part 1
write a 350- to 525-word comparison in which you:

Define both taxonomies.

Detail the usages and designs (how they are structured/read) of both taxonomies.

Compare the types of systems both taxonomies work in.

Compare the datasets both taxonomies may be contained in.
1st Taxonomy

The ICD is an international classification that is internationally well-known system of classification that has been produced and is being sustained by the WHO. It is a thorough framework for categorizing diseases, illness or any health-related issues and conditions. The ICD then makes it easy for recording, analyzing and reporting of health information throughout the world (Harrison et al., 2021). It acts also as a medium for communication between many different players in the field such as healthcare professionals, academics and policy makers to refer to the condition of health both across different geographical areas and over the period of time.

The ICD is widely utilized and applied in health care particularly for different uses. It is basic for medical billing and reimbursement since health care providers write diagnosis utilizing ICD codes in insurance claims. Few of the importance of these codes include; Government and public health organizations use these codes to assess the occurrence of various diseases, to follow up on epidemics, determine their severity and prepare for a likely outbreak. They also use data coded according to ICD for carrying out epidemiological research where they study the trend and result of diseases with a view of enhancing on it. In the context of a clinical use the ICD not only maintains consistency in patient record, but also allows an increased degree of integration among different providers.

Hierarchical structure of the proposed taxonomy is given much thought in order to achieve both precision and practicability. HSC is further divided into chapters they contain general classifications of diseases like Infectious diseases or Mental diseases, within the chapter’s disease is divided into blocks of similar diseases (Harrison et al., 2021). Every condition has an alphanumeric code, for example, the code for typhoid fever is A01.0. It gives health care professionals the facility to record certain conditions on this specific structure while still putting it in tune with broader health classifications. ICD-11 has better digital accompaniments or support systems and higher degree of detail in classification to address changing health care requirements.

ICD plays an important role to enhance the overall health care system of the world because of the interoperability and standardization views. It makes transfer of data between health systems possible enabling the systems in decision making and resource management. It allows for maintenance of straightforward records of health conditions, which in return, strengthens evidenced-based practice, enhances patient centered care and shapes public health policies. By accommodating these advances in medicine practice, it guarantees itself a place among the basic tools that can be used to help the world solve current and future health challenges.

2nd Taxonomy
The Integrated Taxonomy of Health Care (ITHC) is a vertical taxonomy that classifies health care techniques, modalities, domains, systems, and integrative health care. The ITHC was developed through three stages: Creating a uniform health glossary, analyzing existing taxonomies, and Classifying modalities and medical systems into categories. Integrative taxonomy considers many traits for species delimitation and this process enhances the knowledge about the evolutionary processes driving their speciation. Taxonomy codes are used by healthcare providers to self-identify their specialty based on which taxonomy code best matches their specialty. The Health Care Provider Taxonomy code set is a collection of unique alphanumeric codes, ten characters in length.
The Integrated Taxonomy of Health Care (ITHC) is a classification system designed to categorize both conventional biomedical practices and complementary and alternative medicine (CAM) modalities under a single, unified framework, allowing for consistent comparison and analysis across different healthcare approaches; it is essentially a structured way to organize and label diverse healthcare practices, making it easier to study and understand their relationships within the broader healthcare landscape.
The ITHC aims to classify all healthcare practices, including both mainstream medical treatments and CAM therapies, under one system, eliminating the need for separate classification systems for each domain.
The taxonomy is organized into distinct levels, starting with broad categories and progressively narrowing down to specific modalities, allowing for detailed analysis of different practices within their respective domains. The ITHC uses a standardized set of criteria to classify healthcare practices, minimizing subjective interpretation and ensuring consistency in application.

part 2

Respond to the following in a minimum of 175 words:
Evidence-based practice is built on research, best practices, and patient outcomes. This creates a body of evidence to support clinical interventions, treatments, and care plans. The process of analyzing data and reviewing evidence-based practice and research will help an organization grow and improve without reinventing the wheel.
What are the benefits and challenges of evidence-based practice in health care?
What kinds of data are needed for evidence-based practice? For example, what data might support post-operative care choices?
What is your stance on evidence-based practice? Explain.
part 3
write a feedback for the following posts based on part 2
post 1
EBP used to be done by researchers over a period of 17 years. This process was too lengthy and was refined to focus on outcomes. OCR aka outcomes research focuses on measurable outcomes that ensure treatments that provide quality care, promote well-being and are cost effective.
EBP requires data such as patient demographics, outcomes and efficacy of treatment, and cost-effectiveness. Regarding postoperative care, data entails pain management efficacy, infection rates, recovery times, and patient satisfaction.
EBP has been challenging over the years as many organizations implemented different scales that were inconsistent leading to confusion. To combat this, a group was formed called GRADE. This group created an algorithm to streamline EBP research which rates evidence in levels from high to very low. Subsequently other groups such as AACN, EPC, and SORT all adopted grading scales for evidence.
Another challenge for EBP is implementation of said evidence. Various models exist to implement the use of EBP. Resistance can be a barrier to this change, therefore including those who are to be impacted helps the process along.
I support and promote EBP for my colleagues and patients. Research is necessary to support optimum outcomes. EBP helps support fellow colleagues in decision-making for their patients and helps patients understand the treatments.
Hebda, T., & Rose, M. (2024). Handbook of Informatics for Nurses & Healthcare Professionals (7th ed.). Pearson.
post 2
Evidence-based practice (EBP) offers many benefits, including improved patient outcomes and standardized care. By using the latest research and best practices, healthcare providers can deliver more effective, personalized treatments and reduce errors. EBP also helps healthcare organizations stay current and improve quality while lowering costs. It promotes a culture of continuous improvement within healthcare organizations, helping them stay current with new advancements and ultimately leading to higher quality care and potentially lower costs.
However, implementing EBP comes with challenges. It requires healthcare providers to access and apply up-to-date research, which can be time-consuming and overwhelming. Resistance to change from staff and the need for proper training can also be barriers.

For EBP to work, healthcare providers need various types of data, such as patient health records, clinical studies, and outcome data. In post-operative care, for example, data on recovery times, complications, and patient satisfaction can help guide decisions on pain management and follow-up care.

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