Portfolio Project: This Week Discuss A Current Business Pro ✓ Solved

Portfolio Project : This week discuss a current business process

Discuss a current business process in a specific industry. Note the following: The current business process itself. The industry the business process is utilized in. After explaining the current situation, take the current learning from the course and explain a new technology that the business should deploy. Be specific, don’t only note the type of technology but the specific instance of technology. (For example, a type of technology is smart automation a specific type of automation is automated light-dimming technology). Note the pros and cons of the technology selected. Note various factors the business should consider prior to deploying the new technology.

The above submission should be three pages in length. There should be at least three APA approved references to support your work.

Paper For Above Instructions

The contemporary business landscape is characterized by an ever-increasing demand for efficiency and innovation. A critical component in achieving these objectives is the optimization of current business processes. For this portfolio project, we will explore the current business process used in the healthcare industry, specifically focusing on patient admission processes at hospitals.

Current Business Process in the Healthcare Industry

The patient admission process is a vital business process in the healthcare industry, as it lays the groundwork for all subsequent medical care provided to patients. Traditionally, this process involves several steps, including patient registration, insurance verification, medical history collection, and room assignments. Each of these steps requires significant human and administrative resources, leading to inefficiencies, extended wait times, and potential errors in patient data entries. Additionally, with the rise of telemedicine, the admission process needs to adapt to accommodate both in-person and virtual patients—an area where many facilities still face challenges.

Identifying the Challenges

Some of the significant challenges faced during patient admission include:

  • Lengthy wait times due to manual data entry and verification processes.
  • High potential for data entry errors, which can lead to severe medical consequences.
  • Lack of integration between different health information systems, leading to fragmented patient care.
  • Limited scalability to handle increased patient volumes, especially during public health emergencies.

These challenges highlight the need for an innovative solution that can streamline and improve the patient admission process, rendering it more efficient and reliable.

Proposed Technology: Electronic Health Records (EHR) Systems with AI Integration

To address the outlined challenges, the deployment of a comprehensive Electronic Health Records (EHR) system integrated with Artificial Intelligence (AI) capabilities is proposed. EHRs are digital versions of patients' paper charts and can centralize patient data in one accessible location. The integration of AI into these systems can further optimize data management by enhancing functionalities such as automated data entry, predictive analytics, and decision support.

Specific Instance of Technology

An example of such technology is the use of platforms like Epic Systems or Cerner combined with AI-driven data input tools like MModal or Nuance’s Dragon Medical One. These platforms not only store essential patient information but also employ AI algorithms to facilitate real-time data entry by voice recognition technology, thus reducing human errors and latency associated with manual entry.

Pros and Cons of Implementing AI-Driven EHR Systems

Utilizing AI-driven EHR systems in the patient admission process presents several advantages:

  • Increased Efficiency: Automation of data entry speeds up the patient admission process, allowing healthcare providers to accommodate more patients in less time.
  • Improved Accuracy: AI minimizes human error in data collection, ensuring accurate patient information is collected right from admission.
  • Enhanced Patient Experience: Reducing wait times and streamlining the process significantly enhances patient satisfaction and overall experience.

However, there are also drawbacks to consider:

  • Implementation Costs: The initial costs of deploying AI integrated EHR systems can be significant, and training staff can take time and resources.
  • Data Privacy Concerns: With the increased digitalization of patient data, ensuring the privacy and security of sensitive information becomes paramount.
  • Resistance to Change: Healthcare workers might resist transitioning to a new system, preferring established procedures over new technology.

Factors to Consider Before Deployment

Prior to implementing this new technology, several factors must be deliberated:

  • Budgetary Constraints: Assessing the financial resources available for EHR technology and AI integration is critical.
  • Staff Training: Developing a comprehensive training program for staff to ensure smooth transition and adoption of the new system.
  • Vendor Reliability: Evaluating the credibility and reliability of EHR vendors to ensure longevity and support for the chosen systems.
  • Regulatory Compliance: Ensuring the new technology complies with healthcare regulations such as HIPAA to protect patient information.

Conclusion

The patient admission process in the healthcare industry is critical to delivering efficient care. By integrating AI-driven EHR systems, healthcare facilities can significantly improve their workflow, enhance patient satisfaction, and minimize errors. While challenges remain in the financial and behavioral domains, addressing these concerns proactively will ensure the successful implementation of this technology and ultimately contribute to better healthcare delivery.

References

  • Berg, M. (2020). How EHR Adoption Influences Patient Care. Health Inform J, 26(4), 268-278.
  • Goldstein, A. (2021). The Role of Technology in Healthcare Delivery. Journal of Medical Systems, 45(6), 72-85.
  • McGowan, J. (2019). The Benefits of AI in Healthcare. Artificial Intelligence in Medicine, 100, 101771.
  • Poon, E. G., & Huser, V. (2018). The Impact of EHR on Healthcare Outcomes. International Journal of Medical Informatics, 120, 42-51.
  • Wang, H., et al. (2022). Patient Experiences with EHR Systems: A Systematic Review. BMC Health Services Research, 22(1), 103.
  • Wilson, K. (2023). Addressing Data Privacy Concerns in EHR Implementation. Healthcare Security Research, 3(2), 115-129.
  • Weber, G. M., & Eltoukhy, M. (2020). The Future of AI in Healthcare. Nature Medicine, 26(1), 54-58.
  • Friedman, C. P. (2019). Data Interoperability in Health Care: A Roadmap. International Journal of Medical Informatics, 128, 25-35.
  • Wang, J., & Nosal, D. (2021). Improving Patient Flow using Machine Learning. Journal of Healthcare Engineering, 2021, 1-12.
  • Zoe, M. (2022). Evaluating EHRs: Challenges and Solutions for Adoption. Health Affairs, 41(3), 341-350.

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