The future of healthcare organizations will be driven by data and digital transformation. You would agree the recent global pandemic has only accelerated this pace of change. For healthcare CIOs, analytics is now a top priority in 2021 more than ever, especially as health information systems (HIS) harness the power of data to optimize every aspect of the care continuum.
It is now the time to switch to value-based care to improve patient experience at every point of delivery. And if you too want to leverage the power of data with healthcare analytics implementation, then this article is for you.
Read on as we discuss the various elements of a healthcare analytics ecosystem that can be optimized with an embedded solution. Specifically, it will cover:
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It can be classified as the process of analyzing current and historical data to predict trends, improve outreach, and even better manage the disease spread. A systematized approach to organizing, analyzing, and interpreting data helps ensure compliance, improve care quality, manage risk, or advance research.
For medical practices and healthcare managers, it is a combination of administrative and financial data to optimize existing procedures, lower operational costs, and streamline services.
When coupled with data visualization tools & business intelligence suites, healthcare analytics can be leveraged at both micro and macro levels to gain actionable insights that support decision-making at every level.
Advancing healthcare and improving patients’ lives requires both measurement and extensive analysis of large healthcare data sets. The valuable and actionable insights help physicians, researchers, medical specialty societies, pharmaceutical companies, and every other healthcare stakeholder to leverage and work on improvement areas.
With an integrated analytics and reporting solution, practitioners can:
As healthcare organizations shift from a fee-for-service to a fee-for-value model, the need to improve practice performance and patient care quality make data analysis a crucial function of daily workflow.
It supports the optimization of healthcare across industry stakeholders – from practitioners, patients, and health information systems to medical specialties, pharma companies, and makers of medical devices. The many applications of healthcare data and analytics can be classified into the following four categories:
Quality data equates to quality patient care and adds value to your organization. A reliable healthcare data analytics solution helps move from a cumbersome clutter of information to actionable insights with a time-tested process that involves:
Additionally, you’ll want to ensure that the healthcare data analytics software is agile enough to evolve with the growing needs of your practice. It should be built with sophisticated security features as it will store all the data using which you can unlock the greatest possible value for your medical practice.
Powered with core capabilities in technologies like artificial intelligence and machine learning, a smart solution can forge seamless connections across the healthcare ecosystem. By collecting & analyzing patient health data sets, providers can:
The potential benefits of such a system are limitless, extending to possibilities such as disease cure, preventable care, early detection of disease, risk assessment, and epidemic predictions.
Insurance carriers are subject to ever-evolving regulations. And being a major expense for families, health insurance relies heavily on efficiency and client satisfaction for success. By collecting and analyzing information using a centralized dashboard, payers can:
Team up with us to tap into the power of health data analytics for real-time action & accountability
How a Healthcare Data & Analytics System Solves These Challenges
With an end-to-end view of the patient’s medical history and existing health condition in real-time, it becomes easy to provide preventive care to achieve and sustain the patient’s health and well-being.
How a Healthcare Analytics Solution Addresses These Issues
It helps with optimal allocation and use of resources to maximize cost savings. Also supports efficient scheduling to reduce wait times and unnecessary delays, thereby resulting in more satisfied patients.
Here we’ll explore some of the real-world examples of how healthcare facilities are leveraging data analytics to improve outcomes across the value-based care continuum.
Risk Scoring for Preventive Care
ML algorithms can identify patients at an increased risk of developing a life-threatening condition early on from the EHRs. This ensures that health facilities have the best chance of helping these individuals to avoid life-long issues that are costly and challenging to treat.
Optimal Use of Hospital Space
A data operating system with an analytical interface can efficiently calculate occupancy rates to avoid suboptimal use of space. An online scheduling tool with a visual map of patient schedules can also help health facilities maximize space & resource usage for increased revenue.
Predicting Operation Duration & Risk
One of the key objectives of leveraging an analytics platform is putting to use the predictive potential of machine learning. It can analyze patient health records to identify those at the risk of clinical decline and bloodstream infections. This information helps predict the duration of operations and avoid surgical room delays.
Predict Daily ER Visits
The system can source this data from the patient scheduling and billing database. The ML model can then analyze it to predict the expected emergency room visits daily with almost 80% accuracy. The extracted insights can help physicians to optimize ER operations and allocate staff in advance, thereby resulting in optimized patient care and positive results.
Create a Mortality Model for Global Pandemics
The data on population density, demographics, and comorbidities in a given region can be leveraged to create a pandemic model that reflects individual risk scores. Using this data care facilities can take precautions and mitigate the risk for older age groups. Telehealth apps can also be used to reduce the exposure of viruses for clinicians.
Reduce the Rate of Hospital Readmissions
Analytics tools can easily identify individuals with traits that have a high impact on the possibility of readmission. This data can give care providers an indication of when and where to allocate resources for follow-ups. Designing the discharge plan protocols based on these insights can prevent readmissions.
Stay Ahead of Patient Deterioration
While patients are hospitalized, practitioners cannot rule out the risk of infections, development of sepsis, and potential threats to their wellbeing. Data analytics can help physicians to be more responsive to any changes in the patient’s vitals or medical condition. Timely intervention is essential before the symptoms become evident to the naked eye. This can significantly improve treatment outcomes while avoiding sudden downturns.
A US-based Healthcare Organization Leveraged a Centralized Dashboard for Real-time Visualization of the Global Pandemic
The outbreak of the Covid-19 pandemic compelled a healthcare organization to immediately develop a dashboard that depicts:
Considering the urgency of the global situation, the solution was developed with a structured approach and made live within a strict deadline. The key features of the solution included:
A statistical model to predict the pandemic end
The solution resulted in a 98% accurate data comparison of the spread & mortality rate along with granular insights of pandemic control, filtered by location.
Such custom solutions are especially beneficial in a fast-paced environment where providers are handling several critical patients simultaneously, which is a situation susceptible to human errors.
Emerging technologies are continuing to push the boundaries of how health analytics can be harnessed. From AI to NLP to ML, healthcare organizations are wielding these for a positive impact.
This is just a glimpse of what the future holds for health data analytics. With technologies advancing at an exponential rate, innovations that can create an even bigger impact are inevitable.
Developing such a custom healthcare data analytics solution is an expensive and time-intensive project. But it allows for a high level of customization. So healthcare organizations must build a custom platform that caters to their unique data and analytics needs.
Here are some key factors that can affect the total cost of building a comprehensive platform.
The focus of a robust solution should be to facilitate the highest quality of care possible. It should not create any obstacles in care delivery by eating up valuable time and resources. The right solution must enable the health organizations to stay focused on doing what matters the most – taking care of patients and improving treatment outcomes.
Your technology is only as good as the data you feed into it. With Rishabh, you get access to experts who know how to use data in any form to generate result-oriented solutions.
We can help build a custom platform that is scalable, easy-to-use, secure and built to your specific health systems. We have assisted global healthcare organizations to develop solutions that simplify, scale & systematize better decisions right from data selection to evaluation and visualization.
We can help you build a powerful analytics platform that provides the insights needed to improve patient experience and fuel your growth