Adopting data analytics across a healthcare organization will optimize clinician workflows in ways that also cut costs. Three focus areas to apply healthcare analytics are nurse data and chart abstraction, medication compliance, and automated communication alerts for patients
Download
Healthcare leaders inundated with clinical and financial challenges are deeply worried about the long-term viability of their hospital or health system operations, which compels many to invest in healthcare analytics. Some of the challenges include unpredictable cost increases, poor data quality, workforce shortages, persistent staff burnout, and inequitable care. With unique requirements for documentation, record-keeping, and patient communication, program compliance quickly comes into question due to time and resource constraints.
To conquer these obstacles, healthcare executives must strive for constant enhancement in clinical productivity by utilizing cutting-edge technology and collaborating with partners. However, given the many issues to tackle, it can be challenging to know where to begin.
The first step for healthcare executives is understanding the value of data analytics and how it can drive positive organizational change. They must also recognize that implementing new tools can be simple and easy. Many healthcare analytics solutions today can be layered onto legacy technologies and software.
With more modern healthcare analytics tools, healthcare leaders can glean valuable insights, make more informed decisions, and observe immediate results by harnessing the power of their data. These benefits have ripple effects throughout an organization and can improve productivity in three ways:
The healthcare industry is not immune to excessive workforce expenses related to high employee turnover. Manual efforts to retrieve, access, or utilize timely and accurate data contribute to the prevalent burnout and fatigue experienced by healthcare workers.
Fortunately, easier methods are available for extracting relevant data and information from records or patient charts. Indeed, data analytics tools in healthcare reduce manual tasks performed by registered nurse (RN) data abstractors, resulting in significant labor cost savings. Healthcare organizations can also expect an increase in the electronic capture of data elements for numerous measures, which enhances patient safety and care quality.
For instance, patients with complex care needs may require multiple medications to manage their condition. At the same time, providers are looking for ways to refine their medication management processes to better serve their patient populations. Therefore, by integrating refill management technology that includes automated medication compliance checkpoints, physicians and pharmacists can mitigate the risks associated with polypharmacy, such as drug-drug interactions and adherence challenges.
Prescription refill management technology brings efficiency and insights to provider workflows by linking relevant medication to a specific diagnosis during the patient encounter. Leveraging these technological solutions improves quality and compliance monitoring, adding transparency and accountability to the medication dispensing process. Process automation also lowers labor costs while optimizing the quality output of nurses and clinical care teams.
Quality performance programs require adherence to registry submission standards. Yet, some organizations are without the resources or technical ability to comply. Moreover, hiring additional team members to manage the data submission process is a tremendous expense that not all health systems can afford.
On the other hand, data analytics solutions can simplify registry data management for data collection, validation, and submission by automating these tasks using machine learning techniques. This software is attractive for health systems committed to lean principles. Data analytics solutions can extract relevant data and information from records or patient charts so that participation in the quality improvement program isn’t contingent on investing additional resources. With the sophistication of a clinical registry, therefore, healthcare providers improve productivity and performance while reducing the data abstraction burden.
As technology advances, patients anticipate the same level of technological innovation in healthcare, similar to expecting high-speed internet and streaming capabilities in their homes; it’s become a basic necessity. As such, patients desire and expect increased communication with their providers. Greater accessibility to a clinical team through text and mobile communication connects patients to care without requiring them to leave home.
For that reason, many medical institutions have adopted automated patient engagement in the form of secure, text-based communication. This capability simplifies patient outreach and reduces the burden of follow-up calls, visit scheduling, and lab test reminders for providers and staff. As a result, automated patient engagement has been shown to:
Challenges within the healthcare industry will continue as new obstacles emerge for health systems to deliver high-value, affordable care. Organizations can accelerate their improvement of clinical and financial outcomes by embracing data analytics solutions, which foster innovation, adaptability, and a commitment to ongoing quality improvements.
Hospitals and health systems that incorporate analytics technologies into their operations will establish themselves as a dependable partner in care delivery that meets the diverse needs of their patients and communities.
Would you like to learn more about this topic? Here are some articles we suggest:
