A Provider Centric (traditional) Patient Care
Patient care refers to the services and support provided by healthcare professionals to patients to help them manage their health and well-being. It involves a wide range of activities, including diagnosis, treatment, rehabilitation, and emotional support. The goal is to provide the best possible care to help patients manage their health and improve their quality of life.

Earlier, patient care was more “provider-centric”, with healthcare providers making decisions about patients’ care without necessarily involving them in the decision-making process. The primary focus was always on treating illness and disease rather than on preventive care and wellness.

A good example of provider-centric healthcare would be a situation where a healthcare provider makes decisions about a patient’s care without considering their preferences, needs, or values. For instance, a patient with a chronic condition may be prescribed medication without being fully informed about the potential side effects or alternative treatment options. The provider may not take into account the patient’s lifestyle, cultural background, or socioeconomic status, leading to a lack of personalized care.
Another example of provider-centric healthcare is a situation where a provider does not communicate effectively with their patient. For instance, a provider may use medical jargon that the patient does not understand, leading to confusion and potentially compromising the patient’s care. Alternatively, a provider may not take the time to listen to the patient’s concerns, leading to a lack of trust and potentially compromising the patient’s satisfaction with their care.

In both of these examples, the focus is on the provider making decisions about the patient’s care without involving the patient in the decision-making process or prioritizing their needs and preferences.

The Pandemic: A Defining Inflection Point
The COVID-19 pandemic was a watershed moment that forced the healthcare industry to confront critical challenges head-on. It became an inflection point that sparked significant changes, bringing to light the urgent need for healthcare systems to be more agile, adaptable, and patient-centered.

The staggering death toll of the COVID-19 pandemic has upended the healthcare industry, triggering a seismic shift in how patients and healthcare providers approach healthcare. The crisis has resulted in a surge in demand for patient consumerism, with patients demanding greater control over their healthcare decisions and more personalized care.

Provider Centric to Patient Centric, The introduction of healthcare consumerism
COVID-19 pandemic has been a major catalyst for the shift towards patient-centric healthcare from past provider-centric and has undoubtedly introduced healthcare consumerism.

Consumerism is an economic and social ideology that emphasizes the consumption of goods and services, often at a rapid pace and with a focus on personal fulfilment and satisfaction. In the context of healthcare, consumerism refers to a shift in which patients are taking a more active role in managing their own health and healthcare decisions. This includes seeking out information, choosing providers and treatments based on quality and cost, and advocating for their own needs and preferences. The goal of healthcare consumerism is to empower patients and improve the overall quality and value of healthcare.

Healthcare consumerism has demanded a more patient-centered approach to healthcare, which includes the concept of a patient’s longitudinal data. This means that patients want to have access to their complete health history, including previous diagnoses, treatments, and test results. With the help of electronic health records (EHRs) and other digital tools, patients can now easily access their health data and share it with their healthcare providers.

Data-driven healthcare modernization for patient centric personalized care
Today in healthcare, with a demand for Healthcare consumerism, A quantification spree of every human healthcare parameter or factor has started and has led to an overwhelming amount of data. From electronic health records (EHRs), medical imaging (e.g., X-rays, MRIs), wearable devices (e.g., fitness trackers, smartwatches), Internet of Medical Things (IoMT) devices (e.g., remote patient monitoring devices, smart sensors), genomic data (e.g., DNA sequencing), clinical trials data, billing and claims data, and patient-generated health data are generating massive amounts of data on patients. This shift has transformed healthcare from a field driven by intuition and experience to one where data-driven decisions and analytics are paramount.

The scale of healthcare data has grown exponentially, making it difficult for healthcare providers to manage, analyze, and extract meaningful insights from it. The sheer volume of data has transformed it from “BIG DATA” to what can now be referred to as “COLOSSAL DATA” . The challenge now is not just to store and manage data, but also to derive valuable insights that can be used to improve patient outcomes and inform clinical decision-making.

This ever-growing colossal data in healthcare requires sophisticated tools and techniques to manage, analyze and derive insights. Data science, data engineering, data analytics, artificial intelligence (AI) and machine learning (ML) are some of the essential components of the data-driven healthcare modernization.

Data science is concerned with the development of algorithms and statistical models to extract insights from large and complex data sets. Data engineering is responsible for designing and implementing data storage, processing, and retrieval systems that can handle the volume and velocity of data generated in healthcare. Data analytics involves the use of statistical methods and machine learning algorithms to analyze data and identify patterns and trends. AI and ML are used to build intelligent systems that can learn from data and make predictions or decisions.

Together, these technologies are transforming the way healthcare is delivered, enabling more personalized and patient-centric care, improving patient outcomes, and reducing costs. They are also helping healthcare providers to manage their resources more efficiently and optimize their operations.