Health Care Informantics

Health Care Informatics- Quality and Safety in Clinical Information Systems
Name
Institutional Affiliation
Health Care Informatics- Quality and Safety in Clinical Information Systems
Abstract
Clinical information systems (CIS) with their application through electronic health records present pertinent information that drives the course of diagnosis and medication. Doctors rely on the records to complement the diagnosis and prescription processes towards improving the health and the outcomes of the patients. The analysis thus begins from the point of interpreting data and information which are the components of the DIKW pyramid with the inclusion of knowledge and wisdom as their respective derivatives. The operations in a health care system largely depend on the presentation of accurate data, not only on the patient but also on the condition and its existent management procedures. Thus, the backdrop of understanding data, information, knowledge, and wisdom create the foundation for the analysis of ‘standardize terminology,’ as applied in the healthcare settings. Application of the terms in a medical setting provides input for recommendation and conclusion. The application situation includes the need for ensuring positive medical outcomes in the patients. The positive outcome of interest in the report is the outcome of adherence to medical regimen, which is important for the recovery of the patient. Adherence to medical regimen focuses on prescription drugs that are subject to under-dosing or over-dosing with negative implications to the health of the patient.

Introduction
In healthcare operations, interaction occurs across different individuals, cultures, and technologies. Since medical conditions, as well as their manifestations, are universal, it is important for the unification of information to ensure that different individuals and technologies can share, integrate and understand different formats of data that include medical data and information in a healthcare setting. The terminology for the unification of data and operation as well as information sharing among separate entities is ‘standardized terminology’ (Coenen, 2003).
On the other hand, data consists of material and statistics gathered for research and analysis. Subsequently, the outcome of processing and organizing information results in the development of knowledge. Knowledge is, therefore, data that has been processed, organized and analyzed. Finally, while information is similar to data in the sense that they both represent material and statistics gathered for analysis, the fundamental difference between data and information is that information represents material and statistics that are useful (Staggers, 2002). The high point of all the terminologies is wisdom which represents evaluated understanding.
The relationship of the terminologies that are described as data, information, knowledge, and wisdom in the context of the DIKW pyramid which is an acronym for the same elements that follows the respective orders in the model pyramid. The model represents the structural and functional association between the different classes. Subsequently, the definition of information is regarding data, while the understanding of knowledge is in the context of information. Further, the analysis of wisdom relies on the knowledge available from preceding data and information. Wisdom is thus, a derivative of knowledge in which the individual applying the concept or the user places knowledge in the level of the application while answering the question of ‘why’ in the application process. It is vital to note that knowledge is the by-product of the analysis of data and information. Therefore, wisdom represents the ultimate application of the two aspects. Although standardized terminology does not form part of the DIKW pyramid, its basis for coordinating communication processes as well as the available technologies makes standardized terminology a prominent outcome in the combination of the elements that form part of the DIKW pyramid.
The delivery of healthcare is a complex process that consolidates the interaction of human resource and technology. The process of healthcare delivery is complex to the extent that small errors result in unintended adverse consequences that include under-dosing or over-dosing in addition to the failure of detecting serious complications and illnesses as well as delays in treatment. The complexity of the healthcare process also exists in the unique nature of individuals and their presentation of medical conditions as well as reaction to medications. It is very rare to find two individuals who present with similar reactions to a medication or disease symptoms. The reason lies in the unique physiology and psychology of the patient that allows them to process body and foreign chemicals and compounds in different manners to elicit unique outcomes.
Healthcare informatics through the clinical information systems (CIS) along with the integration of technology and human resource attempts to minimize the medical errors along with their cost to human life and productivity (Staggers, 2002). Further, the processes are used for the healthcare facilities which also operate as business settings through the prevention of lawsuits that result from perceived negligence on the side of the healthcare professionals who include physicians, nurses and other health workers and attendants (Rutherford, 2008). The hospitals that implement effective data collection and processing therefore not only save the lives of their patients but also save the finances of their organizations through the prevention of lawsuits.
Therefore, the combination of the elements of DIKW pyramid with standardized terminology is important for effective communication between the individuals that form part of the human resource in the healthcare setting with the interactions of technology to ensure patient safety and positive outcomes. Subsequently, the physicians and nurses in addition to other healthcare providers utilize the process in understanding each other and working with the existing technologies in healthcare provision (Rutherford, 2008). Clinical information systems (CIS) with their application through electronic health records present pertinent information that drives the course of diagnosis and medication. Doctors rely on the records to complement the diagnosis and prescription processes towards improving the health and the outcomes of the patients.
Evidence
The patient group of interest in the evidence-based analysis constitutes the elderly individuals as the patient group. In old age, the body becomes susceptible to a myriad of ailments that are exuberated with the weakening immune system. Subsequently, it is common to find a single elderly patient with several prescription medications. The need for constant medication makes adherence to medication regime a significant patient outcome for the analysis (Bowman, 2013). While most families consider placing their elderly members in a nursing home for care, other elderly individuals have limited financial means to remain in the homes. The result is their staying on their own or in the company of family members. The latter group of out-of-nursing homes elderly individuals represents the setting for the analysis.
Effective dosing is crucial to prevent the contraindications of under-dosing and over-dosing. Adherence to the medical regime is the situation in which the patient takes their medication according to the prescription and on time. The process will ensure consistent disease eradication along with the elimination of various symptoms. Thus, while the healthcare management system and processes work hard to ensure that the patient received optimal care, the lack of adherence to the medication regime causes the drugs to have minimal to zero impact on the condition and symptoms of the patient. Thus, adherence to medication regime is crucial to ensuring that the combined efforts of the healthcare professions and the available technologies, through the consolidation of DIKW elements with standardized terminology work toward ensuring positive health outcomes to the patients and their families. The outcomes extend to national implications with the efficient use of medical finances and aid as well as ensuring that the population is in good health for continued productivity.
The discrete point of data collection for the analysis of the patient outcome of ‘adherence to medication regime’ is through the nursing homes representatives for the elderly patient. The point is important because it provides information on the value of adhering to medication regimes for the patient who is under constant supervision. The supervision by trained personnel and health care profession ensures that the elderly individuals take their medications at the right time as their physicians prescribed, and in the correct doses. The assumption in this situation is that the nursing homes have efficient personnel who will ensure that all the elderly patients’ take their medications in the required dosage and also at the right time. On the other hand, the second discrete data point on the patient outcomes is the reports from social workers whose role is to occasionally monitor the wellbeing of the elderly individuals who are not in the care of nursing home professionals. The individuals either live alone in seclusion or with family members who cater for their needs depending on the existing relationships in their lives.
The discreet data points ultimately contribute to the Clinical Information System (CIS) database by providing information that is crucial in the care and support of the patients in addition to ensuring the integrity of the healthcare facilities and the medical practitioners working in the said facilities. The CIS represents a technology-based model whose application is at the point of care with provision for processing and storage of the data to contribute to the centralized repository information (Staggers, 2002). The centralized repository information provides a basis for the operation of all healthcare providers who will have access to the patients’ records, data, and history to contribute to diagnosis and prescriptions. Both the social work system and the nursing home system will provide the discreet data points during analysis as well as the evaluation of their patients in addition to the related health outcomes.
As indicated in the previous segment the process of data collection in the two separate points will feed the CIS system in the healthcare facilities with patients’ records, data, and history. The history represents the medical history of the patient that includes on-going medication and previous procedures, in addition to the family history that presents conditions that predispose the patient to certain risks. Processing and aggregating the information along with analysis will consolidate patient data to contribute in diagnosis and prescriptions even when the patient visits different healthcare practitioners or is subjected to the assistance of different nurses and physicians (Rutherford, 2008). Having the history of a patient reveals not only risk factors such as obesity but also determined the predisposing situations to various medical conditions such as a family history of cancer.
On the other hand, the process of diagnosis relies on understanding the different medications that the patient is using as well as their contraindication before introducing a new drug. Further, the data from the patient will inform the healthcare provider on the existence of allergic reactions to medication, which are often forgotten by some elderly patients. The patient records and history as contained in CIS will thus ensure quality through effective diagnosis and prescription for the patient (Bowman, 2013). Administrators and policymakers in the healthcare system can also benefit from the information by learning what works for their clients and what does not work. For instance, while the system focuses on the competency of the doctors to ensure desired health outcomes for the patient, the knowledge that adherence to the medical regime is as much the responsibility of the patient as it is for the doctor will help in formulating remedies for non-compliance. The remedies can include diligent follow-up for the patients’ who stay with families or on their own to ensure that they adhere to medical regimes.
Evaluation and Recommendations
The focus of the context in the analysis was the realization of patient outcomes in ‘adhering to medical regimen’ from data available through the networks of social workers and nursing homes. According to the context, the data is relayed to health care providers who store it in the through the clinical information systems (CIS) that include the electronic health records (EHR) for the patients (Thurston, 2014). The channel of information that follows the DIKW pyramid of data, information, knowledge, and wisdom incorporates into the standardized terminology to ensure that the information available for different health practitioners is relevant to individual patients as well as the context of medical provision (Coenen, 2003).
From the perspective above, it is evident that the CIS through the channels indicated can provide data that is relevant to a medical situation as well as useful in diagnosis, treatment, and prescription. While the perspective provides the ideal situation for data and information collection as well as processing, the situation in the healthcare systems presents various limitations. One item that s overlooked is the timeliness of the data and health records.
In an illustration, a situation may arise in which the details of the patient are out-dated and thus, redundant in complementing a medical process. The failure of the health care system through its CIS to update the patient information may impact patient safety and hinder positive patient outcomes. Therefore, the health care system should look into regular updating of patient information so that the diagnosis processes and treatments are accurate as well as being effective in alleviating an ailment and the related symptoms. A second suggestion is for the health care system to incorporate the regular contribution of family members and certified caregivers who are well versed with the living situation of the patient, particularly in elderly patients whose memory sometimes is limited.
Summary
In the process of describing the use of clinical information systems (CIS) towards the support of patient data, the topic selection along with the recommendations in the analysis was useful in guiding the description and providing consistent analysis. Particularly, the DIKW pyramid along with its analysis culminated in providing the relevance of standardized terminology for the various processes within the healthcare system. Further, the recommendations in the analysis were useful in aligning the data with the available literature on the subject of clinical information systems.
Moreover, the data and terminology standards that are available through bodies such as the NIC and the ICNP in addition to the Omaha system allow nurses and healthcare professions from different settings and backgrounds to work together in addressing similar medical conditions (Coenen, 2003). Essentially, the terminology standards provide a unified set of medical terms that can be termed as a medical dictionary. Through the system, the healthcare professionals have unified descriptions for similar conditions using terms that separate medical providers in different locations can understand and apply during their daily operations of patient care.
The relevance of the unification is evident in a situation where an individual from a different health facility in different states seeks medical attention in an alternative location due to an emergency or convenience requirement. The nurses and physicians in the new location ought to understand the medical history of the patient from their previous providers, thus the relevance of the process. The terminology standards contribute to the uniform collection of data so that the information available at different settings is reproducible (Bowman, 2013). The outcome is equalized care and practice for all patients regardless of their backgrounds and global locations.
References
Bowman, S., (2013). Impact of electronic health record systems on information integrity: Quality and safety implications. Perspectives in health information management, fall 2013.
Coenen, A., (2003). The International Classification for Nursing Practice (ICNP®) Programme: Advancing a unifying framework for nursing. Online Journal of Issues in Nursing., published April 3, 2003.
Rutherford, M., (2008). Standardized nursing language: What does it mean for nursing practice? The Online Journal of Issues in Nursing, Vol. 13 No. 1. DOI: 10.3912/OJIN.Vol13No01PPT05
Staggers, N., (2002). The Evolution of definitions for nursing informatics: A critical analysis and revised definition. Journal of the American Medical Informatics Association Volume 9 Number pages 255-261
Thurston, J., (2014). Meaningful use of electronic health records. Elsevier, Inc. JNP Brief report.