Healthcare spending exceeded $2.5 trillion in 2007, and payments to hospitals represented the largest portion of this spending (more than 30%), equaling the combined cost of physician services and prescription drugs.[1, 2] Researchers and policymakers have emphasized the need to improve the value of hospital care in the United States, but this has been challenging, in part because of the difficulty in identifying hospitals that have high resource utilization relative to their peers.[3, 4, 5, 6, 7, 8, 9, 10, 11]

Most hospitals calculate their costs using internal accounting systems that determine resource utilization via relative value units (RVUs).[7, 8] RVU‐derived costs, also known as hospital reported costs, have proven to be an excellent method for quantifying what it costs a given hospital to provide a treatment, test, or procedure. However, RVU‐based costs are less useful for comparing resource utilization across hospitals because the cost to provide a treatment or service varies widely across hospitals. The cost of an item calculated using RVUs includes not just the item itself, but also a portion of the fixed costs of the hospital (overhead, labor, and infrastructure investments such as electronic records, new buildings, or expensive radiological or surgical equipment).[12] These costs vary by institution, patient population, region of the country, teaching status, and many other variables, making it difficult to identify resource utilization across hospitals.[13, 14]

Recently, a few claims‐based multi‐institutional datasets have begun incorporating item‐level RVU‐based costs derived directly from the cost accounting systems of participating institutions.[15] Such datasets allow researchers to compare reported costs of care from hospital to hospital, but because of the limitations we described above, they still cannot be used to answer the question: Which hospitals with higher costs of care are actually providing more treatments and services to patients?

To better facilitate the comparison of resource utilization patterns across hospitals, we standardized the unit costs of all treatments and services across hospitals by applying a single cost to every item across hospitals. This standardized cost allowed to compare utilization of that item (and the 15,000 other items in the database) across hospitals. We then compared estimates of resource utilization as measured by the 2 approaches: standardized and RVU‐based costs.

METHODS

Assignment of Standardized Costs

We defined reported cost as the RVU‐based cost per item in the database. We then calculated the median across hospitals for each item in the database and set this as the standardized unit cost of that item at every hospital (Figure 1). Once standardized costs were assigned at the item level, we summed the costs of all items assigned to each patient and calculated the standardized cost of a hospitalization per patient at each hospital.

Figure 1

RESULTS

The 234 hospitals included in the analysis contributed a total of 165,647 hospitalizations, with the number of hospitalizations ranging from 33 to 2,772 hospitalizations per hospital (see Supporting Table 1 in the online version of this article). Most were located in urban areas (84%), and many were in the southern United States (42%). The median hospital reported cost per hospitalization was $6,535, with an interquartile range of $5,541 to $7,454. The median standardized cost per hospitalization was $6,602, with a range of $5,866 to $7,386. The interquartile ratio (Q75/Q25) of the reported costs of a hospitalization was 1.35. After costs were standardized, the interquartile ratio fell to 1.26, indicating that variation decreased. We found that the median hospital reported cost per day was $1,651, with an IQR of $1,400 to $1,933 (ratio 1.38), whereas the median standardized cost per day was $1,640, with an IQR of $1,511 to $1,812 (ratio 1.20).

There were more than 15,000 items (eg, treatments, tests, and supplies) that received a standardized charge code in our cohort. These were divided into 11 summary departments and 40 standard departments (see Supporting Table 2 in the online version of this article). We observed a high level of variation in the reported costs of individual items: the reported costs of a day of room and board in an ICU ranged from $773 at hospitals at the 10th percentile to $2,471 at the 90th percentile (Table 1.). The standardized cost of a day of ICU room and board was $1,577. We also observed variation in the reported costs of items across item categories. Although a day of medical room and board showed a 3‐fold difference between the 10th and 90th percentile, we observed a more than 10‐fold difference in the reported cost of an echocardiogram, from $31 at the 10th percentile to $356 at the 90th percentile. After examining the hospital‐level cost for a basket of goods, we found variation in the reported costs for these items across hospitals, with a 10th percentile cost of $1,552 and a 90th percentile cost of $3,967.

We found that 46 (20%) hospitals had reported costs of hospitalizations that were 25% greater than standardized costs (Figure 2). This group of hospitals had overestimated reported costs of utilization; 146 (62%) had reported costs within 25% of standardized costs, and 42 (17%) had reported costs that were 25% less than standardized costs (indicating that reported costs underestimated utilization). We examined the relationship between hospital characteristics and strata and found no significant association between the reported to standardized cost ratio and number of beds, teaching status, or urban location (Table 2). Hospitals in the Midwest and South were more likely to have a lower reported cost of hospitalizations, whereas hospitals in the West were more likely to have higher reported costs (P<0.001). When using the CV to compare reported costs to standardized costs, we found that per‐day standardized costs showed reduced variance (P=0.0238), but there was no significant difference in variance of the reported and standardized costs when examining the entire hospitalization (P=0.1423). At the level of the hospitalization, the Spearman correlation coefficient between reported and standardized cost was 0.89.

Figure 2

To better understand how hospitals can achieve high reported costs through different mechanisms, we more closely examined 3 hospitals with similar reported costs (Figure 3). These hospitals represented low, average, and high utilization according to their standardized costs, but had similar average per‐hospitalization reported costs: $11,643, $11,787, and $11,892, respectively. The corresponding standardized costs were $8,757, $11,169, and $15,978. The hospital with high utilization ($15,978 in standardized costs) was accounted for by increased use of supplies and other services. In contrast, the low‐ and average‐utilization hospitals had proportionally lower standardized costs across categories, with the greatest percentage of spending going toward room and board (includes nursing).

Figure 3

DISCUSSION

In a large national sample of hospitals, we observed variation in the reported costs for a uniform basket of goods, with a more than 2‐fold difference in cost between the 10th and 90th percentile hospitals. These findings suggest that reported costs have limited ability to reliably describe differences in utilization across hospitals. In contrast, when we applied standardized costs, the variance of per‐day costs decreased significantly, and the interquartile ratio of per‐day and hospitalization costs decreased as well, suggesting less variation in utilization across hospitals than would have been inferred from a comparison of reported costs. Applying a single, standard cost to all items can facilitate comparisons of utilization between hospitals (Figure 1). Standardized costs will give hospitals the potential to compare their utilization to their competitors and will facilitate research that examines the comparative effectiveness of high and low utilization in the management of medical and surgical conditions.

The reported to standardized cost ratio is another useful tool. It indicates whether the hospital's reported costs exaggerate its utilization relative to other hospitals. In this study, we found that a significant proportion of hospitals (20%) had reported costs that exceeded standardized costs by more than 25%. These hospitals have higher infrastructure, labor, or acquisition costs relative to their peers. To the extent that these hospitals might wish to lower the cost of care at their institution, they could focus on renegotiating purchasing or labor contracts, identifying areas where they may be overstaffed, or holding off on future infrastructure investments (Table 3).[14] In contrast, 17% of hospitals had reported costs that were 25% less than standardized costs. High‐cost hospitals in this group are therefore providing more treatments and testing to patients relative to their peers and could focus cost‐control efforts on reducing unnecessary utilization and duplicative testing.[20] Our examination of the hospital with high reported costs and very high utilization revealed a high percentage of supplies and other items, which is a category used primarily for nursing expenditures (Figure 3). Because the use of nursing services is directly related to days spent in the hospital, this hospital may wish to more closely examine specific strategies for reducing length of stay.

We did not find a consistent association between the reported to standardized cost ratio and hospital characteristics. This is an important finding that contradicts prior work examining associations between hospital characteristics and costs for heart failure patients,[21] further indicating the complexity of the relationship between fixed costs and variable costs and the difficulty in adjusting reported costs to calculate utilization. For example, small hospitals may have higher acquisition costs and more supply chain difficulties, but they may also have less technology, lower overhead costs, and fewer specialists to order tests and procedures. Hospital characteristics, such as urban location and teaching status, are commonly used as adjustors in cost studies because hospitals in urban areas with teaching missions (which often provide care to low‐income populations) are assumed to have higher fixed costs,[3, 4, 5, 6] but the lack of a consistent relationship between these characteristics and the standardized cost ratio may indicate that using these factors as adjustors for cost may not be effective and could even obscure differences in utilization between hospitals. Notably, we did find an association between hospital region and the reported to standardized cost ratio, but we hesitate to draw conclusions from this finding because the Premier database is imbalanced in terms of regional representation, with fewer hospitals in the Midwest and West and the bulk of the hospitals in the South.

Although standardized costs have great potential, this method has limitations as well. Standardized costs can only be applied when detailed billing data with item‐level costs are available. This is because calculation of standardized costs requires taking the median of item costs and applying the median cost across the database, maintaining the integrity of the relative cost of items to one another. The relative cost of items is preserved (ie, magnetic resonance imaging still costs more than an aspirin), which maintains the general scheme of RVU‐based costs while removing the noise of varying RVU‐based costs across hospitals.[7] Application of an arbitrary item cost would result in the loss of this relative cost difference. Because item costs are not available in traditional administrative datasets, these datasets would not be amenable to this method. However, highly detailed billing data are now being shared by hundreds of hospitals in the Premier network and the University Health System Consortium. These data are widely available to investigators, meaning that the generalizability of this method will only improve over time. It was also a limitation of the study that we chose a limited basket of items common to patients with heart failure to describe the range of reported costs and to provide a standardized snapshot by which to compare hospitals. Because we only included a few items, we may have overestimated or underestimated the range of reported costs for such a basket.

Standardized costs are a novel method for comparing utilization across hospitals. Used properly, they will help identify high‐ and low‐intensity providers of hospital care.

Healthcare spending exceeded $2.5 trillion in 2007, and payments to hospitals represented the largest portion of this spending (more than 30%), equaling the combined cost of physician services and prescription drugs.[1, 2] Researchers and policymakers have emphasized the need to improve the value of hospital care in the United States, but this has been challenging, in part because of the difficulty in identifying hospitals that have high resource utilization relative to their peers.[3, 4, 5, 6, 7, 8, 9, 10, 11]

Most hospitals calculate their costs using internal accounting systems that determine resource utilization via relative value units (RVUs).[7, 8] RVU‐derived costs, also known as hospital reported costs, have proven to be an excellent method for quantifying what it costs a given hospital to provide a treatment, test, or procedure. However, RVU‐based costs are less useful for comparing resource utilization across hospitals because the cost to provide a treatment or service varies widely across hospitals. The cost of an item calculated using RVUs includes not just the item itself, but also a portion of the fixed costs of the hospital (overhead, labor, and infrastructure investments such as electronic records, new buildings, or expensive radiological or surgical equipment).[12] These costs vary by institution, patient population, region of the country, teaching status, and many other variables, making it difficult to identify resource utilization across hospitals.[13, 14]

Recently, a few claims‐based multi‐institutional datasets have begun incorporating item‐level RVU‐based costs derived directly from the cost accounting systems of participating institutions.[15] Such datasets allow researchers to compare reported costs of care from hospital to hospital, but because of the limitations we described above, they still cannot be used to answer the question: Which hospitals with higher costs of care are actually providing more treatments and services to patients?

To better facilitate the comparison of resource utilization patterns across hospitals, we standardized the unit costs of all treatments and services across hospitals by applying a single cost to every item across hospitals. This standardized cost allowed to compare utilization of that item (and the 15,000 other items in the database) across hospitals. We then compared estimates of resource utilization as measured by the 2 approaches: standardized and RVU‐based costs.

METHODS

Assignment of Standardized Costs

We defined reported cost as the RVU‐based cost per item in the database. We then calculated the median across hospitals for each item in the database and set this as the standardized unit cost of that item at every hospital (Figure 1). Once standardized costs were assigned at the item level, we summed the costs of all items assigned to each patient and calculated the standardized cost of a hospitalization per patient at each hospital.

Figure 1

RESULTS

The 234 hospitals included in the analysis contributed a total of 165,647 hospitalizations, with the number of hospitalizations ranging from 33 to 2,772 hospitalizations per hospital (see Supporting Table 1 in the online version of this article). Most were located in urban areas (84%), and many were in the southern United States (42%). The median hospital reported cost per hospitalization was $6,535, with an interquartile range of $5,541 to $7,454. The median standardized cost per hospitalization was $6,602, with a range of $5,866 to $7,386. The interquartile ratio (Q75/Q25) of the reported costs of a hospitalization was 1.35. After costs were standardized, the interquartile ratio fell to 1.26, indicating that variation decreased. We found that the median hospital reported cost per day was $1,651, with an IQR of $1,400 to $1,933 (ratio 1.38), whereas the median standardized cost per day was $1,640, with an IQR of $1,511 to $1,812 (ratio 1.20).

There were more than 15,000 items (eg, treatments, tests, and supplies) that received a standardized charge code in our cohort. These were divided into 11 summary departments and 40 standard departments (see Supporting Table 2 in the online version of this article). We observed a high level of variation in the reported costs of individual items: the reported costs of a day of room and board in an ICU ranged from $773 at hospitals at the 10th percentile to $2,471 at the 90th percentile (Table 1.). The standardized cost of a day of ICU room and board was $1,577. We also observed variation in the reported costs of items across item categories. Although a day of medical room and board showed a 3‐fold difference between the 10th and 90th percentile, we observed a more than 10‐fold difference in the reported cost of an echocardiogram, from $31 at the 10th percentile to $356 at the 90th percentile. After examining the hospital‐level cost for a basket of goods, we found variation in the reported costs for these items across hospitals, with a 10th percentile cost of $1,552 and a 90th percentile cost of $3,967.

We found that 46 (20%) hospitals had reported costs of hospitalizations that were 25% greater than standardized costs (Figure 2). This group of hospitals had overestimated reported costs of utilization; 146 (62%) had reported costs within 25% of standardized costs, and 42 (17%) had reported costs that were 25% less than standardized costs (indicating that reported costs underestimated utilization). We examined the relationship between hospital characteristics and strata and found no significant association between the reported to standardized cost ratio and number of beds, teaching status, or urban location (Table 2). Hospitals in the Midwest and South were more likely to have a lower reported cost of hospitalizations, whereas hospitals in the West were more likely to have higher reported costs (P<0.001). When using the CV to compare reported costs to standardized costs, we found that per‐day standardized costs showed reduced variance (P=0.0238), but there was no significant difference in variance of the reported and standardized costs when examining the entire hospitalization (P=0.1423). At the level of the hospitalization, the Spearman correlation coefficient between reported and standardized cost was 0.89.

Figure 2

To better understand how hospitals can achieve high reported costs through different mechanisms, we more closely examined 3 hospitals with similar reported costs (Figure 3). These hospitals represented low, average, and high utilization according to their standardized costs, but had similar average per‐hospitalization reported costs: $11,643, $11,787, and $11,892, respectively. The corresponding standardized costs were $8,757, $11,169, and $15,978. The hospital with high utilization ($15,978 in standardized costs) was accounted for by increased use of supplies and other services. In contrast, the low‐ and average‐utilization hospitals had proportionally lower standardized costs across categories, with the greatest percentage of spending going toward room and board (includes nursing).

Figure 3

DISCUSSION

In a large national sample of hospitals, we observed variation in the reported costs for a uniform basket of goods, with a more than 2‐fold difference in cost between the 10th and 90th percentile hospitals. These findings suggest that reported costs have limited ability to reliably describe differences in utilization across hospitals. In contrast, when we applied standardized costs, the variance of per‐day costs decreased significantly, and the interquartile ratio of per‐day and hospitalization costs decreased as well, suggesting less variation in utilization across hospitals than would have been inferred from a comparison of reported costs. Applying a single, standard cost to all items can facilitate comparisons of utilization between hospitals (Figure 1). Standardized costs will give hospitals the potential to compare their utilization to their competitors and will facilitate research that examines the comparative effectiveness of high and low utilization in the management of medical and surgical conditions.

The reported to standardized cost ratio is another useful tool. It indicates whether the hospital's reported costs exaggerate its utilization relative to other hospitals. In this study, we found that a significant proportion of hospitals (20%) had reported costs that exceeded standardized costs by more than 25%. These hospitals have higher infrastructure, labor, or acquisition costs relative to their peers. To the extent that these hospitals might wish to lower the cost of care at their institution, they could focus on renegotiating purchasing or labor contracts, identifying areas where they may be overstaffed, or holding off on future infrastructure investments (Table 3).[14] In contrast, 17% of hospitals had reported costs that were 25% less than standardized costs. High‐cost hospitals in this group are therefore providing more treatments and testing to patients relative to their peers and could focus cost‐control efforts on reducing unnecessary utilization and duplicative testing.[20] Our examination of the hospital with high reported costs and very high utilization revealed a high percentage of supplies and other items, which is a category used primarily for nursing expenditures (Figure 3). Because the use of nursing services is directly related to days spent in the hospital, this hospital may wish to more closely examine specific strategies for reducing length of stay.

We did not find a consistent association between the reported to standardized cost ratio and hospital characteristics. This is an important finding that contradicts prior work examining associations between hospital characteristics and costs for heart failure patients,[21] further indicating the complexity of the relationship between fixed costs and variable costs and the difficulty in adjusting reported costs to calculate utilization. For example, small hospitals may have higher acquisition costs and more supply chain difficulties, but they may also have less technology, lower overhead costs, and fewer specialists to order tests and procedures. Hospital characteristics, such as urban location and teaching status, are commonly used as adjustors in cost studies because hospitals in urban areas with teaching missions (which often provide care to low‐income populations) are assumed to have higher fixed costs,[3, 4, 5, 6] but the lack of a consistent relationship between these characteristics and the standardized cost ratio may indicate that using these factors as adjustors for cost may not be effective and could even obscure differences in utilization between hospitals. Notably, we did find an association between hospital region and the reported to standardized cost ratio, but we hesitate to draw conclusions from this finding because the Premier database is imbalanced in terms of regional representation, with fewer hospitals in the Midwest and West and the bulk of the hospitals in the South.

Although standardized costs have great potential, this method has limitations as well. Standardized costs can only be applied when detailed billing data with item‐level costs are available. This is because calculation of standardized costs requires taking the median of item costs and applying the median cost across the database, maintaining the integrity of the relative cost of items to one another. The relative cost of items is preserved (ie, magnetic resonance imaging still costs more than an aspirin), which maintains the general scheme of RVU‐based costs while removing the noise of varying RVU‐based costs across hospitals.[7] Application of an arbitrary item cost would result in the loss of this relative cost difference. Because item costs are not available in traditional administrative datasets, these datasets would not be amenable to this method. However, highly detailed billing data are now being shared by hundreds of hospitals in the Premier network and the University Health System Consortium. These data are widely available to investigators, meaning that the generalizability of this method will only improve over time. It was also a limitation of the study that we chose a limited basket of items common to patients with heart failure to describe the range of reported costs and to provide a standardized snapshot by which to compare hospitals. Because we only included a few items, we may have overestimated or underestimated the range of reported costs for such a basket.

Standardized costs are a novel method for comparing utilization across hospitals. Used properly, they will help identify high‐ and low‐intensity providers of hospital care.

Healthcare spending exceeded $2.5 trillion in 2007, and payments to hospitals represented the largest portion of this spending (more than 30%), equaling the combined cost of physician services and prescription drugs.[1, 2] Researchers and policymakers have emphasized the need to improve the value of hospital care in the United States, but this has been challenging, in part because of the difficulty in identifying hospitals that have high resource utilization relative to their peers.[3, 4, 5, 6, 7, 8, 9, 10, 11]

Most hospitals calculate their costs using internal accounting systems that determine resource utilization via relative value units (RVUs).[7, 8] RVU‐derived costs, also known as hospital reported costs, have proven to be an excellent method for quantifying what it costs a given hospital to provide a treatment, test, or procedure. However, RVU‐based costs are less useful for comparing resource utilization across hospitals because the cost to provide a treatment or service varies widely across hospitals. The cost of an item calculated using RVUs includes not just the item itself, but also a portion of the fixed costs of the hospital (overhead, labor, and infrastructure investments such as electronic records, new buildings, or expensive radiological or surgical equipment).[12] These costs vary by institution, patient population, region of the country, teaching status, and many other variables, making it difficult to identify resource utilization across hospitals.[13, 14]

Recently, a few claims‐based multi‐institutional datasets have begun incorporating item‐level RVU‐based costs derived directly from the cost accounting systems of participating institutions.[15] Such datasets allow researchers to compare reported costs of care from hospital to hospital, but because of the limitations we described above, they still cannot be used to answer the question: Which hospitals with higher costs of care are actually providing more treatments and services to patients?

To better facilitate the comparison of resource utilization patterns across hospitals, we standardized the unit costs of all treatments and services across hospitals by applying a single cost to every item across hospitals. This standardized cost allowed to compare utilization of that item (and the 15,000 other items in the database) across hospitals. We then compared estimates of resource utilization as measured by the 2 approaches: standardized and RVU‐based costs.

METHODS

Assignment of Standardized Costs

We defined reported cost as the RVU‐based cost per item in the database. We then calculated the median across hospitals for each item in the database and set this as the standardized unit cost of that item at every hospital (Figure 1). Once standardized costs were assigned at the item level, we summed the costs of all items assigned to each patient and calculated the standardized cost of a hospitalization per patient at each hospital.

Figure 1

RESULTS

The 234 hospitals included in the analysis contributed a total of 165,647 hospitalizations, with the number of hospitalizations ranging from 33 to 2,772 hospitalizations per hospital (see Supporting Table 1 in the online version of this article). Most were located in urban areas (84%), and many were in the southern United States (42%). The median hospital reported cost per hospitalization was $6,535, with an interquartile range of $5,541 to $7,454. The median standardized cost per hospitalization was $6,602, with a range of $5,866 to $7,386. The interquartile ratio (Q75/Q25) of the reported costs of a hospitalization was 1.35. After costs were standardized, the interquartile ratio fell to 1.26, indicating that variation decreased. We found that the median hospital reported cost per day was $1,651, with an IQR of $1,400 to $1,933 (ratio 1.38), whereas the median standardized cost per day was $1,640, with an IQR of $1,511 to $1,812 (ratio 1.20).

There were more than 15,000 items (eg, treatments, tests, and supplies) that received a standardized charge code in our cohort. These were divided into 11 summary departments and 40 standard departments (see Supporting Table 2 in the online version of this article). We observed a high level of variation in the reported costs of individual items: the reported costs of a day of room and board in an ICU ranged from $773 at hospitals at the 10th percentile to $2,471 at the 90th percentile (Table 1.). The standardized cost of a day of ICU room and board was $1,577. We also observed variation in the reported costs of items across item categories. Although a day of medical room and board showed a 3‐fold difference between the 10th and 90th percentile, we observed a more than 10‐fold difference in the reported cost of an echocardiogram, from $31 at the 10th percentile to $356 at the 90th percentile. After examining the hospital‐level cost for a basket of goods, we found variation in the reported costs for these items across hospitals, with a 10th percentile cost of $1,552 and a 90th percentile cost of $3,967.

We found that 46 (20%) hospitals had reported costs of hospitalizations that were 25% greater than standardized costs (Figure 2). This group of hospitals had overestimated reported costs of utilization; 146 (62%) had reported costs within 25% of standardized costs, and 42 (17%) had reported costs that were 25% less than standardized costs (indicating that reported costs underestimated utilization). We examined the relationship between hospital characteristics and strata and found no significant association between the reported to standardized cost ratio and number of beds, teaching status, or urban location (Table 2). Hospitals in the Midwest and South were more likely to have a lower reported cost of hospitalizations, whereas hospitals in the West were more likely to have higher reported costs (P<0.001). When using the CV to compare reported costs to standardized costs, we found that per‐day standardized costs showed reduced variance (P=0.0238), but there was no significant difference in variance of the reported and standardized costs when examining the entire hospitalization (P=0.1423). At the level of the hospitalization, the Spearman correlation coefficient between reported and standardized cost was 0.89.

Figure 2

To better understand how hospitals can achieve high reported costs through different mechanisms, we more closely examined 3 hospitals with similar reported costs (Figure 3). These hospitals represented low, average, and high utilization according to their standardized costs, but had similar average per‐hospitalization reported costs: $11,643, $11,787, and $11,892, respectively. The corresponding standardized costs were $8,757, $11,169, and $15,978. The hospital with high utilization ($15,978 in standardized costs) was accounted for by increased use of supplies and other services. In contrast, the low‐ and average‐utilization hospitals had proportionally lower standardized costs across categories, with the greatest percentage of spending going toward room and board (includes nursing).

Figure 3

DISCUSSION

In a large national sample of hospitals, we observed variation in the reported costs for a uniform basket of goods, with a more than 2‐fold difference in cost between the 10th and 90th percentile hospitals. These findings suggest that reported costs have limited ability to reliably describe differences in utilization across hospitals. In contrast, when we applied standardized costs, the variance of per‐day costs decreased significantly, and the interquartile ratio of per‐day and hospitalization costs decreased as well, suggesting less variation in utilization across hospitals than would have been inferred from a comparison of reported costs. Applying a single, standard cost to all items can facilitate comparisons of utilization between hospitals (Figure 1). Standardized costs will give hospitals the potential to compare their utilization to their competitors and will facilitate research that examines the comparative effectiveness of high and low utilization in the management of medical and surgical conditions.

The reported to standardized cost ratio is another useful tool. It indicates whether the hospital's reported costs exaggerate its utilization relative to other hospitals. In this study, we found that a significant proportion of hospitals (20%) had reported costs that exceeded standardized costs by more than 25%. These hospitals have higher infrastructure, labor, or acquisition costs relative to their peers. To the extent that these hospitals might wish to lower the cost of care at their institution, they could focus on renegotiating purchasing or labor contracts, identifying areas where they may be overstaffed, or holding off on future infrastructure investments (Table 3).[14] In contrast, 17% of hospitals had reported costs that were 25% less than standardized costs. High‐cost hospitals in this group are therefore providing more treatments and testing to patients relative to their peers and could focus cost‐control efforts on reducing unnecessary utilization and duplicative testing.[20] Our examination of the hospital with high reported costs and very high utilization revealed a high percentage of supplies and other items, which is a category used primarily for nursing expenditures (Figure 3). Because the use of nursing services is directly related to days spent in the hospital, this hospital may wish to more closely examine specific strategies for reducing length of stay.

We did not find a consistent association between the reported to standardized cost ratio and hospital characteristics. This is an important finding that contradicts prior work examining associations between hospital characteristics and costs for heart failure patients,[21] further indicating the complexity of the relationship between fixed costs and variable costs and the difficulty in adjusting reported costs to calculate utilization. For example, small hospitals may have higher acquisition costs and more supply chain difficulties, but they may also have less technology, lower overhead costs, and fewer specialists to order tests and procedures. Hospital characteristics, such as urban location and teaching status, are commonly used as adjustors in cost studies because hospitals in urban areas with teaching missions (which often provide care to low‐income populations) are assumed to have higher fixed costs,[3, 4, 5, 6] but the lack of a consistent relationship between these characteristics and the standardized cost ratio may indicate that using these factors as adjustors for cost may not be effective and could even obscure differences in utilization between hospitals. Notably, we did find an association between hospital region and the reported to standardized cost ratio, but we hesitate to draw conclusions from this finding because the Premier database is imbalanced in terms of regional representation, with fewer hospitals in the Midwest and West and the bulk of the hospitals in the South.

Although standardized costs have great potential, this method has limitations as well. Standardized costs can only be applied when detailed billing data with item‐level costs are available. This is because calculation of standardized costs requires taking the median of item costs and applying the median cost across the database, maintaining the integrity of the relative cost of items to one another. The relative cost of items is preserved (ie, magnetic resonance imaging still costs more than an aspirin), which maintains the general scheme of RVU‐based costs while removing the noise of varying RVU‐based costs across hospitals.[7] Application of an arbitrary item cost would result in the loss of this relative cost difference. Because item costs are not available in traditional administrative datasets, these datasets would not be amenable to this method. However, highly detailed billing data are now being shared by hundreds of hospitals in the Premier network and the University Health System Consortium. These data are widely available to investigators, meaning that the generalizability of this method will only improve over time. It was also a limitation of the study that we chose a limited basket of items common to patients with heart failure to describe the range of reported costs and to provide a standardized snapshot by which to compare hospitals. Because we only included a few items, we may have overestimated or underestimated the range of reported costs for such a basket.

Standardized costs are a novel method for comparing utilization across hospitals. Used properly, they will help identify high‐ and low‐intensity providers of hospital care.

Venous thromboembolism (VTE), including deep venous thrombosis (DVT) and pulmonary embolism (PE), is estimated to affect 900,000 Americans each year and is a cause of significant morbidity and mortality with associated high healthcare costs.[1] Accordingly, the comparative effectiveness and safety of interventions for the prevention and treatment of VTE are among the national priorities for comparative effectiveness research.[2] Whereas we have evidence‐based guidelines for the prophylaxis of VTE in the general population, there are no guidelines informing the care of select patient populations. Select populations are those patients in whom there is decisional uncertainty about the optimal choice, timing, and dose of VTE prophylaxis. Not only do these patients have an increased risk of DVT and PE, but most are also at high risk of bleeding, the most important complication of VTE prophylaxis.[3, 4, 5, 6]

The objectives of this systematic review were to define the comparative effectiveness and safety of pharmacologic and mechanical strategies for VTE prevention in some of these select medical populations including obese patients, patients on concomitant antiplatelet therapy, patients with renal insufficiency, patients who are underweight, and patients with coagulopathy due to liver disease.

METHODS

The methods for this comparative effectiveness review (CER) follow the guidelines suggested in the Agency for Healthcare Research and Quality (AHRQ) Methods Guide for Effectiveness and Comparative Effectiveness Reviews.[7] The protocol was publically posted.[8]

RESULTS

We identified 30,902 unique citations and included 9 studies (Figure 1). There were 5 RCTs with relevant subgroups and 4 observational studies (Table 1). Two studies reported on the risk of bleeding in patients given pharmacologic prophylaxis while they are concomitantly taking nonsteroidal anti‐inflammatory drugs (NSAIDS) or antiplatelet agents/aspirin, 1 RCT and 1 prospective observational study reported on obese patients, and 5 studies described outcomes of patients with renal insufficiency (see Supporting Information, Table 1, in the online version of this article). No study tested prophylaxis in underweight patients or those with liver disease.

Figure 1

DISCUSSION

We found that the evidence was very limited about prevention of VTE in these select and yet prevalent patient populations. Despite the fact that there is an increasing number of obese patients and patients who are on antiplatelet therapies, most clinical practice guidelines do not address the care of these populations, which may be entirely appropriate given the state of the evidence.

The ACCP practice guidelines[21] suggest using a higher dose of enoxaparin for the prevention of VTE in obese patients. The subgroup analysis by Kucher et al.[11] showed effect attenuation of dalteparin when given at a fixed dose of 5000 IU/mL to patients with a BMI of >40 kg/m². The Freeman study[12] showed that extremely obese patients (average BMI >62.1 kg/m²) who are given a fixed dose of enoxaparin achieved target anti‐factor Xa levels significantly less often than those who received a higher dose of enoxaparin. The 2 separate findings, although not conclusive, lend some credence to the current ACCP guidelines.[21]

The studies we reviewed on VTE prophylaxis in patients who are concomitantly on antiplatelets including aspirin reported no major increased risk of bleeding; however, in the Friedman et al. study,[15] 3.0% of patients who were put on enoxaparin while still on aspirin had a bleeding event compared to 1.2% of those on enoxaparin alone. This difference is not statistically significant but is a trend possibly worth noting, especially when one looks at the lower RR of bleeding at 0.55 compared to 0.82 when dabigatran is compared with enoxaparin with and without concomitant aspirin therapy, respectively (Table 1). The highest dose of aspirin used in either of the studies was 160 mg/day, and neither study addressed other potent antiplatelets such as clopidogrel or ticlopidine separately, which limits the generalizability of the finding to all antiplatelets. Current ACCP guidelines do not recommend aspirin as a sole option for the prevention of VTE in orthopedic surgery patients.[22] Concerns remain among clinicians that antiplatelets, including aspirin, on their own are unlikely to be fully effective to thwart venous thrombotic processes for most patients, and yet the risk of bleeding is not fully known when these agents are combined with other anticoagulants for VTE prophylaxis.

Our review has several limitations, including the possibility that we may have missed some observational studies, as the identification of relevant observational studies in electronic searches is more challenging than that of RCTs. The few studies made it impossible to quantitatively pool results. These results, however, have important implications, namely that additional research on the comparative effectiveness and safety of pharmacologic and mechanical strategies to prevent VTE is needed for the optimal care of these patient subgroups. This might be achieved with trials dedicated to enrolling these patients or prespecified subgroup analyses within larger trials. Observational data may be appropriate as long as attention is paid to confounding.

Venous thromboembolism (VTE), including deep venous thrombosis (DVT) and pulmonary embolism (PE), is estimated to affect 900,000 Americans each year and is a cause of significant morbidity and mortality with associated high healthcare costs.[1] Accordingly, the comparative effectiveness and safety of interventions for the prevention and treatment of VTE are among the national priorities for comparative effectiveness research.[2] Whereas we have evidence‐based guidelines for the prophylaxis of VTE in the general population, there are no guidelines informing the care of select patient populations. Select populations are those patients in whom there is decisional uncertainty about the optimal choice, timing, and dose of VTE prophylaxis. Not only do these patients have an increased risk of DVT and PE, but most are also at high risk of bleeding, the most important complication of VTE prophylaxis.[3, 4, 5, 6]

The objectives of this systematic review were to define the comparative effectiveness and safety of pharmacologic and mechanical strategies for VTE prevention in some of these select medical populations including obese patients, patients on concomitant antiplatelet therapy, patients with renal insufficiency, patients who are underweight, and patients with coagulopathy due to liver disease.

METHODS

The methods for this comparative effectiveness review (CER) follow the guidelines suggested in the Agency for Healthcare Research and Quality (AHRQ) Methods Guide for Effectiveness and Comparative Effectiveness Reviews.[7] The protocol was publically posted.[8]

RESULTS

We identified 30,902 unique citations and included 9 studies (Figure 1). There were 5 RCTs with relevant subgroups and 4 observational studies (Table 1). Two studies reported on the risk of bleeding in patients given pharmacologic prophylaxis while they are concomitantly taking nonsteroidal anti‐inflammatory drugs (NSAIDS) or antiplatelet agents/aspirin, 1 RCT and 1 prospective observational study reported on obese patients, and 5 studies described outcomes of patients with renal insufficiency (see Supporting Information, Table 1, in the online version of this article). No study tested prophylaxis in underweight patients or those with liver disease.

Figure 1

DISCUSSION

We found that the evidence was very limited about prevention of VTE in these select and yet prevalent patient populations. Despite the fact that there is an increasing number of obese patients and patients who are on antiplatelet therapies, most clinical practice guidelines do not address the care of these populations, which may be entirely appropriate given the state of the evidence.

The ACCP practice guidelines[21] suggest using a higher dose of enoxaparin for the prevention of VTE in obese patients. The subgroup analysis by Kucher et al.[11] showed effect attenuation of dalteparin when given at a fixed dose of 5000 IU/mL to patients with a BMI of >40 kg/m². The Freeman study[12] showed that extremely obese patients (average BMI >62.1 kg/m²) who are given a fixed dose of enoxaparin achieved target anti‐factor Xa levels significantly less often than those who received a higher dose of enoxaparin. The 2 separate findings, although not conclusive, lend some credence to the current ACCP guidelines.[21]

The studies we reviewed on VTE prophylaxis in patients who are concomitantly on antiplatelets including aspirin reported no major increased risk of bleeding; however, in the Friedman et al. study,[15] 3.0% of patients who were put on enoxaparin while still on aspirin had a bleeding event compared to 1.2% of those on enoxaparin alone. This difference is not statistically significant but is a trend possibly worth noting, especially when one looks at the lower RR of bleeding at 0.55 compared to 0.82 when dabigatran is compared with enoxaparin with and without concomitant aspirin therapy, respectively (Table 1). The highest dose of aspirin used in either of the studies was 160 mg/day, and neither study addressed other potent antiplatelets such as clopidogrel or ticlopidine separately, which limits the generalizability of the finding to all antiplatelets. Current ACCP guidelines do not recommend aspirin as a sole option for the prevention of VTE in orthopedic surgery patients.[22] Concerns remain among clinicians that antiplatelets, including aspirin, on their own are unlikely to be fully effective to thwart venous thrombotic processes for most patients, and yet the risk of bleeding is not fully known when these agents are combined with other anticoagulants for VTE prophylaxis.

Our review has several limitations, including the possibility that we may have missed some observational studies, as the identification of relevant observational studies in electronic searches is more challenging than that of RCTs. The few studies made it impossible to quantitatively pool results. These results, however, have important implications, namely that additional research on the comparative effectiveness and safety of pharmacologic and mechanical strategies to prevent VTE is needed for the optimal care of these patient subgroups. This might be achieved with trials dedicated to enrolling these patients or prespecified subgroup analyses within larger trials. Observational data may be appropriate as long as attention is paid to confounding.

Venous thromboembolism (VTE), including deep venous thrombosis (DVT) and pulmonary embolism (PE), is estimated to affect 900,000 Americans each year and is a cause of significant morbidity and mortality with associated high healthcare costs.[1] Accordingly, the comparative effectiveness and safety of interventions for the prevention and treatment of VTE are among the national priorities for comparative effectiveness research.[2] Whereas we have evidence‐based guidelines for the prophylaxis of VTE in the general population, there are no guidelines informing the care of select patient populations. Select populations are those patients in whom there is decisional uncertainty about the optimal choice, timing, and dose of VTE prophylaxis. Not only do these patients have an increased risk of DVT and PE, but most are also at high risk of bleeding, the most important complication of VTE prophylaxis.[3, 4, 5, 6]

The objectives of this systematic review were to define the comparative effectiveness and safety of pharmacologic and mechanical strategies for VTE prevention in some of these select medical populations including obese patients, patients on concomitant antiplatelet therapy, patients with renal insufficiency, patients who are underweight, and patients with coagulopathy due to liver disease.

METHODS

The methods for this comparative effectiveness review (CER) follow the guidelines suggested in the Agency for Healthcare Research and Quality (AHRQ) Methods Guide for Effectiveness and Comparative Effectiveness Reviews.[7] The protocol was publically posted.[8]

RESULTS

We identified 30,902 unique citations and included 9 studies (Figure 1). There were 5 RCTs with relevant subgroups and 4 observational studies (Table 1). Two studies reported on the risk of bleeding in patients given pharmacologic prophylaxis while they are concomitantly taking nonsteroidal anti‐inflammatory drugs (NSAIDS) or antiplatelet agents/aspirin, 1 RCT and 1 prospective observational study reported on obese patients, and 5 studies described outcomes of patients with renal insufficiency (see Supporting Information, Table 1, in the online version of this article). No study tested prophylaxis in underweight patients or those with liver disease.

Figure 1

DISCUSSION

We found that the evidence was very limited about prevention of VTE in these select and yet prevalent patient populations. Despite the fact that there is an increasing number of obese patients and patients who are on antiplatelet therapies, most clinical practice guidelines do not address the care of these populations, which may be entirely appropriate given the state of the evidence.

The ACCP practice guidelines[21] suggest using a higher dose of enoxaparin for the prevention of VTE in obese patients. The subgroup analysis by Kucher et al.[11] showed effect attenuation of dalteparin when given at a fixed dose of 5000 IU/mL to patients with a BMI of >40 kg/m². The Freeman study[12] showed that extremely obese patients (average BMI >62.1 kg/m²) who are given a fixed dose of enoxaparin achieved target anti‐factor Xa levels significantly less often than those who received a higher dose of enoxaparin. The 2 separate findings, although not conclusive, lend some credence to the current ACCP guidelines.[21]

The studies we reviewed on VTE prophylaxis in patients who are concomitantly on antiplatelets including aspirin reported no major increased risk of bleeding; however, in the Friedman et al. study,[15] 3.0% of patients who were put on enoxaparin while still on aspirin had a bleeding event compared to 1.2% of those on enoxaparin alone. This difference is not statistically significant but is a trend possibly worth noting, especially when one looks at the lower RR of bleeding at 0.55 compared to 0.82 when dabigatran is compared with enoxaparin with and without concomitant aspirin therapy, respectively (Table 1). The highest dose of aspirin used in either of the studies was 160 mg/day, and neither study addressed other potent antiplatelets such as clopidogrel or ticlopidine separately, which limits the generalizability of the finding to all antiplatelets. Current ACCP guidelines do not recommend aspirin as a sole option for the prevention of VTE in orthopedic surgery patients.[22] Concerns remain among clinicians that antiplatelets, including aspirin, on their own are unlikely to be fully effective to thwart venous thrombotic processes for most patients, and yet the risk of bleeding is not fully known when these agents are combined with other anticoagulants for VTE prophylaxis.

Our review has several limitations, including the possibility that we may have missed some observational studies, as the identification of relevant observational studies in electronic searches is more challenging than that of RCTs. The few studies made it impossible to quantitatively pool results. These results, however, have important implications, namely that additional research on the comparative effectiveness and safety of pharmacologic and mechanical strategies to prevent VTE is needed for the optimal care of these patient subgroups. This might be achieved with trials dedicated to enrolling these patients or prespecified subgroup analyses within larger trials. Observational data may be appropriate as long as attention is paid to confounding.

Healthcare workers' (HCWs) attire becomes contaminated with bacterial pathogens during the course of the workday,[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] and Munoz‐Price et al.[13] recently demonstrated that finding bacterial pathogens on HCWs' white coats correlated with finding the same pathogens on their hands. Because of concern for an association between attire colonization and nosocomial infection, governmental agencies in England and Scotland banned HCWs from wearing white coats or long‐sleeve garments,[14, 15] despite evidence that such an approach does not reduce contamination.[12]

Newly developed antimicrobial textiles have been incorporated into HCW scrubs,[16, 17, 18, 19, 20] and commercial Web sites and product inserts report that these products can reduce bacterial contamination by 80.9% at 8 hours to greater than 99% under laboratory conditions depending on the product and microbe studied.[16, 17, 19] Because there are limited clinical data pertaining to the effectiveness of antimicrobial scrubs, we performed a prospective study designed to determine whether wearing these products reduced bacterial contamination of HCWs' scrubs or skin at the end of an 8‐hour workday.

METHODS

RESULTS

We screened 118 HCWs for participation and randomized 109, 37 in the control and antimicrobial scrub group A, and 35 in antimicrobial scrub group B (during the course of the study we neglected to culture the pockets of 2 participants in the standard scrub group and 2 in antimicrobial scrub group A). Because our primary end point was total colony count from cultures taken from 3 sites, data from these 4 subjects could not be used, and all the data from these 4 subjects were excluded from the primary analysis; 4 additional subjects were subsequently recruited allowing us to meet our block enrollment target (Figure 1). The first and last participants were studied on March 12, 2012 and August 28, 2012, respectively. The trial ended once the defined number of participants was enrolled. The occupations of the 105 participants are summarized in Table 1.

Figure 1

Colony counts of all scrubs cultured prior to use never exceeded 10 colonies. The median (IQR) total colony counts from all sites on the scrubs was 99 (66182) for standard scrubs, 137 (84289) for antimicrobial scrub type A, and 138 (62274) for antimicrobial scrub type B (P=0.36). We found no significant differences between the colony counts cultured from any of the individual sites among the 3 groups, regardless of occupation (Table 2). No significant difference was observed with respect to colony counts cultured from the wrist among the 3 study groups (Table 2). Comparisons between groups were planned a priori if a difference across all groups was found. Given the nonsignificant P values across all scrub groups, no further comparisons were made.

Fifty‐five participants (52%) reported caring for patients who were known to be colonized or infected with an antibiotic‐resistant organism, 16 (46%) randomized to wear standard scrubs, and 20 (57%) and 19 (54%) randomized to wear antimicrobial scrub A or B, respectively (P=0.61). Of these, however, antibiotic‐resistant organisms were only cultured from the scrubs of 2 providers (1 with 1 colony of MRSA from the breast pocket of antimicrobial scrub A, 1 with 1 colony of MRSA cultured from the pocket of antimicrobial scrub B [P=0.55]), and from the wrist of only 1 provider (a multiresistant Gram‐negative rod who wore antimicrobial scrub B).

DISCUSSION

The important findings of this study are that we found no evidence indicating that either of the 2 antimicrobial scrubs tested reduced bacterial contamination or antibiotic‐resistant contamination on HCWs' scrubs or wrists compared with standard scrubs at the end of an 8‐hour workday, and that despite many HCWs being exposed to patients who were colonized or infected with antibiotic‐resistant bacteria, these organisms were only rarely cultured from their uniforms.

We found that HCWs in all 3 arms of the study had bacterial contamination on their scrubs and skin, consistent with previous studies showing that HCWs' uniforms are frequently contaminated with bacteria, including MRSA, VRE, and other pathogens.[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] We previously found that bacterial contamination of HCWs' uniforms occurs within hours of putting on newly laundered uniforms.[12]

Literature on the effectiveness of antimicrobial HCW uniforms when tested in clinical settings is limited. Bearman and colleagues[23] recently published the results of a study of 31 subjects who wore either standard or antimicrobial scrubs, crossing over every 4 weeks for 4 months, with random culturing done weekly at the beginning and end of a work shift. Scrubs were laundered an average of 1.5 times/week, but the timing of the laundering relative to when cultures were obtained was not reported. Very few isolates of MRSA, Gram‐negative rods, or VRE were found (only 3.9%, 0.4%, and 0.05% of the 2000 samples obtained, respectively), and no differences were observed with respect to the number of HCWs who had antibiotic‐resistant organisms cultured when they were wearing standard versus antimicrobial scrubs. Those who had MRSA cultured, however, had lower mean log colony counts when they were wearing the antimicrobial scrubs. The small number of samples with positive isolates, together with differences in the extent of before‐shift contamination among groups complicates interpreting these data. The authors concluded that a prospective trial was needed. We attempted to include the scrub studied by Bearman and colleagues[23] in our study, but the company had insufficient stock available at the time we tried to purchase the product.

Gross and colleagues[24] found no difference in the mean colony counts of cultures taken from silver‐impregnated versus standard scrubs in a pilot crossover study done with 10 HCWs (although there were trends toward higher colony counts when the subjects wore antimicrobial scrubs).

Antibiotic‐resistant bacteria were only cultured from 3 participants (2.9%) in our current study, compared to 16% of those randomized to wearing white coats in our previous study and 20% of those randomized to wearing standard scrubs.[12] This difference may be explained by several recent studies reporting that rates of MRSA infections in hospitals are decreasing.[25, 26] The rate of hospital‐acquired MRSA infection or colonization at our own institution decreased 80% from 2007 to 2012. At the times of our previous and current studies, providers were expected to wear gowns and gloves when caring for patients as per standard contact precautions. Rates of infection and colonization of VRE and resistant Gram‐negative rods have remained low at our hospital, and our data are consistent with the rates reported on HCWs' uniforms in other studies.[2, 5, 10]

Only 6 of our subjects reported adverse reactions, but all were wearing antimicrobial scrubs (P=0.18). Several of the participants described that the fabrics of the 2 antimicrobial scrubs were heavier and less breathable than the standard scrubs. We believe this difference is more likely to explain the adverse reactions reported than is any type of reaction to the specific chemicals in the fabrics.

Our study has several limitations. Because it was conducted on the general internal medicine units of a single university‐affiliated public hospital, the results may not generalize to other types of institutions or other inpatient services.

As we previously described,[12] the RODAC imprint method only samples a small area of HCWs' uniforms and thus does not represent total bacterial contamination.[21] We specifically cultured areas that are known to be highly contaminated (ie, sleeve cuffs and pockets). Although imprint methods have limitations (as do other methods for culturing clothing), they have been commonly utilized in studies assessing bacterial contamination of HCW clothing.[2, 3, 5]

Although some of the bacterial load we cultured could have come from the providers themselves, previous studies have shown that 80% to 90% of the resistant bacteria cultured from HCWs' attire come from other sources.[1, 2]

Because our sample size was calculated on the basis of being able to detect a difference of 70% in total bacterial colony count, our study was not large enough to exclude a lower level of effectiveness. However, we saw no trends suggesting the antimicrobial products might have a lower level of effectiveness.

We did not observe the hand‐washing practices of the participants, and accordingly, cannot confirm that these practices were the same in each of our 3 study groups. Intermittent, surreptitious monitoring of hand‐washing practices on our internal medicine units over the last several years has found compliance with hand hygiene recommendations varying from 70% to 90%.

Although the participants in our study were not explicitly told to which scrub they were randomized, the colors, appearances, and textures of the antimicrobial fabrics were different from the standard scrubs such that blinding was impossible. Participants wearing antimicrobial scrubs could have changed their hand hygiene practices (ie, less careful hand hygiene). Lack of blinding could also have led to over‐reporting of adverse events by the subjects randomized to wear the antimicrobial scrubs.

In an effort to treat all the scrubs in the same fashion, all were tested new, prior to being washed or previously worn. Studying the scrubs prior to washing or wearing could have increased the reports of adverse effects, as the fabrics could have been stiffer and more uncomfortable than they might have been at a later stage in their use.

Our study also has some strengths. Our participants included physicians, residents, nurses, nurse practitioners, and physician assistants. Accordingly, our results should be generalizable to most HCWs. We also confirmed that the scrubs that were tested were nearly sterile prior to use.

In conclusion, we found no evidence suggesting that either of 2 antimicrobial scrubs tested decreased bacterial contamination of HCWs' scrubs or skin after an 8‐hour workday compared to standard scrubs. We also found that, although HCWs are frequently exposed to patients harboring antibiotic‐resistant bacteria, these bacteria were only rarely cultured from HCWs' scrubs or skin.

Healthcare workers' (HCWs) attire becomes contaminated with bacterial pathogens during the course of the workday,[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] and Munoz‐Price et al.[13] recently demonstrated that finding bacterial pathogens on HCWs' white coats correlated with finding the same pathogens on their hands. Because of concern for an association between attire colonization and nosocomial infection, governmental agencies in England and Scotland banned HCWs from wearing white coats or long‐sleeve garments,[14, 15] despite evidence that such an approach does not reduce contamination.[12]

Newly developed antimicrobial textiles have been incorporated into HCW scrubs,[16, 17, 18, 19, 20] and commercial Web sites and product inserts report that these products can reduce bacterial contamination by 80.9% at 8 hours to greater than 99% under laboratory conditions depending on the product and microbe studied.[16, 17, 19] Because there are limited clinical data pertaining to the effectiveness of antimicrobial scrubs, we performed a prospective study designed to determine whether wearing these products reduced bacterial contamination of HCWs' scrubs or skin at the end of an 8‐hour workday.

METHODS

RESULTS

We screened 118 HCWs for participation and randomized 109, 37 in the control and antimicrobial scrub group A, and 35 in antimicrobial scrub group B (during the course of the study we neglected to culture the pockets of 2 participants in the standard scrub group and 2 in antimicrobial scrub group A). Because our primary end point was total colony count from cultures taken from 3 sites, data from these 4 subjects could not be used, and all the data from these 4 subjects were excluded from the primary analysis; 4 additional subjects were subsequently recruited allowing us to meet our block enrollment target (Figure 1). The first and last participants were studied on March 12, 2012 and August 28, 2012, respectively. The trial ended once the defined number of participants was enrolled. The occupations of the 105 participants are summarized in Table 1.

Figure 1

Colony counts of all scrubs cultured prior to use never exceeded 10 colonies. The median (IQR) total colony counts from all sites on the scrubs was 99 (66182) for standard scrubs, 137 (84289) for antimicrobial scrub type A, and 138 (62274) for antimicrobial scrub type B (P=0.36). We found no significant differences between the colony counts cultured from any of the individual sites among the 3 groups, regardless of occupation (Table 2). No significant difference was observed with respect to colony counts cultured from the wrist among the 3 study groups (Table 2). Comparisons between groups were planned a priori if a difference across all groups was found. Given the nonsignificant P values across all scrub groups, no further comparisons were made.

Fifty‐five participants (52%) reported caring for patients who were known to be colonized or infected with an antibiotic‐resistant organism, 16 (46%) randomized to wear standard scrubs, and 20 (57%) and 19 (54%) randomized to wear antimicrobial scrub A or B, respectively (P=0.61). Of these, however, antibiotic‐resistant organisms were only cultured from the scrubs of 2 providers (1 with 1 colony of MRSA from the breast pocket of antimicrobial scrub A, 1 with 1 colony of MRSA cultured from the pocket of antimicrobial scrub B [P=0.55]), and from the wrist of only 1 provider (a multiresistant Gram‐negative rod who wore antimicrobial scrub B).

DISCUSSION

The important findings of this study are that we found no evidence indicating that either of the 2 antimicrobial scrubs tested reduced bacterial contamination or antibiotic‐resistant contamination on HCWs' scrubs or wrists compared with standard scrubs at the end of an 8‐hour workday, and that despite many HCWs being exposed to patients who were colonized or infected with antibiotic‐resistant bacteria, these organisms were only rarely cultured from their uniforms.

We found that HCWs in all 3 arms of the study had bacterial contamination on their scrubs and skin, consistent with previous studies showing that HCWs' uniforms are frequently contaminated with bacteria, including MRSA, VRE, and other pathogens.[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] We previously found that bacterial contamination of HCWs' uniforms occurs within hours of putting on newly laundered uniforms.[12]

Literature on the effectiveness of antimicrobial HCW uniforms when tested in clinical settings is limited. Bearman and colleagues[23] recently published the results of a study of 31 subjects who wore either standard or antimicrobial scrubs, crossing over every 4 weeks for 4 months, with random culturing done weekly at the beginning and end of a work shift. Scrubs were laundered an average of 1.5 times/week, but the timing of the laundering relative to when cultures were obtained was not reported. Very few isolates of MRSA, Gram‐negative rods, or VRE were found (only 3.9%, 0.4%, and 0.05% of the 2000 samples obtained, respectively), and no differences were observed with respect to the number of HCWs who had antibiotic‐resistant organisms cultured when they were wearing standard versus antimicrobial scrubs. Those who had MRSA cultured, however, had lower mean log colony counts when they were wearing the antimicrobial scrubs. The small number of samples with positive isolates, together with differences in the extent of before‐shift contamination among groups complicates interpreting these data. The authors concluded that a prospective trial was needed. We attempted to include the scrub studied by Bearman and colleagues[23] in our study, but the company had insufficient stock available at the time we tried to purchase the product.

Gross and colleagues[24] found no difference in the mean colony counts of cultures taken from silver‐impregnated versus standard scrubs in a pilot crossover study done with 10 HCWs (although there were trends toward higher colony counts when the subjects wore antimicrobial scrubs).

Antibiotic‐resistant bacteria were only cultured from 3 participants (2.9%) in our current study, compared to 16% of those randomized to wearing white coats in our previous study and 20% of those randomized to wearing standard scrubs.[12] This difference may be explained by several recent studies reporting that rates of MRSA infections in hospitals are decreasing.[25, 26] The rate of hospital‐acquired MRSA infection or colonization at our own institution decreased 80% from 2007 to 2012. At the times of our previous and current studies, providers were expected to wear gowns and gloves when caring for patients as per standard contact precautions. Rates of infection and colonization of VRE and resistant Gram‐negative rods have remained low at our hospital, and our data are consistent with the rates reported on HCWs' uniforms in other studies.[2, 5, 10]

Only 6 of our subjects reported adverse reactions, but all were wearing antimicrobial scrubs (P=0.18). Several of the participants described that the fabrics of the 2 antimicrobial scrubs were heavier and less breathable than the standard scrubs. We believe this difference is more likely to explain the adverse reactions reported than is any type of reaction to the specific chemicals in the fabrics.

Our study has several limitations. Because it was conducted on the general internal medicine units of a single university‐affiliated public hospital, the results may not generalize to other types of institutions or other inpatient services.

As we previously described,[12] the RODAC imprint method only samples a small area of HCWs' uniforms and thus does not represent total bacterial contamination.[21] We specifically cultured areas that are known to be highly contaminated (ie, sleeve cuffs and pockets). Although imprint methods have limitations (as do other methods for culturing clothing), they have been commonly utilized in studies assessing bacterial contamination of HCW clothing.[2, 3, 5]

Although some of the bacterial load we cultured could have come from the providers themselves, previous studies have shown that 80% to 90% of the resistant bacteria cultured from HCWs' attire come from other sources.[1, 2]

Because our sample size was calculated on the basis of being able to detect a difference of 70% in total bacterial colony count, our study was not large enough to exclude a lower level of effectiveness. However, we saw no trends suggesting the antimicrobial products might have a lower level of effectiveness.

We did not observe the hand‐washing practices of the participants, and accordingly, cannot confirm that these practices were the same in each of our 3 study groups. Intermittent, surreptitious monitoring of hand‐washing practices on our internal medicine units over the last several years has found compliance with hand hygiene recommendations varying from 70% to 90%.

Although the participants in our study were not explicitly told to which scrub they were randomized, the colors, appearances, and textures of the antimicrobial fabrics were different from the standard scrubs such that blinding was impossible. Participants wearing antimicrobial scrubs could have changed their hand hygiene practices (ie, less careful hand hygiene). Lack of blinding could also have led to over‐reporting of adverse events by the subjects randomized to wear the antimicrobial scrubs.

In an effort to treat all the scrubs in the same fashion, all were tested new, prior to being washed or previously worn. Studying the scrubs prior to washing or wearing could have increased the reports of adverse effects, as the fabrics could have been stiffer and more uncomfortable than they might have been at a later stage in their use.

Our study also has some strengths. Our participants included physicians, residents, nurses, nurse practitioners, and physician assistants. Accordingly, our results should be generalizable to most HCWs. We also confirmed that the scrubs that were tested were nearly sterile prior to use.

In conclusion, we found no evidence suggesting that either of 2 antimicrobial scrubs tested decreased bacterial contamination of HCWs' scrubs or skin after an 8‐hour workday compared to standard scrubs. We also found that, although HCWs are frequently exposed to patients harboring antibiotic‐resistant bacteria, these bacteria were only rarely cultured from HCWs' scrubs or skin.

Healthcare workers' (HCWs) attire becomes contaminated with bacterial pathogens during the course of the workday,[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] and Munoz‐Price et al.[13] recently demonstrated that finding bacterial pathogens on HCWs' white coats correlated with finding the same pathogens on their hands. Because of concern for an association between attire colonization and nosocomial infection, governmental agencies in England and Scotland banned HCWs from wearing white coats or long‐sleeve garments,[14, 15] despite evidence that such an approach does not reduce contamination.[12]

Newly developed antimicrobial textiles have been incorporated into HCW scrubs,[16, 17, 18, 19, 20] and commercial Web sites and product inserts report that these products can reduce bacterial contamination by 80.9% at 8 hours to greater than 99% under laboratory conditions depending on the product and microbe studied.[16, 17, 19] Because there are limited clinical data pertaining to the effectiveness of antimicrobial scrubs, we performed a prospective study designed to determine whether wearing these products reduced bacterial contamination of HCWs' scrubs or skin at the end of an 8‐hour workday.

METHODS

RESULTS

We screened 118 HCWs for participation and randomized 109, 37 in the control and antimicrobial scrub group A, and 35 in antimicrobial scrub group B (during the course of the study we neglected to culture the pockets of 2 participants in the standard scrub group and 2 in antimicrobial scrub group A). Because our primary end point was total colony count from cultures taken from 3 sites, data from these 4 subjects could not be used, and all the data from these 4 subjects were excluded from the primary analysis; 4 additional subjects were subsequently recruited allowing us to meet our block enrollment target (Figure 1). The first and last participants were studied on March 12, 2012 and August 28, 2012, respectively. The trial ended once the defined number of participants was enrolled. The occupations of the 105 participants are summarized in Table 1.

Figure 1

Colony counts of all scrubs cultured prior to use never exceeded 10 colonies. The median (IQR) total colony counts from all sites on the scrubs was 99 (66182) for standard scrubs, 137 (84289) for antimicrobial scrub type A, and 138 (62274) for antimicrobial scrub type B (P=0.36). We found no significant differences between the colony counts cultured from any of the individual sites among the 3 groups, regardless of occupation (Table 2). No significant difference was observed with respect to colony counts cultured from the wrist among the 3 study groups (Table 2). Comparisons between groups were planned a priori if a difference across all groups was found. Given the nonsignificant P values across all scrub groups, no further comparisons were made.

Fifty‐five participants (52%) reported caring for patients who were known to be colonized or infected with an antibiotic‐resistant organism, 16 (46%) randomized to wear standard scrubs, and 20 (57%) and 19 (54%) randomized to wear antimicrobial scrub A or B, respectively (P=0.61). Of these, however, antibiotic‐resistant organisms were only cultured from the scrubs of 2 providers (1 with 1 colony of MRSA from the breast pocket of antimicrobial scrub A, 1 with 1 colony of MRSA cultured from the pocket of antimicrobial scrub B [P=0.55]), and from the wrist of only 1 provider (a multiresistant Gram‐negative rod who wore antimicrobial scrub B).

DISCUSSION

The important findings of this study are that we found no evidence indicating that either of the 2 antimicrobial scrubs tested reduced bacterial contamination or antibiotic‐resistant contamination on HCWs' scrubs or wrists compared with standard scrubs at the end of an 8‐hour workday, and that despite many HCWs being exposed to patients who were colonized or infected with antibiotic‐resistant bacteria, these organisms were only rarely cultured from their uniforms.

We found that HCWs in all 3 arms of the study had bacterial contamination on their scrubs and skin, consistent with previous studies showing that HCWs' uniforms are frequently contaminated with bacteria, including MRSA, VRE, and other pathogens.[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12] We previously found that bacterial contamination of HCWs' uniforms occurs within hours of putting on newly laundered uniforms.[12]

Literature on the effectiveness of antimicrobial HCW uniforms when tested in clinical settings is limited. Bearman and colleagues[23] recently published the results of a study of 31 subjects who wore either standard or antimicrobial scrubs, crossing over every 4 weeks for 4 months, with random culturing done weekly at the beginning and end of a work shift. Scrubs were laundered an average of 1.5 times/week, but the timing of the laundering relative to when cultures were obtained was not reported. Very few isolates of MRSA, Gram‐negative rods, or VRE were found (only 3.9%, 0.4%, and 0.05% of the 2000 samples obtained, respectively), and no differences were observed with respect to the number of HCWs who had antibiotic‐resistant organisms cultured when they were wearing standard versus antimicrobial scrubs. Those who had MRSA cultured, however, had lower mean log colony counts when they were wearing the antimicrobial scrubs. The small number of samples with positive isolates, together with differences in the extent of before‐shift contamination among groups complicates interpreting these data. The authors concluded that a prospective trial was needed. We attempted to include the scrub studied by Bearman and colleagues[23] in our study, but the company had insufficient stock available at the time we tried to purchase the product.

Gross and colleagues[24] found no difference in the mean colony counts of cultures taken from silver‐impregnated versus standard scrubs in a pilot crossover study done with 10 HCWs (although there were trends toward higher colony counts when the subjects wore antimicrobial scrubs).

Antibiotic‐resistant bacteria were only cultured from 3 participants (2.9%) in our current study, compared to 16% of those randomized to wearing white coats in our previous study and 20% of those randomized to wearing standard scrubs.[12] This difference may be explained by several recent studies reporting that rates of MRSA infections in hospitals are decreasing.[25, 26] The rate of hospital‐acquired MRSA infection or colonization at our own institution decreased 80% from 2007 to 2012. At the times of our previous and current studies, providers were expected to wear gowns and gloves when caring for patients as per standard contact precautions. Rates of infection and colonization of VRE and resistant Gram‐negative rods have remained low at our hospital, and our data are consistent with the rates reported on HCWs' uniforms in other studies.[2, 5, 10]

Only 6 of our subjects reported adverse reactions, but all were wearing antimicrobial scrubs (P=0.18). Several of the participants described that the fabrics of the 2 antimicrobial scrubs were heavier and less breathable than the standard scrubs. We believe this difference is more likely to explain the adverse reactions reported than is any type of reaction to the specific chemicals in the fabrics.

Our study has several limitations. Because it was conducted on the general internal medicine units of a single university‐affiliated public hospital, the results may not generalize to other types of institutions or other inpatient services.

As we previously described,[12] the RODAC imprint method only samples a small area of HCWs' uniforms and thus does not represent total bacterial contamination.[21] We specifically cultured areas that are known to be highly contaminated (ie, sleeve cuffs and pockets). Although imprint methods have limitations (as do other methods for culturing clothing), they have been commonly utilized in studies assessing bacterial contamination of HCW clothing.[2, 3, 5]

Although some of the bacterial load we cultured could have come from the providers themselves, previous studies have shown that 80% to 90% of the resistant bacteria cultured from HCWs' attire come from other sources.[1, 2]

Because our sample size was calculated on the basis of being able to detect a difference of 70% in total bacterial colony count, our study was not large enough to exclude a lower level of effectiveness. However, we saw no trends suggesting the antimicrobial products might have a lower level of effectiveness.

We did not observe the hand‐washing practices of the participants, and accordingly, cannot confirm that these practices were the same in each of our 3 study groups. Intermittent, surreptitious monitoring of hand‐washing practices on our internal medicine units over the last several years has found compliance with hand hygiene recommendations varying from 70% to 90%.

Although the participants in our study were not explicitly told to which scrub they were randomized, the colors, appearances, and textures of the antimicrobial fabrics were different from the standard scrubs such that blinding was impossible. Participants wearing antimicrobial scrubs could have changed their hand hygiene practices (ie, less careful hand hygiene). Lack of blinding could also have led to over‐reporting of adverse events by the subjects randomized to wear the antimicrobial scrubs.

In an effort to treat all the scrubs in the same fashion, all were tested new, prior to being washed or previously worn. Studying the scrubs prior to washing or wearing could have increased the reports of adverse effects, as the fabrics could have been stiffer and more uncomfortable than they might have been at a later stage in their use.

Our study also has some strengths. Our participants included physicians, residents, nurses, nurse practitioners, and physician assistants. Accordingly, our results should be generalizable to most HCWs. We also confirmed that the scrubs that were tested were nearly sterile prior to use.

In conclusion, we found no evidence suggesting that either of 2 antimicrobial scrubs tested decreased bacterial contamination of HCWs' scrubs or skin after an 8‐hour workday compared to standard scrubs. We also found that, although HCWs are frequently exposed to patients harboring antibiotic‐resistant bacteria, these bacteria were only rarely cultured from HCWs' scrubs or skin.