Leveraging Computer-Assisted Coding and Analytics in Today s Radiology Environment. Overview. Goals for This Presentation. Mark Morsch August 22, 2010

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1 Leveraging Computer-Assisted Coding and Analytics in Today s Radiology Environment Mark Morsch August 22, 2010 Overview Introduction Definitions What is Computer-Assisted Coding? What are Radiology Analytics? Importance of Coding Coding Workflow and Benefits of CAC Analytics Measuring Quality and Efficiency Example Metrics Goals for This Presentation Computer-assisted Coding and Radiology Analytics Information Technologies that support improvements in efficiency, quality, and consistency of the delivery and administration of imaging services Help administrative process and decision-making become more transparent and traceable Provide various metrics that can be used to define standards of best practice

2 Computer-Assisted Coding Computer-assisted Coding (CAC) is technology that derives procedure (CPT) and diagnosis (ICD9)codes directly from radiologist reports Natural Language Processing (NLP) is used in most radiology CAC applications Read dictated reports and extract key clinical facts Apply coding guidelines to the extracted facts to derive billing codes Radiology Analytics Radiology Analytics tools provide visualization, trending, aggregation, comparison and reporting for data collected as part of the ordering, delivery and administration of imaging services Key areas of focus Quality of Service Imaging Utilization Productivity and Efficiency Importance of Coding Goal of CPT/HCPCS and ICD-9 code assignment is to present accurate picture (numerically or alphanumerically) of what service(s) were rendered on a particular date of service (DOS). Up/Down, but correct!

3 Accuracy All codes are used to translate numerically what was done (CPT code) and why it was performed (ICD-9 code). 3 rd party payers do not routinely receive written reports. Reimbursement Major payers (Medicare, Medicaid, etc) mandate that CPT, HCPCS and ICD-9 codes as well as modifiers are reported on claim form (UB04 or 1500). Trend is for other payers to follow Medicare s lead is this regard. Percentage of Charge reimbursement thing of past. Compliance Coding for some Radiology procedures repetitive and lend themselves well to Computer Assisted Coding (CAC). Some modalities can utilize CAC, but still need human touch.

4 Computer-Assisted Coding 3 Coding Technology Why is CAC Technology well-suited to Radiology? Very large number of electronic reports Reports are relatively short, most less then one page Most charges for a test or procedure can be derived from a single report Radiologists tend to produce high quality documentation, most follow ACR guidelines Vocabulary is reasonably constrained But remember, it s not simple

5 Benefits of Computer Assisted Coding Increased coding productivity Increased efficiency; frees professional from mundane tasks Comprehensive code assignment Consistent application of rules Electronic coding audit trail How does CAC increase productivity? Automation allows a significant portion of reports to be coded and billed with no manual intervention Coder becomes more of a reviewer/auditor Fewer keystrokes to edit than compose Integrated view of clinical documentation, supporting demographics and codes How does CAC increase efficiency? Automates mundane coding tasks Reduces manual data entry Eliminates paper, supporting a complete electronic workflow Facilitates remote coding

6 How does CAC assist comprehensive code assignment? Codes derived from full clinician documentation Helps direct less-experienced coders to code-able facts that may be overlooked Identify uncommon or complex coding scenarios that require special handling How does CAC help in the consistent application of coding rules? Uniformly apply includes/excludes guidelines for ICD-9 coding Supports correct application of modifiers in CPT coding based on documentation Integrates with code scrubbing functions such as LCD/NCD and CCI Automates rules needed for certain payer-specific reporting Example CAC Metrics Coding Automation and Productivity Reports sent straight to bill Reports per Hour Coding Quality and Consistency Coding agreement rate procedure, diagnosis, coder Service-to-Bill Days DOS-to-Received Days Received-to-Code Days Coded-to-Billed Days

7 Example CAC Metrics Example CAC Application Obstacles to Deployment (ROI) Lack of leadership to change current processes/staff Lack of acceptance by current staff Vendor over-promise and under-deliver Poor documentation or data quality

8 Business Benefits Reduced Revenue Cycle Expenses More Consistent Charge Capture Coding Compliance More Manageable & Flexible Organization Radiology Analytics Quality of Service Right Procedure eg. X-Ray V. MRI Right Time eg. Image now v. image later Right Reasons Within available guidelines Expected outcomes fall within benchmarks Normal/ Positive Findings / Indeterminate Recommended Follow-up Procedure CPT4 Time Frame of Follow-up Physician Communication Coded Significant Findings (ICD9) Prior Exam Mentioned Change from Prior Exam Improved/Worsened/Unchanged

9 Documentation Quality For DI, the radiologist s work product is the report Conformance to ACR guidelines and department standards Clinical indicator Procedure name and description Positive and negative findings included Clear recommendation for follow-up Imaging Utilization What are the Drivers for Imaging Utilization? From 2000 through 2006, Medicare spending for imaging services paid for under the physician fee schedule more than doubled--increasing to about $14 billion. Spending on High Tech imaging (CT, MR, and NM), rose significantly faster than Low Tech (US, XR, and other standard imaging). GAO's analysis of the 6-year period showed certain trends linking spending growth to the provision of imaging services in physician offices. By 2006, in-office imaging spending per beneficiary varied almost eight-fold across the states-- from $62 in Vermont to $472 in Florida 1. Increase in High Tech Imaging Volume 2. Suspicion of volume with respect to where Imaging is being performed 3. Tremendous Variation in Imaging Utilization Imaging Utilization Where is the Industry Today? Payer Centric Imaging Utilization Programs Private Payers Via RBMs have implemented: Prior Notification Programs Pre Authorization Programs Payer Based Safety and Adequacy Benchmarks Accreditation of imaging providers Certification for, facilities, physicians, equipment CMS DRA (Reimbursement is a blunt instrument for the problem) Contemplating possible RBM solutions

10 Productivity and Efficiency Radiologist Productivity and Efficiency of Supporting System Studies per hour difficult to compare across subspecialties RVU Includes three components practice expense, malpractice and work Work RVU more comparable measure, although not perfect Example Analytics Provide Point & Click Business Analytics for your Medical Directors and Business Unit Leaders Local, published and payor guidelines are used to drive clinical feedback and support Standard Reports provide starting point to most common analysis, with the ability to modify the reports with additional information Select Any Criteria to answer specific business questions Order Analytics

11 Report Analytics Potential Technological Benefits Web based business intelligence solution Secure, internet access from anywhere Standardized data communication interfaces to gather order and report data Consolidate data from diagnostic imaging (DI) ordering systems and radiology reporting systems Use NLP to extract and structure outcomes and significance In-memory analysis tool Change data views on the fly Easily move from aggregated summary views to drilling down into subsets of specific data Quickly include or exclude groups of data Business Benefits Improve quality and use of DI Benchmark and analyze ordering patterns and performance metrics, Retrospectively apply appropriateness guidelines Compare ordering and guideline application to radiology outcomes Identify and manage financial exposure to escalating costs Uncover and document areas for improvement, identify outliers Provide evidence to support planning and policy changes Open the door to exemptions from phone-based utilization management programs Transparency through documentation and reporting of ordering and decision support outcomes P4P

12 Summary Computer-assisted Coding and Radiology Analytics are being successfully employed to improve ordering, deliver and administration of imaging services Both require a change in approach to managing people, process and technology Accurately transforming data into information is key Contact Information Mark Morsch Vice President of Technology mmorsch@alifemedical.com