Blockchain is a relatively novel decentralized or distributed data ledger system. Instead of banking health information in a single database, blockchain stores in a chain of data blocks called nods. It wasn’t too long ago I published a piece titled; “The utility of Enterprise-Grade Blockchain Databases with MongoDB in Healthcare.” Within, I particularized how we can use Blockchain in conjunction with a central database and various combinations to use data in consortium with a pool of users and make it operational within the given enterprise boundaries.

Here, I intend to dig deeper into how healthcare can benefit from the best of the two technologies, i.e., MongoDB and the Blockchain. Although decentralization of data and the type of trust it conveys amongst its stakeholders, it does not deny that certain centralized technologies can add extra value to the distributed ledger scheme. And such benefit goes beyond the mere data ownership and hack-resistant nature of the latter system. Here, by focusing on current healthcare logistic needs, I would like to shed light on some of the possible utilities concerning how a centralized database system such as MongoDB can benefit us if utilized in combination with one of the blockchain technologies.

Healthcare demands Data Integrity, be Consistent, and the selected Technology must pledge that Need

Data integrity, or ‘data quality,’ pertains to the process of sustaining the accuracy, reliability, and consistency of data, including but not limited to the patient’s details, health summary, clinical notes, test results, and family information over its entire life-cycle.

Data integrity no longer equates to data security, as mistakenly done previously. A data security breach can end in the corruption of data, which then imperils data integrity. For that reason, it is no longer accurate, hence different from its former, impeccable state.

Generally speaking, every healthcare entity is responsible for ensuring the confidentiality, integrity, and availability of all electronically endangered health data an entity creates, receives, maintains, or transmits. Healthcare industry administrators must do everything in their power to protect against any foreseen threats to the security or integrity of patient information. At all times, a healthcare entity must follow security management and implement policies and procedures to avert, detect, contain, and correct security violations. It must also have a Risk analysis system that offers an accurate and meticulous evaluation of the potential perils and susceptibilities to the confidentiality, integrity, and availability of electronically protected health information held by the embraced entity.

Furthermore, to Standard and Integrity, a healthcare system must implement policies and procedures to safeguard electronically protected health information from indecorous alteration or destruction. Implementing technical security procedures to guard against unauthorized access to data transmitted over an electronic communications network is essential.

Every sovereign healthcare entity must also hold Implementation specifications. The latter includes Business associate contracts between the entity and a business associate. Concomitantly, it must also implement administrative, physical, and technical safeguards that reasonably and appropriately protect the confidentiality, integrity, and availability of the electronically shielded health information from created, received, maintained, or transmitted on the shielded entity’s behalf as deemed necessary.

All said and done with, healthcare is at a juncture concerning data, analytics, and reporting. Healthcare has historically dawdled other industries in its advance to data. Yet still, there is the growing realization that it is even more necessary to accumulate, interpret, and apply data in a meaningful means to promote the representation of high-quality patient care while supporting safety, billing, and reporting calls.

While all industries face various similar hurdles in their approach to data administration and reporting, healthcare systems are at the top of that list with additional challenges of their particular domain. For instance, healthcare today suffers a tremendous lack of data governance. An organization-wide plan and framework for collecting, standardization, and curating data to ensure a “single source of truth” is a relatively modish healthcare notion. Or Healthcare organizations have always struggled with data fragmentation, standardization, resources as well as ownership.

Blockchain offers Integrity to Healthcare Data

The key thing to understand is that Blockchain prevents document tampering. Because sealing each document, the Blockchain creates a digital fingerprint of that document, referred to as a “Hash.” Then Blockchain picks up many Hashes and Hashes them again, resulting in what we call a super-Hash. That super hash is what the software sends to the Blockchain.

Due to the distributed nature of Blockchain, whatever is stored in the system cannot be altered. The super hash and not the blockchain data mean one can use the blockchain capability at a fraction of the cost to write up to 1 million transactions per second, even on public blockchains. “And in the end, what all that means is what matters is to have reliable data.”

By utilizing Blockchain, one can verify data at any time after the document is written. One can check with a simple click. The same can use blockchain technology to prove no one has tampered with the data, the records, and the processes.

Despite the overwhelming benefit that blockchains add to the integrity of health data, with blockchain databases recording exchanges of value, the core database also needs to execute the integrity of data stored in the blockchain database. MongoDB provides a multitude of controls to implement the necessary data integrity guarantees.

Value-based Physician Reimbursement requires Health Information Consistency & Transactional Guarantees

Consistency in healthcare data is of utmost importance. It refers to the ordinance that any given database transaction must change affected data only in a pre-planned manner. Any data within the database must be authenticated according to all pre-defined guidelines, comprising constraints, cascades, triggers, and any combination.

Value-based programs are seemingly designed to reward healthcare providers and physicians with incentive payments for care quality to Medicare patients. These quality programs are designed to reform how healthcare is delivered and reimbursed. Value-based programs support also intends to facilitate Better care for an individual’s well-being for populations at a lower cost. The comprehensiveness and its utter dependence on data are integral parts, hence requisites optimal level of consistency and transactional guarantees.

A decent 21st-century healthcare system must adapt standard technology and information standards amidst Heightened Interoperability and Connectivity to fulfill the novel reimbursement system’s demands. That also includes incorporating certain amelioration for reducing administrative waste. The value-based program necessitates more rapid adoption of tighter data and transaction rules optimized for exchanging countless Health Insurance Portability and Accountability Act (HIPAA) items. The latter include claims submission, claims inquiry, electronic funds transfer, electronic remittance and auto-posting, prior authorization, and demographic updates. The standards should cover critical encounter data, such as care plan, lab results, conditions, and medication orders.

National predictive modeling would actively monitor and flag claims before payment, leading to a more robust real-time adjudication process for most expenses. That is only one of many cases of how Blockchain delivers full real-time contract-based task execution a model through the so-called “Smart Contract” system. Coupled with establishing a national payment accuracy clearinghouse, this service would reduce faulty payment and administrative friction between payers and the healthcare delivery system.

Another exciting healthcare arena where technology can benefit is physician credentialing, privileging, and quality designation Processes. Therefore, adopting a single standardized accreditation method and licensing would reduce physicians’ and hospitals’ costs without compromising quality.

MongoDB Provides Data Guarantee

Blockchain integrity is asserted on a stringent system of blocks, by each block referencing the block before. That scheme provides a flawless and transparent audit trail for each record stored in the chain. It also prevents perpetrating fraudulent actions such as double prescribing controlled drugs. Studies show that through strong consistency, MongoDB creates a straightforward environment to enforce blockchain integrity. It meant that MongoDB ensures the “correct sequencing of blocks” as they are committed to the core database and that all nodes obey one consistent disposition of the core database.

“Through MongoDB change streams, blockchain users can build reactive, real-time blockchain apps that can view, filter, and act on data variations as they ensue in the database.”

Building on its consistency guarantees, MongoDB also provides ACID (Automaticity, Consistency, Isolation, Durability) guarantees for every individual block. The block’s hash, timestamp, metadata, and transaction identifiers are stored in a single JSON (JavaScript Object Notation) document. It is a file format that is an open standard. JSON uses human-readable text to store and transmit data objects consisting of attribute-value pairs and data representations collection with all fields inserted into the core database in a single operation.

Healthcare needs a Flexible Data Model with a Dynamic Schema that MongoDB offers

Modern healthcare has uttered a need for a system that helps healthcare experts to assess the effectiveness, efficiency, and appropriateness of patient care through criteria-based outcomes and program evaluation. However, despite recognizing such necessity, such an undertaking has been severely limited due to the lack of automated means to collect and analyze patient data on a routine, continuous basis within a clinical environment.

In healthcare, an adaptive data model allows us to remain flexible while still being structured and practical. Changes emerging from regulation, scientific advancement, patient populations, and other sources can be accommodated with the least development effort with an adaptive design. Hence, data is prepared and remitted to users efficiently.

With its lightweight format and support for rich data structures, JSON has become the standard data interchange for modern data applications and has been adopted by many blockchain implementations. These rich data structures are well harmonized to MongoDB’s BSON (a computer data interchange format based on the term JSON pointing to what is referred to as- “Binary JSON”) documents. That can install all data in the blockchain block into a single copy, with event identifiers, or the events themselves, modeled as arrays of sub-documents. All values can be stored as native data types.

Rich Queries for Operational Intelligence in Value-based Physician Reimbursement

“The digitalization of healthcare has created abundant and prosperous health-related data.”

Modern applications often need the wealth of information in these healthcare data to exploit and support rich queries that access heterogeneous data from diverse sources. It raises several data management challenges on data placement, data integration, and data querying. Using a healthcare application, several would help physicians match drugs against patient conditions to address these challenges. Three datasets are collected and placed into their respective stores. Those are the relational database, a text search engine, and a graph database. Domain-specific data integration methods are also applied to associate different shards of data together.

Amidst emerging value-based reimbursement systems, ensuring that the right patients are identified early in the cycle of chronic disease management, they are fitted to programs that best suit their needs. They stick with their recommended plans are the fundamental challenges of population health.

Bringing together operational and analytical processing across high volumes of variably structured data, such as in a value-based system in a single database, compels abilities unique to MongoDB. The latter offers Workload isolation, where the MongoDB model sets dedicated analytic nodes to provision them. It allows users to simultaneously run real-time analytics and reporting queries against live data without impacting nodes servicing the operational application and avoiding lengthy ETL (Extract, Transform, Load) cycles. Furthermore, a Dynamic schema, coupled with data governance using MongoDB’s document data prototype, enables users to store and combine any form of datasets without giving up sophisticated validation rules, data admission, and rich indexing functionality.

The database is subjected to complex queries that are executed natively without using additional analytics frameworks. In that way, the system avoids latency that comes from moving data between operational and analytical engines.

“MongoDB is a scalable system designed for and within geographically distributed data centers, providing extreme availability and scalability.”

As the data pools grow, MongoDB scales effortlessly with no account downtime and without requiring application fluctuations.

Beyond efficiently modeling and persisting blocks, the core database also needs to provide the ability to run rich queries on transactions and blocks. These queries need to be serviced in real-time, without the complexity or delay of ETL (Extract, Transform, Load) processes that move data from the core database into a data warehouse or data pool. The expressive MongoDB query language and rich secondary indexes, exposed through the blockchain software, enable developers to build blockchain applications that can query and analyze the core database in any way the medical practice demands. Data is typically accessible by single keys, ranges, text search, graph traversals, geospatial coordinates, and returning responses in milliseconds. It is the type of process which involves accessing the data by multiple attributes such as the transaction identifier, input transactions, outputs, block hash, timestamp, source and destination accounts, and more.

The implementation of the blockchain layer itself benefits from these rich query abilities as well. Consider the process of verifying a transaction or a block!

Elastic Scalability & Always-On Availability is a prerequisite for a Quality Healthcare Enterprise

The Healthcare sphere is a high maintenance environment, particularly when regards to health information and medical data. To maintain quality healthcare, one must preserve data integrity, consistency, flexibility as a rich query system, and needs to ensure elastic scalability and availability at all times. Medical information tends to grow fast and exponentially, thus guaranteeing that it will be available to any privileged user at any time and location carries the challenge of its own. Likewise, as we introduce more and more enterprises into blockchain application platforms or vice versa, it is crucial, the core database can scale to meet demand while ensuring continuous uptime.

MongoDB ensures scalability by providing horizontal expansibility for blockchain applications on low-cost, commodity hardware. In other words, it distributes and replicates data across multiple physical partitions called “Shards,” allowing blockchain deployments to scale beyond a single server by providing continuous uptime in the face of system outages. Sharding also will enable serial sections of the Blockchain’s database to be geographically distributed and controlled by each co-administrator / organization in the federation. MongoDB uniquely supports multiple sharding policies that give the co-administrators precise control over how blockchain data is spread across a cluster. As a result, data can be shared according to application query patterns or regulatory considerations, providing higher scalability over diverse workloads and deployment architectures.

Some examples of Sharding include Range Sharding, Hash Sharding, and Zone sharding.

The “Range Sharding” is used to optimize range-based queries against the core database, such as retrieving all transactions with a specific customer or over a defined time range.

Here, documents are generally partitioned across shards according to the shard key value. Documents with fundamental collective values close to one another are likely to be co-located on the same shard.

Hash Sharding distributes documents according to an MD5 hash of the shard key value. This approach ensures uniform distribution of writes across shards but is less optimal for range-based queries.

On the other hand, Zone Sharding presents database administrators and operations teams’ ability to establish policies governing data arrangement in a sharded cluster. When using zones, each shard is part of the same, single collection and can be queried globally, but data is geographically distributed based on data independence and local access obligations.

Enterprise-Grade Security for Healthcare Compliance & Data Protection using Blockchain and MongoDB

It is no hidden fact that health information today is a valuable commodity. Its direct monetary value and accessing sensitive patient information places the perpetrator in an advantageous position to control the victim’s destiny. Therefore, an enterprise-grade healthcare solution also demands extensive scale security and data protection while maintaining the characteristics mentioned above. So, While the blockchain application cryptographically signs its contents, the core database needs to enforce strict security curbs to protect assets from all threats.

MongoDB enforces access permissions to sensitive data using healthcare standards for authentication and authorization while also concomitantly reconciled at the blockchain database system’s higher level.

MongoDB offers Auditing by Enabling forensic analysis to track any action against the core database. It also provides end-to-end data protection in motion through the network’s encryption process and rests in persistent storage. It offers administrative controls, flawless authentication capability that can be managed from within the core database itself with challenge/response credentials. MongoDB has a centralized permissions system that can be used by the decentralized blockchain application. MongoDB allows healthcare administrators to define permissions for a user or application and control access to data in the core database in a centralized setting.

MongoDB’s permission capabilities can be used by the higher-level decentralized blockchain application software as well. For instance, the co-administrators may configure some admin-style settings, but only if there is sufficient collective agreement. Or, read permissions may be treated as assets: person A can send to person B a property, which is permission, i.e., consent to read field X in transaction Y. This combines the best of both worlds — the datastore and permission capabilities of MongoDB, with the asset capabilities of blockchain technology. That is highly useful in many privacy-related scenarios.

Take-Home Message

Blockchain technology and MongoDB offer the best in their respective worlds. Each comes with particular challenges and uncertainties. Those unpredictable scenarios and challenges can be reduced against their benefits once we consider other factors. These include but are not limited to industry-specific factors, organizational structure and vision, and their system’s mission. What may be a perfect retail system is undoubtedly not the best option for a medical practice or a hospital setting. The matter of choice becomes even more delicate once we throw in other factors such as administrative compliance, data security, cost, scalability, etc.

“MongoDB can be utilized in conjunction with Blockchain in a variety of combinations and sub-combinations.”

When considering Blockchain Database Deployment Scenarios, two dynamic parts move deployment decisions. First, we need to determine whether the planned blockchain database for deployment will be within an “enterprise” or a “consortium.” then, we must decide if the intended blockchain data is operational. The next question is which components of the enterprise need to be deployed where and how. MongoDB comes into play by offering Sharding and many other features discussed earlier in this piece.

I do not perceive myself as a software technology expert; however, based on my research and understanding, there is a potential benefit in utilizing MongoDB in conjunction with one of the Blockchain technologies to enhance patient care and healthcare delivery systems.

Every sovereign healthcare entity must also hold Implementation specifications. The latter includes Business associate contracts between the entity and a business associate. Concomitantly, it must also implement administrative, physical, and technical safeguards that reasonably and appropriately protect the confidentiality, integrity, and availability of the electronically shielded health information from created, received, maintained, or transmitted on the shielded entity’s behalf as deemed necessary.

All said and done with, healthcare is at a juncture concerning data, analytics, and reporting. Healthcare has historically dawdled other industries in its advance to data. Yet still, there is the growing realization that it is even more necessary to accumulate, interpret, and apply data in a meaningful means to promote the representation of high-quality patient care while supporting safety, billing, and reporting calls.

While all industries face various similar hurdles in their approach to data administration and reporting, healthcare systems are at the top of that list with additional challenges of their particular domain. For instance, healthcare today suffers a tremendous lack of data governance. An organization-wide plan and framework for collecting, standardization, and curating data to ensure a “single source of truth” is a relatively modish healthcare notion. Or Healthcare organizations have always struggled with data fragmentation, standardization, resources as well as ownership.