HIM 675 Module 4 Discussion Example

Reviewed by Delia Ravenscroft, MSN, RN

This HIM 675 Module 4 Discussion sample compares research designs and chooses one to fit a specific health information question. It was prepared for SNHU HIM 675 (HIM-675), where the fourth module has MS Health Information Management learners weigh quantitative, qualitative and mixed approaches for the study they are planning. The composite writer manages data integrity at a 340-bed teaching hospital in Tulsa and wants to know how often present-on-admission flags for four hospital-acquired conditions are wrong and why. The post explains what a quantitative record review can and cannot answer, what interviews with coders and nurses would add, and why an explanatory sequential mixed design, numbers first and conversations second, best fits a question with both a how-often and a why. It closes by asking classmates which part of their own questions a single method would miss.

CourseHIM 675 Research Methods and Evaluation
ModuleModule 4
Paper typegraduate discussion post comparing research designs for an HIM study
LengthAbout 360 words, 3 pages
FormatAPA 7 student paper
SchoolSouthern New Hampshire University
ProgramMS Health Information Management
UpdatedOctober 2026

Free sample paper for HIM 675 Module 4

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Module Four Discussion

How Often, and Why

My study question has two parts. The first, how often our present-on-admission flags disagree with the chart, is a counting question. The second, why they go wrong, is not. Choosing a design this week meant deciding whether one method could answer both.

What this page is doingThe post splits the question into its two halves.
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A quantitative design fits the first part. Creswell and Creswell (2018) describe quantitative research as testing relationships among measurable variables, and agreement between a coded flag and a re-abstracted flag is measurable. Goldman et al. (2011) took exactly this route, having reviewers re-read California charts without seeing the original flags, which gave them agreement rates and the direction of errors. A cross-sectional review of about 300 records at Cimarron Heights can tell me how often flags disagree and whether disagreement is more likely without a 24-hour skin assessment. It cannot tell me what coders were thinking when they set a flag, or why nurses skip the assessment on busy nights.

A qualitative design, interviews with coders and admitting nurses, would explore exactly that. It might reveal that coders default to yes when a patient arrives from a nursing home, or that the skin assessment screen is buried. But interviews alone cannot tell me how big the problem is, and leaders will not fund changes without a number.

A mixed design joins them. Fetters et al. (2013) describe an explanatory sequential design in which quantitative results come first and qualitative work then explains them, and they stress that the two strands must be deliberately integrated, for example by using the numbers to choose whom to interview and what to ask. In my case, the record review would identify which conditions and units have the most disagreement, and I would then interview six to eight coders and nurses from those areas, asking about specific types of error the review found.

What this page is doingEach design is matched to the part of the question it can answer.
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I am choosing the explanatory sequential design, with the record review as the core and interviews as a smaller second phase. The risk is scope, so the interviews will be limited and the capstone can drop them if time runs short. For classmates: which half of your question would a single method miss?

What this page is doingA choice, its risk and a fallback are stated before the peer prompt.
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References

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE.

Fetters, M. D., Curry, L. A., & Creswell, J. W. (2013). Achieving integration in mixed methods designs: Principles and practices. Health Services Research, 48(6pt2), 2134-2156. https://doi.org/10.1111/1475-6773.12117

Goldman, L. E., Chu, P. W., Osmond, D., & Bindman, A. (2011). The accuracy of present-on-admission reporting in administrative data. Health Services Research, 46(6pt1), 1946-1962. https://doi.org/10.1111/j.1475-6773.2011.01300.x

What the HIM 675 Module 4 instructions ask for

The fourth module of HIM 675 asks you to choose a research design for your study and defend it in a discussion post of about a page, with a few APA 7 sources and replies later. Restate your question, then weigh at least two designs, typically quantitative, qualitative and mixed, explaining what each could and could not answer. Use a methods text and a study in your area to show how others have approached similar questions. If you choose a mixed design, say which type, such as explanatory sequential or convergent, and how the strands will be integrated. Make a clear choice, name its main risk and how you would manage it, and end by asking peers something that tests how well their design fits.

How this HIM 675 Module 4 discussion example is built

Cimarron Heights Medical Center's question splits into how often present-on-admission flags disagree with the chart and why. Creswell and Creswell's description of quantitative research fits the counting half, modeled on Goldman and colleagues' blind re-abstraction, and a 300-record review could also test the 24-hour assessment link. Interviews with coders and admitting nurses would explore the why but give leaders no number. Fetters and colleagues' explanatory sequential design joins them, with review results choosing which six to eight staff to interview and what to ask. The HIM 675 post chooses that design, flags scope as the risk with interviews as the part that can be dropped, and asks peers which half of their question one method would miss.

Where the HIM 675 Module 4 rubric puts the points

In HIM 675, design discussions earn credit for describing each considered design correctly, a clear match between design and research question, recognition of what each design cannot do, appropriate use of methods literature and an example study, a reasoned final choice and attention to feasibility. Posts that excel explain integration if they choose mixed methods, since simply doing two studies side by side is a common weakness. Graders value realistic plans, including what will be cut if time runs out. Accurate terminology, such as cross-sectional, explanatory sequential and gold standard, and correct APA 7 citations are expected. Replies are rewarded for spotting a mismatch between a classmate's question and design.

HIM 675 Module 4 help: the mistakes that cost points

Design posts in this course often lose credit for choosing mixed methods because it sounds thorough without explaining integration, describing designs from a glossary without tying them to the question, ignoring feasibility in a capstone timeline or calling a record review an experiment. If your question is purely descriptive, purely exploratory or about an intervention you will test, send it with the prompt and the post will weigh the designs that fit, including quasi-experimental options. Note the data and people you can realistically reach. Our HIM 675 posts match each design to the part of the question it can answer and end with a defensible choice.

Get HIM 675 Module 4 written to your instructions

Send the HIM 675 Module 4 prompt with your current research question and the data you can access. The post will weigh the designs that fit, explain what each can and cannot answer, justify a choice with methods literature and an example study and name its main risk. It is written within two days, with no fee for your first. 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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More HIM 675 papers and related MS Health Information Management samples

HIM 675 Module 4 questions, answered

Where can I find a free HIM 675 Module 4 Discussion sample?

The full HIM 675 Module 4 post is on this page, comparing quantitative, qualitative and mixed designs for a present-on-admission accuracy study and choosing an explanatory sequential design.

What is an explanatory sequential mixed methods design?

A design in which quantitative data are collected and analyzed first and qualitative data are then gathered to explain the results, with the first phase guiding the second.

When should an HIM study use qualitative methods?

When the question asks why or how something happens, such as why coders set flags a certain way, rather than how often it happens or how variables are related.

Is a chart review study quantitative?

Usually. A record review that measures agreement rates or associations between documented variables is a quantitative, often cross-sectional, design.

What does integration mean in mixed methods research?

Deliberately connecting the strands, for example using quantitative results to choose interview participants and questions, and interpreting both sets of findings together.