AI-Powered Software + Healthcare Transforming Medical Data and Saving Lives. 

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AI-Powered Software + Healthcare Transforming Medical Data and Saving Lives

OUTCOMES BETTER DECISIONS IMPROVED EFFICIENCY REDUCED ERRORS REDUCED COST IMPROVE REVENUE LESS DEATH LESS PREVENTABLE COMPLICATIONS. 

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OUTCOMES
 BETTER DECISIONS IMPROVED EFFICIENCY
 REDUCED ERRORS REDUCED COST IMPROVE REVENUE
 LESS DEATH LESS PREVENTABLE COMPLICATIONS

Power software for data processing via Machine Learning Natural Language Processing (NLP) Large Language Models (LLMs)

Clinical software  Surgical reporting Pre-surgery decision support Diagnostic  decision support Patient management Electronic data capture

Platform for AI imaging Clinical trial recruitment Clinical trial site selection Quality control data platform

Developed ServHub, industry leading medical specialty data platform Mission is to revolutionize medical data and save lives Utilized AI and big data to address clinical challenges

Healthcare professionals Fragmented Data & Redundant Workflows: Manual processes reduce efficiency and increase clinical errors Limited Compliance & Outcome Tracking: Difficulty adhering to best practices leads to suboptimal patient outcome. 

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Healthcare professionals Fragmented Data & Redundant Workflows: Manual processes reduce efficiency and increase clinical errors Limited Compliance & Outcome Tracking: Difficulty adhering to best practices leads to suboptimal patient outcome

Pharma and device companies Inefficient Trials & Data Gaps: Lack of real-time data integration delays drug/device approvals and post-market surveillance. Revenue Loss from Shortened Therapy Duration: Limited visibility into patient adherence results in reduced therapy duration.

Regulators Wasted Resources & Rising Costs: Fragmented systems complicate public health oversight, driving up costs. Limited Visibility into Outcomes: Delayed or incomplete data hinders policy decisions and quality benchmarking.

Patients Gaps in Care Continuity: Minimal follow-up and poor communication lead to higher readmission rates and worsening chronic conditions. Anxiety & Depression: Uncoordinated care fosters emotional distress and lower treatment adherence.

Multiple Stakeholders Face Critical Pain Points in Specialty Care —We Provide a Unified Solution

Driven by the purpose to improve quality of care and reduce errors in clinical workflows

1. Pre-Surgery Surgery Post-Surgery. Hospitalization. 

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Chronic-Disease Mgmt. (pre-Hospitalization)

Service Value-add 1 Surgical reporting Structured data and improved reporting efficiency 2 Surgical quality reporting Comparison to global quality 3 Surgical quality improvements Lower complication rates and lower length of stay 4 International Center of Excellence Certification Industry recognition as center of excellence by the American College of Cardiology (ACC) 5 Operative efficiency Increased surgery volume & lower workload 6 Real world studies Industry influence and revenue 7 Post-hospitalization management (DTx) Improved accuracy and less human

Service Procedure type 1 Cardiology Angio/PCI, EP/ABL, Pacemaker, TAVR, TEER, LAAO, PFO, PDA  2 Cardiac Surgery CABG, MICS, structural heart,  3 Vascular surgery Lower complication rates 4 Neuro-intervention Hemorrhagic, ischemic 5 Neurosurgery Excavation Tumor excavation 6 Orthopedics TKR, THR, Spinal implant

Cover complex high value, common surgeries

Note 1 Each service includes a software and  services] Other services can be discussed

Key Non-communicable Diseases Addressed & Rationale. 

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Key Non-communicable Diseases Addressed & Rationale

Cardiology: Ablation, pacemaker, heart failure, structural heart, coronary heart disease


 Peripheral vascular surgery Neurosurgery Ischemic stroke, hemorrhagic stroke Cardiac surgery Congenital heart disease, coronary heart disease, valvular heart disease

Large patient base Typically contribute to 50% of a country’s healthcare annual expenditure

Standardized diagnosis & treatments Clinical guideline-driven diagnosis

Long-term treatments Up to 25 years (based on average disease onset & life expectancy)

High unit cost At a minimum USD$2,000 and up to USD $50,000 per patient per episode of care

Note: Serv Medical also addresses common NCDs such as diabetes, hypertension, COPD, chronic kidney disease, mental health disorders, etc.

[image]. [image]. [image] iu%cuu. [image]. ServHub - An End-to-end Digital Care Partner for Severe Chronic Disease Patients. 

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ServHub - An End-to-end Digital Care Partner for Severe Chronic Disease Patients

Web based tool for Family Doctors to manage patients Tool to connect labs, radiology, & pharmacies  1 Clinical mgmt. sys.

AI-generated care plan reviewed by Family Doctor & sent to patient 2 Pt. mgmt. & care

Connected system combines data from episodes of care Algorithm stratifies Sam based on risk assessments and refers to relevant providers 3 Pt. triage & mgmt. CDSS

Patient receives personalized post-op care plan and Rx education materials 4 Specialist care suite

Patient receives personalized education materials, lifestyle recommendation, Rx, visits, and care coordinator 5 Pt. mgmt. & DTx

Harnessing clinic & hospital data to manage cost of care, ensure accountability &compliance 6 Analyze+

Sam Chan Age: 45 years old; married with two kids Occupation: Insurance salesman
 He has atrial fibrillation and the “three highs” (blood pressure, glucose, and cholesterol). His lifestyle is very taxing and he suffers from severe anxiety because of his condition. He understands his risks for acute worsening (60% success rate for a-fib  surgery), but having a long-term digital care partner that can accompany him on his patient journey and provide personalized education and service keeps his mind at ease allowing him to lead a happier life.

Follow-up visit to Family Doctor (ambulatory care)

Connecting patients with primary care physicians (PCPs) and PCPs with specialists to provide integrated care. The AI-driven approach makes management easier and connected digital solution allows regulators and healthcare facilities to centrally manage the entire care process

Time saved during clinical and data QC reporting. 

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Time saved during clinical and data QC reporting

Surgical records completed prior to discharge

Reduction in repeat entries during clinical reporting

Hospitalization time reduced (5 to 2.5 days for PCI)

Data Quality Completeness Uniformity Correctness Truthfulness

Case 1: standardize care + discharge standardization Background Public hospital in Asia Focus: angiography and angioplasty Problem Too many standards
 Data couldn’t be aggregated for performance analytics What we did Standardized terms and processes Technology implemented Surgical reporting (EMR) Post-surgery CDSS on discharge Outcome Standardized reporting across 17 wards
 Operations increased from 14,000(2019) to 30,000 (2024)

Case 1: Surgical reporting standardization and discharge optimization

8. Surgical reporting standardization (with facility in Asia). 

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Surgical reporting standardization (with facility in Asia)

Figure above: pan-vascular intervention solution, including neurovascular, cardiovascular, and peripheral vascular reporting (not shown)

Including, but not limited to:
 Angio/PCI Pacemaker EP/ABL TAVR, TEER PFO, LAAO, PAH Neuro-intervention EVT CABG SAVR MICS

9. Case 2: post-op clinical quality standardization Background Public center in Brazil focused on Cardiovascular care Focus: CABG Problem Unnecessary post-operative complication leads to higher cost and increased length of stay (LOS) What we’re doing (See right for more details) Technology implemented Post-surgery CDSS on routine care Outcome (On-going) Lower complication rate Lower patient cost Lower LOS. 

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Case 2: post-op clinical quality standardization Background Public center in Brazil focused on Cardiovascular care
 Focus: CABG Problem Unnecessary post-operative complication leads to higher cost and increased length of stay (LOS) What we’re doing (See right for more details) Technology implemented Post-surgery CDSS on routine care Outcome (On-going) Lower complication rate Lower patient cost Lower LOS

Case 2: Post-Operative quality of care (Large tertiary center in LATAM)

What We’re Doing
 Workflow & Stakeholder Workshops Baseline Data & Audit CDSS Configuration & Integration Training & Change Management Real‑Time Monitoring & Feedback Iterative Optimization

10. Case 3: post-op clinical efficiency standardization Background Private hospital in Argentina Focus: all surgeries Problem Staffing cost too high Suboptimal operating room usage and staffing What we did Process mapping Stakeholder engagement Baseline mapping Propose new workflow Technology implemented OR workflow mapping tool Outcome (On-going) Lower complication rate Lower patient cost Lower LOS Cost reduction ↓ 33 min on average per procedure ↓ 38% reduction in monthly hours of operation Increased productivity ↑ 36% increase in surgeries per month Surgical quality maintained. 

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Case 3: post-op clinical efficiency  standardization Background Private hospital in Argentina
 Focus: all surgeries Problem Staffing cost too high Suboptimal operating room usage and staffing What we did Process mapping Stakeholder engagement Baseline mapping Propose new workflow Technology implemented OR workflow mapping tool Outcome (On-going) Lower complication rate Lower patient cost Lower LOS Cost reduction ↓ 33 min on average per procedure ↓ 38% reduction in monthly hours of operation Increased productivity ↑ 36% increase in surgeries per month Surgical quality maintained

Case 3: Post-Operative efficiency (Large tertiary center in LATAM)

80 bed hospital looking to improve efficiency
 Overview Stakeholder interview & workflow mapping Workflow tracking Problem identification Optimization and improvement Outcomes tacking
 Problems found Surgical groups without block assigned . Blocks assigned, “without use”.  Excessive time between surgeries.  Beginning of surgeries delayed.  Transportation time for patients, “excessively long”. Time reserved for surgical groups, “without patient”. Time where personnel had nothing to do Time where there were not enough personnel & more...

Scope: all surgeries including OB, GYN, orthopedics, cerebral vascular, cardiac surgery, etc.

11. Case 4: Dtx post PCI Background Public hospital in Asia Focused on neurosurgery and angioplasty Problem Post-surgery cases too high, sub-optimal management Patients lost to follow-up What we did Standard of care Workflow triage Technology implemented Mobile app with RPA for education and follow-up* Outcome 2 people managed 20k patients. 

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Case 4: Dtx post PCI Background Public hospital in Asia
 Focused on neurosurgery and angioplasty Problem Post-surgery cases too high, sub-optimal management
 Patients lost to follow-up What we did Standard of care Workflow triage Technology implemented Mobile app with RPA for education and follow-up* Outcome 2 people managed 20k patients

Case 4: Post-Operative quality of care (Large tertiary center in LATAM)

*Areas covered
 Diet and exercise Co-morbidity management education Medication education Self monitoring Medical follow-up Mental health support Repeat visit support

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sep 29.2023
ACC News Story

Developed through a collaboration with the ACC and faculty from top medical facilities.

AI & Big Data as the foundation for automation. 12. 

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AI & Big Data as the foundation for automation

Data Retrieval & Integration  Automatically retrieve relevant patient data from e-health records Integration with various data sources  Periodic & near real-time access to ensure CDSS has highest quality patient data

 Clinical Guidelines & Protocols Automatically integrate and apply clinical guidelines and protocols  Ensure data collected and decisions adhere to evidence-based practices Reduce variations and errors

 RPA (Robotic Process Automation) Automate tasks and allocate resources more effectively for patient-centric care Reduce cost by eliminating manual labor and human error in medical administration Standardizing processes for enhancing compliance and security

 Documentation & Reporting Automatically document and report clinical decision support activities  Simplify the process of data capture  Tracking the impact of CDSS on clinical decision-making


 Generative AI Automatically learn from user interactions and feedback Continuously improve algorithms and suggestions Adapt to evolving clinical knowledge and practices

 Artificial Intelligence Implement machine learning Large language models (LLM) Natural language processing (NLP) in our platform

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