A Preselected Solution in a Hospital Laboratory Project
A 420-bed regional hospital has chartered a project to reduce laboratory errors by implementing a new laboratory information system by Q4. The charter lists the IT director as sponsor, a go-live date, and a scope covering five outpatient draw sites plus the main lab. No baseline defect rate is stated. The lab manager, who was not on the charter team, says most errors are mislabeled specimens at two draw sites and that the LIS will not fix them. Patient complaints mention repeat draws and delays; there were 12 complaints in six months. Interviews with three physicians emphasize fast result turnaround for stat chemistry. A new analyzer is scheduled for two of the sites in eight weeks, which will change workflow. The project team has 0.5 FTE analyst, one lab supervisor, and one quality engineer. The steering committee wants a go/no-go decision in two weeks.
1. Critique the project charter and rewrite the problem statement so it is suitable for the Define phase.
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The charter is a solution in search of a problem. It preselects an LIS, states no baseline, defines an overly broad scope of five sites plus the main lab, and names an IT sponsor without confirming the process owner. It also ignores the analyzer change that will alter workflow in eight weeks. The 12 complaints are a useful signal but not a defect rate.
A better problem statement would be: Between January and June, the outpatient laboratory experienced an unacceptably high specimen rejection rate due to labeling errors, concentrated at two draw sites; this caused repeat collections and delayed results. Baseline rejection rate, repeat-draw rate, and stat turnaround time will be validated in the first two weeks; the project will reduce specimen rejection by at least 50% at the two highest-error sites without degrading stat turnaround.
If baseline data are not yet available, the charter should say so explicitly rather than assert an improvement target. The LIS should be treated as a possible countermeasure, not as the project definition. The steering committee should make the go/no-go decision on a validated baseline and focused scope, not on the software go-live date.
2. Translate the voice of the customer into CTQs and recommend the scope boundary.
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VOC themes are: patients do not want to be stuck twice; clinicians need fast stat chemistry results; the lab needs correct labels and fewer rework calls. Useful CTQs are specimen rejection rate per 1,000 collections, repeat-draw rate, median stat turnaround time, and mislabeling rate by site. The complaint count is not sufficient as a CTQ because it measures escalation, not process defects.
Scope should include the main lab and the two draw sites with the highest mislabeling counts, because that is where the Pareto evidence points. Exclude the other three sites and exclude the LIS build from the Define scope. The new analyzer at two sites is a constraint: map the future workflow before choosing countermeasures. Use the error log to stratify by site, shift, collector, and specimen type. If the data show errors are spread evenly, revisit the scope; do not assume the lab manager's two-site explanation is correct until verified.
3. How would you handle the lab manager and the steering committee to improve the project's chance of success?
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The lab manager is high-power, high-interest, and currently skeptical, so treat this as a stakeholder and change-management issue, not a communication formality. Interview the lab manager, review the error data together, and offer a process-owner or co-lead role. Ask what would make the project useful to the lab and what would disrupt operations. Use the lab's own data rather than IT's project language.
For the steering committee, separate the decision into two gates: first approve a two-week baseline and scoping sprint; then approve countermeasures based on data. Clarify that the IT director is an enabler, not automatically the process owner. Address the analyzer constraint directly by including it in the future-state map. Build a stakeholder map, agree on weekly updates, and look for a quick win at one draw site. The goal is not to win an argument with the lab manager but to make the project solve the mislabeling problem the lab already sees.