Advice You - Business

Average medical practice may lose as much as 11% of its revenue due to underpayments. But underpayment recovery potential averages only 5% of revenue and involves costly appeal process. To avoid unrecoverable losses, some providers discontinue servicing patient

According to USFDA, a combination product is one composed of any combination of a drug and device; biological product and device; drug and biological product

s insured by the worst performing payers. Unfortunately, such a drastic loss reduction measure may boomerang and increase losses depending on complexity of referral relationships. This article outlines limitations of traditional database queries used to identif

; or drug, device, and biological product and fixed dose combination would include two or more combinations of drug.

Examples of combination products may in

payer candidates for contract termination and demonstrates alternative decision choices with superior performance in terms of revenue and risk management, facilitated with On Line Analytical Processing (OLAP) technology.

First Order SQL Queries for Accounts

lude drug-coated devices, drugs packaged with delivery devices in medical kits, and drugs and devices packaged separately but intended to be used together.

Receivable Analysis

Traditional accounts receivable analysis includes identification of payers that systematically underpay and refuse denial appeals. Such analysis is based on simple queries, designed to identify the best CPT code or the worst payer in ab

here is enormous increase in the number of combination products entering the market in the recent years. Combination products have proven advantages but fixe

olute terms:

Comparison of revenue for various CPT codes for a given time-period
Comparison of underpayments for various payers for a given time-period
Comparison of denials for various payers for a given time-period

d dose combinations are still in the process of convincing regulatory authority on their advantages over the single ingredient formulations.

Combination pro

ul>

A single key database indexing is a standard measure to improve time performance of such queries. It builds an ordered relationship within the data elements based on the value of the selected metric. But single key indexing precludes implementation of more

ucts have become life saving products for the pharmaceutical companies who doesn’t have many innovative molecules in their product pipeline and have been inc

complex queries like "who is the payer that underpays the most for the best CPT code," or "who is the worst referring physician for my worst payer?" and require complex SQL programming skills because of the need to store and process intermediate results. Therefo

easingly used in the product life cycle management. Even the companies having product patents are trying to extend their product life cycle through the combi

e, ranking the data elements along a single attribute, forces a limited choice for management decision:

Ignore the problem,
Renegotiate the contract with the payer, or
Stop serving patients insured by the worst payer.

nation products and maximize the revenues. But the companies involved in this practice are overlooking that they are burdening the patients both economically

But to find more subtle solutions the office manager requires the ability to aggregate and drill into data and formulate queries in real time, in response to observed results to the previous queries. Specifically, a low frequency under performing payer

and physically. They need to rightly judge the benefits of the combination products and they have to even look at the risks involved when combining the produ

with a high degree of underpayment may not be as detrimental to the office as a high frequency under performing payer with a low degree of underpayment. Contract termination with a wrong payer may accomplish the opposite result to practice goals in terms of reve

ts. Some of the combination products were well accepted by physicians while others suffered. Companies involved in development of combination products are fi

ue maximization and workload reduction. Additionally, a decision to stop serving patients insured by any one payer may cause reduction of referral volume of other patients across all payers for a particular referring physician.

Combinatorial (Second Order S

ding difficulty in defining their combination products and facing various challenges from selecting a combination to marketing it.

Following aspects would a

QL) Queries for Accounts Receivable Analysis

Fortunately, modern database query technology can address both limitations by enabling "second order SQL" queries, which allow data manipulation based on multiple criteria and using functions of combinations of su

dd to the challenges in developing combination products:

Which markets to tap where the combination products can do fairly well?
Which combination prod

h criteria.

In our case, second-degree SQL queries allow finding the worst payer for best revenue generating code. Such a discriminating approach allows focusing on higher priority items first, resulting in more effective management. In general, the manager pe

cts are meaningful and rational?
Which therapeutic categories to select?
Which Combinations can address unmet needs of the patients?
Do combin

forms a custom comparison of payers according to the following four-step sequence:

Select metrics (e.g., % paid, % accounts receivable beyond 120 days, % denials)
Select dimensions (providers, payers, CPT codes, ICD-9 codes, referring phy

tions increase the patient compliance?
What would be the developing cost?
How to tackle the risks encountered during combination product developmen

icians)

Partition

Aggregate, drill-down, pivot

Worst Payer Query

To find a payer with highest amount of underpayments for the most-frequent CPT code, a second order SQL query can be written along the following l

t?

As combination products don't fit into the traditional categories of drugs, medical devices, or biological products, the USFDA is in the process of devel

nes:

For a given time-interval,

Select payers

Where sum of underpayments over

(all CPT codes Where Revenue > Revenue Threshold) > Underpayment Threshold

Worst Referring Physician Query

To avoid the risk of losing referrals from better-performing pa

ping new procedures for reviewing their safety, efficacy and quality.

Professional from academic institutions, pharmaceutical industries, health care indust

ers, the manager may consider severing referral relationship with some referring physicians instead of payers. In such a case, distribution of patients across various payers plays an important role for each referring physician. A single combinatorial query may

y and representatives from various regulatory agencies are working out to design the regulatory requirements for manufacture and sale of combination products

etch the Worst Referring Physician as follows:

For a given time-interval,

Select referring physicians Where Revenue for the Worst Payer > Threshold

Summary

Underpayment management involves all phases of claims processing and requires powerful Vericle-

.

As there is an increasing trend of the combination products companies manufacturing such products should be able to tackle the problems involved in the de

ike computing platforms for exhaustive comparisons of payments versus allowed amounts and subsequent appeal management. OLAP allows better analysis of accounts receivable and more effective management because of the ability to handle queries with functions of mu

elopment. They need to be wiser in analyzing the market trends and the regulatory requirements.

Companies that provide selfless information through particip

tiple attributes and dimensions. Note that in the absence of native OLAP mechanism, effective Vericle-like billing platforms allow similarly powerful analysis by introducing intermediary steps. Such steps may add insight to analysis and improve decision quality

tion in industry events and feedback to regulatory authorities would be able to face the challenges and will be successful in developing combination products

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