Smarter BPM using Blockchain concept

Blockchain based distributed ledgers have been used to enable collaboration in a number of environments ranging from diamond trading to securities settlement. Systems ability to execute defined scripts in the form of smart contracts along with blockchain Distributed Ledger Technology makes it capable of managing inter-organizational processes. Blockchain platforms that support both DLT and smart contracts should be capable of not only hosting business data but also the rules for managing the data. Smart contracts execute code directly on the blockchain network as a series of process steps, based on an algorithm programmed to the rules of the contract and the blockchain.

Multi-party Collaboration

Smart contracts can be used to implement business collaborations both within and external to the organization. A blockchain-based real estate registry would allow banks, government agencies, buyers, and sellers to collaborate and track the progress of a process in real-time. Specific aspects of inter-organizational business processes can be compiled into rules based smart contracts to ensure that processes are correctly executed. Smart contracts can independently monitor processes, so that only valid messages are accepted and are sent only from registered process participants. Security and accountability can be factored in the contract, as well as compliance with government regulations and internal rules and processes. 

Blockchain and smart Business Process Management

Even though smart contracts are self-executing, they can play a role in business process improvement. For example, in the case of supply chains, information from blockchain-based tracking of goods and materials can be used to develop algorithms that would prevent counterfeit products or lower quality materials from entering the chain. By combining process information gathered by the smart contract, with visualized process, lean and six sigma techniques, improvements can be made to the rules governing smart contracts.

Digital India cannot be achieved without Health Insurance Portability and Accountability Act

Let me begin by reiterating the subject line - Digital India cannot be achieved without Health Insurance Portability and Accountability Act. America revolutionized is Healthcare with computers and when it noticed there was a need for a law to ensure compliance it passed  Health Insurance Portability and Accountability Act that also defines the requirement of Digital America and Digital Healthcare for America. If Indian government wants successful Ayushmaan Bharat which is similar to Obama Care of USA it cannot be achieved without2 important foundations
1) Data Protection Law to protect the healthcare and private data of every individual
2) Health Care Accountability Law that mandates certain standard of healthcare in every hospital

For an ordinary man 'Going Digital' means primarily storing information in 'Digital Format'. For government 'Going Digital' also means guaranteeing protection of privacy for its citizen and allowing use of healthcare data in such a manner that the data is Secure, Restricted to authorized entities, ensuring data privacy and should be made available to authorized entities over secured internet with minimal efforts.

When you go to a hospital for a medical test the test reports and your personal data are stored on some hospital computer system. The hospital gives you a print of your report and maintains your medical records
for a undisclosed period of time which could be infinite.

When you go to 2nd hospital to take a 2nd opinion you have to share your paper reports with doctor because your 1st hospital does not give you access to your report over internet in more than 99% of hospitals in #India. The 2nd hospital , he may ask you do another round of test and again give your reports in paper format.

After years a person has hundreds of pages of paper report and the report format varies from hospital to hospital because India does not mandate hospitals to have a standard format for medical records - a major failure of the Indian Medical Association, Government of India and other bodies who are responsible for implementing standards in healthcare.

USA government signed the Health Insurance Portability and Accountability Act of 1996.  The HIPAA Privacy Rule is composed of national regulations for the use and disclosure of Protected Health Information (PHI) in healthcare treatment, payment and operations by covered entities. HIPPA was created primarily to

1. modernize the flow of healthcare information, 
2. stipulate how Personally Identifiable Information maintained by the healthcare and healthcare insurance industries should be protected from fraud and theft, 
3. and address limitations on healthcare insurance coverage.

HIPAA was created to “improve the portability and accountability of health insurance coverage” for employees between jobs to combat waste, fraud and abuse in health insurance and healthcare delivery. The act also contained passages to promote the use of medical savings accounts by introducing tax breaks, provides coverage for employees with pre-existing medical conditions and simplifies the administration of health insurance. The procedures for simplifying the administration of health insurance became a vehicle to encourage the healthcare industry to computerize patients´ medical records. This particular part of the Act spawned the Health Information Technology for Economic and Clinical Health Act (HITECH) in 2009, which in turn lead to the introduction of the Meaningful Use incentive program – described by leaders in the healthcare industry as “the most important piece of healthcare legislation to be passed in the last 20 to 30 years”


https://www.hipaajournal.com/hipaa-history/

https://en.wikipedia.org/wiki/Health_Insurance_Portability_and_Accountability_Act

Enterprise Guide: Transitioning from Microsoft to Open Source – Cost, Strategy & Tools ( Part-1) – Ajay K Barve

Part 1: Strategic Overview and Key Considerations

1. Introduction

In the modern digital era, enterprises are under increasing pressure to balance innovation, cost efficiency, security, and agility. Proprietary platforms like Microsoft Office 365, Windows, and Azure have long been industry standards. However, the growing maturity, stability, and feature-richness of open-source solutions have made them viable—and often superior—alternatives for a broad range of enterprise needs.

This guide—crafted for medium to large enterprises—provides a structured approach to replacing Microsoft products with open-source equivalents. Drawing on four decades of software architecture experience, this two-part series will help IT leaders make confident, informed decisions, avoid common pitfalls, and unlock long-term value.

2. The Business Case for Open Source

Advantages:

·       Cost Reduction: Elimination of recurring licensing fees and reduced vendor lock-in costs.

·       Vendor Independence: Avoid monopolistic pricing and roadmap lock-ins.

·       Customization: Full access to source code enables tailored enhancements.

·       Security: Open code allows rapid vulnerability detection, audits, and independent fixes.

·       Agility: Open-source communities foster rapid innovation and modular architectures.

·       Ecosystem Maturity: Enterprise-grade solutions like Red Hat, Ubuntu LTS, and OpenStack offer stability.

Disadvantages:

·       Skill Gaps: Requires training or hiring staff skilled in open-source tools.

·       Support Challenges: May need third-party SLAs for critical systems.

·       Integration Complexity: Complex hybrid environments can pose migration challenges.

·       UI/UX Resistance: Some users may struggle with different interfaces or workflows.

3. Key Pillars of an Open Source Strategy

1.       Executive Sponsorship & Cultural Buy-in: Secure top-level backing from CIO, CTO, and finance heads. Foster a culture that values open standards, transparency, and innovation.

2.       Legal & Licensing Readiness: Audit software for compliance with OSS licenses (GPL, Apache, MIT, etc.). Establish an internal legal review process and an Open Source Program Office (OSPO).

3.       Training & Change Management: Develop internal champions, provide workshops, create onboarding documentation. Ensure regular engagement and training to reduce friction.

4.       Incremental Migration: Focus on non-critical systems first. Use a phased rollout strategy. Implement fallback mechanisms for each stage.

5.       Support Ecosystem: Engage with Red Hat, Canonical, SUSE, or other enterprise vendors for SLAs. Contribute back to open-source projects to build long-term influence.

4. Open Source Alternatives to Microsoft Products

Microsoft Product	Open Source Alternative	Notes
Windows OS	Ubuntu LTS, Fedora, Linux Mint	Ubuntu LTS offers excellent hardware compatibility and enterprise support.
MS Office	LibreOffice, OnlyOffice	OnlyOffice offers better fidelity with Microsoft formats.
Outlook	Thunderbird with ExQuilla/Owl	Thunderbird can integrate well with Exchange protocols.
Teams	Mattermost, Rocket.Chat, Jitsi	Mattermost is highly scalable and ideal for internal collaboration.
SharePoint	Nextcloud, Alfresco	Nextcloud for file sync/share; Alfresco for advanced DMS.
SQL Server	PostgreSQL, MariaDB	PostgreSQL offers enterprise-grade features, scalability, and tools.
Power BI	Metabase, Apache Superset, Redash	Metabase is intuitive and powerful for most BI needs.
Azure	OpenStack, Kubernetes, DigitalOcean	OpenStack provides infrastructure-as-a-service with full control.
Visual Studio	Eclipse, VS Code (open core)	VS Code is open-source at its core and widely supported.

5. Planning Your Transition

6.       Assessment: Audit current software stack, usage data, and licensing dependencies. Prioritize software based on user base, business criticality, and ease of replacement.

7.       Pilot Projects: Select departments like internal admin or R&D for pilot deployments. Gather user feedback and adapt migration playbooks accordingly.

8.       Security Planning: Implement OSS security tools: OpenVAS, OSQuery, ClamAV. Enforce strict patch management, monitoring, and identity controls.

9.       Migration Roadmap: Create a phased timeline with rollback procedures. Establish KPIs: cost savings, performance benchmarks, user satisfaction.

10.   Evaluate ROI and Iterate: Use analytics tools to measure impact. Plan for continuous improvements based on feedback loops.

6. Risks and Mitigation Strategies

Risk	Mitigation
Lack of Support	Contract vendors for enterprise-grade SLAs (e.g., Red Hat, Canonical)
Integration Complexity	Use APIs, open standards, and middleware like Apache Camel or WSO2
User Resistance	Offer UI-familiar options (OnlyOffice), run workshops, incentivize adoption
Legal Issues	Form an OSPO, define an internal open-source usage policy, track license types

7. Final Thoughts

Transitioning to open-source software is a strategic move—technically, culturally, and financially. While risks exist, the long-term benefits of freedom from vendor lock-in, cost savings, and innovation agility can be transformative.

Done right, open-source transformation creates a resilient, future-proof IT ecosystem.

Stay tuned for Part 2, where we’ll explore real-world success stories, architecture patterns, migration templates, and OpenStack vs Azure Stack comparisons.

 

How AI in Healthcare is performing diagnosis and saving lives at NHS

A doctor can use Optical Coherence Tomography (OCT) scanners to scan an eye and detect eye diseases. OCT scanners create around 65 million data points each time they are used – mapping each layer of the retina and that's lot of data for doctor to study. DeepMind's AI claims to recognise 50 common eye problems from the OCT data - which means a doctor does not have to spend time in analyzing the data. The results of AI have been promising in the trials considering the algorithms were correct 94.5 per cent of the time, which is equal to retina specialists doctors who were using extra notes along with the OCT scans.
                                       Deepmind & Google joined force in 2014 to accelerate AI research in healthcare and built medical assistant application for the National Health Scheme.. The significant AI work done by Deepmind in diagnosing eye diseases as effectively as the world’s top doctors, to in saving 30% of the energy used to keep data centers cool & to predict the complex 3D shapes of proteins is disruptive in field of Artificial General Intelligence (AGI).
The application called Streams is a mobile phone app that aims to provide timely diagnoses using AI so that right nurse or doctor get to the right patient in time and save the lilfe of patient who would have died otherwise. Each year, many thousands of patients in UK hospitals die from conditions like sepsis and acute kidney injury (AKI), because the warning signs aren't picked up and acted on in time

Streams mobile medical assistant for clinicians has been in use at the Royal Free London NHS Foundation Trust since early 2017. The app uses the existing national AKI algorithm to flag patient deterioration, supports the review of medical information at the bedside, and enables instant communication between clinical teams. Shortly after rolling out at the Royal Free, clinicians said that Streams was saving them up to two hours a day. We also heard about patients whose treatment was escalated thanks to the timely alert by the app. Statistics show that the app saved clinicians time, improved care and reduced the number of AKI cases being missed at the hospital.

The above figure shows how the automated process in the medical app saves time and connects doctor directly to the patient with serious condition.

There has been controversy around Google taking Over NHS data when DeepMind was taken over by Google in early 2017. DeepMind, which is now owned by Google used to operate the NHS app independently until 2017. DeepMind justified the decision explaining how Google would allow the app to scale in a way that would not be possible by itself.  Earlier in 2017 the Streams app attracted controversy after the UK’s data watchdog found that the NHS had illegally handed 1.6 million patient records to DeepMind as part of a trials. DeepMind subsequently made assurances that the medical data “will never be linked or associated with Google accounts, products or services”, and that all patient data will remain under the strict control of its NHS partners. As long as DeepMind does not share or link patient data with Google it will be major achievement for NHS in providing smarter health monitoring for AKI and many more diseases. 

Link to NHS Website-  link