HIM 480 Module 4 Capstone Milestone Two Example

Capstone Milestone Two: 72% Complete, 23% Out of Date, Baseline Results and Root Causes at Hollis Ridge Health

[Student Name]

Southern New Hampshire University

HIM 480: Health Information Management Capstone

Capstone Milestone Two

[Instructor Name]

[Date]

The organization, setting and figures below are a composite written as a model document. No real employer, client, colleague or patient is described.

Capstone Milestone Two: 72% Complete, 23% Out of Date, Baseline Results and Root Causes at Hollis Ridge Health

The Milestone One proposal set out to measure how complete and current Hollis Ridge's primary care problem lists are for six chronic conditions and to find the causes of any gaps. This milestone reports the baseline audit, checks its reliability, summarizes clinician interviews and a workflow review, and organizes the root causes that the solution must address.

Audit Method in Brief

The scheduling system supplied a random sample of 400 adult patients with two or more primary care visits during the prior twelve months. For each patient, reviewers applied the reference standard for each condition, using diagnoses in notes, medications and laboratory results, and then checked whether the condition appeared on the problem list with a codable term. They also recorded resolved problems still marked active and duplicate entries. Two reviewers independently audited 40 of the charts; they agreed on 94% of condition judgments, a kappa of 0.86, which indicates strong agreement and supports using single review for the rest.

Completeness by Condition

Table 1 shows completeness for each condition. Across 569 condition instances meeting the reference standard, 72.6% appeared on the problem list. Completeness was highest for hypertension and lowest for chronic kidney disease, which was often recorded only as an estimated glomerular filtration rate in laboratory results without a diagnosis on the list.

Table 1. Problem List Completeness by Condition

Note. Audit of 400 randomly sampled adult primary care patients; composite data.

Currency, Duplicates and Terms

Currency problems were common. Of the 400 lists, 92, or 23%, carried at least one problem that the record showed had resolved, such as pneumonia from two years earlier or a pregnancy long since delivered, still marked active. Duplicate entries appeared on 56 lists, or 14%, most often the same condition entered once by primary care and again by a specialist using a different term. Only 6% of entries were free text rather than codable terms, which was better than expected and means decision support can read most of what is on the list.

Where the Gaps Fall

Breaking the results down further showed where attention should go first. Completeness varied by clinic, from 81% at the best-performing clinic to 61% at the lowest, with the two clinics that rely most on part-time and locum clinicians at the bottom. Patients seen by more than three different clinicians in the year had lower completeness than patients with a stable primary care relationship, consistent with the interview finding that no single person feels responsible for the list. Missing chronic kidney disease was concentrated among patients whose kidney function had declined gradually, suggesting that the change was noticed in the laboratory results but never translated into a diagnosis. These patterns point to specific clinics, care patterns and conditions where interventions may have the greatest effect.

How the Findings Compare

Hollis Ridge's results fall within the range reported elsewhere. Wright et al. (2015) found completeness varying widely across ten sites for common conditions, and Hollis Ridge's pattern, strong for hypertension and weak for kidney disease, resembles the variation they described between well-recognized and less-recognized conditions. Few published studies measure currency, so the finding that nearly a quarter of lists contain stale problems adds information that the literature largely lacks, as the literature review anticipated.

What Clinicians Said

Twelve clinicians, eight physicians and four nurse practitioners, were interviewed for about 20 minutes each. Four themes emerged. First, nobody felt responsible for the whole list: primary care clinicians assumed specialists would add their diagnoses, and specialists assumed primary care would. Second, updating the list took several clicks that interrupted the visit, so clinicians documented in the note instead. Third, clinicians doubted the list's value because they had seen it cluttered with old entries. Fourth, none had been told that the list drives decision support and quality measures. These themes echo Holmes et al. (2012), who found clinicians divided over responsibility and content, and Klappe et al. (2020), who found that expected usefulness, effort and colleagues' habits shaped whether clinicians used the list.

Root Causes

Table 2 organizes the root causes found through the audit, interviews and a hands-on review of the screens clinicians use to enter or close a problem. The categories follow the factors that Hodge and Narus (2018) identified as critical to problem list success.

Table 2. Root Causes by Category

Note. Root causes identified by the author and validated with the sponsor.

Limitations

The reference standard relied on structured data, so conditions documented only in narrative notes may have been missed, which would make completeness look better than it is. Interviews included clinicians who agreed to participate and may have been more engaged than their colleagues. The audit reflects one point in time, so seasonal patterns, such as respiratory illnesses added in winter and never resolved, may be under- or overrepresented. Finally, the sample of clinicians interviewed was small, and their views may not represent every clinic.

Conclusion

Hollis Ridge's problem lists are about three-quarters complete for six chronic conditions, with chronic kidney disease and depression most often missing, and nearly a quarter of lists contain resolved problems still marked active. The causes lie in unclear ownership, missing routines, cumbersome design, absent prompts and no policy. The solution design in Module Five must address each of these causes rather than only asking clinicians to try harder.

References

Hodge, C. M., & Narus, S. P. (2018). Electronic problem lists: A thematic analysis of a systematic literature review to identify aspects critical to success. Journal of the American Medical Informatics Association, 25(5), 603-613. https://doi.org/10.1093/jamia/ocy011

Holmes, C., Brown, M., Hilaire, D. S., & Wright, A. (2012). Healthcare provider attitudes towards the problem list in an electronic health record: A mixed-methods qualitative study. BMC Medical Informatics and Decision Making, 12, Article 127. https://doi.org/10.1186/1472-6947-12-127

Klappe, E. S., de Keizer, N. F., & Cornet, R. (2020). Factors influencing problem list use in electronic health records: Application of the unified theory of acceptance and use of technology. Applied Clinical Informatics, 11(3), 415-426. https://doi.org/10.1055/s-0040-1712466

Wright, A., McCoy, A. B., Hickman, T.-T. T., Hilaire, D. S., Borbolla, D., Bowes, W. A., Dixon, W. G., Dorr, D. A., Krall, M., Malhotra, S., Bates, D. W., & Sittig, D. F. (2015). Problem list completeness in electronic health records: A multi-site study and assessment of success factors. International Journal of Medical Informatics, 84(10), 784-790. https://doi.org/10.1016/j.ijmedinf.2015.06.011