MedPass SafeStaff

The current landscape for nurse scheduling in skilled nursing facilities is dominated by manual and fragmented solutions. Most facilities rely on ad-hoc methods such as traveler coverage (hiring temporary staff), manager shift coverage (nurse managers filling gaps), and coworker shift coverage (informal shift swapping). These approaches are reactive, inefficient, and fail to address the underlying workload imbalance—especially during medication pass, where patient volume and medication complexity can vary dramatically. Existing scheduling software like OnShift, ShiftWizard, and Kronos offer automated scheduling and shift trading but are generic—they do not factor in patient acuity, medication complexity, or real-time workload scoring for medication pass. Their strengths include broad adoption, EHR integrations, and compliance features; weaknesses include a lack of specialty focus and inability to prevent unsafe nurse-to-patient ratios in high-risk periods. There is a clear gap for a purpose-built solution that dynamically assigns nurses based on real-time workload during medication pass, alerts supervisors to unsafe ratios, and directly addresses the burnout and patient safety concerns highlighted by respondents. MedPass SafeStaff can exploit this gap by offering a vertical-specific platform that integrates clinical data (e.g., EHR medication lists, patient acuity scores) to create a safer, more equitable scheduling system.

The ideal customer is the Director of Nursing (DON) or Nurse Manager at a skilled nursing facility (SNF) or a hospital unit with high medication pass demands. The buyer, however, is typically a facility administrator, operations director, or corporate finance executive who approves SaaS subscriptions and has authority over budgets. The user (DON or scheduler) currently spends hours each week manually creating schedules or scrambling to fill gaps using spreadsheets, phone calls, or text groups. Their workflow is reactive—they become aware of unsafe ratios only after a shift starts or when complaints arise. The trigger to seek a solution is an acute event: a sentinel event due to medication error, a nurse leaving due to burnout, or regulatory pressure on staffing ratios. Budget-wise, SNFs often have tight margins, but they are willing to pay for tools that reduce turnover (which costs $50k+ per nurse), improve patient safety, and help with compliance. Typical SaaS spending for SNFs is $500–$3,000 per month per facility, with a preference for per-bed pricing ($2–$6 per bed/month). The buyer will require ROI justification linked to reduced overtime, lower agency spend, and better retention.

MedPass SafeStaff should differentiate by focusing exclusively on the medication pass period—a high-risk, repetitive, and often chaotic time in SNFs. While general scheduling tools optimize for shift coverage, SafeStaff optimizes for safe workload using a proprietary algorithm that combines patient count, medication complexity (number of meds, route, frequency), and patient acuity (e.g., cognitive impairment, disease severity). This is a unique value proposition that no existing tool offers. The product should position itself as a 'critical incident prevention system' for medication pass, rather than just a scheduler. The positioning statement: 'SafeStaff ensures every medication pass has the right nurse, with the right patient load, at the right time—so that no nurse feels like they are spinning out in the mud.' Key angles include: (1) real-time alerts to administrators when safe ratios are exceeded, enabling proactive adjustment; (2) integration with EHR and payroll systems to remove friction; (3) a simple, mobile-first interface that nurses can use to swap shifts or request coverage while maintaining safe limits. Additionally, offering a 30-day free trial with onboarding and a success manager can reduce adoption risk. The revenue model (SaaS per facility) aligns with buyer expectations.

Overall risk is medium-high. **Technical risks**: Building a reliable workload scoring algorithm that integrates with diverse EHR systems (e.g., PointClickCare, Epic, Cerner) is non-trivial. Data quality and access can vary, and HIPAA compliance adds complexity. The algorithm must be clinically validated to avoid incorrect assignments that could harm patients. **Market risks**: SNF decision-makers are often risk-averse and may resist adopting new software due to integration disruptions and training burdens. Willingness to pay is implied but not explicit in the data (only 1 out of 8 explicit); pricing sensitivity could be high. Budgets in SNFs are constrained, but the cost of nurse turnover and overtime provides a strong ROI argument. **Execution risks**: Timing is favorable as nurse burnout and staffing shortages are top-of-mind, but competition from traditional scheduling vendors (e.g., OnShift) expanding their features could erode the window. The product needs a strong sales playbook targeting DONs and administrators. **Regulatory risks**: The solution must comply with nurse staffing ratio laws (state-specific) and patient privacy laws (HIPAA). Any suggestion of replacing clinical judgment must be carefully positioned. On balance, the risk is medium-high due to technical and market complexity, but the pain is severe and the gap is real.

1. Conduct 20 in-depth interviews with Directors of Nursing at SNFs (via LinkedIn outreach or industry events like AHCA/NCAL) to map current med pass scheduling pain points, workflow, and budget constraints. Ask specifically about workload scoring and alert features. 2. Create a landing page for 'MedPass SafeStaff' with a clear value proposition (e.g., 'Stop unsafe med pass ratios'), a 30-day free trial CTA, and a waitlist sign-up. Drive targeted Facebook/ LinkedIn ads to 'Director of Nursing' at SNFs in three high-population states (CA, TX, FL) and measure click-through and sign-up rates. 3. Build a clickable no-code prototype using Bubble or Glide that simulates the workload scoring dashboard and scheduling interface. Demo it remotely to 5–7 DONs from the interviews and collect feedback on usability and perceived value. 4. Post in the r/nursing subreddit and the SNF-specific LinkedIn groups (e.g., 'Skilled Nursing Facility Professionals') describing the core problem and offering a prototype preview; gauge sentiment and collect email contacts. 5. Analyze contractual features of leading scheduling EHRs (OnShift, ShiftWizard) by requesting demos as a prospective buyer; note their lack of med pass acuity and alert features. 6. Run a pricing A/B test on the landing page with three tiers: $2/bed/month, $4/bed/month, $6/bed/month. Track which tier yields the highest CTR and sign-up conversion. 7. Develop a one-page ROI calculator showing cost savings from reduced overtime and agency spend (e.g., average 10% reduction) and share with interviewees; ask if they would pay for a tool delivering those savings.

Directional market sizing: The Total Addressable Market (TAM) is all U.S. skilled nursing facilities (approximately 15,000) plus hospital units with high med pass demands (e.g., med-surg, ER) – roughly 20,000 potential facilities. Assuming an average of 100 beds per facility, the TAM is 2 million beds. If each facility spends $500/month on a scheduling tool, the TAM is $120 million/year. The Serviceable Addressable Market (SAM) is facilities that already use EHR systems (all of them) and are open to add-on SaaS tools – perhaps 10,000 facilities (50% penetration). That yields $60 million/year. The Serviceable Obtainable Market (SOM) in Year 1 is aspirational: given 8 signals and limited resources, capturing 0.1% of TAM (~15 facilities) at $500/month average = $90,000 ARR. For Year 2, with strong traction, 1% of SAM (100 facilities) translates to $600,000 ARR. These are rough estimates based on the data and industry averages; actual growth depends on sales velocity and pricing validation. The high severity and implied willingness to pay suggest a real need, but the market is fragmented and price-sensitive, so early adoption may require heavy education and proof of ROI.