Optimizing Coder and CDIS Productivity & Accuracy Using Prescriptive Analytics

The global healthcare industry is transitioning from a volume-based to a value-based business on a large scale. With an increased demand for quality healthcare, healthcare providers need to deliver better outcomes. Prescriptive analytics allow healthcare authorities to optimize business outcomes through the best course of action for providers and patients.

Prescriptive Analytics and Healthcare

Prescriptive analytics is a form of data analytics that proposes possible solutions to complex problems. It analyzes real-time and historical data, making compelling predictions using data modeling, data mining, and artificial intelligence. It allows healthcare businesses to evaluate multiple “what-if” scenarios and selects the best solution for the patient.

Prescriptive analytics ensures that multiple variables, such as treatment plans, patient mix, and resources, are considered when making decisions. They establish clearly defined objectives and improve the healthcare organization’s ability to achieve each. Healthcare prescriptive analytics play a vital role in enhancing performance and productivity of coding and Clinical Documentation Improvement Systems (CDIS).

How can Prescriptive Analytics improve coding productivity?

The significance of complete and accurate coding in health systems cannot be stressed enough. The use of compliant coding procedures ensures that the reporting scores of new and developing health systems are optimized. Productivity and quality are the two key indicators of coder performance.

Health Information Management (HIM) officials have successfully used coder performance to suggest process improvement methods. Advances in prescriptive analytics provide healthcare professionals with new opportunities to gain valuable insights and improve business processes.

HIM managers can use predictive analytics tools to analyze, visualize, and influence real-time coder performance. By leveraging intuitive real-time reporting dashboards, they can record coder output, conduct cause-and-effect analyses, and spot improvement opportunities. Reports can display primary metrics such as length of patient stay, time for service, physician performance, patient satisfaction, and the number of outpatients. Trends can be identified and compared with competitors, and crucial data-driven decisions can be made.

Prescriptive analytics reports can highlight the corrective actions required to improve coder performance. They also reveal whether HIM professionals adhere to the guidelines listed in the CDIS.

Companies can accurately measure and monitor coding productivity by implementing prescriptive analytics in healthcare. The primary step to coding optimization is measurement. Knowing what to expect in terms of productivity can help the company focus on areas of improvement.

Optimizing CDIS through Prescriptive Analytics

CDIS remains a top priority for most healthcare facilities. Better documentation equates to value-based care, higher quality, fewer risks, and faster reimbursements.

Prescriptive analytics makes certain that clinical documentation is complete, relevant, accurate, and compliant with all regulations.

Clinical Documentation Improvement (CDI) programs are typically focused on in-patient settings, but as more physicians become affiliated with hospitals, demand for outpatient CDI is continuing to increase.

Prescriptive data analytics in CDIS ensures the following:

• Guidelines are in place for HIM professionals to manage, produce, store and analyze healthcare data.
• An informative governance framework is established to make certain that the clinical documentation will meet the HIM goals.
• Healthcare organizations are following principles concerning data integrity, privacy, security, and staff accountability.

Prescriptive analytics in healthcare can drive better decision-making and identify any complications before impacting critical processes if built on a solid foundation of accurate and detailed documentation.

By providing accurate and complete diagnosis capture, proper review of medical records, computation of payments, review of professional services, ambulance, and physician clinics, a robust CDIS can improve outpatient outcomes.

Infusing CDIS into ICD-10 must be a continuous process to ensure the quality of delivery. This will provide better opportunities for data integrity and information management. Prescriptive analytics can drive the success of CDIS management even when clinical and financial constraints are present.

Prescriptive Analytics: The Future of Healthcare

Prescriptive analytics is the future of healthcare as it offers the power to identify interventions and critical risks. Critical healthcare decisions cannot depend on simplistic tools but on real-time data analytics that enables transparent and proof-based decisions. Prescriptive analytics' decision optimization feature is essential in managing the uncertainties of the evolving health sector and improving patient outcomes.

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