The future of patient data: 3 pillars of successful analysis
In the era of COVID-19, the health system recognizes that the existing data infrastructure is insufficient. Here are three things that need to be useful for large data sets.
In recent years, wearable devices and smartphone applications have become more and more popular. More and more patients are self-monitoring their health parameters and bringing these data to appointments. According to Gartner, in 2021, the total expenditure of end users worldwide on wearable devices will reach 81.5 billion U.S. dollars, an increase of 18.1% from the 69 billion U.S. dollars in 2020.
Today, healthcare consumers can easily obtain health data through healthcare information tools and equipment. Informed patients track all aspects of their care from many sources, including personal gadgets, health apps, counseling and diagnostic centers from multiple specialties.
The influx of data from many sources and open API technologies are changing the way patients prepare for outpatient consultations. They want to get care in the home health environment and get data from their equipment and Google research.
On the other hand, data on health systems and doctors comes from multiple sources-patient care applications, personal and medical equipment, hospital management, operations, supply chain, logistics, referrals, and human resource management.
This data can solve practical problems in daily work processes, such as appointment availability, access to chronically ill patients’ diet patterns, supply chain logistics of PPE kits, drug inventory, patient lists that require routine laboratory testing, and identification of gaps in regulatory compliance .
The list is long. Developers in EHR markets such as Epic Orchard, Allscripts Applications Store and Athenahealth Market have proven that more and more applications are released on a regular basis for different workflows for management, clinicians, patients, and back-end infrastructure users.
Due to the technological disruption and open FHIR API in the past decade, the health system has obtained data from various sources. Organizing all the data is still a challenge. From a technical point of view, key components include data integration from multiple sources, hosting it in a data mart consistent with specific business processes, and flexible expansion as needed.
This is similar to stacking the same items on different shelves in a grocery store to facilitate consumption. After collecting the data, it can provide actionable insights to business partners. What technical standards will enable healthcare data to benefit consumers and the health system? What has changed in healthcare technology in the past ten years? This is my prediction of patient data and visits in 2022.
Enterprise Digital Transformation: Three Pillars of Success
During the pandemic, large-scale health systems quickly adapt and manage various nursing and operational workflows. Save, standardize, and analyze data from multiple sources. They aggregated data from different sources and created supply chain workflows for providing PPE kits, maintaining medical inventory, tracking patients requiring COVID-19 testing, improving virtual and telemedicine platforms for routine access, and installing remote Equipment to coordinate elderly care and fragile patient care.
Data becomes the source for large organizations to piece all the puzzles together into the cloud infrastructure.
In the era of COVID-19, the health system recognizes that the existing data infrastructure is insufficient to meet the diverse needs of multiple stakeholders. Large amounts of data require three things to be effective: residence-hosted in the cloud, the ability to exchange it-interoperability, and semantic or language understanding-terminology standards.
Health cloud. For a period of time, the digital transformation of enterprises has been using the power of the cloud to migrate part of its technical infrastructure to the cloud. Today, most health systems are in a hybrid mode, with some applications in the cloud and some locally.
The infrastructure provided by large technology companies such as Google, Microsoft, Amazon, and Salesforce includes data ingestion in multiple formats, conversion of the data into medical standard formats, storage, and finally sharing them among users in the FHIR format.
Health Cloud is a unified data repository across systems and care settings. It enables healthcare organizations to rapidly develop scalable applications, unleashing the power of data to improve clinical, operational, and financial results.
Interoperability. Healthcare data formats include text, graphics, numbers, paper, numbers, photos, videos, multimedia, radiological images, ECG waveforms, and other more complex data formats. Raw data in healthcare can be in various formats, including flat files, XML, JSON, database extraction, and standards-based documents such as HL7, CDA, or X12.
Cloud platforms need to parse, encode and store data in a unified data model with standard ontology. Only in this way can downstream applications use it to support patients and their providers at every step of the journey. Standardizing this data and running smart algorithms on it can provide valuable insights into all functions.
Standard terminology. As part of standardized ontology exercises, let different systems use the same language. The recommended USCDI data classes for clinical and administrative data define recommended interoperability terminology standards.
Recently, USCDI revised the second iteration of the data standard to cover the socioeconomic determinants of health, sexual orientation, and gender identity. These are becoming important data sources for tracking and creating health equity.
For example, healthcare data platforms provide information about the supply of nutritional food for patients, or help clinicians understand patients’ lifestyles and how this may affect their overall health.
Once the above three areas are resolved, many downstream use cases can be met. Executive leaders can determine the supply gap by understanding the consumption of each clinical department. With the power of a single dashboard, data from linked devices can reveal gaps in care and help in outreach activities for disadvantaged groups.
The 360-degree view of a single patient or a group of patients can determine the quality indicators of regulatory requirements. The FHIR-based API interface also helps application developers quickly deploy user-friendly mobile applications that can be easily linked to electronic medical records and provide critical information to patients and doctors.
The way ahead
Compared with any other industry, the 5 V of big data is more suitable for healthcare. The amount of health data collected over time, the speed at which medical devices collect real-time data, the diversity of structured and unstructured data, the accuracy of missing and inaccurate medication history, and the value of combined data can increase the value obtained Business insight.
All this big data deployed in the cloud infrastructure brings us into the world of healthy cloud, which is now entering the forefront of healthcare technology as the next level of evolution.
Once healthcare organizations understand the power of a unified data platform, steps to improve patient treatment outcomes and reduce costs will become more apparent. Key performance indicators and reports derived from the health cloud can provide transparency and automated processes in care to reduce employee turnaround time and effort in finding care gaps, reacquiring codes, and avoiding unnecessary use.
Many participants can coordinate the patient-centered ecosystem, including their clinical care providers, payers, and policy makers. The digitization of healthcare data is now the key to adopting three technological pillars: standardizing data using standard terminology, promoting interoperability with FHIR standards, and ultimately hosting them on cloud infrastructure.
Dr. Joyoti Goswami is the chief consultant of Dharma Consulting.