The Rise of Medicare Advantage: Effects on Total Joint Arthroplasty Patient Care and Research.

BACKGROUND: Medicare Advantage (MA) plans are popular among Medicare-eligible patients, but little is known about MA in lower-extremity total joint arthroplasty (TJA). The purpose of this study was to describe trends in MA utilization and analyze differences in patient characteristics and postoperative outcomes between patients undergoing primary TJA using traditional Medicare (TM) or MA plans. METHODS: Patients ≥65 years of age who underwent primary total knee or total hip arthroplasty were identified using the Premier Healthcare Database. Patients were categorized into TM and MA cohorts. Data from 2004 to 2020 were used to describe trends in insurance coverage. Data from 2015 to 2020 were used to identify differences in patient characteristics and postoperative complications using ICD-10 codes. Multivariate analyses were performed using 2015 to 2020 data to account for potential confounders. RESULTS: From 2004 to 2020, the proportion of patients with MA increased from 7.9% to 34.4%, while those with TM decreased from 83.7% to 54.0%. Of the 697,317 patients who underwent primary elective TJA from 2015 to 2020, 471,439 (67.6%) had TM coverage and 225,878 (32.4%) had MA coverage. The cohorts were similar in terms of age and sex. However, a higher proportion of Black patients (8.29% compared with 4.62%; p < 0.001) and a lower proportion of White patients (84.0% compared with 89.2%; p < 0.001) were enrolled in MA compared with TM. After controlling for confounders, patients with MA had higher odds of surgical site infection (adjusted odds ratio [aOR]: 1.15; 95% confidence interval [CI]: 1.04 to 1.47; p = 0.031), periprosthetic joint infection (aOR: 1.10; 95% CI: 1.03 to 1.18; p = 0.006), stroke (aOR: 1.15; 95% CI: 1.02 to 1.31; p = 0.026), and acute kidney injury (aOR: 1.08; 95% CI: 1.04 to 1.11; p < 0.001), but lower odds of urinary tract infection (aOR: 0.94; 95% CI: 0.90 to 0.98; p = 0.003). CONCLUSIONS: From 2004 to 2020, the number of patients utilizing MA increased markedly such that 1 in 3 were covered by MA in 2020. From 2015 to 2020, patients who were non-White were more likely to have MA than TM, and the MA group had a higher rate of several postoperative complications compared with the TM group. As TM claims data inform health-care policy and clinical decisions, this change portends future challenges, including limitations in arthroplasty registry research, an increase in the administrative burden of surgeons, and a potential worsening of social disparities in health care.

Comparison of Patient-Reported Outcomes and Functional Assessment Using a Marker-Less Image Capture System in End-Stage Knee Arthritis.

BACKGROUND: Patient self-assessment of knee function in end-stage osteoarthritis (OA) and following total knee arthroplasty (TKA) using patient-reported outcome measures (PROMs) has become standard for defining disability. The relationship of PROMs to functional performance requires a continued investigation. The purpose of this study was to determine correlations between patient demographics, PROMs, and functional performances using a marker-less image capture system (MICS). METHODS: Patients indicated for elective TKA completed the Knee Injury and Osteoarthritis Score for Joint Replacement (KOOS-JR) and an office-based functional assessment using a MICS. Patient age, body mass index (BMI), and gender were collected. A total of 112 patients were enrolled. Their mean age was 65.0 (±9.7) years, mean BMI was 32.5 (±6.6) kg/m2, and mean KOOS-JR was 14.5 (±5.7). The relationships between patient characteristics, KOOS-JR, MICS Alignment (coronal), MICS Mobility (flexion), and composite Total Joint scores were described using Spearman's correlation coefficients. RESULTS: BMI was weakly correlated with KOOS-JR (ρ = -0.22, P = .024), whereas age was not. Age and BMI were not correlated with performance scores. There were weak to no correlations between KOOS-JR and MICS Alignment (ρ = -0.01, P = .951), Mobility (ρ = 0.33, P < .001), and Total Joint scores (ρ = 0.06, P = .504). CONCLUSION: This study found no strong correlation between KOOS-JR and functional performance using a validated MICS for patients with end-stage knee OA. Further study is warranted in determining the relationship between PROMs and performance to optimize outcomes of patients undergoing nonoperative or surgical interventions for knee OA. The use of high-fidelity functional assessment tools that can be integrated into clinical workflow, such as the MICS used in this study, should permit PROM/functional performance comparisons in large populations.

Longer Length of Stay Is Associated With More Early Complications After Total Knee Arthroplasty.

Background: Length of stay (LOS) following total knee arthroplasty (TKA) has decreased over recently years. In 2018, the Centers for Medicare and Medicaid Services removed TKA from Inpatient-Only List (IPO), incentivizing further expansion of outpatient TKA. However, many patients may still require postsurgical hospitalization. The purpose of this study was to assess early outcomes for TKA based on length of stay (LOS). Methods: We identified patients undergoing elective, primary TKA in the National Surgical Quality Improvement Program database using CPT code 27447 between 2015 and 2018. Patients were stratified by length of stay (LOS) 0 days, 1-2 days, and ≥3 days. Thirty-day rates of any complication, wound complications, readmission, and reoperation were assessed. Multivariate analysis was performed to adjust for confounding variables. Results: 5,655 (3%) patients underwent outpatient TKA, 130,543 (59%) had LOS 1-2 days, and 84,986 (38%) had LOS ≥3 days. Any complication was experienced in 4.1% of those with LOS 0 days, 4.3% for those with LOS of 1-2 days, and 10.5% for patients with LOS ≥3 days (p<0.0001). Readmission occurred in 2.2%, 2.6%, and 4.0% for the 3 groups, respectively (p<0.0001). After multivariate analysis, there was no significant difference in any outcome measure between patients with LOS 0 and 1-2 days, however those with LOS ≥3 days had higher odds of complications, reoperation, and readmission. Conclusion: A significant number of patients had LOS ≥3 days following TKA and had more comorbidities and complications. Outpatient TKA was not associated with increased early complication compared to those with LOS of 1-2 days. Despite expansion of outpatient surgery, postsurgical hospitalization remains an integral part of care following TKA. Level of Evidence: III.

Clinical and Administrative Databases Used in Lower Extremity Arthroplasty Research.

BACKGROUND: The use of national databases in lower extremity arthroplasty research has grown rapidly in recent years. We aimed to better characterize available databases by: (1) quantifying the number of these studies in the highest impact arthroplasty journals; (2) comparing respective sample sizes; and (3) contrasting their measured variables/outcomes. METHODS: An extensive literature search was conducted to identify all database studies in the top 12 highest impact factor journals that published arthroplasty research between January 1, 2018 and December 31, 2019. A total of 5070 publications were identified. These studies were sorted by both database utilized and journal published. Tables were constructed to compare/contrast databases by metrics and measured outcome parameters including coding, patient sample size, preoperative comorbidities, postoperative complications, and limitations/barriers to their use. RESULTS: Four hundred twenty-six database studies (8.4%, range 0.4%-29.7% per journal) were identified, of which 139 were from non-English-speaking arthroplasty databases. Among English-speaking arthroplasty databases, the 5 most common sources were National Surgical Quality Improvement Project (n = 72), Medicare (n = 62, 39 from Medicare Claims and 23 from PearlDiver), Nationwide Inpatient Sample (n = 35), PearlDiver non-Medicare private insurance (n = 18), and Statewide Planning and Research Cooperative System (n = 18). Metrics, outcome parameters, and features of commonly used registries were reviewed. CONCLUSION: Database studies constitute an important part of arthroplasty-specific orthopedic research. Their use will continue to grow in the future, and it would be beneficial for clinicians/researchers to be aware of and familiarize themselves with their features to understand which are most appropriate for their work.

Has Removal From the Inpatient-Only List Increased Complications After Outpatient Total Knee Arthroplasty?

BACKGROUND: On 1/1/2018, the Centers for Medicare and Medicaid Services removed total knee arthroplasty (TKA) from the Inpatient-Only (IPO) list. This change allowed expansion of outpatient TKA, potentially to include older, more frail patients at greater risk for perioperative complications. The purpose of this study was to evaluate the impact of removing TKA from the IPO list on early complications. METHODS: Patients undergoing TKA in the National Surgical Quality Improvement Program database were identified using CPT code 27447. Only cases with length of stay of zero days were included. Rates of 30-day complications, readmissions, and reoperation were compared before and after TKA was removed from the IPO list (2015-2017 vs 2018). The analysis was performed both with and without propensity score matching. RESULTS: 212,313 patients underwent TKA during the study period. 2466 (1.5%) were outpatient TKA in 2015-2017 and 3189 (5.6%) in 2018. After propensity matching, there were 2458 patients in each cohort. Rates of total 30-day complications were significantly lower in 2018 (3.7%) than the years TKA remained on the IPO (4.5%, P = .04). Similarly, rates of any reoperation decreased from 1.2% during 2015-2017 to 0.6% in 2018 (P = .03). There were no significant changes in rates of readmission (2.5% vs 2.2%, P = .5) or wound complications (0.8% vs 0.8%, P = 1.0). CONCLUSION: Removal of TKA from the IPO list did not result in an increase in complications or readmissions. These data suggest, despite the regulatory change, surgeons have continued to exercise sound judgment as to what patients can safely undergo outpatient TKA.

Outcomes of Hip Arthroscopy in the Medicare Patient: A Growing Population.

Background: Although the results of hip arthroscopy in the elderly have been inferior to the results in younger patients, there have recently been some encouraging reports in carefully selected series of older patients. The purpose of this study was to identify the utilization of hip arthroscopy in the Medicare population and to determine the rate and timing of revision arthroscopy and/or total hip arthroplasty (THA) with the goal of identifying risk factors for secondary procedures based on patient demographics, comorbidities and the diagnosis at the time of arthroscopy. Methods: The Medicare Standard Analytic Files were reviewed from 2005-2014 for all patients undergoing hip arthroscopy allowing for minimum 2 year follow-up (100% sample). Patients were tracked through the dataset for the occurrence of an ipsilateral THA or revision hip arthroscopy. Rates and timing of the subsequent procedures were then determined within 6 month intervals. Patients less than 65 years old were excluded. Multivariate logistic regression analysis was performed to determine the impact of patient age, sex, obesity or a diagnosis of hip osteoarthritis on need for revision procedures. Results: 3,320 Medicare patients had a hip arthroscopy during 2005-2014 (0.3% compared to THA). 73 patients (2.2%) underwent reoperation during the follow-up period. Two-thirds (n = 46) of all revision procedures occurred within one year of primary hip arthroscopy. A pre-operative diagnosis of hip osteoarthritis significantly increased the odds of reoperation (OR = 5.3). (Conclusion: Relatively few numbers of Medicare patients underwent hip arthroscopy during the time interval evaluated (0.3% when compared to THA utilization). 2.2% underwent a subsequent revision arthroscopy or THA with many occurring soon after the procedure and for the diagnosis of hip OA demonstrating the need to better define indications in this population. This study should provide baseline utilization and outcome trends for future studies.Level of Evidence: IV.

Artificial Intelligence and Machine Learning in Lower Extremity Arthroplasty: A Review.

BACKGROUND: Driven by the rapid development of big data and processing power, artificial intelligence and machine learning (ML) applications are poised to expand orthopedic surgery frontiers. Lower extremity arthroplasty is uniquely positioned to most dramatically benefit from ML applications given its central role in alternative payment models and the value equation. METHODS: In this report, we discuss the origins and model specifics behind machine learning, consider its progression into healthcare, and present some of its most recent advances and applications in arthroplasty. RESULTS: A narrative review of artificial intelligence and ML developments is summarized with specific applications to lower extremity arthroplasty, with specific lessons learned from osteoarthritis gait models, joint-specific imaging analysis, and value-based payment models. CONCLUSION: The advancement and employment of ML provides an opportunity to provide data-driven, high performance medicine that can rapidly improve the science, economics, and delivery of lower extremity arthroplasty.

2018 International Consensus Meeting on Musculoskeletal Infection: Research Priorities from the General Assembly Questions.

Musculoskeletal infections (MSKI) remain the bane of orthopedic surgery, and result in grievous illness and inordinate costs that threaten healthcare systems. As prevention, diagnosis, and treatment has remained largely unchanged over the last 50 years, a 2nd International Consensus Meeting on Musculoskeletal Infection (ICM 2018, https://icmphilly.com) was completed. Questions pertaining to all areas of MSKI were extensively researched to prepare recommendations, which were discussed and voted on by the delegates using the Delphi methodology. The questions, including the General Assembly (GA) results, have been published (GA questions). However, as critical outcomes include: (i) incidence and cost data that substantiate the problems, and (ii) establishment of research priorities; an ICM 2018 research workgroup (RW) was assembled to accomplish these tasks. Here, we present the result of the RW consensus on the current and projected incidence of infection, and the costs per patient, for all orthopedic subspecialties, which range from 0.1% to 30%, and $17,000 to $150,000. The RW also identified the most important research questions. The Delphi methodology was utilized to initially derive four objective criteria to define a subset of the 164 GA questions that are high priority for future research. Thirty-eight questions (23% of all GA questions) achieved the requisite > 70% agreement vote, and are highlighted in this Consensus article within six thematic categories: acute versus chronic infection, host immunity, antibiotics, diagnosis, research caveats, and modifiable factors. Finally, the RW emphasizes that without appropriate funding to address these high priority research questions, a 3rd ICM on MSKI to address similar issues at greater cost is inevitable.

Might Doctors Really "Know Best"?: Utilizing Surgeon Intuition to Strengthen Preoperative Surgical Risk Assessment.

Background: Many clinical factors are known to increase an individual patient's risk of perioperative complications and hospital readmission. Several novel risk calculators have been created to predict the risk of postoperative complications for specific procedures that rely entirely on objective measurements. Our goal was to determine if surgeon intuition (an estimate of the percent likelihood of minor and major medical and surgical complications and 30-day readmission) could provide an additional source of data in the preoperative setting that may enhance the prediction of complications after surgery. Methods: We targeted the operative practices of three subspecialized orthopedic surgeons over a 6-month period (February 1 to July 31, 2015). We administered surveys to attending surgeons and assisting residents or nurse practitioners prior to each operation. Surgeons were asked to predict each patient's likelihood, on a scale from <1-100, for experiencing a complication. Following the procedure, we analyzed each patient's electronic medical record to determine any adverse events and readmissions. We then looked at levels of association between predictor variables and complications. Analysis of maximum likelihood estimates for complication outcome was performed comparing objective variables and surgeon prediction. Results: A total of 417 surveys in 270 patients were available for analysis. Defining the predicted likelihood of minor medical complications as <10% (low), 10-40% (intermediate), and >40% (high), provided discrimination of postoperative complications for a single observer in the first three month. These cutoff ranges showed inter-observer consistency and a trend towards intra-observer consistency. The only three variables predictive of minor medical complications were ASA class (OR=3.63, 95%CI=1.76-7.52, p=0.0005; comparing >2 vs ≤2), age (ß=0.034±0.012, p=0.0032) and surgeon prediction when comparing high to low risk (ß=0.034±0.008 (0.018-0.049), p<0.0001). Conclusions: Quantitative surgeon preoperative risk assessment was able to accurately discriminate between low- and high-risk groups of minor medical complications. We did not find a similar association between major complications and readmissions.Level of Evidence: IV.

Rapid Recovery Total Joint Arthroplasty is Safe, Efficient, and Cost-Effective in the Veterans Administration Setting.

BACKGROUND: Institutional pathways in total joint arthroplasty (TJA) have been shown to reduce costs and improve patient care, but questions remain regarding their efficacy in certain populations. We sought to evaluate the comprehensive effect of a rapid recovery perioperative TJA protocol in the Veterans Health Administration (VA) setting. METHODS: In a VA hospital, a rapid recovery protocol was implemented for all patients undergoing primary total hip or knee arthroplasty. A retrospective chart review was performed comparing pre-protocol (n = 174) and protocol (n = 78) cohorts. Measured outcomes included length of stay (LOS), discharge destination, unplanned readmissions, overall complications, and total cost of healthcare during admission and at 30 and 90 days postoperatively. RESULTS: After implementation of the protocol, the average LOS decreased from 3.2 to 1.7 days (P < .0001). In the protocol group, there was a 12.3% increase in patients discharging directly home (85.1% vs 97.4%, P = .005). There were lower unplanned readmissions (6.3% vs 3.8%, P = .56) and overall complications (7.5% vs 3.8%, P = .40), but these were not statistically significant. The summative cost of all perioperative healthcare was lower after implementation of the protocol during the inpatient stay ($19,015 vs $21,719, P = .002) and out to 30 days postoperatively ($21,083 vs $23,420, P = .03) and 90 days postoperatively ($24,189 vs $26,514, P = .07). CONCLUSION: In the VA setting, implementation of a rapid recovery TJA protocol led to decreased LOS, decreased cost of perioperative healthcare, and an increase in patients discharging directly home without increased readmission or complication rates. Such protocols are essential as we transition into an era of value-based arthroplasty.

Short-term Morbidity and Readmissions Increase With Skilled Nursing Facility Discharge After Total Joint Arthroplasty in a Medicare-Eligible and Skilled Nursing Facility-Eligible Patient Cohort.

BACKGROUND: The benefits of discharge to a skilled nursing facility (SNF) in Medicare-eligible patients after total joint arthroplasty (TJA) have recently been scrutinized. The purpose of this study was to determine short-term complication and readmission rates for SNF versus home discharge in patients eligible for Medicare and SNF discharge. METHODS: Patients who underwent TJA between 2012 and 2013 were identified in the National Surgical Quality Improvement Project database. Patients over 65 years and who discharged at or after postoperative day 3, and thus SNF eligible by Medicare rule, were included. Patient demographics and comorbidities were compared in the 2 cohorts (home versus SNF), and subsequent univariate and multivariate analyses were used to determine risk factors for short-term complications. RESULTS: We identified 34,610 Medicare- and SNF-eligible TJA patients; 54.8% discharged home. Patients with SNF discharge were older, had higher rates of comorbidities, and were more frequently American Society of Anesthesiologists class 3 or 4 (P < .001). Univariate analysis revealed that patients with SNF discharge had higher rates of any complication (7.9% vs. 4.7%, P < .001) and readmission (5.3% vs. 3.3%, P < .001). Multivariate regression analysis identified SNF discharge (adjusted odds ratio 1.9, 95% confidence interval 1.7-2.0) as an independent risk factor for a 30-day complication and readmission. CONCLUSIONS: In a cohort of Medicare- and SNF-eligible patients, SNF discharge was the strongest predictor of 30-day complication after TJA. SNF discharge was also an independent predictor of readmission after TJA.

What is the Impact of Smoking on Revision Total Hip Arthroplasty?

BACKGROUND: There is a paucity of literature evaluating the impact of smoking on revision total hip arthroplasty (THA) outcomes. The purpose of this study was to identify the effect of smoking on complications after revision THA. METHODS: We queried the American College of Surgeons National Surgical Quality Improvement Program database to identify patients who underwent revision THA between 2006 and 2014. Patients were divided into current smokers and nonsmokers. Each cohort was compared in terms of demographics, preoperative comorbidities, and operative time. Multivariate logistic regression analysis was utilized. Adjusted odds ratios (OR) for the outcomes of any wound complication, deep infection, and reoperation within 30 days of revision THA were calculated. RESULTS: In total, 8237 patients had undergone a revision THA. Of these patients, 14.7% were current smokers and 85.3% were nonsmokers. Univariate analyses demonstrated that smokers had a higher rate of any wound complication (4.1% vs 3.0%, P = .04), deep infection (3.2% vs 1.9%, P = .003), and reoperation (6.8% vs 4.8%, P = .003). Multivariate analysis controlling for confounding demographic, comorbidity, and operative variables identified current smokers as having a significantly increased risk of deep infection (OR, 1.58; 95% CI, 1.04-2.38) and reoperation (OR, 1.37; 95% CI, 1.03-1.85). CONCLUSION: Smoking significantly increases the risk of infection and reoperation after revision THA. The results are even more magnified for revision procedures compared to published effects of smoking on primary THA complications. Further research is needed regarding the impact of smoking cessation on mitigation of these observed risks.

Big Data and Total Hip Arthroplasty: How Do Large Databases Compare?

BACKGROUND: Use of large databases for orthopedic research has become extremely popular in recent years. Each database varies in the methods used to capture data and the population it represents. The purpose of this study was to evaluate how these databases differed in reported demographics, comorbidities, and postoperative complications for primary total hip arthroplasty (THA) patients. METHODS: Primary THA patients were identified within National Surgical Quality Improvement Programs (NSQIP), Nationwide Inpatient Sample (NIS), Medicare Standard Analytic Files (MED), and Humana administrative claims database (HAC). NSQIP definitions for comorbidities and complications were matched to corresponding International Classification of Diseases, 9th Revision/Current Procedural Terminology codes to query the other databases. Demographics, comorbidities, and postoperative complications were compared. RESULTS: The number of patients from each database was 22,644 in HAC, 371,715 in MED, 188,779 in NIS, and 27,818 in NSQIP. Age and gender distribution were clinically similar. Overall, there was variation in prevalence of comorbidities and rates of postoperative complications between databases. As an example, NSQIP had more than twice the obesity than NIS. HAC and MED had more than 2 times the diabetics than NSQIP. Rates of deep infection and stroke 30 days after THA had more than 2-fold difference between all databases. CONCLUSION: Among databases commonly used in orthopedic research, there is considerable variation in complication rates following THA depending upon the database used for analysis. It is important to consider these differences when critically evaluating database research. Additionally, with the advent of bundled payments, these differences must be considered in risk adjustment models.

The Seasonal Variability of Surgical Site Infections in Knee and Hip Arthroplasty.

BACKGROUND: Surgical site infections (SSIs) after total knee (TKA) and total hip (THA) arthroplasty are devastating to patients and costly to healthcare systems. The purpose of this study is to investigate the seasonality of TKA and THA SSIs at a national level. METHODS: All data were extracted from the National Readmission Database for 2013 and 2014. Patients were included if they had undergone TKA or THA. We modeled the odds of having a primary diagnosis of SSI as a function of discharge date by month, payer status, hospital size, and various patient co-morbidities. SSI status was defined as patients who were readmitted to the hospital with a primary diagnosis of SSI within 30 days of their arthroplasty procedure. RESULTS: There were 760,283 procedures (TKA 424,104, THA 336,179) in our sample. Our models indicate that SSI risk was highest for patients discharged from their surgery in June and lowest for December discharges. For TKA, the odds of a 30-day readmission for SSI were 30.5% higher at the peak compared to the nadir time (95% confidence interval [CI] 20-42). For THA, the seasonal increase in SSI was 19% (95% CI 9-30). Compared to Medicare, patients with Medicaid as the primary payer had a 49% higher odds of 30-day SSI after TKA (95% CI 32-68). CONCLUSION: SSIs following TKA and THA are seasonal peaking in summer months. Payer status was also a significant risk factor for SSIs. Future studies should investigate potential factors that could relate to the associations demonstrated in this study.

The AAHKS Clinical Research Award: What Are the Costs of Knee Osteoarthritis in the Year Prior to Total Knee Arthroplasty?

BACKGROUND: Despite American Academy of Orthopaedic Surgeons Clinical Practice Guidelines (CPGs) related to the non-arthroplasty management of osteoarthritis (OA) of the knee, non-recommended treatments remain in common use. We sought to determine the costs associated with non-arthroplasty management of knee OA in the year prior to total knee arthroplasty (TKA) and stratify them by CPG recommendation status. METHODS: The Humana database was reviewed from 2007 to 2015 for primary TKA patients. Costs for hyaluronic acid (HA) and corticosteroid injections, physical therapy, braces, wedge insoles, opioids, non-steroidal anti-inflammatories, and tramadol in the year prior to TKA were calculated. Cost was defined as reimbursement paid by the insurance provider. Costs were analyzed relative to the overall non-inpatient costs for knee OA and categorized based on CPG recommendations. RESULTS: In total 86,081 primary TKA patients were analyzed and 65.8% had at least one treatment in the year prior to TKA. Treatments analyzed made up 57.6% of the total non-inpatient cost of knee OA in the year prior to TKA. Only 3 of the 8 treatments studied have a strong recommendation for their use (physical therapy, non-steroidal anti-inflammatories, tramadol) and costs for these interventions represented 12.2% of non-inpatient knee OA cost. In contrast, 29.3% of the costs are due to HA injections alone, which are not supported by CPGs. CONCLUSION: In the year prior to TKA, over half of the non-inpatient costs associated with knee OA are from injections, therapy, prosthetics, and prescriptions. Approximately 30% of this is due to HA injections alone. If only interventions recommend by the CPG are utilized then costs associated with knee OA could be decreased by 45%.

Medicare's Hospital-Acquired Conditions Policy: A Problem of Nonpayment After Total Joint Arthroplasty.

BACKGROUND: Total joint arthroplasty (TJA) utilization continues to increase, and optimizing efficiency while reducing complications is critical to provide a sustainable product. Recent policy has defined several hospital-acquired conditions (HACs) that are the target of reducing complications with significant financial implications. The present study defines the incidence of HACs after TJA as well as patient and hospital factors associated with HACs. METHODS: The National Inpatient Sample (NIS) was used to identify all patients from 2009 to 2011 undergoing elective total hip or knee arthroplasty. Patient demographics, comorbidities, and hospital characteristics were obtained from the database, and HACs defined according to established International Classification of Diseases, Ninth Revision, Clinical Modification criteria. The incidence of HACs after TJA was calculated, as were demographic factors and preadmission comorbidities associated with HACs using bivariate and multivariable analysis. RESULTS: The overall incidence of HACs after TJA was 1.3%. Several patient and hospital factors, including increased age, female gender, black race, medium hospital bed size, year of surgery, and Charlson Comorbidity Index ≥1, independently predicted development of a HAC. When evaluating the financial impact of the development of a HAC after TJA, more than 200 million dollars in hospital costs would be lost during the inclusive years of this study, equating to nearly 70 million dollars annually. CONCLUSION: The incidence of HACs after TJA is 1.3%. Many of the patient factors associated with HACs are nonmodifiable, and risk adjustment should be considered to provide a sustainable product to a diverse patient population.

Database and Registry Research in Orthopaedic Surgery: Part I: Claims-Based Data.

The use of large-scale national databases for observational research in orthopaedic surgery has grown substantially in the last decade, and the data sets can be grossly categorized as either administrative claims or clinical registries. Administrative claims data comprise the billing records associated with the delivery of health-care services. Orthopaedic researchers have used both government and private claims to describe temporal trends, geographic variation, disparities, complications, outcomes, and resource utilization associated with both musculoskeletal disease and treatment. Medicare claims comprise one of the most robust data sets used to perform orthopaedic research, with >45 million beneficiaries. The U.S. government, through the Centers for Medicare & Medicaid Services, often uses these data to drive changes in health policy. Private claims data used in orthopaedic research often comprise more heterogeneous patient demographic samples, but allow longitudinal analysis similar to that offered by Medicare claims. Discharge databases, such as the U.S. National Inpatient Sample, provide a wide national sampling of inpatient hospital stays from all payers and allow analysis of associated adverse events and resource utilization. Administrative claims data benefit from the high patient numbers obtained through a majority of hospitals. Using claims, it is possible to follow patients longitudinally throughout encounters irrespective of the location of the institution delivering health care. Some disadvantages include lack of precision of ICD-9 (International Classification of Diseases, Ninth Revision) coding schemes. Much of these data are expensive to purchase, complicated to organize, and labor-intensive to manipulate--often requiring trained specialists for analysis. Given the changing health-care environment, it is likely that databases will provide valuable information that has the potential to influence clinical practice improvement and health policy for years to come.