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Building Patient Intimacy with Big Data Analytics

March 14, 2021 - by Parul Saini, Webmedy team


Doctors sometimes see dozens of patients in a single day, which makes it difficult to build rapport with them. Requiring efforts to get in-depth patient data at the beginning of an appointment, doctors and nursing staff may find themselves puzzled by a patient's conditions and symptoms. This naturally turns into uncertainty among hospital administrators and other management as well. As a healthcare organization endeavors to improve patient outcomes and satisfaction, patient intimacy dramatically affects the future of the organization.

Achieving patient intimacy needs careful use of patient data analytics to draw a clearer picture of patient needs. Using technology like big data analysis is the only way to build rapport with patients in an era where patient and doctor time is limited.

Why Is Patient Intimacy Important?

Patient intimacy plays a huge role in the growth of a healthcare organization. While external marketing is important, existing customers may not recommend the provider if they don't have a strong relationship with the doctor or clinic. Even more importantly, patient intimacy can build trust in physicians, which has generally decreased in recent years. This may increase patient compliance with guided treatment plans, which is especially critical for individuals living with chronic conditions.

What is Big Data Analytics in Healthcare?

Big data analytics in healthcare is the method of gathering, curating, enriching, and dynamically determining patterns and insights from massive quantities of consumer and patient data. Information resulted can be used by health systems to improve management, operations, drive ongoing growth, and generate a higher quality of care.

What are some hurdles in Healthcare Data Analytics?

The challenges with healthcare data have to do with its quantity, velocity, variety, veracity, and value - none of which should be taken lightly. Sorting through zettabytes of data is expensive and resource-intensive: it's simply an issue of volume. On top of this, this data has a shelf life and therefore requires healthcare data professionals to make sure that it is processed with timeliness in mind.

The incredible variety of data is also a possible challenge: with so many formats of information (alphanumeric text, audio, video, image), it's difficult to process data in an effective, unified way. Of course, if data is gathered or analyzed improperly, the resulting insights may not be accurate nor trustworthy - so it's incredibly important to take careful steps to standardize data formatting, collection, curation, and enrichment.

Why is Data Analytics important in healthcare?

Healthcare data analytics can be used to feed the patient-physician relationship, allowing patient-centric care. Although analyzing big data doesn't always have an immediate impact on revenue, it has many applications, from informing healthcare marketing strategy to personalizing the clinical experience.

Clinicians can pinpoint individuals who have a chronic disease, why they should contact them based on anticipated and predicted requirements, what issues they might have with their current care, and how to craft their message to that specific person. This opportunity exists outside of chronic illness, too - so long as a healthcare professional knows who needs attention, what their issues might be, and how to craft a message that's relevant to the patient.

Finally, the goal of leveraging patient data is to predict a patient issue before it occurs and deliver a resolution or message by the preferred channel of communication.

How does Aig Data Analytics impact Patient Intimacy and Engagement?

Maintaining patient intimacy needs a strong relationship between patients and health care providers. Establishing a healthy two-way communication stream is important to better understand patient needs and drive loyalty. Patient intimacy is also vital for efficiently engaging patients in their care. The problem is that many clinicians feel frustrated that their tight timetables are not helpful for a growing and evolving relationship with their patients. The average visit with a doctor is only 17 minutes - and according to a study, 44% of patients didn't visit their doctor in the past year, and 13% haven't visited their primary care physician in the last five years.

With the help of personal information, healthcare professionals can predict a patient's future issues and deliver messages however and wherever they are most relevant to that individual. For example, some patients might want this message to be delivered through mobile or SMS, while others prefer an email. It's important to have a clear understanding of not just consumer data but also communication preferences.

By leveraging enriched predictive insights alongside an EHR, mixing massive quantities of patient data with the data available in the EHR provides clinicians with already-aggregated information to anticipate patients' needs and involve with them.

Giving Preventive Care Information

Many patients don't visit their primary doctors yearly and may miss out on chances for preventive care. Preventive care appointments are both medically necessary and a great opportunity to build patient trust and intimacy. Giving custom-tailored preventive care data to patients may motivate them to visit their doctor again, improving the chances of them getting the care they need. This information could be tailored based on the number of children in the household, income, age, and other factors that affect the type of care they need.

Summary

The impact of big data analytics on healthcare is multifaceted, and as technology changes, we may see even more ways to use big data analysis. Healthcare providers need to start the process of big data analytics as soon as possible to improve patient outcomes and organizational growth.

The world of data analytics is a marathon, and your healthcare staff won't become innovators in the field of analytics overnight. Instead, view your engagement with analytics as a continuous lifecycle. It begins with acquiring and integrating data and continues with updating patient profiles, assessing risks, identifying gaps in care, and personalizing an engagement plan.

If used efficiently, big data has huge potential to positively impact the healthcare industry. Finally, investing in data aggregation, integration, curation, and enrichment solutions benefits the infrastructure of a healthcare business. Doctors are better informed to do their work and reach out to patients in meaningful ways - and nurturing intimate relationships with patients will mean a healthcare business is more relevant and competitive in the long run.

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