Using machine learning methods to predict nonhome discharge after elective total shoulder arthroplasty

Lopez, Cesar D.; Constant, Michael; Anderson, Matthew J.; Confino, Jamie; Heffernan, John T.; Jobin, Charles M.

doi:10.1016/j.jseint.2021.02.011

Cited by 26 publications

(20 citation statements)

References 39 publications

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“…Predicting Nonhome Discharges ML algorithms may also be used to predict nonhome discharges. Predicting nonhome discharges can potentially decrease the postoperative length of stay at the hospital, thus reducing the risk of complications and health care costs 46 .…”

Section: Predicting Costsmentioning

confidence: 99%

“…Predicting Adverse Outcomes, Cost, and Nonhome Discharges After Shoulder Arthroplasty Predicting Complications ML has been used to predict the postoperative complications that may arise subsequent to TSA procedures. Predicting these complications can allow for improved patient selection, risk stratification, and preoperative planning 46 .…”

Section: Predictions Using Smaller Inputsmentioning

confidence: 99%

“…Lopez et al examined the usage of ML methods to predict nonhome discharges after elective TSA 46 . Andrews et al, as cited by Lopez et al, found that patients with longer hospital stays were more likely to face postoperative complications 52 .…”

Section: Predicting Adverse Outcomes Cost and Nonhome Discharges Afte...mentioning

confidence: 99%

“…The use of large databases for the studies discussed also serve as a limitation because of their lack of specificity for variables that may be relevant to shoulder arthroplasty 49 . Further studies must be conducted with different data sets to ascertain the external validity of the ML models discussed 46 .…”

Section: Predicting Nonhome Dischargesmentioning

confidence: 99%

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Modern Applications of Machine Learning in Shoulder Arthroplasty

Patel,

Stevens,

Mallory

et al. 2023

JBJS Reviews

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» There is increased integration of machine learning (ML) to aid clinical decision-making in orthopaedic surgery.» ML has the ability to predict both clinical outcomes such as range of motion and complications in total shoulder arthroplasty patients.» An increased area of focus is the ability for ML to identify implants to aid in revision surgery planning.» In this article, we review the current applications of ML in shoulder arthroplasty and discuss future areas where it may enhance orthopaedic practice.

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Section: Predicting Costsmentioning

confidence: 99%

Section: Predictions Using Smaller Inputsmentioning

confidence: 99%

Section: Predicting Adverse Outcomes Cost and Nonhome Discharges Afte...mentioning

confidence: 99%

Section: Predicting Nonhome Dischargesmentioning

confidence: 99%

See 2 more Smart Citations

Modern Applications of Machine Learning in Shoulder Arthroplasty

Patel,

Stevens,

Mallory

et al. 2023

JBJS Reviews

View full text Add to dashboard Cite

show abstract

“… 4 , 7 , 21 , 22 , 25 , 29 , 32 In one study, using a set of 21,544 elective total shoulder arthroplasty (TSA) cases, AI models were developed and performed well in predicting nonhome discharge and the occurrence of 1 or more postoperative complications following elective TSA. 25 Similarly, AI models were developed and performed well in predicting patient satisfaction two years after primary anatomic and reverse TSA patients. 32 These and other related investigations into the applications of AI in shoulder surgery have stirred much discussion.…”

mentioning

confidence: 99%

Research on artificial intelligence in shoulder and elbow surgery is increasing

Gupta¹,

Marigi²,

Sánchez-Sotelo³

2023

JSES International

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Orthopaedic surgeons display a positive outlook towards artificial intelligence: A survey among members of the AGA Society for Arthroscopy and Joint Surgery

Rupp,

Moser,

Hess

et al. 2024

J. exp. orthop.

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PurposeThe purpose of this study was to evaluate the perspective of orthopaedic surgeons on the impact of artificial intelligence (AI) and to evaluate the influence of experience, workplace setting and familiarity with digital solutions on views on AI.MethodsOrthopaedic surgeons of the AGA Society for Arthroscopy and Joint Surgery were invited to participate in an online, cross‐sectional survey designed to gather information on professional background, subjective AI knowledge, opinion on the future impact of AI, openness towards different applications of AI, and perceived advantages and disadvantages of AI. Subgroup analyses were performed to examine the influence of experience, workplace setting and openness towards digital solutions on perspectives towards AI.ResultsOverall, 360 orthopaedic surgeons participated. The majority indicated average (43.6%) or rudimentary (38.1%) AI knowledge. Most (54.5%) expected AI to substantially influence orthopaedics within 5–10 years, predominantly as a complementary tool (91.1%). Preoperative planning (83.8%) was identified as the most likely clinical use case. A lack of consensus was observed regarding acceptable error levels. Time savings in preoperative planning (62.5%) and improved documentation (81%) were identified as notable advantages while declining skills of the next generation (64.5%) were rated as the most substantial drawback. There were significant differences in subjective AI knowledge depending on participants' experience (p = 0.021) and familiarity with digital solutions (p < 0.001), acceptable error levels depending on workplace setting (p = 0.004), and prediction of AI impact depending on familiarity with digital solutions (p < 0.001).ConclusionThe majority of orthopaedic surgeons in this survey anticipated a notable positive impact of AI on their field, primarily as an assistive technology. A lack of consensus on acceptable error levels of AI and concerns about declining skills among future surgeons were observed.Level of EvidenceLevel IV, cross‐sectional study.

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Using machine learning methods to predict nonhome discharge after elective total shoulder arthroplasty

Cited by 26 publications

References 39 publications

Modern Applications of Machine Learning in Shoulder Arthroplasty

Modern Applications of Machine Learning in Shoulder Arthroplasty

Research on artificial intelligence in shoulder and elbow surgery is increasing

Orthopaedic surgeons display a positive outlook towards artificial intelligence: A survey among members of the AGA Society for Arthroscopy and Joint Surgery

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