translation

Since LLMs are just starting to gain ground in medicine, it is crucial that healthcare leaders critically evaluate how to safely and effectively incorporate this technology into their organizations. Priority areas should be patient safety, ensuring data privacy, and generating accurate information.

3. Streamlining clinical trials

Tapping into digital technologies and adapting them to streamline clinical trials could transform the research of new medicines this year. 

Conventionally, patients often need to travel a significant distance to participate in a trial. The pharmaceutical industry is therefore shifting towards decentralized clinical trials to enhance clinical research. Offering participation options for subjects at local facilities or remotely can improve accessibility to groundbreaking science. 

Technologies that streamline clinical trials include LLMs, which could help with screening subjects, patient engagement, and study design, or wearable technologies that can continuously monitor symptoms and capture a broad range of real-world data.

4. Identifying digital biomarkers to improve diagnostics

Digital biomarkers are digital signatures correlated to specific conditions.⁶ They are becoming more widely recognized as potentially enabling more accurate and reliable disease diagnosis. 

Stakeholders are developing digital biomarkers by using machine learning and AI with novel algorithms trained on data from wearable devices or medical imaging to identify patterns that may indicate disease. This expansion of digital biomarkers and its rapid adoption is evident in healthcare, with current trends estimating that the global digital biomarkers market is expected to increase with a compound annual growth rate (CAGR) of 22.3% in the next decade.⁷

In rare diseases specifically, digital biomarkers have a notable opportunity to pioneer how we treat conditions only found in a handful of patients. Since differential diagnosis is difficult and access to specialists can be limited, using digital biomarkers could strengthen and improve the care patients receive. 

5. Supporting the smart lab for faster and more accurate clinical tests

Clinical labs deliver vital diagnostic and screening services to healthcare providers and patients. Approximately 70% of diagnoses are achieved with the help of lab tests.⁸ However, over the last several years, health systems have struggled to keep up with the demand due to staff shortages, and decreased access to funding, resources, real estate, and automated equipment.^9-11 

Lab managers can address these challenges by streamlining processes through greater automation and wider use of digital technologies. Some examples that lab leaders are already utilizing include improved workspace design, quality management systems to ensure better utilization of resources, robotics and automated systems, and cloud-based technologies.^12-14

This year, we believe that more labs will consider how to scale their clinical lab procedures, especially as the workforce in the space continues to see a steady decline, to improve turnaround times, decrease costs, and expand access.

6. Increasing adoption of mass spec in the clinical lab

Within clinical labs, lab personnel traditionally employ immunoassays to help diagnose disease and pinpoint the presence or absence of compounds, such as peptides and proteins. However, challenges with immunoassays like cross-reactivity issues or a lack of available reagents have led to the need for better solutions. For decades, researchers worldwide, especially in academia, have utilized mass spectrometry (mass spec) as a basic research tool. Over the last 10 years, mass spec has become a popular technique in the clinical lab setting for routine diagnostic testing and drug monitoring.¹⁵

Mass spec, an analytical technique that measures molecules’ mass-to-charge ratio (m/z) within samples, is increasingly accessible in the clinical space due to increased molecular detection sensitivity and specificity.¹⁵ From better screening of protein pathogens to improved therapeutic drug monitoring, mass spec can reshape healthcare.

Improving automated workflows and standardizing protocols to accelerate turnaround times with higher throughput will allow results to be scaled accurately and reliably. This will enable healthcare providers to leverage the results from mass spec and customize treatment strategies.

To learn more about mass spec and how it is transforming clinical labs, visit our article Revolutionizing the clinical lab with mass spectrometry on LabLeaders.

7. Using clinical decision support systems for value-based healthcare

Physicians now have more novel computational technologies, known as clinical decision support systems (CDSS), available to help manage the vast amounts of patient data, thus improving their critical decision-making and increasing value-based healthcare. These tools tap into AI and can dramatically impact patient engagement and their experience with healthcare organizations. Types of CDSS include:^{16, 17}

• Medication and drug interaction alerts
• Best practice notifications
• Health maintenance reminders
• Differential diagnosis

Machine learning and AI are critical components of CDSS and promise to help sift through and integrate different healthcare data available throughout a patient’s journey, from physician visits to information from wearable devices and participation in clinical trials.  

8. Elevating population health management

With the evident challenges seen during the COVID-19 pandemic, healthcare leaders must remain steadfast in boosting population health. Today, results from physician visits and lab tests, genomic data, and information from wearable devices all play an essential role in how stakeholders respond to public health crises. By having widely available data collected with population health in mind, leaders can pinpoint areas that need the most attention and devise plans to anticipate problems before they occur. 

Health systems are now building collaborations with companies that can monitor infectious diseases or identify patients with cancer or cardiovascular issues on a large scale. Identifying health risks among populations and intervening and taking preventative approaches will be a crucial part of boosting responses to acute epidemics and chronic disease management.

Benefits of population health include:^18-19

• Better clinical results
• Advancing patient engagement and advocation of their care
• Efficient spending
• Improvement in patient triage
• Reduction in hospital admissions
• Decrease in readmission and hospital stays

9. Investing in women’s health

The industry needs to be inclusive of all populations, especially women who have been underserved in many aspects of healthcare, including the funding of conditions that mainly affect women, representation in clinical trials, and higher rates of misdiagnosis in the clinical setting. 

Investments in the women’s healthcare ecosystem have skyrocketed in the past few years, with current trends predicting the market to grow to almost US$ 18 billion by next year.²⁰ Healthcare leaders can participate in this growing market by increasing awareness, education, and accessibility to preventive services. 

To learn more about how we should be investing more into understanding women’s health, visit our article Cutting corners on women’s healthcare is proving costly.

10. Leveraging data monetization in healthcare

With electronic health records available to patients in most healthcare organizations, the data available for monetization is increasing exponentially.²¹ In brief, data monetization is data that can be used to obtain quantifiable economic benefits, typically done by providing data access to third parties. For example, this approach allows health systems to negotiate benefit terms from health insurers or share data with pharmaceutical companies for better insights into personalized medicines or diagnostics.²¹

Beyond data collected in clinics, remote digital technologies, like wearable devices and mobile applications, enable rapid data creation.¹ The wealth of information available can offer valuable insights across various domains, including strategies for growing revenues in health systems and the development of health products and services to enhance patient outcomes. However, it is essential to note that when implementing data monetization, leaders consider data security, privacy, and accessibility when determining the best strategy.

As for current trends, the global healthcare data monetization market is expected to grow by over 18% in the next five years, so healthcare leaders need to evaluate how this approach can benefit their respective companies and, most importantly, patients.²²

A new era in healthcare

The healthcare landscape is transforming profoundly and swiftly, marked by various emerging trends. From mass spec and digital biomarkers to population health and data monetization, these trends encompass innovative methodologies geared toward delivering results to patients with heightened efficiency and reliability. 

The urgency to adapt and respond to these trends is evident as they collectively redefine the landscape of healthcare delivery. As the industry navigates through this rapidly changing landscape, it becomes increasingly vital for stakeholders to remain current with these changes. By doing so, they can ensure optimal patient outcomes and the overall advancement of healthcare practices within their organizations.

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