Personalized Healthcare: What It Is and Why It Matters

Traditional healthcare models often rely on standardized treatment plans. This can mean key differences in patients' genetics, lifestyles, and environments are overlooked — potentially resulting in less-effective care. That can be frustrating for both patients and providers.

Personalized healthcare addresses this with technology that helps providers provide targeted, patient-centric care.

For example, a treatment plan for a newly diagnosed type 2 diabetes patient might involve a collaborative shared decision-making process between the patient and healthcare team, considering individual medical factors like comorbidities, genetic predispositions, and lifestyle. This process might include steps such as: 

• Assessing the patient’s specific needs, preferences, psychological factors, and social circumstances
• Using biomarkers and genetic insights to select appropriate therapies
• Tailoring lifestyle interventions such as diet and exercise 
• Continuously monitoring progress to adjust the treatment plan as needed 

With personalization as part of the clinical workflow, providers can improve outcomes, boost patient engagement, and drive operational efficiency.

Personalized healthcare is a proactive, individualized approach to patient care that moves beyond a one-size-fits-all model to tailor treatment and preventive strategies to each patient's unique needs, circumstances, and preferences. It includes these key aspects:

Personalized healthcare uses comprehensive patient data, including medical history, genetics, lifestyle, environmental factors, and even social factors, to gain a holistic understanding of the person's health profile and potential risks. This data-informed approach allows for more precise disease prediction, earlier detection, and optimized treatment strategies.

The core principle of personalized healthcare is recognizing and addressing the distinct characteristics of each patient, ensuring that care plans, interventions, and communication strategies are specifically designed to meet their personal requirements and preferences. This approach enhances treatment effectiveness and patient satisfaction.

It actively involves patients in their own health journey, fostering a collaborative partnership between patients and providers. This engagement empowers patients to make informed decisions, follow treatment plans, and actively participate in managing their wellness, ultimately leading to improved health outcomes and better quality of life.

The four core pillars of personalized healthcare are deeply connected, working together to create a more effective and patient-centric healthcare journey. They are:

• Personalized: Tailors medical treatment and health plans to an individual's unique characteristics, such as their dietary choices, physical activity, social circumstances, and medical history. Personalized care can involve developing specific dietary or exercise recommendations based on a patient's individual risk factors for diseases like diabetes or heart disease.
• Predictive: Uses data analytics and AI to forecast health risks and disease progression, allowing for early intervention and proactive management. Predictive analytics help doctors choose treatments likely to succeed. For example, AI can improve diagnostic accuracy by using machine learning algorithms, particularly deep learning, to analyze millions of medical images. The AI can identify patterns that humans might miss, which helps with earlier detection of diseases and enables more preventive care. 
• Preventive: Focuses on preventing diseases and health problems before they occur or worsen, through screenings, immunizations, and lifestyle interventions. Preventive care may include guidance on smoking cessation, weight management, and healthy eating to reduce risk factors for various chronic conditions.
• Participatory: Actively involves patients in their own healthcare decisions and management, empowering them to take a central role in their health journey. Participatory care may use online portals or mobile apps for patients to access their health records, track their progress, and communicate with their care team.
  

Personalized healthcare services can improve the patient experience from chronic care management to post-acute engagement. It provides a wide range of benefits for both patients and providers.

Personalized healthcare uses information like family history, genetics, and lifestyle factors to identify people at higher risk for certain conditions. This allows for earlier screenings and interventions, leading to better clinical outcomes.

Targeted therapies and personalized prevention strategies increase treatment effectiveness, reduce adverse effects, and improve disease management. This can lead to better recovery rates, longer remission periods, and overall enhancement of patients' lives. For example, a patient with congestive heart failure might be given a personalized discharge plan outlining medication schedules, dietary guidelines, and activity recommendations. This helps the patient experience a smoother transition from the hospital to home — they feel supported and less overwhelmed by the complexities of their care. Regular follow-up calls and telehealth visits can help identify and address potential complications early, reducing the risk of hospital readmissions and promoting a smoother recovery.

Early detection and effective management of chronic conditions through personalized healthcare solutions minimize the need for expensive and invasive interventions later on. This includes reducing hospitalizations and emergency room visits and making sure patients receive the appropriate tests.

Personalized approaches foster a deeper understanding and acceptance of treatment plans by actively involving patients in their care decisions. This empowers patients to take an active role in their health management — they're more likely to follow treatment protocols and make healthier lifestyle choices.

Concierge medicine, a model often associated with personalized care, promotes deeper relationships by allowing doctors more time to understand patients' needs and build rapport. This translates to increased trust, better communication, and higher patient satisfaction.

Clinical decision-making can be improved by creating customized treatment plans based on a patient's unique genetic factors, medical history, and lifestyle preferences. Advanced tools like EHRs and AI can process vast amounts of patient data to identify patterns and suggest customized treatment alternatives, supporting the decision-making process. By focusing on an individual's specific profile, providers can move away from broad, one-size-fits-all approaches toward targeted, evidence-based interventions that are more likely to be effective. 

Personalized care can streamline processes, ensure appropriate scheduling, and improve communication, potentially reducing workload and stress for healthcare staff.

Personalization in healthcare is essential as disease management becomes more complex. Multiple factors, including biological processes, lifestyle, and socioeconomic conditions, contribute to the increased potential for the co-occurrence of multiple diseases in one individual. These factors are often interconnected and can lead to a cycle of worsening health.

Here are some top areas where personalization is critical to solving healthcare problems:

• Chronic conditions: Personalized healthcare can enable providers to identify health risks earlier, allowing for interventions before a disease progresses. For instance, access to genetic and molecular information can help doctors predict which treatments will be most effective for a specific patient, shifting focus from trial-and-error to proactive, evidence-based care. Care teams can develop personalized strategies that focus on preventing or delaying the development and progression of chronic conditions by addressing individual risk factors.
• Aging populations: Older adults often have complex health needs and multiple chronic conditions. Personalized care, especially in settings like home healthcare, addresses these unique needs, promoting independence, comfort, and improved quality of life in a familiar environment.
• Rising costs: Personalized care, by focusing on preventive measures and early detection, can reduce the need for expensive and invasive interventions, minimizing hospitalizations and ultimately lowering healthcare costs for individuals and the system.
• Patient expectations: Modern patients expect to be actively involved in their care decisions. Personalizing the patient experience fosters this engagement, leading to increased patient satisfaction, adherence to treatment plans, and a sense of empowerment over their health journey.

Without personalized treatments, patients may get ineffective or suboptimal care, leading to adverse reactions, lingering illnesses, or reduced quality of life. For providers, the lack of personalization can mean inefficient resource allocation, high readmission rates, and a greater burden on the healthcare system.

Using technology to help providers more easily deliver personalized care can revolutionize the approach to and logistics of providing patients with care.

By centralizing patient data from various sources (electronic health records, wearables, lab results), unified records offer a holistic view of a patient's health, allowing providers to make informed decisions based on a complete medical history. Integration facilitates seamless data flow, reducing information silos and enabling coordinated care across different settings and specialists.

AI and machine learning tools analyze this vast data to identify patterns, predict disease progression, and forecast patient outcomes, supporting clinicians in making precise diagnoses and optimizing treatment plans. Advanced analytics enable predictive modeling for preventive care, identifying at-risk patients for early interventions.

Raw data consists of unprocessed facts and figures (e.g., blood pressure readings, lab values). Actionable insights, however, are derived from raw data through analysis and interpretation, providing meaningful, valuable information that can directly inform decision-making and lead to specific actions for improvement. For instance, a series of blood pressure readings is raw data, but an analysis showing a consistent pattern of high readings linked to specific lifestyle factors becomes an actionable insight prompting a dietary or medication adjustment.

Ultimately, technology should be designed to streamline workflows and reduce administrative burdens, freeing up providers to focus on patient care. Presenting data in a clear, accessible, and actionable format, such as through dashboards or alerts, helps providers quickly grasp key information without being overwhelmed by excessive raw data.

Delivering outstanding patient care means more than just managing your patients' information and healthcare events. It's about creating a strong, collaborative relationship with patients and caregivers to help your patients along on their journey to better health.

Providers can use AI tools like Agentforce to create a patient summary, including medications, diagnoses, social determinants, assessments, clinical service requests, and care gaps. Solutions such as Health Cloud benefit patients and providers by providing a consolidated view of critical patient records, access to a patient's care team, and the tools to bring it all together to improve healthcare outcomes.