Optimizing Coder and CDIS productivity & accuracy using prescriptive analytics

Optimizing Coder and CDIS productivity & accuracy using prescriptive analytics

The global healthcare industry is undergoing a large scale transformation from a volume based to a value based business. With increase in demand for quality healthcare, healthcare providers need to deliver better outcomes. Prescriptive analytics enables healthcare authorities to optimize business outcomes through the best course of action for providers and patients.

Prescriptive Analytics and Healthcare

Prescriptive analytics is a branch of data analytics that focuses on recommending possible solutions to a complex problem. It leverages data modeling, data mining and artificial intelligence to assess real-time and historic data and make effective predictions. It enables healthcare businesses to compare multiple “what-if” options and choose the best solution for the patient.

Prescriptive analytics ensure that decision making includes multiple variables such as treatment plans, patient mix, resources and so on. They lay down clearly defined objectives and enhance the healthcare firm’s ability to maximize each objective.  Prescriptive analytics plays a vital role in enhancing coder performance CDI productivity. 

How can Prescriptive Analytics improve coding productivity?

The significance of complete and accurate coding in health systems cannot be stressed enough. Compliant coding procedures ensure that the new and developing health systems receive optimized reporting scores. Productivity and quality are the 2 key indicators of coder performance. 

Health Information Management (HIM) officials have successfully used coder performance to suggest process improvement methods. Advances in prescriptive analytics are opening new doors for healthcare professionals to gain valuable insights and scope for business process improvements.

Prescriptive analytics tools assist HIM managers analyze, visualize, and influence real-time coder performance. The tool’s dashboard feature helps them monitor coder output, perform cause-effect analysis, and recognize opportunities for enhancement. Primary metrics such as length of patient stay, time for service, physician performance, patient satisfaction, number of out-patients can be viewed on the dashboard. Trends can be identified, compared with competitors and crucial data driven decisions can be taken.

Prescriptive analytics reports can point out the corrective actions that need to be taken to enhance coder performance. Reports also give useful insights on whether HIM professionals are adhering to the guidelines listed in the Clinical Documentation Improvement Systems. 

 By implementing prescriptive analytics, companies can effectively measure and monitor coding productivity. Measurement is the primary step to coding optimization. Understanding the expected productivity can help the business to focus on areas of improvement. 

Optimizing CDIS through Prescriptive Analytics

Clinical Documentation Improvement Systems remains a top priority for most healthcare facilities. Better documentation means value-based care, higher quality, lower risks, and quicker reimbursements.

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

Typically, CDI programs focus on in-patient settings but as more physicians become associated with hospitals, there is growing demand for outpatient CDI as well. 

Prescriptive data analytics in CDIS ensures the following:

  • Guidelines are set for HIM professionals to manage, produce, store, and analyze healthcare data.
  • An informative governance framework is established to ensure that the clinical documentation will meet the HIM goals.
  • Principles are being followed by healthcare organizations with respect to data integrity, privacy, security, and staff accountability.

With a strong foundation of accurate and detailed documentation, prescriptive analytics can drive better decision making and identify any complications before they impact critical processes.  

A solid CDIS can enhance better outcomes for out-patients by providing accurate and complete capture of diagnosis, proper review of medical records, computation of payments, review of professional services, ambulance, and physician clinics.

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

Prescriptive Analytics-The Future of Healthcare

Prescriptive analytics is clearly the future of healthcare as it provides the power to influence the outcomes. Healthcare providers can get a holistic view of their patients, identify interventions and key risks. Critical healthcare decisions cannot rely on simplistic tools but rely on real-time data analytics that enable decisions to be transparent and proof-based. The decision optimization feature of prescriptive analytics plays a critical role in managing the uncertainties of the evolving health sector and enhancing patient outcomes.  



By designing a next-generation clinical NLP engine supporting advanced documentation and coding functions, EZDI turned their vision to reality. Their CAC and CDI solutions received tremendous feedback, providing system accuracy and ease of use. EZDI removes the data complexity and highlights what matters for healthcare professionals.

EZDI is a provider of AI-based mid-revenue cycle management solutions to Hospitals and Health Systems.

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