This is an original excerpt written by our team to show structure, depth and referencing. It is modelled on the course named above but is not a university document. Use samples as a study guide and follow your school's academic integrity policy.
The informatics problem
On the medical units described in this paper, audits show that many patients at risk of venous thromboembolism (VTE) are admitted without a documented risk assessment or a prophylaxis order. The hospital wants to add clinical decision support (CDS) to the admission workflow. The units and their figures are illustrative. Before designing it, the informatics team needs to know which CDS features predict success.
What makes decision support work
Kawamoto et al. (2005) reviewed 70 randomized trials of clinical decision support systems. Decision support significantly improved clinical practice in 68% of the trials. Four features independently predicted success:
- Automatic provision as part of the clinician's workflow, rather than requiring the clinician to look for it.
- Recommendations, not just assessments: telling the clinician what to do, not only that a patient is at risk.
- Delivery at the time and location of decision making.
- Computer-based decision support.
Of 32 systems with all four features, 30 (94%) significantly improved practice. The review also found experimental support for periodic performance feedback, sharing recommendations with patients, and asking clinicians to document their reasons for not following a recommendation.
Evidence that order entry systems reduce errors
Computerized order entry gives decision support a place to act. In a before-and-after study at a large teaching hospital, physician computer order entry reduced nonintercepted serious medication errors by 55%, from 10.7 to 4.86 per 1,000 patient-days, with declines at every stage of the medication-use process. Adding a team intervention that changed pharmacists' roles gave no additional benefit over order entry alone (Bates et al., 1998).
Applying the evidence to VTE prophylaxis
| Feature | Design decision |
|---|---|
| Part of the workflow | The VTE risk assessment is built into the admission order set rather than a separate form |
| Recommendation, not assessment | After the risk score, the order set preselects the recommended prophylaxis, such as anticoagulant or mechanical, with dosing adjusted for kidney function |
| At the time of the decision | Appears when the admitting provider signs admission orders |
| Computer-based | Pulls weight, kidney function, bleeding risk and current anticoagulants from the record automatically |
| Reason for not following | Requires a brief reason, such as active bleeding, if prophylaxis isn't ordered |
| Performance feedback | Monthly unit reports on assessment and prophylaxis rates |
Avoiding alert fatigue
The design deliberately avoids a pop-up that interrupts unrelated work. Interruptive alerts that fire too often teach clinicians to dismiss them. Testing the order set with frontline providers before launch helps catch workflow problems.
Evaluation
The team will measure the percentage of admissions with a completed risk assessment, appropriate prophylaxis among high-risk patients, hospital-acquired VTE rates, bleeding events, and the reasons clinicians give for declining recommendations.
The MSN-prepared nurse's role
The informatics nurse translates clinical evidence into system design, brings frontline clinicians into testing, and monitors whether the tool improves care.
References
Bates, D. W., Leape, L. L., Cullen, D. J., Laird, N., Petersen, L. A., Teich, J. M., Burdick, E., Hickey, M., Kleefield, S., Shea, B., Vander Vliet, M., & Seger, D. L. (1998). Effect of computerized physician order entry and a team intervention on prevention of serious medication errors. JAMA, 280(15), 1311–1316. https://doi.org/10.1001/jama.280.15.1311
Kawamoto, K., Houlihan, C. A., Balas, E. A., & Lobach, D. F. (2005). Improving clinical practice using clinical decision support systems: A systematic review of trials to identify features critical to success. BMJ, 330(7494), Article 765. https://doi.org/10.1136/bmj.38398.500764.8F
