Software Development for Nursing

Solution

We first look at the specific nursing workflows the new software is meant to change. For each workflow, we trace what triggers the work, what information nurses have to collect or enter, which systems they open, who receives the result, what handoffs happen, and what has to be documented at the end. Then we question each step: Why is this information collected? Who actually needs it? Is it required for care, compliance, or management reporting? Does it already exist somewhere else? Does it have to be entered by a nurse specifically? This helps distinguish necessary work from duplicate documentation, old processes that were never retired, and local habits that should not automatically be reproduced in new software.

Based on this analysis, we define which existing entries, checks, or handoffs the new software will replace or automate. Then we decide what information can be reused automatically and what must be confirmed or re-entered because it reflects the patient’s current condition or a new clinical action. When different stakeholders have competing requirements, we clarify the underlying need and look for the least burdensome way to meet it. For example, if management wants additional proof that a round was completed, we first check whether it can come from the original nursing record, a task status, a timestamp, or another existing action. If additional documentation is genuinely necessary, we make that requirement explicit and try to enable completion with as few steps as possible.

For software products intended for multiple healthcare providers, we do not treat one hospital’s current process as a universal nursing workflow. We identify which parts should work consistently across customers and which need to stay configurable, such as task ownership, documentation requirements, or unit-specific workflows.

Solution

First, we limit what information the AI can use for each task. For example, a discharge tool can only work from the finalized medication list, follow-up orders, pending tests, and other approved discharge data rather than whatever it finds in the chart. For handoffs or documentation, we define the relevant record types and time period and set rules for resolving conflicts between sources. If the records disagree or required information is missing, the software flags the issue for review instead of letting the model choose one version or fill the gap on its own.

Next, we separate the parts of the output that can be checked automatically from those that require clinical judgment. The software can compare medication details, dates, ordered follow-ups, or other structured facts in the AI-generated draft with the source records and flag mismatches or omissions. We use AI for summarization and rewriting where it adds value, but keep verifiable facts tied to deterministic checks.

We also design the review step so nurses can verify the output more efficiently. The software shows the source data behind important statements and surfaces detected discrepancies in context, so nurses do not have to reconstruct the draft against the patient record manually. Until the nurse resolves the flagged issues and approves the result, the output remains a draft and is not added to the record, passed to the next care team, or shared with the patient.

Solution

When defining routing logic, we distinguish between who is on shift, who is currently assigned to the patient, and who may be temporarily covering that responsibility. A schedule may show that a nurse is on duty, but it does not necessarily mean that the nurse still covers a particular patient or can take an alert at this moment. We identify where each type of information is maintained and make routing follow the current assignment rather than the original shift plan. This accounts for routine changes such as patient transfers, mid-shift reassignments, float nurses, breaks, and cross-coverage.

We also define fallback paths for cases where no responsible nurse is assigned, the intended recipient is unavailable, or current assignment data cannot be obtained reliably. Depending on the workflow, the alert can move to an approved backup, charge nurse, or unit-level recipient rather than waiting indefinitely.