Considerations within a Healthcare Setting

Part 1 

The selected clinical classification and coding applications include the SNOMED (Systemized Nomenclature of Medicine) and ICD (International Classification of Disease). SNOMED serves as the most broadly understood healthcare nomenclature. It mostly emphasizes of offering several relationships and concepts that provide a mutual point of reference for aggregating and comparing data concerning the process of healthcare. It comprises of around 311,000 concepts that offer definitions based on logic and unique meanings. The application is computer based while it facilitates in handling sophisticated relationships. In the event of the ICD application, it aims at categorizing illnesses for reporting on matters related to mortality and morbidity. The WHO (World Health Organization) supports the application while it adopts a hierarchical structure for coding purposes (Heier, 2019) . The two applications are quite useful when it comes to clinical classification as well as coding.

When looking for ways of assessing the quality of coding efforts, it is crucial to have understanding of several considerations or issues. The initial area to consider in this case is one of the limited grace period, meaning insufficient time for assessing incorrect codes, which leads the healthcare professionals to lack adequate comprehension of the process. An additional issue that emerges in this case is one of backlog. Adopting the coding applications does not indicate that all people have understood how it works thereby hindering the implementation efforts.

System management challenges also prevail when considering adopting classification and coding applications. For instance, it is possible to lack sufficient coders thereby meaning that instant acceptance would not take place overnight meaning that it would be possible to face managerial issues especially when considering hiring additional coder. The other managerial issue relates to combating slow transition. This is because each facility or service within a healthcare institution has adopted the applications. Lastly, the issue of managing the overload of the systems might also emerge. Adopting the classification and coding systems indicates that instability within a healthcare institution would emerge in the event of a system shutdown (McCarthy, 2015) . Overall, the application worth recommending is the one of SNOMED. It is quite popular while it is easier to implement when compared to the ICD.

Part 2 

When considering the principles together with the classification system applications in line with auditing of medical records within a CDI (clinical documentation improvement) initiative, it is vital to have understanding of the value as well as challenges attributed to a quality CDI program. When it comes to the value of CDI, they allow hospitals to have adequate and quality documentation. These lead to improved relationships with diverse providers internal and external to a healthcare setting. Nevertheless, certain challenges also prevail when adopting the systems. For instance, healthcare institutions are realizing tremendous improvements to an extent that providers are devoting a considerable amount of their time on caring for patients as opposed to documentation. This would lead a healthcare institution to experience various problems, such as financial risks with the providers directing their attention to other areas. An additional challenge that would emerge is one whereby a healthcare facility lacks a skilled and experienced CDI team hence leading to issues whereby the care offered does not meet the provided care. The last challenge would relate to where the coding staff within the healthcare facility offers buy-in to other professionals in other areas of specialization. In this vein, all the clinical and coding staff should embrace the change together to avoid any glitches with the classification and coding applications. 

Part 3 

An interoperability issue that would result within a HIE (health information exchange) would relate to the one in which cyber security attacks are becoming increasingly common to an extent that they threaten sensitive and private patient information. The issue has raised concerns within the data security area. As such, a growing number of physicians are showing increased concerns with the rising data that it possible to share, which would burden the providers while leading to ineffective care towards the patients. Concerning this issue, it is crucial to adopt best practices to facilitate in handling the issue effectively. For instance, the involved healthcare stakeholders should focus on minimizing administrative burden, boost interoperability, as well as improve the options for improving health date exchange. They should ensure that they establish a system that emphasizes on delivering value-based care while making sure that the safety of patient information comes first (Weber, 2016) . Lastly, it is crucial to emphasize on the requirements of healthcare data security while reassuring the patients that their data will remain safe. 

Part 4 

From the evaluated HIS (Health Information Systems), including EHR (electronic health records), Patient Portal, and Remote Patient Monitoring, the one perceived as ideal for disaster recovery is Remote Patient Monitoring. The reason for choosing it is that remote patient monitoring has the capacity of sending patient data using medical sensors while in their homes or in any location to healthcare experts at facilities. The process is minimizing costs attributed to hospital readmissions and chronic care while at the same time contributing to improved patient care. When it comes to data storage designs, including onsite, cloud, and hybrid, the cloud design it the most appropriate (Heier, 2019) . It provides scalable and flexible environments at reduced costs as opposed to on-premise applications thereby boosting security of data. 

Part 5 

Clinical databases, indices, and registries feature various managerial challenges from the perspective of the health information management’s function within a hospital. The major challenge is one of limited transparency as well as visibility when evaluating the programs. These systems require analytics access with the goal of determining the ones that are working properly and the ones that are not. The second issue is attributed to absence of standardization, especially when it comes to managing ambulatory care. The third challenge is associated with lack of managerial involvement in governance of data and IT, owing to the manual state of the work that managers handle hence lack time for road mapping and governing data. Here, the first best practice would revolve around the management ensuring to track the implications of the changes to performance of the program while at the same time monitoring operational metrics to determine the ones that work best. The second best practice would entail ensuring that the existing skills within the organization have the sufficient skills and experience to handle the different data processes (Prometheus Research, 2019) . Lastly, the management needs to establish new or boost the relationships with the responsible teams to ensure that the processes work efficiently. 

Part 6 

When it comes to data warehousing, the key approaches of designing a data warehouse would comprise of the Late-Binding Architecture and the Independent Data Marts. In the case of the Late-Binding Architecture, it serves as a data modelling approach, which focuses on the unique requirements of a healthcare institution. Binding data usually means delaying to deploy the rules of business, including data normalization, cleansing, and aggregation to the longest possible period. In this manner, healthcare institutions are capable of having sufficient time for reviewing and revising data allowing them to realize them to realize the ideal analytics to utilize. When it comes to Independent Data Marts, it allows an organization to commence small, establish individual data marts as areas for storing key information for every department, and ensuring to have specific data from particular key sources to meet all the needs of the departments (Barlow, 2014) . Adopting either of these data warehousing approaches would ensure that healthcare institutions operate at optimal levels. 

References 

Barlow, S. (2014). Comparing the three major approaches to healthcare data warehousing: a deep dive review (white paper). Retrieved from https://www.healthcatalyst.com/whitepaper/3-approaches-healthcare-data-warehousing

Heier, E. (2019). 8 types of health information technology & healthcare software systems. Retrieved from https://selecthub.com/medical-software/7-categories-healthcare-information-technology/

McCarthy, K. (2015). 5 early problems encountered with ICD-10. Retrieved from https://www.nuemd.com/news/2015/10/09/5-early-problems-encountered-with-icd-10

Prometheus Research. (2019). 7 challenges of mastering clinical data registries. Retrieved from https://www.prometheusresearch.com/challenges-of-clinical-data-registry/

Weber, B. (2016). The six care management challenges healthcare must overcome. Retrieved from https://www.healthcatalyst.com/Six-Care-Management-Challenges-Healthcare-Must-Overcome