Trial Data Transparency and Disclosure †Free Samples to Students

Question: Discuss about Trial Data Transparency and Disclosurethe . Answer: Introduction: There should be availability of opioid antagonist like naloxone while administering opioid in paediatric. Opioids have potential to produce sedation, nausea, vomiting, itching, urinary retention and constipation. Hence, nurse should monitor all these signs in the patients and report it promptly to the clinician. Dose related allergy can also be evident during administration of opioids. Management of side effects and allergy also include arranging adjuvant analgesia to reduce opioids dose. Nurse should monitor pain score and sedation score for altering dose and frequency of opioid administration. Respiratory depression is one of prominent factor which needs to be closely monitored during administration of opioids. If patient is kept on opioid administration for more than one week, weaning process should be implemented prior to cessation of opioid administration (Krashin et al., 2015). Researchers should inform participants that participants can withdraw from the study at any time point without any penalty or loss of benefit. Withdrawal of the participant form the study can be either from all the components of the study or some components of the study. Participants should infrom researchers about their withdrawal plan form the study. Participants should be given instructions about their withdrawal. Participants should be instructed to safely stop the medications. It would be helpful in preventing withdrawal symptoms in the participants. Participants might face problems after leaving the study. Participants should be well informed about the contact person to whom participants should be contacted after withdrawing themselves from the study. Return schedule should be prepared for the participants to assess adverse events due to treatments, procedures, or interventions. Research team should collect health information about the participant at the time of withdrawal from the study. Assessment data of the participants in the form of physical examination, biochemical analysis in the blood sample, photos and scans should be properly documented. This data should be used at the time of data analysis. Collected data of withdrawn participant should be incorporated along with the data of other participants data up to that particular time point. Collected data from the participants should be used for this particular study and it should not be used for any other purpose (NRC, 2011). High withdrawal rates secondary to the adverse reactions should make researcher to think about the anticipated risk-benefit ratio. Researchers should allow participants to withdraw from the study to reduce adverse effects in the participants (Lawton et al., 2017). Withdrawn participants from the study should not be replaced by new participants. However, additional participant from the same study should be incorporated to replace withdrawn participant. Arrangement of these additional participants should be made at the time of initiation of the study. Addition of new participants would not be helpful in comparison with the existing participants. If number of withdrawn participants raised above certain level, it would be difficult to get statistically significant results due to less power for comparison. Hence, researchers should make sure that optimum number of participants should be maintained in the study to get statistically significant results (Chen et al., 2015). Records from the study comprising of consent forms, data files and medical records should be stored in the archive of the organisation. Along with the data, biological samples used in the study should be stored in the archives. Both data and biological samples should be stored for minimum of five years. Achieve should be entirely secure under control of head of the institute. Data should also be stored in the electronic form. Consideration should be given to security safeguard, back-up plans and disaster recovery plans in the storage of data. Collected data should not be stored in the shared drive. Access to the stored files should be restricted to the principle investigator of the study upon approval by the head of the institute (Li et al.,2012). Confidentiality of the patient data should be maintained by authorizing external distribution of personal data to the key personal. Personal data about the patients should not be publicly available. Institute should develop certain laws and rules to maintain confidentiality of the data. Certain transformational methods should be implemented for maintaining confidentiality of the data. It involves modifications of certain details which can not retrieve data. Electronic storage of data is more susceptible for data leakage. Hence, more precautions should be taken in electronic storage of data. Data should be stored by providing codes for each participant. It would be helpful in hiding identity of the participant. Ancillary data like blood samples and photographs should be stored for a minimum of five years in the archive of the institute. For each sample certain code should be given, hence, confidentiality of the participant sample can be maintained (Berlin et al., 2014; Alemayehu et al., 2014). References: Alemayehu, D., Anziano, R.J., and Levenstein, M. (2014). Perspectives on clinical trial data transparency and disclosure. Contemporary Clinical Trials, 39(1), 28-33. Berlin, J.A., Morris, S., Rockhold, F., Askie, L., Ghersi, D., and Waldstreicher, J. (2014). Bumps and bridges on the road to responsible sharing of clinical trial data. Clinical Trials, 11(1), 7-12. Chen, Z., Aiyi, L., Yongming, Q., Larry, T., Naitee, T., Yi, T. (2015). Applied Statistics in Biomedicine and Clinical Trials Design. Springer. Krashin, D., Murinova, N., Jumelle, P., and Ballantyne, J. (2015). Opioid risk assessment in palliative medicine. Expert Opinion on Drug Safety, 14(7), 1023-33. Lawton, J., David, W., David, R., Jackie, E., et al. (2017). Staff experiences of closing out a clinical trial involving withdrawal of treatment: qualitative study. Trials, 18, 61. https://doi.org/10.1186/s13063-017-1813-y. Li, Z., Wen, J., Zhang, X., Wu, C., Li, Z., Liu, L. (2012). ClinData Express--a metadata driven clinical research data management system for secondary use of clinical data. AMIA Annual Symposium Proceedings, 2012, 552-7. National Research Council (NRC). (2011). The Prevention and Treatment of Missing Data in Clinical Trials. National Academies Press.