2.1 Sources of data and search strategy

Web of Science (WOS) Core Collection of Clarivate Analytics was used as it is the most commonly used scientific information source for bibliometric analysis given the detailed data accessible through the engine. A literature search utilizing the Science Citation Index Expanded and Social Science Citation index was conducted. The search terminology included “hip replacement” OR “hip arthroplasty” OR “total hip” OR “knee replacement” OR “knee arthroplasty” OR “total knee” OR “TKA” OR “THA” (All Fields) AND “National Inpatient Sample” OR “Nationwide Inpatient Sample” OR “NIS” OR “NSQIP” OR “National Surgical Quality Improvement Program” OR “Veterans Surgical Quality Improvement Program” OR “VSQIP” OR “MarketScan” OR “OptumLabs” OR “PearlDiver” OR “AJRR” OR “American Joint Replacement Registry” OR “CJRR” OR “California Joint Replacement Registry” OR “Virginia State Registry” OR “VSR” OR “MARCQI” OR “Michigan Arthroplasty Registry Collaborative Quality Initiative” OR “Veterans Health Affairs” OR “VHA” OR “Administrative Database” OR “State Inpatient Sample” OR “SIS” (Topic) AND 1982–2022 (Year Published) AND Article (Document Type). This search utilized articles as the document type and index of SCI-EXPANDED and SSCI with the time period of 1982–2022 in an attempt to minimize any omissions. The search terms were identified and selected based on published literature highlighting the key and most widely used US-based large databases.

2.2 Data extraction

Data collection was performed by two authors. After screening of the database, all information regarding the articles and pertinent to the required subsequent analysis were collected and included: publication year, title, authors, institution, countries, journal published, abstracts, references, citations, and impact factor.

2.3 Bibliometric analysis

Bibliometric indicators were obtained in excel format from the WOS database, and then subsequently imported for further analysis. Deficiencies in data were crosschecked with the WOS database. Information from various regions of interest were categorized by their corresponding country. Data visualization with knowledge maps of scientific production, co-authorship, co-citation, topic trend, thematic map, dual-map overlay, and thematic evolution with VOSviewer (version 1.6.19.0) (Leiden University, Leiden, Netherlands) and Bibliometrix (University of Naples Federico, Naples, Italy).

3.1 Publication data

WOS database search identified 811 articles associating with arthroplasty major databases published between the years 1995–2022. Number of citations in major database were 14185 with an average of 38.62 citations per document. Fig. 1 highlights global annual publication numbers and is notable for an increasing trend within major database with an annual growth rate of 19.62%. The largest increase in publication output was in 2016 with a difference of (34) followed by 2019 (24), 2020 (14), and 2012/2021 (13).

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Fig. 1 Global annual scientific production with the greatest increase in article production in 2016.

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3.2 Countries

Table 1 illustrates the productivity of worldwide research. While the databases of interest were US-based registries, publications demonstrated origin in 28 countries with the US as the largest contributor (89.47%). The top 10 producing countries consisted of 5 from Europe, 3 from Asia/Oceania and 2 from North America. Other countries following the United States include Canada (3.39%), China (1.61%), UK (0.87%), Germany (0.70%), and Japan (0.57%). Fig. 2 highlights that, among the included countries, United States had the greatest citations (29034) and ranked first in annual productivity.

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Fig. 2 Trends in country A) production and B) country total citations over time.

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3.3 Institutions/authors

With the use of US-based large databases for arthroplasty research, 477 institutions published at least 1 article. Fig. 3A highlights the top 5 institutions, which were all from the US with the Cleveland Clinic and Harvard University contributing the most with 64 articles each, followed by the University of Alabama Birmingham (62), Weill Cornell Medicine (58), and University of California System (55). The greatest annual production was University of Alabama Birmingham in 2019 and 2020 with 23 and 22 articles, respectively. The greatest annual production for the other top 5 institutions were Cleveland Clinic (2019, 16), Harvard University (2017, 13), Weill Cornell Medicine (2022, 15), and University of California System (2020, 13) (see Fig. 4).

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Fig. 3 A) Affliated institutions over time in Big Database article production. B) Total author contribution and C) author citations over 40 year period. D) Lotka's law diagram demonstrating the decreasing % of authors with increasing amounts of articles written.

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A total of 2266 authors contributed to arthroplasty research utilizing US-based major database. All top 10 authors in productivity were from the US as shown in Fig. 3B, with the top three authors being Mont MA from Sinai Hospital of Baltimore (63), Grauer JN from Yale University (38), and Piuzzi NS from Cleveland Clinic (31). Fig. 3C demonstrates the most cited author was Lau E (390), followed by Ong K (291), Kurtz S (253), and Mowat F (236). The most impactful authors by h-index were Mont MA (18), Grauer JN (17), Bozic KJ (15), Bohl DD (14), Callaghan JJ (14), and Memtsoudis SG (14).

3.4 Journals

A total of 118 journals published arthroplasty-specific studies utilizing major databases of interest between years 1995–2022 as shown in Fig. 4A. Among the list of journals, the journal with the greatest number of articles and highest citations was the Journal of Arthroplasty with a total of 331 articles. This was followed by the Journal of Bone and Joint Surgery and Journal of Knee Surgery with 67 and 42 articles, respectively. The greatest annual production from Journal of Arthroplasty was 2017 with 49 articles published. Co-citation analysis was also performed with a minimum of 100 citations. Among the 31 journals analyzed, the top journals were Journal of Arthroplasty (4309), Journal of Bone and Joint Surgery (2615), and Clinical Orthopaedics and Related Research (1951). The top 5 impactful journals in Fig. 4B by h-index were Journal of Arthroplasty (56), Journal of Bone and Joint Surgery (41), Clinical Orthopaedics and Related Research (19), Journal of Knee Surgery (11), and Journal of the American Academy of Orthopaedic Surgeons (9).

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Fig. 4 A) Publication output by journal over the year and B) journal impact by H index.

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3.5 Most influential articles

The globally top 10 most cited articles are shown in Fig. 5. The most influential article appeared in 2007. The biggest burst referenced was published by Kurtz et al. (5451).⁴ Following the highest burst were Bozic et al. (1114)⁵ and Kurtz SM (1108).⁶

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Fig. 5 Most influential articles with author, publication year, and journal published.

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3.6 Keywords

Fig. 6 demonstrates the co-occurrence visualization with a treemap for trends for keywords within arthroplasty research utilizing US-based big databases. Of the 1024 keywords, a total of 58 keywords occurred at least 15 times. Among those, 37 had sufficient link strength in determining occurrence clusters. Analysis demonstrates clusters as seen in Fig. 6A, with the size of the circle correlating to frequency of occurrence. Fig. 6B demonstrates the trend evolution in keywords from 1995 to 2010 to the period between 2011 and 2022. A shift in trend towards patient specific variables, value based care, post operative complication, infection, and venous thromboembolism (VTE) is highlighted. Fig. 6D demonstrates the density clusters of topics. Fig. 7 is the thematic map that outlines relevance and current development of themes within the literature. The thematic map is organized by centrality and density. Centrality is the strength of association by numerous keywords that links clusters together. Density is the development of clusters and the topic strength. The niche themes in Fig. 7 (high density, low centrality) represents individual clusters that are highly developed and focused on one theme, but do not yet play an essential role in Big Database arthroplasty research. The basic themes (low density, high centrality) are themes that are central to Big Database with cluster linking keywords, but have yet to be fully developed.

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Fig. 6 A) Network co-occurrence overlay showing keywords with a minimum of 15 for cluster determination. B) Diagram detailing the shift of thematic evolution from 1995 to 2010 to 2011–2022. C) Co-occurrence overlay demonstrating thematic keyword development by time. D) Co-occurrence overlay showing cluster by density.

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Fig. 7 Thematic map detailing themes by their development and centrality by keyword association.

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4.1 Publication production

The global scientific output showed a positive trend from 2007 to 2022 with an annual growth rate of 19.62%. The greatest absolute increase was from 2015 to 2016 with 34 articles.

4.2 Countries

The United States was the most productive country with the greatest total number of articles published, annual productivity, and total citations. This finding is not surprising given the databases of interest are US-based. The United States had 89.47% of the total articles globally and 29,034 total citations. Global collaboration mostly occurred between the United States (77.14%) and other countries, with the top 3 collaborating countries being Canada (10), United Kingdom (7), and Austria (6).

4.3 Institutions/authors

The Cleveland Clinic Foundation and Harvard University were the most relevant academic institution for conducting arthroplasty research utilizing the major US-based large databases. Mont MA was the most relevant and influential author with 63 total publications and a H index of 18. Fig. 3D represent the collective author productivity and highlighting Lotka's Law demonstrating a decreasing number of authors with increasing articles written. Fig. 8 is a three fields plot representation demonstrating the most active authors with the associated most commonly cited studies by those authors and the corresponding keywords within those studies.

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Fig. 8 Three fields plot demonstrating reference paper (CR) cited by the authoring paper (AU) using key words (DE).

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4.4 Journals

The Journal of Arthroplasty had the highest total of articles and citations. Additionally, the journal was the most influential within this topic and exhibited the highest h-index. Following Journal of Arthroplasty 331 total articles was Journal of Bone and Joint Surgery (67) and Journal of Knee Surgery (42). There was also an increasing amount of journal interest to large database research from 2009 with increasing publication numbers.

4.5 Most relevant articles

This study demonstrated the most common articles with the highest citation clusters. The identification of these articles is essential for assessing topic trends as well as future hotspots for future research.⁷ The most relevant article was “Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030,“⁴ “The epidemiology of revision total hip arthroplasty in the United States,“⁵ and “Economic burden of periprosthetic joint infection in the United States.“⁶

4.6 Keywords

The co-occurrence overlay visuals in Fig. 6A and density map in Fig. 6D highlight the clusters and the affiliated keywords. The thematic evolution in Fig. 6B demonstrates the transition from 1995 to 2010 to 2011–2022 with increasing emphasis on quality and outcome assessment. The most frequently used keywords between 2018 and 2019 was “outcomes”, “mortality”, and “care”. This corresponds with the increasing trend of peri-operative optimization towards mitigating risk factors with protocol development. The co-occurrence overlay in Fig. 6C demonstrates the clusters and the respective time period. VTE as a cluster example received more focus in 2017 with keywords including “venous thromboembolism”, “prophylaxis”, and “prevention” with node connection to “deep vein thrombosis” and “mortality” in 2018. Another cluster from the co-occurrence overlay include the topic of infection with keywords of “infection” and “comorbidities” in 2018 extending to “complications”, “periprosthetic infection”, and “revision” in 2019.

4.7 Clusters

Five clusters were identified through relevant keyword search with the cluster themes generally falling into the following categories: value-based care, patient specific variables, postoperative complications, infection, and venous thromboembolism (VTE).

4.8 Value based care

Value based care cluster included keywords of bundle payments, cost, LOS, impact, pain, and trends. The Comprehensive Care of Joint Replacement program was introduced in 2016 to incentivize reimbursement for total hip and knee arthroplasty with the goal of promoting value-oriented care.⁸ Quality and health measures including outcome indicators of postoperative complications and functional status have been increasingly used as an indicator to quantify performance and the quality of delivered care.⁹ A systematic review of health indicators by Amanatullah et al. evaluated outcome quality indicators with 34% total applicable measures identified for total joint arthroplasty compared to 20% among other specialties, indicating a space for continued development.¹⁰ Despite the notable success of the procedures, arthroplasty remains a target for improvement with the recent traction in value-based care as quality measures are consistently associated to highlight bundled reimbursements as a guide for resource allocation. Discussion regarding value-oriented care has been an evolving theme since 2011 with increasing focus on outcomes and prevention (thematic evolution) with recent trend in 2017–2019 in the co-occurrence overlay (Fig. 6) on “bundled payments”, “trends”, and “readmission”.

4.9 Patient specific variables

Patient variable cluster included keywords of BMI, comorbidity, disparities, outcomes, osteoarthritis, and race, among others. The evolution of themes after 2011 highlights a shifting focus within large database arthroplasty research towards outcomes and identifying patient-specific predictive factors. With the advent of big data, recent traction in mid 2018–2019 have been increasingly focusing on “outcomes”, “risk factors”, “comorbidity”, “body mass index”, and “predictors”. As highlighted in the aforementioned section, the transition towards value-based models elevated the interest in prevention and adequate perioperative optimization. Kort et al. identified modifiable patient specific variables including obesity, functional status, diabetes and smoking status as independent predictors for extended LOS and readmission after revision arthroplasty.¹¹ Another analysis of the NSQIP by Liodakis et al. identified preoperative anemia as the most important patient specific variable predictive of complications and prolonged inpatient admission.¹² Analysis of the Medicare database by Benito et al. showed LOS and patient specific variables as crucial risk factors in primary joint arthroplasty for hospital readmission.¹³ Large data analysis allows for the identification of patient variables that provide a target for perioperative optimization protocols aimed at minimizing postoperative complications.

4.10 Postoperative complications

Postoperative complications cluster include keywords of complications, failures, morbidity, mortality, periprosthetic joint infection, and safety. Total joint arthroplasty once required weeks of inpatient admission and targeted rehabilitation has progressed to fast-tracked outpatient procedures.¹⁴ With continued clinical pathways development, healthcare providers and all stakeholders aim to minimize postoperative complications.¹⁵ Large database studies allow for the assessment of the implication of such pathways and identify complications in the direct postoperative period. Lovecchio et al. analyzed the NSQIP Database and demonstrated no significant increase in long term hospital admission despite an increase post-discharge complications for fast-track arthroplasty.¹⁶ Another study by Sutton et al. analyzed the same database and demonstrated early discharge for total joint arthroplasty was not a risk factor for 30-day complication or readmission, but rather patient comorbidity was a significant risk factor.¹⁷ The ongoing research into postoperative complications presents as another developing cluster in arthroplasty literature with focus in the mid 2018–2019 with increasing focus on “outcome”, “revision”, “failure”, and “complications”.

4.11 Infection

The infection cluster included keywords of infection, obesity, prevalence, quality, and revision. Periprosthetic joint infection (PJI) is a catastrophic complication of total joint arthroplasty with significant morbidity and mortality to the patient. The burden of a PJI to the healthcare system is estimated at 3 to 4 times of the primary surgery, with increasing annual costs of upwards to $1.85 billion in 2030.⁶ The current gold standard for treatment is a 2 staged revision with mortalities as high as 42% necessitating an ongoing research interest in infection.¹⁸ In the current analysis, the topics of prevention and failure represent niche themes with increasing development in the thematic map (Fig. 7). Bozic et al. analyzed PJI within the Medicare database to identify specific patient risk factors as potential targets for optimization protocols.¹⁹ Large population-based studies have identified multiple risks factors, such as male sex and diabetes, to be associated with PJI,²⁰ and continuous efforts towards intervention have been assessed. The use of operating room airflow, exhaust suit, chlorhexidine preoperative wash, intravenous antibiotics, and antibiotic irrigation have all been assessed in large database studies showing minimal to no improvement in PJI rates.²¹ The co-occurrence overlay demonstrates the ongoing trend in 2019 for increasing interest in “infection”, “management”, “revision”, “risk”, and “complications”. Further studies toward infection prevention have been increasing to decrease the incidence of this catastrophic outcome.

4.12 Venous thromboembolism

VTE cluster included keywords of deep vein thrombosis (DVT), epidemiology, prevention, prophylaxis, and VTE. DVT and VTE encompass a rare, fatal, and potentially preventable condition with appropriate prophylaxis.²² With the advent of newer modalities of VTE prophylaxis, the cluster of venous thromboembolism is an emerging theme with increasing development, as highlighted in the thematic map (Fig. 7). The interest in prevention and prophylaxis demonstrates a cluster burst in 2017–2018 with increasing literature on the topic. Shahi et al. analyzed the NSI and reported that DVT has been decreasing with unchanged pulmonary embolus (PE) incidence, which can be attributed to recent prophylaxis recommendations.²³ Sloan et al. assess the NSQIP database regarding VTE risk factors and identified obesity as a risk factor of 3.4 compared to non-obese individuals.²⁴ Increasing studies identifying risk factors highlight the intricacies of DVT and with no pharmacologic agent identified to be superior,²⁵ this cluster represent an emerging topic.