With the constantly increasing number of data sources and the complexity of data generated within healthcare organizations, the need for advanced analytics to support decision-making capabilities is growing. Hospitals and other healthcare organizations require predictive modeling and data visualization tools from modern business intelligence software applications to gain insights regarding patient care and satisfaction, labor distribution, clinical operations, daily practices of physician and nurses, and administration and management.
Elevating care throughout all departments and becoming a value-based organization can only be achieved through the intelligent application of data-derived insights obtained thanks to comprehensive, advanced BI software.
Why Does Healthcare Needs Business Intelligence?
Improving patient care
According to Gartner’s report, “most vendors working in healthcare and other industries observe that healthcare has the most complex data of any industry” and the lack of a BI strategy is a “flaw in business operations improvement (BOI)” in healthcare.
Healthcare is increasingly dependent on digital technology to support the operations of a functioning healthcare system. Hospitals and other healthcare organizations need an environment that supports the daily practices of physicians, administration, and all other healthcare personnel.
Business Intelligence for healthcare is critical to managing the massive amounts of both structured and unstructured data that healthcare institutions deal with daily.
Allocating expenses better
For healthcare organizations to address operational, financial, patient care, and clinical practices most effectively, they must implement business intelligence platforms that allow them to make the most of their analytical capabilities and address core challenges within the industry.
Predictive modeling and data visualization are key components in selecting the right healthcare analytics software for your hospital or healthcare organization. When BI users can easily understand healthcare information, apply insights towards addressing risks, forecast future events, and answer vital areas of care, management, and operation, chances for successful application of analytics-based insights are increased. The numerous examples of big data in healthcare illustrate it every day.
Providing better patient and clinical care, improving personnel distribution, decreasing readmissions, and managing expenses require the smart application of business intelligence in healthcare. The true value for healthcare stems from providing the best level of care for patients based on well-analyzed data.
Utilizing a BI software is part of the growth process for the healthcare industry, and will enable hospitals and other organizations to establish best practices across all elements of care and management.
Supporting and improving decision-making
Healthcare administrators and managers face specific issues related to system operations, equipment and facilities, diagnostics, patient and clinical care, and physician practices, all of which requires efficient coordination.
Healthcare organizations need the support of a BI software to navigate the complexities of healthcare governance. Additionally, advanced analytical capabilities are necessary to solving key challenges and connecting patient, clinical, and operational data. BI software allow administrators to track Key Performance Indicators (KPIs) that analyze, manage, and help healthcare organizations adapt their performance based on accurate data and analytics-based insights.
Deriving value from healthcare data, and connecting all of the varied data sources to obtain patient-related insights is crucial to providing elevated care. Streamlined, simple, and efficient business intelligence for healthcare dashboards are also key to helping hospitals and other healthcare organizations leverage their data most effectively.
Healthcare Metrics For Saving Life And Money
Healthcare KPIs provide dependable insights that can be analyzed and utilized for fast, intelligent decision-making capabilities.
The following KPIs can be measured utilizing a Hospital Performance Dashboard, which provide actionable data regarding clinical, financial, and operational aspects, and represent examples of business intelligence in healthcare:
Average hospital stay
- Measures the average time spent by patients accepted into healthcare facilities.
- Though this is a generalized KPI, it can indicate widespread numbers given the nature of the type of stay.
- For this example, a lung transplant surgery or cardiothoracic surgery will increase figures, where an outpatient surgery, such as wisdom teeth removal, will decrease the figures.
- Healthcare organizations can set a target length of stay based upon KPI evaluations.
- Ideal for financial management, healthcare institutions can track metrics that directly affect finances and the ability of the organization to sustain itself over time.
- Helps to identify irregularities in expense, take swift action, and ensure that the budget is applied where it’s more effective.
- Various categories include per units, per operations, or per age groups.
- Treatment costs can be calculated according to certain times and the evolution can then be analyzed.
Hospital readmission rates
- Measures the number of patients who are readmitted into hospital care shortly after their initial release from care.
- Provides critical insight regarding the level of care patients receive while in treatment at a healthcare facility.
- Helps healthcare organizations identify certain flaws in healthcare management practices, such as insufficient staff, lack of materials, or areas with special needs.
The following KPIs can be measured by using a Patient Satisfaction Dashboard, which provides data regarding patient and clinical care, and are further examples of business intelligence in healthcare:
Patient wait time
- Patient contentment is directly linked to their wait time at a healthcare facility, and this measures how long a patient has to wait between the time they check into a facility and the time they see a doctor.
- It offers insights into how quickly hospitals and other healthcare organizations are able to provide care.
- Measuring over a period of time enables facilities to identify trends and apply labor distribution towards providing more efficient patient management.
- One of the most crucial factors in healthcare management, this measures how patients feel about how they’re cared for while being treated at a facility, how well they like the food or personnel, and if they feel doctors and nurses take the appropriate time to discuss their care.
- Patient satisfaction levels should be constantly monitored so it can be addressed and improved where needed.
- Provides insights into how a healthcare facility is viewed by patients.
- Measures the ability of a hospital to extend high-quality care to patients and ensure that they’re safe from exposure to new infections or sepsis, or post-op complications.
- Helps healthcare organizations figure out exactly where problems originate and make necessary improvements.
- Metrics can be categorized by various categories such as post-op infections or treatment-based diseases.
ER wait time
- Closely tied to Patient Wait Time, this KPI factors in time specifically related to the Emergency Room.
- Provides insights into rush hours and busy days, average patient wait time in the ER and allows healthcare organizations to evaluate if their check-in process needs updating or if their staff is overwhelmed.
- This KPI is important to keep checking as improvements often need to be made on an on-going process.
Business Intelligence In Healthcare: Advanced Analytics Applications
With advanced analytics, business questions have evolved from “what happened” to “why” and “what will happen in the future”. They give healthcare institutions the power to ask important questions about the future, and not simply rely on historical data to inform their decision-making – and this is enabled by the application of business intelligence in healthcare.
Having foresight enables healthcare management to take preventative, proactive steps towards providing the best care for patients, and ensuring that all levels and elements of their facility are able to effectively deliver high-quality treatment and care.
For example, readmissions are particularly expensive and actually preventable to a certain degree. The Affordable Healthcare Act, implemented in 2012, created the Hospital Readmissions Reduction Program that took effect in 2013. It gave hospitals incentives to take steps to reduce patient readmissions. Those hospitals with higher than average readmission rates face financial penalties.
With this in mind, hospitals need to ensure that they’re evaluating their Patient Readmission figures and obtaining accurate insights that can be utilized to address necessary improvements.
BI software give hospitals the tools they need to make accurate predictions regarding potential patient readmissions:
- High-risk patients can be identified based on various factors like social or clinical metrics and receive extra attention or care prior to leaving a facility.
- Patients who have received surgical care can be assessed for potential readmission based on factors such as post-surgical non-absorption rates, age, and pre-existing conditions.
Examples of business intelligence in healthcare
The following examples indicate successful applications, built on a foundation of advanced analytical capabilities, in the healthcare industry:
- UnityPoint Health in Iowa: managed to reduce their risk-adjusted readmission rate by 40% over the course of three years in one of their pilot hospitals by utilizing predictive modeling via Business Intelligence software.
- Washington State Health Care Authority: reduced unnecessary ER visits by implementing a Business Intelligence for healthcare system to electronically integrate and distribute patient data across ER departments. Hospitals were able to identify patients who visited more frequently than others and share that patient’s information with other hospitals. This resulted in an overall reduction of frequent ER visits by 10%, a decrease in visits by frequent ER patients by 10.7%, and scheduled prescription allocation decreased by 24%.
Predictive analytics is key to enabling hospitals to properly manage their readmission rates and sidestep costly penalties while simultaneously addressing important aspects of patient treatment and care.
Data Visualization Helping Healthcare Professionals
Data visualization enables hospitals to better interpret, describe, and apply information that’s contained within their data, essentially creating a complete visual of healthcare information using visuals.
Healthcare data is high-stakes data, as it encompasses people and factors that are crucial to life and death. BI software, quite simply, must be readable and understandable, not only for IT and analysts but for all users. Hospitals can more accurately understand abstract, complex data and identify patterns and trends within data by seeing it depicted in easily interpreted forms, like graphs. Furthermore, it enables the user to see their data as an easily comprehensible story.
Data visualization requires a precise approach, combined with advanced techniques and tools, and clinical and business resources. The interpretation and analysis of complex patient and clinical data, finances, and business information give healthcare institutions insights that can be presented to doctors and nurses, administrators, management, and other sources.
Sanket Shah, Director of Client Management at Blue Health Intelligence, an independent branch of the Blue Cross Blue Shield Association recently stated that “you can only get those answers… and you can only understand it [data] when it’s presented in a human-readable way,” and that “unless you’re a highly trained data analyst, a (sic) visualization is the best way to make data comprehensible to the end user”.
Data analysis tools can help healthcare organizations better address issues related to the management of their facilities and the operations surrounding patient and clinical care.
Examples of data visualization applications in healthcare
NYU Langone Medical Center and the National Resource Networks created a City Health Dashboard to identify public health needs on a neighborhood level, which gives healthcare organizations critical information about social determinants and health behaviors, including smoking rates, opioid-related deaths, housing affordability, poverty rates, environment, and unemployment levels. All of which affects hospital practices and care. Users can even compare metrics like accessible preventive health services and the number of residents with mental health conditions.
Oslo University Hospital is utilizing data visualization to collect radiology data from across departments to enhance their ability to offer real-time education and collaboration, built on a foundation of actionable insights, within their facility.
With the sheer amount of data being generated by hospitals and healthcare organizations daily, having advanced tools in place is a vital asset to making the most of the healthcare-related data.
Implementing Business Intelligence In Healthcare
Implementing the right BI reporting tools can increase performance across departments, including financial, patient care, administration, labor, and give healthcare organization the tools and advanced analytics capabilities they need to establish best practices and effectively address patient care.
The healthcare industry needs agile, fast, responsive, and interactive BI software to maximize the value of their data and support critical areas of decision making. Having the ability to accurately analyze data related to new patient acquisition, patient safety, readmissions, hospital-acquired conditions, and patient willingness to recommend, can drive performance across all departments.
Basically, business intelligence in healthcare allows organizations to build a reputation around patient and clinical care, create a solid foundation built on insights, better address patient concerns, and drive collaboration throughout all departments.
datapine’s healthcare analytics offers hospitals and healthcare organizations the right tools to support their advanced analytics needs, easily interpret complex data sets, and drive business value.
Being data-driven is integral to success in a modern digital world, and healthcare organizations must implement the advanced analytical tools needed to ensure that effective, quality patient care is always at the forefront of their practices.
See how it can help your healthcare organization with datapine’s 14-day free trial!