Evaluation of the challenges in the implementation of healthcare analytics in health care industry
The healthcare industry continues to experience changes in big data and the adoption of technological advancements. One such area that has been getting traction is implementing healthcare analytics in healthcare organizations and industries. Patel & Patel (2016) affirm privacy and security issues, data retention, data accessibility, and data management as some of the major challenges in implementing healthcare analytics. The healthcare data is lucrative to criminals making it a top target for attacks. Healthcare organizations struggle with implementing the healthcare analytics while at the same time keeping the client data safe from breaches and all other forms of attacks. The individuals whose data is stolen due to the attacks suffer more than others. Their data, such as diagnosis, lab tests, and credit card numbers, are accessed by the criminals raising concerns over security and data.
The healthcare institutions also suffer financial costs and reputational costs that linger with them longer even after the breaches have ended. Regardless of where the healthcare institutions store their data, in their premises, in SaaS applications, or shared centers, privacy and security issues still implement healthcare analytics an uphill task. Due to this, healthcare systems and healthcare centers find it challenging to implement cutting edge transformation and achieving operational efficiency (McNeill & Davenport, 2014). It makes the process of enhancing clinical outcomes arduous as they cannot optimally leverage the use of analytics, reducing medical costs, and fast-tracking transformation. The challenge raises the threats of identity theft and blackmail. HCO’s also facing the setbacks of effective data retention in implementing healthcare analytics (Sousa et al., 2019). The requirement for HCOs to keep data accessible for a minimum of five years requires them to decipher long-term approaches that will continuously monitor its accessibility. They can use data management software but get into difficulties in periodic sorting through data and deleting it when necessary.
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Application of PICO (problem, intervention, comparison group, and outcomes)
Problem
The problem is applying the integration of data-driven insights into initiating and sustaining the implementation of healthcare analytics in clinical and operational processes. The problem is the imminent vulnerability of the attacks that affect privacy and security. Healthcare organizations have to grapple between implementing the strategies and ensuring privacy/security, which has proven difficult to achieve concurrently. The HCOs face the conundrum of either implementing the healthcare analytics or violating the data retention accessibility requirements of five years due to challenges in getting reliable data stewardship methods for long-term implementation.
Intervention
HCOs can overcome the challenge of privacy and security through various interventions. The use of control data accessibility should limit access to data to need-to-know-basis only. The implication is the physician will only have access to patient data briefly and when they need it and not whenever they choose to. The HCOs can also ensure that patient access to their data is password-protected. Galetsi et al. (2019) recommend training employees to recognize potential attacks as viable interventions. Training employees will help them adjust and apply best practices in their use of technology. The HCOs should develop thorough confidentiality agreements and policies to complement the training of their staff. HCOs should ensure they store information on secure systems and keep mobile phones away from patient areas to eliminate patient confidentiality threats.
Comparison Group
A suitable comparison group is a Telco company that offers customer telephony and data communication services. The challenges in implementing the analytics are similar, and applying the same interventions will deliver similar results.
Outcomes
The data accessibility controls will prevent insiders from intentionally or unintentionally, contributing to data breaches. It will help eliminate the 58% of the data breach incidents facilitated by insiders. The interventions will help reduce the hefty amounts that HCOs spend on lawsuits emanating from data breaches. The other expected outcomes are patients will be more confident in HCOs in delivering privacy and security and thus leverage the benefits of health organizations (Patel & Patel, 2016). The interventions will reduce stress and increase resources available to both patients and the health organizations.
References
Galetsi, P., Katsaliaki, K., & Kumar, S. (2019). Values, challenges and future directions of big data analytics in healthcare: A systematic review. Social Science & Medicine, 241 , 112-533.
McNeill, D., & Davenport, T. H. (Eds.). (2014). Analytics in Healthcare and the Life Sciences: Strategies, Implementation Methods, and Best Practices . Pearson Education.
Patel, S., & Patel, A. (2016). Abig data revolution in health care sector: Opportunities, challenges and technological advancements. International Journal of Information, 6(1/2) , 155-162.
Rahman, F., & Slepian, M. J. (2016). Application of big-data in healthcare analytics—Prospects and challenges. n 2016 IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI) (pp. 13-16). IEEE .
Sousa, M. J., Pesqueira, A. M., Lemos, C., Sousa, M., & Rocha, Á. (2019). Decision-making based on big data analytics for people management in healthcare organizations. Journal of medical systems, 43(9) , 290.
