Health IT teams jump from go-live to go-live and never measure post-stabilization success — adoption rates, clinician satisfaction, and workflow optimization are invisible.
Automated post-go-live dashboards that track EHR adoption metrics, clinician workflow efficiency, ticket volume trends, and satisfaction scores — giving implementation teams proof of success and optimization targets.
subscription per facility, with premium tier for benchmarking across health systems
Real pain confirmed by the Reddit thread and broadly known in health IT — teams move from go-live to go-live with no measurement of success. However, it's a 'nice to have' pain for most orgs, not a 'hair on fire' problem. CMIOs want this data but rarely have budget earmarked for it. The pain is genuine but latent — most orgs have normalized the gap.
~6,000 hospitals in the US, ~2,000 health systems. Realistic TAM at $20K-$50K/facility/year is $120M-$300M if every system bought in. But realistic serviceable market is mid-to-large health systems actively in or post-implementation — maybe 500-800 orgs. SAM closer to $15M-$40M. Niche but viable for a bootstrapped startup.
Health systems spend heavily on EHR implementations ($50M-$500M+) but historically treat post-go-live measurement as an afterthought. Budget lives in IT ops, not a dedicated line item. You'd need to convince CMIOs or CIOs to carve out new budget or attach to existing optimization spend. Implementation consultants (your other target) have tighter margins and may resist adding tool costs. Willingness exists at the executive level but procurement friction is high.
The dashboard/analytics layer is straightforward. The hard part is data integration — pulling EHR usage logs, help desk ticket data, satisfaction survey responses, and workflow metrics from disparate systems (Epic, Cerner, ServiceNow, homegrown ticketing). Each health system's data architecture is different. HL7/FHIR helps for clinical data but not for operational/usage data. A solo dev could build the dashboard MVP in 4-8 weeks but the data connectors are a 3-6 month grind per EHR vendor, and you'll need pilot site cooperation.
This is the strongest signal. Nobody owns the integrated post-go-live measurement view. KLAS does surveys only. EHR vendors provide raw data only. Consultants deliver one-time assessments. Health Catalyst is a sledgehammer for a nail. There is a clear whitespace for a purpose-built, lightweight platform that combines usage analytics + satisfaction + ticket trends + workflow metrics into a single post-go-live command center.
Strong recurring potential. Post-go-live measurement isn't a one-time event — health systems need continuous monitoring as they optimize, upgrade, and expand. Subscription per facility with annual benchmarking reports is natural. Upsell to multi-facility benchmarking and optimization recommendations. Once embedded in a health system's post-implementation workflow, switching costs are moderate.
- +Clear competitive whitespace — no one owns the integrated post-go-live measurement category
- +Strong narrative alignment with clinician burnout and EHR optimization trends that have C-suite attention
- +Natural land-and-expand model: start with one facility, expand across health system
- +Implementation consultants are a high-leverage channel — they need proof of ROI for their own services
- +Recurring revenue model fits naturally with ongoing optimization cycles
- !Data integration complexity is the MVP killer — each health system is a snowflake, and EHR usage data is not standardized or easily accessible
- !Long enterprise sales cycles (6-18 months) with budget holders who don't have a dedicated line item for this
- !Epic or Oracle Health could build 'good enough' native dashboards and kill the market overnight
- !Health system IT teams may resist giving a third-party tool access to operational data
- !The pain is real but latent — you'll spend significant effort on market education before demand generation
Industry-wide clinician satisfaction benchmarking survey for EHR systems. Collects standardized survey data from clinicians across hundreds of health systems to benchmark EHR experience and satisfaction.
Enterprise data platform for healthcare analytics including clinical, financial, and operational data. Offers pre-built analytics applications and data warehousing for health systems.
EHR implementation consulting firms that offer optimization services post-go-live, including workflow assessments, training gap analysis, and optimization sprints.
Native reporting tools within EHR platforms — Epic's Signal, Reporting Workbench, Cogito; Oracle Health's HealtheAnalytics. Track system usage, feature adoption, and basic operational metrics.
Enterprise survey platforms used by health systems to measure clinician experience, burnout, and satisfaction — sometimes repurposed for EHR satisfaction measurement.
Start with implementation consultants as your first customer, not health systems directly. Build a lightweight web dashboard that consultants manually populate or upload data into (CSV upload for EHR usage stats, ticket exports, survey results). No direct EHR integration in V1. Provide beautiful, client-ready post-go-live scorecards and trend reports that consultants can white-label and present to their health system clients. This sidesteps the data integration problem, shortens the sales cycle, and lets consultants be your sales force.
Free tier: 1 project, basic scorecard templates, manual data entry → Paid ($500-$1,500/mo per consultant team): unlimited projects, benchmarking, white-label reports, trend analytics → Enterprise ($2K-$5K/mo per facility): direct EHR integrations, automated data pulls, real-time dashboards, multi-facility benchmarking → Scale: anonymized cross-system benchmarking database becomes the moat (KLAS for post-go-live)
3-5 months if you target implementation consultants with the manual-upload MVP. 9-18 months if you go direct to health systems requiring EHR integrations. Recommend the consultant path for fastest revenue.
- “you never actually see what 'good' looks like post stabilization”
- “success was measured after going live and adopting by end user, optimization, clinician satisfaction, workflow ef”
- “consciously moving into a project where success was measured after going live”