Modeling and Database Design Data Modeling Database

¶ … Modeling and Database Design Data Modeling Database Design The databases significantly improve organization's ability access, share, apply relevant information. However, wealth data a database, greatly dependent design. Designing a database creates logical data relationships end Data modeling and database design Making use of database systems would benefit a health care organization as information regarding a patient can be retrieved easily and quickly Choobineh & Lo, 2004. The initial design of the database is vital to ensure that information is accurate and logical.

Patient information can be easily retrieved and shared with other professionals. Information sharing becomes easy, and health care workers can collaborate with others irrespective of location. Using different descriptions for the same data in a database will create confusion especially when the information has to be exported to another system. The database system would treat the description differently and create a new field for storing the data. This would result in confusion when the data is retrieved by other health care workers.

During the design phase, the health care workers should be consulted in order to establish their preferences and collate the information. Health care organizations have different ways of storing information. One health care facility could store its patient's names under one field while another would separate the fields into first, last, and surname. Creating a blueprint for the required data, assists the designers to create logical presentations of the data captured Mantha, 1987. Logical data relationships are vital for the database.

When users query the database they expect to receive accurate information, but in some instances there might be conflicting information because of the database design. Health care organizations use database systems for capturing and storing patient information. This ease the burden and risk of losing patient records. In case the patient needs to be referred to another facility, the organization would submit the patient's records electronically.

The receiving facility will need to have a database system similar to the one used by the sending facility in order for them to import the data. In case they have a different system the information would not be properly imported, and they would have inaccurate information. Benefits and challenges of data modeling Data modeling reduces the development time of database systems. Data modeling provides the designers and developers with a thorough understanding of the source systems.

With this understanding, the developers are able to conceptualize the system and develop the system rapidly. There is improved accuracy of the results. The designers of the database would have understood the requirements and the system will deliver results and information as required by the end users. Parsons (2002) posits that data modeling provides for increased transparency. The health care workers will have enough transparency, to enable them realize the available information.

This is beneficial as the health care workers might not be aware of the information they can retrieve from the system. Knowing that information that can be retrieved from the system would allow the health care workers to make full use of the system. In most health care organizations, workers are not aware of their systems full potential. They only make use of the simple queries, but if during the data modeling workers could be shown the extent of information they can retrieve they would appreciate the system.

If the data models are not flexible enough to accommodate future changes any small enhancement would result in a major rework of the whole system, this according to Dekleva (1992) would also result in increased costs for maintaining the system. The data models should be checked to ensure that they have the capability to be flexible in case of any future enhancements. The data models will ensure that the system meets the reporting needs of the workers.

If the system does not capture and deliver the required reports, the users will reject the system and misuse the system. Data modeling should be conducted in conjunction with the end users. Consultation will provide the modelers with information regarding the requirements for the users and the expected reports. Database design issues The case study has identified six design issues namely data problems, interoperability of the systems, poor system design, coding issues, database formatting, and use of the data received. The data received could be dirty that contains errors.

The cause of the errors could be numerous, and it is easy to avoid these errors. An organization should standardize the recording of its data. This will ensure that data from the organization will be similar, and there is no likelihood of the data containing duplicate or incomplete records. Storey and Goldstein (1993) argue the interoperability of systems is vital for the sharing of information with other organizations or departments. If systems are interoperable there will be a need to enter the same patient data, which results in multiple entries.

The lack of interoperability will result in different information for the same patient. This causes problems as the patient could be assigned a number for another patient. There is also potential of having two patients having the same data or their data been combined. The design of the system will determine its success. Data from one system could be unusable because it contains incorrect information. How dates are stored in the system is vital as a simple error in entering the date would lead to confusion in the whole system.

The same format should be used for entering dates to ensure there will be no mix up. The use of error messages is vital as this will alert the user of any problems during data entry. Error messages that users will easily understand are included within the EPIC system. This provides users with information and a chance to correct their mistakes. Systems should be coded using universally accepted codes for the different treatments. In a health care system codes are critical in determining the patient ailment.

Consistency in using the applicable codes will ensure that there is little confusion when users access the records stored in the system. Data retrieval is vital for the success of a database design. The person or user retrieving the information should understand the basics of database requirements and design. This ensures that they will extract the required data for use in a database and not for users to read. Proper planning.