Dr. Noah Payne shook his head in disbelief: the practice instead of climbing refunds shrank in response to the recent recruitment of Dr. Inna Ternist. The new doctor is clearly on the total number of patients, the total payments have not seen the additional fees. Maybe the new claims were not created, or the? Dr. Noah reminds notice the growing pile of rejected and denied claims gather dust on his desk - he never had the time, it ... How many of these details are clean How many of them require manual review and correction?

Dr. Noah saw his Vericle screen and began to analyze the numbers. The system showed 58 percent of clean claims (PCC). In other words, almost every second manual exposure correction. Who could cause such a high level of problems: the practice of the settlement, or the client? Dr. Noah's instinctively felt that perhaps the settlement has been negligent about data capture and hold the massive introduction of data errors. But the service manager was quick to declare a strict quality control for data entry. What could cause such a high degree of manual work in an apparently streamlined process?

A brief review shows that the PCC varies along several dimensions:

1. 19 and 70 per cent for the financial class
2. 37 and 66 percent for the month of notification
3. 55 and 59 percent for the doctor
4. 29 and 70 percent for various CPT codes

Tries, a pattern Dr. Noah for a cause dimension. He drilled in 99,213 - the largest frequency CPT code for its practice. Vericle receivables and 3135 showed the average of 62 on the PCC, the fees and payments for the 99,213-code.

After isolation of the single most common CPT code, Dr. Noah thought about other dimensions, the influence on PCC. He suspects that if all the doctors in his practice had the same coding skills, and assuming equal distribution of error, he should not observe variance in the PCC doctors. However, a quick click on a Vericle screen showed a spread, confirmed his suspicion that the various doctors maintain something other coding skills:

1. 1554 Dr. Ted claims and PCC = 63%
2. Dr. Lori 865 claims and PCC = 62%
3. Dr. Inna 194 claims and PCC = 61%
4. Dr. Noah, 516 claims and PCC = 60%

Next, Dr. Noah turned his attention to the distribution of PCC in the financial classes. He also suspects that if all payers use the same rules to deny claims then there should be no difference in the average PCC for various cost, with the equal distribution of errors over a large sample of claims submitted and paid. But the figures showed a significant (30 percent) of variation of PCC for the same CPT code: UHC - 82, Blue Cross Blue Shield - 73, Oxford - 64, Aetna - 59, Medicare - 59, and Cigna - 51, confirming his , concluding that different payers, different rules to deny and underpay claims.

Dr. Noah recalls reading an article about Pacificare, a California insurance against fine on a test. The joint Department of Managed Health Care and Insurance recently analyzed 1.1 million paid claims from June 2005 to May 2007 that approximately 190,000 members in the Pacificare HMO and PPO coverage [Gilbert Chan, "" fine Pacificare Record $ 3.5 Million "," www. sacbee.com, 30 January, 2008]. They found 30 percent of the HMO claims wrongly denied and 29 percent of the disputes with physicians have been treated incorrectly. Pacificare be disbursed over $ 1 million fine and an additional $ 3.5 million. Dr. Noah results with Pacificare about testing - the insurance companies have not been anywhere between twenty to fifty percent of its claims and any insurance company, showed a different failure rate, depending on a system for the applications not.

Finally, Dr. Noah said the payroll service. If his payroll service work systematically, not their claims and to improve the response to these findings? Is there a pattern of occasional drop of PCC, the deterioration of the response to the various contracting initiatives? Conversely, there is no evidence of a systematic improvement effort? A graph of the distribution of a single CPT code clean claim per cent over the year-round to answer his question. In his mind, PCC should iterate between the drops and is growing each time, hopefully at a higher level. Vericle confirmed his expectations that a general improvement of the PCC in the year (46% 1-07 39% 2-07 52% 3-07 55% 4-07, 63% 5-07 67% 6-07, 72% 7 / 07, 69% 8-07 72% 9-07 68% 10-07 74% 11-07 73% 12-07)

In summary, that Dr. Noah concluded that PCC has a time-dependent function, the dives and rises as a function of four important factors. In particular, PCC is deteriorating as a reaction to one of (a) continuous-payer initiatives to impede settlement, rejection, loss, delay, and underpaying claims, (b) the practice is missing or incorrect filing codes and demographics, or (c) the billing service entering data incorrectly and inconsistently, and improves the PCC in response to a concerted action of the practice and the billing to discover, to correct and prevent demographics, coding and data collection problems. Large-scale medical billing networks create the necessary quantities and the resulting economies of scale, to the payment of tests to detect systemic processing problems.

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