| Course | HIM 550 Data Management and Data Quality |
|---|---|
| Module | Module 2 |
| Paper type | graduate reflective journal tracing a data element through its life cycle |
| Length | About 400 words, 3 pages |
| Format | APA 7 student paper |
| School | Southern New Hampshire University |
| Program | MS Health Information Management |
| Updated | September 2026 |
Free sample paper for HIM 550 Module 2
Module Two Journal
One Small Field, Many Owners
This week I chose one field and followed it everywhere it goes: admission source, which records whether a patient arrived from home, a clinic, another hospital, a skilled nursing facility or somewhere else. It seemed too small to matter. At Cypress Hollow Medical Center it is blank on 12% of admissions, and until this week I did not know who would notice.
The field is created by registrars in the emergency department and admitting office, who choose from a list while also verifying insurance, scanning identification and answering phones. On busy nights, the field is skipped, because nothing stops the registration from completing without it. From there it is stored in the registration system, copied into the clinical record and loaded each night into the data warehouse.
Then it is used in more places than I expected. Quality staff rely on it to exclude patients transferred from other hospitals from certain measures. Case management uses it to plan returns to nursing facilities. The transfer center uses it to count incoming transfers for regional planning. And it is part of the hospital's discharge data submission to the state, which feeds public reports. Weiskopf and Weng (2013) found that record data are usually judged by whether they are complete, correct and current enough for a particular reuse, and admission source fails the completeness test for every one of these reuses at once. Kahn et al. (2016) describe completeness as one of the core dimensions of data quality, but I had never before connected a blank field to so many downstream decisions.
The warehouse made things worse, and I had missed it for years. When the warehouse was built, blank values were loaded as a category called Other, so reports show a large Other group rather than missing data. Chute et al. (2010) described how an integrated warehouse must preserve the meaning of source data through the loading process, and ours quietly changed it.
I am proposing two changes. Admission source will become required at registration, with a short list and help text, and the warehouse will load blanks as Missing rather than Other so reports show the real gap. I also realized that no one owns this field; it belongs to registration, quality, case management and analytics all at once. Of everything I learned this week, that gap in ownership worries me most.
References
Chute, C. G., Beck, S. A., Fisk, T. B., & Mohr, D. N. (2010). The Enterprise Data Trust at Mayo Clinic: A semantically integrated warehouse of biomedical data. Journal of the American Medical Informatics Association, 17(2), 131-135. https://doi.org/10.1136/jamia.2009.002691
Kahn, M. G., Callahan, T. J., Barnard, J., Bauck, A. E., Brown, J., Davidson, B. N., Estiri, H., Goerg, C., Holve, E., Johnson, S. G., Liaw, S.-T., Hamilton-Lopez, M., Meeker, D., Ong, T. C., Ryan, P., Shang, N., Weiskopf, N. G., Weng, C., Zozus, M. N., & Schilling, L. (2016). A harmonized data quality assessment terminology and framework for the secondary use of electronic health record data. eGEMs, 4(1), Article 1244. https://doi.org/10.13063/2327-9214.1244
Weiskopf, N. G., & Weng, C. (2013). Methods and dimensions of electronic health record data quality assessment: Enabling reuse for clinical research. Journal of the American Medical Informatics Association, 20(1), 144-151. https://doi.org/10.1136/amiajnl-2011-000681
What the HIM 550 Module 2 instructions ask for
The second HIM 550 module asks you to journal about the data life cycle in your own setting. Pick one data element and follow it from creation through storage, use, sharing, retention and disposal. Keep the entry to roughly a page or a little more, personal in tone, with a few sources in APA 7 where they help explain what you saw. Describe who creates the element and under what conditions, where it is stored and copied, every use you can find and what happens to it at the end of its life. Reflect honestly on what surprised you, especially uses you did not know about, and close with the changes you would propose and who should own the element.
How this HIM 550 Module 2 journal example is built
The data manager at Cypress Hollow Medical Center follows admission source, blank on 12% of admissions, from busy registrars through the registration system and record to the nightly warehouse load. Uses turn up in quality exclusions, case management, the transfer center and a state discharge data submission. Weiskopf and Weng's focus on fitness for reuse and Kahn and colleagues' completeness dimension explain why one blank field fails every downstream use, while Chute and colleagues' point about preserving meaning exposes a warehouse that turned blanks into Other. The HIM 550 journal ends with a required field, honest Missing values and the discovery that no one owns the element. Its closing lines hand the question of a steward to the data governance group.
Where the HIM 550 Module 2 rubric puts the points
Life cycle journals in HIM 550 tend to be judged on a specific element followed through every stage, honest reflection on surprises, accurate use of data quality and data management concepts, research that explains rather than decorates, practical proposals and clear, personal writing. Journals that stand out find downstream uses the writer had not known and show how a problem at creation spreads. Graders reward attention to what happens inside warehouses and extracts, since that is where meaning is often changed without anyone noticing. Naming the ownership question, not only the technical fix, shows the governance thinking the course builds toward. A short note on how the element is disposed of, or whether it ever is, completes the cycle.
HIM 550 Module 2 help: the mistakes that cost points
HIM 550 journals lose credit when they describe the life cycle in textbook terms without following a real element, list stages without uses, skip reflection or propose fixes that only clean reports. Some drafts also forget storage and transformation steps, where much data damage occurs. If your prompt asks you to reflect on a different topic, such as your organization's data management maturity or a data problem you faced at work, share the prompt and the journal will address it in the same personal, evidence-supported style. Mention your role so the element chosen fits your work. HIM 550 journals we write follow one element from creation to disposal and end with ownership.
Get HIM 550 Module 2 written to your instructions
Send the HIM 550 Module 2 journal prompt and a data element you work with. The entry will follow it from creation to disposal, uncover the places it is used, reflect honestly on what surprised you and propose practical changes and an owner, turned around in 24 to 48 hours, the first request free. The paper above is an original model document written by our desk, not a submitted student paper and not an official Southern New Hampshire University document.
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HIM 550 Module 2 questions, answered
Where can I find a free HIM 550 Module 2 Journal sample?
This page holds the whole HIM 550 Module 2 journal: following admission source from registration to warehouse to state submission, and what it revealed.
What are the stages of the data life cycle?
Creation or collection, storage, use, sharing, retention and disposal, with transformation often happening between storage and use.
Why can one missing field matter so much?
A single field may feed quality measures, operations, planning and external submissions, so a gap at entry spreads to every use.
How can a data warehouse change the meaning of data?
Loading rules may convert blanks to a default category or recode values, hiding gaps unless the rules are documented and reviewed.
Who should own a shared data element?
A named data steward accountable for its definition and quality, coordinating with every department that uses it.