Introduction
Modern technological breakthroughs are currently transforming the way practitioners support their patients’ health needs. Medical institutions and organizations can gather and analyze data in order to develop superior decisions for improving care delivery procedures. The presented case study indicates how the use of metadata in physician training and radiology has made it possible for health leaders (HLs) to monitor their followers’ activities, commitments, and achievements. This paper describes the role of metadata in fostering positive behavior, minimizing fraud, and supporting malpractice litigation.
Given the above case study, how else might metadata be used to evaluate physician, nurse, or other clinician behavior?
The studied case study has indicated that metadata is a powerful tool for recording physicians’ activities. A query submitted to the electronic health record (EHR) system will generate provider-specific reports. Such findings can inform better practices and initiatives to improve health service delivery. Joudaki et al. (2015) believe that managers can use metadata differently to evaluate physician, nurse, or any other clinician behavior.
To begin with, EHR metadata can play a positive role in monitoring practitioner’s effective use of clinical guidelines. The intended information can provide insights on the specific procedures undertaken to provide evidence-based medical services. Secondly, technological systems can be redesigned in such a way that they monitor drug labeling, prescription, and intake. The system will record the activities undertaken by nurses or clinicians who are responsible for administering specific medicines to the targeted patients.
The outstanding fact is that practitioners who fail to consult existing guidelines will be identified (Joudaki et al., 2016). The reports should provide information about patients and pharmacists involved throughout the drug prescription process. Such an initiative will encourage clinicians to embrace appropriate behaviors, thereby minimizing medication errors in their units.
The third example revolves around the implementation of evidence-based treatment plans. For instance, technologists can develop a powerful EHR system to record every procedure and activity undertaken throughout the care delivery process. The introduction of scanners or real-time cameras can guide inspectors to evaluate every physician’s behaviors. The system can also create accounts or audit reports for every healthcare professional. The collected information can, therefore, guide policymakers and disciplinarians to identify practitioners who portray undesirable or appropriate behaviors (Xu, Xu, Fu, Xin, & Cai, 2015). This means that effective use of metadata will encourage many professionals to focus on the changing needs of the targeted patients and eventually improve the country’s healthcare sector.
How might metadata be used to investigate fraud?
Fraud remains a major challenge in healthcare. This predicament arises from numerous malpractices, including corruption, provision of ineffective medical services, and financial dishonesty. Private providers can deceive their patients in an attempt to make a lot money (Joudaki et al., 2015). Metadata can, therefore, empower medical organizations to monitor or prevent fraud. The use of this system can guide auditors to extract meaningful information and identify every activity undertaken by physicians throughout the care delivery process. The ultimate objective is to ensure that the correct amount of money is paid to hospitals and other health facilities.
Insurance companies supporting patients’ needs have reported numerous incidences of fraud and dishonesty from health providers. Xu et al. (2015) argue that data mining can make it possible for payers to extract claimants’ information for assessment and decision-making purposes. Metadata can be a powerful tool for monitoring and locating any form of fraud. The collected information can guide such companies to make quality decisions and implement appropriate action plans against any form of dishonesty. Modern EHR can empower investigators to examine or monitor every completed transaction. Such professionals will find it easier to locate abnormal dealings and act accordingly.
The healthcare industry brings together different stakeholders such as vendors, suppliers, patients, practitioners, pharmacists, and payers. In government health systems, cases of fraud are usually high due to poor managerial, monitoring, auditing, and decision-making processes. Cartels have also been found to control a number of operations such as drug distribution, purchase of health equipment, and prices (Joudaki et al., 2015).
With the use of superior systems, auditors and investigators can be in a position to identify any form of malpractice (Joudaki et al., 2015). This is possible since they will capture every activity or drug delivered to a given facility. Investigators and auditors will locate culprits and institute proper punitive mechanisms. Consequently, the level of fraud will reduce significantly and eventually ensure that high-quality services are available to more citizens in the country.
How might metadata be used in malpractice litigation?
The occurrence of sentinel events in healthcare settings can affect patients’ health outcomes. This challenge can arise from different factors, including physicians’ negligence and the inability to follow existing clinical or care delivery models. Rahmati, Hyman, Black, Liu, & Silver (2018) indicate that some uncontrollable conditions or situations might catalyze errors when practitioners are supporting their respective patients.
This analysis shows that malpractice litigation is an area that stands a chance to benefit from the utilization of metadata. The implementation of powerful EHR systems can make it possible for medical facilities to monitor the behaviors, activities, procedures, and processes undertaken by physicians and professionals throughout the care delivery process. Such systems will highlight the tools, guidelines, and initiatives considered during the targeted period. The consulted physician-specific query will offer key insights and revelations that can be considered throughout the medical litigation process.
The collected information or evidence from the existing system will empower patients, litigation officers, and physicians to get justice depending on the nature of the malpractice. For example, attorneys can use the presented data to represent victims of healthcare negligence (Xu et al., 2015). Legal experts can use the gathered information as evidence in court, thereby ensuring that the targeted patients receive desirable representation and justice.
This modern technology can also become a powerful tool for medical providers and their attorneys. This is true because metadata can ensure that medical professionals are not punished for a malpractice caused by another factor or provider. The outstanding fact is that the use of metadata is a powerful approach or procedure that can address the legal needs of both medical practitioners and recipients. Medical institutions should also consider the use of metadata in order to address various challenges that might arise from any form of malpractice litigation.
Conclusion
The above discussion has revealed that metadata can play a crucial role in monitoring the nature of medical practices and services available in healthcare facilities. The use of this technology can empower investigators to evaluate the behaviors undertaken by physicians, nurses, and clinicians in their respective settings. Modern EHR systems can also guide HLs to investigate fraud in the health sector. The utilization of metadata during malpractice litigation is something that can support the demands of patients, institutions, and providers. In conclusion, healthcare organizations should embrace the use of modern technologies in order to achieve their potential.
References
Joudaki, H., Rashidian, A., Minaei-Bidgoli, B., Mahmoodi, M., Geraili, B., Nasiri, M., & Arab, M. (2015). Using data mining to detect health care fraud and abuse: A review of literature. Global Journal of Health Science, 7(1), 194-202. Web.
Joudaki, H., Rashidian, A., Minaei-Bidgoli, B., Mahmoodi, M., Geraili, B., Nasiri, M., & Arab, M. (2016). Improving fraud and abuse detection in general physician claims: A data mining study. International Journal of Health Policy and Management, 5(3), 165-172. Web.
Rahmati, M., Hyman, D. A., Black, B., Liu, J., & Silver, C. (2018). Screening plaintiffs and selecting defendants in medical malpractice litigation: Evidence from Illinois and Indiana. Journal of Empirical Legal Studies, 15(1), 41-79. Web.
Xu, B., Xu, K., Fu, L., Xin, W., & Cai, H. (2015). Healthcare data analytics: Using a metadata annotation approach for integrating electronic hospital records. Journal of Management Analytics, 3(2), 136-151. Web.