NUR 5310 Module 6 Informatics Project Proposal Example

One Accurate List by Noon: An Integrated Proposal for Informatics-Supported Admission Medication Reconciliation

Student Name

Master of Science in Nursing (MSN), Thomas Edison State University

NUR-5310: Nursing Informatics: Concepts and Issues

Mentor Name

Month Day, Year

One Accurate List by Noon: An Integrated Proposal for Informatics-Supported Admission Medication Reconciliation

Over the term, this course project has examined one problem from several angles: admission medication lists on our medical units are often incomplete or wrong, and the information needed to correct them exists in pharmacy and other external systems that the record has only recently begun to receive. This final paper brings the earlier analyses together as a single proposal for the hospital's clinical informatics committee. It states the problem and aim, summarizes the technical, privacy, decision support and implementation components, sets out governance and an evaluation plan with specific measures, and describes the role of the nurse informaticist in carrying the project forward.

Problem and Aim

Medication discrepancies at admission are common and can cause harm. Cornish et al. (2005) compared admission orders with a comprehensive medication history for 151 patients admitted to general medicine and found that 53.6% had at least one unintended discrepancy, most often an omitted home medication, and 38.6% of discrepancies were judged capable of moderate or severe harm. A baseline audit on our units found a similar pattern, with omissions of home medications the most frequent error.

The aim of the project is that, by the end of the first year, at least 90% of patients admitted to the four medical units will have a complete, reconciled admission medication list documented by noon on the day after admission, and that high-risk medications for night admissions will be confirmed within twelve hours. These targets are specific, measurable and tied to the workflow the project redesigns.

Components of the Solution

The solution has four parts, each developed in an earlier module. The first is a shared vocabulary and data model so that the external fill history, the patient's report and the inpatient orders describe medications in the same terms. The second is the interface that brings external fills to the admission screen through a standards-based connection, consistent with federal interoperability rules. The third is a privacy and security framework that limits access by role and care team, treats addiction treatment records under their separate federal rules and audits access to the external tab. The fourth is retuned decision support: the duplicate therapy rule will compare only medications marked as currently taken and will group same-ingredient fills rather than interrupting the reconciler.

The technology alone will not meet the aim. The evidence base points toward people as much as software. Mueller et al. (2012) systematically reviewed 26 controlled studies of hospital medication reconciliation and found that interventions consistently reduced discrepancies and potential adverse drug events; the most successful relied heavily on pharmacy staff and targeted patients at high risk. The proposal therefore pairs the new screen with the split night and day workflow described in the implementation plan, with pharmacy technicians completing full histories on days and nurses confirming high-risk drugs at night.

Governance

The project will be governed by a steering group reporting to the clinical informatics committee. Membership includes a nurse informaticist as project lead, a clinical pharmacist, a hospitalist, a night charge nurse, a privacy officer, an analyst from the record vendor team and a patient safety officer. The group will meet every two weeks during build and go-live and monthly afterward. Decisions about decision support rules will follow the committee's change process: written request, evidence review, testing and approval, with monitoring after each change. Access and privacy questions go to the privacy officer, and any proposed expansion of external data sources requires a fresh privacy review. A risk log will be maintained and reviewed at each meeting.

Costs and resources are part of governance. The proposal requests analyst time for interface build and report development, super-user hours for training and go-live coverage, and a modest increase in pharmacy technician hours on days to complete full histories. The interface fee charged by the external data network is already covered under an existing contract. Against these costs, the steering group will weigh the time nurses now spend calling community pharmacies and the cost of preventable medication events at admission, which the safety team estimates from past event reports.

Evaluation Plan

Measures were chosen to track structure, process and outcome. Process measures are the percentage of admissions with a completed reconciled list by noon the next day, the share of overnight arrivals whose anticoagulants, insulin, seizure drugs and opioids are verified inside the first half day, and the percentage of admissions with external data reviewed. Outcome measures are the rate of unintended discrepancies found on a monthly pharmacist audit of twenty randomly selected admissions per unit, and medication events at admission reported through the safety system. Balancing measures watch for harm elsewhere: nurse-reported time spent on admission documentation, the duplicate therapy alert firing and override rates, and access audit flags for the external tab. Override monitoring matters because, as Nanji et al. (2014) found, override rates and their appropriateness vary sharply by alert type, so each rule must be followed individually.

Data will come from record reports built by the analyst, the pharmacist audit and the safety reporting system. Results will be shown on run charts on each unit's quality board and reviewed monthly by the steering group, with formal reports to the informatics committee at three, six and twelve months.

The Nurse Informaticist's Role

The specialty's scope and standards place the informatics nurse between clinical practice and information science, responsible for turning recorded data into knowledge that improves care (American Nurses Association, 2022). In this project, that work is concrete. The nurse informaticist translates bedside workflow into requirements the analyst can build, brings night nurses into testing, interprets audit and override data for clinicians, protects patients' privacy in design decisions and keeps the project's aim visible when technical problems compete for attention. The role connects the people who use the system with the people who build it, and that connection is what the proposal depends on.

The informaticist also owns the project's learning. Each month, the informaticist will summarize what the measures show, what staff have reported and what has changed, and will share that summary with the units in plain language. When results stall, the informaticist leads the small tests of change that try new approaches before larger revisions.

Conclusion

This proposal combines a data model, an interface, privacy safeguards, retuned decision support and a redesigned workflow into one project with a measurable aim, clear governance and an evaluation plan that watches for unintended effects. If the committee approves it, the first unit could go live within six months, and the measure that matters will be simple to check: whether each patient's medication list is complete and correct by noon the next day.

References

American Nurses Association. (2022). Nursing informatics: Scope and standards of practice (3rd ed.). American Nurses Association.

Cornish, P. L., Knowles, S. R., Marchesano, R., Tam, V., Shadowitz, S., Juurlink, D. N., & Etchells, E. E. (2005). Unintended medication discrepancies at the time of hospital admission. Archives of Internal Medicine, 165(4), 424-429. https://doi.org/10.1001/archinte.165.4.424

Mueller, S. K., Sponsler, K. C., Kripalani, S., & Schnipper, J. L. (2012). Hospital-based medication reconciliation practices: A systematic review. Archives of Internal Medicine, 172(14), 1057-1069. https://doi.org/10.1001/archinternmed.2012.2246

Nanji, K. C., Slight, S. P., Seger, D. L., Cho, I., Fiskio, J. M., Redden, L. M., Volk, L. A., & Bates, D. W. (2014). Overrides of medication-related clinical decision support alerts in outpatients. Journal of the American Medical Informatics Association, 21(3), 487-491. https://doi.org/10.1136/amiajnl-2013-001813