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There is a wealth of information available that healthcare organizations can leverage to streamline efficiency and revolutionize patient care — thanks to an abundance of raw data. The key is to collect and organize this data into an easy-to-interpret format and leverage it to improve current processes and procedures.
In particular, studying healthcare data analytics helps facilities identify where they can cut costs to improve their bottom lines. Keep reading to learn more about the positive financial impact of implementing and studying data analytics in your healthcare organization.
Explore how we can help you harness the power of data analytics in healthcare when you contact one of our consultants today.
Data analytics in healthcare is the act of compiling, categorizing and interpreting previously disorganized data to learn from and use it to optimize a healthcare organization’s operations and services. In short, it’s studying data-derived insights to improve operational efficiency and patient care. The most notable uses of data analytics in healthcare include:
Studying data-derived intelligence is helpful for every aspect of running a patient-centered, profitable healthcare facility. For example, healthcare practitioners can use data to spot trends that could cause re-admissions or assist in disease prevention. Plus, analyzing data could surge a facility’s bottom line by streamlining its operational efforts, like anticipating supply or staffing needs.
To study data, healthcare organizations first need special software to collect it and systems to compile it into easy-to-digest information. It’s also helpful to understand the different kinds of data analytics. Depending on an organization’s goals or pain points, one type of data analytics might be more beneficial to gather and study than another.
There are four main types of healthcare data analytics organizations can leverage:
There are several ways utilizing data analytics improves patient care and boosts an organization’s bottom line. Keep reading to learn how data analytics reduces healthcare costs.
Going paperless with digital medical records or Electronic Healthcare Records (EHR) boasts significant cost savings for healthcare facilities. EHRs are also superb for collecting real-time clinical, administrative and diagnostic information healthcare professionals can use to anticipate a patient’s needs and further personalize their care.
For example, EHRs can prompt practitioners and administrative staff to schedule reminders and medication orders or note patient preferences and trigger warnings, thus improving the patient experience. Plus, an EHR helps streamline time-consuming clerical tasks, like data access and entry. It has the potential to reduce errors and make information accessible from multiple facilities.
Supply chain breakdowns result in lost time and revenue, but they also affect patient care. Organizations can use data analytics to assess and anticipate their supply needs. Doing so optimizes inventory management for a smoother and better patient experience.
For example, data analytics highlights trends like shipment delays and order-to-delivery time frames. Analyzing supply chain disruptions or issues reduces the likelihood of overspending and streamlines inventory management, resulting in smarter spending and prompt care.
Unfortunately, data breaches and fraud claims are all too common in healthcare. Cybercriminals are known to target healthcare organizations for sensitive information. Cyberattacks were especially prevalent during the COVID-19 pandemic when healthcare professionals felt overwhelmed and burnt out.
The effects of data breaches are exceptionally costly for hospitals and other healthcare practices. To tackle cyberattacks and data breaches head-on, healthcare facilities can study data analytics to analyze the status quo and identify unexpected changes. For example, pinpointing suspicious events like surges in network traffic might indicate fraudulent activity.
An understaffed healthcare facility affects professionals and their patients. Thus, it’s crucial that an organization can anticipate staffing needs — especially during seasons when staffing might naturally fluctuate, like the holidays or flu season.
However, it’s tricky to distinguish between overstaffing and understaffing. Overstaffing leads to overspending and understaffing negatively impacts patient care. Studying historical staffing data and seeing how the seasons and other commonplace events affect it helps organizations hire and schedule the appropriate number of staff members during times of critical need.
Are you ready to use healthcare data analytics to improve your organization but don’t know where to begin? Consult our experts at Pathstone Partners! We’re a leading healthcare management consulting firm that collaborates with healthcare facilities to improve their financial and operational efficiency.
It’s our ultimate mission to empower practitioners to provide the best patient experience possible. Contact us today to learn more about how data analytics can transform the way you run your healthcare organization and provide patient care.
This article was authored by Yera Patel. Yera is a senior associate with expertise in performance improvement and non-labor cost reduction engagements at Pathstone Partners.
