# Healthcare Finance And Accounting Assignment #8

## AUTHORS’ NOTE

This CMS example illustrates the computation of hospital training costs and productivity loss costs and estimates a cost for system changes and upgrades in order to arrive at a total hospital ICD-10 conversion cost. We have numbered the paragraphs for easy reference. (And FYI, when the scenario below says “we” it means CMS, not the authors.)

## Introduction

To further illustrate the computation of hospital ICD-10 conversion costs, CMS staff developed a scenario for a typical community hospital in the Midwest. The material presented in the appendix was published in the proposed rule as an example of costs that might be incurred by a hospital. The data were drawn from the American Hospital Directory, available at www.AHD.com . While based on an actual hospital in a midwestern state, the data have been altered to make calculations simpler.

## The Scenario

· 1. The hospital has 100 beds, 4,000 discharges annually, and gross revenues of \$200 million. Using the factors presented in the impact analysis, we estimated training costs (including the cost of the actual training as well as lost time away from the job), productivity loss for the first six months resulting from becoming familiar with the diagnostic and procedure codes, and the cost of system changes.

· 2. For our scenario, we assumed that the hospital employs three full-time coders who will require eight hours of training at \$500 per coder for \$1,500 (\$500 times 3). While they are in training, the hospital will have to substitute other staff, either by hiring temporary coders if possible, or by shifting staff. The estimated cost at \$50 per hour is \$1,200 (8 hours times 3 staff times \$50 per hour).

· 3. In estimating the productivity loss, we are only looking at the initial six months after implementation. Therefore, we divided the annual number of discharges of 4,000 by 2 to equal 2,000. We assume that three-quarters of the discharges are surgical, giving us 1,500 discharges requiring use of PCS codes. Dividing this by six months yields an average monthly discharge rate of 250.

· 4. We performed a similar calculation for outpatient claims. Of the 13,000 outpatient claims, the monthly average is 1,083 (we do not distinguish between medical and surgical outpatient claims).

· 5. Applying the 1.7 extra minutes per discharge, we estimated it would take an extra 425 minutes (1.7 times 250) to code the discharges in the first month. At \$50 per hour, the cost per minute is \$0.83 (\$50 divided by 60 minutes) and the cost per claim is \$1.41 (\$0.83 times 1.7). For the first month, the productivity loss for inpatient coding is \$353 (\$1.41 times 250). Assuming for simplicity’s sake that the resumption of productivity over the six-month period would increase in a straight line, we divide the \$353 by six to come up with \$59. We reduce the productivity loss by this amount each month through the sixth month. The total loss for the six-month period is \$1,233.

· 6. We apply the same method to determine the outpatient productivity loss. Based on our assumption that outpatient claims will require one-hundredth of the time for hospital inpatient claims, when applying the 0.17 extra minutes per claim, we estimate it would take an extra 18.41 minutes (0.017 times 1,083) to code the discharges in the first month. At \$50 per hour, the cost per minute is \$0.83 (\$50 divided by 60 minutes) and the cost per claim is \$0.14 (\$0.83 times 0.017). For the first month, the productivity loss for outpatient coding is \$15.28 (\$0.014 times 1,083). Assuming for simplicity sake that the resumption of productivity over the six-month period would increase in a straight line, we divide the \$15.28 by six, coming up with \$2.55. We reduce the productivity loss by this amount each month through the sixth month. Thus the total loss for the first six months will equal \$53.

· 7. In estimating the cost of system changes and software upgrades, we deliberately chose a value that we think overstates the cost. We assumed that the hospital will have to spend \$300,000 on its data infrastructure to accommodate the new codes. Summing the training costs, productivity losses, and system upgrades, we estimate the total cost to the hospital will equal approximately \$303,990. Finally, in order to determine the percentage of the hospital’s revenue that would be diverted to funding the conversion to the ICD-10, we compared the estimated cost associated with the conversion to ICD-10 to the total hospital revenue of \$200 million. The costs amount to 0.15% of the hospital’s annual revenues.

· 8. We note that although the impact in our scenario of 0.15% is significantly larger than the estimated impact of 0.03% for inpatient facilities (set out in the rule), it is still significantly below the threshold the Department considers a significant economic impact. We are of the opinion that, for most providers and suppliers, payers, and computer firms involved in facilitating the transition, the costs will be relatively small.

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