1
|
Fu SH, Yu PY, Li CY, Hung CC, Lee CC, Chen HY, Tai TW, Hwang JS, Yang RS, Chiang H, Lin SY, Wu CH, Liao LC, Chuang CJ, Wu CY, Chang CY, Lee MT, Chen CH, Wang CY. Diagnostic accuracy of algorithms to define incident and second hip fractures: A Taiwan validation study. J Formos Med Assoc 2023; 122 Suppl 1:S82-S91. [PMID: 37353444 DOI: 10.1016/j.jfma.2023.05.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/31/2023] [Accepted: 05/29/2023] [Indexed: 06/25/2023] Open
Abstract
BACKGROUND Previous epidemiological researchers have used various algorithms to identify a second hip fracture; however, there has been no validation of these algorithms to date. This study aimed to verify existing algorithms for identifying second hip fracture under the International Classification of Diseases diagnostic coding systems. Furthermore, we examined the validity of two newly proposed algorithms that integrated the concept of periprosthetic fractures and laterality of the ICD-10 coding system. METHODS Claims data of patients hospitalized for hip fracture from National Taiwan University Hospitals between 2007 and 2020 were retrieved. Hip fracture was confirmed by 2 orthopaedic surgeons with medical records and imaging data as gold standards. The validity of 9 existing and 2 newly proposed algorithms for identifying second hip fracture was evaluated. RESULTS The positive predictive value (PPV) range between 84% and 90% in existing algorithms for identifying second hip fractures. Noteworthy, the longer time interval for discrimination resulted in slightly increased PPV (from 87% to 90%), while decreased sensitivity noticeably (from 87% to 72%). When considering the information about periprosthetic fracture, the PPV increased to 91% without diminished sensitivity. The PPV of the newly proposed ICD-10-specific algorithm was 100%. CONCLUSION Algorithms integrated clinical insights of periprosthetic fractures and laterality concept of ICD-10 coding system provided satisfactory validity and help precisely define second hip fracture in future database research.
Collapse
Affiliation(s)
- Shau-Huai Fu
- Department of Orthopedics, National Taiwan University Hospital Yunlin Branch, Yunlin County, Taiwan; Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Ping-Ying Yu
- Department of General Internal Medicine, Mackay Memorial Hospital, Taipei, Taiwan
| | - Chung-Yi Li
- Department of Public Health, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Public Health, College of Public Health, China Medical University, Taichung, Taiwan; Department of Healthcare Administration, College of Medical and Health Science, Asia University, Taichung, Taiwan
| | - Chih-Chien Hung
- Department of Orthopedics, National Taiwan University Hospital Yunlin Branch, Yunlin County, Taiwan
| | - Chia-Che Lee
- Department of Orthopedic Surgery, National Taiwan University Hospital, Taipei, Taiwan; Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan
| | - Hsuan-Yu Chen
- Department of Orthopedic Surgery, National Taiwan University Hospital, Taipei, Taiwan
| | - Ta-Wei Tai
- Department of Orthopedics, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Skeleton Materials and Biocompatibility Core Lab, Research Center of Clinical Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Jawl-Shan Hwang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Chang Gung Memorial Hospital, Chang Gung University, Taoyuan, Taiwan
| | - Rong-Sen Yang
- Department of Orthopedics, National Taiwan University Hospital, Taipei, Taiwan
| | - Hongsen Chiang
- Department of Orthopedics, National Taiwan University Hospital, Taipei, Taiwan
| | - Sung-Yen Lin
- Department of Orthopedics, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Chih-Hsing Wu
- Institute of Gerontology, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Family Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Department of Family Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Ling-Chiao Liao
- Department of Pharmacy, National Taiwan University Hospital Yunlin Branch, Yunlin County, Taiwan
| | - Chin-Ju Chuang
- Department of Pharmacy, National Taiwan University Hospital Yunlin Branch, Yunlin County, Taiwan
| | - Chiu-Yi Wu
- Department of Pharmacy, National Taiwan University Hospital Yunlin Branch, Yunlin County, Taiwan
| | - Cheng-Ying Chang
- Department of Pharmacy, National Taiwan University Hospital Yunlin Branch, Yunlin County, Taiwan
| | - Ming-Tsung Lee
- National Center for Geriatrics and Welfare Research, National Health Research Institutes, Yunlin County, Taiwan; Department of Nursing, Hungkuang University, Taichung, Taiwan
| | - Chung-Hwan Chen
- Department of Orthopedics, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan; Orthopaedic Research Center and Department of Orthopedics, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan; Regenerative Medicine and Cell Therapy Research Center, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Orthopedics, Kaohsiung Municipal Ta-Tung Hospital and Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.
| | - Chen-Yu Wang
- Department of Pharmacy, National Taiwan University Hospital Yunlin Branch, Yunlin County, Taiwan; National Center for Geriatrics and Welfare Research, National Health Research Institutes, Yunlin County, Taiwan; School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan; Graduate Institute of Clinical Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan.
| |
Collapse
|
2
|
Wang JC, Piple AS, Chen XT, Bedard NA, Callaghan JJ, Berry DJ, Christ AB, Heckmann ND. The Rise of Medicare Advantage: Effects on Total Joint Arthroplasty Patient Care and Research. J Bone Joint Surg Am 2022; 104:2145-2152. [PMID: 36367757 DOI: 10.2106/jbjs.22.00254] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
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.
Collapse
Affiliation(s)
| | - Amit S Piple
- Keck School of Medicine of USC, Los Angeles, California
| | | | | | | | | | | | | |
Collapse
|
3
|
Bedard NA, Katz JN, Losina E, Opare-Addo MB, Kopp PT. Administrative Data Use in National Registry Efforts: Blessing or Curse? J Bone Joint Surg Am 2022; 104:39-46. [PMID: 36260043 DOI: 10.2106/jbjs.22.00565] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
"Big data" refers to a growing field of large database research. Administrative data, a subset of big data, includes information from insurance claims, electronic medical records, and registries that can be useful for investigating novel research questions. While its use provides salient advantages, potential researchers relying on big data would benefit from knowing about how these databases are coded, common errors they may encounter, and how to best use large data to address various research questions. In the first section of this paper, Dr. Nicholas A. Bedard addresses the four major pitfalls to avoid with diagnosis and procedure codes in administrative data. In the next section, Dr. Jeffrey N. Katz et al. focus on the strengths and limitations of administrative data, suggesting methods to mitigate these limitations. Lastly, Dr. Elena Losina et al. review the uses and misuses of large databases for cost-effectiveness research, detailing methods for careful economic evaluations.
Collapse
Affiliation(s)
| | - Jeffrey N Katz
- Orthopaedic and Arthritis Center for Outcomes Research, Department of Orthopedic Surgery, Brigham and Women's Hospital, Boston, Massachusetts.,Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Boston, Massachusetts.,Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts.,Department of Orthopaedic Surgery, Harvard Medical School, Boston, Massachusetts
| | - Elena Losina
- Orthopaedic and Arthritis Center for Outcomes Research, Department of Orthopedic Surgery, Brigham and Women's Hospital, Boston, Massachusetts.,Department of Orthopaedic Surgery, Harvard Medical School, Boston, Massachusetts.,Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Maame B Opare-Addo
- Orthopaedic and Arthritis Center for Outcomes Research, Department of Orthopedic Surgery, Brigham and Women's Hospital, Boston, Massachusetts
| | - Paul T Kopp
- Orthopaedic and Arthritis Center for Outcomes Research, Department of Orthopedic Surgery, Brigham and Women's Hospital, Boston, Massachusetts
| |
Collapse
|
4
|
Callaghan JJ, DeMik DE, Carender CN, Bedard NA. Analysis of New Orthopaedic Technologies in Large Database Research. J Bone Joint Surg Am 2022; 104:47-50. [PMID: 36260044 DOI: 10.2106/jbjs.22.00566] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Improvements in orthopaedic surgery go hand in hand with technological advances. The present article outlines the historical and current uses of large databases and registries for the evaluation of new orthopaedic technologies, providing insights for future utilization, with robotic-assisted surgery as the example technology.
Collapse
Affiliation(s)
- John J Callaghan
- Editor in Chief Emeritus, Journal of Arthroplasty.,Department of Orthopedics and Rehabilitation, University of Iowa, Iowa City, Iowa
| | - David E DeMik
- Department of Orthopedics and Rehabilitation, University of Iowa, Iowa City, Iowa
| | | | | |
Collapse
|
5
|
Chen X, Li Z, Zhang X, Yan J, Ding L, Song Y, Huo Y, Chan MTV, Wu WKK, Lin J. A new robotically assisted system for total knee arthroplasty: A sheep model study. Int J Med Robot 2021; 17:e2264. [PMID: 33855810 DOI: 10.1002/rcs.2264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Revised: 04/09/2021] [Accepted: 04/09/2021] [Indexed: 11/06/2022]
Abstract
BACKGROUND We investigated the accuracy and safety of a new HURWA robotic-assisted total knee arthroplasty (TKA) system in a sheep model. METHODS Ten male small-tailed Han sheep were used in this study. Sheep were imaged by computed tomography scan before and after bone resection and the cutting errors between actual bone preparation and preoperative planning of the femur and tibia in three dimensions were measured. RESULTS The overall accuracies after surgery compared with that from preoperative surgical planning of the left and right femurs were 1.93 ± 1.02° and 1.93 ± 1.23°, respectively. Additionally, similarly high overall accuracies for the left and right tibia of 1.26 ± 1.04 and 1.68 ± 0.92°, respectively, were obtained. The gap distances of the distal cut, anterior chamfer, anterior cut, posterior chamfer and posterior cut on the medial side were 0.47 ± 0.35 mm, 0.41 ± 0.37 mm, 0.12 ± 0.26 mm, 0.41 ± 0.44 mm and 0.12 ± 0.23 mm, respectively. No intraoperative complications, such as intraoperative fracture, massive bleeding or death, occurred. CONCLUSION This new HURWA robotic-assisted TKA system is an accurate and safe tool for TKA surgery based on the sheep model.
Collapse
Affiliation(s)
- Xin Chen
- Department of Orthopaedic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zheng Li
- Department of Orthopaedic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaofeng Zhang
- BEIJING HURWA-ROBOT Medical Technology Co.Ltd, Beijing, China
| | - Jun Yan
- BEIJING HURWA-ROBOT Medical Technology Co.Ltd, Beijing, China
| | - Lele Ding
- BEIJING HURWA-ROBOT Medical Technology Co.Ltd, Beijing, China
| | - Youdong Song
- BEIJING HURWA-ROBOT Medical Technology Co.Ltd, Beijing, China
| | - Yujia Huo
- BEIJING HURWA-ROBOT Medical Technology Co.Ltd, Beijing, China
| | - Matthew T V Chan
- Department of Anaesthesia and Intensive Care and Peter Hung Pain Research Institute, The Chinese University of Hong Kong, Hong Kong, China
| | - William K K Wu
- Department of Anaesthesia and Intensive Care and Peter Hung Pain Research Institute, The Chinese University of Hong Kong, Hong Kong, China.,State Key Laboratory of Digestive Diseases, Centre for Gut Microbiota Research, Institute of Digestive Diseases and LKS Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
| | - Jin Lin
- Department of Orthopaedic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| |
Collapse
|