HIM 680 Module 10 Reflection Example

Reviewed by Delia Ravenscroft, MSN, RN

This HIM 680 Module 10 Reflection sample considers how an advanced course in classification, governance and data management changed one leader's practice. It was written for SNHU HIM 680 (HIM-680), whose tenth module invites MS Health Information Management learners to reflect on their growth before moving on. The composite writer directs data governance at a four-hospital system around Cedar Rapids, Iowa, and confesses to having started the course believing governance was mostly about forming committees. The entry describes three shifts, beginning with a single data element rather than an organization chart, treating a missing number as a design flaw rather than a staff failure and reading a low rate as a possible sign of distrust, then ends on a promise about the first quarter's figures that the writer finds uneasy.

CourseHIM 680 Advanced Topics in HIM I
ModuleModule 10
Paper typegraduate reflection on learning advanced data governance and management
LengthAbout 360 words, 3 pages
FormatAPA 7 student paper
SchoolSouthern New Hampshire University
ProgramMS Health Information Management
UpdatedOctober 2026

Free sample paper for HIM 680 Module 10

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Module Ten Reflection

I Thought Governance Was a Meeting

In my first week I drafted a governance charter with eleven committee members and no data elements. I believed that if the right people met regularly, good data would follow. Ten weeks later our council has five members, three decision rights and one definition approved, and I have learned more from following one food screening answer than from any meeting.

What this page is doingAn overbuilt first charter is set against the lean council that replaced it.
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The first shift is that I now start with a data element, not an organization chart. Tracing a single answer through eight hops showed me that 9,040 answers recorded in a month became zero in the warehouse. No charter would have found that. Kahn et al. (2016) treat quality as a question of whether data suit the job at hand, and I now see that the only way to check is to follow the data all the way to that job.

The second is that a missing number is usually a design flaw. I had assumed coders simply did not bother with social risk codes. Truong et al. (2020) showed how rare they are on national hospital claims, and at Cedar Prairie the reason turned out to be that coders never saw the screening results. When I blamed people, I proposed training. When I looked at the path, I proposed a worklist.

The third is that a low rate can mean distrust. Watching a mother answer no while her son ate the waiting room crackers changed how I read our clinic data. De Marchis et al. (2019) found that patients who had faced discrimination in health care were less comfortable with social risk documentation. Our lowest-rate clinics may be our least trusted ones, and governance has to measure that too.

What this page is doingEach of the three shifts rests on a piece of course work and a source.
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My commitment is to present the first quarter's quality measures to the chief medical officer exactly as they come out, even though complete data will almost certainly make our food insecurity rate look higher and our clinics look less consistent than the old reports did. Better data can look like worse performance. I still need to learn to explain that to executives without sounding defensive, and I have asked the population health director to co-present with me.

What this page is doingA promise that better data may look worse closes the entry.
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References

De Marchis, E. H., Hessler, D., Fichtenberg, C., Adler, N., Byhoff, E., Cohen, A. J., Doran, K. M., Ettinger de Cuba, S., Fleegler, E. W., Lewis, C. C., Lindau, S. T., Tung, E. L., Huebschmann, A. G., Prather, A. A., Raven, M., Gavin, N., Jepson, S., Johnson, W., Ochoa, E., . . . Gottlieb, L. M. (2019). Part I: A quantitative study of social risk screening acceptability in patients and caregivers. American Journal of Preventive Medicine, 57(6, Suppl. 1), S25-S37. https://doi.org/10.1016/j.amepre.2019.07.010

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

Truong, H. P., Luke, A. A., Hammond, G., Wadhera, R. K., Reidhead, M., & Joynt Maddox, K. E. (2020). Utilization of social determinants of health ICD-10 Z-codes among hospitalized patients in the United States, 2016-2017. Medical Care, 58(12), 1037-1043. https://doi.org/10.1097/MLR.0000000000001418

What the HIM 680 Module 10 instructions ask for

The final HIM 680 module asks how this advanced work on classification, governance and data management has changed what you do. A page is plenty, and a reading in APA 7 belongs only if it actually moved your thinking. Do not tour the syllabus. Pick a couple of concrete changes in how you handle data and anchor each to something you did in your milestones, a definition you tested or a path you traced. Own an assumption you arrived with that did not survive. Close with a promise someone could check, preferably one with professional risk attached, and name a skill you still need before the work can continue without you.

How this HIM 680 Module 10 reflection example is built

Cedar Prairie Health's director opens with an eleven-member charter that had no data elements and contrasts it with a five-member council, three decision rights and one approved definition. Three shifts follow: starting from a data element, after an eight-hop trace found 9,040 answers becoming zero, read through Kahn and colleagues' idea of fitness for use; treating missing codes as a design flaw, given Truong and colleagues' national figure and coders who never saw screens; and reading low rates as possible distrust, informed by De Marchis and colleagues. The HIM 680 reflection commits to reporting first-quarter measures honestly even though complete data will look worse, with the population health director co-presenting.

Where the HIM 680 Module 10 rubric puts the points

Graders of the closing HIM 680 entry reward concrete changes in the writer's approach to data, each tied to course work, candor about where the writer started, readings that explain rather than decorate, awareness of the people behind the numbers and a promise with some professional exposure. Top entries show that the writer can now reason from a data element to its uses and causes rather than only about committees and policies. Agreeing to report results that may look unfavorable shows integrity. A clear structure, a voice that is personal and professional at once and correct APA 7 citations finish the stronger entries. Praise for the course on its own earns very little.

HIM 680 Module 10 help: the mistakes that cost points

Final HIM 680 reflections lose credit for listing topics, claiming expertise with no example, citing frameworks that changed no decision or closing with a hope to keep learning about informatics. An entry with no early misstep in it also reads as thin. If your instructor asks instead about program outcomes, leadership in data work or a next career step, send that prompt along with a summary of your proposal and a line about your position, so the reflection can lean on the papers you actually wrote. One surprising moment, such as a definition test or a load that never ran, beats a summary of the term. Our HIM 680 reflections start with a real misstep and finish with a promise you can be held to.

Get HIM 680 Module 10 written to your instructions

Pass along the HIM 680 Module 10 prompt, a paragraph on what your proposal argued and the role you hold. The entry will tie a few real changes to moments from your papers, admit an assumption you dropped and end with a promise someone can check, completed in one to two days and free the first time. 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 680 Module 10 questions, answered

Where can I find a free HIM 680 Module 10 Reflection sample?

This page has the full HIM 680 Module 10 reflection, in which a data governance director moves from committee-first thinking to following data elements and reading low rates as possible distrust.

What should a data governance reflection cover?

Concrete ways your handling of data changed, each traced to something you did in the course, an assumption you gave up and a promise tied to your job.

Why might better data make performance look worse?

Complete data often reveal needs or problems that incomplete data hid, so rates can rise or vary more even though the information has improved.

How many sources should the HIM 680 reflection cite?

Usually one to three in APA 7, chosen because they helped change your thinking, so the entry stays personal.

What makes a good commitment in a final reflection?

A promise with something at stake, for example reporting first results as they are even when they make the program look worse, phrased so a supervisor could later confirm it happened.