Predictive modeling to enhance Revenue Cycle Management & Health Information Management performance
- Can you quickly identify the number of timely filing accounts remaining in the month?
- Can you forecast your cash daily, weekly, monthly?
- Do you have drill-down capabilities with your A/R?
- Do you have denial management challenges?
- Is the capture rate within 5 percentage points of CMS to avoid a potential audit?
As the volume of healthcare data grows exponentially, the power of that data can be harnessed and utilized to improve outcomes in revenue cycle. JTS’ Analytics offer a powerful view that can be used to enhance claims process efforts to prevent errors and loss of time. Using near real time information to predict trends can change the trajectory of the bottom line.
Obtaining multiple data sources, without building interfaces, allows for a more accurate understanding of both positive and problematic trends. In addition to establishing predictive measurements of future revenue and cash management, JTS can pinpoint areas that require process and quality improvement initiatives.
JTS’ Healthcare Analytics as a Service model offers powerful, predictive tools in the following areas:
JTS' Healthcare Analytics works with key organizational stakeholders to:
- Create more accurate, complete and compliant coding
- Increase revenue by developing a roadmap for the reduction of lost revenue
- Provide resources to retrospectively correct coding and rebill third party payors
- Educate coders, CDI and clinical staff on where to focus for improved documentation quality
- Improve denials management process
- Increase staff productivity through operational analytics
- Facilitate culture and work process improvement initiatives
Revenue Cycle Management (RCM) Analytics offers a full analytical suite of reports with drill-down capabilities that analyzes cash and accounts receivables. Additionally, the suite examines accounts from highest to lowest level in order to prioritize work.
The suite of A/R Management tools provide dashboards with predictive healthcare analytics to identify trends and high-value opportunities in Cash Collection, Accounts Receivable and Account Auditing. The A/R suite creates a simple yet powerful dashboard that can integrate with any healthcare financial system or multiple systems across different facilities.
Combining multiple data sources into one usable package, RCM Analytics provides a full view of historical, trending and predictive data to speed decision making and identify necessary process improvement requirements.
Collections capabilities provide powerful insights and predictive analytics for your cash goals, staff productivity, account inactivity, timely filing and collection rates.
As medical denial rates continue to increase, so does the importance for revenue cycle teams to pinpoint trends and gaps. JTS’ Denial Management platform provides analysis of denial rates based on services by location and payor data with predictive analytics representing total expected reimbursement outcomes.
JTS’ Denials Management categorizes your denials by department to determine volume, dollars and rate. It examines your historical recovery rate by denial code and department as well as potential recovery opportunities. This suite also enables pinpointing of denials remaining untouched.
All data inside nCREAS™ Denials Management reports can drill down through our hierarchy levels to a single account number.
Complete and accurate coding and appropriate revenue capture are vital to the integrity of Health Information Management (HIM). To ensure that clients are coding correctly and receiving the appropriate reimbursement, JTS Health Partners created nCREAS™ Analytics as a Service solution to dissect client data to offer insights for improvement.
Targeted DRG Revenue Capture
Hospitals typically audit coding to make sure it is accurate, complete and compliant with national correct coding guidelines. Audits are usually concurrent and retrospective and often focus on high volume diagnoses, procedures or Diagnosis Related Groups (DRGs). Audits may also include a random sample of inpatient and outpatient coding.
Coding audits are a valuable tool for educating coders and improving coding quality and compliance. However, the sample sizes are frequently insufficient to identify problematic patterns that result in lost revenue.
Targeted education improves coding quality, pinpoints specific groupings of MS-DRG’s to identify lost revenue, solidifies future revenue through training and process improvement
JTS' Healthcare Analytics works with key HIM stakeholders to create:
- Accurate, complete and compliant coding programs
- Roadmaps to reduce lost revenue caused by incomplete or inaccurate coding
- Workstreams to retrospectively correct coding and rebill third-party payors
- Programs for coders, CDI and clinical staff to be trained where to focus energy for improved documentation quality, patient care and enhanced revenue
- Comprehensive educational models for clinicians and CDI staff for improved documentation, coding practices and appropriate reimbursement
Historically achieved 200 - 600% ROI
CC/MCC Capture Rate
The CC/MCC Capture Rate Analytics will compare your data to CMS established benchmarks. Any deviations outside the expected norm are reviewed to determine if your facility has the documentation to support the assigned MS-DRG. The analysis can be expanded to non-Medicare payors to look for opportunities within that population that would affect payment and severity.
Target trends of data for facilities comparing their MS-DRG rates to established Centers for Medicare & Medicaid Services (CMS) MS-DRG benchmarks.
TELEHEALTH REIMBURSEMENT REVIEW
JTS can provide a thorough Telehealth Reimbursement Review of your organization’s telehealth claims to ensure compliance with payor reimbursement rules and regulations
JTS’ operational analytics offers tools and services to provide a systematic quality review with workstream enhancements that address the following areas:
- Productivity & Performance Management
- Compliance & Quality Management
- Data Management