Hip fracture is a serious and common problem for both men and women. In-hospital mortality estimates have ranged from 3% to 9%1-3, but they have declined over the past decade in the United States. This decline in mortality may be more apparent than real as hospital stays are shorter and patients may be dying at home or at subacute rehabilitation facilities instead of in the hospital4-7. One-year mortality estimates following hip fracture remain significantly higher than expected for these patients1. Mortality rates for United States Medicare patients within one year after a fracture have been estimated to be >20%3. Among survivors, 20% do not walk again and 30% do not regain their previous level of function. As many as 70% will be institutionalized for skilled nursing care following fracture repair, and 10% will remain in nursing homes for a year or longer3,8,9. Lifetime attributable costs for these procedures exceed $81,000 per patient3,10. Hip fracture is thus a sentinel event that often results in permanent functional impairment, immobility, institutionalization, and death1,8.
While much is already known about hip fracture outcomes in elderly women, much less has been reported about men, although recovery for male patients is longer and has been associated with higher mortality11-14. These gender differences in mortality have been attributed to increased post-fracture risk of pneumonia and septicemia12. A meta-analysis of the literature indicated that improved clinical outcomes and survival rates following hip fracture were related to perioperative care processes, including the type of surgical technique (internal fixation as opposed to arthroplasty)15 and the performance of surgery within twenty-four hours after admission16,17. We are not aware of any large-scale national studies of men that have assessed the relationship between operative characteristics and thirty-day outcome.
The largest concentration of hip fracture repairs in American men occurs in the Veterans Health Administration system, where more than 1200 men with hip fractures are managed each year, constituting approximately 13% of the major orthopaedic procedures performed in Veterans Health Administration hospitals18. For Veterans Health Administration patients, in-hospital mortality rates have been estimated to exceed 6%19. The Veterans Health Administration National Surgical Quality Improvement Program (NSQIP) has prospectively collected data on preoperative patient risk factors, care processes, and outcomes related to all major noncardiac surgical procedures performed at 123 Veterans Health Administration medical centers since 1991. The purpose of this large-scale data set program is to provide risk-adjusted data to monitor and improve surgical care provided to patients in Veterans Administration hospitals. We utilized the Veterans Health Administration National Surgical Quality Improvement Program data set to explore which preoperative patient risk characteristics and perioperative care processes are associated with thirty-day outcomes in terms of mortality, complications, and readmission.
Materials and Methods
The data-collection methods of the Veterans Health Administration National Surgical Quality Improvement Program have been described in detail elsewhere20-22. Briefly, trained nurses collect information preoperatively, intraoperatively, and postoperatively (for thirty days) with use of a standardized protocol for most major surgical operations performed at participating Veterans Health Administration medical centers. Most patients who are scheduled to undergo major noncardiac procedures (such as hip fracture repair) with use of general, spinal, or epidural anesthesia are included in the database. The Veterans Health Administration National Surgical Quality Improvement Program collects demographic information, including age, gender, and ethnicity, at the time of surgery. Preoperative laboratory values and prefracture functional status measures are also collected as part of the Veterans Health Administration National Surgical Quality Improvement Program data. Other ICD-9 (International Classification of Diseases, Ninth Revision) diagnoses for each patient that were not included as part of the Veterans Health Administration National Surgical Quality Improvement Program data, but that are necessary to establish diagnoses for osteoporosis, dementia, and bone cancer, are available from Veterans Health Administration inpatient treatment records23,24.
For the present study, we selected male patients aged sixty-five years or older who underwent acute hip fracture repair surgery during fiscal years 1998 to 2003. Patients were identified by Current Procedural Terminology (CPT) codes 27235, 27236, 27244, or 27245, indicating skeletal traction or open or closed treatment of a hip fracture. We also included CPT codes 27125 (hemiarthroplasty) and 27130 (arthroplasty) when the patient had a diagnosis code consistent with an acute hip fracture (ICD-9 codes 820.x, 820.2x, or 820.8). Similar to the authors of other Veterans Health Administration National Surgical Quality Improvement Program studies, we selected only the first surgical admission for patients who were identified as having had multiple operations during the sample time-frame. To ensure that the prefracture health status of the sample was as uniform as possible, we selected patients who had originated from the community, defined as those who had not been transferred from any institutional setting. Records from the Veterans Health Administration National Surgical Quality Improvement Program database were matched on the basis of unique patient identifiers to Veterans Health Administration inpatient hospital records in order to obtain information regarding certain premorbid health traits and any subsequent admissions to a Veterans Health Administration hospital.
Mortality within thirty days after surgery was determined from the Department of Veterans Affairs Beneficiary Identification and Records Locator Subsystem (BIRLS) Death File. Because our data were abstracted at least two years after the date of surgery, this data source was considered to be an accurate source of thirty-day mortality information. Hospital readmission was determined by assessing the number of unique admissions to a Veterans Health Administration hospital within thirty days after the date of surgery from linked inpatient treatment records. The occurrence of complications within thirty days was ascertained by the Veterans Health Administration National Surgical Quality Improvement Program data-collection nurse with use of a chart-review protocol. Data on cardiac, central nervous system, respiratory, urinary tract, wound, and bleeding complications, deep-vein thrombosis; graft/prosthesis failure; and systemic sepsis were included.
Simple univariate statistics were used to describe the sample and variables. Next, chi-square analysis determined bivariate relationships between key risk factors, perioperative care characteristics, and the three outcomes. Guided by these results, we constructed logistic regression models to predict thirty-day outcomes of mortality, the presence of at least one complication, and readmission. Our regression models included all variables that were found to be significant risk factors in the descriptive and chi-square analyses at the p ≤ 0.05 level as well as some variables that were deemed to be clinically important, including the type of anesthesia, the time from admission to surgery, the need for blood transfusions, and the type of procedure (CPT code). Because none of the three outcome variables changed significantly over the fiscal years studied (p > 0.075, chi-square test), all data years were pooled for analysis. The analysis of readmission excluded the subsample of forty-three patients who died within two days after surgery. Regression model fit was assessed with use of a C-index25,26. We performed all statistical analysis with use of Stata (release 9.1 SE)27. Investigators received institutional review board approval and a waiver of informed consent prior to accessing or analyzing any of the data files.
The Veterans Health Administration National Surgical Quality Improvement Program sample included 5683 men who had been admitted from the community for the operative treatment of a hip fracture at one of 108 Veterans Health Administration medical centers between 1998 and 2003. Table I presents the demographic and preoperative health characteristics of the sample. The average age was seventy-seven years (range, sixty-five to 104 years), which was similar to the average age of seventy-six years for Medicare patients with hip fractures28. Seventy-six percent of the patients in the sample were white. Most subjects (60%) had been functionally independent prior to the fracture but had a heavy burden of comorbid conditions, including diabetes (19%), severe chronic obstructive pulmonary disease (27%), and dementia (15%). Following methods similar to those described by Elixhauser and colleagues29, we examined ten preoperative diagnoses and health factors that were likely to be associated with an increased risk of hip fracture and adverse outcome: steroid use, disseminated cancer, impaired sensorium, congestive heart failure, dementia, diabetes, hemiplegia, severe chronic obstructive pulmonary disease, a history of stroke, and recent weight loss.
Risk factors that were assessed at the time of surgery include American Society of Anesthesiologists Physical Status Classification (ASA class) and preoperative laboratory values to indicate anemia, hypoalbuminemia, renal insufficiency, and abnormal serum sodium levels. According to the ASA classification, only six patients (<1%) were considered healthy (ASA class 1) and twenty-three (<1%) were considered moribund (ASA class 5). The median and modal ASA class was 3, indicating that the typical patient had severe systemic disease.
A table in the Appendix provides a description of the operative characteristics that we examined. The treatment of intertrochanteric, pertrochanteric, or subtrochanteric femoral fracture with a plate/screw implant (CPT 27244) was the most common procedure, representing 35% of the sample. The treatment of displaced intracapsular fractures with total arthroplasty (CPT 27130) was the least common procedure, representing <3% of the sample. Because of the intensity of this procedure, it is generally reserved for younger or healthier patients with longer life expectancies who can withstand longer operative time30.
Anesthesia technique, emergent surgery, the number of days between hospital admission and operative treatment, and the need for transfusions could influence thirty-day outcomes following the treatment of a hip fracture. The majority of the sample (59%) received general anesthesia as the primary anesthetic, with epidural anesthesia representing another 39% of the sample; most of the few remaining patients received spinal anesthesia. Among the patients who received general anesthesia, the average duration of anesthesia (and standard deviation) was 177 ± 59 minutes (range, twenty-eight to 520 minutes). Transfusions were given to 630 patients (11%), with a range of one to twelve units of red blood cells being transfused. Friday was the most common day of the operation, representing 22% of the procedures, with only 396 procedures (7%) being performed on the weekend. Concurrent procedures (data not shown) were not common; 84% of the patients had one operative procedure. The postoperative duration of hospitalization was highly skewed and had several outliers (range, one to 376 days). The mean duration of hospitalization was 19 ± 32 days (median, thirteen days).
The overall unadjusted thirty-day mortality rate was 8%, representing 468 decedents. Most (80%) of these deaths occurred before hospital discharge, with forty-three deaths occurring within two days after surgery. Of the subjects who survived to at least Day 2, 7% were readmitted to the hospital within thirty days. Among the entire sample, 21% of the patients had at least one surgical complication. The most common complications were urinary tract infection and pneumonia, with a prevalence of 7% for each. Other common complications included reintubation (3%); cardiac arrest, failure to wean from the ventilator, wound infection or disruption, and systemic sepsis (2% each); and acute myocardial infarction, pulmonary embolism, deep-vein thrombosis, bleeding requiring transfusion of >4 U of packed red blood cells, deep-wound infection, and decubital gangrene (1% each). A return to the operating room was recorded for 303 patients (5%).
A table in the Appendix presents unadjusted associations between preoperative characteristics and the three outcomes of interest. Older age, reduced functional status, and higher ASA score increased the risk of mortality. Heavy alcohol use was associated with a lower mortality risk, but further analysis demonstrated an underlying relationship between this factor and both better functional status and younger age. The clinical risk factors showing the most consistent effects on the three outcomes of mortality, complications, and readmissions were congestive heart failure, chronic obstructive pulmonary disease, and impaired sensorium.
Table II illustrates unadjusted associations between operative characteristics and thirty-day outcomes. Procedure type was significantly associated with both mortality and complications. The lowest mortality rate (3%) was associated with total hip arthroplasty (CPT 27130). The highest mortality rate (10%) was associated with open treatment with internal fixation or prosthetic replacement (CPT 27236), followed by treatment with an intramedullary implant with or without interlocking screws and/or cerclage wires (CPT 27245). The lowest complication rates were associated with total hip arthroplasty and percutaneous fixation (16% for each), and the highest rate was associated with hemiarthroplasty (23%). The rate of readmission did not significantly differ according to procedure type.
Other operative characteristics that were associated with mortality included transfusions and delayed surgery. The relationship between transfusions and mortality increased monotonically with the number of transfusions required. Similarly, the mortality rate increased with number of days between admission and the operation. Operative characteristics that were related to complications included general anesthesia, with a greater risk being associated with a duration of anesthesia of more than three hours, and having at least one blood transfusion. Readmission within thirty days after surgery was significantly associated with several clinical risks, including heart failure and severe chronic obstructive pulmonary disease, but was only marginally associated with reduced health status as indicated by the ASA score (see Appendix). However, none of the intraoperative characteristics had a significant bivariate relationship with readmission.
Logistic Regression Models
Results for the three logistic regression models are provided in Table III. Adjusted odds ratios and p values are provided to indicate the magnitude and significance (p < 0.05) of the relationship between covariates and outcomes while controlling for all other variables included in the models. Of the 5683 patients who were identified, 5381 had complete information for all variables included in the regression models for mortality and complications whereas 5320 had complete information for the readmission model. Model fit for the three equations, based on the C-index, was moderate, ranging from 0.62 for the readmission equation to 0.73 for the mortality equation.
With other covariates being held fixed, a surgical delay of four days or more after hospital admission (odds ratio, 1.29; 95% confidence interval, 1.02 to 1.61) and the use of general anesthesia (odds ratio, 1.27; 95% confidence interval, 1.01 to 1.55) were related to an increased risk of death within thirty days after surgery. The type of surgical procedure was not related to the risk of mortality after controlling for other variables in the model. Several prefracture risk factors were predictive of mortality, including white ethnicity, older age category, disseminated cancer, impaired sensorium, congestive heart failure, recent substantial weight loss, higher levels of functional dependence prior to fracture, and higher ASA class.
Two surgical factors were related to readmission within thirty days after surgery. Patients in whom surgery had been performed four days or more after admission were less likely to be readmitted within thirty days (odds ratio, 0.70; 95% confidence interval, 0.54 to 0.91). However, those patients tended to have longer durations of hospitalization and therefore would have had a shorter window for potential readmission. In addition, emergency admission was associated with a reduced odds ratio for readmission (odds ratio, 0.74; 95% confidence interval, 0.57 to 0.96). Abnormal renal function and impaired sensorium also were associated with higher adjusted odds ratios for readmission.
Blood transfusion and wound infection were associated with the occurrence of at least one complication, as was general anesthesia (odds ratio, 1.33, 95% confidence interval, 1.15 to 1.53). Heavy alcohol use prior to the fracture was significantly related to the occurrence of at least one postoperative complication (odds ratio, 1.32; 95% confidence interval, 1.06 to 1.64). There were multiple patient risk factors that were associated with an increased complication risk, including white ethnicity, older age, recent weight loss, congestive heart failure, impaired sensorium, diabetes, severe chronic obstructive pulmonary disease, abnormal renal function, partial or total functional dependence, and ASA class III or higher.
In the present study, we observed an overall thirty-day mortality rate of 8.2% for patients treated in Veterans Health Administration hospitals. Furthermore, >20% of the patients had at least one surgical complication and 7% of those who survived the procedure were readmitted to a Veterans Health Administration hospital within thirty days. The risk of adverse outcomes suggests a need to explore ways to improve short-term survival and other outcomes for older male veterans with a hip fracture. The current report presents data that can be useful for informing surgical practice for this unique patient group.
Surgical care that was delayed by four days or more after admission was related both to an increased risk of mortality within thirty days and to a reduced risk of readmission. The reduced risk of readmission was likely related to a longer overall length of stay following surgery, implying a shortened window for rehospitalization rather than a positive outcome. As delayed surgery remained predictive of mortality even after controlling for ASA class, age, premorbid functional status, and comorbidity, it is likely that hospital or system-related factors (e.g., the adequacy of weekend coverage), rather than intrinsic patient-related factors, were responsible for delays. A more detailed chart abstraction of records with delayed operations might reveal whether the delays were prompted by the need to stabilize sicker patients or if they were due to the lack of surgical capacity. However, our examination of the available data suggested differing distributions of surgical wait times based on the day of the week on which the patient was admitted. Whereas 60% of the patients who were hospitalized on a Thursday or Friday had surgery within three days after admission, >70% of those who were hospitalized on Sunday through Wednesday underwent surgery within three days after admission (data not shown). Thus, it would seem that the difficulty in scheduling surgery on weekends may explain much of the variation in surgical timing. Given that surgical delay has been associated with worse outcome in other studies16,17 and that surgery within twenty-four to forty-eight hours after fracture is recommended, finding ways to operate sooner for stable patients who are admitted near the weekend may be indicated as a mechanism to improve survival.
General anesthesia was associated with higher odds ratios for both mortality and the presence of complications when compared with neuraxial (spinal or epidural) anesthesia. To test whether the duration of general anesthesia rather than the method of anesthesia was an important consideration, we ran a logistic regression model (results not shown) that included the number of hours for which the patient was anesthetized. The adjusted odds ratio for the duration of anesthesia in this alternate model was not significant. Categorical variables to allow a nonlinear association between the duration of anesthesia and mortality also were not found to be significant. Therefore, it was the method of anesthesia rather than the duration of anesthesia that seemed to matter most for this group of patients. These findings are consistent with the meta-analysis of randomized clinical trials performed by Rodgers et al.31, which showed a 30% reduction in mortality due to all causes at one month in patients who received neuraxial blockade as a part of their anesthetic. That meta-analysis of 141 clinical trials also demonstrated large reductions in the risk of deep-vein thrombosis (44%), pulmonary embolism (50%), pneumonia (39%), transfusion requirements (50%), and respiratory depression (59%) as well as smaller reductions in the incidence of myocardial infarction and renal failure. The mechanism by which mortality is reduced has not been clearly elucidated but is likely multifactorial. The use of neuraxial anesthesia has been associated with benefits to the patient that include better pain management, a reduced need for blood products, less hyperglycemia, and attenuation of the neuroendocrine stress response that results in decreased circulating catecholamine levels32. Several explanations for why regional anesthesia is not more commonly used include contraindications related to the use and timing of anticoagulants in the perioperative period, contraindications related to other preexisting patient risk characteristics, and the coding conventions used for the Veterans Health Administration National Surgical Quality Improvement Program data set.
Both the ASA status and the functional status were strong predictors of outcome. ASA status is based on a subjective assessment of the patient's preoperative health status and is usually assigned by the person providing anesthesia care. ASA status was an important measure in the prediction of thirty-day mortality and morbidity because (1) it was assessed immediately before surgery, (2) it was designed to assess physical status as it relates to fitness for surgery, and (3) it captured additional information based on the physician's clinical judgment. Similarly, premorbid function was assessed prior to surgery and has many of the same benefits as ASA status for this particular type of surgery.
Among the procedure types selected for study, total hip arthroplasty and percutaneous skeletal fixation typically are reserved for healthier patients, so the finding of lower unadjusted mortality rates for these procedures is not surprising. Higher unadjusted mortality rates were associated with procedures that typically are chosen for the majority of patients with higher disease burdens and that are performed by surgeons familiar with open reduction and internal fixation, i.e., hemiarthroplasty and plate-and-screw implantation. The highest unadjusted mortality rate was associated with procedures that were used to treat patients who had greater comorbidity and who were undergoing open treatment with internal fixation or intramedullary implants. The finding that procedure type was not associated with outcomes once we controlled for other factors suggests that Veterans Health Administration surgeons are generally selecting operative procedures that are appropriate for their patients.
To our knowledge, the present study is the largest and most detailed study to date of perioperative risk factors, process of care, and outcomes for community-dwelling male veterans who have sustained a fracture of the hip. Whereas other studies have offered insights regarding hip fracture outcomes for men and for veterans14-17,19, the present study provides information on both preoperative risk factors and perioperative process of care for a large national sample of patients with multiple years of detailed data.
The present study had several limitations. First, our data do not capture readmissions and outcomes beyond thirty days. Second, patients admitted to Veterans Health Administration facilities for surgery may have been readmitted to hospitals outside of the Veterans Health Administration system. We suspect that most patients who initially select a Veterans Health Administration facility for surgical care would consider a Veterans Health Administration facility first if a subsequent hospitalization was required. For future studies, it would be valuable to capture more comprehensive information regarding care trajectories and outcomes across systems of care and beyond thirty days. In addition, we were unable to capture the reason for return to the operating room (noted for 5% of the patients in our sample).
Our findings both confirm and expand on the findings of other studies. We found that the timing of surgery is important, as is the type of anesthesia. We explored whether the type of procedure was associated with outcome and found that the unadjusted associations between procedure and outcome did not generally persist once key patient characteristics such as age, ethnicity, and health status were taken into consideration. With use of the Veterans Health Administration's uniquely detailed quality improvement database, we demonstrated that there are potentially mutable surgical characteristics associated with adverse outcomes. For example, reducing surgical delays is clearly indicated. On the basis of our findings, more detailed evaluations of the association between surgical delay, the type of anesthesia, and adverse outcomes should be undertaken to develop interventions that improve care and outcomes for veterans and others.
Tables showing perioperative care characteristics and associations between preoperative characteristics and outcomes are available with the electronic versions of this article, on our web site at jbjs.org (go to the article citation and click on “Supplementary Material”) and on our quarterly CD-ROM (call our subscription department, at 781-449-9780, to order the CD-ROM).
NOTE: The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs. Human subjects approval and a waiver of informed consent were provided by the Colorado Multiple Institutional Review Board (COMIRB protocol #05-0420). The authors greatly appreciate the substantive input of the Veterans Health Administration National Surgical Quality Improvement Program advisory board, Dr. Andrew Kramer, Division of Health Care Policy and Research at UCDHSC, and three anonymous reviewers. In addition, they thank Tracy Schifftner and Ron Fish for their assistance extracting and preparing the data files for analysis.
Disclosure: In support of their research for or preparation of this work, one or more of the authors received, in any one year, outside funding or grants of more than $10,000 from the Department of Veteran Affairs. (Financial and salary support for Drs. Radcliff and Hutt was provided by the Department of Veterans Affairs, Office of Research and Development, Health Services Research and Development Service via the Targeted Research Enhancement Program (TREP) to Improve the Quality of Life and Care to Veterans in Long-term Care, Denver Veterans Administration Medical Center. Collection of the National Surgical Quality Improvement Program data is supported by the Office of Patient Care Services, Department of Veterans Affairs Central Office, Washington, D.C.) Neither they nor a member of their immediate families received payments or other benefits or a commitment or agreement to provide such benefits from a commercial entity. No commercial entity paid or directed, or agreed to pay or direct, any benefits to any research fund, foundation, division, center, clinical practice, or other charitable or nonprofit organization with which the authors, or a member of their immediate families, are affiliated or associated.
A commentary is available with the electronic versions of this article, on our web site (www.jbjs.org) and on our quarterly CD-ROM (call our subscription department, at 781-449-9780, to order the CD-ROM).
Investigation performed at the Denver VA Medical Center, Denver, Colorado
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