Worklist Prioritization The Critical Element in Today CDI Operations

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Information about Worklist Prioritization The Critical Element in Today CDI Operations
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Published on November 21, 2019

Author: ezDIinc

Source: authorstream.com

slide 1: https://www.ezdi.com/ slide 2: • The past few years have been transformative for healthcare in the truest sense. From the rise of virtual care to big techs crafting innovative care delivery models the healthcare industry has been witnessing some interesting shifts. • Prodded by new programs and practices the shift from fee- for-service reimbursement to value-based care has resulted in improved outcomes for patients providers and payers alike. slide 3: • There’s no denying – the opportunity to enhance patient outcomes while reducing cost is driving the industry forward and instigating healthcare providers to modernize legacy practices. • The push for improved performance and financial health however is also putting clinical documentation improvement CDI programs under intense pressure to ensure accurate documentation rightly that justifies medical necessity. slide 4: • The situation has influenced healthcare providers to redesign their CDI programs by implementing new methodologies and technologies that can help them prioritize workflows and focus closely on cases that have greatest quality and financial impact. • Worklist prioritization is a critical objective for healthcare providers especially at a time when the importance of CDI is growing fast. slide 5: • Accurately capturing and documenting the patient conditions require dedicated clinical documentation improvement specialists CDIS with coding and clinical knowledge. • Additionally hospitals need to implement a process that enables detailed evaluation of patient reports on a regular basis. Prioritization – Why is it Challenging Healthcare Providers slide 6: • With new documentation and clinical evidence being added every hour regular evaluation of the data is required to ensure that the medical records are thorough and accurate. • In order to achieve this goal the majority of CDI programs will have to increase the number of employees involved. Unfortunately most healthcare providers lack the necessary resources or budget to train a large pool of staff. slide 7: • To enhance the existing staff’s capability in identifying records that require improvement CDI programs often implement several methods to classify a specific set of records to evaluate every day. • There are programs that even attempt to prioritize worklists on the basis of clinical experience. slide 8: • In this case specialists end up guesstimating the records that are likely to have documentation integrity concerns. • Their decisions are often based on factors such as length of stay LOS chief complaint list of providers with the past record of poor documentation habits and so on. slide 9: • A solution that accurately identifies the discrepancies between clinical evidence and documentation would effectively address documentation prioritization issues. Doing so however requires additional focus on separate clinical data to identify probable conditions. • While rule-based methods have already been attempted to simplify the process of extracting the right data they often suffer from the false-positive/negative dilemma. Thankfully cognitive technologies such as artificial intelligence provide CDI specialists a solution to this problem. How can Technology Create a Difference slide 10: • For instance machine learning algorithms can analyze real- time patient data to accurately predict potential medical conditions. By identifying gaps between documentation and clinical evidence ML can create a catalog of prioritized patient records for CDI staff to evaluate. With this approach CDI specialists can address some of the most pressing documentation concerns. Halifax Regional Medical Center’s HRMC initiative to improve its financials with an AI-based Clinical Documentation Improvement software serves as an excellent example in this regard. slide 11: • Another critical issue was the encoder which wasn’t ICD-10- ready. As a result the teams were experiencing issues with encoder speed and responsiveness unnecessary downtime and connectivity issues between the EHR and the encoder. • In order to resolve the issues Halifax collaborated with ezDI to deploy our full suite of NLP-technologies including total coding workflow automation with ezDI’s integrated computer-assisted coding application CAC. slide 12: • To learn more about ezDI’s AI-based mid-revenue cycle management solutions visit www.ezDI.com and see the live product demo of our Clinical Documentation Coding Compliance/Auditing Quality Measures Encoder and Enterprise Analytics request a live demo. slide 13: Contact us Visit Our Website:- https://www.ezdi.com/ Phone no:- 8866408081 Address:- 12806 Townepark Way Louisville Kentucky 40243

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