William O. Cleverley

James O. Cleverley

With a tough economy forcing hospitals to cut costs, how can executives find areas of the greatest possible savings?

At a Glance

  • Inpatient and outpatient patient-encounter components provide a far better indicator of relative cost position than measures such as cost per adjusted discharge or cost per adjusted patient day.
  • Cost per encounter can be expressed as the product of three key cost drivers: intensity of services, productivity/efficiency, and resource prices/salaries and wages.
  • Cost reductions result from actions taken in two primary areas: utilization of services and cost efficiency.
     

The nation's economy has experienced significant decline in the past 18 months. In response, individuals, businesses, and government have sought ways to trim budgets to reduce costs in alignment with declining revenue. The healthcare sector has not been immune to these pressures and has renewed its focus on cost savings. Stories of medical staff and administrative downsizing have reached the headlines in many communities as hospitals have felt the effects of eroding volumes and payer mix. Yet many financial executives feel such actions are like placing a finger on the proverbial leak without understanding the extent of the pressures behind the dam. How can hospital leaders identify the actual size of their facility's cost opportunity? And what areas appear to be driving the cost issues? These appear to be the most critical questions in addressing cost concerns.

A cost metric defined as the Hospital Cost Index® was introduced in the July 2002 issue of Healthcare Financial Management (Cleverley, W.O., "The Hospital Cost Index: A New Way to Assess Relative Cost-Efficiency," Healthcare Financial Management, July 2002, pp. 36-42). The metric answers the question of "How large is the opportunity?" by providing a facilitywide comparison of cost. The specific inpatient and outpatient patient-encounter components provide a far better indicator of relative cost position than measures such as cost per adjusted discharge or cost per adjusted patient day. Assuming this proposition is correct, one major problem remains. If costs are high relative to industry norms, in what specific areas are cost savings located? Without specific direction, reducing costs becomes a subjective process and is often associated with across-the-board budget cuts that may not be beneficial from a long-term perspective.

The Healthcare Cost Function

The first step in being able to identify specific areas for cost reduction is to recognize the ultimate objective. Although this may seem terribly simplistic, it is crucial to any effective cost-saving process. In health care, as in other business units, the ultimate goal is to produce products or services at an efficient level of cost. The product of a healthcare business is a specific encounter of care, an inpatient discharge, or an outpatient visit. Management's task is to develop a production process that can generate high-quality encounters of care at efficient cost levels. Although some policy advocates might stipulate that healthcare executives should be more concerned about the efficacy of what they produce (e.g., do we really need more hip replacements?), those decisions are best left to physicians and policy-makers. Healthcare executives are charged with providing services ordered by physicians at the highest level of quality and cost efficiency.

Cost per encounter can be expressed simply as the product of three key cost drivers:

  •   Intensity of services
  •   Productivity/efficiency
  •   Resource prices/salaries and wages
     

Intensity of services. The mix and quantity of services that are combined to produce the encounter of care define the intensity of services. For example, a five-day inpatient stay for pneumonia includes five days of nursing care, a series of drugs, laboratory procedures, and many more ancillary services. There is often wide variation in the intensity of services across patients and across hospital providers. Although many intensity factors are physician driven, healthcare managers can and do play an instrumental role in explaining the relative costs associated with alternative treatment protocols. Lowering intensity of services for a defined encounter of care can lead to reductions in total cost per encounter-again, the primary goal.

Productivity or efficiency. The costs incurred to produce a specific procedure that is part of an overall encounter of care represent productivity or efficiency. For example, what staffing mix and levels are used to produce a day of nursing care in specific nursing units? Although intensity and productivity are related, they are different. To make the distinction, nursing intensity would involve the number of nursing days involved in the patient stay. Nursing productivity would measure the number of hours nurses worked to provide one day of nursing care.

Cost efficiency is usually associated with specific cost centers or departments, and the cost per unit of service in that cost center (e.g., cost per laboratory procedure) is often referred to as the departmental measure of efficiency. Lowering the unit costs of departmental products that together constitute a patient encounter can reduce the total cost of the encounter.

Resource prices or salaries. As the price paid to hire staff or purchase supplies and drugs increases, the encounter of care becomes more expensive. For example, a hospital can minimize the length of stay (LOS) associated with an inpatient encounter and maintain low nurse staffing ratios, but if it pays its nurses salaries that are 25 percent higher than those paid by its peers, its overall costs may still be high.

How the Drivers of Cost Relate

The three drivers of cost per encounter are fairly basic and understood by most healthcare financial executives. However, the relationships among them are more easily missed. Lowering costs in any given area can produce an adverse effect in one of the other two areas. For example, a hospital may have an all-RN staff, which increases the cost per day of nursing care but may not increase the overall cost per encounter. Perhaps the all-RN staff reduces the LOS and drives the total cost per encounter down. It is the cost per encounter that is of ultimate concern-not the specific cost of any intermediate procedure produced in a cost center. Similarly, it is possible to have a high cost per unit of operating room time, but low total operating room costs because of reduced operating room intensity. The lesson to be learned is a simple one. Focus first on the cost per encounter, not on salaries, staffing, or use of ancillaries. There are trade-offs that can and do exist among all three areas.

Quality of care is also important. If cost per encounter is high and yields a higher quality product, then the higher cost can be justified. However, the existence of higher cost without any objective evidence of quality enhancement needs to be seriously challenged by healthcare executives who are charged with maintaining the financial solvency of their organizations.

The Patient Encounter Production Function

A useful approach to evaluate cost efficiencies across healthcare organizations is the economist's production function. Simply put, a production function specifies the relationship between output and the related inputs required to produce the output. When converting this approach to a healthcare setting, healthcare financial managers want to know what inputs or departmental products (e.g., nursing days, laboratory procedures, and other ancillary services) are normally expected to be used to provide one encounter of a certain type.

To complete the cost analysis, healthcare financial managers also need to know what the expected cost of each of those required inputs will be. Cost of a certain encounter can then be expressed mathematically as:

Cost = (Q1 x C1) + (Q2 x C2) + ……+ (Qn x Cn)
Where Q = quantity of units and C = cost per unit

Case Example: MS-DRG 233

A case example for a specific encounter, MS-DRG 233 (coronary bypass with cardiac catheterization with major complication/comorbidity [MCC]), illustrates the power of cost analysis with the production function construct. To realize the potential of the analysis, the following data elements must be present:

  •   Detailed line item level claim data for the encounter to be reviewed at the hospital
  •   Detailed line item level claim data for the encounter to be reviewed for a defined benchmark group of hospitals
  •   Estimates of cost for the associated inputs present in both the sample hospital and the benchmark hospitals
     

The exhibit provides some comparative data for a sample hospital and a benchmark set of hospitals for the encounter category indicated by MS-DRG 233. This procedure is complex and costly and was selected to demonstrate the potential of the methodology that is proposed. The summary data in the exhibit break out the cost data by revenue code. Each of these cost values is the result of summing individual charge code lines to the revenue code level.

Exhibit 1 
exhibit-1-Cost Reduction

 

For example, if a laboratory procedure was used 20 times in the treatment of a specific MS-DRG and the estimated cost of the laboratory procedure was $75, the estimated total cost would be $1,500 (20 x $75). The estimated cost for specific line item charge codes is based upon departmental specific ratios of cost to charge (RCC). In the above example, the laboratory RCC might be 50 percent. A laboratory procedure with a charge of $150 would have an estimated cost of $75 (0.5 x $150). Although departmental RCCs are not perfect, they permit us to estimate costs in a uniform manner across hospitals.

The "type of unit" column includes terms such as units, days, and relative weight. This critical portion of the analysis defines the volume or intensity of service used as measured by days, units, or relative weights. The term days refers to nursing centers-routine, intensive care, and coronary care in this example. The term units simply designates the number of times a specific charge code item was used. For example, the drug Amiodarone HCl may have appeared on the claim one time with two units used. The units value for this code would then be two.

The last term, relative  

weight, references the number of weighted units used. The weighting system uses the weights developed by the Centers for Medicare & Medicaid Services for outpatient payment, known as ambulatory payment classification (APC). Nuances in the weighting exist to apply the weights for cost analysis. For example, laboratory procedures do not often have APC weights, but they are paid on a fee schedule basis. We have converted the fee schedule paid items to an APC weight. To illustrate, the lab procedure Assay of troponin, quant with CPT® code 84484, was converted to an APC weight of 0.2202. The use of these weights permits us to analyze the intensity of services for many ancillary departments with large numbers of different procedures. The use of APC weights also provide a mechanism for assessing relative resource intensity and case mix at the revenue code level. For example, it would be interesting to know that one hospital uses an average of 25 laboratory procedures to treat a patient encounter while another hospital uses only 15 procedures. This information might suggest that the hospital that performs 25 laboratory procedures is more costly, but the relative resource intensity or case mix of those laboratory procedures could be totally different. The use of APC weights can help identify case mix issues much more clearly than simple procedure counts.

Detailed Revenue Code Analysis

A significant amount of the unfavorable cost variation between the hospital and its benchmark group is attributable to three areas: nursing, laboratory, and drugs requiring specific identification (with relative weight).

The exhibit shows the detail for th

e three nursing centers. The total cost variance in these three areas is $5,967. Most of this variance is due to a longer LOS-16.44 days compared with 12.97. The LOS at Sample Hospital is 27 percent higher than the benchmark average, while the average cost per day over all nursing categories is only 6 percent higher at Sample Hospital.

Exhibit 2
exhibit-2-Cost Reduction
Intensive care costs, however, differ from the overall nursing assessment. The LOS at Sample Hospital is lower than the benchmark group, but the cost per day is 32 percent higher at Sample Hospital. The exhibit shows that 40 percent (2.63/6.52) of the total days in the intensive care unit (ICU) revenue code 20X were in revenue code 206, ICU Intermediate Care. This finding would suggest that a large number of the benchmark hospitals are using intermediate ICU beds at significantly lower costs.

Exhibit 3
exhibit-3-Cost Reduction

A similar finding is observed when the Coronary Care revenue code is broken out. Sample Hospital is not using intermediate ICU or CCU units, which increases the total cost. Further, the hospital is not realizing any reduction in LOS from the higher intensity nursing care. Finally, although quality data are not shown, mortality rates at Sample Hospital are similar to the Benchmark group averages. In sum, Sample Hospital has significantly higher nursing costs without any measurable quality or LOS advantages.

Laboratory costs at Sample Hospital also exhibit an unfavorable variance. Although there are 267 lab procedures in this revenue group that were used by some of the benchmark hospitals, Sample Hospital used only 29 lab procedures. A review of all of the codes shows that one cause of the unfavorable variance is directly associated with significantly greater usage of blood gas procedures, as shown in the exhibit . Given the relative weight of 0.4259, Sample Hospital has total weight in this one lab procedure of 8.19 compared with 4.40 at the benchmark hospitals. Although the relative weight provides a method of assessing overall lab usage aggregating multiple lab procedures, it is not necessary when making comparisons that involve only one lab procedure. Using the weight of 0.4259, Sample Hospital performed 19.22 blood gas tests per case (8.19/0.4259), while the benchmark group performed 10.33 (4.4/0.4259) blood gas tests per case. Three factors are increasing blood gas costs at Sample Hospital compared with the benchmark group. First, LOS is higher at Sample Hospital-16.44 compared with 12.97 at the benchmark group. Second, Sample Hospital is performing 1.17 of these tests per day (19.22/16.44) compared with 0.8 tests per day (10.33/12.97) at the benchmark group. Third, cost per test is higher at Sample Hospital-$175.61 compared with $155.62.

Exhibit 4
exhibit-4-Cost Reduction

The last area of significant cost variation to be reviewed is "Drugs Requiring Specific Identification-with Relative Weights." The variation in total for this area is an unfavorable $2,209. As the exhibit on page 59 shows, most of the variation is attributable to significantly greater use of three drugs. The use of these drugs is a physician preference designed to avoid the use of transfusions during surgery. An examination of the data under revenue code 39X, Blood Storage and Processing, in the exhibit shows some offset. Sample Hospital's costs are $452 less than the benchmark group's costs. This difference offsets only 22 percent of the $2,021 of higher cost incurred with the use of these three drugs. Some cost benefit analysis is clearly needed in this area. In short, is there a quantitative improvement in quality of care to offset the higher cost of this treatment protocol?

Exhibit 5
exhibit-5-Cost Reduction

A Powerful Tool in Detailed Charge Code Analysis

Cost reduction will be the primary weapon for dealing with ever-tightening payments from major healthcare payers. Revenue management can be helpful, but its effects are short-term and limited. Reductions in cost result from actions taken in two primary areas. First, the utilization of services such as nursing days, lab tests, and drugs can be reduced on a per-encounter basis. Second, the cost efficiency with which nursing care and other ancillary procedures are produced can be improved.

The detailed charge code analysis presented here can be a powerful tool to identify specific areas for cost reduction, which can lead to large and sustainable improvements. The primary constraint hindering widespread use of the analysis described here is the availability of benchmark data. Few organizations collect the massive amount of detailed line item charge code data that are critical to the development of reasonable benchmark standards. The databases can, however, be developed as illustrated in the example described here, which is based upon more than 200 acute care hospitals across the country.

William O. Cleverley, PhD, is president, Cleverley and Associates, Worthington, Ohio, and a member of HFMA's Central Ohio Chapter
(bcleverley@cleverleyassociates.com).

James O. Cleverley is principal, Cleverley and Associates, Worthington, Ohio, and a member of HFMA's Central Ohio Chapter
(jcleverley@cleverleyassociates.com).

Publication Date: Monday, March 01, 2010

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