HIM 540 Module 9 Final Project Example

Final Project: One System, One Set of Rules, an Information Governance Program for Tidewater Crossing Health

[Student Name]

Southern New Hampshire University

HIM 540: Health Information Governance

Final Project

[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.

Final Project: One System, One Set of Rules, an Information Governance Program for Tidewater Crossing Health

Executive Summary

Tidewater Crossing Health became one organization eighteen months ago but still runs on four sets of information rules. The board has received conflicting readmission rates, three retention schedules keep 22,000 boxes of paper in storage, coded sepsis varies twofold across hospitals and an estimated 7% of patient records are duplicates. This proposal establishes an information governance program with an executive sponsor, a council and committee with real decision rights, named data stewards and five program areas. Over eighteen months it would adopt shared definitions, one coding manual, one retention schedule and one approval path for data sharing, and it would cut the duplicate rate below 2%. Net first-year cost is about $214,000 after storage savings. Leadership is asked to approve the charter, the resources and a quarterly scorecard to the board.

Why Governance, and Why Now

Merged organizations inherit every predecessor's habits. Without an owner for shared rules, each hospital keeps its own, and reports that seem to line up actually measure different things. Rosenbaum (2010) argued that trustworthy data depend on stewardship entities with defined authority, transparency and accountability, and the conflicting readmission rates showed what happens without them. Waiting would make the problem harder, since each new report, interface and data request built on inconsistent rules adds to the eventual cleanup.

Governance With Decision Rights

The chief operating officer sponsors the program. The health information director leads the information governance council, which owns policy from creation to destruction and signs off on retention, access and sharing rules. Beneath the council, a data governance committee rules on definitions and quality, and five domain stewards keep their data current. Each hospital keeps a vote on the council, and documented local variations are allowed where genuinely needed. Disputes follow a published path with a thirty-day target, ending with the sponsor.

Program Areas

The work is organized into five program areas. Definitions and data collection: every element in a system report has a dictionary entry, collection uses standard vocabularies and quality is checked at entry using conformance, completeness and plausibility, the categories Kahn et al. (2016) proposed for a shared data quality language. Coded data: the four local coding manuals become one, with a common approach to validating high-impact diagnoses, shared query templates and a single audit cycle, because coded data drive payment, quality and research; Rhee et al. (2017) showed how claims-based trends can reflect coding changes rather than disease, which is why coding practice needs governance. Sharing and interoperability: a bridge between the two record platforms, national exchange, patient access and one approval path and register for external sharing, justified by evidence reviewed by Menachemi et al. (2018) that exchange reduces duplicate testing and costs. Patient identity: probabilistic matching with human review, standardized registration data and a governed cleanup, since McCoy et al. (2013) showed how often patients share names and birth dates in large systems. Information life cycle: one retention schedule from a legal requirements register, a legal hold process and documented destruction.

How Governance Reaches the Front Line

Governance succeeds only if it changes daily work. Registration staff will see new required fields and a smarter patient search. Coders will work from one manual and receive audit feedback on the same schedule at every hospital. Clinicians will notice outside records appearing in a reconciliation view and fewer conflicting queries. Department managers will find definitions for every report in one dictionary. Health information staff will manage retention and legal holds from one schedule. Each change will be introduced with a short explanation of the problem it solves, because staff accept rules more readily when they can see the reason behind them.

Eighteen-Month Roadmap

Table 1 sequences the program.

Table 1. Eighteen-Month Roadmap

Note. Roadmap prepared by the author with the governance council.

Resources and Savings

The program needs a half-time governance coordinator, about $45,000 a year; protected steward time of four hours a month; $120,000 for patient identity cleanup support; $95,000 for interface work to bridge the platforms; and $30,000 for training and communication, a first-year total of about $290,000. Destroying eligible paper records will cut storage costs by an estimated $76,000 a year once complete, bringing the net first-year cost to about $214,000. Harder to count, but larger, are the savings from avoided rework on conflicting reports, fewer denied claims for poorly supported diagnoses and less duplicate testing when outside records are available.

Governance Scorecard

The board will receive a quarterly scorecard with seven measures: share of system reports using approved dictionary definitions; estimated duplicate rate and overlays; range of coded sepsis rates across hospitals; boxes and legacy systems past retention; legal holds documented and acknowledged; transfers with outside records available; and external data sharing arrangements with current agreements. Each measure has an owner and a target.

Risks

Three risks stand out. Hospitals may resist system rules they see as the flagship's, which the council's shared votes and local variations are designed to address. Stewards may lack time, which protected hours and recognition in performance goals aim to prevent. And early wins may fade into routine, which the quarterly scorecard is meant to keep visible. A fourth risk, that the two record platforms converge more slowly than planned, would lengthen the bridging work but not change the governance design, since definitions and stewardship apply regardless of platform.

Conclusion

Tidewater Crossing does not need more data; it needs data it can trust and rules that apply everywhere. With governance that has authority, stewards who own definitions, program areas that cover collection, coding, sharing, identity and the life cycle and a scorecard the board reviews, the system can become one organization in how it manages information, not only on its organization chart.

References

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

McCoy, A. B., Wright, A., Kahn, M. G., Shapiro, J. S., Bernstam, E. V., & Sittig, D. F. (2013). Matching identifiers in electronic health records: Implications for duplicate records and patient safety. BMJ Quality & Safety, 22(3), 219-224. https://doi.org/10.1136/bmjqs-2012-001419

Menachemi, N., Rahurkar, S., Harle, C. A., & Vest, J. R. (2018). The benefits of health information exchange: An updated systematic review. Journal of the American Medical Informatics Association, 25(9), 1259-1265. https://doi.org/10.1093/jamia/ocy035

Rhee, C., Dantes, R., Epstein, L., Murphy, D. J., Seymour, C. W., Iwashyna, T. J., Kadri, S. S., Angus, D. C., Danner, R. L., Fiore, A. E., Jernigan, J. A., Martin, G. S., Septimus, E., Warren, D. K., Karcz, A., Chan, C., Menchaca, J. T., Wang, R., Gruber, S., & Klompas, M. (2017). Incidence and trends of sepsis in US hospitals using clinical vs claims data, 2009-2014. JAMA, 318(13), 1241-1249. https://doi.org/10.1001/jama.2017.13836

Rosenbaum, S. (2010). Data governance and stewardship: Designing data stewardship entities and advancing data access. Health Services Research, 45(5, Pt. 2), 1442-1455. https://doi.org/10.1111/j.1475-6773.2010.01140.x