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5 Benefits of Predictive Analytics in Healthcare

By Paul Sinclair 02.24.21 Predeictive Analytics in Healthcare: Concept art, a doctor holders a physical folder while viewing digital data on a computer screen
Reading time: 4 minutes

Healthcare providers today can access a wealth of data at their fingertips. From EHRs/EMRs, medical images, insurance claims, medical devices, and administrative data — there’s no shortage of information about patient healthcare data.

The question is, what to do with it?

For many healthcare systems and organizations, the sheer size and number of data sources can be overwhelming, especially with databases that don’t talk to one another. To really drive positive patient outcomes, you need a 360-degree view of the patient — from their complete medical history to social determinants and more.

Predictive analytics, a discipline that uses various techniques through modeling, data mining, statistics, and artificial intelligence (AI), can evaluate historical and real-time data to make predictions about the future. It’s what makes sense of disparate, disconnected data sources and can help your organization see patterns that can make your operations more efficient and deliver a higher quality of care.

5 ways healthcare predictive analytics help providers improve patient outcomes

Your patients expect a cohesive, intelligent experience every time they interact with their provider. Whether they’re doing a routine check-up or seeing a specialist, they expect a seamless, personalized experience.

Predictive analytics, powered by Salesforce Einstein and integrated with Salesforce Health Cloud, enables healthcare providers of all sizes to discover insights, predict outcomes, recommend next steps, and automate tasks for business users. With predictive analytics, you can:

Optimize operations and prevent patient leakage

It happens every day. Even after a patient confirms their appointment, late arrivals and no-shows wreak havoc with scheduling. But do you know why they no-show?

Predictive analytics can help sift through the data to understand the bigger picture. Perhaps patients don’t have access to a car and are unable to make an appointment or childcare falls through at the last minute. It may be that you have a doctor’s office closer to their home or workplace that’s easier for them to get to. AI can detect if a patient lacks access to transportation — captured as part of their social determinants of health — the provider is alerted and can help the patient arrange a ride to avoid missing the appointment.

It can also help understand the overall coverage for your healthcare provider network. If the majority of your patient population are parents with young kids, you may want to focus on hiring more pediatric specialists or offering pediatric services in the same building as adult medicine.

Identify at-risk patient cohorts

Predictive analytics can identify specific risk factors for various populations. For example, it can identify diabetic patients with the highest probability of hospitalization based on age, coexisting chronic illnesses, medication adherence, and past patterns of care.

Predictions on the likelihood of disease and chronic illness based on this analysis can create early interventions that aim to reduce emergency room visits and reduce hospital readmission rates. Rather than wait for an at-risk patient to come in for a regular check-up, you can proactively provide care, sending an email notification or call to remind them to come in, to see a specialist, or to take certain screening or imaging tests.

You can also raise awareness of different issues for your patients, such as running an email campaign around the health impact of smoking and offering support for patients interested in quitting.

Chronic disease management and preventative care

Predictive tools such as remote patient monitoring and machine learning can work hand in hand to support decisions made in hospitals through risk scoring as well as threshold alerts. This feeds into tailored communications with Salesforce Health Cloud to remind patients to refill prescriptions, or to assist them if they’re having trouble accessing refills or going to the pharmacy.

Einstein can then feed into Salesforce to trigger an email notification or phone call to check in with patients managing long-term health issues. This technology can allow the involved parties to proactively prevent readmissions, and emergency room visits, as well as other negative events.

Additionally, AI can alert a care manager of patients falling behind on their care plan and recommend personalized outreach. These are the types of seamless patient experiences that encourage better adherence to care pathways and ultimately influence better health outcomes.

Population health management

Physicians can improve patient outcomes by selecting the best treatment plans utilizing predictive analytics. Considering what is known about a patient’s existing conditions, medications, and personal history, AI can be used to find other patients within a population cohort that are similar.

Machine learning algorithms can find patterns in EMR data to cluster together similar patient procedures and identify clinical pathways that result in the best patient outcomes. Based on the data aggregation, the treatment plans given to these patients could be analyzed by the physician to determine the most appropriate option for a patient.

Scheduling and patient utilization patterns

AI can predict peak highs and lows as well as the weak points of the workflow, building an effective schedule that will avoid extreme workload and avoid needless downtime. Looking at seasonality, common patterns, and clinic capacity, predictive analytics can show your team how many appointments to book on a given day and how much space to leave open for emergency visits.

This can also help prevent patient leakage due to scheduling. If your primary care doctor refers you to an oncologist for a cancer screening, but the oncologist on staff is booked for six weeks, it’s more likely that patient will go elsewhere, seeking care as soon as possible.

Harness the power of predictive analytics with Salesforce Einstein and Silverline

With Salesforce, healthcare organizations can harness already existing data into a strategic, cohesive patient experience that streamlines your operations while improving patient outcomes. Integration with Salesforce Health Cloud and Einstein Analytics has made it easier than ever to understand the roadblocks to an excellent patient experience and build a stronger patient relationship that anticipates their needs.

The opportunity and benefits of predictive analytics is continuing to accelerate, with the latest AI and machine learning technologies now enabling healthcare professionals to answer not only what happened, and why it happened, but what will happen and provide insights on the best course of action to take.

Going forward, technology will continue to play a fundamental role in improving patient care and outcomes as more providers invest in understanding the wealth of data at their fingertips.

Silverline can help you make sense of all of that data by selecting the right Salesforce solution for your organization. Our experienced team members come from across the healthcare industry and have a wealth of experience when it comes to standing up best-in-class patient experiences. Interested? Reach out.

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