Today, every industry is data-driven. In The Data Behind, we dig into the data creating change in rapidly evolving industries.

Healthcare is experiencing a digital transformation, shifting how the medical ecosystem operates and the way that care is delivered. And all of this change comes down to one little word: data. In 2013, the healthcare industry produced 153 exabytes of data; in 2020, that volume is estimated to increase over 15-fold to 2,314 exabytes. It’s projected that healthcare data is expanding faster than in manufacturing, financial services, and media.

That’s right — we produce more data at the doctor’s office annually than we do swiping our credit cards or surfing Netflix. It follows that unlocking the power of all that data is the key to transforming the future of healthcare with quality and precision in mind, across clinical, financial,  and operational processes. 

As Big Data continues to expand, what are some of the major trends that data leaders in the healthcare industry are addressing in 2020 and beyond? In this piece, we explore the data that impacts decision-making within the healthcare industry, and how this data helps practices tackle the challenges facing the communities that they serve.

Embedded analytics

Conquering mountains of health data

With COVID-19 reshaping our world, the use of data and analytics has surged across the healthcare industry as they take this unprecedented opportunity to refocus their business models and resource planning. 

Identified opportunities in healthcare

One opportunity includes electronic health records that can be bolstered by BI and change the game for clinicians. Traditionally, the immense amounts of data produced by patients and doctors was confined to paper records in a doctor’s filing cabinet. Electronic health records (EHRs) were a revolution because of the mobility they granted health data and medical records to move between multiple doctors and clinics. Now, these records have the potential to vastly improve clinical outcomes for patients. But many of these systems fall short when it’s time to bring together financial, clinical, and operational data to help practitioners make informed decisions about patient care.

Hamza Jap-Tjong is the CEO of Gerimedica Inzicht, the analytics subsidiary of a SaaS company focused on delivering the best software and service for healthcare professionals in the eldercare sector. For Hamza, embedding a BI solution within Gerimedica’s EHR was key to maximizing the efficiency of each caregiver’s time in a particular hospital ward. 

“Caregivers now have access to alert dashboards that highlight patients who are struggling or not making anticipated progress. Caregivers are able to connect the dots between clinical and operational data and focus their discussions on a handful of patients.”

Hamza Jap-Tjong, CEO of Gerimedica Inzicht

As is the case in many data-heavy industries, it’s often the employees on the job who produce the largest amount of data and who need those insights the most. Yet they have the least amount of time to sift through heavy data exports to put the pieces together. Healthcare providers are skilled at providing care to their patients, and making the lift lighter on the way to gaining critical insights allows them to do what we all hope our caregivers are prioritizing: the highest quality care.

Although use cases for data and healthcare are on the rise, 43% of respondents to the BI & Analytics Special COVID-19 Edition report showed they don’t expect a rise in investment, rather they will maintain the current spend with no reduction. This delivers a positive testament to the importance of data during these unprecedented times.  

Healthcare industry deep dive
State of BI & Analytics 2020

Digital transformation within Healthcare improving visibility for communities in need

Population health management (PHM) is the practice of aggregating numerous sets of patient health data across a specific geography to produce a single record from which health care providers can make important clinical and financial decisions. Presently, these solutions combine public health and technological disciplines to achieve high-level health outcomes for broader populations.

A compelling example of this practice was also employed within a network of state clinics. With 16 clinics already in practice, the organization’s data team aggregated patient records from all of these clinics in order to select the neighborhood that would be best served by a specialty outpatient clinic for Chronic Obstructive Pulmonary Disease (COPD) and Congestive Heart Failure (CHF). With the ability to blend patients’ diagnostic history (clinical data) with their addresses (operational data), the clinic could be built where the highest concentration of potential patients were already living, maximizing clinical outcomes for local patients and financial outcomes for the new clinic.

A great example of this is D-tree International, that is deploying these solutions to enable international volunteers to pass actionable insights to government health organizations in Africa.

“Recently, a local government leader noticed that pregnant women were facing unusually high costs following visits to healthcare facilities in a specific region. That’s not how healthcare should work in Zanzibar — costs should be limited when going to public healthcare facilities. Upon digging further into the visualizations, they discovered that a very important product was out of stock at the facility and patients were required to buy and pay for it themselves.”

Sam Lilienfeld, D-Tree International Technology and Data Manager

With a clear view of the causal link between clinical data (women with a pregnancy diagnosis), operational data (clinic locations), and financial data (heightened aftercare costs), there were immediate calls for policy change in the region that lead to budget reallocations to cover these vital pregnancy products. 

Building the future of healthcare with data 

Radical Transparency

According to Andy Slavitt, former Acting Administrator of the Centers for Medicare and Medicaid, “Doctors are overloaded on data entry and yet rampantly under-informed.” Slavitt’s assessment highlights the immense amount of data going into healthcare systems, as well as the unreasonable amount of pressure on caregivers to make sense of that siloed data fast enough to make long-term clinical and operational changes that will benefit future patients.

Through the successful adoption of advanced data strategies, clinics and hospitals, healthcare organizations, and government health initiatives can aspire to achieve healthier outcomes for patients with precision, accuracy, and superior efficiency. 

Healthcare Dashboards

Spending her early career as a travel writer, Emily Arent found a home in Copenhagen and Denver before settling in Tel Aviv. She’s spent the last 8 years contributing to content programs at agencies and start-ups across Israel.

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