340B Guardian Model Overview

Transcription

1 340B Guardian Model Overview

2 Why monitor 340B program compliance? The 340B program has grown from less than $2B in total sales in 2002 to over $8B in sales in Currently, approximately 30,000 covered entity sites participate in the program. (Source: OPA Database) 1/3 of all hospitals are now covered entities (Source: 2011 GAO Report) 1 in 4 pharmacies is now a 340B contract pharmacy; that s over 15, B contract pharmacies (Source: Very high rates of non-compliance in government audits (53% in 2012, 59% in 2013 Source: OPA audit result files) The program is projected to grow to over $16B by 2019 (Source: BRG) These same drivers of growth are also increasing the complexity of the 340B program which creates more areas of risk for diversion and duplicate discounts Page 2

3 Prohibition Against Diversion Covered entities cannot resell or transfer a 340B drug to a person who is not a patient of the entity. Current (1996) patient definition requires: Covered entity has a relationship w/individual such that the covered entity maintains records of the individual s health care Individual receives services from a health care professional who is an employee of the entity or provides care under contract or other arrangement with the entity, such that responsibility for the care provided remains with the covered entity and Individual receives care from the covered entity that is consistent with the service or range of services for which the entity receives federal grant funding Page 3

4 Prohibition Against Duplicate Discounts Manufacturers are not required to provide a discounted 340B price and a Medicaid rebate on the same drug 340B statute required HRSA to create a mechanism to ensure that manufacturers did not pay "duplicate discounts." HRSA created the Medicaid Exclusion File: The entities listed on the Exclusion File have reported that they will fill Medicaid prescriptions with 340B-purchased drugs. Claims for these prescriptions are not eligible for rebates. Some covered entities purchase drugs for their Medicaid patients outside of the 340B program ( Medicaid carve-out ). These entities are not included on the Medicaid Exclusion File. The 2011 OIG report noted that many states don t use the exclusion file. Page 4

5 Cause for Concern: HRSA Audits / GAO & OIG For audits conducted in 2012 & 2013, HRSA reported results from 126 CE audits (Source: OPA website) 56% of these audits found either diversion or duplicate discounts 52 instances of product diversion 39 instances of duplicate discounting In GAO s words: increased use of the 340B program by contract pharmacies and hospitals may result in a greater risk of drug diversion, further heightening concerns about HRSA s reliance on self-policing to oversee the program. Recent OIG Report had further troubling findings Bottom Line: Significant leakage in this channel Page 5

6 What type of numbers are we talking about? Duplicate discounts can result in manufacturer overpayments that exceed 50% of WAC Diversion results in lost revenue of 30% or greater of WAC Page 6

7 Root causes of Medicaid duplicate discounts Duplicate discounts occur for a variety of reasons Inappropriate use of OPA s Medicaid Exclusion File Only a sub-set of NPIs and Medicaid Provider Numbers are identified Or, a covered entity fails to properly include the NPI on billed outpatient drugs Managed Medicaid patients are not properly identified as requiring carve-out status Technical issues at point of dispensing in contract pharmacy arrangements Dual-eligible patients are not properly identified as requiring carve-out status State Medicaid Program s role/responsibilities to prevent claims being received from CE s and/or being sent to manufacturers Page 7

8 Duplicate discount monitoring Manufacturers can do a number of things to monitor covered entity compliance Review state claims level rebate data to identify units potentially purchased by 340B facilities (using NPI scrubbing or reimbursement tests) Calculate the percentage of total sales at a 340B price for covered entities not listed on the Medicaid Exclusion File Identify changes in Medicaid Exclusion File status that don t align with trends in chargeback volume Trend 340B chargeback volume following ACA implementation Chargebacks to Sales Ra6o Immunology Actual Ra6o Expected Ra6o % of Medicaid Pa6ents Chargebacks Sales Percen6le % 64% 35.9% 14,419 15, % % 63% 36.8% 14,974 15, % % 63% 36.8% 11,810 11, % Page 8

9 Root causes of diversion Diversion can occur in a number of different ways: Inpatient utilization Utilization at ineligible sites Utilization through ineligible physicians Utilization by ineligible patients Programmatic errors in virtual inventory management systems (e.g. incorrectly including ineligible claims data ) Page 9

10 Diversion monitoring Manufacturers can do a number of things to monitor covered entity compliance Correlate increased 340B sales (both onsite and through contract pharmacies) with newly listed non-reimbursable hospital sites Identify outlier hospitals based on benchmarking 340B sales as a percentage of total sales across all similar covered entities Trend chargebacks over time for covered entities to identify unexplained increases in 340B utilization Look for instances of shifts in utilization that correlate with new entity registrations 6,000 Oncology Chargebacks (Units) 5,000 4,000 3,000 2,000 1, Combined Shift Entity New Entity Page 10

11 BRG s Approach to Monitoring for Diversion & Duplicate Discounts Integration of manufacturer data with publicly available data Utilizing manufacturer data in isolation can lead to false positives and can overlook instances of diversion due to lack of context We supplement third party data to the manufacturer data to provide additional insight into expected levels of utilization and significant events at a covered entity Third party data can be used to find explanations for root causes of changes in chargeback data that is not inherent in manufacturer data Page 11

12 BRG s Approach to Monitoring for Diversion & Duplicate Discounts Correlation of trends in chargebacks with events at covered entities Increases in chargeback data alone could have reasonable explanations unrelated to diversion and/or duplicate discounts But increases in chargeback data with a corresponding event identified through hospital cost report data could be a stronger indication of diversion or duplicate discounts For example, a large increase in chargebacks correlated with a newly listed outpatient clinic on the non-reimbursable portion of a cost report could reflect diversion through a newly acquired physician group that is ineligible for 340B pricing Page 12

13 BRG s Approach to Monitoring for Diversion & Duplicate Discounts Benchmarking entities against peers to standardize results and flag outliers Define key statistic for comparison Standardize key statistic for each entity Entities may have different profiles and therefore comparison without adjustment could miss potential diversion or duplicate discounts or create false positives Identify outliers based off variation calculation of key statistic Distributions may not be normal and different methodologies for outlier identification may need to be used Entities identified as outliers have higher probability of diverting product or creating duplicate discounts Page 13

14 BRG s Approach to Monitoring for Diversion & Duplicate Discounts Comparison of results across numerous products Capability to group products together can be critical in determining whether trends in the chargeback data reflect a systemic issue at a hospital or an isolated event Grouping products mitigates probability of incorrectly identified diversion or duplicate discounts due to data noise For example, if a contract pharmacy is flagged for potentially diverting product for product A, but not products B, C, D, E, and F, then most likely diversion is not the root cause for the increase in chargebacks Page 14

15 340B Guardian Using the concepts outlined in the previous slides, BRG has developed a comprehensive 340B compliance monitoring model called 340B Guardian The model includes 11 modules that utilize a diverse set of metrics and analytical approaches to identify duplicate discounts and diversion Each module is designed to identify different root causes of duplicate discounts and diversion Page 15

16 Utilizing the Analytical Output Dispute resolution with state Medicaid programs In instances of duplicate discounts, manufacturers may be able to dispute historical rebates paid to state Medicaid programs Covered entity engagement Open a dialogue to better understand the analytical results and address potential ongoing diversion Highlight options for covered entities to address ongoing duplicate discounts Correcting the Medicaid Exclusion File Listing the covered entity on the Medicaid Exclusion File Properly identifying managed Medicaid patients Properly identifying dual eligibles Page 16