LISTA DE DOCUMENTOS PARA LA INTEGRACIÓN DEL EXPEDIENTE DE AFILIACIÓN AL PROGRAMA DE CADENAS PRODUCTIVAS

When analyzing the monthly RAPS management reports, CMS urges MA organizations to consider the following questions:

• “Is my organization collecting enough data from physicians and providers?” • “Is my organization collecting the correct data from physicians and providers?” • “Are external issues affecting data collection?”

• “Are internal processes supporting data submissions?” Each question is discussed below.

5.6.1 Collecting Sufficient Accurate Data

The Monthly Plan Activity Report is a good place to start the analysis. Because this report provides a summary of the status of data submitted for each month, it allows organizations to check, on a monthly basis, the number of diagnosis clusters submitted overall, the number of clusters submitted by data source (hospital inpatient, hospital outpatient, and physician), and the status of those clusters. Reading the report from left to right, the report identifies the number of clusters submitted in the reporting month (April 2004 in Figure 5P) for every month in the data collection period.

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Figure 5S on the next page illustrates a Cumulative Plan Activity Report for April 2004. It reports the number of diagnoses submitted from July 2003 through March 2004. Analysis of this report might begin with a review of the number of clusters submitted by provider (source) type. This plan is doing well because it is submitting the vast majority of its hospital inpatient data for service through dates within 90 days of the report date. If the organization is submitting data at about the same pace received, then the

umber of clusters seems appropriate, at least for hospital inpatient. n

CMS recommends MA organizations collect data from providers and physicians within 90 days of the service through date. Consistent collection lags of more than 90 days may cause problems in submitting data in a timely manner.

The average rate of rejected data is below one percent for MA organizations. The plan in this example has a rejection rate for hospital inpatient services at about nine percent during April. If the other provider type information reflects a similar rate of rejected data, it is higher than it should be and a cause for investigation.

EDITS AND REPORTS

Figure 5S – Analysis of Cumulative Plan Activity Report

REPORT: RAPS0010 CMS RAPS ADMINISTRATION PAGE: 1 RUN DATE: 20040501 RAPS CUMULATIVE PLAN ACTIVITY REPORT SERVICE YEAR: 2003 SUBMITTER ID: SH8888 FOR THE MONTH OF APRIL, 2004

PLAN NO: H8888

PROVIDER TYPE/TOTALS JULY AUGUST SEPTEMBER OCTOBER NOVEMBER DECEMBER TOTAL PRINCIPAL INPATIENT

TOTAL SUBMITTED 12 30 21 43 58 101 265 TOTAL REJECTED 5 3 4 5 2 8 27 TOTAL ACCEPTED 7 27 17 38 56 93 238

REPORT: RAPS0010 CMS RAPS ADMINISTRATION PAGE: 2 RUN DATE: 20040501 RAPS CUMULATIVE PLAN ACTIVITY REPORT SERVICE YEAR: 2004

On the Cumulative Report, MA organizations should review the data across the collection period, ensuring that the number of data for each month is consistent. Low submission months or significant spikes in the data submitted for a month may indicate a problem in either data collection from providers and

physicians, or issues related to data submission. Generally, each quarter of data should reflect about 25 percent of the expected data for the collection period.

5.6.2 External Issues Affecting Data Collection

When reviewing the management reports, MA organizations should consider external issues that affect data collection. The Cumulative Report is a good place to start analysis because it gauges the number of data collected and submitted over the course of the collection year. For an organization just starting operations, a steady increase in data submissions from month to month is expected. However, an MA organization that has a relatively stable population should have consistent numbers from month to month. Significant fluctuations from month to month may be cause for investigation.

The risk adjustment rules require that for each quarter MA organizations submit approximately 25 percent of the total expected data for the year for each provider type (source). Meeting or exceeding this standard (e.g., submitting monthly or weekly) helps organizations avoid “playing catch up” at the end of the collection year and helps ensure accurate risk adjustment calculation. If data are not submitted in a timely and consistent manner, there may be a data collection issue. Provider education may be necessary to remedy the problem. Also, it may be necessary to check that third party billers used by providers (especially large volume providers) are current on risk adjustment procedures and the importance of timely filing.

SUBMITTER ID: SH8888 FOR THE MONTH OF APRIL, 2004 PLAN NO: H8888

PROVIDER TYPE/TOTALS JANUARY FEBUARY MARCH APRIL MAY JUNE TOTAL PRINCIPAL INPATIENT TOTAL SUBMITTED 1940 1944 643 50 0 0 4577 TOTAL REJECTED 158 203 54 5 0 0 415 TOTAL ACCEPTED 1782 1741 589 45 0 0 4157 Data collection “lag” is 90 days.

High rate of rejected data.

EDITS AND REPORTS

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5.6.3 Internal Processes Supporting Data Submissions

The RAPS management reports can help MA organizations identify internal processes negatively affecting data collection and submission. Organizations should check to make certain that data, as it is collected, is properly translated for submission.

MA organizations should take steps to ensure they have, or have access to, the proper medical documentation to support diagnoses being submitted for risk adjustment. MA organizations are responsible for the accuracy of the data submitted to CMS. When necessary, they should obtain the proper documentation to support diagnoses and maintain an efficient system for tracking diagnoses back to medical records.

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If the appropriate amount of data are collected from providers and physicians for a month or quarter, but only a fraction of the data are submitted, there may be an over filtering issue, i.e., the plan may not be submitting all required data. Also, the plan should check for higher than normal rejection rates, possibly dicating a problem with the data submission system (bad formatting, assigning the wrong HIC, etc.). in

If an organization is submitting well above the benchmark levels, it should check to see if proper filtering occurred before submission. Many plans collect data from provider types not covered by the risk

adjustment instructions. Submitting data from these non-covered provider types violates the instructions nd will probably cause the diagnostic-to-beneficiary ratios to be high.

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