Digitizing patient records can significantly simplify the provision of quality healthcare. Managed analytics service providers are essential in helping hospitals glean actionable insights in real time. Here, we will explore the ways managed analytics can enhance patient outcomes.
In recent years, the healthcare sector has increasingly embraced a data-driven approach. The Covid-19 pandemic compelled many hospitals and healthcare facilities to modernize their technology and systems. As a result, the demand for managed analytics services has surged in the industry. Healthcare institutions are collaborating with data analytics firms to implement and tailor analytical models that enable them to make informed decisions based on real-time data.
According to Mordor Intelligence, the global healthcare analytics market is anticipated to reach $37.83 billion in 2023, with projections of $106.16 billion by 2028, growing at a compound annual growth rate (CAGR) of 22.92%. The report indicates that the predictive analytics sector will see the highest growth during the forecast period.
Additionally, a study by Global Market Insights reveals that financial management, clinical management, and population health management are the three primary application areas within the healthcare analytics market.
In this concise guide, we will delve deeper into managed analytics services in healthcare and their necessity in the current landscape.
What are Managed Analytics Services?
Managed analytics services refer to third-party (nearshore, onshore, and offshore) solutions provided by data analytics and artificial intelligence firms that assist hospitals in optimizing workflows, enhancing patient care, and increasing overall efficiency. These services encompass a variety of activities, such as data warehousing, data analytics, business intelligence, data visualization, big data analytics, data governance, and ongoing maintenance.
In simple terms, third-party managed analytics companies implement a data-driven model within healthcare facilities and create customized dashboards to present real-time reports to staff and medical professionals. These companies can also deliver data maintenance and embedded analytics services, with the IT framework handled by the service provider. The hospitals then receive these reports for effective decision-making.
What is Healthcare Analytics Management?
Healthcare analytics involves utilizing data along with statistical techniques and tools to transform raw data into valuable insights that drive better decision-making. The data primarily originates from the healthcare sector and provides crucial information for hospitals and doctors. Healthcare analytics serves as a potent tool to fully capitalize on patient data, uncover hidden trends and patterns, identify correlations, and ultimately enhance patient care.
Healthcare Analytics as a Service (HAaaS) is on the rise, with more hospitals opting for cloud-based third-party analytical solutions for managing clinical operations. The entire process can be outlined as follows:
Data collection
Data management
Data analysis
Data visualization and reporting
Data governance
System monitoring
System maintenance and upgrades
Data intelligence management is an ongoing process where new data is continually integrated into the database, cleaned, formatted, and analyzed to derive actionable insights. This enables healthcare centers to offer superior services to patients while alleviating demands on medical staff. Common offerings in healthcare managed analytics include data mining, developing predictive models, and automating reports.
What are the Three Varieties of Analytics Utilized in Healthcare?
Healthcare analytics encompasses a broad spectrum of processes and solutions, which can be classified into the following three categories:
Clinical Analytics
Focused on patient care, clinical analytics leverages data from electronic health records (EHR) to forecast future health issues for patients based on their medical histories. For instance, hospitals can monitor patients with serious conditions like heart attacks, cancers, or organ failures, allowing healthcare providers to intervene promptly if a patient's condition declines. This proactive approach can save lives.
Financial Analytics
Financial analytics examines the economic impact of treatments on patients. Variables such as surgery costs, insurance coverage, and medication expenses are calculated for each patient to aid them in managing their treatment expenses effectively. For instance, the financial requirements for a patient with Medicare will differ from those without such coverage. Understanding the overall cost assists patients in planning their budgets better.
Outcomes Research
Outcomes research evaluates potential results in the healthcare domain, including mortality rates, length of hospital stays, and readmission rates. This data-driven approach enables hospital management to refine treatment protocols to become more patient-oriented. For example, more effective management of hospital beds, ICU rooms, and patient monitoring can ensure that patients receive necessary resources without delay.
Healthcare data analytics consulting firms establish an automated analytics lifecycle that ensures relevant reports are consistently available to the appropriate stakeholders, minimizing the risks of mismanagement and miscommunication.
What is Data Analytics in Healthcare?
Data analytics extends beyond mere dataset analysis; it encompasses the overall data framework and how models are deployed to extract insights from vast amounts of information. In healthcare, delivering real-time analytic insights to decision-makers promotes transparency, efficiency, and cost savings without compromising the quality of patient care.
Managed predictive modeling analyzes historical and real-time datasets to identify future trends and outcomes. For instance, evaluating patient behavioral data can help manage visit timings and medication schedules. Historical and current information from cancer patients can indicate risks related to disease progression, while monitoring previously admitted patients for self-harm can reduce the likelihood of recurrence.
Advantages of Healthcare Analytics
Improved operational efficiency
Enhanced transparency
Cost reduction
Immediate access to patient records
Enhanced patient care
Improved collaboration
Quicker decision-making
Increased time with healthcare providers
Ensured data security and privacy
Applications of Healthcare Data Analytics
Managed analytics services find various applications in health systems, optimizing hospital operational efficiency while conserving time and resources across multiple domains.
Strategic Planning
Data science managed services are essential for healthcare facilities to develop strategic decisions regarding treatment opportunities, patient record management, and admission processes. It aids in tracking resource availability, the number of waiting patients, the list of available healthcare providers, potential emergency cases, and more. By preparing for crises, hospitals can build patient trust and satisfaction.
Staffing Management
Staffing shortages pose a significant challenge within the healthcare sector. Nurses endure extended shifts, leading to fatigue. While hiring additional personnel can inflate labor costs, hiring fewer staff can impede efficiency and elevate risks. Data analytics can help address this dilemma by enabling effective hospital staff management. Reports generated by analytical systems help inform decisions regarding working hours, staff rotations, part-time employees, interns, and volunteers.
Fraud Detection
Detecting fraudulent activities is yet another argument for employing data analytics consulting in healthcare. Insurance claims frequently encounter fraudulent practices. Hospital personnel devote extensive hours processing these claims and coordinating with insurance companies and patients. By incorporating data analytics, the risk of fraudulent claims can be mitigated by alerting hospital staff to potential risks before they arise, through pattern detection and identifying vulnerabilities.
Medical Logistics and Distribution
Medical logistics involve all entities required for patient care, such as hospitals, pharmaceutical companies, suppliers, and more. Delays in supply deliveries can have dire consequences. For example, a patient in need of urgent blood transfusion due to severe injuries cannot afford any delay in locating necessary supplies. Data analytics reports offer real-time inventory statuses in hospitals, signaling when to restock supplies.
Electronic Health Records
Possibly the most significant application of managed analytics solutions in healthcare is the efficient organization of electronic health records (EHRs). These digital records must be accessible whenever a physician requires them to discuss a patient's condition. Critical data-such as the patient’s age, gender, lab results, medications, concerns, and allergies-equips doctors with the essential information needed for accurate diagnosis and effective treatment plans. This capability helps avoid prescribing medications that could trigger allergies and facilitates timely outreach for annual check-ups.
Conclusion
Managed analytics in healthcare is essential for hospitals aiming to enhance efficiency and elevate patient care standards. The sector should leverage data's power to make swift, informed decisions. From fraud detection to efficient patient management and cost reduction, managed analytics service providers can significantly impact the healthcare field.
Consulting firms further enhance system scalability and agility, simplifying the integration of cutting-edge technologies and transformation of services and care delivery. By implementing healthcare managed analytics services, patient well-being can be substantially improved.
