Assisted Reproductive Technology Practice Management

Abstract

A basic knowledge of management issues is required in the operation of any medical practice. This chapter highlights the critical practice management principles necessary for effective interaction with other professionals in business management, human resources, payer organizations, legal counsel, accounting, and risk management who interface with the practice.

Appendix

Business operations require close attention to detail. Most billing systems have the ability to extract significant amounts of data. The organization of the data is critical, to ensure appropriate and maximum oversight of the financial health of your practice.

The Operational Indicator (see figure 2.2 for example of full report) has been designed to provide a visual overview of the financial status of your practice. This picture gives access to allow for review of the most immediate month’s data, trending for 13 months, benchmarking and variances - all at a quick glance. This important review can be completed quickly and efficiently. Concerns are readily identified to allow the implementation of timely corrective action. The operational indicator provides a view of financial issues. By having this information reported consistently it allows you to recognize problems and make adjustments quickly. With relevant, understandable data you can ensure that your goals are being met.

The following is a step by step review of the data, shows the importance of the assessment of the data, and gives detailed examples of areas that should be given additional review.

Figure 2.2

section 1

Please note that for best data review the indicators should allow for 13 months of data. Figure 2.2, section 1 reflects 3 months in the interest of space. You will want to include the most current month that has closed and 12 prior months.

• 1-1. Charges - Gross charges keyed into your billing system for that specific month.

  You will want to ensure consistency in productivity and posting.

• 1-2. Payments - Gross payments, prior to refunds posted in that specific month.

  It is important to remember that post dates have no ­correlation to the date of service, or the date the charge was posted in the system; especially when it relates to insurances and payment plans. A charge could be posted in April for a March date of service. A payment may be posted in April for a January date of service, etc.

• 1-3. Net Payments - Gross payments less refunds

• 1-4. Contractual Adjustments - This is the amount that has been negotiated with contracted payers and must be written off.

If you have contractually agreed to $1000 reimbursement for a specific code(s), you may bill any amount you wish.

Billed Amount $ 1500

Allowed $ 1000

$500 **

** This is a contractual adjustment that must be credited, and may not be billed to the patient or secondary insurances. Watch for unanticipated spikes by specific payers in their contractual adjustments. This could indicate changes in their bundling and other payer policies.

• 1-5. Refunds - Money returned to insurances and/or patients. Refunds are costly. Are there billing practices that are contributing such as continuous submission of claims instead of actual follow up? The Federal Payers expect timely processing of refunds. The following measures are basic but critical to the health of your practice.

• 1-6. Work RVU - Is a measurement that is used for productivity. Most CPT codes are assigned a relative value unit. An office consult 99243 has a 1.88 wrvu value, while an established patient 99203 is 1.34. The wrvu is a fairly consistent number that allows for the month to month, and year to year trending on productivity in your practice.

• 1-7. Total Discounts - Provides you with a roll up total of adjustments for hardship, bankruptcy, administrative, etc. If this number increases, further evaluation of why is important.

Figure 2.2

section 2

This section provides trending for the measures in figure 2.2.1. On a landscape report the above information would be to the immediate right (see figure 2.2 for example of full report).

• 2-1. Previous 12 Month Total allows a comparison between two complete 12 month time periods. This compares seasonality, conferences, etc. between years.

• 2-2. 12 Month Variance shows the difference between the two 12 month periods.

• 2-3. 12 Month Average allows you to identify the one month average for the last 12 months of information.

• 2-4. Current Month Variance show the difference between the most current month and the 12 month average. In this example the last complete month was April. Charges were $445,066. (See figure 1) When compared to the 12 month average of $400,494 (2.3) you can quickly see the operation has a gain of $44,571 in charges. Each measure from figure 1 can be quickly reviewed with this structure.

• 2-5. Prior Fiscal Year to Date allows an exact month(s) review compared to the exact number of months in the current fiscal year. For this example, the fiscal year begins in July. By April there would be a total of seven months reported. 2-5 looks at the seven months of the prior fiscal year and compares them to the seven months of this fiscal year.

• 2-6. Fiscal Year to Date as explained above looks at where the operation stands at the end of seven months.

• 2-7. Fiscal Year Variance provides a quick snapshot of whether the operation is above or behind at this same period in the fiscal year (seven months).

Figure 2.2

section 3

Collection agency/bad debt is an area that must be tracked to ensure consistent review of aged self-pay and appropriate transfer to bad debt (Figure 2.2. section 3). Are self pay accounts being reviewed monthly? Are broken payment plans for non responsive patients being sent monthly to collections? This type of A/R has your lowest return on staff time and effort and should be managed accordingly.

Figure 2.2

section 4

Figure 2.2 section 4 captures your patient population payer information. Self-Pay in this category reflects patients registered as uninsured. Process review of front desk demographic capture may be necessary. You may also have a referral problem - more than your share of uninsured patients, or you may be providing services that insurances do not cover.

• 4-1. Mix Current Month lets you know the population mix for the most current post month.

• 4-2. Mix Prior Year to Date allows you to compare last prior year (exact same number of months) to the current fiscal year.

• 4-3. Mix Fiscal Year to Date allows you to look and see if you are trending up or down of the last prior year’s insurance category.

Figure 2.2

section 5

The difference between Original Insurance information capture vs. Payer, is the Payer section reflects what percentage of your collections is paid by which Insurance Company. The measures and columns work the same as above.

If you compare the original insurance information captures in Fig 2.2 section 4 to payer category in Fig 2.2 section 5, you can ensure that you do not have a payer category that is significantly behind on payments.

Look at Blue Shield in 4-3 you will see the current mix is 22.83%. Compare this to Blue Shield the payer in 5-3, and you will see Blue Shield comprises 24.16% of the total collections.

Self-pay (figure 4-3) represented 15.25% of the original insurance charges but only 8% of the total collections. Reasons may include that many of the invoices initially reflect no insurance information and subsequently insurance is identified, billed and paid. The difference and primary concern would be the actual amount you must adjust off to bad debt - see figure 3.

Comprehensive data compilation of your outstanding accounts receivable (A/R) allows you to review the specific performance of your revenue cycle processes. If you generate a large month of billings, did it ultimately get collected? Is it being collected timely? Do you have payer/rejection issues? Do you have a billing office performance issue? How are we doing compared to others? All questions you can answer quickly with the data capture and organization indicated below in section 6 and 7.

Section 6 provides a succinct summary of aging of your outstanding A/R, whereas section 7 expands it to payer category. You may want to expand to payer - the report is much longer. The key area here to focus on is the aged A/R. If your percent of A/R > 20 is higher than the benchmarks (section 6-5 to 6-7) you wish to compare your practice to, then you need to begin the process of drilling down data and processes to identify the reasons for the aging. With complete data you can determine on what and where you want to focus your business office resources.

Figure 2.2

section 6

Benchmarking reflected in 6-5 through 6-7 is Faculty Practice Solutions (FPSC). This is appropriate if you are an academic institution. Another good source is Medical Group Management (MGMA). Also, some societies provide specific numbers based on surveys of their members.

Figure 2.2

section 7

The categories listed in 7-2 through 7-5 are standard A/R breakouts. For space purposes the first two categories of A/R 0-30 and 31-60 were removed. An important note - A/R is a good thing. You have to have it to collect it. It is the age of the A/R that must be managed carefully.

In this example, April reflects 37.63% (section 6.4;100-[17.96+13.12+10.51+20.79=62.38]) of total A/R ­outstanding is 0-30 days old. The corresponding benchmark indicates that the majority of members reported they have about 50% in this category 0-30. The first few categories is where you want the majority of you’re A/R. Aged accounts receivable is usually due to rejections, pending appeals, and self-pay.

A/R over 90 days identifies some potential problem areas. The second section breaks out the A/R by category. The category should be able to be drilled down to specific insurance company.

The aging category information allows you to quickly see where the largest areas of concern lies. Self pay, by its nature, will trend older. If an account has insurance, the insurance will be billed, paid (perhaps 2-3 months later), account will be 3-4 months old as it comes into the self-pay category.

By Looking at Total A/R column on the far right you can see that Self Pay is 39% of total A/R $308,072/$788,640. The second highest is all contracted payers, and in third place is Medicaid.

In reviewing the aging self pay. We know it makes up 39% of total A/R for this practice. Again, that in itself is not problematic. How old is it? 43% is greater than 90 days [16.52+7.44+10.42+8.64=43]. Is this a problem? Could be. If you allow 2 year payment contracts, then perhaps not. Knowing what your team is doing with self-pay collections is important. This isn’t captured in the report, but the report lets you decide what assessments you do need to have completed by your team. Questions like - did staff collect all appropriate point of service collections? Are accounts without payment arrangements being routinely transferred to collections? What amount of self-pay was created by incorrect insurance information at point of service? Etc.

Contracted payers generally are expected to pay within a 30-60 day time period for clean claims. This is a category that you would expect to be more timely than self pay.

In this example A/R still listed as outstanding for Contracted Payers is 20.33% of all my outstanding accounts receivable. Of the 20.33%, 18.5% [6.84+2.66+2.93+6.11 =18.5] is over 90 days. According to the FPSC benchmarks above the other practices surveys showed their A/R over 90 was about 15% (8.8% and 6.34%). Is this due to rejections, information requests, poor follow up by staff or by insurance? Some of these questions can be answered in the next section under rejections, others may require an analysis focusing on different payers.

Rejections are costly. Having to touch a claim several times takes staff time and possibly physician time. Ignoring rejections allows insurances to not fulfill their contractual obligation and in fact increases your “free care”. Rejections must be managed in a timely manner. In addition to working the rejections you need to know what and why you are receiving them.

Figure 2.2

section 8

The data in section 8 is grouped into three categories. This allows you to break out where the problem may be occurring and what resources are necessary to fix process. The three categories we established are Coding (8-1), Registration (8-2) and Follow Up (8-3).

• Coding (8-1) allows you to potential documentation and coding practices that are not in alignment with payer policies.

• Registration (8-2) are generally rejections that may have been avoided with better point of service processes.

• Follow Up (8-3) are often issues with payers. They may be requesting additional information, which if not sent, claim will not be paid. Payers may have system constraints so they are not reading modifiers, and denying claims as duplicates - again requiring an appeal with documentation.

Figure 2.2

section 9

The data captured in section 9 provides greater trending then figure 8. This section provides comparisons between the months and years. Rejections are calculated as a percent of charges. So if charges (9A) have gone up, either through fee schedule increases or increased productivity, it will reflect on the % of change in this row. When you review the Coding Category (9B) of rejections - the dollar amount of change between fiscal years is up 232% (9-6), but because charges were up 264% the actual change in coding rejections is actually down as a percent of total charges (.11%).

The key to this data and any other that you are reviewing is to ensure you understand the parameters of the data you are analyzing so that it provides accurate and valid information. Insufficient or flawed data will impact your responsiveness and accurate resolution of issues.

Whether you call it your financial analysis, dashboard, scorecard or operational indicator; the final objective is to have timely, manageable data in a format that allows you to monitor and manage your business. It must provide you a tool to process and manage key information to support your strategic growth and operational decisions.