Stephen Hightower

We help New England municipalities turn fragile IT stacks into resilient, compliant platforms — one pragmatic phase at a time. First we assess current systems and risks, then we deliver prioritized remediation, staged cloud migration, and ongoing governance that keeps pace with changing regulations. The result: measurable reductions in downtime, predictable operating budgets, and simpler regulatory reporting. With deep public‑sector experience, we partner with procurement and IT leaders to design phased, auditable transitions that meet compliance and budget constraints. Learn how this approach can work for your town or agency: https://wix.to/VtkUeMl 🔎✅ #MunicipalIT #CloudMigration #PublicSectorIT

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CMS's Proposed Rule creates a new and mandatory two-sided risk model, the Ambulatory Specialty Model (ASM). What to know: #totalcostofcare #CMSrule #valuebasedcare https://lnkd.in/gRCgZTCV

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The move to cloud-native, interoperable RTSM solutions like those from Oracle Life Sciences will reshape how clinical trials are managed.

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The expert noted the inherent advantages that legacy EHR (Electronic Health Record) companies have as the gate keeper of features. As shown by Epic's (private) recent announcement to develop an internal AI scribe solution, EHR vendors are in a position to limit third-party integration for features such as order mapping, pre-charting or clinical decision support. He noted an increased focus on AI by Oracle Cerner (ORCL, covered by Keith Weiss) post the merger.

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Big step forward in Agentic Document Extraction! LandingAI’s new DPT (Document Pre-trained Transformer) can now accurately extract data from even the most complex documents and large tables. Why does this matter? 👉 In Energy & Utilities, trading desks and compliance teams spend enormous effort extracting and validating data from contracts, invoices, and regulatory filings. 👉 In Finance, complex statements and reconciliations often remain trapped in PDFs. 👉 For Compliance, reducing manual review of large, unstructured datasets is both a cost and risk win. With a lightweight SDK (just 3 lines of code), this opens the door to unlocking “dark data” and enabling new automation at enterprise scale. Excited to see how innovations like this accelerate our work in trading, finance, and compliance transformation across the industries we serve.

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Congratulations to North York General Hospital on this major milestone — the first hospital in Canada to migrate its EHR to Oracle Cloud Infrastructure (OCI). At Tectonic Advisory Services Inc. we help healthcare organizations across the country move their mission-critical clinical systems to the cloud. It’s not just about infrastructure. It’s about improving performance, enabling innovation, and giving clinicians more time to focus on patient care. North York General’s results speak volumes: - 26% faster transaction response times - 40% faster logins - A foundation for AI, analytics, and future innovation We’re proud to support hospitals in designing and executing strategies like this modernizing systems, improving resilience, and embracing platforms like OCI, Microsoft Azure, and others to transform how care is delivered. If you’re planning your cloud journey or looking to optimize your clinical systems, let’s talk. #CloudHealth #HealthcareInnovation #EHR #OracleOCI #DigitalHealth #TectonicAdvisory #HealthIT #CanadaHealthCare

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📉 Health Systems' Big Restructuring Its Major Impacts on Tech Procurement👇 Great article out of Modern Healthcare on health systems org structure overhaul. What does this mean for tech procurement and GTM. (link in comments - paywalled). 🚦 Major Healthcare System Changes: - Reducing middle management layers - Flattening organizational hierarchies - Centralizing decision processes From Yale New Haven to Main Line Health, executive restructures are becoming standard practice. 💥 Impact on AI HealthTech GTM: 🔄 Buyer Evolution - Frontline adoption remains critical success factor - Enterprise stakeholders now control service spans - New leadership brings systemic strategy changes - Middle management faces increased workload pressure 💡 Critical GTM Adaptations: - Workflow integration becomes mission-critical - Department-level selling no longer aligns with system buyers - Middle management needs enablement support vs evangelism - Champions require Salient Value Dashboards (SVDs) for internal validation ⚡ Strategic Imperatives: - Leverage restructures as GTM pivot opportunities - Align messaging across executive ROI metrics - Map GTM to Clinical Enterprise Value Stack - Bridge the system-wide implementation gap 🔑 Core Reality: Siloed decision-making is obsolete. Modern GTM must address enterprise-wide value creation and system-level stakeholder needs. The evidence shows: 📍 Successful healthtech GTM requires enterprise-level engagement and system-wide value demonstration. ➡️ P.S. Need help realigning your GTM strategy? Let's connect for a strategic assessment #llm #ai #artificialintelligence #medicalai #healthcareai #genai #GTM

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Insourcing PI with AMS: two engines, one platform, compounding savings. 1) PredictPi - PI nanoscripts plus governance (platform savings): • $70+ PMPY incremental savings directly attributed to AMS software • $400M+ verified annual savings at scale (anonymized national TPA/ASO) • ~90% faster flag → decision; 30-40% higher audit precision • 250+ users unified across PI/SIU/Claims with transparent, rules-based evidence 2) AI-Bill - automated Itemized Bill review (IBR) savings: • Micro-sprint result: ~$7.1M identified in ~12–12.5 hours • >$9.4K–$9.8K per minute in savings; >$0.57M–$0.59M per hour • >11,000× ROI on labor (at ~$50/hr), yes, empirical data and metrics make this attainable. Together (additive impact with one Health Affordability Platform): • PredictPi’s continuous surveillance + nanoscripts deliver broad, recurring PMPY lift across lines of business. • AI-Bill’s high-throughput IBR adds concentrated, rapid savings bursts, without adding headcount. • Subscription model democratizes PI (predictable TCO, aligned with prevention and fiduciary governance) while keeping contingency only for niche retros/capacity spikes. Why it works: • Aligned incentives: prevention + unit-cost reduction, not just recoveries. • Capability transfer: tools + reference directories + nanoscripts move IP in-house. • Operating discipline: governance layer, evidence packs, provider-ready documentation, and enterprise-wide queueing for 200–300 users. The punchline: • Platform (PredictPi): $70+ PMPY; $400M+ verified annually; speed and precision gains. • IBR (AI-Bill): $7.1M in hours; >11,000× labor ROI. • Model: subscription pricing that lowers total cost, scales savings, and strengthens fiduciary posture. Call to action: If you want to insource PI, cut TCO, and run a continuous prevention engine-with rapid IBR savings on top—let’s connect. Summary – You Will Want to Save This Post PredictPi drives recurring PMPY + governance at scale; AI-Bill adds rapid IBR wins. One subscription platform; additive savings; stronger fiduciary confidence. Amspredict.com Pricetransparency.com #PaymentIntegrity #PriceTransparency #ERISA #HealthcareAnalytics #Claims #SIU #TPA #SelfFunded #Automation #Affordability #FiduciaryRisk

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