Improving Data Collection in Health Information Systems Report

This report focuses on data collection within health information systems, emphasizing the importance of data quality. It begins by highlighting the significance of upgrading health information systems to record patient and employee data. A detailed discussion on data quality standards, including accuracy, validity, reliability, relevance, and security, is provided. The report suggests improvements to the data collection process, such as using printed forms for patients and implementing a database administrator for system maintenance. It also proposes changes to the data dictionary, including breaking down the name field, organizing address fields, and modifying date formats for better data organization. The report concludes by emphasizing the creation of a Master Patient Index (MPI) system to centralize health and personal information within the health service organization, ensuring easy access when needed. The report provides an updated data dictionary table and references relevant literature supporting the analysis.

Running head: DATA COLLECTION IN HEALTH INFORMATION SYSTEM
Data Collection in Health Information System
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DATA COLLECTION IN HEALTH INFORMATION SYSTEM
Importance of Data Collection in Health Information System
In the health industry, information system up-gradation is a major booming factor
nowadays. It records all data and information of patients and other relevant employees and
tasks (Bowman 2013). A data dictionary is a tabular framework that is used to guide the
process of data collection and storage with proper data types and other necessary parameters.
Data Quality Standards
The system of data or information collection must adhere to the data quality standards
in order to improve as a whole. The data dictionary that has been provided needs numerous
amendments to be considered as a valid data dictionary for the health IT storage process.
Guptill and Morisson (2013), states that the information stored in the system must abide by
the following quality standards:
Accuracy: Data about every patient must be stored with utter precision and accuracy. Every
details of the health records and personal information must be completely collected and noted
down in the database. Accurate information would help in the analytics and hence improve
services (Chib, van Velthoven and Car).
 Validity: Data must be checked for validity before committing to the database
permanently. This must be done either manually or through artificial intelligent (AI)
methods. Manual cross checking of stored data would help spot out the errors but
would be time consuming whereas AI modules that can check uploaded documents
for validity with the database records would provide faster means to store and access
valid data.

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DATA COLLECTION IN HEALTH INFORMATION SYSTEM
 Reliability: The data collection process must be ensure reliability among the patients
and all other stakeholders. They must all be satisfied with the process of data
collection and thus heavily endow trust on the information system.
 Relevance and security: The data stored in the system must be secured using proper
means. The data must also be used for only relevant purposes. Unauthorized access of
health related data must be prohibited as it can prove to be fatal (Murdoch and Detsky
2013).
The above mentioned data quality standards shall be further used in the following
sections, in order to make changes to the data dictionary that has been provided.
Improve Data collection
The data collection method should one such that it ensures reliability as mentioned in
the data quality standards. In this case, printed forms are to be handed to patient parties and
they shall be asked to fill up the respective required data slots. They must also provide
necessary proofs wherever required by the management. On submission of these forms,
respective database handler employees shall check for the validity of the information entered
and add other required information before submitting the data over to the database handler
team. There, they shall carefully input each data entries into respective fields into the
computer-server database. A database administrator must be in charge of the entire system
and in the maintenance of security and integrity, as health information privacy is essectial
(Wilkowska and Ziefle). The patient parties shall be allowed to view their updated personal
information anytime from the online portal, by entering a unique consumer ID that would be
generated against the submission of valid documents.
Changes to the Data Dictionary

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DATA COLLECTION IN HEALTH INFORMATION SYSTEM
The Name field must be broken down into three separate components namely First
name, Middle name and Last name, with each having alphabetical data types and a limit of up
to 15 characters only.
The Address data field must also be categorized into House Number, Street, State,
City and Pin Code. This would allow the users to enter their address in an organized manner
and the database shall have a common layout for the address entered by all. The respective
data type and character length will be presented in the table below.
Admission Date field should come before the Discharge Date field. This provides a
more meaningful way to store the data. The data type should also be changed to Date with
MM/DD/YYYY format, to ensure that the years are entered completely, thus maintain data
accuracy.
The Discharge Disposition field is perfectly represented in the provided table,
however there must be a separate data description table allocated that defines the meaning of
each of the codes used here. This would bring in data validity.
The Date of Birth field must move higher up the order and must be in the date format
as mentioned earlier. The Gender field too must move up and stick to other personal
information sections.
Apart from the Services field, there must also be another Doctor’s Remarks field
where the regular remarks from the doctors about the respective patients must be stored for
later references.
There is no necessity for the Race field. It is an unnecessary addition to the table and
must be removed at once. Fields such as these downgrade the quality of the system and data
can be misused.

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DATA COLLECTION IN HEALTH INFORMATION SYSTEM
Data collected in this manner would hence help to create the MPI system, where all
health related and personal information would be available within the health service
organization and can be accessed whenever needed.
The Updated Data Dictionary
Field Type Character length or
format
First Name Alphabetical 15
Middle Name Alphabetical 15
Last Name Alphabetical 15
Date of Birth Date MM/DD/YYYY
Gender Character 01
House Number Alpha-Numeric 05
Street Alphabetical 45
City Alphabetical 10
State Alphabetical 15
Pin code Numeric 05
Admission Date Date MM/DD/YYYY
Discharge Date Date MM/DD/YYYY
Discharge Disposition Numeric 02
Services Alphabetical 20
Doctor’s Name Alphabetical 45

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DATA COLLECTION IN HEALTH INFORMATION SYSTEM
Doctor’s Remarks Alphabetical 500
Medical Prescriptions File Attachment PDF, JPEG.