Zero Work to Predict Final DRGs

Working diagnosis-related group (DRGs) are utilized for a variety of functions across healthcare organizations, including case management, finance, and care coordination. In particular, working DRGs contribute to many system-wide forecasts, so accuracy is vital. This necessity is increasingly apparent during times of high uncertainty when the margin for error is even more slim than usual.

Today, the responsibility for generating concurrent working DRGs typically falls on CDI teams. This increases their already over-burdened workload and makes it difficult, if not impossible, for each patient to be assigned a working DRG. As a result, opportunity for DRG assignment and/or correction is often missed, decreasing the accuracy of both the overall clinical picture and DRG-based predictions.

Enter Forecast™, a fully-automated, clinically-driven module that assigns a final DRG prediction for every patient record, early in each patient stay, effectively obsoleting conventional working DRGs. Powered by the Iodine CognitiveMLTM Engine, Forecast automatically and concurrently predicts MS-DRGs for all inpatients based on the available patient record, including the clinical data and electronic documentation, even if no prior manual review has been performed.

In addition, geometric mean length of stay (GMLOS), relative weight, and other associated DRG information is included for each forecasted MS-DRG. This data can be leveraged for discharge planning, resource utilization, early identification of bundle DRG cases, revenue forecasting, and other relevant use cases. All Iodine Forecast data can be exported to and integrated with other systems, allowing it to be utilized by all relevant teams in their daily workflow and planning, and creating cohesiveness across the organization. All data is kept up-to-date from admission through discharge as new patient information is received.

Leveraging Forecast to help understand the reimbursement impact of COVID-19

Recently, Iodine applied its machine learning models to 60,000+ COVID-19 cases from more than 600 hospitals across the U.S. to better understand the reimbursement impact of COVID-19. In this analysis, Forecast enabled Iodine to consider all discharged patients without waiting weeks for final coded DRGs. 

Timeliness of financial insights is critical–especially when navigating the challenges of a crisis such as COVID-19–and Iodine Forecast provides near-real-time access to the data that supports these insights. The Iodine Forecast Module enables hospitals to better understand trends such as the reimbursement impact of COVID-19 and develop strategies to get ahead of unforeseen challenges.

To learn how Forecast can empower your Case Management and Finance teams, reach out to info@iodinesoftware.com.

Zero Work for Working DRGs

Working diagnosis-related group (DRGs) are utilized for a variety of functions across healthcare organizations, including case management, finance, and care coordination. In particular, working DRGs contribute to many system-wide forecasts, so accuracy is vital. This necessity is increasingly apparent during times of high uncertainty when the margin for error is even more slim than usual.

The responsibility for generating working DRGs typically falls on CDI teams. This increases their already large workload and makes it difficult, if not impossible, for each patient to be assigned a working DRG and for these codes to be re-reviewed every day to incorporate new data. As a result, opportunity for DRG assignment and/or correction is often missed, decreasing the accuracy of both the overall clinical picture and DRG-based predictions.

Iodine built a fully-automated, clinically-driven module that increases the accuracy and efficiency of assigning working DRGs, supports clinical documentation integrity (CDI) workflow, and enables teams across the health system to make real-time, evidence-based predictions — without needing to rely on final coded data. The Iodine Forecast Module – part of Iodine’s AwareCDI suite –  leverages Iodine’s CognitiveML™ engine to automatically and concurrently predict MS-DRG codes for all inpatients based on patient documents and data, even if no prior manual review has been performed.

In addition, geometric mean length of stay (GMLOS), relative weight, and other associated DRG information is included for each forecasted MS-DRG. This data can be leveraged for discharge planning, resource utilization, early identification of bundle DRG cases, revenue forecasting, and other relevant use cases. All Iodine Forecast data can be exported to and integrated with other systems, allowing it to be utilized by all relevant teams in their daily workflow and planning, and creating cohesiveness across the organization. All data is kept up-to-date from admission through discharge as new patient information is received.

Leveraging Forecast to help understand the reimbursement impact of COVID-19

Recently, Iodine applied its machine learning models to 60,000+ COVID-19 cases from more than 600 hospitals across the U.S. to better understand the reimbursement impact of COVID-19. In this analysis, Forecast enabled Iodine to consider all discharged patients without waiting weeks for final coded DRGs. 

Timeliness of financial insights is critical–especially when navigating the challenges of a crisis such as COVID-19–and Iodine Forecast provides near-real-time access to the data that supports these insights. The Iodine Forecast Module enables hospitals to better understand trends such as the reimbursement impact of COVID-19 and develop strategies to get ahead of unforeseen challenges.

To learn how Forecast can empower your Case Management and Finance teams, reach out to info@iodinesoftware.com.

Redefining Reconciliation with Iodine Retrospect

Prior to COVID-19, health systems were already operating on generally thin margins, with many finance leaders acknowledging that a significant root cause was leakage from their mid-revenue cycle and that “average performance” was still well below optimal results. Given the unforeseen impact of COVID-19 on hospital revenue, healthcare finance leaders must now be even more protective of margins.

Retrospective reviews are the last opportunity to resolve documentation and coding issues for billing and quality reporting purposes. However, traditional reconciliation is inefficient and often ineffective for a number of reasons, including:

  • Chart selection criteria that do not specifically identify all correction opportunities
  • Manual processes, which force unnecessary chart reviews
  • Complex, frequently changing documentation and coding guidelines
  • Over- and under-documentation by physicians
  • Understaffed CDI teams
  • Strict productivity requirements for coders

Traditional approaches force clinical documentation integrity (CDI) specialists to unnecessarily review a significant number of charts in search of these opportunities, which extends DNFB to no benefit. Additionally, most CDI teams are unable to review every chart, leaving many documentation and coding issues unidentified prior to billing.

The broad scope of factors impacting CDI efficiency and accuracy require creative solutions beyond hiring more CDI specialists. Only technology can automatically review each record during the retrospective review process and direct CDI teams to the charts that are most likely to require their attention, allowing them to eliminate a significant, unproductive portion of their workload and focus on improving documentation integrity.

Iodine Software is redefining reconciliation through its Retrospect module, which eases the burden on CDI and coding teams by automatically reviewing every chart prior to billing. Iodine Retrospect combines the prioritization technology of Iodine’s SmartList with an integrated CDI review workflow for post-discharge records. Narrative documentation, clinical evidence, and patient demographics are all taken into consideration, allowing Retrospect to make accurate predictions and automatically identify both cases that do and do not require a review. Discharged patients are therefore prioritized based on their statistical likelihood of containing documentation opportunities.

Retrospect also helps quality-audit CDI staff. Residual documentation concerns are detected in records already reviewed by CDI teams, allowing CDI program leaders to isolate knowledge deficits and identify workflow and process opportunities to support continued CDI program growth and success.

To learn more about the Iodine Retrospect Module, contact: info@iodinesoftware.com.