- Email: [email protected]
A Cost-Effectiveness Analysis of Obtaining Blood Cultures in Children Hospitalized for Community-Acquired Pneumonia
A Cost-Effectiveness Analysis of Obtaining Blood Cultures in Children Hospitalized for Community-Acquired Pneumonia Annie Lintzenich Andrews, MD, MSCR1, Annie N. Simpson, PhD2, Daniel Heine, MD3, and Ronald J. Teufel, II, MD, MSCR1 Objective To determine the clinical utility and cost-effectiveness of universal vs targeted approach to obtaining blood cultures in children hospitalized with community-acquired pneumonia (CAP).
Study design We conducted a cost-effectiveness analysis using a decision tree to compare 2 approaches to ordering blood cultures in children hospitalized with CAP: obtaining blood cultures in all children admitted with CAP (universal approach) and obtaining blood cultures in patients identified as high risk for bacteremia (targeted approach). We searched the literature to determine expected proportions of high-risk patients, positive culture rates, and predicted bacteria and susceptibility patterns. Our primary clinical outcome was projected rate of missed bacteremia with associated treatment failure in the targeted approach. Costs per 100 patients and annualized costs on the national level were calculated for each approach. Results The model predicts that in the targeted approach, there will be 0.07 cases of missed bacteremia with treatment failure per 100 patients, or 133 annually. In the universal approach, 118 blood cultures would need to be drawn to identify 1 patient with bacteremia, in which the result would lead to a meaningful antibiotic change compared with 42 cultures in the targeted approach. The universal approach would cost $5178 per 100 patients or $9 214 238 annually. The targeted approach would cost $1992 per 100 patients or $3 545 460 annually. The laboratory-related cost savings attributed to the targeted approach would be projected to be $5 668 778 annually. Conclusions This decision analysis model suggests that a targeted approach to obtaining blood cultures in children hospitalized with CAP may be clinically effective, cost-saving, and reduce unnecessary testing. (J Pediatr 2015;-:---).
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ommunity-acquired pneumonia (CAP) is one of the most common reasons for hospitalization among children.1 According to Healthcare Cost and Utilization Project (HCUP) data, there are over 178 000 pediatric admissions for CAP annually.2 In 2011, the Infectious Diseases Society of America (IDSA) published guidelines for the management of CAP in children.3 The guidelines recommend obtaining blood cultures in moderately or severely ill children who are hospitalized with CAP. This was a strong recommendation supported by low quality evidence, and authors of the guideline state that the cost-effectiveness of this approach is not known. Since the publication of the IDSA guidelines, there has been frequent discussion in the literature regarding the clinical utility of obtaining blood cultures in this population of children, primarily because of the low rate of positivity.4-8 Reported rates of bacteremia in children with CAP range from 1.4%-7.0% in recent studies.5-10 Not surprisingly, hospitals have taken different approaches to this clinical decision. Published approaches include aiming for obtaining blood cultures in 100% of children admitted with CAP,9 using criteria to identify children who are at higher risk for bacteremia and obtaining cultures in this subset of patients,8 and benchmarking performance variation among hospital collaboratives and attempting to associate performance with outcomes.11,12 Even in the less likely event that a blood culture is positive, the result does not often change the clinical management.6 Furthermore, if a child is not improving while receiving narrow spectrum antibiotics, a clinician could obtain a culture before broadening coverage. In order to avoid unnecessary testing while also being consistent with guideline recommendation for children who are “moderately to severely ill,”3 a targeted approach focusing on blood culture testing for hospitalized children at higher risk for bacteremia (eg, pneumonia with effusion or empyema or patient admitted to the intensive care unit or immunosuppressed) may improve diagnostic testing yield and avoid tests that are less likely to influence clinical management.8 The objective of this study is to compare the clinical utility and costFrom the Department of Pediatrics, Medical University effectiveness of a universal vs targeted approach to obtaining blood cultures in of South Carolina; Department of Healthcare Leadership and Management, Medical University of children hospitalized with CAP. We included both cost and clinical outcome South Carolina, Charleston, SC; and East Cobb Pediatrics, Marietta, GA measures on a national level in order to inform future guidelines and national 1
2
3
The authors declare no conflicts of interest.
CAP HCUP IDSA
Community-acquired pneumonia Healthcare Cost and Utilization Project Infectious Diseases Society of America
Portions of the study were presented as an abstract at the meeting of the Pediatric Academic Societies, San Diego, CA, April 25-28, 2015. 0022-3476/$ - see front matter. Copyright ª 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jpeds.2015.09.025
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policy decisions with regard to clinical care and quality metrics for children hospitalized with CAP.
We performed a decision analysis, an approach to costeffectiveness analysis that models various approaches to a clinical decision, incorporating the best current evidence available. We estimate the clinical and financial impact of 2 approaches: obtaining a blood culture on all patients with CAP vs a targeted approach focused on identifying children who are at higher risk for bacteremia and limiting blood cultures to this subset of patients. We used the HCUP Kids Inpatient Database to extrapolate our results to the national population to determine the effect of this decision on a national level.
result of which will lead to a meaningful antibiotic change (meaning the isolated bacteria is not susceptible to ampicillin) (38%).6 Consistent with a previously published study, for the purpose of this analysis, patients were considered “high risk” if they met any of the following criteria: (1) <6 months with fever or not fully immunized; (2) have a central line; (3) are immunocompromised; (4) are toxic appearing or admitted to the intensive care unit; (5) have a chronic medical condition; and (6) have an effusion or empyema on chest radiograph.8 The 6 studies referenced in our model include data from 12 US hospitals that care for children from the years 2010-2013. Over 4900 patients are represented in these studies. To arrive at our final model inputs as listed above, we averaged the data from all contributing studies and weighted to account for sample size.
Decision Analysis Model Clinical Data. Once the decision analysis model was created, we surveyed the literature to obtain data on the assumptions needed for the decision tree (Figure 1 and Table I). Assumptions for this analysis included proportion of patients who will qualify as “high risk” based on published guidelines (32%),8 proportion of blood cultures that will be positive (3.5%),5-10 proportion of positive blood cultures that will be true positives (60%) vs contaminants (40%) (representing an overall contamination rate of 1.4%),5-10 and the proportion of true positive cultures, the
Cost Data. The purpose of the cost-effectiveness analysis was to evaluate the cost-effectiveness and/or potential cost savings attributable to applying a targeted approach to obtaining blood cultures in children hospitalized with CAP compared with a universal approach. The primary analysis is from the perspective of the hospital and includes only direct costs related to laboratory costs in addition to the cost of a 2-day hospital readmission for patients with missed bacteremia and associated treatment failure. The cost of blood cultures was obtained from Medical Fees 2014 (and was converted to 2015 dollars using the medical care services
Methods
Figure 1. Blood culture decision tree comparing universal approach to targeted approach. 2
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ORIGINAL ARTICLES
Table I. Key assumptions for the decision tree Model input
References Author/year
Proportion of children who will be high risk for bacteremia
32%
Proportion of cultures that will be positive in universal arm
3.6%
Proportion of cultures that will be positive in targeted arm (95% guideline sensitivity) Proportion of patients with missed bacteremia in targeted arm (95% guideline sensitivity) Proportion of cultures that will be positive in targeted arm (90% guideline sensitivity) Proportion of patients with missed bacteremia in targeted arm (90% guideline sensitivity) Proportion of cultures that will be positive in targeted arm (80% guideline sensitivity) Proportion of patients with missed bacteremia in targeted arm (80% guideline sensitivity) Proportion of cultures that will be positive in targeted arm (70% guideline sensitivity) Proportion of patients with missed bacteremia in targeted arm (70% guideline sensitivity) Proportion of positive cultures that will be true positive
10.9%
Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Myers et al6 2013
Assumptions
0.15% 10.4% 0.29% 9.4% 0.59% 7.8% 1.0% 60%
Proportion of positive cultures that will be contaminants
40%
Proportion of true positive cultures that will require antibiotic change (bacteria resistant to ampicillin) Cost of positive blood culture Cost of negative or contaminant blood culture Cost of hospital day Length of stay if blood culture drawn (d) Length of stay if no blood culture drawn (d) Annual number of CAP admits
38% $87 $51 $1880 2.0 1.2 177 958
Medical Fees 201413,* Medical Fees 201413,* HCUP 20092,* McCulloh et al7 2015 McCulloh et al7 2015 HCUP 20092
*All costs are converted to 2015 dollars using the Medical Care Services consumer price index.
consumer price index). Medical Fees’ reported costs are based on usual, customary, and reasonable fee schedules used by healthcare managers to set and negotiate healthcare costs; 50th percentile fees were included in our model, and these were varied in the probabilistic sensitivity analysis to account for variations in costs. Blood culture cost was determined to be $51 for a negative blood culture and $87 for a positive culture ($36 for sensitivities).13 We assumed that false-positive cultures would not have sensitivities, thus, a $51 cost was assigned. Secondary analyses from the hospital and patient/family perspective included costs associated with hospital stay. Mean cost/day was estimated using 2009 HCUP Kids Inpatient Database. We used a previously published algorithm for identifying children with CAP in administrative data to then determine mean cost/day.14 We converted these 2009 dollars to 2015 dollars using the Medical Care Services specific consumer price index. In addition, for this secondary analysis, we assumed a 1.2-day length of stay for children who did not have blood cultures drawn and a 2.0-day length of stay for children who did have a blood culture drawn.7
Additional Model Assumptions. Several assumptions were made during the construction of this model. First, consistent with IDSA guidelines, we assumed that all children hospitalized with CAP were started on ampicillin or another
narrow spectrum penicillin. In addition, we assumed that the treating provider would not recognize the patients with missed bacteremia that ultimately leads to treatment failure prior to discharge home. For our primary analysis, we also assumed that the guidelines for identifying children who are at high risk for bacteremia would be 90% sensitive. Using this assigned guideline sensitivity and the known number of cases of true bacteremia per 100 patients,5-10 we were able to assign a proportion of positive cultures, true positive cultures, contaminants, and cases of missed bacteremia in the targeted arm of the decision model. These values vary based on guideline sensitivity. Outcomes The 2 primary clinical outcomes for our model were: (1) the number of patients identified with true bacteremia that would lead to meaningful antibiotic change per 100 hypothetical patients entered into each arm of the model; and (2) the number of patients with missed bacteremia with associated treatment failure (bacteria not susceptible to ampicillin) per 100 hypothetical patients in the targeted arm. Our primary cost outcome was the difference in cost per 100 patients between the targeted arm and the universal arm. For this primary cost analysis, we only included direct costs related to the blood cultures themselves as well as the cost of an additional 2-day readmission for those patients
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with missed bacteremia that leads to treatment failure. Secondary outcomes included the number of blood cultures drawn to identify 1 case of bacteremia that leads to a meaningful antibiotic change in each arm, the difference in laboratory-related costs between arms on an annual population level (using the estimated annual number of pediatric pneumonia admissions from HCUP 2009), and the difference in overall direct costs (laboratory costs plus hospital costs, assuming a 0.8-day length of stay differential between arms) both per 100 patients and on an annual population level. Sensitivity Analyses We performed a probabilistic sensitivity analysis to determine the stability of our model using Oracle Crystal Ball software (Oracle Corporation, Redwood Shores, California). We used beta distributions for proportions and normal distributions for cost and ran 1000 simulations. Because the evidence for the estimate of guideline sensitivity is limited to 1 institution (and was 100% in that study),8 we elected to vary this model input more widely, from 70%-95% and reported these results as part of our primary analysis. For the whole model sensitivity analysis, we assumed a guideline sensitivity of 90%. Because this is a decision analysis model and does not involve interaction with real patients, the Medical University of South Carolina institutional review board does not require review or approval. All analyses were conducted with Excel 2011. Oracle Crystal Ball, a software add-on for Microsoft Excel, was used to run the sensitivity analysis and to generate Figure 2.
Results Compared with the universal approach of obtaining blood cultures in all children admitted with CAP, our model predicts that a targeted approach (assuming 90% guideline sensitivity) results in a cost-savings of $3186 per 100 patients. With this approach, there would be an estimated 0.07 cases of bacteremia missed with treatment failure per 100 patients, compared with zero in the universal approach. In addition, in the universal approach, there would be 0.82 patients with true bacteremia that leads to a meaningful antibiotic change identified per 100 patients. In the universal approach, there would be 122 cultures drawn for every 1 case of bacteremia that leads to a meaningful antibiotic change compared with 42 cultures in the targeted approach (Table II). For our secondary cost analysis including only laboratoryrelated costs on a population level, the targeted approach will save approximately $5 668 778 annually. If hospital costs are included and we assume a 0.8 longer length of stay for patients with blood cultures, the targeted approach is estimated to save approximately $187 669 983 annually (Table II). If the targeted approach is used, and we assume a 90% guideline sensitivity for identifying patients with true bacteremia, we estimate a potential 133 cases of missed bacteremia that lead to treatment failure out of the approximate 178 000 annual admissions for pediatric CAP per year. Results of the sensitivity analysis show stability of our model, with a consistent prediction of cost-savings for the targeted arm (Figure 2). The annual laboratory-related cost savings on the population level ranged from $3 553 077$8 091 890. The number of patients with missed bacteremia
Figure 2. Probabilistic sensitivity analysis results. *Out of estimated 178 000 annual pediatric admissions for CAP. †In 2015 USD. 4
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*Guideline sensitivity for identifying true positives. †Costs are in 2015 US dollars. Blood culture costs and are derived from Medical Fees 2014–A Comprehensive Listing of Current Usual, Customary, and Reasonable, and Medicare Fees with Relative Value Units. Hospital-related costs are from HCUP 2009. Costs were adjusted to 2015 dollars using the Medical Care Services consumer price index. Overall costs include hospital costs and blood culture costs assuming 1.2-day length of stay for nonblood culture patients and 2.0-day length of stay for blood culture patients.
$491 943 304 $276 438 $4 822 430 $2710 0.27 0.57
56
$491 184 248 $276 011 $4 063 373 $2283 0.15 0.68
47
$490 666 335 $275 720 $3 545 460 $1992 0.07 0.76
42
$490 424 945 $275 584 $3 304 071 $1857 0.04 0.79
40
$678 336 318 $381 178 $9 214 238 $5178 122 0 0.82
Universal approach Targeted approach 95% Guideline sensitivity* 90% Guideline sensitivity* 80% Guideline sensitivity* 70% Guideline sensitivity*
Cases of missed bacteremia with treatment failure (per 100 patients)
Number of cultures drawn to identify 1 case of bacteremia with antibiotic change
Laboratory-related costs (per 100 patients)†
Laboratory-related costs (annual population level)
Overall cost including hospital costs (per 100 patients)
Overall cost including hospital costs (annual population level)
ORIGINAL ARTICLES
Patients with true bacteremia that leads to a meaningful antibiotic change (per 100 patients)
Table II. Decision tree analysis results: clinical outcomes and cost differences between universal and targeted approach to obtaining blood cultures in children hospitalized for CAP
- 2015
that leads to treatment failure ranged from 119-149 out of the approximate 178 000 admissions annually (Figure 2).
Discussion Our decision analysis model provides evidence that a targeted approach to obtaining blood cultures in children hospitalized with CAP may be clinically effective, cost-saving, and reduce unnecessary testing. We created a decision analysis model to compare 2 blood culture approaches in children hospitalized with CAP: a universal approach in which blood cultures are obtained in all children and a targeted approach in which blood cultures are obtained in the subset of patients identified as higher risk for bacteremia using published guidelines.8 Our model, which used previously published data regarding proportion of patients who have higher risk for bacteremia, true and false positive culture rates, and the proportion of bacteria isolated that will be sensitive to ampicillin, predicts that the targeted approach will demonstrate cost savings. We have also quantified the clinical implications of these 2 approaches. In 2011, the IDSA published guidelines for the management of CAP in children.3 The guidelines state, “Blood cultures should be obtained in children requiring hospitalization for presumed bacterial CAP that is moderate to severe, particularly those with complicated pneumonia.” This was noted to be a strong recommendation with low quality evidence. The guidelines specifically state, “The costeffectiveness of obtaining blood cultures in all children hospitalized with CAP is not known.” Since the publication of these guidelines, several studies have evaluated the merits of this approach.5-8 These studies, along with the recent publication of the Etiology of Pneumonia in the Community study by Jain et al10 have provided a large amount of data (that was not available at the time of the IDSA guideline publication) that has informed this decision analysis. To assess the impact that the guidelines have had on clinical practice, we refer to a quality improvement project that recently was published describing one institution’s successful effort to increase the percentage of patients admitted with CAP who have blood cultures drawn.9 This group increased the percentage of patients admitted with CAP who had blood cultures drawn from 53%-100% in 6 months.9 This suggests that the IDSA guidelines are impacting physicians’ decision making. In situations such as this, when the medical community is having difficulty arriving at a consensus about which approach is best, a cost-effectiveness analysis can contribute new information that is vital to the debate. In our model, we tried to make conservative assumptions that could bias our results toward the null (or no cost savings in the targeted approach). As an example, our model does not take into account the clinical decision making skills of the treating provider. The model assumes that the provider will not recognize that a child with ampicillinresistant bacteremia is not improving and will discharge this child home on narrow spectrum antibiotics. In reality,
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when a child in the hospital is not improving on narrow spectrum antibiotics, the clinician may consider broadening antibiotic therapy to include coverage for ampicillinresistant Streptococcus pneumoniae or methicillin-resistant Staphylococcal aureus or Mycoplasma pneumoniae. In addition, our primary analysis includes only direct costs related to the blood cultures themselves and not any other downstream costs that would result from having blood cultures drawn including repeat blood cultures for false-positives or true-positive results. We also assumed that all children would be started on ampicillin on admission, and although this is the IDSA recommendation, it is unlikely that these guidelines are followed all of the time. McCulloh et al7 reported that 4 out of 6 of their patients with bacteremia received broad-spectrum cephalosporin therapy at hospital admission. It is difficult to determine if this was because of lack of awareness of the guidelines or the provider identified these children as “sicker” and subsequently choose broader coverage. Therefore, in reality some of the children with ampicillin-resistant bacteremia potentially might be receiving adequate coverage from the beginning of the hospitalization. Finally, the ratio of true positive cultures to false positive cultures in our model is 1.5:1. Among the studies represented in our model the ratio varied from 3.3:1 to 1:1.5, highlighting the variability in this model input.5-10 However, when the data from the 6 included studies was combined, the overall ratio was 1.5:1 or a 60/ 40 split between true positives and false positives. We reran the model to test how our results would be affected if the ratio of true positives to false positives was 1:1.5, and the variable that was affected the most was the number of blood cultures drawn to identify 1 case of bacteremia that required an antibiotic change. In the universal arm, this went from 122-182 and in the targeted arm from 42-63. Because this model input change affects both arms simultaneously, the change in laboratory-related cost savings on the annual population level was negligible (from $5 668 778$5 665 374). This demonstrates that our model is not overly sensitive to change in any 1 model input. This study has several limitations. We are unable to truly predict what will happen to each patient admitted to the hospital with CAP. This decision analysis model, however, takes the best current evidence and makes reasonable assumptions to inform decisions that can have significant clinical and financial impact. Although these assumptions may not precisely reflect real world findings, the effect of the model assumptions on the projected outcomes were carefully tested by probabilistic sensitivity analysis, and the results were consistent. Decision analysis models are limited by the quality of existing literature that can contribute to the model inputs. In our study, data supporting the model assumption of proportion of patients who will be high risk are limited to 1 study8 as are the data supporting the proportion of bacterial isolates that will be susceptible to ampicillin.6 However, the data informing the other model inputs are robust and include recent data (2010-2013) from 12 institutions including over 4900 6
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patients and over 3300 blood cultures. In addition, the published sensitivity of guidelines to identify children with bacteremia is limited to a single institution study, which found that they were 100% sensitive for identifying children with bacteremia. However, because this particular model input is critical for this analysis, we chose to vary the guideline sensitivity widely, from 70%-95%. This variation is much wider than expected in a traditional sensitivity analysis and biases our results toward no cost savings and greater number of cases of missed bacteremia. The primary cost analysis is limited to the direct costs of the blood cultures and sensitivities and does not include costs related to nursing time. In addition, our secondary cost analysis that includes overall hospital costs takes into account one study’s finding that patients with blood cultures drawn have longer hospital length of stays compared with patients with no blood cultures.7 Although this study is retrospective, the authors use propensity score matching in an attempt to isolate the effect of blood culture obtainment on hospital length of stay. Despite their successful matching, there may be unmeasured factors that contribute to hospital length of stay. In conclusion, this decision analysis model provides evidence that a targeted approach to obtaining blood cultures in children hospitalized with community-acquired pneumonia may be clinically effective, cost-saving, and reduce unnecessary testing. n We would like to acknowledge Kit N. Simpson, DrPH (Medical University of South Carolina College of Health Professions), for her assistance in conducting the sensitivity analysis. Submitted for publication Jun 4, 2015; last revision received Jul 22, 2015; accepted Sep 4, 2015. Reprint requests: Annie Lintzenich Andrews, MD, MSCR, Division of General Pediatrics, Department of Pediatrics, Medical University of South Carolina, College of Medicine, 135 Rutledge Ave, PO Box 250561, Charleston, SC 29425. E-mail: [email protected]
References 1. Pfuntner A, Weir LM, Stocks C. Most frequent conditions in U.S. hospitals, 2011. HCUP statistical brief #162. Rockville, MD: Agency for Healthcare Research and Quality; 2013. 2. Healthcare Cost and Utilization Project (HCUP) Kids’ Inpatient Database (KID) [database on the Internet], http://www.hcup-us.ahrq.gov/ kidoverview.jsp; 2009. Accessed October 15, 2014. 3. Bradley JS, Byington CL, Shah SS, Alverson B, Carter ER, Harrison C, et al. The management of community-acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. Clin Infect Dis 2011;53:e25-76. 4. Williams DJ. Do all children hospitalized with community-acquired pneumonia require blood cultures? Hosp Pediatr 2013;3:177-9. 5. Parikh K, Davis AB, Pavuluri P. Do we need this blood culture? Hosp Pediatr 2014;4:78-84. 6. Myers AL, Hall M, Williams DJ, Auger K, Tieder JS, Statile A, et al. Prevalence of bacteremia in hospitalized pediatric patients with communityacquired pneumonia. Pediatr Infect Dis J 2013;32:736-40. 7. McCulloh RJ, Koster MP, Yin DE, Milner TL, Ralston SL, Hill VL, et al. Evaluating the use of blood cultures in the management of children
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- 2015 hospitalized for community-acquired pneumonia. PLoS One 2015;10: e0117462. 8. Heine D, Cochran C, Moore M, Titus MO, Andrews AL. The prevalence of bacteremia in pediatric patients with community acquired pneumona: guidelines to reduce the frequency of obtaining blood cultures. Hosp Pediatr 2013;3:92-6. 9. Kurowski ME, Shah SS, Thomson J, Statile A, Sheehan B, Iyer S, et al. Improvement methodology increases guideline recommended blood cultures in children with pneumonia. Pediatrics 2015;135: e1052-9. 10. Jain S, Williams DJ, Arnold SR, Ampofo K, Bramley AM, Reed C, et al. Community-acquired pneumonia requiring hospitalization among US children. N Engl J Med 2015;372:835-45.
ORIGINAL ARTICLES 11. Leyenaar JK, Lagu T, Shieh MS, Pekow PS, Lindenauer PK. Variation in resource utilization for the management of uncomplicated communityacquired pneumonia across community and children’s hospitals. J Pediatr 2014;165:585-91. 12. Florin TA, French B, Zorc JJ, Alpern ER, Shah SS. Variation in emergency department diagnostic testing and disposition outcomes in pneumonia. Pediatrics 2013;132:237-44. 13. Medical Fees 2015: A Comprehensive Listing of Current UCR and Medicare Fees with Relative Value Units. 1st ed. Los Angeles, CA: PMIC (Practice Management Information Corporation); 2015. p. 644. 14. Williams DJ, Shah SS, Myers A, Hall M, Auger K, Queen MA, et al. Identifying pediatric community-acquired pneumonia hospitalizations: accuracy of administrative billing codes. JAMA Pediatr 2013;167:851-8.
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Study design We conducted a cost-effectiveness analysis using a decision tree to compare 2 approaches to ordering blood cultures in children hospitalized with CAP: obtaining blood cultures in all children admitted with CAP (universal approach) and obtaining blood cultures in patients identified as high risk for bacteremia (targeted approach). We searched the literature to determine expected proportions of high-risk patients, positive culture rates, and predicted bacteria and susceptibility patterns. Our primary clinical outcome was projected rate of missed bacteremia with associated treatment failure in the targeted approach. Costs per 100 patients and annualized costs on the national level were calculated for each approach. Results The model predicts that in the targeted approach, there will be 0.07 cases of missed bacteremia with treatment failure per 100 patients, or 133 annually. In the universal approach, 118 blood cultures would need to be drawn to identify 1 patient with bacteremia, in which the result would lead to a meaningful antibiotic change compared with 42 cultures in the targeted approach. The universal approach would cost $5178 per 100 patients or $9 214 238 annually. The targeted approach would cost $1992 per 100 patients or $3 545 460 annually. The laboratory-related cost savings attributed to the targeted approach would be projected to be $5 668 778 annually. Conclusions This decision analysis model suggests that a targeted approach to obtaining blood cultures in children hospitalized with CAP may be clinically effective, cost-saving, and reduce unnecessary testing. (J Pediatr 2015;-:---).
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ommunity-acquired pneumonia (CAP) is one of the most common reasons for hospitalization among children.1 According to Healthcare Cost and Utilization Project (HCUP) data, there are over 178 000 pediatric admissions for CAP annually.2 In 2011, the Infectious Diseases Society of America (IDSA) published guidelines for the management of CAP in children.3 The guidelines recommend obtaining blood cultures in moderately or severely ill children who are hospitalized with CAP. This was a strong recommendation supported by low quality evidence, and authors of the guideline state that the cost-effectiveness of this approach is not known. Since the publication of the IDSA guidelines, there has been frequent discussion in the literature regarding the clinical utility of obtaining blood cultures in this population of children, primarily because of the low rate of positivity.4-8 Reported rates of bacteremia in children with CAP range from 1.4%-7.0% in recent studies.5-10 Not surprisingly, hospitals have taken different approaches to this clinical decision. Published approaches include aiming for obtaining blood cultures in 100% of children admitted with CAP,9 using criteria to identify children who are at higher risk for bacteremia and obtaining cultures in this subset of patients,8 and benchmarking performance variation among hospital collaboratives and attempting to associate performance with outcomes.11,12 Even in the less likely event that a blood culture is positive, the result does not often change the clinical management.6 Furthermore, if a child is not improving while receiving narrow spectrum antibiotics, a clinician could obtain a culture before broadening coverage. In order to avoid unnecessary testing while also being consistent with guideline recommendation for children who are “moderately to severely ill,”3 a targeted approach focusing on blood culture testing for hospitalized children at higher risk for bacteremia (eg, pneumonia with effusion or empyema or patient admitted to the intensive care unit or immunosuppressed) may improve diagnostic testing yield and avoid tests that are less likely to influence clinical management.8 The objective of this study is to compare the clinical utility and costFrom the Department of Pediatrics, Medical University effectiveness of a universal vs targeted approach to obtaining blood cultures in of South Carolina; Department of Healthcare Leadership and Management, Medical University of children hospitalized with CAP. We included both cost and clinical outcome South Carolina, Charleston, SC; and East Cobb Pediatrics, Marietta, GA measures on a national level in order to inform future guidelines and national 1
2
3
The authors declare no conflicts of interest.
CAP HCUP IDSA
Community-acquired pneumonia Healthcare Cost and Utilization Project Infectious Diseases Society of America
Portions of the study were presented as an abstract at the meeting of the Pediatric Academic Societies, San Diego, CA, April 25-28, 2015. 0022-3476/$ - see front matter. Copyright ª 2015 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jpeds.2015.09.025
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policy decisions with regard to clinical care and quality metrics for children hospitalized with CAP.
We performed a decision analysis, an approach to costeffectiveness analysis that models various approaches to a clinical decision, incorporating the best current evidence available. We estimate the clinical and financial impact of 2 approaches: obtaining a blood culture on all patients with CAP vs a targeted approach focused on identifying children who are at higher risk for bacteremia and limiting blood cultures to this subset of patients. We used the HCUP Kids Inpatient Database to extrapolate our results to the national population to determine the effect of this decision on a national level.
result of which will lead to a meaningful antibiotic change (meaning the isolated bacteria is not susceptible to ampicillin) (38%).6 Consistent with a previously published study, for the purpose of this analysis, patients were considered “high risk” if they met any of the following criteria: (1) <6 months with fever or not fully immunized; (2) have a central line; (3) are immunocompromised; (4) are toxic appearing or admitted to the intensive care unit; (5) have a chronic medical condition; and (6) have an effusion or empyema on chest radiograph.8 The 6 studies referenced in our model include data from 12 US hospitals that care for children from the years 2010-2013. Over 4900 patients are represented in these studies. To arrive at our final model inputs as listed above, we averaged the data from all contributing studies and weighted to account for sample size.
Decision Analysis Model Clinical Data. Once the decision analysis model was created, we surveyed the literature to obtain data on the assumptions needed for the decision tree (Figure 1 and Table I). Assumptions for this analysis included proportion of patients who will qualify as “high risk” based on published guidelines (32%),8 proportion of blood cultures that will be positive (3.5%),5-10 proportion of positive blood cultures that will be true positives (60%) vs contaminants (40%) (representing an overall contamination rate of 1.4%),5-10 and the proportion of true positive cultures, the
Cost Data. The purpose of the cost-effectiveness analysis was to evaluate the cost-effectiveness and/or potential cost savings attributable to applying a targeted approach to obtaining blood cultures in children hospitalized with CAP compared with a universal approach. The primary analysis is from the perspective of the hospital and includes only direct costs related to laboratory costs in addition to the cost of a 2-day hospital readmission for patients with missed bacteremia and associated treatment failure. The cost of blood cultures was obtained from Medical Fees 2014 (and was converted to 2015 dollars using the medical care services
Methods
Figure 1. Blood culture decision tree comparing universal approach to targeted approach. 2
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ORIGINAL ARTICLES
Table I. Key assumptions for the decision tree Model input
References Author/year
Proportion of children who will be high risk for bacteremia
32%
Proportion of cultures that will be positive in universal arm
3.6%
Proportion of cultures that will be positive in targeted arm (95% guideline sensitivity) Proportion of patients with missed bacteremia in targeted arm (95% guideline sensitivity) Proportion of cultures that will be positive in targeted arm (90% guideline sensitivity) Proportion of patients with missed bacteremia in targeted arm (90% guideline sensitivity) Proportion of cultures that will be positive in targeted arm (80% guideline sensitivity) Proportion of patients with missed bacteremia in targeted arm (80% guideline sensitivity) Proportion of cultures that will be positive in targeted arm (70% guideline sensitivity) Proportion of patients with missed bacteremia in targeted arm (70% guideline sensitivity) Proportion of positive cultures that will be true positive
10.9%
Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Parikh et al5 2014; Myers et al6 2013; McCulloh et al7 2015; Heine et al8 2013; Kurowski et al9 2015; Jain et al 201510 Myers et al6 2013
Assumptions
0.15% 10.4% 0.29% 9.4% 0.59% 7.8% 1.0% 60%
Proportion of positive cultures that will be contaminants
40%
Proportion of true positive cultures that will require antibiotic change (bacteria resistant to ampicillin) Cost of positive blood culture Cost of negative or contaminant blood culture Cost of hospital day Length of stay if blood culture drawn (d) Length of stay if no blood culture drawn (d) Annual number of CAP admits
38% $87 $51 $1880 2.0 1.2 177 958
Medical Fees 201413,* Medical Fees 201413,* HCUP 20092,* McCulloh et al7 2015 McCulloh et al7 2015 HCUP 20092
*All costs are converted to 2015 dollars using the Medical Care Services consumer price index.
consumer price index). Medical Fees’ reported costs are based on usual, customary, and reasonable fee schedules used by healthcare managers to set and negotiate healthcare costs; 50th percentile fees were included in our model, and these were varied in the probabilistic sensitivity analysis to account for variations in costs. Blood culture cost was determined to be $51 for a negative blood culture and $87 for a positive culture ($36 for sensitivities).13 We assumed that false-positive cultures would not have sensitivities, thus, a $51 cost was assigned. Secondary analyses from the hospital and patient/family perspective included costs associated with hospital stay. Mean cost/day was estimated using 2009 HCUP Kids Inpatient Database. We used a previously published algorithm for identifying children with CAP in administrative data to then determine mean cost/day.14 We converted these 2009 dollars to 2015 dollars using the Medical Care Services specific consumer price index. In addition, for this secondary analysis, we assumed a 1.2-day length of stay for children who did not have blood cultures drawn and a 2.0-day length of stay for children who did have a blood culture drawn.7
Additional Model Assumptions. Several assumptions were made during the construction of this model. First, consistent with IDSA guidelines, we assumed that all children hospitalized with CAP were started on ampicillin or another
narrow spectrum penicillin. In addition, we assumed that the treating provider would not recognize the patients with missed bacteremia that ultimately leads to treatment failure prior to discharge home. For our primary analysis, we also assumed that the guidelines for identifying children who are at high risk for bacteremia would be 90% sensitive. Using this assigned guideline sensitivity and the known number of cases of true bacteremia per 100 patients,5-10 we were able to assign a proportion of positive cultures, true positive cultures, contaminants, and cases of missed bacteremia in the targeted arm of the decision model. These values vary based on guideline sensitivity. Outcomes The 2 primary clinical outcomes for our model were: (1) the number of patients identified with true bacteremia that would lead to meaningful antibiotic change per 100 hypothetical patients entered into each arm of the model; and (2) the number of patients with missed bacteremia with associated treatment failure (bacteria not susceptible to ampicillin) per 100 hypothetical patients in the targeted arm. Our primary cost outcome was the difference in cost per 100 patients between the targeted arm and the universal arm. For this primary cost analysis, we only included direct costs related to the blood cultures themselves as well as the cost of an additional 2-day readmission for those patients
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with missed bacteremia that leads to treatment failure. Secondary outcomes included the number of blood cultures drawn to identify 1 case of bacteremia that leads to a meaningful antibiotic change in each arm, the difference in laboratory-related costs between arms on an annual population level (using the estimated annual number of pediatric pneumonia admissions from HCUP 2009), and the difference in overall direct costs (laboratory costs plus hospital costs, assuming a 0.8-day length of stay differential between arms) both per 100 patients and on an annual population level. Sensitivity Analyses We performed a probabilistic sensitivity analysis to determine the stability of our model using Oracle Crystal Ball software (Oracle Corporation, Redwood Shores, California). We used beta distributions for proportions and normal distributions for cost and ran 1000 simulations. Because the evidence for the estimate of guideline sensitivity is limited to 1 institution (and was 100% in that study),8 we elected to vary this model input more widely, from 70%-95% and reported these results as part of our primary analysis. For the whole model sensitivity analysis, we assumed a guideline sensitivity of 90%. Because this is a decision analysis model and does not involve interaction with real patients, the Medical University of South Carolina institutional review board does not require review or approval. All analyses were conducted with Excel 2011. Oracle Crystal Ball, a software add-on for Microsoft Excel, was used to run the sensitivity analysis and to generate Figure 2.
Results Compared with the universal approach of obtaining blood cultures in all children admitted with CAP, our model predicts that a targeted approach (assuming 90% guideline sensitivity) results in a cost-savings of $3186 per 100 patients. With this approach, there would be an estimated 0.07 cases of bacteremia missed with treatment failure per 100 patients, compared with zero in the universal approach. In addition, in the universal approach, there would be 0.82 patients with true bacteremia that leads to a meaningful antibiotic change identified per 100 patients. In the universal approach, there would be 122 cultures drawn for every 1 case of bacteremia that leads to a meaningful antibiotic change compared with 42 cultures in the targeted approach (Table II). For our secondary cost analysis including only laboratoryrelated costs on a population level, the targeted approach will save approximately $5 668 778 annually. If hospital costs are included and we assume a 0.8 longer length of stay for patients with blood cultures, the targeted approach is estimated to save approximately $187 669 983 annually (Table II). If the targeted approach is used, and we assume a 90% guideline sensitivity for identifying patients with true bacteremia, we estimate a potential 133 cases of missed bacteremia that lead to treatment failure out of the approximate 178 000 annual admissions for pediatric CAP per year. Results of the sensitivity analysis show stability of our model, with a consistent prediction of cost-savings for the targeted arm (Figure 2). The annual laboratory-related cost savings on the population level ranged from $3 553 077$8 091 890. The number of patients with missed bacteremia
Figure 2. Probabilistic sensitivity analysis results. *Out of estimated 178 000 annual pediatric admissions for CAP. †In 2015 USD. 4
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*Guideline sensitivity for identifying true positives. †Costs are in 2015 US dollars. Blood culture costs and are derived from Medical Fees 2014–A Comprehensive Listing of Current Usual, Customary, and Reasonable, and Medicare Fees with Relative Value Units. Hospital-related costs are from HCUP 2009. Costs were adjusted to 2015 dollars using the Medical Care Services consumer price index. Overall costs include hospital costs and blood culture costs assuming 1.2-day length of stay for nonblood culture patients and 2.0-day length of stay for blood culture patients.
$491 943 304 $276 438 $4 822 430 $2710 0.27 0.57
56
$491 184 248 $276 011 $4 063 373 $2283 0.15 0.68
47
$490 666 335 $275 720 $3 545 460 $1992 0.07 0.76
42
$490 424 945 $275 584 $3 304 071 $1857 0.04 0.79
40
$678 336 318 $381 178 $9 214 238 $5178 122 0 0.82
Universal approach Targeted approach 95% Guideline sensitivity* 90% Guideline sensitivity* 80% Guideline sensitivity* 70% Guideline sensitivity*
Cases of missed bacteremia with treatment failure (per 100 patients)
Number of cultures drawn to identify 1 case of bacteremia with antibiotic change
Laboratory-related costs (per 100 patients)†
Laboratory-related costs (annual population level)
Overall cost including hospital costs (per 100 patients)
Overall cost including hospital costs (annual population level)
ORIGINAL ARTICLES
Patients with true bacteremia that leads to a meaningful antibiotic change (per 100 patients)
Table II. Decision tree analysis results: clinical outcomes and cost differences between universal and targeted approach to obtaining blood cultures in children hospitalized for CAP
- 2015
that leads to treatment failure ranged from 119-149 out of the approximate 178 000 admissions annually (Figure 2).
Discussion Our decision analysis model provides evidence that a targeted approach to obtaining blood cultures in children hospitalized with CAP may be clinically effective, cost-saving, and reduce unnecessary testing. We created a decision analysis model to compare 2 blood culture approaches in children hospitalized with CAP: a universal approach in which blood cultures are obtained in all children and a targeted approach in which blood cultures are obtained in the subset of patients identified as higher risk for bacteremia using published guidelines.8 Our model, which used previously published data regarding proportion of patients who have higher risk for bacteremia, true and false positive culture rates, and the proportion of bacteria isolated that will be sensitive to ampicillin, predicts that the targeted approach will demonstrate cost savings. We have also quantified the clinical implications of these 2 approaches. In 2011, the IDSA published guidelines for the management of CAP in children.3 The guidelines state, “Blood cultures should be obtained in children requiring hospitalization for presumed bacterial CAP that is moderate to severe, particularly those with complicated pneumonia.” This was noted to be a strong recommendation with low quality evidence. The guidelines specifically state, “The costeffectiveness of obtaining blood cultures in all children hospitalized with CAP is not known.” Since the publication of these guidelines, several studies have evaluated the merits of this approach.5-8 These studies, along with the recent publication of the Etiology of Pneumonia in the Community study by Jain et al10 have provided a large amount of data (that was not available at the time of the IDSA guideline publication) that has informed this decision analysis. To assess the impact that the guidelines have had on clinical practice, we refer to a quality improvement project that recently was published describing one institution’s successful effort to increase the percentage of patients admitted with CAP who have blood cultures drawn.9 This group increased the percentage of patients admitted with CAP who had blood cultures drawn from 53%-100% in 6 months.9 This suggests that the IDSA guidelines are impacting physicians’ decision making. In situations such as this, when the medical community is having difficulty arriving at a consensus about which approach is best, a cost-effectiveness analysis can contribute new information that is vital to the debate. In our model, we tried to make conservative assumptions that could bias our results toward the null (or no cost savings in the targeted approach). As an example, our model does not take into account the clinical decision making skills of the treating provider. The model assumes that the provider will not recognize that a child with ampicillinresistant bacteremia is not improving and will discharge this child home on narrow spectrum antibiotics. In reality,
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when a child in the hospital is not improving on narrow spectrum antibiotics, the clinician may consider broadening antibiotic therapy to include coverage for ampicillinresistant Streptococcus pneumoniae or methicillin-resistant Staphylococcal aureus or Mycoplasma pneumoniae. In addition, our primary analysis includes only direct costs related to the blood cultures themselves and not any other downstream costs that would result from having blood cultures drawn including repeat blood cultures for false-positives or true-positive results. We also assumed that all children would be started on ampicillin on admission, and although this is the IDSA recommendation, it is unlikely that these guidelines are followed all of the time. McCulloh et al7 reported that 4 out of 6 of their patients with bacteremia received broad-spectrum cephalosporin therapy at hospital admission. It is difficult to determine if this was because of lack of awareness of the guidelines or the provider identified these children as “sicker” and subsequently choose broader coverage. Therefore, in reality some of the children with ampicillin-resistant bacteremia potentially might be receiving adequate coverage from the beginning of the hospitalization. Finally, the ratio of true positive cultures to false positive cultures in our model is 1.5:1. Among the studies represented in our model the ratio varied from 3.3:1 to 1:1.5, highlighting the variability in this model input.5-10 However, when the data from the 6 included studies was combined, the overall ratio was 1.5:1 or a 60/ 40 split between true positives and false positives. We reran the model to test how our results would be affected if the ratio of true positives to false positives was 1:1.5, and the variable that was affected the most was the number of blood cultures drawn to identify 1 case of bacteremia that required an antibiotic change. In the universal arm, this went from 122-182 and in the targeted arm from 42-63. Because this model input change affects both arms simultaneously, the change in laboratory-related cost savings on the annual population level was negligible (from $5 668 778$5 665 374). This demonstrates that our model is not overly sensitive to change in any 1 model input. This study has several limitations. We are unable to truly predict what will happen to each patient admitted to the hospital with CAP. This decision analysis model, however, takes the best current evidence and makes reasonable assumptions to inform decisions that can have significant clinical and financial impact. Although these assumptions may not precisely reflect real world findings, the effect of the model assumptions on the projected outcomes were carefully tested by probabilistic sensitivity analysis, and the results were consistent. Decision analysis models are limited by the quality of existing literature that can contribute to the model inputs. In our study, data supporting the model assumption of proportion of patients who will be high risk are limited to 1 study8 as are the data supporting the proportion of bacterial isolates that will be susceptible to ampicillin.6 However, the data informing the other model inputs are robust and include recent data (2010-2013) from 12 institutions including over 4900 6
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patients and over 3300 blood cultures. In addition, the published sensitivity of guidelines to identify children with bacteremia is limited to a single institution study, which found that they were 100% sensitive for identifying children with bacteremia. However, because this particular model input is critical for this analysis, we chose to vary the guideline sensitivity widely, from 70%-95%. This variation is much wider than expected in a traditional sensitivity analysis and biases our results toward no cost savings and greater number of cases of missed bacteremia. The primary cost analysis is limited to the direct costs of the blood cultures and sensitivities and does not include costs related to nursing time. In addition, our secondary cost analysis that includes overall hospital costs takes into account one study’s finding that patients with blood cultures drawn have longer hospital length of stays compared with patients with no blood cultures.7 Although this study is retrospective, the authors use propensity score matching in an attempt to isolate the effect of blood culture obtainment on hospital length of stay. Despite their successful matching, there may be unmeasured factors that contribute to hospital length of stay. In conclusion, this decision analysis model provides evidence that a targeted approach to obtaining blood cultures in children hospitalized with community-acquired pneumonia may be clinically effective, cost-saving, and reduce unnecessary testing. n We would like to acknowledge Kit N. Simpson, DrPH (Medical University of South Carolina College of Health Professions), for her assistance in conducting the sensitivity analysis. Submitted for publication Jun 4, 2015; last revision received Jul 22, 2015; accepted Sep 4, 2015. Reprint requests: Annie Lintzenich Andrews, MD, MSCR, Division of General Pediatrics, Department of Pediatrics, Medical University of South Carolina, College of Medicine, 135 Rutledge Ave, PO Box 250561, Charleston, SC 29425. E-mail: [email protected]
References 1. Pfuntner A, Weir LM, Stocks C. Most frequent conditions in U.S. hospitals, 2011. HCUP statistical brief #162. Rockville, MD: Agency for Healthcare Research and Quality; 2013. 2. Healthcare Cost and Utilization Project (HCUP) Kids’ Inpatient Database (KID) [database on the Internet], http://www.hcup-us.ahrq.gov/ kidoverview.jsp; 2009. Accessed October 15, 2014. 3. Bradley JS, Byington CL, Shah SS, Alverson B, Carter ER, Harrison C, et al. The management of community-acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. Clin Infect Dis 2011;53:e25-76. 4. Williams DJ. Do all children hospitalized with community-acquired pneumonia require blood cultures? Hosp Pediatr 2013;3:177-9. 5. Parikh K, Davis AB, Pavuluri P. Do we need this blood culture? Hosp Pediatr 2014;4:78-84. 6. Myers AL, Hall M, Williams DJ, Auger K, Tieder JS, Statile A, et al. Prevalence of bacteremia in hospitalized pediatric patients with communityacquired pneumonia. Pediatr Infect Dis J 2013;32:736-40. 7. McCulloh RJ, Koster MP, Yin DE, Milner TL, Ralston SL, Hill VL, et al. Evaluating the use of blood cultures in the management of children
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- 2015 hospitalized for community-acquired pneumonia. PLoS One 2015;10: e0117462. 8. Heine D, Cochran C, Moore M, Titus MO, Andrews AL. The prevalence of bacteremia in pediatric patients with community acquired pneumona: guidelines to reduce the frequency of obtaining blood cultures. Hosp Pediatr 2013;3:92-6. 9. Kurowski ME, Shah SS, Thomson J, Statile A, Sheehan B, Iyer S, et al. Improvement methodology increases guideline recommended blood cultures in children with pneumonia. Pediatrics 2015;135: e1052-9. 10. Jain S, Williams DJ, Arnold SR, Ampofo K, Bramley AM, Reed C, et al. Community-acquired pneumonia requiring hospitalization among US children. N Engl J Med 2015;372:835-45.
ORIGINAL ARTICLES 11. Leyenaar JK, Lagu T, Shieh MS, Pekow PS, Lindenauer PK. Variation in resource utilization for the management of uncomplicated communityacquired pneumonia across community and children’s hospitals. J Pediatr 2014;165:585-91. 12. Florin TA, French B, Zorc JJ, Alpern ER, Shah SS. Variation in emergency department diagnostic testing and disposition outcomes in pneumonia. Pediatrics 2013;132:237-44. 13. Medical Fees 2015: A Comprehensive Listing of Current UCR and Medicare Fees with Relative Value Units. 1st ed. Los Angeles, CA: PMIC (Practice Management Information Corporation); 2015. p. 644. 14. Williams DJ, Shah SS, Myers A, Hall M, Auger K, Queen MA, et al. Identifying pediatric community-acquired pneumonia hospitalizations: accuracy of administrative billing codes. JAMA Pediatr 2013;167:851-8.
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