Ashay Thakur

Contextual Analytics – Dashboards Don’t Save Lives. Context Does. • Hospitals are not lacking data. They are lacking context. • Clinical information is scattered across EHR, lab, pharmacy, and device systems, forcing clinicians to search rather than act. • RGI’s Contextual Analytics platform brings streaming data together and presents it in clinical context so clinicians see what matters immediately. • Real-time awareness • Patient-level insight • Workflow-aligned analytics #RGIInformatics #ContextualAnalytics #HealthcareInnovation #ClinicalDecisionSupport #DigitalHealth #HealthData #ClinicalAnalytics #PatientSafety

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Gaps in EHR data highlight the need to involve patients for collection of medication usage data. Andaman7 empowers patients to share information on adherence, prescriptions and OTC medications that would otherwise be missing. This insight comes from our study published in JAMIA Open. Read more: https://lnkd.in/esRzGYCF Big thanks to our co-authors from Johnson & Johnson / Kenvue and Sutter Health, California.

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Black Book Research Releases 2026 India Digital Health & Acute Care EHR Market Report Highlighting ABDM-Driven Procurement Shift, Rapid Cloud Adoption, and a Coming HIS Replacement Wave Download gratis research at https://lnkd.in/eE6_W5iz TOP VENDORS AND TOP CONTENDERS IN INDIA The report's vendor landscape identifies established platforms and scaled deployments across public-sector programs and private acute care networks. On the institutional side, it highlights major public-sector platforms such as NIC eHospital /NextGen eHospital and C-DAC light HMIS/eSushrut@Clinic, alongside enterprise-grade operational capabilities from providers such as TCS DigiGOV @HMIS and Napier Healthcare supporting broader hospital workflows. Among high-momentum contenders, Black Book profiles cloud-forward, implementation-optimized platforms including KareXpert , MocDoc , @SoftClinic, MediXcel , HaleMind Inc. , and Caresoft Inc. , which are increasingly competing on rapid onboarding, configurable workflows, patient engagement, and measurable ABDM transaction readiness. In ambulatory care, the report identifies Practo Ray and HealthPlix among prominent platforms supporting high-volume outpatient digitization and ABHA-linked adoption pathways.

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In today’s dynamic healthcare landscape, payer organizations are navigating immense pressure to balance cost, quality, and member experience. But with data scattered across silos, how do executives gain the real-time insights needed to make confident decisions? In Part 2 of our series, Kumaravel Chidamparam (Director, Healthcare & Pharma at Exafluence) dives deep into a comprehensive 67-measure KPI framework designed to bring clarity and action to payer operations. The future of healthcare leadership is data-informed. Are your dashboards built to support it? #HealthcareAnalytics #PayerStrategy #DataDrivenDecisionMaking #HealthTech #KPIs #DigitalTransformation

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Clinical workflow readiness checklist. Based on 50+ digital health workflows. What’s inside: • alignment across product, clinical, and operational teams • readiness of real-world clinical workflows • completeness of patient engagement paths and touchpoints • availability of baseline metrics and data access • integration points with EHR, scheduling, and compliance systems • operational impact and staffing implications • preparedness of internal teams for adoption and rollout – to receive this checklist ✅ 𝗖𝗼𝗻𝗻𝗲𝗰𝘁 𝘄𝗶𝘁𝗵 𝗺𝗲 ✅ 𝗖𝗼𝗺𝗺𝗲𝗻𝘁 “𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄” ✅ 𝗟𝗶𝗸𝗲 𝘁𝗵𝗶𝘀 𝗽𝗼𝘀𝘁 #workflow #digitalhealthcare #productdevelopment

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Whitepaper: How unified EHR + RCM platform drives practice growth, data-driven case study for post- acute long-term care practices. Read now → https://bit.ly/45BtX1L #SaisystemsHealth #PracticeGrowth #EHR #RCM #PALTC

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eClinicalWorks, Sunoh.ai Cut Docs Time by 1+ Hour at Clinic Why this matters: - This integration reduces provider burnout, eliminates after-hours charting, and frees up valuable time—allowing more focus on patient care. - By simplifying the workflow and improving documentation accuracy, the solution reinforces clinical efficiency and enhances overall patient experience. Our take: This represents a powerful opportunity, AI medical scribing is proving to be a game-changer for clinical workflows. By automating time-consuming note-taking, it restores provider time to care, supports work-life balance, and could become a staple in modern, patient-centered practices. What do you think? Would reclaiming an hour a day with tools like Sunoh.ai make a big difference for your team—and how might that extra time be best utilized in direct patient care or workflow improvement? Read More:- https://lnkd.in/dYX5Zd3F #eClinicalWorks #SunohAI #AIMedicalScribe #ClinicalDocumentation #HealthcareInnovation #PatientCare #businessnews #businessinsights #businessinsightsjournal #BIJ

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Keeping Up With CMS Model Runs Throughout a calendar year, CMS releases several HPMS memos on Model Runs - the process of calculating and re-calculating risk scores for adjustment payments - and payment months. In RA payments reconciliation where payments that come in for a specific month may have multiple adjustments for other periods, it can be very painful and time consuming to keep up, to find, and to answer a basic question like: "Which calendar years did CMS perform overpayment re-runs, and for which payment years?" - ChatGPT will spin your head in a different directions  - Google Search + Gemini may waste your time - Perplexity's results will perplex you Going through this challenge myself, I started to curate these information into a resource that is: - enjoyable - accurate - quick - easy Playing around it in the mimilabs workspace with the Databricks Genie... Be on the lookout for falcon health. Reach out. 👤Follow to learn more.  ♻️ Repost to share with your audience.

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𝐂𝐨𝐡𝐞𝐫𝐞𝐧𝐜𝐞 𝐖𝐢𝐭𝐡𝐨𝐮𝐭 𝐂𝐫𝐮𝐞𝐥𝐭𝐲⁣ The core concern regulators raise around risk adjustment is reasonable: diagnoses that drive payment should be coherent—anchored to real encounters, treatments, and longitudinal care. When diagnoses appear once and never again, trust in the system erodes. On that premise, regulators are right.⁣ Where the system breaks is 𝐰𝐡𝐨 𝐛𝐞𝐚𝐫𝐬 𝐭𝐡𝐞 𝐛𝐮𝐫𝐝𝐞𝐧 𝐨𝐟 𝐩𝐫𝐨𝐯𝐢𝐧𝐠 𝐜𝐨𝐡𝐞𝐫𝐞𝐧𝐜𝐞.⁣ Clinicians are increasingly judged—years later—as if they should have anticipated persistence, audit logic, and downstream utilization from a single visit. That is an inhuman expectation. Longitudinal coherence is not a visit‑level cognitive task; it is a s𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐚𝐥 𝐩𝐫𝐨𝐩𝐞𝐫𝐭𝐲 𝐨𝐟 𝐩𝐨𝐩𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐬 𝐨𝐯𝐞𝐫 𝐭𝐢𝐦𝐞. No clinician, acting in good faith, can reliably predict it in the exam room.⁣ Seen this way, defensive documentation is not abuse—it is rational self‑protection in a system that applies hindsight enforcement asymmetrically.⁣ Analytics could help here, but only if roles are cleanly separated. Machines should detect longitudinal patterns and flag incoherence. Clinicians should attest only to what they actually evaluated and addressed today. 𝐓𝐡𝐞 𝐬𝐲𝐬𝐭𝐞𝐦—𝐧𝐨𝐭 𝐭𝐡𝐞 𝐩𝐫𝐨𝐯𝐢𝐝𝐞𝐫—𝐦𝐮𝐬𝐭 𝐚𝐛𝐬𝐨𝐫𝐛 𝐬𝐭𝐚𝐭𝐢𝐬𝐭𝐢𝐜𝐚𝐥 𝐮𝐧𝐜𝐞𝐫𝐭𝐚𝐢𝐧𝐭𝐲.⁣ Coherence without cruelty requires better role design, not more documentation or algorithms in the exam room. Accountability and empathy are compatible—but only if we stop asking clinicians to function as surrogate statisticians. #RiskAdjustment #USHealthcare #AuditWithIntegrity #HealthcareCompliance #HealthcareRisk #AuditAndCompliance

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