Hysterectomy is one the most common major surgical procedures performed in the United States. With more than 500,000 hysterectomies performed each year, it accounts for more than $5 billion in health care spending.1,2 Traditionally, hysterectomy has been performed abdominally through a laparotomy incision, vaginally, or laparoscopically. Over the past 25 years, technologic advances, coupled with changes in practice patterns regarding route of hysterectomy, have led to an increase in minimally invasive options.1,3,4
Advantages of laparoscopic hysterectomy over open abdominal hysterectomy are decreased postoperative pain, shorter hospital stay, and quicker return to daily activities.3,4 However, some of the challenges to widespread adoption of the laparoscopic approach are the steep learning curve, longer operating times as well as counterintuitive hand movement, two-dimensional visualization, and limited instrument mobility.5 Robotic-assisted laparoscopic surgery was developed to overcome some of the limiting aspects of conventional laparoscopy. Advantages of the robotic platform include better ergonomics, wider range of motion, and three-dimensional stereo vision.5 This platform has grown increasingly popular with gynecologic surgeries currently composing approximately half of all procedures using the Intuitive DaVinci System.6,7
The rapid uptake of robotic-assisted hysterectomy for benign gynecologic disease has expanded the options for achieving a minimally invasive hysterectomy; however, the available data about its comparative effectiveness have been limited to observational studies and two randomized trials which in total include 148 patients.8–16 These studies have demonstrated similar outcomes between robotic-assisted hysterectomy and conventional laparoscopic hysterectomy with higher costs for robotic-assisted procedures. However, the majority of the published data from observational studies and clinical trials come from highly experienced surgical centers. These results may not be generalizable as the procedure diffuses into wider practice.
Using a nationwide sample, a recent study by Wright et al16 showed similar results as the previous observational studies. Using an all-payer representative nationwide population-based database, we examined specific perioperative outcomes and costs of robotic-assisted hysterectomy compared with laparoscopic hysterectomy. As the largest all-payer inpatient database, the Nationwide Inpatient Sample captures 20% of all hospital admissions in the United States, allowing us to examine whether there is an improvement in perioperative outcomes when using robotic technology for benign hysterectomy.
MATERIALS AND METHODS
The population of patients for the study consisted of women older than 18 years of age undergoing conventional or robotic laparoscopic hysterectomy for treatment of benign uterine disease in the United States. Data were obtained from the 2009 and 2010 Nationwide Inpatient Sample from the Healthcare Cost and Utilization Project of the Agency for Health Care Research and Quality.17 The Nationwide Inpatient Sample is the largest all-payer inpatient database in the United States. It represents a 20% stratified sample of inpatient discharges from nonfederal academic, community, and acute care hospitals. More than 1,000 hospitals are included in the Nationwide Inpatient Sample each year. The sampling strategy of the Nationwide Inpatient Sample allows inclusion in the database of all discharge data from hospitals selected for the survey in a specific year. A total of 44 and 45 states contributed to Nationwide Inpatient Sample data in 2009 and 2010, respectively. The study was limited to the years 2009 and 2010 because a specific International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) procedure code useful to identify robotic-assisted hysterectomy was first introduced in 2008. However, data from the 2008 Nationwide Inpatient Sample data set was not included in the analysis to avoid the effect of undercoding of the newly introduced procedure code in 2008. Because the Nationwide Inpatient Sample data sets consist of publically available and deidentified data, the study was determined to be exempt from review by the University of Texas Southwestern Medical Center institutional review board.
Hospital discharges with ICD-9-CM procedure codes for laparoscopic supracervical hysterectomy (68.31), laparoscopic total abdominal hysterectomy (68.41, 68.61), and laparoscopic-assisted vaginal hysterectomy (68.51) were identified from the Nationwide Inpatient Sample data sets. Discharges with the ICD-9-CM procedure code for “laparoscopic robotic-assisted procedure” (17.42 and 17.44) in combination with any of the hysterectomy codes were categorized as having undergone a robotic-assisted hysterectomy. Otherwise, cases were categorized as laparoscopic hysterectomy. Patients with ICD-9-CM diagnostic codes for malignant neoplasm of female genital organs (179 and 180.0–184.9) were excluded from the analyses.
Twenty-six comorbidity variables were created from the up to 25 ICD-9-CM diagnosis codes present in each discharge record. The Agency for Healthcare Research and Quality Comorbidity Software, a family of tools developed as part of the Healthcare Cost and Utilization Project, was used to create the comorbidity variables. The software allows identification of comorbidities excluding conditions that may be complications of the admission or procedure or that may be related to the principal diagnosis.18 In addition, the Charlson-Deyo comorbidity index was calculated for each patient based on the ICD-9-CM diagnosis codes available from the database. The Charlson comorbidity index is a validated measure for use with administrative data that correlates with in-hospital morbidity and mortality after surgical procedures.19 The index is the composite of 22 comorbidities, which are assigned a score of 1, 2, 3, or 6 depending on the respective associated postoperative risk. Hospital characteristics such as teaching status of hospital, bed size, and location of hospital (urban compared with rural) as well as demographic characteristics of patients (age, race and ethnicity, and type of health care insurance) were obtained directly from separate variables available in the Nationwide Inpatient Sample. A hospital was defined as a teaching hospitals if it had an approved residency program, was a member of the Council of Teaching Hospitals, or had a ratio of full-time equivalent interns and residents to beds of .25 or higher. Socioeconomic status was assessed using the quartile classification of the estimated median household income of residents in the patient's zip code. This information is provided directly in the Nationwide Inpatient Sample database. Because practice patterns have been shown to vary substantially by geographic region in the United States,20,21 the hospital's census region (Northeast, Midwest or North–Central, South, and West) was also identified and incorporated into the analyses.
Given that the comparative rate of outcomes between robotic-assisted hysterectomy and laparoscopic hysterectomy can be affected by the surgical diagnosis and performance of concomitant procedures during hysterectomy, additional variables were created to account for these factors. ICD-9-CM codes and Agency for Healthcare Research and Quality Clinical Classifications Software22 codes were used to define these variables. Surgical diagnoses included endometriosis (Clinical Classification code 169); fibroids (Clinical Classification code 46); adenomyosis (ICD-9-CM code 617.0); peritoneal adhesions (ICD-9-CM code 568.0,614.6); presence of adnexal mass, inflammation, or infection (ICD-9-CM codes 220, 221, 620.1, 620.2, 621, 614, 614.1, 614.2, 614.3, 614.4, 614.8); chronic pelvic pain (ICD-9-CM codes 625.8, 625.9); and pelvic organ prolapse (Clinical Classification code 170). Additional surgical procedures included adnexal surgery (Clinical Classification codes 119, 120, 123); repair of pelvic organ prolapse (ICD-9-CM codes 705.0, 705.1, 705.2, 705.3, 705.4, 705.5, 707.2, 707.3, 707.4, 707.5, 707.7, 707.8, 707.9, 709.4, 709.5); lysis of peritoneal adhesions (ICD-9-CM codes 545.1, 545.9); and procedures to treat endometriosis (ICD-9-CM codes 54.4, 68.23, 65.25, 65.29, 66.61, 68.29, 70.32). Any cases identified with the ICD-9 diagnosis code V64.41 (conversion to open surgery) were excluded as a result of the inability to classify whether the case started as either a robotic-assisted hysterectomy or laparoscopic hysterectomy.
In-hospital mortality, perioperative adverse events, hospital length of stay, and cost of hospital care were compared between robotic-assisted hysterectomy and laparoscopic hysterectomy. The primary end point for the study was the composite of any in-hospital death or any surgical or medical perioperative adverse event. In-hospital death was determined directly from a variable present in the database. In-hospital perioperative adverse events were determined from the diagnostic and procedure ICD-9-CM codes present in the Nationwide Inpatient Sample. Surgical adverse events included accidental puncture or laceration of pelvic or abdominal organs, foreign body left during procedure, iatrogenic pneumothorax, surgical wound disruption, postoperative hemorrhage or hematoma, and blood transfusion. Medical adverse events included postoperative stroke, respiratory failure, endotracheal intubation, pneumonia, atelectasis, pulmonary embolism or deep vein thrombosis, myocardial infarction, acute renal failure, ileus, urinary tract infection, urinary retention, fever, and sepsis.
The cost of hospital services was estimated by applying the Healthcare Cost Utilization Project Cost-to-Charge Ratio Files to reported hospital charges. The Nationwide Inpatient Sample only provides information on hospital charges, which usually overestimates the actual cost of hospital care. However, the use of Cost-to Charge Ratio Files allows the conversion of charge data to cost estimates. The Cost-to-Charge files are a validated tool to estimate hospital costs and are constructed using all-payer, inpatient cost and charge information from the detailed reports by hospitals to the Centers for Medicare and Medicaid Services.23 Hospital charges were adjusted for inflation using the Consumer Price Index and converted to 2010 U.S. dollars.
Univariate analyses were performed to compare patients undergoing robotic-assisted hysterectomy or laparoscopic hysterectomy regarding baseline characteristics. Weighted analyses taking into account the Nationwide Inpatient Sample survey design were conducted on the nonmatched cohort of hospital discharges using the SURVEY FREQ, SURVEY REG, and SURVEY MEANS procedures of SAS software. Continuous variables are summarized as means±standard deviations, except for heavily skewed distributions, which are reported as medians and interquartile ranges. Discrete variables are presented as frequencies and group percentages. Propensity scores derived from a logistic regression model (constructed to estimate the conditional probability for receiving a robotic-assisted hysterectomy) were used to assemble a one-to-one matched cohort of patients undergoing robotic-assisted hysterectomy or laparoscopic hysterectomy. Covariates in the model for propensity score included demographics, comorbidities, surgical diagnoses, type of hysterectomy (total compared with supracervical), concomitant surgical procedures, type of health care insurance, and hospital characteristics. Propensity matching was done using a greedy eight-to-one digit-matching algorithm technique. Under this algorithm, each patient undergoing robotic-assisted hysterectomy was matched to a patient undergoing laparoscopic hysterectomy whose propensity score was as close as possible to that of the patient undergoing robotic-assisted hysterectomy starting at the eighth digit of precision. When all matches at the eighth digit were exhausted, patients undergoing robotic-assisted hysterectomy were then matched to patients undergoing laparoscopic hysterectomy on seven digits of the propensity score, and the algorithm proceeded sequentially until finding a laparoscopic hysterectomy match for each patient undergoing robotic-assisted hysterectomy or until the one digit of propensity score precision matching was reached. Absolute standardized differences were calculated to assess postmatch balance between the propensity-matched groups. An absolute standardized difference equal to or smaller than 10% indicates appropriate balance of a baseline covariate between the groups.24 Differences in the composite primary end point as well as in in-hospital mortality and incidence of perioperative surgical and medical adverse events were assessed between the matched groups using McNemar's tests. Relative risks with 95% confidence intervals (CIs) were calculated for each outcome. Because hospital length of stay and costs of hospital care were not normally distributed, these variables were described as medians and interquartile ranges and compared between the matched groups using Wilcoxon signed-rank tests. Given the right-skewed distribution of the data, differences in hospital cost of care between robotic-assisted hysterectomy and laparoscopic hysterectomy were estimated using quantile regression analyses, as described previously.25 Quantile regression results in estimates approximating the median (or other quantile) of the response variable, and because it makes no distributional assumption about the error term in the model, this technique offers considerable robustness when the distributional assumptions of conditional mean regression are not met.26 All statistical tests were two-tailed. A P value of .005 (adjusting for multiple testing) was considered statistically significant. SAS 9.2 software was used for all the analyses.
A total of 804,551 hysterectomies for benign conditions were performed in the United States during 2009 and 2010. In 2009, there were 242,428 (56.68%) abdominal hysterectomies, 81,446 (19.04%) total vaginal hysterectomies, 86,253 (20.17%) laparoscopic hysterectomies, and 17,587 (4.11%) robotic-assisted hysterectomies. In 2010, there were 202,262 (53.67%) abdominal hysterectomies, 71,793 (19.05%) total vaginal hysterectomies, 79,128 (21.0%) laparoscopic hysterectomies, and 23,654 (6.28%) robotic-assisted hysterectomies. The total number of hysterectomies decreased from 427,714 to 376,837, and in relation to all hysterectomies over the time period, the rate of abdominal hysterectomy decreased 3%, laparoscopic hysterectomy increased 1%, robotic-assisted hysterectomy increased 2%, whereas the rate of total vaginal hysterectomy remained unchanged. The use of robotic-assisted hysterectomy among minimally invasive hysterectomies increased from 9.5 in 2009 to 13.6% in 2010 (P=.002). Laparoscopic hysterectomy and robotic-assisted hysterectomy represented, respectively, 20.6% and 5.1% of the 804,551 hysterectomies performed in the United States in 2009 and 2010. Table 1 describes the baseline clinical, demographic, and hospital characteristics of patients undergoing robotic-assisted hysterectomy and laparoscopic hysterectomy in 2009 to 2010 in the United States in the nonmatched cohort. Patients undergoing robotic-assisted hysterectomy were on an average older and had higher comorbidity scores than patients undergoing laparoscopic hysterectomy. The weighted data before matching revealed that patients undergoing robotic-assisted hysterectomy were more likely to have Medicare or private insurance, to live in zip code areas of higher median household income, and to have the procedure performed in large, urban, and teaching hospitals. Patients undergoing robotic-assisted hysterectomy were also more likely to have higher prevalence of chronic conditions like hypertension, congestive heart failure, diabetes mellitus, chronic renal failure, and obesity. Similarly, a diagnosis of fibroids or peritoneal adhesions was more frequent among patients undergoing robotic-assisted hysterectomy . In contrast, patients undergoing laparoscopic hysterectomy were more likely to have diagnoses of endometriosis, adenomyosis, pelvic organ prolapse, and chronic pelvic pain. In addition, laparoscopic hysterectomy was used more often to perform supracervical hysterectomies (21.9% compared with 13.1%), whereas robotic-assisted hysterectomy was used more frequently to perform total hysterectomies (86.9% compared with 78.1%).
The propensity-matching algorithm produced a cohort of 7,788 patients undergoing robotic-assisted hysterectomy and 7,788 patients undergoing laparoscopic hysterectomy for benign gynecologic conditions, well balanced on baseline characteristics (Table 2). The rate of in-hospital mortality was very low for both robotic-assisted hysterectomy and laparoscopic hysterectomy and not statistically different between the groups (0.03% compared with 0%, respectively; P=.249). Similarly, the incidence of the composite outcome of death, surgical, or medical complications was similar for both groups (8.80% compared with 8.85%, relative risk for robotic-assisted hysterectomy 0.99, 95% CI 0.89–1.09, P=.910) (Table 3). Although patients undergoing robotic-assisted hysterectomy had significantly lower incidence of blood transfusions than patients undergoing laparoscopic hysterectomy (2.1% compared with 3.1%, respectively; P<.001), in general, the rate of surgical complications was comparable between the groups (4.67% compared with 5.33%; P=.060). The rate of medical postoperative adverse events was also similar between robotic-assisted hysterectomy and laparoscopic hysterectomy (4.78% compared with 4.35%, respectively; P=.205). However, patients undergoing robotic-assisted hysterectomy were approximately two times more likely to experience postoperative pneumonia (relative risk 2.2, 95% CI 1.24–3.78, P=.005) than patients undergoing laparoscopic hysterectomy, and there was a trend to increased postoperative endotracheal intubations (relative risk 1.84, 95% CI 0.94–3.62, P=.07) in the robotic-assisted hysterectomy group.
Hospital length of stay was, on average, not significantly different between the groups. For both robotic-assisted hysterectomy and laparoscopic hysterectomy the median length of stay was 1 day and 75% of the patients were discharged from the hospital in 2 days or less. Finally, the median inflation-adjusted cost of hospital care was $9,788 (interquartile range $7,105–12,780) for robotic-assisted hysterectomy and $7,299 (interquartile range $5,650–9,583) for laparoscopic hysterectomy (P<.001). Hospital costs were on average $2,489 (95% CI $2,313–2,664) higher for patients undergoing robotic-assisted hysterectomy compared with those undergoing laparoscopic hysterectomy.
This nationwide, population-based analysis demonstrates that 25% of all hysterectomies for benign disease were performed either laparoscopically or robotically assisted with one robotic-assisted hysterectomy performed for every four laparoscopic hysterectomies. From 2009 to 2010, the use of robotic-assisted hysterectomy increased from 4.1% to 6.3% of all hysterectomies, whereas abdominal hysterectomy rates fell and vaginal hysterectomy rates remained unchanged. Compared with laparoscopic hysterectomy, robotic-assisted hysterectomy is being performed more frequently in patients with higher incomes and who have private insurance as well as in larger, urban, teaching hospitals. Notably patients undergoing robotic-assisted hysterectomy were older and had more comorbidities.
In our comparison of 7,778 closely matched patients, in-hospital perioperative complication rates were similar between the two procedures. Our analysis demonstrated significantly more blood transfusions in the laparoscopic hysterectomy group, although hemorrhage and hematoma rates were similar. These findings contrast with previous randomized trials that found no difference in blood loss between the two groups.13,14 The robotic-assisted hysterectomy group experienced more pulmonary complications with a higher incidence of postoperative pneumonia. Possibly related to this was a trend toward more postoperative endotracheal intubations. Most studies have consistently demonstrated longer operating times for robotic-assisted hysterectomy (ranging from 26 to 72 minutes longer)9–13,15 and Pasic et al15 found a similar trend toward pulmonary adverse events. We propose that the increased need for postoperative intubation may be the result of airway edema and basal atelectasis that may develop during lengthy procedures in steep Trendelenburg positioning, which may make tracheal extubation difficult.
Affirming the finding that robotic-assisted hysterectomy cases cost more, we found that the total cost estimates for robotic-assisted hysterectomy are consistently higher by $2,489 per case.12,15,16 Unfortunately, the greater costs associated with robotic-assisted hysterectomy were not reflected in improvement in outcomes.
We recognize several limitations of our analysis. The Nationwide Inpatient Sample is a large database that receives diagnosis and procedural codes from 45 state databases. Therefore, underestimation of complication rates and errors in classification of predictor variables are possible, although it is likely that such systematic errors would be consistent across groups. Additionally, the Nationwide Inpatient Sample does not include factors such as patient body mass index, uterine weight, operating time, and physician characteristics such as specialty training or surgeon experience. Although we used conservative matching criteria, it is possible that the two groups may not be matched with regard to such unmeasured characteristics. We were also unable to factor capital costs, annual service contract charges, and depreciation of the robot into our analyses. Use of the Agency for Healthcare Research and Quality cost-to-charge converted cost values allows estimates of the entire hospital stay rather than specific line item charges. Physician charges, indirect costs, societal costs, and secondary charges associated with subsequent hospital stays or ambulatory visits are, therefore, unavailable from the Nationwide Inpatient Sample.
A strength of our study is the use of the largest publicly available, all-payer inpatient care database in the United States, which allows us to analyze large cohorts of procedures that would be difficult to assess in a clinical trial. Although Wright et al examined data from 441 hospitals, our analysis consists of laparoscopic hysterectomies and robotic-assisted hysterectomies performed in 590 hospitals in 2009 and 612 hospitals in 2010. The consistency of the overall findings between these two studies provides a strengthening of the limited available comparisons between laparoscopic hysterectomy and robotic-assisted hysterectomy and the representativeness of the hospitals sampled allows for generalizability of these results. Complications such as pneumonia and need for blood transfusion may not have been recognized previously because of their rarity, which would require assessment of large numbers of cases. By aggregating 2 years of data, we were able to create matched cohorts, which are large enough to demonstrate these clinically significant findings. Like with any new technology, we may find different results as the learning curve progresses, training programs formalize technical skills training, and institutions become more stringent about credentialing of surgeons.
Our findings augment the existing data and may serve to determine sample sizes of future clinical trials appraising the comparative effectiveness of robotic-assisted hysterectomy and identify potential subgroups of patients who may benefit from the use of the robotic platform.27 Furthermore, we hope to have highlighted hypothesis-generating differences in clinical outcomes, including pulmonary complications.
In conclusion, the use of robotics for benign gynecologic conditions increased from 2009 to 2010 despite higher associated charges and similar perioperative outcomes to laparoscopic hysterectomy. As this technology evolves and diffuses into practice, we should continue to examine the comparative effectiveness of robotic hysterectomy and critically appraise its role in the performance of benign hysterectomies.
1. Jacoby VL, Autry A, Jacobson G, Domush R, Nakagawa S, Jacoby A. Nationwide use of laparoscopic hysterectomy compared with abdominal and vaginal approaches. Obstet Gynecol 2009;114:1041–8.
2. Agency for Healthcare Research and Quality. Health services research on hysterectomy and alternatives. Available at: http://archive.ahrq.gov/research/hysterec.htm
. Retrieved August 15, 2013.
3. Nieboer TE, Johnson N, Lethaby A, Tavender E, Curr E, Garry R, et al.. Surgical approach to hysterectomy for benign gynaecological disease. Cochrane Database of Systematic Reviews 2009, Issue 3. Art. No.: CD003677. DOI 10.1002/14651858.CDC003677.pub4.
4. Choosing the route of hysterectomy for benign disease. ACOG Committee Opinion No. 444. American College of Obstetricians and Gynecologists. Obstet Gynecol 2009;114:1156–8.
5. Visco AG, Advincula AP. Robotic gynecologic surgery. Obstet Gynecol 2008;112:1369–84.
6. Langreth R. Intuitive robot probe threatens trend-setting surgeries. Available at: http://www.bloomberg.com/news/2013-02-28/intuitive-surgical-robots-probed-by-u-s-in-survey-of-surgeons.html
. Retrieved March 5, 2013.
7. Anderson JE, Chang DC, Parsons JK, Talamini MA. The first national examination of outcomes and trends in robotic surgery in the United States. J Am Coll Surg 2012;215:107–14.
8. Liu H, Lu D, Wang L, Shi G, Song H, Clarke J. Robotic surgery for benign gynaecological disease. The Cochrane Database of Systematic Reviews 2012, Issue 2. Art. No.: CD008978. doi: 10.1002/14651858.CD008978.pub2.
9. Payne TN, Dauterive FR. A comparison of total laparoscopic hysterectomy to robotically assisted hysterectomy: surgical outcomes in a community practice. J Minim Invasive Gynecol 2008;15:286–91.
10. Nezhat C, Lavie O, Lemyre M, Gemer O, Bhagan L, Nezhat C. Laparoscopic hysterectomy with and without a robot: Stanford experience. JSLS 2009;13:125–8.
11. Shashoua AR, Gill D, Locher SR. Robotic-assisted total laparoscopic hysterectomy versus conventional total laparoscopic hysterectomy. JSLS 2009;13:364–9.
12. Sarlos D, Kots L, Stevanovic N, Schaer G. Robotic hysterectomy versus conventional laparoscopic hysterectomy: outcome and cost analyses of a matched case-control study. Eur J Obstet Gynecol Reprod Biol 2010;150:92–6.
13. Sarlos D, Kots L, Stevanovic N, von Felten S, Schar G. Robotic compared with conventional laparoscopic hysterectomy: a randomized controlled trial. Obstet Gynecol 2012;120:604–11.
14. Paraiso MF, Ridgeway B, Park AJ, Jelovsek JE, Barber MD, Falcone T, et al.. A randomized trial comparing conventional and robotically assisted total laparoscopic hysterectomy. Am J Obstet Gynecol 2013;208:368.e1–7.
15. Pasic RP, Rizzo JA, Fang H, Ross S, Moore M, Gunnarsson C. Comparing robot-assisted with conventional laparoscopic hysterectomy: impact on cost and clinical outcomes. J Minim Invasive Gynecol 2010;17:730–8.
16. Wright JD, Ananth CV, Lewin SN, Burke WM, Lu YS, Neugut AI, et al.. Robotically assisted vs laparoscopic hysterectomy among women with benign gynecologic disease. JAMA 2013;309:689–98.
17. HCUP Nationwide Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). Available at: http://www.hcup-us.ahrq.gov/nisoverview.jsp
. Retrieved January 23, 2012.
18. Healthcare Cost and Utilization Project (HCUP). Comorbidity software, Version 3.7. Available at: http://www.hcup-us.ahrq.gov/toolssoftware/comorbidity/comorbidity.jsp
. Retrieved December 15, 2012.
19. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992;45:613–9.
20. Makarov DV, Loeb S, Landman AB, Nielsen ME, Gross CP, Leslie DL, et al.. Regional variation in total cost per radical prostatectomy in the healthcare cost and utilization project nationwide inpatient sample database. J Urol 2010;183:1504–9.
21. Wu JM, Wechter ME, Geller EJ, Nguyen TV, Visco AG. Hysterectomy rates in the United States, 2003. Obstet Gynecol 2007;110:1091–5.
22. Clinical classifications software (CCS) for ICD-9-CM. Available at: http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp
. Retrieved December 15, 2012.
23. Healthcare Cost and Utilization Project (HCUP). Cost-to-charge ratio files. Rockville (MD): Agency for Healthcare Research and Quality; 2012. Available at: http://www.hcup-us.ahrq.gov/db/state/costtocharge.jsp
. Retrieved December 15, 2012.
24. Austin PC. Using the standardized difference to compare the prevalence of a binary variable between two groups in observational research. Comm Statist Simulation Comput 2009;38:1228–34.
25. Rosero EB, Peshock RM, Khera A, Clagett P, Lo H, Timaran CH. Sex, race, and age distributions of mean aortic wall thickness in a multiethnic population-based sample. J Vasc Surg 2011;53:950–7.
26. Olsen CS, Clark AE, Thomas AM, Cook LJ. Comparing least-squares and quantile regression approaches to analyzing median hospital charges. Acad Emerg Med 2012;19:866–75.
27. Barbash GI, Glied SA. New technology and health care costs—the case of robot-assisted surgery. N Engl J Med 2010;363:701–4.