Colorectal cancer health and care quality indicators in a federated setting using the Personal Health Train

Objective: Hospitals and healthcare providers should assess and compare the quality of care given to patients and based on this improve the care. In the Netherlands, hospitals provide data to national quality registries, which in return provide annual quality indicators. However, this process is time-consuming, resource intensive and risks patient privacy and confidentiality. In this paper, we presented a multicentric ‘Proof of Principle’ study for federated calculation of quality indicators in patients with colorectal cancer. The findings suggest that the proposed approach is highly time-efficient and consume significantly lesser resources. Materials and methods: Two quality indicators are calculated in an efficient and privacy presevering federated manner, by i) applying the Findable Accessible Interoperable and Reusable (FAIR) data principles and ii) using the Personal Health Train (PHT) infrastructure. Instead of sharing data to a centralized registry, PHT enables analysis by sending algorithms and sharing only insights from the data. Results: ETL process extracted data from the Electronic Health Record systems of the hospitals, converted them to FAIR data and hosted in RDF endpoints within each hospital. Finally, quality indicators from each center are calculated using PHT and the mean result along with the individual results plotted. Discussion and conclusion: PHT and FAIR data principles can efficiently calculate quality indicators in a privacy-preserving federated approach and the work can be scaled up both nationally and internationally. Despite this, application of the methodology was largely hampered by ELSI issues. However, the lessons learned from this study can provide other hospitals and researchers to adapt to the process easily and take effective measures in building quality of care infrastructures.</p

Colorectal cancer health and care quality indicators in a federated setting using the Personal Health Train

Objective: Hospitals and healthcare providers should assess and compare the quality of care given to patients and based on this improve the care. In the Netherlands, hospitals provide data to national quality registries, which in return provide annual quality indicators. However, this process is time-consuming, resource intensive and risks patient privacy and confidentiality. In this paper, we presented a multicentric ‘Proof of Principle’ study for federated calculation of quality indicators in patients with colorectal cancer. The findings suggest that the proposed approach is highly time-efficient and consume significantly lesser resources. Materials and methods: Two quality indicators are calculated in an efficient and privacy presevering federated manner, by i) applying the Findable Accessible Interoperable and Reusable (FAIR) data principles and ii) using the Personal Health Train (PHT) infrastructure. Instead of sharing data to a centralized registry, PHT enables analysis by sending algorithms and sharing only insights from the data. Results: ETL process extracted data from the Electronic Health Record systems of the hospitals, converted them to FAIR data and hosted in RDF endpoints within each hospital. Finally, quality indicators from each center are calculated using PHT and the mean result along with the individual results plotted. Discussion and conclusion: PHT and FAIR data principles can efficiently calculate quality indicators in a privacy-preserving federated approach and the work can be scaled up both nationally and internationally. Despite this, application of the methodology was largely hampered by ELSI issues. However, the lessons learned from this study can provide other hospitals and researchers to adapt to the process easily and take effective measures in building quality of care infrastructures.</p

Physical Effects, Safety and Feasibility of Prehabilitation in Patients Awaiting Orthotopic Liver Transplantation, a Systematic Review

Prehabilitation improves surgical outcomes in patients undergoing surgery. However, patients preparing for orthotopic liver transplantation (OLT) are physically “frail” and suffer from comorbidities that generally hamper physical activity. This systematic review aims to evaluate the physical effects, safety and feasibility of prehabilitation in OLT candidates. Relevant articles were searched, in Embase, Web of Science, Cochrane, Medline and Google Scholar, to December 2021. Studies reporting on specified preoperative exercise programs, including adult OLT candidates with end-stage liver disease, with a model for end-stage liver disease (MELD) score ≥12 or Child-Pugh classification B/C, were included. This resulted in 563 potentially eligible studies, out of which eight were selected for inclusion, consisting of 1,094 patients (male sex 68%; mean age 51–61 years; mean MELD score 12-21). Six of the included studies were classified as low-quality by the GRADE system, and three studies had high risk for ineffectiveness of the training program according to the i-CONTENT tool. Significant improvement was observed in VO2 peak, 6-minute walking distance, hand grip strength, liver frailty index and quality of life. Feasibility ranged from an adherence of 38%–90% in unsupervised-to &gt;94% in supervised programs. No serious adverse events were reported. In conclusion, prehabilitation in patients awaiting OLT appears to improve aerobic capacity, and seems feasible and safe. However, larger clinical trials are required to accurately examine the preoperative and postoperative effects of prehabilitation in this specific patient population.</p

Physical Effects, Safety and Feasibility of Prehabilitation in Patients Awaiting Orthotopic Liver Transplantation, a Systematic Review

Prehabilitation improves surgical outcomes in patients undergoing surgery. However, patients preparing for orthotopic liver transplantation (OLT) are physically “frail” and suffer from comorbidities that generally hamper physical activity. This systematic review aims to evaluate the physical effects, safety and feasibility of prehabilitation in OLT candidates. Relevant articles were searched, in Embase, Web of Science, Cochrane, Medline and Google Scholar, to December 2021. Studies reporting on specified preoperative exercise programs, including adult OLT candidates with end-stage liver disease, with a model for end-stage liver disease (MELD) score ≥12 or Child-Pugh classification B/C, were included. This resulted in 563 potentially eligible studies, out of which eight were selected for inclusion, consisting of 1,094 patients (male sex 68%; mean age 51–61 years; mean MELD score 12-21). Six of the included studies were classified as low-quality by the GRADE system, and three studies had high risk for ineffectiveness of the training program according to the i-CONTENT tool. Significant improvement was observed in VO2 peak, 6-minute walking distance, hand grip strength, liver frailty index and quality of life. Feasibility ranged from an adherence of 38%–90% in unsupervised-to >94% in supervised programs. No serious adverse events were reported. In conclusion, prehabilitation in patients awaiting OLT appears to improve aerobic capacity, and seems feasible and safe. However, larger clinical trials are required to accurately examine the preoperative and postoperative effects of prehabilitation in this specific patient population

Development and external validation of preoperative clinical prediction models for postoperative outcomes including preoperative aerobic fitness in patients approaching elective colorectal cancer surgery

Introduction: Preoperative aerobic fitness is associated with postoperative outcomes after elective colorectal cancer (CRC) surgery. This study aimed to develop and externally validate two clinical prediction models incorporating a practical test to assess preoperative aerobic fitness to distinguish between patients with and without an increased risk for 1) postoperative complications and 2) a prolonged time to in-hospital recovery of physical functioning after elective colorectal cancer (CRC) surgery. Materials and methods: Models were developed using prospective data from 256 patients and externally validated using prospective data of 291 patients. Postoperative complications were classified according to Clavien-Dindo. The modified Iowa level of assistance scale (mILAS) was used to determine time to postoperative in-hospital physical recovery. Aerobic fitness, age, sex, body mass index, American Society of Anesthesiologists (ASA) classification, neoadjuvant treatment, surgical approach, tumour location, and preoperative haemoglobin level were potential predictors. Areas under the curve (AUC), calibration plots, and Hosmer-Lemeshow tests evaluated predictive performance. Results: Aerobic fitness, sex, age, ASA, tumour location, and surgical approach were included in the final models. External validation of the model for complications and postoperative recovery presented moderate to fair discrimination (AUC 0.666 (0.598–0.733) and 0.722 (0.651–0.794), respectively) and good calibration. High sensitivity and high negative predictive values were observed in the lower predicted risk categories (&lt;40 %). Conclusion: Both models identify patients with and without an increased risk of complications or a prolonged time to in-hospital physical recovery. They might be used for improving patient-tailored preoperative risk assessment and targeted and cost-effective application of prehabilitation interventions.</p

Development and external validation of preoperative clinical prediction models for postoperative outcomes including preoperative aerobic fitness in patients approaching elective colorectal cancer surgery

Introduction: Preoperative aerobic fitness is associated with postoperative outcomes after elective colorectal cancer (CRC) surgery. This study aimed to develop and externally validate two clinical prediction models incorporating a practical test to assess preoperative aerobic fitness to distinguish between patients with and without an increased risk for 1) postoperative complications and 2) a prolonged time to in-hospital recovery of physical functioning after elective colorectal cancer (CRC) surgery. Materials and methods: Models were developed using prospective data from 256 patients and externally validated using prospective data of 291 patients. Postoperative complications were classified according to Clavien-Dindo. The modified Iowa level of assistance scale (mILAS) was used to determine time to postoperative in-hospital physical recovery. Aerobic fitness, age, sex, body mass index, American Society of Anesthesiologists (ASA) classification, neoadjuvant treatment, surgical approach, tumour location, and preoperative haemoglobin level were potential predictors. Areas under the curve (AUC), calibration plots, and Hosmer-Lemeshow tests evaluated predictive performance. Results: Aerobic fitness, sex, age, ASA, tumour location, and surgical approach were included in the final models. External validation of the model for complications and postoperative recovery presented moderate to fair discrimination (AUC 0.666 (0.598–0.733) and 0.722 (0.651–0.794), respectively) and good calibration. High sensitivity and high negative predictive values were observed in the lower predicted risk categories (&lt;40 %). Conclusion: Both models identify patients with and without an increased risk of complications or a prolonged time to in-hospital physical recovery. They might be used for improving patient-tailored preoperative risk assessment and targeted and cost-effective application of prehabilitation interventions.</p

Operationalizing and digitizing person-centered daily functioning:a case for functionomics

An ever-increasing amount of data on a person’s daily functioning is being collected, which holds information to revolutionize person-centered healthcare. However, the full potential of data on daily functioning cannot yet be exploited as it is mostly stored in an unstructured and inaccessible manner. The integration of these data, and thereby expedited knowledge discovery, is possible by the introduction of functionomics as a complementary ‘omics’ initiative, embracing the advances in data science. Functionomics is the study of high-throughput data on a person’s daily functioning, that can be operationalized with the International Classification of Functioning, Disability and Health (ICF). A prerequisite for making functionomics operational are the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This paper illustrates a step by step application of the FAIR principles for making functionomics data machine readable and accessible, under strictly certified conditions, in a practical example. Establishing more FAIR functionomics data repositories, analyzed using a federated data infrastructure, enables new knowledge generation to improve health and person-centered healthcare. Together, as one allied health and healthcare research community, we need to consider to take up the here proposed methods.</p

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Perioperatieve zorg rondom een TKA: veranderingen binnen Nij Smellinghe in de periode 2009 t/m 202