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How many people go to the doctor every year? While healthy people go once a year, patients with debilitating diseases may visit multiple specialists daily. This fact, combined with the world’s population of <\/span>around 8 billion people<\/span><\/a>, results in many healthcare records being created yearly.<\/span><\/p>\n The amount of healthcare data available for analysis is enormous. Doctors and nurses record a patient’s history and any allergies, previous medical procedures, and medications at each visit. Furthermore, new opportunities to collect healthcare data continue to emerge. Patients are purchasing and interacting with wearables and other medical devices, and they have begun to use telehealth services, which provide healthcare appointments and information via telecommunication devices.<\/span><\/p>\n Analyzing this data can identify effective preventative strategies, eliminate inadequate care, and expose fraud.<\/span><\/p>\n Why are companies taking so long to start leveraging healthcare data? Healthcare data is frequently unstructured and difficult to extract. This creates a genuine and pressing need for data integration in the healthcare industry.<\/span><\/p>\n Data can come from various sources, posing a significant challenge for healthcare providers. Here’s a simple example:<\/span><\/p>\n A patient visits three clinics in their area to seek advice on a medical problem. Each clinic has its EMR system that stores data from each visit. Following the last stop, the patient goes to the drugstore to pick up a prescription, resulting in a fourth data point. Any additional health data, such as heart rate records from a wearable device or virtual doctor visits, will generate new data points stored in separate databases.<\/span><\/p>\n Connecting data points from multiple databases are time-consuming, but consolidating the data would be highly beneficial, even in this simple case. Here is where data integration comes in.<\/span><\/p>\n Combining data from various sources into a unified set is called data integration. Data is cleansed and transformed during the integration process to ensure accurate analysis. Data integration brings together disparate data sources to provide invaluable business intelligence.<\/span><\/p>\n Read more: <\/span>Managed Services for Cloud Infrastructure and Healthcare Applications<\/span><\/a><\/p>\n Although there is an obvious need for data integration in healthcare, the industry currently faces significant challenges.<\/span><\/p>\n Healthcare data can come from various sources, as illustrated in the simple example above. Medical devices and wearables are one source of data. While this trend encourages people to be more involved in their health, it generates excessive data and raises compliance and privacy concerns.<\/span><\/p>\n Aside from the processing power needed to integrate all health-related data sources, the data must also be presented so that doctors, nurses, medical researchers, and patients can understand.<\/span><\/p>\n These two major impediments, along with the following, pose significant challenges in data integration and, ultimately, provide healthcare providers with a comprehensive picture of their patients.<\/span><\/p>\n Healthcare data is fragmented, coming in various formats from multiple sources. Images, texts, and videos, as well as traditional EMR records, must be supported by healthcare technology.<\/span><\/p>\n Furthermore, healthcare is notorious for its out-of-date, expensive on-premises data warehouses. These systems cannot “communicate” with one another or new data sources. Healthcare IT departments struggle to automate processes, keep up with market changes, and provide consolidated data to decision-makers without a unified solution.<\/span><\/p>\n One solution to this growing issue is to build a cloud-based data lake. Building a data warehouse in the cloud allows businesses to track a patient’s journey in real-time. Traditional ETL processes take far less time on the cloud, and storage is no longer an issue. Healthcare organizations can quickly and efficiently cleanse, standardize, and segment data without these impediments.<\/span><\/p>\n It may be impossible to get all healthcare providers (hospitals, clinics, doctor’s offices, pharmacies, research labs, and telehealth providers) to use the same methodology. On the other hand, creating cloud-based data lakes can significantly improve data quality while allowing healthcare organizations to make quick, accurate patient decisions.<\/span><\/p>\n Medical wearables have transformed healthcare. Pacemakers, insulin pumps, and fitness trackers are all commonplace. This information is precious to healthcare professionals and can mean life and death.<\/span><\/p>\n Nonetheless, medical devices complicate and complicate data collection. Devices continuously transmit data. For the time being, the wearable trend shows no signs of abating, putting a significant strain on IT departments that must aggregate and process medical device data.<\/span><\/p>\n Real-time pipelines integrate the deployment and automation capabilities required for continuous data integration. These pipelines clean and condense medical wearable data before integrating it with EMR, claim, and provider data. Real-time pipelines, in this way, provide a comprehensive picture of a patient’s health while accommodating their modern lifestyle.<\/span><\/p>\n Everyone is concerned about privacy and regulation with so much data on the internet. This concern becomes even more pronounced when it comes to people’s health. To ensure that data is not accidentally shared or stolen, healthcare organizations must thoroughly understand confidentiality laws.<\/span><\/p>\n In the past, laws such as HIPAA required businesses to keep EMR, billing, and research data separate. This unintentionally created departmental silos, making data integration even more difficult.<\/span><\/p>\n Healthcare organizations moving to a cloud-based data lake should implement a robust data governance practice to enforce security. Data governance enables database administrators to restrict access to specific data at specific times. This ensures compliance while keeping data visible to those who need to view and analyze it.<\/span><\/p>\n Many industries have failed to scale since the advent of cloud computing and social media. They are unable to process data as quickly as it is generated.<\/span><\/p>\n Healthcare has arguably more data than any other industry, and most healthcare companies on-premises data warehouses cannot keep up with the rate of data influx. As a result, healthcare organizations miss essential insights and opportunities to improve patient care. Healthcare organizations increasingly rely on cloud-based integration solutions to bridge the gap.<\/span><\/p>\n Many healthcare organizations are turning to cloud-based platforms that interact with various tools and languages, such as SQL, Apache Spark, and Tableau. These tools can add meaning and context to data before it is analyzed. Because of their ability to handle and analyze petabytes of data, artificial intelligence and machine learning are also becoming popular solutions.<\/span><\/p>\n Healthcare data benefits patients, doctors, nurses, researchers, and even medical device inventors. Data can be used to improve medical devices, make more accurate diagnoses, study patient behaviour, and assess pharmaceutical success.<\/span><\/p>\n While healthcare data can be compelling, without the guidance of data scientists, raw data is easy to misinterpret. Furthermore, data can be abused if it falls into the wrong hands. Because of these risks, IT is primarily in charge of managing healthcare database access. However, resolving help desk tickets end user by an end user is time-consuming.<\/span><\/p>\n One solution is to create a self-service access model. The IT team implements these models, which include hierarchies to protect confidential information. Furthermore, self-service platforms have production-ready data, which reduces end-user extrapolation and interpretation.<\/span><\/p>\n Modern healthcare is inextricably linked to the cloud. Patients can now interact with providers and wellness programs online, increasing their independence, awareness, and empowerment. Similarly, audio, video, and other files accumulate and must be integrated into complex datasets.<\/span><\/p>\n With the increasing need for data storage, the cloud is becoming indispensable. Still, promoting patient engagement and assessing patient populations is also critical. Furthermore, the healthcare industry is experiencing more mergers and acquisitions than ever before, necessitating adopting a new data storage and integration strategy.<\/span><\/p>\n These increasingly large healthcare datasets can be analyzed using cloud-based data integration. Agile, cloud-based platforms can connect previously disjointed or siloed datasets, resulting in a universal reporting methodology. Cloud technology’s continued growth and development will undoubtedly drive healthcare technology innovations.<\/span><\/p>\n As the number of healthcare data sources and types grows, gaining a comprehensive picture of an individual’s health and producing better patient outcomes becomes increasingly difficult.<\/span><\/p>\n Data integration is critical to the success of healthcare. Integration of large datasets can help to identify disease prevention methods, reduce the number of incorrect diagnoses, introduce more personalized care, and reduce costs by detecting fraud and avoidable overuse. Companies are storing and interpreting this ever-growing data using cloud-based or hybrid infrastructures.<\/span><\/p>\n Bestarion<\/span><\/a> is one of the leading solution providers for data integration to the cloud. We collect and integrate data from multiple systems and sources, transform it into usable formats, and govern it to ensure compliance. A healthcare organization can use our Data Fabric to selectively share data with internal and external stakeholders to make life-saving decisions.<\/span><\/p>\n There is a wealth of health information available that is just waiting to be analyzed. <\/span>Contact us<\/span><\/a> today to become a leading provider.<\/span><\/p>\n <\/span>The Advantages of Data Integration in Healthcare<\/span><\/span><\/h2>\n
<\/span>What Are The Top Data Integration Challenges For Healthcare Companies?<\/span><\/span><\/h2>\n
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1. There Is No Way To Standardize Data Formats<\/span><\/h3>\n
2. Medical Wearables Create Streaming Data<\/span><\/h3>\n
3. Data Privacy And Compliance Regulations<\/span><\/h3>\n
4. Healthcare Needs More Data Integration Processing Power<\/span><\/h3>\n
5. End Users Are Not Data Scientists<\/span><\/h3>\n
<\/span>The Cloud And The Future Of Data Integration In Healthcare<\/span><\/span><\/h2>\n
<\/span>Getting Started With Data Integration For Healthcare<\/span><\/span><\/h2>\n