Week 1 Project Over The Next Four Weeks You Will Review
Week 1 Projectover The Next Four Weeks You Will Review And Analyze A
Over the next four weeks, you will review and analyze a pre-intervention elementary school asthma database from a community that has four elementary schools. Each week, you will write a short paper describing the role of an informatician in regard to data capture and use within the Public Health Information Management Systems (PHIS) and Public Health Information Network (PHIN). You will explore the data elements, database technologies, analytics, and processes used by an informatician including data capture, scrubbing, coding, warehousing, managing, and reporting of public health information. In Week 5, you will complete a comprehensive term paper and PowerPoint presentation that demonstrates a public health needs assessment using your primary asthma source data.
Your paper and presentation should show why an asthma prevention intervention program is needed in the selected community and summarize how you came to your conclusions. The objective of this five-week project is for you to demonstrate the processes used in public health informatics through its application. You will begin your course project by explaining how data is collected, scrubbed, coded, and stored within the PHIS. You will then explain how data is organized in databases, using the asthma data provided below. You will describe the data elements in the spreadsheet and the processes of an informatician by answering the questions below.
Click here to download the asthma data for 2013. Note: Use this Excel spreadsheet throughout the course to complete your weekly data analyses and prepare your written assignments as they relate to public health informatics. Your weekly assignments will provide data to support your final term paper to be submitted in Week 5. Based on the data in the spreadsheet, prepare a 3–4-page paper addressing the following questions:
Introduction:
How is information collected, organized, scrubbed, coded, and entered into the PHIS?
Asthma Database Analyses:
Describe the structural organization of your database.
What is the survey population description?
Define pre-intervention
Define a database record. How many records are in your database?
Define a database field. How many fields are in your database?
Define a database field data definition (DD). What is an example in this database of a DD?
Based on the data collected, what is the purpose and potential use of this asthma survey data?
Summary:
From the perspective of an informatician, discuss the asthma database’s key structural components, its organization, and potential uses.
Submission Details: Give reasons and examples in support of your responses.
Cite all sources using APA format. Submit a 3–4-page paper in a Microsoft Word document to the Submissions Area by the due date assigned. Name your document SU_PHE6203_W1_A3_LastName_FirstInitial.doc
Paper For Above instruction
The collection and management of data within public health systems are critical components for effective disease surveillance, intervention planning, and policy development. In the context of pediatric asthma, particularly within elementary school populations, robust data management enables health informaticians to track prevalence, identify at-risk populations, and evaluate intervention outcomes. This paper discusses the processes involved in data collection, organization, scrubbing, coding, and database structuring within the Public Health Information System (PHIS), specifically analyzing an asthma database from a community with four elementary schools.
Data collection in public health settings involves gathering information from various sources such as healthcare providers, school health records, and parental reports. In this case, data related to asthma incidences, hospital visits, medication use, and demographic variables are obtained via surveys administered in elementary schools. Once collected, data are organized into a structured format—typically spreadsheets or electronic databases—where data sanitation (or scrubbing) ensures accuracy and completeness by removing duplicates, correcting errors, and standardizing entries. Coding transforms raw data into standardized formats, such as ICD codes for asthma, which facilitate comparison and analysis. This information is then entered into the PHIS, where it is stored securely for further analysis and reporting.
The structural organization of the asthma database is designed to facilitate easy access, analysis, and reporting. Generally, it comprises a table with multiple records, each representing an individual student's data. The database includes various fields such as student ID, age, gender, asthma diagnosis status, hospital visits, medication adherence, and environmental factors. The total number of records depends on the survey population, which in this case, reflects the student population within the four elementary schools, possibly numbering in the hundreds or thousands.
A database record in this context refers to a single unit of data representing a student’s health profile regarding asthma. Each record contains multiple fields—data points such as age, gender, diagnostic codes, and visit dates—that collectively provide a comprehensive picture of each student's health status related to asthma. For example, the student ID uniquely identifies each record, while other fields like 'Asthma Diagnosis' (coded as yes/no) and 'Number of hospital visits' provide health insights. The total number of fields may vary but typically includes demographic, clinical, and environmental data, often numbering between 15-25 fields.
A database field data definition (DD) specifies the type and format of data stored in each field. An example from the asthma database could be the 'Age' field, defined as an integer representing the student's age in years, or 'Asthma Diagnosis,' a binary field coded as 0 (no) or 1 (yes). Clearly defining each field ensures data consistency, accuracy, and ease of analysis.
The purpose of this asthma survey data is to monitor the prevalence and severity of asthma among elementary school children, assess environmental and behavioral risk factors, and evaluate the effectiveness of interventions. Potential uses include identifying high-risk subpopulations, informing targeted educational campaigns, guiding resource allocation, and evaluating the impact of public health initiatives over time. For example, if data indicate higher asthma rates among children exposed to indoor allergens, interventions such as environmental modifications can be prioritized.
From the perspective of an informatician, the key structural components of the asthma database include the data fields, data types, relational links (if any), and storage formats. The organization ensures that data are coherent, interoperable, and accessible for analysis. Proper organization enables efficient querying, reporting, and integration with other public health datasets. The database’s potential uses extend beyond epidemiological monitoring to include research, policy development, and real-time surveillance, providing insights that can drive community-specific intervention programs and health policies.
References
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