Healthcare organizations are responsible for massive volumes of highly sensitive data. Although managing this data may pose a challenge, gathering insights from it can be incredibly beneficial.
Establishing a data-driven culture within a healthcare organization promises significant benefits ranging from improved patient treatment to faster diagnosis.
Everything you need to know about Healthcare Data Analytics:
- What is Data Analytics?
- Types of Data Analytics
- 6 Benefits of Data Analytics in the Healthcare Industry
- Risks of Healthcare Data Analytics
- Leverage the Full Value of Your Healthcare Data
What is Data Analytics?
Data analytics is the ability to leverage an organization’s data to help them gain deeper insights and enhanced decision-making capabilities. It helps organizations be more agile and proactive, ultimately gaining a competitive edge in the market.
How is Data Analytics Used in Healthcare Settings?
Healthcare organizations use data analytics to detect diseases earlier and more accurately, identify and address inefficiencies within a practice, identify healthcare issues within a community and establish appropriate preventative care initiatives, personalize patient care, and more.
Types of Data Analytics
There are four main types of data analysis:
- Descriptive analysis: Focuses on past events, leveraging historical data to identify trends and relationships.
- Predictive analysis: Uses data, modeling, and machine learning (ML) to analyze current and historical data to make predictions about future outcomes.
- Diagnostic analysis: Examines data to determine the causes of trends and relationships, answering the question, “Why did this happen?” This is particularly relevant in the healthcare industry when diagnosing a patient with a certain injury or illness based on the symptoms they are exhibiting.
- Prescriptive analysis: Analyzes data to provide recommendations on the best course of action to achieve a desired outcome. In healthcare, this may look like analyzing a patient’s current condition along with relevant risks to identify and implement specific treatment plans.
6 Benefits of Data Analytics in Healthcare
The greatest benefits healthcare organizations can realize from leveraging data analytics are:
- Improved patient care
- More accurate and quicker diagnoses
- Empowered decision making
- Greater operational efficiency
- Improved staffing
- Greater insights into public health
Improved patient care
Healthcare organizations strive to treat patients as effectively as possible while minimizing the trauma and risk associated with their treatment. To achieve this objective, it’s important for organizations to continuously develop, test, and implement improvements to their processes and services.
Healthcare providers can analyze data like patient temperature, blood test results, and blood sugar levels to improve patient care. They can also analyze qualitative data, such as a patient’s energy levels, mood, level of pain they report experiencing, and how well they can complete day-to-day activities.
By tracking and analyzing patient data, healthcare providers can:
- Better identify at-risk populations
- Reduce errors in diagnosis and treatment
- Determine which treatments are most effective
- Lower readmission rates
- Determine how long patients need to be in care
More accurate and quicker diagnoses
Artificial intelligence (AI) and machine learning (ML) can use patient data to predict the most likely diagnosis, eliminating unnecessary testing and increasing the speed at which patients can start receiving treatment.
For example, AI and ML have been used to sample radiology images and classify disease and damage to soft and hard tissue, then to triage, diagnose, and recommend appropriate treatments based on that analysis.
Diagnostic tests with ML and AI capabilities are extremely beneficial in reducing the burden on doctors and specialists, leading to faster assessments and treatments at a better cost value for patients.
Empowered decision making
Data analytics gives providers insights into the most effective treatments, trends and patterns that indicate certain conditions, common risk factors to be aware of, and more.
When your healthcare workers are empowered by the right data to inform their decisions and approaches, it enables them to provide the best treatment for their patients, enhancing the quality of patient care.
Greater operational efficiency
Studies estimate that approximately 25% of total healthcare spending in the U.S. is waste, and implementing measures to reduce waste could save between $191 and $286 billion across the industry.
Data analytics enables your organization to assess its current conditions, structure, and processes to identify areas for improvement.
Areas in which healthcare organizations can enhance their operational efficiencies are:
- Applying analytics techniques to better manage the demand for healthcare resources such as hospital beds, ultimately increasing hospital capacity
- Measuring, understanding, and improving the use of healthcare technologies to improve cost-efficiency
- Addressing factors that contribute to waste, including inappropriate care, preventable care-related injury and death, variations in clinical practices, and failure to follow proven procedures
- Focusing on the areas that can realize the greatest improvement from increased efficiency, including employee scheduling, administration, charting, financial management, and compliance
Improved staffing
Labor accounts for approximately 60% of hospital costs. Data analytics in clinical settings can be used to forecast staffing requirements and optimize inpatient staffing.
AI can also be used for lower-value, time-intensive tasks like collecting insurance information and symptoms, reminding patients of prescription refills and follow-up appointments, entering and analyzing data, and collecting payments.
These improvements streamline and optimize patient care, reduce labor costs, and improve employee satisfaction.
Greater insights into public health
Data analytics can be used to identify and predict trends in public health and in the spread of illnesses, such as the flu and COVID-19.
Leveraging this historic and current data to predict spikes in cases can ensure your healthcare organization has the necessary supplies and equipment ready to treat the increasing number of patients.
This enables your organization to be proactive, not reactive, in treating and supporting your community.
Risks of Healthcare Data Analytics
Leveraging data analytics in the healthcare industry can enable your organization to realize significant benefits, but hosting this data also comes with risk and responsibility.
Healthcare organizations house extremely sensitive data, including patients’ medical history, insurance information, Social Security numbers, credit card and billing information, and diagnosis data.
This makes these organizations a frequent target of cyber-attacks; in fact, the FBI’s Internet Crime Report found that the healthcare industry faced more ransomware attacks than any other critical infrastructure sector.
It’s vital to ensure you have a strong data governance program in place to support your data analytics strategy and practices, protect your data, and comply with regulations like HIPAA.
Leverage the Full Value of Your Healthcare Data
When you look to turn insights into action, it’s helpful to have experts in your corner.
At AIM Consulting, we leverage proven analytics methodologies, best practices, and tools to define the right analytics solutions for your healthcare organization’s needs, solving complex business challenges and driving future growth.
Our high-performing teams are ready to deliver a custom-fit data analytics solution that will enable you to empower your providers with the right information, increase your organization’s efficiency, and improve the treatment of your patients.
Need Help Creating Impact from Insightful Data?
We help companies strategize, design, build and operationalize data and analytical platforms through our high-performing teams of data engineers, architects, data scientists, and analysts.
