| Course | HI499 Bachelor's Capstone in Health Information Management |
|---|---|
| Unit | Unit 2 |
| Paper type | Capstone proposal |
| Length | About 1,120 words, 7 pages double-spaced |
| Format | APA 7 student paper |
| School | Purdue University Global |
| Program | BS in Health Information Management |
| Updated | October 2026 |
Free sample paper for HI499 Unit 2
One Tool, One Rate, One Boundary: A Unit 2 Capstone Proposal to Bring Self-Scheduling Duplicates From 4.09 Percent to 1.0 Percent
[Student Name]
Purdue University Global
HI499: Bachelor's Capstone in Health Information Management
Unit 2 Capstone Proposal
[Instructor Name]
[Date]
Callowfield Health, its people and its figures are composite; the sources cited are real.
Problem Statement
At Callowfield Health, a composite network with two hospitals and fourteen clinics, 4.09 percent of patient records created through the online self-scheduling tool are later confirmed as duplicates of an existing record, compared with 1.79 percent across all registration sources, and this project aims to bring the tool's rate to 1.0 percent within six months of a change.
Rationale
The case for this problem is local, not national. Over the past twelve months, the self-scheduling tool created about 18.2 percent of the system's new patient records but 41.5 percent of its confirmed duplicates. No other registration source shows a gap that large between its share of records and its share of errors. National work on patient matching treats duplicates as a costly and persistent problem, and professional reviews describe the matching techniques organizations use and their limits (Riplinger et al., 2020). Studies of index data also show where mismatches concentrate, in names, birth dates and addresses (Just et al., 2016), which are exactly the fields a patient types into a booking screen. That background matters, but the reason to choose this problem is the ratio: one channel, launched eighteen months ago and owned by one application analyst, produces more than two of every five duplicates.
What a Duplicate Costs the People Involved
A duplicate record is easy to treat as a clerical nuisance, but each one has consequences for someone. For the patient, the second record starts empty: no allergies, no medication list, no problem list and no history of the results that led to the visit. A clinician who opens the new record sees a stranger. For the registration and scheduling staff, a duplicate means an insurance authorization or eligibility check attached to the wrong record, so a visit can be held at check-in or a claim held after it. For the two data integrity specialists, each confirmed pair takes research, a merge and a note to every department whose work touched the second record, about 45 minutes of skilled time. And for the organization, a duplicate is the raw material of an overlay, the more serious error in which two people's information ends up in one record after a wrong merge. The proposal treats all four costs as reasons to act, but it measures only one thing, the duplicate rate, because the other costs follow from it.
The Measure
The project uses one outcome measure throughout, defined as follows.
1. Numerator: records created by the self-scheduling tool in a calendar month that are later confirmed as duplicates of a record that existed before them.
2. Denominator: all records created by the self-scheduling tool in the same month.
3. Confirmation: a merge decision recorded in the merge log by a data integrity specialist.
4. Counting window: the month's count is closed 60 days after month end, so that duplicates found at a patient's next visit are included.
5. Baseline: 4.09 percent, the average of the most recent twelve closed months.
6. Target: 1.0 percent, sustained for three consecutive closed months, within six months of go-live.
Fixing the definition now, down to the 60-day counting window, prevents the project from appearing to succeed later simply because recent months have had less time to find their duplicates. The 60-day window is the most important line in the box. Duplicates are often found weeks after they are created, so a count closed at month end would always make the latest month look better than it is.
Scope
In scope:
1. New records created through the online self-scheduling tool, for any service line.
2. The tool's matching step, its settings and the screens patients see while booking.
3. The work queue and staffing for reviewing possible matches from the tool.
Out of scope, each with its reason:
1. Emergency department registrations, because their duplicates arise under urgent conditions with different causes and a different owner.
2. Clinic front desk registrations, because their rate is already 0.66 percent and the staff there are trained and audited separately.
3. The existing backlog of duplicate pairs, because cleaning old records does nothing to stop new ones and would consume the whole term.
4. A system-wide change of matching vendor, because it is outside the authority of any stakeholder in this project.
Stakeholders
The project sponsor is the director of health information management, who owns the merge log and the data integrity staff. The patient access director owns registration policy and must approve any change to what patients are asked. The application analyst who configures the self-scheduling tool must make any technical change. The privacy officer must review anything that changes what a patient sees or what staff can access. The two data integrity specialists will be consulted throughout, since they confirm every duplicate and know which pairs are hard. Clinic managers and the revenue cycle director will be informed but do not approve.
Plan for the Remaining Units
1. Unit 3: departmental data review of twelve months of the merge log by source, trend, detection route and consequence.
2. Unit 4: synthesis of professional guidance and research on patient matching.
3. Unit 5: root cause analysis of a sample of confirmed pairs from the tool.
4. Unit 6: review of privacy, breach, record amendment, state law and claims rules that would constrain a fix.
5. Unit 7: implementation and cost plan for the changes that survive.
6. Unit 8: seminar reflection on questions raised by classmates.
7. Unit 9: professional artifact built from the project's own data.
8. Unit 10: final paper presenting the full argument and an evaluation plan.
Risks and Limits
The largest risk is access. The merge log is maintained by the department and the sponsor has approved its use with patient identifiers removed, but the tool's matching settings belong to the application team, and the analyst's time is limited. A second risk is that confirmed duplicates undercount the true number, since some duplicates are never found. The project accepts that limit because the same undercount applies before and after any change. Finally, six months after a change is longer than the term, so the final paper will present an evaluation plan with early readings rather than a finished result. Patient identity work in health information management has long been described as a shared responsibility between registration and records staff (Oachs & Watters, 2020), and this proposal keeps both groups at the table.
References
Just, B. H., Marc, D., Munns, M., & Sandefer, R. (2016). Why patient matching is a challenge: Research on master patient index (MPI) data discrepancies in key identifying fields. Perspectives in Health Information Management, 13(Spring), 1e.
Oachs, P. K., & Watters, A. L. (Eds.). (2020). Health information management: Concepts, principles, and practice (6th ed.). AHIMA Press.
Riplinger, L., Piera-Jiménez, J., & Dooling, J. P. (2020). Patient identification techniques: Approaches, implications, and findings. Yearbook of Medical Informatics, 29(1), 81-86. https://doi.org/10.1055/s-0040-1701984
HI499 Unit 2 instructions, in plain terms
The second unit typically asks for a formal proposal that turns your chosen topic into a project. Expect a problem statement, a rationale, a measure with a baseline and target, scope, stakeholders and a plan for the remaining units. Many instructors want the problem statement to carry the setting, the process, the current figure and the goal in a single sentence. The measure should be defined well enough that someone else could reproduce it, including how a case is confirmed and when counting closes. Scope should state exclusions with reasons, not just list what is included. Stakeholders are usually divided into those who approve, those who do the work and those who are informed. Expect to cite at least two sources, one on the problem's importance and one on method or practice. Risks and limits round out the document.
How the HI 499 Unit 2 example is put together
The proposal opens with a one-sentence problem statement that names the system, the tool, the rate, the comparison and the target. The rationale rests on a local ratio, the tool's share of new records against its share of duplicates, and uses published work only for background. A section on costs explains who bears each consequence of a duplicate, from the patient's empty record to the risk of an overlay. The measure is laid out in six numbered lines, and the highlighted sentence explains why the 60-day counting window prevents a false appearance of success. Scope lists three inclusions and four exclusions with reasons. Stakeholders are named by role and approval authority. Eight units are mapped to their deliverables, and a final section admits access limits, the undercount of confirmed duplicates and the term ending before six months pass.
Reading the HI499 Unit 2 grading rubric
Proposals are typically marked on the problem statement, the measure, scope, stakeholders, the project plan and writing. The problem statement and measure carry the most points, because every later unit depends on them; vague goals such as reducing duplicates without a baseline and target lose heavily. Measure points reward a definition that names the numerator, denominator and counting rules. Scope earns credit when exclusions come with reasons. Stakeholder points depend on distinguishing approval from consultation and naming roles that can actually act. The plan should map each remaining unit to a concrete deliverable. Graders also reward a candid section on risks, especially access to data. Sources should support the significance of the problem, and APA format, headings that match the template and concise writing secure the remaining points.
Common HI499 Unit 2 mistakes, and how to avoid them
The most common problem in Unit 2 is a measure that cannot be reproduced because the numerator or the counting window is undefined. Another is a target picked without reference to the baseline, such as zero duplicates, which no reviewer will accept as realistic. Some proposals list every possible stakeholder without saying who approves, which weakens the implementation plan later. Scope sections that omit exclusions invite the project to grow until it cannot finish. Students also lean on national reports for the rationale and leave out the local figure that makes the case. Plans that describe units by their titles instead of their outputs lose points too. If you are drafting your own proposal, send the problem, any baseline data, the template your instructor provided and the people involved, and we can help shape a proposal with a reproducible measure.
Get an HI499 Unit 2 example written to your instructions
Bring the problem your first post settled on and any figures you can already cite, with the Unit 2 instructions and rubric. Back comes a proposal whose problem statement fits in one sentence and whose measure is defined down to its counting lag; figures you lack stay bracketed. Ready within 24-48h, and your first sample is free. The paper above is an original model document written by our desk, not a submitted student paper and not an official Purdue University Global document.
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HI499 Unit 2 questions, answered
Where can I find a free HI499 Unit 2 sample paper?
Read the whole Unit 2 proposal here; it sets a 1.0 percent target for duplicates created by online self-scheduling.
What goes into an HI 499 problem statement?
In one sentence with the setting, the process, the current figure, a comparison and the target, as the sample does for its 4.09 percent rate.
Why does the sample use a 60-day counting window?
Duplicates are often found weeks later, so closing counts at month end would make recent months look better than they are.
What belongs in the scope section of an HI 499 proposal?
Both the inclusions and the exclusions, and a reason for every exclusion. The sample excludes emergency registrations, clinic desks, the old backlog and a vendor change.
How should stakeholders be listed?
By role and authority: who approves, who does the work and who is consulted or informed.