ELEMENTS OF SYSTEM ASSESSMENT

Posted by Winnie Melda on February 19th, 2019

Plan for assessing the EHR system
The commitment of the healthcare industry is to improve the safety of patients, attain cost-effectiveness and improve the quality of healthcare. The industry has also seen the importance of prioritizing the implementation of the Electronic Health Record (EHR) because it is a tool that will contribute to the achievement of the goals. The goal to improve healthcare quality depends on identifying, promoting and developing of solutions to central issues that affect healthcare service. It also means that the electronic health data should be accurate for use in research.
Other elements needed for improving healthcare services include stakeholder engagement, ethical and regulatory issue; data quality and data standards; interactions of the healthcare system; patient reported outcome and study design and biostatistics. These core aspects have bidirectional objectives that promote the exchange of information on approaches and methods. The main goal is to ensure that patients and healthcare providers can make the best decisions according to the available and best clinical evidence (Waton, 2005).
What is electronic health record?
The electronic health record (EHR) is the paper chart of patients but in a digital version. EHRs provide real-time and patient-centered records that ensure the instant availability of patient information and the transmission of this information in a secure manner to the authorized users. The EHR contain treatment and medical histories of patients, but the EHR system is designed to go beyond the standard collection of clinical data by the provider’s office. It also includes a broad view of care for patients. Thus, the EHRs can streamline and automated provider workflow. It enables evidence -based tools to be accessed so that providers can use the information to decide on the best care for patients. Lastly, the EHRs contain the medical history of patients, their diagnosis, treatment plans, and medications. Other aspects are allergies, immunization dates, test and laboratory results, radiology images and allergic reactions (Davidson, Lee, & Wang, 2004).
Assessment of the electronic health record (EHR) Systems
Scientific questions on a given study rely on the generated data from care routines and the collection of data. Thus, assessment of such studies and data quality assurance do include the methods for the situations like using data from routine care in which the researcher has no influence or control of the collected data. It can also be the case where the researcher can control or influence data from the original collection. Whatever the case, data accuracy found in the EHR system has to be accurate and up-to-date. The data also has to show completeness that are the assessment elements in health-based research. The five dimensions for assessment of electronic healthcare record data used for research purpose are correctness; completeness; currency; plausibility; and concordance.
The system assessment elements are critical in conducting health-related research. For example consistency, completeness and accuracy have an impact on the data’s capacity to support the conclusions of the research and are therefore the necessary elements for assessment (Amatayakul,2005).
Completeness means the availability of the necessary data such as the percentage of missing values, percentages of sufficient data in a record. Accuracy is also another aspect that shows the closeness of an agreement between the true value and data value. The data value percentage in an error measurement by the gold standard. Others are percentages of data values that are not within the expected range. Lastly is the percentage of the physically implausible values. Consistency means the relevant uniformity of data across facilities, clinical sites of investigation and among the units of providers, facilities, and other assessors. Thus, the goal of consistency assessment is to find comparable relevant diagnosis portions across sites or from procurement reports (Lee, 2006).
Thus, data quality is the criteria I will use to assess the EHR System. The quality of data is the level to which the inherent set of characteristics fulfills certain requirements of data. Thus, for my assessment, I will subscribe to data quality in a multidimensional conceptualization. The inherent characteristics are the veracious dimensions of data quality. These characteristics include aspects such as completeness, timeliness, contemporaneity, relevance and accessibility (Blair, 2006).
Plan implementation
For the implementation of my assessment, I plan to establish the multidimensional data quality conceptualization for more than 200 dimensions across various organizations being surveyed from various industries. However, with the limited time and expensive budget, I will narrow down the dimensions to a handful of them which I find important in my assessment and measure of the system. The measured dimensions for data quality assessment are those that are necessary for showing the fitness of data to specific issues. Overall, data quality assessment is by identifying the vital dimensions such as accuracy, relevance, timeliness, completeness, contemporaneity, and accessibility. I will also measure these dimensions; the review criteria will involve the following:
Criterion 1: are the methods of data collection properly validated?
Criterion 2: what will be the validated methods for EHR information?
Criterion 3; is the plan adequate for data control in trial phase
Criterion 4: does it demonstrate quality harmonization and assurance of data elements
across healthcare sites and systems.

References
Amatayakul, Margret. “HER Assess Readiness First.” Healthcare Financial Management 59, no. 5 (May 2005): 112–113.
Blair, Robin. “Worth the Wait.” Healthcare Management Technology 26, no. 1(Jan 2006): 48–50.
Davidson B, Lee WY, Wang R (2004). Data production maps development for meeting the discharge of patients and submission requirements. Journal of International Healthcare Management and Technology. 6:223–240. 2.
Lee Y, Pipino L Wang R and Funk, J. Journey to Data Quality. Cambridge, MA: MIT Press; 2006.
Watson, Kathleen. “Tap, Tap, Tap to Better Patient Documentation Technology in Health Management. 26, 11, 16–18.

Sherry Roberts is the author of this paper. A senior editor at MeldaResearch.Com in custom essay paper writing if you need a similar paper you can place your order from custom research paper services.