Adoption of New Medical Technologies: The Case of Customized Individually Made Knee Implants

A pilot study on preferences from surgeons to deal with an innovative customized and connected knee prosthesis - A discret choice experiment

Background

To address the increasing global demand for Total Knee Arthroplasty and reduce the need for revisions, several technologies combining 3D planning and artificial intelligence have emerged. These innovations aim to enhance customization, improve component positioning accuracy and precision. The integration of these advancements paves the way for the development of personalized and connected knee implant.

Questions/purposes

These groundbreaking advancements may necessitate changes in surgical practices. Hence, it is important to comprehend surgeons' intentions in integrating these technologies into their routine procedures. Our study aims to assess how surgeons' preferences will affect the acceptability of using this new implant and associated technologies within the entire care chain.

Methods

We employed a Discrete Choice Experiment, a predictive technique mirroring real-world healthcare decisions, to assess surgeons' trade-off evaluations and preferences.

Results

A total of 90 experienced surgeons, performing a significant number of procedures annually (mostly over 51) answered. Analysis indicates an affinity for technology but limited interest in integrating digital advancements like preoperative software and robotics. However, they are receptive to practice improvements and considering the adoption of future sensors.

Conclusions

In conclusion, surgeons prefer customized prostheses via augmented reality, accepting extra cost. Embedded sensor technology is deemed premature by them.

Planning, implementing and governing systems-based co-creation: the DISCOVER framework

BACKGROUND

Increasingly, public health faces challenges requiring complex, multifaceted and multi-sectoral responses. This calls for systems-based approaches that facilitate the kind of collective and collaborative thinking and working required to address complexity. While the literature on systems thinking, system dynamics and the associated methodologies is extensive, there remains little clear guidance on how to plan, govern and implement participatory systems approaches within a co-creation process.

METHODS

We used a three-step process to develop DISCOVER, a framework for implementing, and governing systems-based co-creation: Stage 1: We conducted a literature analysis of key texts to identify well-documented methods and phases for co-creation using a systems approach, as well as areas where gaps existed. Stage 2: We looked for the most appropriate methods and approaches to fill the gaps in the knowledge production chain. Stage 3: We developed the framework, identifying how the different tools and approaches fit together end-to-end, from sampling and recruiting participants all the way through to responding with an action plan.

RESULTS

We devised DISCOVER to help guide researchers and stakeholders to collectively respond to complex social, health and wider problems. DISCOVER is a strategic research planning and governance framework that provides an actionable, systematic way to conceptualise complex problems and move from evidence to action, using systems approaches and co-creation. In this article, we introduce the eight-step framework and provide an illustrative case study showcasing its potential. The framework integrates complementary approaches and methods from social network analysis, systems thinking and co-creation literature. The eight steps are followed sequentially but can overlap.

CONCLUSIONS

DISCOVER increases rigour and transparency in system approaches to tackling complex issues going from planning to action. It is being piloted in environmental health research but may be suitable to address other complex challenges and could be incorporated into research proposals and protocols for future projects.

Three-Dimensional Printed Knee Implants: Insights into Surgeons' Points of View

Three-dimensional printing is a technology that has been developed and applied in several medical specialties, especially orthopedic surgery. Knee arthroplasty is the most commonly performed procedure. To fit the morphology of each knee, surgeons can choose between different standardized off-the-shelf implant sizes or opt for customized 3D-printed implants. However, routine adoption of the latter has been slow and faces several barriers. Existing studies focus on technical improvements or case studies and do not directly address the surgeon's perspective. Our study invited surgeons to express themselves freely and answer the question "What do you think about the manufacture of a prosthesis by 3D printing?". The questionnaire was completed by 90 surgeons. On average, they had more than 10 years of experience (52, 57.8% ± 10.2%), worked in public hospitals (54, 60% ± 10.1%), and performed between 0 and 100 prostheses per year (60, 66.7% ± 9.7%). They also reported not using planning software (47, 52.2% ± 9.7%), navigation systems, or robots (62, 68.9% ± 9.6%). Regarding the use of technological innovation, they agreed on the extra surgical time needed (67, 74.4% ± 9.0%). The answers obtained were classified according to two criteria: (i) opinions, and (ii) motivations. Among the respondents, 51 (70% ± 9.5%) had positive and 22 (30% ± 9.5%) had negative opinions about 3D printing. The motivations were distributed among seven categories (surgery, materials, costs, logistics, time, customization, and regulatory) and mainly related to "pre-surgery" and "post-surgery" concerns. Finally, the results showed that the use of navigation systems or robots may be associated with a more positive view of 3DP. The purpose of our study was to examine knee surgeons' perceptions of 3DP at a time of significant expansion of this technology. Our study showed that there was no opposition to its implementation, although some surgeons indicated that they were waiting for validated results. They also questioned the entire supply chain, including hospitals, insurance companies, and manufacturers. Although there was no opposition to its implementation, 3D printing is at a crucial point in its development and its full adoption will require advances in all areas of joint replacement.

Decision-analytic modeling for early health technology assessment of medical devices - a scoping review

Objective

The goal of this review was to identify decision-analytic modeling studies in early health technology assessments (HTA) of high-risk medical devices, published over the last three years, and to provide a systematic overview of model purposes and characteristics. Additionally, the aim was to describe recent developments in modeling techniques.

Methods

For this scoping review, we performed a systematic literature search in PubMed and Embase including studies published in English or German. The search code consisted of terms describing early health technology assessment and terms for decision-analytic models. In abstract and full-text screening, studies were excluded that were not modeling studies for a high-risk medical device or an in-vitro diagnostic test. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram was used to report on the search and exclusion of studies. For all included studies, study purpose, framework and model characteristics were extracted and reported in systematic evidence tables and a narrative summary.

Results

Out of 206 identified studies, 19 studies were included in the review. Studies were either conducted for hypothetical devices or for existing devices after they were already available on the market. No study extrapolated technical data from early development stages to estimate potential value of devices in development. All studies except one included cost as an outcome. Two studies were budget impact analyses. Most studies aimed at adoption and reimbursement decisions. The majority of studies were on in-vitro diagnostic tests for personalized and targeted medicine. A timed automata model, to our knowledge a model type new to HTA, was tested by one study. It describes the agents in a clinical pathway in separate models and, by allowing for interaction between the models, can reflect complex individual clinical pathways and dynamic system interactions. Not all sources of uncertainty for in-vitro tests were explicitly modeled. Elicitation of expert knowledge and judgement was used for substitution of missing empirical data. Analysis of uncertainty was the most valuable strength of decision-analytic models in early HTA, but no model applied sensitivity analysis to optimize the test positivity cutoff with regard to the benefit-harm balance or cost-effectiveness. Value-of-information analysis was rarely performed. No information was found on the use of causal inference methods for estimation of effect parameters from observational data.

Conclusion

Our review provides an overview of the purposes and model characteristics of nineteen recent early evaluation studies on medical devices. The review shows the growing importance of personalized interventions and confirms previously published recommendations for careful modeling of uncertainties surrounding diagnostic devices and for increased use of value-of-information analysis. Timed automata may be a model type worth exploring further in HTA. In addition, we recommend to extend the application of sensitivity analysis to optimize positivity criteria for in-vitro tests with regard to benefit-harm or cost-effectiveness. We emphasize the importance of causal inference methods when estimating effect parameters from observational data.

Custom total knee: understanding the indication and process

Patient-specific total knee arthroplasty (TKA) is a copy of the bony knee morphology based on a pre-op computer tomography (CT). The images are segmented in 3D and software is utilized through a proprietary process to generate individual total knee implants to recreate the articulating surfaces. The distal condylar valgus angle of the prosthesis is matched anatomically to the distal femur and reversely matched on the tibia with a thicker lateral insert. The implant, a set of patient-specific jigs (PSJ), which are 3D printed in nylon, and a detailed surgical plan are sent to the hospital in one box. The system is available with one solid or two separated medial and lateral PE inserts. There is a cruciate retaining (CR) and posterior stabilized (PS) version available, including various insert thicknesses. The system allows the addition of two different cemented stem extensions if needed at the time of surgery.

No significant difference in early clinical outcomes of custom versus off-the-shelf total knee arthroplasty: a systematic review and meta-analysis

PURPOSE

The purpose of this systematic review and meta-analysis was to collect, synthesise and critically appraise findings of clinical studies that report outcomes of custom total knee arthroplasty (TKA). The hypothesis was that, compared to off-the-shelf (OTS) TKA, custom TKA would yield better surgical, clinical and radiographic outcomes.

METHODS

This systematic review and meta-analysis was performed in accordance with the guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). On 8 February 2021, two authors independently searched and screened articles using MEDLINE®, Embase® and the Cochrane Library without restriction on date of publication. Findings from eligible articles were narratively synthesised and tabulated, and when ≥ 3 comparative studies reported the same outcome, results were pooled and summarised in forest plots. Quality assessments of the studies were done according to the guidelines of the Joanna Briggs Institute (JBI) Checklists.

RESULTS

A total of 15 articles were eligible for data extraction, of which 9 were case-control studies reporting on 929 custom versus 998 OTS TKA, 5 were case series reporting on results of 587 custom TKA, and 1 was a cross-sectional study reporting on results of 44 custom versus 132 OTS TKA. Five studies that compared early revision rates found the overall effect in favour of OTS TKA (odds ratio (OR), 0.4; p = n.s.) but the result did not reach statistical significance. Four studies found no statistically significant difference in KSS knee (standardised mean difference (SMD), - 0.10; p = n.s.) and function (SMD, 0.03; p = n.s.), and five studies found no statistically significant difference in range of motion (SMD, 0.02; p = n.s.). One study that compared bone-implant fit between custom and three OTS tibial components found no overhang but revealed under-coverage of up to 18% in knees with custom tibial baseplates.

CONCLUSION

Custom TKA demonstrated no significant benefits compared to OTS TKA in terms of pooled clinical outcomes, but had considerably higher early revision rates. The findings of the present systematic review and meta-analysis suggest the need for studies with better comparable groups and standardisation of reporting outcomes amongst studies, that could increase the quality of evidence and enable pooling of results in future meta-analyses.

LEVEL OF EVIDENCE

Level IV.

Clinical and Radiological Outcomes after Knee Arthroplasty with Patient-Specific versus Off-the-Shelf Knee Implants: A Systematic Review

Customised, patient-specific implants (PSI) manufactured based on computed tomography data are intended to improve the clinical outcome by restoring more natural knee kinematics as well as providing a better fit and a more precise positioning. The aim of this systematic review is to investigate the effect of these PSI on the clinical and radiological outcome compared to standard, off-the-shelf (OTS) implants. Thirteen comparative studies including a total of 2127 knee implants were identified. No significant differences in clinical outcome assessed with the range of motion, the Knee Society Score (KSS), and the Forgotten Joint Score (FJS-12) were found between PSI and OTS implants. PSI showed fewer outliers from the neutral limb axis and a better implant fit and positioning. Whether these radiological differences lead to long-term advantages in terms of implant survival cannot be answered based on the current data. Patients receiving PSI could be discharged home earlier at the same or at an even lower total cost. The effective overall superiority of PSI has yet to be proven in long-term studies.

Customised, individually made total knee arthroplasty shows promising 1-year clinical and patient reported outcomes

INTRODUCTION

Customised individually made (CIM) implants for total knee arthroplasty (TKA) were introduced about 10 years ago. These implants aim to reduce the risk of prosthesis-related issues resulting from anthropometric differences between different knees. The purpose of this study was to analyse the short-term clinical outcome and patient reported outcome measures (PROMs) of a specific CIM implant, the ORIGIN^® knee replacement system (Symbios, Yverdon-les-Bains, Switzerland), which was introduced in 2018.

MATERIALS AND METHODS

This is a prospective cohort study of patients undergoing primary posterior-stabilised (PS) CIM TKA using the specific ORIGIN^® knee replacement system, (Symbios, Yverdon-les-Bains, Switzerland). TKAs were performed from February 2019 to October 2020. Data was collected preoperatively and postoperatively at 4 and 12 months. Outcome measures included the objective part of the Knee Society Score (KSS) with the range of motion (ROM) and the following PROMs: the Knee injury and Osteoarthritis Outcome Score (KOOS), the Forgotten Joint Score (FJS-12), the EuroQol, five dimensions, three levels (EQ-5D-3L) with the EuroQol visual analogue scale (EQ-VAS) and patient satisfaction. Differences in pre- to preoperative data were assessed with paired sample t tests. A p value < 0.05 was considered significant.

RESULTS

Twenty-five CIM TKA (20 patients, 8 female) were included. The mean age at surgery was 66 years (SD, 6.9). At 4 and 12 months, significant improvements in the KSS (p < 0.001), the ROM (p < 0.001), all KOOS subscales (p < 0.001), the FJS (p < 0.001) and the EQ-5D-3L (p < 0.026) were found. Satisfaction rate was 91% and 88% at 4 and 12 months, respectively. Intraoperative complications did not occur and no revision surgeries were undertaken.

CONCLUSIONS

The present study demonstrated significant improvements in the KSS and specific PROMs 1 year after CIM TKA. This study suggests that CIM TKA is a safe and suitable option, which can yield good clinical outcome and PROMs at least during short-term follow-up.

Predicting Unplanned Readmissions Following a Hip or Knee Arthroplasty: Retrospective Observational Study

BACKGROUND

Total joint replacements are high-volume and high-cost procedures that should be monitored for cost and quality control. Models that can identify patients at high risk of readmission might help reduce costs by suggesting who should be enrolled in preventive care programs. Previous models for risk prediction have relied on structured data of patients rather than clinical notes in electronic health records (EHRs). The former approach requires manual feature extraction by domain experts, which may limit the applicability of these models.

OBJECTIVE

This study aims to develop and evaluate a machine learning model for predicting the risk of 30-day readmission following knee and hip arthroplasty procedures. The input data for these models come from raw EHRs. We empirically demonstrate that unstructured free-text notes contain a reasonably predictive signal for this task.

METHODS

We performed a retrospective analysis of data from 7174 patients at Partners Healthcare collected between 2006 and 2016. These data were split into train, validation, and test sets. These data sets were used to build, validate, and test models to predict unplanned readmission within 30 days of hospital discharge. The proposed models made predictions on the basis of clinical notes, obviating the need for performing manual feature extraction by domain and machine learning experts. The notes that served as model inputs were written by physicians, nurses, pathologists, and others who diagnose and treat patients and may have their own predictions, even if these are not recorded.

RESULTS

The proposed models output readmission risk scores (propensities) for each patient. The best models (as selected on a development set) yielded an area under the receiver operating characteristic curve of 0.846 (95% CI 82.75-87.11) for hip and 0.822 (95% CI 80.94-86.22) for knee surgery, indicating reasonable discriminative ability.

CONCLUSIONS

Machine learning models can predict which patients are at a high risk of readmission within 30 days following hip and knee arthroplasty procedures on the basis of notes in EHRs with reasonable discriminative power. Following further validation and empirical demonstration that the models realize predictive performance above that which clinical judgment may provide, such models may be used to build an automated decision support tool to help caretakers identify at-risk patients.

[Custom made total knee arthroplasty : Review of current literature]

Custom-designed total knee replacement has become a standard procedure in some orthopaedic centres worldwide. Due to the lack of literature, the discussion about the hypothetical advantages has remained controversial. It was the aim of this study to focus on the current literature on custom-made total knee arthroplasty. We can demonstrate that custom-made total knee arthroplasty is a reproducible strategy with good clinical results in terms of leg-axis reconstruction, natural kinematics, patient-related outcomes and cost effectiveness. This has led to the fact that the Orthopaedic Data Evaluation Panel (ODEP) of the National Health Service in Great Britain rated the Conformis custom-designed knee replacement in 2017 with a 3D rating.