Pub Date : 2019-11-01DOI: 10.1097/CORR.0000000000000860
D. Austin, M. Torchia, J. Lurie, D. Jevsevar, John‐Erik Bell
BACKGROUND The mechanism by which surgical innovation is spread in orthopaedic surgery is not well studied. The recent widespread transition from open to arthroscopic rotator cuff repair techniques provides us with the opportunity to study the spread of new technology; doing so would be important because it is unclear how novel orthopaedic techniques disseminate across time and geography, and previous studies of innovation in healthcare may not apply to the orthopaedic community. QUESTIONS/PURPOSES (1) How much regional variation was associated with the adoption of arthroscopic rotator cuff repair in the United States Medicare population between 2006 and 2014 and how did this change over time? (2) In which regions of the United States was arthroscopic rotator cuff repair first adopted and how did it spread geographically? (3) Which regional factors were associated with the adoption of this new technology? METHODS We divided the United States into 306 hospital referral regions based upon referral patterns observed in the Centers for Medicare & Medicaid Services MedPAR database, which records all Medicare hospital admissions; this has been done in numerous previous studies using methodology introduced by the Dartmouth Atlas. The proportion of arthroscopic rotator cuff repairs versus open rotator cuff repairs in each hospital referral region was calculated using adjusted procedural rates from the Medicare Part B Carrier File from 2006 to 2014, as it provided a nationwide sample of patients, and was used as a measure of adoption. A population-weighted, multivariable linear regression analysis was used to identify regional characteristics independently associated with adoption. RESULTS There was substantial regional variation associated with the adoption of arthroscopy for rotator cuff repair as the percentage of rotator cuff repair completed arthroscopically in 2006 ranged widely among hospital referral regions with a high of 85.3% in Provo, UT, USA, and a low of 16.7% in Seattle, WA, USA (OR 30, 95% CI 17.6 to 52.2; p < 0.001). In 2006, regions in the top quartiles for Medicare spending (+9.1%; p = 0.008) independently had higher adoption rates than those in the bottom quartile, as did regions with a greater proportion of college-educated residents (+12.0%; p = 0.009). The Northwest region (-14.4%; p = 0.009) and the presence of an academic medical center (-5.8%; p = 0.026) independently had lower adoption than other regions and those without academic medical centers. In 2014, regions in the top quartiles for Medicare spending (+5.7%; p = 0.033) and regions with a greater proportion of college-educated residents (+9.4%; p = 0.005) independently had higher adoption rates than those in the bottom quartiles, while the Northwest (-9.6%; p = 0.009) and Midwest regions (-5.1%; p = 0.017) independently had lower adoption than other regions. CONCLUSION The heterogeneous diffusion of arthroscopic rotator cuff repair across the United States highlight
{"title":"Mapping the Diffusion of Technology in Orthopaedic Surgery: Understanding the Spread of Arthroscopic Rotator Cuff Repair in the United States.","authors":"D. Austin, M. Torchia, J. Lurie, D. Jevsevar, John‐Erik Bell","doi":"10.1097/CORR.0000000000000860","DOIUrl":"https://doi.org/10.1097/CORR.0000000000000860","url":null,"abstract":"BACKGROUND\u0000The mechanism by which surgical innovation is spread in orthopaedic surgery is not well studied. The recent widespread transition from open to arthroscopic rotator cuff repair techniques provides us with the opportunity to study the spread of new technology; doing so would be important because it is unclear how novel orthopaedic techniques disseminate across time and geography, and previous studies of innovation in healthcare may not apply to the orthopaedic community.\u0000\u0000\u0000QUESTIONS/PURPOSES\u0000(1) How much regional variation was associated with the adoption of arthroscopic rotator cuff repair in the United States Medicare population between 2006 and 2014 and how did this change over time? (2) In which regions of the United States was arthroscopic rotator cuff repair first adopted and how did it spread geographically? (3) Which regional factors were associated with the adoption of this new technology?\u0000\u0000\u0000METHODS\u0000We divided the United States into 306 hospital referral regions based upon referral patterns observed in the Centers for Medicare & Medicaid Services MedPAR database, which records all Medicare hospital admissions; this has been done in numerous previous studies using methodology introduced by the Dartmouth Atlas. The proportion of arthroscopic rotator cuff repairs versus open rotator cuff repairs in each hospital referral region was calculated using adjusted procedural rates from the Medicare Part B Carrier File from 2006 to 2014, as it provided a nationwide sample of patients, and was used as a measure of adoption. A population-weighted, multivariable linear regression analysis was used to identify regional characteristics independently associated with adoption.\u0000\u0000\u0000RESULTS\u0000There was substantial regional variation associated with the adoption of arthroscopy for rotator cuff repair as the percentage of rotator cuff repair completed arthroscopically in 2006 ranged widely among hospital referral regions with a high of 85.3% in Provo, UT, USA, and a low of 16.7% in Seattle, WA, USA (OR 30, 95% CI 17.6 to 52.2; p < 0.001). In 2006, regions in the top quartiles for Medicare spending (+9.1%; p = 0.008) independently had higher adoption rates than those in the bottom quartile, as did regions with a greater proportion of college-educated residents (+12.0%; p = 0.009). The Northwest region (-14.4%; p = 0.009) and the presence of an academic medical center (-5.8%; p = 0.026) independently had lower adoption than other regions and those without academic medical centers. In 2014, regions in the top quartiles for Medicare spending (+5.7%; p = 0.033) and regions with a greater proportion of college-educated residents (+9.4%; p = 0.005) independently had higher adoption rates than those in the bottom quartiles, while the Northwest (-9.6%; p = 0.009) and Midwest regions (-5.1%; p = 0.017) independently had lower adoption than other regions.\u0000\u0000\u0000CONCLUSION\u0000The heterogeneous diffusion of arthroscopic rotator cuff repair across the United States highlight","PeriodicalId":10465,"journal":{"name":"Clinical Orthopaedics & Related Research","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84774555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1097/CORR.0000000000000891
T. Tan
In the current study, Hernandez and colleagues [4] performed a prospective study utilizing a mouse model with a titanium tibial implant that was directly inoculated with bacteria to simulate periprosthetic joint infection (PJI). The authors found that if they disrupted the gutmicrobiotawith chronic oral antibiotics, the odds of developing PJI more than doubled that of controls. The authors also noted a blunted immune response in patients with altered gut microbiota [4]. This finding supports the idea that alterations or dysbiosis in the natural gut microbiome of a host or patient may influence the risk of PJI in patients who undergo arthroplasty. As we search to minimize the frequency of what might be the most devastating complication of total joint arthroplasty, PJI, the current study supports two hypotheses of interest. First, that the gut microbiome is linked with the immune system, and second, that alterations in the gut microbiome may influence the susceptibility of patients to joint infection. The presence and importance of the humanmicrobiome has gained increased attention in medicine within the last decade [3, 7]. The majority of the 1000 distinct microbial species in each individual are found in the gastrointestinal system [3]. As suggested by the authors of the current study, changes in the microbiome may influence distant organs and have musculoskeletal implications by several mechanisms [4]. Nutritional absorption is influenced by the gut microbiota and alterations in flora may impair the absorption of key nutrients [7]. Furthermore, malnutrition is a potential modifiable risk factor for PJI [9], raising the question as towhether this link is actually caused by alterations in the microbiome. The gut is also the largest immune organ, and thus, changes in the gut microbiome may influence the immunological response directly [3]. Several strategies in modern medicine are currently used to target of the gut microbiome and combat microbial community alterations, referred to as dysbiosis. For example, fecal transplantation has been successfully used to combat Clostridium difficile infection and inflammatory bowel disease [10]. While there is no evidence to suggest that fecal transplantation would decrease the risk of PJI, there is some preliminary evidence to suggest that modifying the gut microbiome may influence PJI in an animal model. For example, one study correlated the presence of Bacillus bacteria in the gut (which is the most common bacteria included in probiotics and can be increased through simple dietary interventions like eating Greek yogurt or drinking kombucha tea) with the absence of Staphylococcus aureus colonization in the gut and nares [7]. Given that nasal decolonization of S aureus is a widely adopted strategy for preventing PJI, modifying the gut microbiome may be a novel and viable eradication strategy, though the evidence on this topic is premature, to say the least.
{"title":"CORR Insights®: Disruption of the Gut Microbiome Increases the Risk of Periprosthetic Joint Infection in Mice.","authors":"T. Tan","doi":"10.1097/CORR.0000000000000891","DOIUrl":"https://doi.org/10.1097/CORR.0000000000000891","url":null,"abstract":"In the current study, Hernandez and colleagues [4] performed a prospective study utilizing a mouse model with a titanium tibial implant that was directly inoculated with bacteria to simulate periprosthetic joint infection (PJI). The authors found that if they disrupted the gutmicrobiotawith chronic oral antibiotics, the odds of developing PJI more than doubled that of controls. The authors also noted a blunted immune response in patients with altered gut microbiota [4]. This finding supports the idea that alterations or dysbiosis in the natural gut microbiome of a host or patient may influence the risk of PJI in patients who undergo arthroplasty. As we search to minimize the frequency of what might be the most devastating complication of total joint arthroplasty, PJI, the current study supports two hypotheses of interest. First, that the gut microbiome is linked with the immune system, and second, that alterations in the gut microbiome may influence the susceptibility of patients to joint infection. The presence and importance of the humanmicrobiome has gained increased attention in medicine within the last decade [3, 7]. The majority of the 1000 distinct microbial species in each individual are found in the gastrointestinal system [3]. As suggested by the authors of the current study, changes in the microbiome may influence distant organs and have musculoskeletal implications by several mechanisms [4]. Nutritional absorption is influenced by the gut microbiota and alterations in flora may impair the absorption of key nutrients [7]. Furthermore, malnutrition is a potential modifiable risk factor for PJI [9], raising the question as towhether this link is actually caused by alterations in the microbiome. The gut is also the largest immune organ, and thus, changes in the gut microbiome may influence the immunological response directly [3]. Several strategies in modern medicine are currently used to target of the gut microbiome and combat microbial community alterations, referred to as dysbiosis. For example, fecal transplantation has been successfully used to combat Clostridium difficile infection and inflammatory bowel disease [10]. While there is no evidence to suggest that fecal transplantation would decrease the risk of PJI, there is some preliminary evidence to suggest that modifying the gut microbiome may influence PJI in an animal model. For example, one study correlated the presence of Bacillus bacteria in the gut (which is the most common bacteria included in probiotics and can be increased through simple dietary interventions like eating Greek yogurt or drinking kombucha tea) with the absence of Staphylococcus aureus colonization in the gut and nares [7]. Given that nasal decolonization of S aureus is a widely adopted strategy for preventing PJI, modifying the gut microbiome may be a novel and viable eradication strategy, though the evidence on this topic is premature, to say the least.","PeriodicalId":10465,"journal":{"name":"Clinical Orthopaedics & Related Research","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82970275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1097/CORR.0000000000000980
P. Meshram
From the column editor, In this month’s CORR International—Asia-Pacific column, Prashant Meshram MS, DNB, a research fellow from Mumbai, India details the obstacles young orthopaedic surgeons from the Asia-Pacific region face when pursuing a fellowship abroad. Dr. Meshram has worked as a resident and junior physician at two of the highest-volume tertiary care centers in the region, and has experience of fellowship at three centers in developed countries including the United States. After a young surgeon in a developing country finishes his or her residency, (s)he must decide whether to pursue subspecialty training or start an independent practice. Traditionally, young surgeons would jump into private practice. But today, we are seeing more surgeons from the AsiaPacific countries pursuing and securing international fellowships. Why are more surgeons taking the road less traveled? And how can young surgeons get the most out of their fellowship abroad? Read this month’s guest column from Dr. Meshram to find out the answers to these questions. — Tae Kyun Kim MD, PhD Orthopaedic surgeons who complete their residency in the Asia-Pacific region often face a difficult question: What’s next? Unlike in the United States, where more than 96% of orthopaedic surgery residents pursue fellowship training [8], many of the orthopaedic graduates in the AsiaPacific region choose private practice or accept a junior physician position at public or private hospitals. Without access to a formal matching process [8], there is a notion, at least in India where I am from, that starting independent clinical practice right after residency will help build one’s reputation among patients and peers. Yet more orthopaedic surgeons in the Asia-Pacific region are choosing international fellowships to practice their chosen subspecialty. Fellowships help build one’s depth of knowledge and skills in a subspecialty, and overseas fellowships offer physicians a chance to learn about different aspects of patient care that they may not see or use in private practice in their home country. But lack of opportunity, a dearth of mentorship or guidance, and financial constraints are just some of the obstacles that may discourage physicians from pursuing their fellowship abroad. After my residency inMumbai, India, I was fortunate to work in clinical fellowships under two leading surgeons in South Korea, and I am currently working as a research fellow at Johns Hopkins University in Baltimore, MD, USA. My experience helped me understand the key aspects that will help young orthopaedic physicians get the most out of their overseas fellowship.
在本月的CORR国际-亚太专栏中，来自印度孟买的研究人员普拉桑特·梅什拉姆(Prashant Meshram)详细介绍了来自亚太地区的年轻整形外科医生在寻求海外奖学金时面临的障碍。Meshram博士曾在该地区两家规模最大的三级医疗中心担任住院医师和初级医师，并在包括美国在内的三个发达国家的中心担任研究员。在发展中国家，一位年轻的外科医生在完成他或她的住院医师实习期后，他必须决定是继续专科培训还是开始独立执业。传统上，年轻的外科医生会跳进私人诊所。但今天，我们看到越来越多来自亚太国家的外科医生寻求并获得国际奖学金。为什么越来越多的外科医生选择人迹罕至的路?年轻的外科医生怎样才能最大限度地利用他们在国外的实习机会呢?阅读梅什拉姆博士本月的客座专栏，找出这些问题的答案。- Tae Kyun Kim MD, PhD在亚太地区完成实习的骨科医生经常面临一个难题:下一步是什么?与美国96%以上的骨科住院医师接受奖学金培训不同[8]，亚太地区的许多骨科毕业生选择私人执业或接受公立或私立医院的初级医师职位。如果没有正式的匹配过程[8]，至少在我来自的印度，有一种观念认为，在住院医生之后立即开始独立的临床实践将有助于在患者和同行中建立声誉。然而，亚太地区越来越多的整形外科医生选择国际奖学金来实践他们选择的专科。奖学金可以帮助医生在一个亚专业中积累知识和技能，海外奖学金为医生提供了一个学习病人护理的不同方面的机会，这些方面他们在本国的私人诊所中可能看不到或使用不到。但是，缺乏机会、缺乏指导和经济上的限制可能只是阻碍医生在国外攻读博士学位的一些障碍。在印度孟买住院医师实习期结束后，我有幸在韩国两位顶尖外科医生的指导下从事临床研究工作，目前我在美国马里兰州巴尔的摩的约翰霍普金斯大学担任研究员。我的经历帮助我了解了帮助年轻骨科医生从海外学习中获得最大收益的关键方面。
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Pub Date : 2019-11-01DOI: 10.1097/CORR.0000000000000984
P. Manner
Why are some technologies adopted quickly, while others are not? Why are some surgical procedures adopted wholeheartedly and others simply dismissed? Why does this vary from place to place? In this month’s Editor’s Spotlight/Take 5, Daniel C. Austin MD, MS and his team from Dartmouth-Hitchcock Medical Center, already known for their work on surgical variation [2], show profound differences in adoption of arthroscopic repair of rotator cuff tears between hospital referral regions across the United States [1]. Why might this be so? Providers may surmise that a patient in Paris, TX, USA and one in Rome, GA, USA (to borrow half a line from a country song) both will receive the same surgical recommendation if they present with the same clinical problem. But while variation is typically quite low for straightforward problems— surgery is appropriate for almost all patients with hip fractures—the degree of variation for other diagnoses is surprising. For example, coils are used to treat cerebral aneurysms in 99% of patients covered byMedicare in Tacoma, WA, USA, while less than 40% of patients treated for unruptured aneurysms received coiling in Modesto, CA, USA, Madison, WI, USA and Manchester, NH, USA [2]. What about when new procedures or approaches are introduced? Presumably, we’re all reading the same studies and getting the same information on the risks and benefits of a new technique. It’s reasonable to think that adoption would occur with similar patterns, and over the same amount of time. But this is almost never the case. There are notable differences in how individuals approach technological novelty. The first systematic assessment on how to incorporate new practice into daily life dates back to the early 20th century. Ryan and Gross [7] looked at how Iowa farmers used hybrid seed corn and found features that resonate even today: There was a time lag of about 5 years between first knowledge and first adoption; those who tried the approach earliest were somewhat tentative in incorporating new seed; late adopters were more likely to carry out a full conversion, and “almost all had heard of the new trait before more than a handful were planting it” [7]. Farmers fell into several categories: Innovators, early adopters, early majority, late majority, and laggards—familiar territory for surgeons. In the early 1960s, Everett Rogers developed the theory of diffusion of innovations, and proposed four elements that influence the spread of a new idea: (1) The innovation itself, (2) communication channels, (3) time, and (4) a social system [6]. Although Rogers did not write specifically about medical or surgical techniques, his model resonates with providers trying out new forms of therapy. A note from the Editor-In-Chief: In “Editor’s Spotlight,” one of our editors provides brief commentary on a paper we believe is especially important and worthy of general interest. Following the explanation of our choice, we present “Take 5,” in which the editor goes b
为什么有些技术被迅速采用，而另一些却没有?为什么有些外科手术被全心全意地接受，而另一些则被简单地抛弃?为什么各地的情况不同呢?在本月的编辑聚焦/第5篇中，达特茅斯-希区柯克医疗中心的Daniel C. Austin MD, MS和他的团队已经以手术变异的研究而闻名[2]，他们展示了美国不同医院转诊地区在采用关节镜修复肩袖撕裂方面的巨大差异[1]。为什么会这样呢?提供者可能会推测，一个在美国德克萨斯州巴黎的病人和一个在美国佐治亚州罗马的病人(借用一首乡村歌曲的半句歌词)，如果他们表现出相同的临床问题，他们会得到相同的手术建议。但是，尽管对于直接的问题来说，手术通常是非常低的——几乎所有髋部骨折的患者都可以接受手术——但其他诊断的差异程度却令人惊讶。例如，在美国华盛顿州塔科马市，99%的医疗保险患者使用线圈治疗脑动脉瘤，而在美国加利福尼亚州莫德斯托市、美国威斯康星州麦迪逊市和美国新罕布什尔州曼彻斯特市，只有不到40%的未破裂动脉瘤患者接受了线圈治疗[2]。当引入新的程序或方法时怎么办?大概，我们都在阅读同样的研究，并得到同样的信息，关于一项新技术的风险和好处。有理由认为，采用将以类似的模式发生，并在相同的时间内。但这种情况几乎从未发生过。不同个体对待新技术的方式存在显著差异。关于如何将新的实践融入日常生活的第一次系统评估可以追溯到20世纪初。Ryan和Gross[7]研究了爱荷华州农民如何使用杂交玉米种子，并发现了一些即使在今天也能引起共鸣的特征:从第一次知道到第一次采用之间大约有5年的时间滞后;那些最早尝试这种方法的人在加入新种子方面有些犹豫不决;较晚的采用者更有可能进行完全的转化，而且“在少数人种植这种新性状之前，几乎所有人都听说过它”[7]。农民分为几类:创新者、早期采用者、早期多数、晚期多数和落后者——这是外科医生熟悉的领域。20世纪60年代初，埃弗雷特·罗杰斯(Everett Rogers)发展了创新扩散理论，提出了影响新思想传播的四个因素:(1)创新本身;(2)传播渠道;(3)时间;(4)社会制度[6]。虽然罗杰斯没有专门写关于医疗或外科技术的文章，但他的模型与尝试新形式治疗的提供者产生了共鸣。总编辑的注释:在“编辑聚焦”中，我们的一位编辑对一篇我们认为特别重要且值得普遍关注的论文提供了简短的评论。在解释了我们的选择之后，我们将呈现“第5条”，在这条视频中，编辑将通过对“编辑聚焦”中这篇文章的一位作者的一对一采访，深入了解这一发现的背后。提交人证明，他本人及其直系亲属均无任何可能与所提交文章产生利益冲突的商业协会(如咨询公司、股票所有权、股权、专利/许可安排等)。所有ICMJE作者和临床骨科及相关研究编辑和董事会成员的利益冲突表都在出版物中存档，可以根据要求查看。所表达的观点是作者的观点，不反映CORR或骨关节外科医生协会的观点或政策。此评论参考的文章可在:DOI: 10.1097/CORR.0000000000000860。P.A. Manner医学博士，临床骨科及相关研究，美国费城1600 Spruce St, PA 19013 USA，电子邮件:sleopold@clinorthop.org P.A. Manner，美国费城临床骨科及相关研究高级编辑
{"title":"Editor's Spotlight/Take 5: Mapping the Diffusion of Technology in Orthopaedic Surgery: Understanding the Spread of Arthroscopic Rotator Cuff Repair in the United States.","authors":"P. Manner","doi":"10.1097/CORR.0000000000000984","DOIUrl":"https://doi.org/10.1097/CORR.0000000000000984","url":null,"abstract":"Why are some technologies adopted quickly, while others are not? Why are some surgical procedures adopted wholeheartedly and others simply dismissed? Why does this vary from place to place? In this month’s Editor’s Spotlight/Take 5, Daniel C. Austin MD, MS and his team from Dartmouth-Hitchcock Medical Center, already known for their work on surgical variation [2], show profound differences in adoption of arthroscopic repair of rotator cuff tears between hospital referral regions across the United States [1]. Why might this be so? Providers may surmise that a patient in Paris, TX, USA and one in Rome, GA, USA (to borrow half a line from a country song) both will receive the same surgical recommendation if they present with the same clinical problem. But while variation is typically quite low for straightforward problems— surgery is appropriate for almost all patients with hip fractures—the degree of variation for other diagnoses is surprising. For example, coils are used to treat cerebral aneurysms in 99% of patients covered byMedicare in Tacoma, WA, USA, while less than 40% of patients treated for unruptured aneurysms received coiling in Modesto, CA, USA, Madison, WI, USA and Manchester, NH, USA [2]. What about when new procedures or approaches are introduced? Presumably, we’re all reading the same studies and getting the same information on the risks and benefits of a new technique. It’s reasonable to think that adoption would occur with similar patterns, and over the same amount of time. But this is almost never the case. There are notable differences in how individuals approach technological novelty. The first systematic assessment on how to incorporate new practice into daily life dates back to the early 20th century. Ryan and Gross [7] looked at how Iowa farmers used hybrid seed corn and found features that resonate even today: There was a time lag of about 5 years between first knowledge and first adoption; those who tried the approach earliest were somewhat tentative in incorporating new seed; late adopters were more likely to carry out a full conversion, and “almost all had heard of the new trait before more than a handful were planting it” [7]. Farmers fell into several categories: Innovators, early adopters, early majority, late majority, and laggards—familiar territory for surgeons. In the early 1960s, Everett Rogers developed the theory of diffusion of innovations, and proposed four elements that influence the spread of a new idea: (1) The innovation itself, (2) communication channels, (3) time, and (4) a social system [6]. Although Rogers did not write specifically about medical or surgical techniques, his model resonates with providers trying out new forms of therapy. A note from the Editor-In-Chief: In “Editor’s Spotlight,” one of our editors provides brief commentary on a paper we believe is especially important and worthy of general interest. Following the explanation of our choice, we present “Take 5,” in which the editor goes b","PeriodicalId":10465,"journal":{"name":"Clinical Orthopaedics & Related Research","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87732095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1097/CORR.0000000000000928
P. Jayakumar, T. Teunis, A. Vranceanu, S. Lamb, Mark A Williams, D. Ring, S. Gwilym
BACKGROUND Patient perceptions of their limitations after illness and injury can be quantified using patient-reported outcome measures (PROMs). Few studies have assessed construct validity (using correlations and factor analysis) and precision (floor and ceiling effects) of a range of frequently used PROMs longitudinally in a population of patients recovering from common upper extremity fractures according to area (general health, region-specific, or joint-specific measures) and mode of administration (fixed-scale or computer adaptive test). QUESTIONS/PURPOSES (1) What is the strength of the correlation between different PROMs within 1 week, 2 to 4 weeks and 6 to 9 months after shoulder, elbow, and wrist fractures? (2) Using a factor analysis, what underlying constructs are being measured by these PROMs? (3) Are there strong floor and ceiling effects with these instruments? METHODS Between January 2016 and August 2016, 734 patients recovering from an isolated shoulder, elbow, or wrist fracture completed physical-limitation PROMs at baseline (the initial office visit after diagnosis in the emergency department), 2 to 4 weeks after injury, and at the final assessment 6 to 9 months after injury. In all, 775 patients were originally approached; 31 patients (4%) declined to participate due to time constraints, four patients died of unrelated illness, and six patients were lost to follow-up. The PROMs included the PROMIS Physical Function (PF, a computer adaptive, general measure of physical function), the PROMIS Upper Extremity (UE, a computer adaptive measure of upper extremity physical function), the QuickDASH (a fixed-scale, region-specific measure), the Oxford Shoulder Score (OSS), the Oxford Elbow Score (OES) and the Patient-rated Wrist Evaluation (PRWE) (a fixed-scale, joint-specific measure), and the EQ-5D-3L (a fixed-scale measure of general health). PROMs were evaluated during recovery for construct validity (using correlations and factor analysis) and precision (using floor and ceiling effects). RESULTS Physical-limitation PROMs were intercorrelated at all time points, and the correlation strengthened over time (for example, PROMIS UE and QuickDASH at 1 week, r = -0.4665; at 2 to 4 weeks, r = -0.7763; at 6 to 9 months, r = -0.8326; p < 0.001). Factor analysis generated two factors or groupings of PROMs that could be described as capability (perceived ability to perform or engage in activities), and quality of life (an overall sense of health and wellbeing) that varied by time point and fracture type, Joint-specific and general-health PROMs demonstrated high ceiling effects 6 to 9 months after injury and PROMIS PF, PROMIS UE and QuickDASH had no floor or ceiling effects at any time points. CONCLUSIONS There is a substantial correlation between PROMs that assess physical limitations (based on anatomic region) and general health after upper extremity fractures, and these relationships strengthen during recovery. Regardless of the delive
{"title":"Construct Validity and Precision of Different Patient-reported Outcome Measures During Recovery After Upper Extremity Fractures.","authors":"P. Jayakumar, T. Teunis, A. Vranceanu, S. Lamb, Mark A Williams, D. Ring, S. Gwilym","doi":"10.1097/CORR.0000000000000928","DOIUrl":"https://doi.org/10.1097/CORR.0000000000000928","url":null,"abstract":"BACKGROUND\u0000Patient perceptions of their limitations after illness and injury can be quantified using patient-reported outcome measures (PROMs). Few studies have assessed construct validity (using correlations and factor analysis) and precision (floor and ceiling effects) of a range of frequently used PROMs longitudinally in a population of patients recovering from common upper extremity fractures according to area (general health, region-specific, or joint-specific measures) and mode of administration (fixed-scale or computer adaptive test).\u0000\u0000\u0000QUESTIONS/PURPOSES\u0000(1) What is the strength of the correlation between different PROMs within 1 week, 2 to 4 weeks and 6 to 9 months after shoulder, elbow, and wrist fractures? (2) Using a factor analysis, what underlying constructs are being measured by these PROMs? (3) Are there strong floor and ceiling effects with these instruments?\u0000\u0000\u0000METHODS\u0000Between January 2016 and August 2016, 734 patients recovering from an isolated shoulder, elbow, or wrist fracture completed physical-limitation PROMs at baseline (the initial office visit after diagnosis in the emergency department), 2 to 4 weeks after injury, and at the final assessment 6 to 9 months after injury. In all, 775 patients were originally approached; 31 patients (4%) declined to participate due to time constraints, four patients died of unrelated illness, and six patients were lost to follow-up. The PROMs included the PROMIS Physical Function (PF, a computer adaptive, general measure of physical function), the PROMIS Upper Extremity (UE, a computer adaptive measure of upper extremity physical function), the QuickDASH (a fixed-scale, region-specific measure), the Oxford Shoulder Score (OSS), the Oxford Elbow Score (OES) and the Patient-rated Wrist Evaluation (PRWE) (a fixed-scale, joint-specific measure), and the EQ-5D-3L (a fixed-scale measure of general health). PROMs were evaluated during recovery for construct validity (using correlations and factor analysis) and precision (using floor and ceiling effects).\u0000\u0000\u0000RESULTS\u0000Physical-limitation PROMs were intercorrelated at all time points, and the correlation strengthened over time (for example, PROMIS UE and QuickDASH at 1 week, r = -0.4665; at 2 to 4 weeks, r = -0.7763; at 6 to 9 months, r = -0.8326; p < 0.001). Factor analysis generated two factors or groupings of PROMs that could be described as capability (perceived ability to perform or engage in activities), and quality of life (an overall sense of health and wellbeing) that varied by time point and fracture type, Joint-specific and general-health PROMs demonstrated high ceiling effects 6 to 9 months after injury and PROMIS PF, PROMIS UE and QuickDASH had no floor or ceiling effects at any time points.\u0000\u0000\u0000CONCLUSIONS\u0000There is a substantial correlation between PROMs that assess physical limitations (based on anatomic region) and general health after upper extremity fractures, and these relationships strengthen during recovery. Regardless of the delive","PeriodicalId":10465,"journal":{"name":"Clinical Orthopaedics & Related Research","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83698426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1097/CORR.0000000000000987
Fatih Özden
To the Editor, I read the study by Kayaalp and colleagues [1] with great interest. While I believe the authors have made a considerable contribution with this work, there are some concerns that I would like to address. The authors analyzed the construct validity of the new Knee Society Score (KSS) using the German WOMAC and the German SF-36. The Licensed User Manual of the Knee Society Knee Scoring System [5] stated that the new KSS was generally consistent with other “knee-specific” scores. In this study, the German WOMAC does not meet all parameters evaluated by the new KSS, which now includes patient expectation and satisfaction parameters. The low correlation values between the patient expectations subdomain and the German WOMAC subdomain support this criticism. Additionally, applying such long questionnaires burdens the patient [3]. Shortening the questionnaires for patients may reduce the burden, but a validity study with a single knee-specific questionnaire may not provide all the information that patients wish to share or that providers need to make good surgical decisions. Another concern is that although the Licensed User Manual of the Knee Society Scoring System [5] states that there is no total score of the survey, the authors calculated the total score and performed a statistical analysis. This situation should be corrected immediately, as this may lead to misleading results and the development of chain errors. The authors performed the study with 100 patients, and they also included 39 patients for test-re-test reliability. That number of patients is low for the validity and reliability of this questionnaire, considering the recommendation that the sample size should be 10 times the number of items [4]. Since only the patient expectations subdomain of the questionnaire is different between preoperative and post-operative versions of the new KSS, performing the analysis of the other subdomains with all patients could make the statistical analysis more valuable like in the Turkish version of the new KSS. [2]. Finally, I would like to mention a minor error. In Table 3, the correlation coefficient (symptoms subdomain of the new KSS and mental health subdomain of the German SF36), which we normally expect to be negative, was positive, whereas the correlation coefficient (between symptoms subdomain of the new KSS and vitality subdomain of German SF-36), which we expected to be positive, was negative. This may adversely affect the validity of the study.
{"title":"Letter to the Editor: Translation and Validation of the German New Knee Society Scoring System.","authors":"Fatih Özden","doi":"10.1097/CORR.0000000000000987","DOIUrl":"https://doi.org/10.1097/CORR.0000000000000987","url":null,"abstract":"To the Editor, I read the study by Kayaalp and colleagues [1] with great interest. While I believe the authors have made a considerable contribution with this work, there are some concerns that I would like to address. The authors analyzed the construct validity of the new Knee Society Score (KSS) using the German WOMAC and the German SF-36. The Licensed User Manual of the Knee Society Knee Scoring System [5] stated that the new KSS was generally consistent with other “knee-specific” scores. In this study, the German WOMAC does not meet all parameters evaluated by the new KSS, which now includes patient expectation and satisfaction parameters. The low correlation values between the patient expectations subdomain and the German WOMAC subdomain support this criticism. Additionally, applying such long questionnaires burdens the patient [3]. Shortening the questionnaires for patients may reduce the burden, but a validity study with a single knee-specific questionnaire may not provide all the information that patients wish to share or that providers need to make good surgical decisions. Another concern is that although the Licensed User Manual of the Knee Society Scoring System [5] states that there is no total score of the survey, the authors calculated the total score and performed a statistical analysis. This situation should be corrected immediately, as this may lead to misleading results and the development of chain errors. The authors performed the study with 100 patients, and they also included 39 patients for test-re-test reliability. That number of patients is low for the validity and reliability of this questionnaire, considering the recommendation that the sample size should be 10 times the number of items [4]. Since only the patient expectations subdomain of the questionnaire is different between preoperative and post-operative versions of the new KSS, performing the analysis of the other subdomains with all patients could make the statistical analysis more valuable like in the Turkish version of the new KSS. [2]. Finally, I would like to mention a minor error. In Table 3, the correlation coefficient (symptoms subdomain of the new KSS and mental health subdomain of the German SF36), which we normally expect to be negative, was positive, whereas the correlation coefficient (between symptoms subdomain of the new KSS and vitality subdomain of German SF-36), which we expected to be positive, was negative. This may adversely affect the validity of the study.","PeriodicalId":10465,"journal":{"name":"Clinical Orthopaedics & Related Research","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81993354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1097/CORR.0000000000000985
Aaron Alokozai, P. Jayakumar, K. Bozic
As orthopaedic surgery shifts toward value-based payment and delivery models [12], clinicians and payers alike are prioritizing efforts to identify patients at risk of poor clinical and patient-reported outcomes following an orthopaedic procedure. What if there was a measurable parameter thatwe could use to help patients improve their ownhealth, inexpensively, and with little risk? Such a parameter exists—although surgeons likely do not know about it. That parameter is called patient activation, which is a patients’ level of engagement in their own health. In our view, the more engaged a patient is, the more “activated” they are in taking interest in and managing their health, as well as interacting with their surrounding health ecosystem. We believe this concept is especially relevant in the context of patient risk factors surrounding orthopaedic surgery. While identifying and ameliorating modifiable risk factors (BMI, high A1C, and smoking cessation) early along the care continuum can predictably improve patient-reported and clinical outcomes following surgery [5], the role of patient activation as a modifiable risk factor has not been definitively proven. Validated patient-reported survey instruments for measuring activation include the Patient Activation Measure (PAM-13/PAM-10) and the Effective Consumer Scale (EC-17) [7, 10]. Survey instruments like PAM specifically assesses activation and the personal and psychological competencies (knowledge, skills, confidence) required to manage one’s health. The EC-17 scale is designed to measure an individual’s skills, behaviors, and effectiveness in dealing with their condition andmaking decisions to effectively manage their health. Intuitively, the propensity to engage in adaptive health behaviors demands a level of self-efficacy, which can be measured using tools such as the validated Pain Self Efficacy Questionnaire [11]. These measures have been developed mostly for chronic conditions involving non-musculoskeletal populations. Not surprisingly, many orthopaedic surgeons are unaware of the concept of patient activation, let alone the existence of these measures. Still, there is a growing body of work in orthopaedics, particularly in upper extremity, spine, and total joint arthroplasty evaluating the impact of patient activation on clinical and patientreported outcomes [5, 13, 14]. These studies found greater decreases in pain and disability, as well as improved adherence with physical therapy in patients who were more activated. A note from the Editor-in-Chief: We are pleased to present to readers of Clinical Orthopaedics and Related Research the latest Value-based Healthcare column (formerly Orthopaedic Healthcare Worldwide). Valuebased Healthcare explores strategies to enhance the value of musculoskeletal care by improving health outcomes and reducing the overall cost of care delivery. We welcome reader feedback on all of our columns and articles; please send your comments to eic@ clinorthop.org.
随着骨科手术转向以价值为基础的支付和交付模式[12]，临床医生和支付方都在优先努力识别在骨科手术后存在不良临床和患者报告结果风险的患者。如果有一个可测量的参数，我们可以用它来帮助病人改善自己的健康，成本低，风险小呢?这样的参数是存在的——尽管外科医生可能不知道。这个参数被称为患者激活，这是患者对自己健康的参与程度。在我们看来，患者的参与度越高，他们就越“活跃”地关注和管理自己的健康，并与周围的健康生态系统互动。我们认为这一概念在骨科手术患者风险因素的背景下尤其相关。虽然在护理过程中早期识别和改善可改变的危险因素(BMI、高糖化血红蛋白和戒烟)可以预测地改善手术后患者报告和临床结果[5]，但患者激活作为可改变的危险因素的作用尚未得到明确证实。经过验证的患者报告的测量激活的调查工具包括患者激活量表(PAM-13/PAM-10)和有效消费者量表(EC-17)[7,10]。像PAM这样的调查工具专门评估管理一个人健康所需的激活和个人和心理能力(知识、技能、信心)。EC-17量表旨在衡量个人的技能、行为和处理病情的有效性，并做出有效管理自己健康的决定。直观地说，从事适应性健康行为的倾向需要一定程度的自我效能感，这可以使用诸如经过验证的疼痛自我效能问卷等工具来测量[11]。这些措施主要是针对涉及非肌肉骨骼人群的慢性疾病而制定的。毫不奇怪，许多骨科医生都不知道患者激活的概念，更不用说这些措施的存在了。尽管如此，在骨科，特别是在上肢、脊柱和全关节置换术中，仍有越来越多的工作评估患者激活对临床和患者报告结果的影响[5,13,14]。这些研究发现，更活跃的患者疼痛和残疾的减少幅度更大，并且更坚持物理治疗。总编辑的注释:我们很高兴向《临床骨科及相关研究》的读者介绍最新的基于价值的医疗保健专栏(前身为《全球骨科医疗保健》)。《基于价值的医疗保健》探讨了通过改善健康结果和降低护理交付的总体成本来提高肌肉骨骼护理价值的策略。我们欢迎读者对我们所有的专栏和文章进行反馈;请将您的意见发送至eic@clinorthop.org。一位作者(KJB)证明，在研究期间，他或他的直系亲属作为顾问已经或可能收到来自医疗保险和医疗补助服务中心(Baltimore, MD, USA)的金额为1万至10万美元的付款或福利。所有ICMJE作者和临床骨科及相关研究编辑和董事会成员的利益冲突表都在出版物中存档，可以根据要求查看。本文仅代表作者个人观点，不代表CORR或骨关节外科医师协会的观点或政策。K. J. Bozic医学博士，工商管理硕士(MD)，得克萨斯大学奥斯汀分校戴尔医学院，1701 Trinity Street, Austin, TX 78712 USA, Email: kevin.bozic@austin.utexas.edu A. Alokozai，杜兰大学医学院，新奥尔良，LA, USA，外科和围手术期护理助理教授，临床研究和结果测量主任。英国哈克尼斯卫生保健政策和实践创新研究员。K. J. Bozic，美国德克萨斯大学奥斯汀分校戴尔医学院外科与围手术期护理系主任，美国德克萨斯大学奥斯汀分校戴尔医学院外科与围手术期护理系主任
{"title":"Value-based Healthcare: Improving Outcomes through Patient Activation and Risk Factor Modification.","authors":"Aaron Alokozai, P. Jayakumar, K. Bozic","doi":"10.1097/CORR.0000000000000985","DOIUrl":"https://doi.org/10.1097/CORR.0000000000000985","url":null,"abstract":"As orthopaedic surgery shifts toward value-based payment and delivery models [12], clinicians and payers alike are prioritizing efforts to identify patients at risk of poor clinical and patient-reported outcomes following an orthopaedic procedure. What if there was a measurable parameter thatwe could use to help patients improve their ownhealth, inexpensively, and with little risk? Such a parameter exists—although surgeons likely do not know about it. That parameter is called patient activation, which is a patients’ level of engagement in their own health. In our view, the more engaged a patient is, the more “activated” they are in taking interest in and managing their health, as well as interacting with their surrounding health ecosystem. We believe this concept is especially relevant in the context of patient risk factors surrounding orthopaedic surgery. While identifying and ameliorating modifiable risk factors (BMI, high A1C, and smoking cessation) early along the care continuum can predictably improve patient-reported and clinical outcomes following surgery [5], the role of patient activation as a modifiable risk factor has not been definitively proven. Validated patient-reported survey instruments for measuring activation include the Patient Activation Measure (PAM-13/PAM-10) and the Effective Consumer Scale (EC-17) [7, 10]. Survey instruments like PAM specifically assesses activation and the personal and psychological competencies (knowledge, skills, confidence) required to manage one’s health. The EC-17 scale is designed to measure an individual’s skills, behaviors, and effectiveness in dealing with their condition andmaking decisions to effectively manage their health. Intuitively, the propensity to engage in adaptive health behaviors demands a level of self-efficacy, which can be measured using tools such as the validated Pain Self Efficacy Questionnaire [11]. These measures have been developed mostly for chronic conditions involving non-musculoskeletal populations. Not surprisingly, many orthopaedic surgeons are unaware of the concept of patient activation, let alone the existence of these measures. Still, there is a growing body of work in orthopaedics, particularly in upper extremity, spine, and total joint arthroplasty evaluating the impact of patient activation on clinical and patientreported outcomes [5, 13, 14]. These studies found greater decreases in pain and disability, as well as improved adherence with physical therapy in patients who were more activated. A note from the Editor-in-Chief: We are pleased to present to readers of Clinical Orthopaedics and Related Research the latest Value-based Healthcare column (formerly Orthopaedic Healthcare Worldwide). Valuebased Healthcare explores strategies to enhance the value of musculoskeletal care by improving health outcomes and reducing the overall cost of care delivery. We welcome reader feedback on all of our columns and articles; please send your comments to eic@ clinorthop.org.","PeriodicalId":10465,"journal":{"name":"Clinical Orthopaedics & Related Research","volume":"95 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76782121","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1097/CORR.0000000000000898
T. Tachibana, Masanori Fujii, Kenji Kitamura, Tetsuro Nakamura, Y. Nakashima
BACKGROUND Although variation in physiologic pelvic tilt may affect acetabular version and coverage, postural change in pelvic tilt in patients with hip dysplasia who are candidates for hip preservation surgery has not been well characterized, and its clinical importance is unknown. QUESTIONS/PURPOSES The aim of this study was to determine (1) postural changes in sagittal pelvic tilt between the supine and standing positions; (2) postural changes in the acetabular orientation and coverage of the femoral head between the supine and standing positions; and (3) patient demographic and morphologic factors associated with sagittal pelvic tilt. METHODS Between 2009 and 2016, 102 patients underwent pelvic osteotomy to treat hip dysplasia. All patients had supine and standing AP pelvic radiographs and pelvic CT images taken during their preoperative examination. Ninety-five patients with hip dysplasia (lateral center-edge angle < 20°) younger than 60 years old were included. Patients with advanced osteoarthritis, other hip disease, prior hip or spine surgery, femoral head deformity, or inadequate imaging were excluded. Sixty-five patients (64%) were eligible for participation in this retrospective study. Two board-certified orthopaedic surgeons (TT and MF) investigated sagittal pelvic tilt, spinopelvic parameters, and acetabular version and coverage using pelvic radiographs and CT images. Intra- and interobserver reliabilities, evaluated using the intraclass correlation coefficient (0.90 to 0.98, 0.93 to 0.99, and 0.87 to 0.96, respectively), were excellent. Demographic data (age, gender, and BMI) were collected by medical record review. Sagittal pelvic tilt was quantified as the angle formed by the anterior pelvic plane and a z-axis (anterior pelvic plane angle). Using a 2D-3D matching technique, we measured the change in sagittal pelvic tilt, acetabular version, and three-dimensional coverage between the supine and standing positions. We correlated sagittal pelvic tilt with demographic and CT measurement parameters using Pearson's or Spearman's correlation coefficients. RESULTS Although functional pelvic tilt varied widely among individuals, the pelvis of patients with hip dysplasia tilted posteriorly from the supine to the standing position (mean APP angle 8° ± 6° versus 2° ± 7°; mean difference -6°; 95% CI, -7° to -5°; range -17° to 4.1°; p < 0.001; paired t-test).The pelvis tilted more than 5° posteriorly from the supine to the standing position in 39 patients (60%), and the change was greater than 10° in 12 (18%). In the latter subgroup of patients, the mean acetabular anteversion angle increased (22° ± 5° versus 27° ±5°; mean difference 5°; 95% CI, 4°-6°; p < 0.001) and the mean anterosuperior acetabular sector angle notably deceased from the supine to the standing position (91° ± 11° versus 77° ± 14°; mean difference -14°; 95% CI, -17° to -11°; p < 0.001; paired t-test). Postural change in pelvic tilt was not associated with any of the stud
{"title":"Does Acetabular Coverage Vary Between the Supine and Standing Positions in Patients with Hip Dysplasia?","authors":"T. Tachibana, Masanori Fujii, Kenji Kitamura, Tetsuro Nakamura, Y. Nakashima","doi":"10.1097/CORR.0000000000000898","DOIUrl":"https://doi.org/10.1097/CORR.0000000000000898","url":null,"abstract":"BACKGROUND\u0000Although variation in physiologic pelvic tilt may affect acetabular version and coverage, postural change in pelvic tilt in patients with hip dysplasia who are candidates for hip preservation surgery has not been well characterized, and its clinical importance is unknown.\u0000\u0000\u0000QUESTIONS/PURPOSES\u0000The aim of this study was to determine (1) postural changes in sagittal pelvic tilt between the supine and standing positions; (2) postural changes in the acetabular orientation and coverage of the femoral head between the supine and standing positions; and (3) patient demographic and morphologic factors associated with sagittal pelvic tilt.\u0000\u0000\u0000METHODS\u0000Between 2009 and 2016, 102 patients underwent pelvic osteotomy to treat hip dysplasia. All patients had supine and standing AP pelvic radiographs and pelvic CT images taken during their preoperative examination. Ninety-five patients with hip dysplasia (lateral center-edge angle < 20°) younger than 60 years old were included. Patients with advanced osteoarthritis, other hip disease, prior hip or spine surgery, femoral head deformity, or inadequate imaging were excluded. Sixty-five patients (64%) were eligible for participation in this retrospective study. Two board-certified orthopaedic surgeons (TT and MF) investigated sagittal pelvic tilt, spinopelvic parameters, and acetabular version and coverage using pelvic radiographs and CT images. Intra- and interobserver reliabilities, evaluated using the intraclass correlation coefficient (0.90 to 0.98, 0.93 to 0.99, and 0.87 to 0.96, respectively), were excellent. Demographic data (age, gender, and BMI) were collected by medical record review. Sagittal pelvic tilt was quantified as the angle formed by the anterior pelvic plane and a z-axis (anterior pelvic plane angle). Using a 2D-3D matching technique, we measured the change in sagittal pelvic tilt, acetabular version, and three-dimensional coverage between the supine and standing positions. We correlated sagittal pelvic tilt with demographic and CT measurement parameters using Pearson's or Spearman's correlation coefficients.\u0000\u0000\u0000RESULTS\u0000Although functional pelvic tilt varied widely among individuals, the pelvis of patients with hip dysplasia tilted posteriorly from the supine to the standing position (mean APP angle 8° ± 6° versus 2° ± 7°; mean difference -6°; 95% CI, -7° to -5°; range -17° to 4.1°; p < 0.001; paired t-test).The pelvis tilted more than 5° posteriorly from the supine to the standing position in 39 patients (60%), and the change was greater than 10° in 12 (18%). In the latter subgroup of patients, the mean acetabular anteversion angle increased (22° ± 5° versus 27° ±5°; mean difference 5°; 95% CI, 4°-6°; p < 0.001) and the mean anterosuperior acetabular sector angle notably deceased from the supine to the standing position (91° ± 11° versus 77° ± 14°; mean difference -14°; 95% CI, -17° to -11°; p < 0.001; paired t-test). Postural change in pelvic tilt was not associated with any of the stud","PeriodicalId":10465,"journal":{"name":"Clinical Orthopaedics & Related Research","volume":"104 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75518519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-11-01DOI: 10.1097/CORR.0000000000000973
T. Wuest
In a retrospective study of various national databases, Dandu and colleagues [2] report a number of key findings and provide some interesting observations on how the Electronic Health Record (EHR) impacts various aspects of an orthopaedic practice. They document support of some widely held assumptions, including that Meaningful Use payments were a potent stimulus for adoption of EHRs. However, these bonus payments were not sufficient to assure neither universal nor uniform adoption, and there remains a large percentage (nearly 50% in US orthopaedic practices) that have yet to fully embrace their implementation. Also, despite the purported benefits of more thorough and accurate coding and enhancement of documentation, there was little effect on productivity, billing practices, and surgical volumes. This is an important first step in trying to unravel the cavalcade of potential consequences, both intended and unintended, of the near-ubiquitous use of EHRs in clinical practice. As part of the American Recovery and Reinvestment Act (ARRA), the Health Information Technology for Economic and Clinical Health generously incentivized EHR adoption, and the authors of the current study demonstrate that the “carrot” was more effective than the “stick” in increasing EHR utilization. That is, the Meaningful Use payments in the early implementation phase of the ARRA were largely successful, and the latter penalty phase has been much less impactful. In addition, the economic realities of an orthopaedic practice can make the decision to move ahead with adoption both complicated and difficult. On one hand, the gross practice income may facilitate adoption, capital investment, and systems purchasing that would otherwise be prohibitive for smaller primary care offices or less wellcompensated practitioners and groups. On the other hand, if the Meaningful Use payments are merely “a rounding error” with respect to total practice income, the investment may be seen as a waste of time, money, and resources. Clearly, this presents an interesting dilemma in highly compensated specialties like orthopaedic surgery, especially if no perceived benefit to the patient, the practice, or practitioner can be identified [7]. And, as Dandu and colleagues [2] show, only about half of the practicing orthopaedic surgeons in the United States have adopted meaningful use implementation standards.
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Pub Date : 2019-11-01DOI: 10.1097/CORR.0000000000000975
I. Azboy, J. Parvizi
{"title":"Reply to the Letter to the Editor: Bilateral Femoroacetabular Impingement: What is the Fate of the Asymptomatic Hip?","authors":"I. Azboy, J. Parvizi","doi":"10.1097/CORR.0000000000000975","DOIUrl":"https://doi.org/10.1097/CORR.0000000000000975","url":null,"abstract":"","PeriodicalId":10465,"journal":{"name":"Clinical Orthopaedics & Related Research","volume":"37 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87189822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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