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Impact of CK-MB testing policies on hospital length of stay and laboratory costs for patients with myocardial infarction or chest pain

¹ Clinical Chemistry Laboratory, Hartford Hospital, 80 Seymour St., Hartford, CT, 06102. Fax 860-545-5206.

² Office of Biostatistical Consultation, University of Connecticut Health Center, 263 Farmington Ave., Farmington, CT 06030.
^a Author for correspondence.

	Abstract

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We obtained data on hospital length of stay (LOS) and total laboratory charges for Medicare patients admitted to 82 hospitals in Massachusetts during 1994. Five Diagnosis Related Groups (DRGs) were selected: surviving acute myocardial infarction (AMI) with, and without, complications; AMI with death; angina pectoris; and chest pain. The hospitals were grouped according to their laboratory policies for testing CK-MB (e.g., frequency of assay runs; information obtained by telephone survey). The study was conducted to determine whether there was an association between turnaround times for results and LOS for cardiac DRGs. The mean LOS for AMIs with complication for 1513 patients admitted to 22 hospitals whose laboratories perform CK-MB testing once or twice daily was 8.4 days [95% confidence interval (CI): 8.2–8.7]. In contrast, the mean LOS for hospitals with CK-MB test policies of at least 3 runs daily or random-access stat was significantly (P <0.05) lower, 7.7 days (CI: 7.4–8.0 and 7.5–7.9, respectively). Overall laboratory charges were lower in the hospitals with shorter LOS. With one exception, there was no significant difference in LOS between patients with DRGs of angina pectoris or chest pain or other AMI DRGs. For AMI, a CK-MB testing policy that produces shorter turnaround times may be justified because of an association with reductions in LOS and overall laboratory costs.

Key Words: indexing terms: laboratory management • turnaround times • outcomes analysis • Diagnosis Related Group • random-access analysis • creatine kinase • isoenzymes

	Introduction

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Hospitals and their clinical laboratories are under increasing pressure by third-party payers to reduce costs by controlling the utilization of clinical services. Establishment of clinical practice guidelines is one means by which test-ordering patterns for a specific Diagnosis Related Group (DRG) can be standardized.¹ For DRGs that have a heavy laboratory component, clinical scientists should play an active role in establishing efficient testing policies, especially regarding the proper selection of available tests, the manner and frequency of testing, the reporting of turnaround times, and laboratory costs. Hypothesis-driven outcomes research can be helpful in determining how clinical services can be most efficiently delivered. Clinical outcome measures include rates for morbidity, mortality, and disease recurrence as well as quality-of-life assessments. Financial outcomes should be measured from an overall hospital cost for delivery of healthcare and not be isolated to laboratory expenses alone. If studies demonstrate that added tests or greater frequencies of testing lead to better clinical or financial outcomes, utilization of laboratory resources should be increased rather than decreased.

The practice of cardiology continues to evolve at a rapid rate, such that utilization of cardiac markers for patients with ischemic heart disease is one area in which outcomes analysis is particularly warranted. Efficient testing policies will have a dramatic effect on costs, given the high number of hospital admissions per year for cardiac patients (>700 000 for Medicare alone). Moreover, Medicare weighting factors for cardiac DRGs (Table 1 ) are among the highest of all medical DRGs listed by the Health Care Financing Administration (HCFA) (1). The clinical chemistry laboratory has traditionally played a large role in triage, diagnosis, and management of coronary artery disease. The assay for creatine kinase (CK) MB isoenzyme has become standard practice for serologic diagnosis of acute myocardial infarction (AMI). Guidelines established by the American College of Physicians recommend use of CK and lactate dehydrogenase isoenzymes at admission and at 12 and 24 h after admission (2). In uncomplicated AMI cases, activities of total CK and CK-MB increase and return to normal limits within 3–4 days, usually before the patient has been discharged. Some AMI patients, however, develop complications—e.g., congestive heart failure, postinfarction angina, cardiogenic shock, and reinfarction—either while hospitalized or within a few weeks or months after discharge (3)(4)(5). Thus, it is typical practice for cardiologists to continue ordering assays of total CK and CK-MB until the day of discharge. Some laboratories have elected to use myoglobin or CK-MB isoforms to detect new injury attributable to complications, because these markers rapidly return to normal after the initial insult (6)(7); however, use of these markers is not yet as widespread as CK-MB testing. Although not specifically documented, lactate dehydrogenase isoenzymes and cardiac troponins T and I are not likely to be as useful as CK-MB for detecting postinfarction ischemia because their concentrations remain abnormally high for a week or more after AMI, obscuring the release of proteins and enzymes from any subsequent injury (8)(9).

The present study was designed to determine whether the frequency of CK-MB testing is associated with hospital lengths of stay (LOS) and laboratory charges for cardiac DRGs. A prospective placebo-controlled LOS trial—i.e., at a single hospital in which some patients would receive stat CK-MB results and others would receive batched results—cannot be justified on an ethical basis. Therefore, we compared retrospective data from one hospital with those from another for a homogeneously reimbursed patient population.

	Materials and Methods

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los database
LOS data for Medicare patients admitted to 84 Massachusetts hospitals in 1994 was purchased from HCIA Inc. (Baltimore, MD) for the following DRGs: no. 121, circulatory disorders with AMI with complications; no. 122, circulatory disorders with AMI without complications; no. 123, circulatory disorders with AMI and death; no. 140, angina pectoris; and no. 143, chest pain (10). For DRG 123, AMI patients with cardiovascular complications who died were not included (10). All hospital admissions were used, not just those admitted to a coronary care unit. HCFA data specific for these DRGs (1) are shown in Table 1 .

Medicare patients were chosen because the reimbursement policies are prospective and because financial incentives to reduce LOS and test utilization costs are uniform across the state. We were not able to use the All Patient Refined DRGs classifications, because these data were not available until after 1994 (11). The All Patient Refined DRG index, which incorporates complexity subclasses for each DRG (ranked from minor to extreme), would have been useful to subclassify hospital and patient groups.

Total numbers of patients in each DRG were broken down into age categories of <25-44, 45–64, 65–90 (in 5-year increments), and >90 years. Because these were all Medicare patients, most of them were >65. We also obtained the discharge destination (to home, short-term hospital, skilled nursing home, intermediate medical care center, home health, or discharged against medical advice) information for these patients and their total associated laboratory charges.

Data from two hospitals were omitted because one is now closed (CK-MB testing policy was thus unavailable) and the other does not have an on-site laboratory. Data from the remaining 82 hospitals are the basis for this analysis.

hospital demographics
Massachusetts hospitals were broken down into bed sizes as listed in the 1994 American Hospital Association Guide (12). For this study, we classified hospitals with <150 beds as small. Those with bed sizes between 150 and 300 were classified as medium, and those with >300 beds were large. Hospitals were also classified according to location, in terms of population area served (denoted by the US Census) (13): Hospitals in rural areas served populations of <250 000; hospitals in small cities (Springfield or Worcester areas) served populations of 250 000–1 000 000; and urban hospitals (greater Boston area) served populations of >2.5 million (no areas in Massachusetts contained a population between 1.0 and 2.5 million). The DRG Case Mix Index for the individual providers was obtained from data published by HCFA (1). This index is an average of relative weights for medical and surgical DRGs admitted in each hospital. The higher the average, the greater the number of complicated cases seen by that provider. As shown in Table 1 , AMI DRGs have higher weighting factors than do non-AMI DRGs.

laboratory policies for CK-MB testing
Using Massachusetts hospital addresses and telephone numbers obtained from the American Hospital Association Guide (12), we contacted chemistry laboratory supervisors and appropriate bench technologists by telephone to determine what CK-MB testing policies they used during all or most of fiscal year 1994. The laboratories were accordingly categorized into one of four groups: Those conducting CK-MB testing once or twice daily were classified into group 1, slow; those conducting testing once per shift (three times daily) were classified into group 2, intermediate; laboratories that conducted testing as needed on a stat basis or in four or more scheduled batched runs per day were classified into group 3, fast. We classified into group 4 the laboratories that used immunoinhibition (INH screen) to determine CK-B subunit activity and either did not perform confirmation analysis (e.g., electrophoresis) or conducted confirmations on a nonstat basis. Laboratories that screened with INH and confirmed for CK-MB in real time were included in group 3. Although stat results can be obtained with INH, this assay can produce falsely high CK-MB values in the presence of interferences such as CK-BB and macro CK (14). Thus, we put hospitals that used INH without immediate confirmation into a separate group (group 4) to see whether the occasional false-positive INH result led to enough diagnostic ambiguity to affect LOS.

statistical analysis
For each group, the mean (and SD) LOS was calculated from the total numbers of patients and LOS values reported for each hospital. Patients whose LOS exceeded the HCFA outlier thresholds, as defined in Table 1 , were removed from the database. The 95% confidence intervals (CI) were computed from an established formula (15). One-way analysis of variance (ANOVA) was used to compare means across groups. Significant differences between LOS values were determined by using the Tukey –HSD test, with significance indicated by P <0.05. We also conducted a correlation analysis with LOS as an outcome measure and patient's age as a covariate; P <0.05 for Pearson's correlation coefficient was considered significant. Data were entered and evaluated by using a commercial PC-based package (Ver. 6.1; Statistical Package for the Social Sciences, Chicago, IL).

	Results

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The telephone survey revealed that all hospitals in Massachusetts measured total CK with automated chemistry analyzers and provided stat results on a regular basis. Some laboratories used total CK to determine whether CK-MB analysis was warranted (i.e., low values resulted in cancellation of the CK-MB test request). Table 2 tabulates the CK-MB assays cited in this study. Laboratories reporting use of INH were linked to high-volume general chemistry analyzers. Only one manufacturer produced assays based on immunoprecipitation and column chromatography/INH. Immunoassays (reporting in units of mass) from several different manufacturers were used.

In general, surviving AMI patients with complications (DRG 121) had longer mean LOS, 7.9 days (CI: 7.8–8.0, n = 5984, combining results for all hospitals), than did those without complications (DRG 122), 5.9 days (CI: 5.8–6.0, n = 2820). The LOS for AMI patients who died (DRG 123), 4.9 days (CI: 4.6–5.1, n = 1397), was statistically lower than for either of the other AMI groups. For patients in whom AMI was ruled out, those with a primary diagnosis of angina pectoris (DRG 140) had longer LOS, 3.4 days (CI: 3.4–3.5, n = 8198), than did those with chest pain (DRG 143), 2.5 days (CI: 2.4–2.5, n = 5122). These LOS results are similar to published national means for 1994 (Table 1 ).

Table 3 , comparing effect of hospital size on LOS, shows that AMI patients (especially DRG 121) in small hospitals had significantly shorter mean LOS times than those in medium-size and large hospitals. An age breakdown of the DRG 121 cases showed that the numbers of enrolled patients at ages 85–90 and >90 years were identical for the different hospital sizes: respectively 12.2% and 6.4% for small hospitals, 12.0% and 6.5% for medium, and 11.7% and 5.5% for large. However, there were some differences in discharge destinations according to hospital sizes. For DRG 121 cases, small and medium-size hospitals had a larger percentage of their patients transferred to other short-term hospitals (25.5% and 24.3%, respectively) than did large hospitals (14.1%), which are presumably able to handle the more difficult referral cases. No consistent trend was observed between hospital size for any of the other DRGs studied.

Table 3 also shows the mean LOS as a function of the geographic area serviced by the hospital. Although we saw significant differences between some groups, there was no consistent trend: e.g., hospitals in small cities had a longer LOS for DRG 121 than did hospitals in rural and urban areas, whereas for DRG 143 the rural hospitals had slightly longer LOS than did the small city and urban hospitals.

Table 4 lists the LOS for various AMI and AMI-rule-out DRGs, grouped according to CK-MB testing policies. For DRGs 121, 122, and 123, there were no significant differences in LOS between groups 2, 3, and 4 [i.e., intermediate assay frequency (at least every 8 h), fast (stat analysis), and INH screen]. We therefore combined the data for groups 2–4 and obtained an LOS for DRG 121 of 7.8 days (CI: 7.6–7.9, n = 4471). In contrast, laboratories who had slow CK-MB reporting policies (once or twice per day; group 1) had significantly longer LOS for DRG 121: 8.4 days (CI: 8.2–8.7, n = 1513). Except for one marginal exception (DRG 143, group 1 vs 3), we observed no significant difference between group 1 and any other group for DRGs 122, 123, 140, and 143.

Table 4 also shows the average total laboratory charge per patient in these various DRG groups. Although there was no direct correlation between laboratory charges and CK-MB turnaround times, patients in group 1 hospitals incurred more total laboratory charges for DRGs 121–123 than did those in any of the other groups.

Factors such as hospital size, location, age distribution of patients, discharge destination, and DRG Case Mix Index were computed (Table 5 ) to determine whether these influenced the observation that group 1 hospitals had longer mean LOS for DRG 121 patients. Mean bed size had no significant effect because each test-frequency group contained an approximately equal mix of small, medium, and large hospitals (see group 1 vs combined groups 2–4). With regards to geographic locations, group 1 had a higher percentage of hospitals located in urban areas and a lower percentage located in rural areas than did combined groups 2–4. For age of the patients presenting to hospitals, group 1 had a slightly lower percentage of patients at 85–90 (6.7%) and >90 years (3.1%) than did the composite of groups 2–4 (10.6% and 5.1%, respectively). However, the Pearson correlation analysis between LOS and age (combining 85–90 and >90 years groups) for all hospitals showed no significant difference for any of the DRGs (e.g., P = 0.7 for DRG 121). Discharge destinations to short-term hospitals, and DRG Case Mix Index, were also not significantly different between group 1 and any other individual group or combined groups 2–4 (Table 5 ).

	Discussion

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Assays for CK-MB differ in performance and convenience for stat analysis (16)(17). Manual electrophoresis is labor intensive and not practical for stat reporting. Many laboratories in group 1 perform electrophoresis once or twice per day. If electrophoresis is to be used for stat testing, an automated analyzer that can deliver stat results within 30 min should be used instead of manual electrophoresis, which requires 2–3 h for completion (6). CK-B INH assays are inexpensive and can be coupled to automated chemistry analyzers to enable stat delivery of results. In this study, because the LOS for all AMI and non-AMI DRGs for hospitals with laboratories using INH (group 4) was identical to that for laboratories performing mass assays on a stat basis, one might conclude that INH is the assay of choice. However, INH is subject to interferences from CK-BB and macro CK (14), which can lead to falsely positive test results. Most laboratories surveyed used a more-definitive CK-MB assay such as electrophoresis or immunoassay in cases where INH results had led to ambiguous interpretations and delays in the management and triage of patients. CK-MB immunoassays have evolved from manual to automated assays, first onto batch analyzers and now onto random-access instruments. Stat testing on manual or batch instruments is not efficient because reagents and controls have to be loaded before each analysis. Random-access analyzers are more conducive for stat testing because on-board reagent storage allows immediate access.

Previous outcomes studies for cardiac markers have focused on the selection of available tests, and the need and frequency of serial sample testing. For example, Fisher and Plotnick (18) suggested that aspartate aminotransferase has no useful role in AMI diagnosis. Lewandrowski et al. (19) instituted a mandatory approval program for lactate dehydrogenase isoenzymes and demonstrated a >99% decrease in testing. Saxena et al. (20), examining the appropriateness of the timing of serial tests relative to the time of admission, found that only a minority of tests were ordered according to recommended protocols. None of these studies reported the effect of changing test-ordering patterns on LOS. In the only study comparing random-access vs batch CK-MB testing, Anderson et al. (21) showed that changing the testing policy from batch to random-access reduced LOS for AMI patients with a nondiagnostic ECG from 8.2 to 6.3 days and laboratory costs from $2194 to $1924. These results were not statistically significant because the two groups studied contained only 23 patients; for patients in whom an AMI was ruled out, however, the LOS difference (4.4 vs 3.0 days) was significant. Their use of historic data for the control group may have biased results because the reductions in LOS may have been caused by increasing pressure in managed care to discharge all admitted patients.

Our study differs from the others because results are computed for large numbers of patients and the lengths of stay are compared over one period of time rather than sequentially. However, different medical practices from one institution to another create many other uncontrollable variables; a more ideal study would compare LOS from matched cases from different institutions. Because such data were not available to us, we attempted to characterize the CK-MB testing-policy groups according to hospital and patient demographics. For example, one might expect a shorter mean LOS for hospitals that had a disproportionately high rate of patient transfers to tertiary institutions; however, our data showed that this was not the case: Because there were no differences in DRG mix, hospitals with an infrequent CK-MB testing policy did not see inordinate numbers of complicated cases in comparison with hospitals with more frequent testing policies. Group 1 did have more patients <85 years, which might favor a shorter LOS, but the Pearson correlation showed no significant relation between these age groups and LOS. A rural hospital might also be slower in adopting the new managed-care practices, but Table 3 showed no consistent trend between LOS and geographic location.

It is possible that laboratories with liberal CK-MB testing policies practice at hospitals that are progressive and more responsive to changes in reimbursement polices. Such institutions might also be biased towards being more aggressive in reducing the LOS for all DRGs. Data for the chest pain DRG 143 were used as a control because this is a noncardiac DRG. Because the LOS for DRG 143 patients in group 1 institutions was no longer than for any other group, we suggest that the higher LOS for group 1 DRG 121 patients was not linked to the progressiveness of the individual hospitals.

We conclude that infrequent CK-MB testing policy is associated with a longer LOS (by 0.7 days) and higher laboratory costs for cardiac patients. The potential impact is tremendous when this difference is multiplied by the millions of cardiac patients seen in the US each year. LOS may be less affected by CK-MB testing policies in AMI-rule-out groups because, in most angina and chest pain cases, stat total CK results are available in all hospitals—and are usually within the normal range, which often obviates the need for further testing for CK-MB. Given that the clinical status of AMI patients is not generally made available to the laboratory, we suggest that all samples be tested on a frequent or stat basis (>3 times a day). The incremental expense for delivering the CK-MB results on a more timely basis does not outweigh the additional overall laboratory costs incurred by keeping patients in the hospital for the extra hours until the next testing run.

	Acknowledgments

 
We thank Carin Salonia, Decision Support Services of Hartford Hospital, for in-house LOS data, and Barry Utterbaugh of HCIA Inc. (Baltimore, MD), for assistance in specifying the Massachusetts outcome databases used in this study.

	Footnotes

 
¹ Nonstandard abbreviations: LOS, length of stay; DRG, Diagnosis Related Group; AMI, acute myocardial infarction; HCFA, Health Care Financing Administration; CK, creatine kinase; INH, immunoinhibition; CI, 95% confidence interval.

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This Article Abstract Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Citation Map Services Email this article to a friend Similar articles in this journal Similar articles in Web of Science Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Web of Science (24) Citing Articles via Google Scholar Google Scholar Articles by Wu, A. H. B. Articles by Clive, J. M. Search for Related Content PubMed PubMed Citation Articles by Wu, A. H. B. Articles by Clive, J. M. Related Collections Laboratory Management Evidence Based Laboratory Medicine and Test Utilization Proteomics and Protein Markers