High Quality Data Quality Analysis

Apply accurate, complete, and consistent coding practices for the production of high-quality of healthcare data.

It is usually presented in the form of a report in tables, charts, statistics, and graphs or on spread sheets etc. This data may be used to arrive at important decisions within the organisation or with external organisations. So the data report has to be produced in such a way that it meets the aims and

Technology: Technology can single handedly improve a data reporting system if applied properly . It can solve problems like a lack of standardization, electrical power and backup of the system. Using standalone databases without deploying standard enterprise databases that aligned data as the occur checking for accuracy and quality issues in real-time

Part 1: Recommend elements included in the design of audit trails and data quality monitoring programs

Quality is an indicator of how well the end result of the project satisfies the project management. All of the objectives specified by the project management must meet and exceed their expectations. The quality for our CRM system project will usually boil down to improved national marketing campaigns, instant access to customer data, simplified account management, enhanced lead and sales tracking, and opportunity for additional sales to current customers. The quality can also be considered by the accuracy in the scheduling and timeliness that our project was completed. The accuracy of information that is produced by our new CRM system and ease of use is another way to judge its quality. There is also the quality of hardware and software used in the project this can determine the overall quality of our new CRM system. If we used low end equipment and cheap software produced by an unknown company, and then dramatically decrease the quality of the CRM system. This will also lower the quality of information that is given from the system as well.

Precisely some of the characteristics are generally based on the main levels of quality assurance such as with accuracy, accessibility, comprehensiveness, consistency.

AHIMA. (2015). Data Standards, Data Quality, and Interoperability (Updated). Retrieved from http://Data Standards, Data Quality, and Interoperability (Updated)

Task 4 - P4 Create features in data entry forms to ensure validity and integrity of data:

The goals have been set and data analytics best practices need to be monitored. The experienced gained in this phase will shape the next course of action based on external and internal issues. As the data is formulated, it will identify the strengths and the weaknesses, threats and opportunities for improvements. Because the internal and external issues will continue

The hospital could improve the data quality by design primary models that gathered and organized key information. Make sure proper training and coordination of the system capabilities are enhance on all level of the organization chain. Make sure you have a backup system if the system seems to not be working properly or crash. Making sure the patient is overall satisfied and the providers are up to par with the technology and its usages. Make sure audits are done randomly and errors are eliminated. If any information is missing or incorrect information is update immediately.

Discuss the importance of data accuracy. Inaccurate data leads to inaccurate information. What can be some of the consequences of data inaccuracy? What can be done to ensure data accuracy? Data accuracy is important because inaccurate data leads may lead to such things as the closing down of business, it may also lead to the loosing of jobs, and it may also lead to the failure of a new product. To ensure that one’s data is accurate one may double check the data given to them, as well as has more than one person researching the data they are researching.

Data management is vital to any business as this is a key tool to an organisations business improvement, as you can refer back to data, and compare them against benchmarks. Analysing data can provide evidence for possible future structure such as identify trends, as well as indicate where improvements can be made. However there are strict procedures to be followed when collecting and storing data.

Improper analyzed or interpreted data can lead the decision maker to the wrong conclusions or make decisions that are based on bias rather than facts; garbage in, garbage out.

Firstly, data accuracy and reliability issues arise due to the consumer/patient being the sole responsible individual to enter and review all pertinent health information into his/her record. Patients can be

There is an accentuation on the need for quality of coded data with the use of computer-assisted coding in healthcare organizations to assure compliance is being met with regards to the increasingly multifaceted quality reporting requirements.