Paper Example on Data Types and Structures

Introduction

Aggregate data involves data which belong to several patients hence its back traction is not possible especially for the specific patient. It includes counts like diseases incidences or types of appointments. Aggregate data is normally used in the organization to get feedback for strategic planning, outside agency reposting, and quality. Aggregate data do not have protected individual patient health information because it is de-identified. It is therefore used as a tool for health population management. Aggregate data can be used to give outcome as a result of its disease feedback with an inclusion of prevention measures. It can also provide information in a population to priorities one medication over the other rather than an individual.

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Aggregate data cannot, therefore, give patient-centric information. It cannot also give feedback on the patient medication progress. It gives interventions based on statistic indicators which might help to improve the patient's health but not caring for the specific patient. The importance of aggregate data is its information which is to be shared with the organization and other agencies.

Data collected and shared with several sources result into Big Data hence can be used subsequently to in observation of trends in wellness, health, health primitive measures, and disease states including various quality indicators and interventions success. Trending data enhance healthcare monitoring and potential epidemics identification thus providing a start to natural disaster and bio-threats (Randall-Lewis &Regan, 2018).

Comparative data provides the comparison of patient vast pool data and staggering implications in terms of future healthcare. Comparative data provide ensure information compilation of many patients. Despite the fact that comparative data does not have research scientific methods, it can be used to give feedback which is tremendous in terms of effectiveness of conditions and treatment. The current methods of medications testing including other interventions prevent any practical in getting patient's sample size which is large enough in the determination of effectiveness and safety. The current clinical research has a disadvantage whereby respondent is small in number in each study, therefore, the potential treatment which is valuable has its options dismissed since the researchers could not be able to statistically detect the difference existing between the options B and A. (Cerrato, 2013).

Both aggregate data and comparative data have limited from the fact that it is not able to give specific patient information. The compared data has been de-identified for the sake of patient privacy hence can be used to return patient's group information compared to other patients group information. Comparative data is not scientific process subject. Correlations can only be given by comparative data hence may be high quality but misleading from the fact that it lacks effect and causes relationship. Comparative data is used currently in measuring of quality outcomes in healthcare. The disadvantage of the type of data collection is its timeliness. The events are always transpired before effective compilation and comparison of outcomes. The process thus requires improvement in order to ensure the healthcare system is of high quality.

Patient-centric data is effective in cases where approach which is individualized is needed. It combines data belonging from both the provider and patient with an aim of ensuring care to the certain patient. The idea was initiated from patient care focus. Patient-centric data concentrates on an individual which is vital based on tailoring care but limited to one patient experience. Unlike the comparative data and aggregate data, centric data is not extracted. Its compilation is based on the history of the patient. Patient-centric data is different in that interactions and information originate from the patient. There exist wireless technology which is configured around the patient place of stay so as to personalize data and patient prompted interactions whereby it is being managed by both provider and the patient (Scher, 2012). Patient-centric data is thus not used in comparing other things unless its extraction. It is therefore not applicable to population health.

Health record data from uniform data sets can be used in healthcare organizations whereby the patient's charts are used in treating the patient. The health providers collect data during treatment process hence use it as a guide for future individual treatment and in ensuring the information of the patient is communicated to the healthcare team. The member of staff can, therefore, access the patient's information from patient's chart provided the member goes as per the HIPPA guidelines. The information on the chart involves the surgical history, medical history, social history, patient care plan and medication. In order to enhance the transition of primary data from organization to organization, Health Information Exchange board has been formed in the entire country thus enabling accuracy and efficiency that exist among the entities.

Continuity of Care Document is another tool which is used by health organization in the transmission of patient's record part. CCD ensures increased operation by allowing physicians clinical data to send medical electronic information and ensuring the meaning is not lost especially to other providers and patients care improvement ("HL7," n.d.).The continuity of Care Document involves a summarized document which has administrative, parental clinical and patient democratic data. The interoperability is provided by The CCD hence can be transferred to enhance communication between the organization on matters pertaining to patient's information. The facilities in healthcare, however, lack safety and efficiency in transmission of information of patient electronically.

The other use of electronic health record is problem list. It is individual specific hence used in guiding the patients care. The presence of problem list allows the patient care continuity through the provision of accessible and comprehensive problem list belonging to patients in one category. The problem list in health record involves injuries, illness, and factors which affect individual health thus identification of occurrences time and resolution. It is essential communication vehicle which is used in the entire health organization (AHIMA, 2011). A problem list in some cases may be referred to as working problem list which consists of health chronic issues which are current, chronic problem list comprised of health issues which are ongoing and chart which involves the history of the patient with an inclusion of its resolution. The list is thus used by healthcare teams such as nurses, therapist, doctors, and dietitians. In the current situations, the problem lists are applied in organization's discretion internal policy provided they go as per accrediting body guidelines. Apart from problem list, medication active list is imperative part in the EHR for the data of the patient. The CMS has established a Meaningful Use measure which aid in implementation and improvement of active medication list belonging to patients so that the accuracy can be improved. Safe delivery and clinical care which is effective can be enhanced by the use of accurate records belonging to the patient. The physicians can manage well the side effects, direct the patients more effectively and ensure drug interactions avoidance by exactly knowing the patient's medications. In cases of emergency, medical records are used as the only source of patient's medication information hence ensuring the individual's care is perfected (Staroselsky et al., 2008). Throughout the continuum of care, the active medication is responsible to ensure that the patient reserve required medications and determine the patient's negative effects as a result of medications.

The other use of health records comprised of electronic charts obstruction of data into database and registries. In various study fields, a lot of effort involves primary data collection which is original by nature. The advantage of healthcare research is whereby primary data is collected so as to keep and treat individual records of patient care. Secondary data is thus aggregate data. Its extraction is through mapping individual patient's chart to a database. The database may either be external or internal. Various organizations use secondary data for different functions. Secondary data may thus be used for population health management, quality measure achievement determination, diseases index, inpatient facility stay length determination and payers and government agencies reporting. Collected secondary data is called Uniform Hospital Discharge Data Set only if the payer is Medicare. UHDDS was established by Health and Human Service (DHHS) department so as to provide reimbursement standardized schedule and thereafter compare hospital in a process of quality care implementation. Due to the fact that UHDDS has been proven, other payers have implemented it. The establishment of UHDDS was done indirectly as a result of Medicare program foundation in 1965. The federal government with their health care increase in terms of involvement noted that creation of medical coding standardized system ensured easier hospital comparison ("Admin," 2015).

UHDDS data has been widely been used to give feedback concerning the care of various ethnicities and races. The medicine institute conducted a research so as to determine the minority population of healthcare which was of lower quality. Payers, physicians, and hospitals used the data which was collected about ethnicity and race. Concerning the UHDDS the "unknown" option was for the race. To ensure that the limitation was rectified, the data collected by health research, Educational Trust which is American Hospital Association and inpatient facilities created a toolkit which was to ensure systematic data collection used in healthcare disparities assessment. The toolkit is a good resource used by the organizations which seek to improve and standardize its processes of data collection (Garvin, Jones, Washington, & Weeks, 2009).

For effective communication in regards to data collected by organization its uses and ways, the use of data dictionary is recommended. A data dictionary involves database organization. A data dictionary ensures that there is data integrity due to the implementation of data consistency elements and other terminologies which are relevant to IT health systems. The implementation of data integrity in an organization ensures that there is the presence of reliability, trustworthiness, and dependability of data (Clark, Dempster, & Solberg, 2012). The data dictionary use can be implemented to enhance interoperability that of systems and data inconsistency and continuum of care error reduction. The data dictionary is thus essential because it is a protocol that ensures the reliability of data with an inclusion of ensuring that the data is well documented so that every staff member in an organization can work and read the available health record especially when required. Time sensitivity is also another factor accompanied by the data dictionary and which should be ensured in the health record. The availability of data dictionary is of great importance to the organization hence it should be maintained and managed regularly so as to ensure improved communication across the continuum of care.

References

AHIMA. (2011). Problem List Guidance in the EHR. Retrieved from http://library.ahima.org/xpedio/groups/public/documents/ahima/bok1_049241.hcsp?dDocName=bok1_049241Cerrato, P. (2013). Can Data-Powered Co...