It’s no secret that digital technology advances continue to be poised to further disrupt the healthcare industry. Everywhere you turn, there are new articles, new case studies, new products, and new vendors. Today’s technologies can result in better outcomes, more efficient care flows, and lower costs . . . in the long run. To thrive in the landscape of tomorrow, healthcare providers will have to proactively innovate in many areas. The question is: which technologies should be used, where, and how?
Though much progress has been made in the past few decades, the area of information collection, storage, and sharing is still in need of significant innovation. Electronic Health Records (EHRs) have been around since the 1970s, with large-scale adoption happening after the 2009 HITECH Act outlined incentive payments for providers who adopted EHR systems in a “meaningful” way.
Although EHRs are now widespread, they’re often constricted to use within one organization, sometimes not accessible to all locations within a system, causing disparity in records. Inability to associate a national patient identifier (NPID) to each patient creates issues with continuity of records within and between providers. Blockchain has emerged as a possible solution, but is still in early stages. Much of the collected data is input manually by clinicians and staff during patient visits. And many organizations still store that data on local servers due to security concerns among other issues.
Unfortunately, while today’s EHR systems have helped with patient care, challenges remain. They may take time away from direct patient interaction, lead to issues with empathy, and introduce steep integration costs. Digital technology advances can move organizations from basic installations that check a regulatory box to full-scale ecosystems that drive success and profitability.
While EHRs are valuable as a centralized collection of records, the data comes largely from one place. According to the National Academy of Medicine, “doctors and nurses spend up to 50 percent of their clinical encounters completing clinical documentation and up to several hours per week outside of encounters documenting in the electronic health record.” Not only does this take time away from meaningful patient interaction, it also presents a lopsided view into a patient’s health. A balanced view should include daily symptoms and vitals, medication levels, behavioral health issues, socioeconomic and social determinants of health, among others.
Enter cloud-based platforms and Internet of Things (IoT) devices. Cloud-based platforms make it easier for multiple sources to transmit patient data into one place. Other providers—like pharmacies, behavioral health centers, and community clinics—can send relevant, up-to-date information. In 2006, University of Pittsburgh Medical Center (UPMC) began connecting their two major EHR systems in the cloud via dbMotion (now AllScripts). They reported that by 2012, “two out of three providers in the system . . . used information in dbMotion to make clinical decisions and direct course of treatment.” IoT devices, like smart watches, wearable health devices, and digital pills, can both automate data collection and provide a deeper look into a patient’s daily wellness.
More and more healthcare organizations are moving to cloud-based platforms for interoperability and secure data storage. The emergence of data lakes and enterprise data warehouses (EDWs) has provided a cost-effective option compared to the scaling of on-premises networks. A data lake is “an architecture used to store high-volume, high-velocity, high-variety, as-is data in a centralized repository for Big Data and real-time analytics.” It can pool structured, unstructured, and semi-structured data from any source. An EDW is similar, but contains only data that’s been converted into a structured schema.
A regular occurrence of high-visibility, high-cost data security breaches has dampened some groups’ enthusiasm to move in that direction. But the truth is that security issues stem more from policy gaps than from any risks inherent in cloud technology. In fact, cloud providers often have more resources to invest in cybersecurity, and can guide private organizations through the planning process.
The benefits of gathering data in one place is also a matter of scale. Deep Learning combines with massive amounts of data (i.e. “Big Data”) stored in data lakes and EDWs to identify patterns and predict outcomes. The more data, the more accurate those predictions will be. Analytics can be applied to data from diverse sources to create better flow patterns, diagnoses, and business decisions.
Besides abilities for collection and storage, cloud-based technology and artificial intelligence (AI) can come together to create end-to-end platforms that allow input and provide output to all involved parties.
“Imagine a portal funneling information from patients, providers, payers, and community groups into a centralized repository that then applies analytics, Deep Learning, and Natural Language Processing for a highly personalized, contextual, predictive environment.”
Once cloud technology is implemented, interoperability is established, allowing for global data accessibility. AI can be layered on top to enable things like voice-to-text input, preference-based delivery, and predictive health risk identification. Analytics can be applied to provide predictive data, enabling better treatment and business decisions.
Platforms like this aren’t unattainable fantasy. Lehigh Valley Health Network’s investment several years ago in their current platform has resulted in sharing over 6 million healthcare records with over 600 other providers, and creation of an analytics application that’s reduced their number of fatal sepsis cases by 40%. These platforms are within reach today and will be the standard of tomorrow. They’ll serve as a springboard to innovation that transforms healthcare IT into a more efficient, effective ecosystem.
Eliminating the administrative time staff and clinicians spend collecting and transmitting health information cuts costs and allows more focus on patient care. This renewed focus, ease of access to health records and services, and customized platform interfaces will enhance patient experience, in turn increasing market share. Aggregating data in the cloud opens up exciting possibilities for improved care flows and business decision-making offered by AI and analytics.
Healthcare organizations can thrive by proactively innovating—pursuing ways to put technology to use and implementing in a way that serves everyone. Interoperable, cloud-based platforms for better information handling is a crucial first step.