Introducing PIONEER: a project to harness big data in prostate cancer research

Public Involvement and Engagement in Big Data Research: Scoping Review

BACKGROUND

The success of big data initiatives depends on public support. Public involvement and engagement could be a way of establishing public support for big data research.

OBJECTIVE

This review aims to synthesize the evidence on public involvement and engagement in big data research.

METHODS

This scoping review mapped the current evidence on public involvement and engagement activities in big data research. We searched 5 electronic databases, followed by additional manual searches of Google Scholar and gray literature. In total, 2 public contributors were involved at all stages of the review.

RESULTS

A total of 53 papers were included in the scoping review. The review showed the ways in which the public could be involved and engaged in big data research. The papers discussed a broad range of involvement activities, who could be involved or engaged, and the importance of the context in which public involvement and engagement occur. The findings show how public involvement, engagement, and consultation could be delivered in big data research. Furthermore, the review provides examples of potential outcomes that were produced by involving and engaging the public in big data research.

CONCLUSIONS

This review provides an overview of the current evidence on public involvement and engagement in big data research. While the evidence is mostly derived from discussion papers, it is still valuable in illustrating how public involvement and engagement in big data research can be implemented and what outcomes they may yield. Further research and evaluation of public involvement and engagement in big data research are needed to better understand how to effectively involve and engage the public in big data research.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-https://doi.org/10.1136/bmjopen-2021-050167.

Transforming a Large-Scale Prostate Cancer Outcomes Dataset to the OMOP Common Data Model-Experiences from a Scientific Data Holder's Perspective

To enhance international and joint research collaborations in prostate cancer research, data from different sources should use a common data model (CDM) that enables researchers to share their analysis scripts and merge results. The OMOP CDM maintained by OHDSI is such a data model developed for a federated data analysis with partners from different institutions that want to jointly investigate research questions using clinical care data. The German Cancer Society as the scientific lead of the Prostate Cancer Outcomes (PCO) study gathers data from prostate cancer care including routine oncological care data and survey data (incl. patient-reported outcomes) and uses a common data specification (called OncoBox Research Prostate) for this purpose. To further enhance research collaborations outside the PCO study, the purpose of this article is to describe the process of transferring the PCO study data to the internationally well-established OMOP CDM. This process was carried out together with an IT company that specialised in supporting research institutions to transfer their data to OMOP CDM. Of n = 49,692 prostate cancer cases with 318 data fields each, n = 392 had to be excluded during the OMOPing process, and n = 247 of the data fields could be mapped to OMOP CDM. The resulting PostgreSQL database with OMOPed PCO study data is now ready to use within larger research collaborations such as the EU-funded EHDEN and OPTIMA consortium.

Research Protocol for an Observational Health Data Analysis on the Adverse Events of Systemic Treatment in Patients with Metastatic Hormone-sensitive Prostate Cancer: Big Data Analytics Using the PIONEER Platform

Combination therapies in metastatic hormone-sensitive prostate cancer (mHSPC), which include the addition of an androgen receptor signaling inhibitor and/or docetaxel to androgen deprivation therapy, have been a game changer in the management of this disease stage. However, these therapies come with their fair share of toxicities and side effects. The goal of this observational study is to report drug-related adverse events (AEs), which are correlated with systemic combination therapies for mHSPC. Determining the optimal treatment option requires large cohorts to estimate the tolerability and AEs of these combination therapies in "real-life" patients with mHSPC, as provided in this study. We use a network of databases that includes population-based registries, electronic health records, and insurance claims, containing the overall target population and subgroups of patients defined by unique certain characteristics, demographics, and comorbidities, to compute the incidence of common AEs associated with systemic therapies in the setting of mHSPC. These data sources are standardised using the Observational Medical Outcomes Partnership Common Data Model. We perform the descriptive statistics as well as calculate the AE incidence rate separately for each treatment group, stratified by age groups and index year. The time until the first event is estimated using the Kaplan-Meier method within each age group. In the case of episodic events, the anticipated mean cumulative counts of events are calculated. Our study will allow clinicians to tailor optimal therapies for mHSPC patients, and they will serve as a basis for comparative method studies.

Clinical Characterization of Patients Diagnosed with Prostate Cancer and Undergoing Conservative Management: A PIONEER Analysis Based on Big Data

BACKGROUND

Conservative management is an option for prostate cancer (PCa) patients either with the objective of delaying or even avoiding curative therapy, or to wait until palliative treatment is needed. PIONEER, funded by the European Commission Innovative Medicines Initiative, aims at improving PCa care across Europe through the application of big data analytics.

OBJECTIVE

To describe the clinical characteristics and long-term outcomes of PCa patients on conservative management by using an international large network of real-world data.

DESIGN, SETTING, AND PARTICIPANTS

From an initial cohort of >100 000 000 adult individuals included in eight databases evaluated during a virtual study-a-thon hosted by PIONEER, we identified newly diagnosed PCa cases (n = 527 311). Among those, we selected patients who did not receive curative or palliative treatment within 6 mo from diagnosis (n = 123 146).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Patient and disease characteristics were reported. The number of patients who experienced the main study outcomes was quantified for each stratum and the overall cohort. Kaplan-Meier analyses were used to estimate the distribution of time to event data.

RESULTS AND LIMITATIONS

The most common comorbidities were hypertension (35-73%), obesity (9.2-54%), and type 2 diabetes (11-28%). The rate of PCa-related symptomatic progression ranged between 2.6% and 6.2%. Hospitalization (12-25%) and emergency department visits (10-14%) were common events during the 1st year of follow-up. The probability of being free from both palliative and curative treatments decreased during follow-up. Limitations include a lack of information on patients and disease characteristics and on treatment intent.

CONCLUSIONS

Our results allow us to better understand the current landscape of patients with PCa managed with conservative treatment. PIONEER offers a unique opportunity to characterize the baseline features and outcomes of PCa patients managed conservatively using real-world data.

PATIENT SUMMARY

Up to 25% of men with prostate cancer (PCa) managed conservatively experienced hospitalization and emergency department visits within the 1st year after diagnosis; 6% experienced PCa-related symptoms. The probability of receiving therapies for PCa decreased according to time elapsed after the diagnosis.

Predictive Models for Assessing Patients' Response to Treatment in Metastatic Prostate Cancer: A Systematic Review

Background and objective

The treatment landscape of metastatic prostate cancer (mPCa) has evolved significantly over the past two decades. Despite this, the optimal therapy for patients with mPCa has not been determined. This systematic review identifies available predictive models that assess mPCa patients' response to treatment.

Methods

We critically reviewed MEDLINE and CENTRAL in December 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses statement. Only quantitative studies in English were included with no time restrictions. The quality of the included studies was assessed using the PROBAST tool. Data were extracted following the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews criteria.

Key findings and limitations

The search identified 616 citations, of which 15 studies were included in our review. Nine of the included studies were validated internally or externally. Only one study had a low risk of bias and a low risk concerning applicability. Many studies failed to detail model performance adequately, resulting in a high risk of bias. Where reported, the models indicated good or excellent performance.

Conclusions and clinical implications

Most of the identified predictive models require additional evaluation and validation in properly designed studies before these can be implemented in clinical practice to assist with treatment decision-making for men with mPCa.

Patient summary

In this review, we evaluate studies that predict which treatments will work best for which metastatic prostate cancer patients. We found that existing studies need further improvement before these can be used by health care professionals.

Bioinformatics in urology - molecular characterization of pathophysiology and response to treatment

The application of bioinformatics has revolutionized the practice of medicine in the past 20 years. From early studies that uncovered subtypes of cancer to broad efforts spearheaded by the Cancer Genome Atlas initiative, the use of bioinformatics strategies to analyse high-dimensional data has provided unprecedented insights into the molecular basis of disease. In addition to the identification of disease subtypes - which enables risk stratification - informatics analysis has facilitated the identification of novel risk factors and drivers of disease, biomarkers of progression and treatment response, as well as possibilities for drug repurposing or repositioning; moreover, bioinformatics has guided research towards precision and personalized medicine. Implementation of specific computational approaches such as artificial intelligence, machine learning and molecular subtyping has yet to become widespread in urology clinical practice for reasons of cost, disruption of clinical workflow and need for prospective validation of informatics approaches in independent patient cohorts. Solving these challenges might accelerate routine integration of bioinformatics into clinical settings.

Survivorship Data in Prostate Cancer: Where Are We and Where Do We Need To Be?

Cancer survivorship was recently identified as a prostate cancer (PCa) research priority by PIONEER, a European network of excellence for big data in PCa. Despite being a research priority, cancer survivorship lacks a clear and agreed definition, and there is a distinct paucity of patient-reported outcome (PRO) data available on the subject. Data collection on cancer survivorship depends on the availability and implementation of (validated) routinely collected patient-reported outcome measures (PROMs). There have been recent advances in the availability of such PROMs. For instance, the European Organisation for Research and Treatment of Cancer Quality of Life Group (EORTC QLG) is developing survivorship questionnaires. This provides an excellent first step in improving the data available on cancer survivorship. However, we propose that an agreed, standardised definition of (prostate) cancer survivorship must first be established. Only then can real-world data on survivorship be collected to strengthen our knowledge base. With more men than ever surviving PCa, this type of research is imperative to ensure that the quality of life of these men is considered as much as their quantity of life.

Patient summary

As there are more prostate cancer survivors than ever before, research into cancer survivorship is crucial. We highlight the importance of such research and provide recommendations on how to carry it out. The first step should be establishing agreement on a standardised definition of survivorship. From this, patient-reported outcome measures can then be used to collect important survivorship data.

Transforming Estonian health data to the Observational Medical Outcomes Partnership (OMOP) Common Data Model: lessons learned

Objective

To describe the reusable transformation process of electronic health records (EHR), claims, and prescriptions data into Observational Medical Outcome Partnership (OMOP) Common Data Model (CDM), together with challenges faced and solutions implemented.

Materials and Methods

We used Estonian national health databases that store almost all residents' claims, prescriptions, and EHR records. To develop and demonstrate the transformation process of Estonian health data to OMOP CDM, we used a 10% random sample of the Estonian population (n = 150 824 patients) from 2012 to 2019 (MAITT dataset). For the sample, complete information from all 3 databases was converted to OMOP CDM version 5.3. The validation was performed using open-source tools.

Results

In total, we transformed over 100 million entries to standard concepts using standard OMOP vocabularies with the average mapping rate 95%. For conditions, observations, drugs, and measurements, the mapping rate was over 90%. In most cases, SNOMED Clinical Terms were used as the target vocabulary.

Discussion

During the transformation process, we encountered several challenges, which are described in detail with concrete examples and solutions.

Conclusion

For a representative 10% random sample, we successfully transferred complete records from 3 national health databases to OMOP CDM and created a reusable transformation process. Our work helps future researchers to transform linked databases into OMOP CDM more efficiently, ultimately leading to better real-world evidence.

Unanswered questions in prostate cancer - findings of an international multi-stakeholder consensus by the PIONEER consortium

PIONEER is a European network of excellence for big data in prostate cancer consisting of 37 private and public stakeholders from 9 countries across Europe. Many progresses have been done in prostate cancer management, but unanswered questions in the field still exist, and big data could help to answer these questions. The PIONEER consortium conducted a two-round modified Delphi survey aiming at building consensus between two stakeholder groups - health-care professionals and patients with prostate cancer - about the most important questions in the field of prostate cancer to be answered using big data. Respondents were asked to consider what would be the effect of answering the proposed questions on improving diagnosis and treatment outcomes for patients with prostate cancer and to score these questions on a scale of 1 (not important) to 9 (critically important). The mean percentage of participants who scored each of the proposed questions as critically important was calculated across the two stakeholder groups and used to rank the questions and identify the highest scoring questions in the critically important category. The identification of questions in prostate cancer that are important to various stakeholders will help the PIONEER consortium to provide answers to these questions to improve the clinical care of patients with prostate cancer.

Best Current Practice and Research Priorities in Active Surveillance for Prostate Cancer-A Report of a Movember International Consensus Meeting

BACKGROUND

Active surveillance (AS) is recommended for low-risk and some intermediate-risk prostate cancer. Uptake and practice of AS vary significantly across different settings, as does the experience of surveillance-from which tests are offered, and to the levels of psychological support.

OBJECTIVE

To explore the current best practice and determine the most important research priorities in AS for prostate cancer.

DESIGN, SETTING, AND PARTICIPANTS

A formal consensus process was followed, with an international expert panel of purposively sampled participants across a range of health care professionals and researchers, and those with lived experience of prostate cancer. Statements regarding the practice of AS and potential research priorities spanning the patient journey from surveillance to initiating treatment were developed.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Panel members scored each statement on a Likert scale. The group median score and measure of consensus were presented to participants prior to discussion and rescoring at panel meetings. Current best practice and future research priorities were identified, agreed upon, and finally ranked by panel members.

RESULTS AND LIMITATIONS

There was consensus agreement that best practice includes the use of high-quality magnetic resonance imaging (MRI), which allows digital rectal examination (DRE) to be omitted, that repeat standard biopsy can be omitted when MRI and prostate-specific antigen (PSA) kinetics are stable, and that changes in PSA or DRE should prompt MRI ± biopsy rather than immediate active treatment. The highest ranked research priority was a dynamic, risk-adjusted AS approach, reducing testing for those at the least risk of progression. Improving the tests used in surveillance, ensuring equity of access and experience across different patients and settings, and improving information and communication between and within clinicians and patients were also high priorities. Limitations include the use of a limited number of panel members for practical reasons.

CONCLUSIONS

The current best practice in AS includes the use of high-quality MRI to avoid DRE and as the first assessment for changes in PSA, with omission of repeat standard biopsy when PSA and MRI are stable. Development of a robust, dynamic, risk-adapted approach to surveillance is the highest research priority in AS for prostate cancer.

PATIENT SUMMARY

A diverse group of experts in active surveillance, including a broad range of health care professionals and researchers and those with lived experience of prostate cancer, agreed that best practice includes the use of high-quality magnetic resonance imaging, which can allow digital rectal examination and some biopsies to be omitted. The highest research priority in active surveillance research was identified as the development of a dynamic, risk-adjusted approach.

Costs of radium-223 and the pharmacy preparation 177Lu-PSMA-I&T for metastatic castration-resistant prostate cancer in Dutch hospitals

OBJECTIVE

The radiopharmaceuticals radium-223 and the pharmacy preparation ¹⁷⁷Lu-PSMA-I&T are reimbursed in the Netherlands for metastatic castration-resistant prostate cancer (mCRPC) treatment. Although shown to be life-prolonging in patients with mCRPC, the treatment procedures associated with these radiopharmaceuticals can be challenging for both patients and hospitals. This study investigates the costs of mCRPC treatment in Dutch hospitals for currently reimbursed radiopharmaceuticals with a demonstrated overall survival benefit.

METHODS

A cost model that calculated the direct medical per-patient costs of radium-223 and ¹⁷⁷Lu-PSMA-I&T was developed, following clinical trial regimens. The model considered six 4-weekly administrations (i.e. ALSYMPCA regimen) of radium-223. Regarding ¹⁷⁷Lu-PSMA-I&T, the model used both the VISION regimen (i.e. five 6-weekly administrations) and the SPLASH regimen (i.e. four 8-weekly administrations). Based on health insurance claims, we also estimated the coverage a hospital would receive for providing treatment. No fitting health insurance claim for ¹⁷⁷Lu-PSMA-I&T is currently available; therefore, we calculated a break-even value for a potential health insurance claim that would exactly counterbalance the per-patient costs and coverage.

RESULTS

Radium-223 administration is associated with per-patient costs of €30,905, and these costs are fully covered by the coverage a hospital receives. The per-patient costs of ¹⁷⁷Lu-PSMA-I&T range between €35,866 and €47,546 per administration period, depending on the regimen. Current healthcare insurance claims do not fully cover the costs of providing ¹⁷⁷Lu-PSMA-I&T: hospitals must pay €4,414-€4,922 for each patient out of their own budget. The break-even value for the potential insurance claim covering ¹⁷⁷Lu-PSMA-I&T administration with a VISION (SPLASH) regimen is €1,073 (€1,215).

CONCLUSION

This study shows that, without consideration of the treatment effect, radium-223 treatment for mCRPC leads to lower per-patient costs than treatment with ¹⁷⁷Lu-PSMA-I&T. The detailed overview of the costs associated with radiopharmaceutical treatment provided by this study is relevant for both hospitals and healthcare insurers.

Improving Guideline Adherence in Urology

CONTEXT

Clinical practice guidelines (CPGs) distil an evidence base into recommendations. CPG adherence is associated with better patient outcomes. However, preparation and dissemination of CPGs are a costly task involving multiple skilled personnel. Furthermore, dissemination alone does not ensure CPG adherence. Reasons for nonadherence are often complex, but understanding practice variations and reasons for nonadherence is key to improving CPG adherence and harmonising clinically appropriate and cost-effective care.

OBJECTIVE

To overview approaches to improving guideline adherence, to provide urology-specific examples of knowledge-practice gaps, and to highlight potential solutions informed by implementation science.

EVIDENCE ACQUISITION

Three common approaches to implementation science (the Knowledge-To-Action framework, the Consolidated Framework for Implementation Research, and the Behaviour Change Wheel), are summarised.

EVIDENCE SYNTHESIS

Three implementation problems in urology are illustrated: underuse of single instillation of intravesical chemotherapy in non-muscle-invasive bladder cancer, overuse of androgen deprivation therapy in localised prostate cancer, and guideline-discordant imaging in prostate cancer. Research using implementation science approaches to address these implementation problems is discussed.

CONCLUSIONS

Urologists, patients, health care providers, funders, and other key stakeholders must commit to reliably capturing and reporting data on patient outcomes, practice variations, guideline adherence, and the impact of adherence on outcomes. Leverage of implementation science frameworks is a sound next step towards improving guideline adherence and the associated benefits of evidence-based care.

PATIENT SUMMARY

Clinical practice guideline documents are created by expert panels. These documents provide overviews of the evidence for the tests and treatments used in patient care. They also provide recommendations and it is expected that in most circumstances clinicians will follow these recommendations. Sometimes, health care professionals cannot or do not follow these recommendations and it is not always clear why. In this review article we look at some examples of research approaches to addressing this problem of nonadherence and we provide some examples specific to urology.

Standardising the Assessment of Patient-reported Outcome Measures in Localised Prostate Cancer. A Systematic Review

CONTEXT

Prostate cancer (PCa) is the second most common cancer among men worldwide. Urinary, bowel, and sexual function, as well as hormonal symptoms and health-related quality of life (HRQoL), were prioritised by patients and professionals as part of a core outcome set for localised PCa regardless of treatment type.

OBJECTIVE

To systematically review the measurement properties of patient-reported outcome measures (PROMs) used in localised PCa and recommend PROMs for use in routine practice and research settings.

EVIDENCE ACQUISITION

The psychometric properties of PROMs measuring functional and HRQoL domains used in randomised controlled trials including patients with localised PCa were assessed according to the Consensus-based Standards for the Selection of Health Measurement Instruments (COSMIN) methodology. MEDLINE and Embase were searched to identify publications evaluating psychometric properties of the PROMs. The characteristics and methodological quality of the studies included were extracted, tabulated, and assessed according to the COSMIN criteria.

EVIDENCE SYNTHESIS

Overall, 27 studies evaluating psychometric properties of the Expanded Prostate Cancer Index Composite (EPIC), University of California-Los Angeles Prostate Cancer Index (UCLA-PCI), European Organisation for Research and Treatment of Cancer (EORTC) quality of life core 30 (QLQ-C30) and prostate cancer 25 (QLQ-PR25) modules, International Index of Erectile Function (IIEF), and the 36-item (SF-36) and 12-item Short-Form health survey (SF-12) PROMs were identified and included in the systematic review. EPIC and EORTC QLQ-C30, a general module that assesses patients' physical, psychological, and social functions, were characterised by high internal consistency (Cronbach's α 0.46-0.96 and 0.68-0.94 respectively) but low content validity. EORTC QLQ-PR25, which is primarily designed to assess PCa-specific HRQoL, had moderate content validity and internal consistency (Cronbach's α 0.39-0.87). UCLA-PCI was characterised by moderate content validity and high internal consistency (Cronbach's α 0.21-0.94). However, it does not directly assess hormonal symptoms, whereas EORTC QLQ-PR25 does.

CONCLUSION

The tools with the best evidence for psychometric properties and feasibility for use in routine practice and research settings to assess PROMs in patients with localised PCa were EORTC QLQ-C30 and QLQ-PR25. Since EORTC QLQ-C30 is a general module that does not directly assess PCa-specific issues, it should be adopted in conjunction with the QLQ-PR25 module.

PATIENT SUMMARY

We reviewed and appraised the measurement properties of patient-reported outcome measure questionnaires used for patients with localised prostate cancer. We found good evidence to suggest that two questionnaires (EORTC QLQ-C30 and QLQ-PR25) can be used to measure urinary, bowel, and sexual functions and health-related quality of life.

The Key Role of Patient Involvement in the Development of Core Outcome Sets in Prostate Cancer

Patients are the stewards of their own care and hence their voice is important when designing and implementing research. Patients should be involved not only as participants in research that impacts their care, as the recipients of that care and any associated harms, but also as research collaborators in prioritising important questions from the patient perspective and designing the research and the ways in which is it most appropriate to involve patients. The PIONEER Consortium, an international multistakeholder collaboration lead by the European Association of Urology, has developed a core outcome set (COS) for localised and metastatic prostate cancer relevant to all stakeholders in particular patients. Throughout the work of PIONEER, patient representatives were involved as collaborators in setting the research agenda, and a wider group of patients was involved as participants in developing COSs, for instance in consensus meetings on choosing important outcomes and appropriate definitions. This publication showcases the process for COS development and highlights the most important recommendations to ultimately inform future research projects co-created between patients and other stakeholders. PATIENT SUMMARY: An important step in involving patients in the selection of outcomes for clinical trials, clinical audits, and real-world evidence is the development of a core outcome set (COS) that is relevant to all stakeholders. This report highlights the patient participation throughout our PIONEER COS development. TAKE HOME  MESSAGE: An important step in involving patients in the selection of outcomes for clinical trials, clinical audits, and real-world evidence is to develop a core outcome set (COS) that is relevant to all stakeholders. As part of the work of the PIONEER Consortium, we aim to highlight the patient participation throughout our PIONEER COS development.

Evidence and clinical trials in Endourology: where are we going

PURPOSE OF REVIEW

There is an ongoing explosion in the amount and quality, of research in the field of Endourology. From a solid basis of systematic reviews and small, single centre trials it has been possible to design large randomised controlled trials in the UK and in the USA. This review will describe some of the more recent trials (small and large) that are helping to provide a solid evidence base for our practice in Endourology.

ONGOING STUDIES

Randomised controlled trial (RCTs) include: The Therapeutic Interventions for Stones in the Ureter (TISU), the Percutaneous nephrolithotomy, flexible Ureterorenoscopy and extracorporeal Shockwave lithotripsy for lower pole kidney stones (PURE RCTs) and the Prevention of Urinary Stones with Hydration (PUSH). Quality of life (QoL) measures and studies include: the Wisconsin Stone QoL Questionnaire, the Cambridge Renal Stone PROM, the Cambridge Ureteral Stone PROM, the Urinary stone and Intervention QoL questionnaire and the Study to Enhance Understanding of sTent-associated Symptoms (STENTS). The Core Outcome Set in Trials on treatments for Renal and UreteriC sTones (COSTRUCT) study aims to define a core outcome set to be used in future trials.

SUMMARY

On-going studies will provide higher quality evidence on the treatment of ureteric and renal stones to inform treatment decision making and guideline recommendations. They will also guide decisions relating to prevention and recurrence and give insight into the true impact of urinary stones and endourological interventions on patients' quality of life. Future studies will incorporate big data and artificial intelligence.

Contemporary application of artificial intelligence in prostate cancer: an i-TRUE study

Artificial intelligence (AI) involves technology that is able to emulate tasks previously carried out by humans. The growing incidence, novel diagnostic strategies and newer available therapeutic options have had resource and economic impacts on the healthcare organizations providing prostate cancer care. AI has the potential to be an adjunct to and, in certain cases, a replacement for human input in prostate cancer care delivery. Automation can also address issues such as inter- and intra-observer variability and has the ability to deliver analysis of large volume datasets quickly and accurately. The continuous training and testing of AI algorithms will facilitate development of futuristic AI models that will have integral roles to play in diagnostics, enhanced training and surgical outcomes and developments of prostate cancer predictive tools. These AI related innovations will enable clinicians to provide individualized care. Despite its potential benefits, it is vital that governance with AI related care is maintained and responsible adoption is achieved.