Theindustry is beginning to digitally transform with its adoption of continuously advancing technologies. organizations are moving toward a more connected and collaborative ecosystem for improving the way they provide care.
Arefers to connectors that are responsible for moving and transforming medical data between systems. A high-quality allows institutions to access fresh and accurate medical data for providing accurate diagnoses and prognoses.
Before talking about the different processes involved, let us discuss the existing challenges in building secure .
Table of Contents
- What Are the Existing Challenges When Building ?
- Unifying Records
- Ensuring Data Credibility
- Eliminating False Positives During Data Transformation
- Ensuring Data Security & Compliance in
- Cloud Strategy
- Detecting Fraud
- Delivering Insights Faster
- Secure Your Analytics Solutions with Integrate.io
What Are the Existing Challenges When Building?
Theindustry deals with large from disparate . When building , data can pose many challenges. For better understanding, the challenges of building can be categorized into general and specific challenges. General challenges are those that are typically faced by any industry that builds their own , like:
Avoiding duplicate data
Dealing with cascadingfailures
with increasing data
Data pipe-lining challenges specific to theindustry are based on particular characteristics of data. Data in is private, highly sensitive, and continuously changing in . Errors in such critical data can pose threats to a patient’s health and safety. Consequently, medical can be difficult to build with challenges like:
Handling massive amounts of medical and administrative
Ensuring patient data privacy
Ensuring medical data credibility and availability, delays can be crucial for a patient
Ensuring robustthat respond timely to errors with minimal downtime
These are just a few of the many challenges faced bywhen building medical . However, creating data accessibility with high-quality is a necessity. Efficient medical can open gateways for the industry to leverage the applications of technologies like and .
The digitization of the vastindustry has contributed to creating , collected and unified for making important medical decisions.
With the advancements in technology, numerous isolated medical applications have been made to leverage. The need of the hour for is consolidating data from these applications to create a holistic view of medical data. As a result of this consolidation, important insights can be driven to treatment options at reduced costs.
data entails data collection from a large number of sources and data transformation. Types of records include:
Patient medical records either from patient'sdevices or from hospital appliances.
Patient/doctor survey results
There are so many layers to medical records that are complex and time-consuming to analyze. Before consolidating all these records, some transformations are required to structure thein uniform formats. The unification of records is an important step toward making data-driven decisions based on actionable insights. As a result of these insights, hospitals can effectively improve their disease prevention and prediction processes.
Ensuring Data Credibility
An important consideration when buildingis the maintenance of data credibility and integrity throughout the data . It is critical for doctors to have authentic data at hand to make the right medical decisions. Ensuring data credibility is a critical factor in as the slightest modification in patient data can have devastating health outcomes for a patient.
Patient information is the most important type of medical data. It involves a patient's medical history, test results, personal information, and more. Accurate patient information can help derive reliable results, whereas inaccurate or tampered data can result in the wrong treatment of patients.
Ensuring patient data credibility and accuracy duringcan result in:
Improved patient care
Accurate diagnostic and prognostic insights
Personalized patient treatment
Efficient communication and understanding betweenproviders and patients
Eliminating False Positives During Data Transformation
Alerts are an essential security component of the data transformation process. However, there are some alerts that can be costly to pursue. These alerts are called false positives and they are generated as a result of a that turns out to be a bad lead.data pipe-lining process. Alerts allow security officers to detect anomalies during the
Owing to the sensitivity of data in, every alert is treated critically. Responding to alerts is a time and resource-consuming process, therefore it is crucial for security models to eliminate false positives.
While eliminating false positives altogether might be challenging, there are AI andresources that can drastically reduce false positives. These models automatically filter out false positives and send legitimate alerts back for further investigation. As a result, security professionals can save a lot of time that can be spent on pursuing true violations.
Ensuring Data Security & Compliance in
attacks and breaches.systems today are continuously evolving by embracing technologies like cloud and for data management and effective patient care. While the advancements of these systems are increasing convenience, data is becoming increasingly vulnerable to
In addition to data security, compliance also has an important role to play in building secure. There are a number of standards that aim to ensure patient privacy and data safety. The most widely accepted of these include:
Health Insurance Portability and Accountability Act (HIPAA): A standard for regulating the usage of private patient data.
General Data Protection Regulation (GDPR): A European standard for data protection laws.
FastInteroperability Resources (FHIR): A standard for regulating the electronic exchange of sensitive information.
Compliance with these standards aids the Data compliance ensures medical data safety in storage as well as during data exchange.industry in reinforcing and upholding a standard of data security.
The growing volume and usage ofdata are becoming increasingly difficult to analyze and manage. Data warehousing has become a necessity for institutions to effectively manage their data. A is a central database for , that all the transformed data, ready for analysis.
As the digital world moves to the cloud for data warehousing strategy is particularly useful for the industry in the following ways:, there is no reason why and its cannot be leveraged to manage data. A cloud
Implementing data rules specific toand ensuring data compliance
Implementing complexon clinical data for diagnosis and treatment.
Automating and optimizingservices
Improvingin a manner
Delivering fast and actionableinsights for quality patient care
These are just a few of the many advantages of utilizing a cloudstrategy for analytics.
Althoughfrauds have been around for a long time, their discrete nature rendered them difficult to detect in most cases. However, the recent digitization of the industry has opened new gateways for detecting frauds.
An important advantage of the digital world is that every action leaves a digital footprint. This footprint serves as a clue for modern fraud detection technologies to not only detect but also predict, frauds.
Most common fraudulent activities in theindustry include:
providers multiple-billing for their services.
providers conducting unnecessary medical tests or procedures
Unnecessary use of medical equipment
Patients forging prescriptions
insurance fraud by patients
Identity theft to use another patient'scards.
These are just a few of the many ways in whichproviders and patients commit fraud. Fortunately, technologies have advanced enough to fight these frauds.
fraud detection leverages the benefits of AI for auditing to quickly and accurately detect anomalies. Furthermore, the patterns of historic frauds are used by predictive models to predict fraudulent behaviors.
As AI andtechnologies advance, fraud detection is only going to improve in the future.
Owing to its digital transformation, theindustry stores and moves bulks of data. This data withholds tons of important insights that can dramatically patient care. For manifesting better medical data outcomes, it is important to provide all stakeholders of a clinical setup timely access to relevant information.
is very useful in this aspect as its offer to derive insights from the continuously increasing data. Furthermore, data platforms are also becoming popular for providing interactive to analyze medical data. Following are the examples of tools that leverage these solutions to offer large-scale medical :
's Healthlake: A popular analytics solution that uses and analytics tools to help organizations perform optimized medical .
: An framework for large-scale , suitable for .
In addition toand warehousing solutions for , also use infrastructure tooling solutions like . These tools can dramatically reduce the time for medical insights delivery from months to weeks.
Secure Your Integrate.ioAnalytics Solutions with
Thesector is directly linked to the world population. As the population grows, so do the needs of the people, eventually adding to the increasing records. A connected ecosystem has become a necessity for organizations to keep up with the growing medical information.
Buildingto create a collaborative environment is not enough. Effective measures need to be taken to ensure the protection of .
Want to know how you can protect your medical data while still using it for valuable insights? Check out Integrate.io, an solution for masking your data before transferring it to your . Try it out now.