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Data analytics in healthcare involves collecting, studying, and interpreting historical and real-time healthcare data to gain actionable insights by uncovering trends, relationships, and correlations between datasets. Examples of this type of analytics include medical claims data analysis, healthcare insurance analytics, value-based care data analytics, and more.
“An analytical platform can be invaluable to healthcare providers transitioning to value-based care. It delivers actionable insights, such as identifying high-risk patients that need proactive care, alerting providers to misdiagnosed conditions and additional screening opportunities, and notifying care teams of hospitalized patients to prevent readmissions. These insights enable clinics to manage patient populations effectively and achieve better health outcomes.”
Delivery Manager
We develop big data analytics solutions capable of analyzing large amounts of data from electronic health records/electronic medical records (EHRs/EMRs), wearable devices, and other sources. With the software we deliver, healthcare providers uncover valuable insights and make efficient medical decisions to enhance clinical care and improve patient outcomes.
EffectiveSoft’s developers create healthcare data warehouses (HDWs) that unify, store, and manage vast amounts of heterogeneous clinical, administrative, financial, and operational data. By using the HDWs we build, medical professionals can quickly access essential information to further employ it for data analysis purposes.
If you want to forecast healthcare risks and outcomes based on real-time and historical data, harness the power of the predictive analytics solutions we create. Our specialists develop AI-powered software that helps identify health conditions and create lists of high-risk patients, alerting medical professionals to complications before they arise.
We create high-quality medical image analysis tools powered by machine learning (ML), deep learning (DL), and computer vision (CV). By deriving meaningful insights from magnetic resonance imaging (MRI), X-rays, and other relevant images, healthcare facilities can increase diagnostic speed, improve accuracy, and foster value-based care.
Our developers build Internet of Medical Things (IoMT) analytics solutions to help healthcare companies gather, analyze, and exchange real-time data from medical devices, sensors, and software. The IoMT analytics solutions delivered by EffectiveSoft enhance remote patient monitoring, optimize healthcare workflows, and reduce operational costs.
The custom data visualization tools we build support data analytics and transform complex clinical data into easily comprehensible dashboards, featuring detailed reports, graphs, and charts. If you are seeking actionable insights to guide strategic medical decisions and improve patient care, data visualization software is a must.
Out-of-the-box medical data analytics solutions | Bespoke healthcare analytics solutions | |
---|---|---|
Alignment with needs | Designed for generic healthcare needs and workflows | Tailored to specific healthcare needs, workflows, and challenges |
Scalability | Present scalability challenges with growth | Scale and adapt as healthcare needs evolve |
Customization and flexibility | Offer predefined features and limited customization options | Provide unique features and full customization capabilities |
Implementation | Don’t require extensive planning and full-scale development, allowing for quicker deployment | Require detailed planning and development from the ground up, resulting in longer implementation times |
Security | Come with limited security features, creating data breach risks | Offer enhanced and tailor-made security measures, reliably protecting healthcare data |
Integration capabilities | May require extra resources to ensure smooth integration | Integrate seamlessly with existing infrastructure and systems, such as EHRs/EMRs |
Cost and return on investment (ROI) | Require lower initial costs, but deliver lower ROI to the need for customizations and integrations | Require upfront investment but offer higher ROI due to improved efficiency and fewer errors |
User experience | Provide a generic user experience that lacks personalization | Deliver a highly customized and personalized user experience |
Maintenance and support | Maintained and supported by software vendors, which can be limiting | Require ongoing maintenance and support, imposing additional costs |
The applications of healthcare data analytics are numerous and can be broadly categorized into healthcare and data use cases.
Data analytics in healthcare can enable faster and more accurate diagnoses and improve patient and clinical outcomes. The healthcare use cases of data analytics include but are not limited to the following:
Data analytics helps harness vast amounts of healthcare data to extract valuable insights and drive informed clinical decisions. The data use cases of healthcare analytics encompass:
Centralized data storage solution for reporting, analysis, and data-driven decision making.
First, we identify our client’s pain points, establish clear objectives, and define the project’s scope, including technical requirements, milestones, and deliverables.
We then collect healthcare data from various sources, evaluate its quality, identify potential issues, and clean and validate it for further analytics.
Next, we create an initial design for your healthcare data analytics solution, outlining a user experience (UX) roadmap and highlighting key product features.
Our specialists then choose the appropriate algorithms for building and training an ML model, fine-tuning and improving relevant parameters if needed.
We test the ML model with new data to assess its performance and make adjustments. At this stage, we prioritize clinical utility, ensuring the model delivers high-quality data at the right time and can be integrated into clinical practice.
We then integrate the ML model into the production environment, ensuring it fully meets the scalability, security, and compliance requirements of the healthcare provider.
Our team creates interactive dashboards to support data-driven decision-making and deliver results to all healthcare stakeholders.
Finally, our maintenance and support team monitors the ML model’s performance, implements any required updates, and resolves emerging issues.
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“EffectiveSoft is laser-focused on creating best-of-breed data analytics solutions that transform vast amounts of raw medical information into actionable insights, accessible 24/7. If you, as a healthcare business, have growing concerns about data silos, operational inefficiency, suboptimal patient experiences, or poor security, our data analytics team has the latest competencies to overcome all these challenges, allowing you to deliver patient care more proactively, quickly, and efficiently.”
Senior Data Scientist
Data analytics plays a pivotal role in the modern healthcare industry, with its multiple use cases like precision medicine and fraud prevention. Does it have the potential to render medical care more proactive, patient-oriented, and cost-efficient while transforming operations, administration, financial management, and other healthcare aspects? Absolutely. So, why wait to create and implement custom healthcare data analytics solutions? Contact us now to squeeze the maximum value out of your healthcare and patient data for increased clinical efficiency, reduced costs, and improved value-based care delivery.
By implementing data analytics into their processes, healthcare entities can achieve the following benefits:
Although data analytics is highly beneficial for the healthcare industry, its implementation comes with particular challenges. They include substandard data quality, security and privacy, integration with existing systems, talent shortage, resistance to change, and more. Are you feeling overwhelmed by some of these problems and want fast and effective solutions? Our data analysts are ready to assist.
The cost of implementing healthcare data analytics varies significantly based on factors like data diversity and complexity, the required integrations, the use of AI/ML algorithms, and more. To receive an exact quote tailored to your project, contact us now.
The future of data analytics in healthcare looks bright, given the advancements within AI/ML, such as natural language processing (NLP) and CV. Key trends in healthcare data analytics include NLP- and CV-powered data analytics, healthcare data visualization, a focus on value-based care, the use of blockchain for security, and others.
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