7 Key Privacy and Security Considerations While Using Healthcare APIs

7 Key Privacy and Security Considerations While Using Healthcare APIs

Application programming interfaces (APIs) today are transforming business processes by enabling one software program to access the data or services of another. They are particularly useful for the healthcare industry, with its closed health IT systems and siloed data stores. The ability of APIs to manage the flow of information between disparate systems is helpful in supporting healthcare data interoperability between internal apps, EHRs and other data exchange tools.

The healthcare industry today is moving to digitize its records and making them discoverable and understandable. It is also structuring them and trying to standardize them in such a way as to support automated clinical decisions and enable machine-based processing of records. In doing so, it’s important to ensure that the API connections are secure and that any vulnerabilities which open the door for unauthorized access to the data do not leak information. We list 7 such privacy and security considerations with healthcare APIs, and how they can be mitigated to succeed and get accepted.

Privacy and Security Concerns with Healthcare APIs

  • With APIs, users may gain access to a lot of data as compared to limited access offered by an email interface or a web site. Even if the data is not misused for malicious purposes, the unauthorized access provided to the data can violate the privacy regulations laid down by HIPAA.
  • Though managed APIs are secure, there’s a risk of privacy violation when patients access PHI without being familiar with the HIPAA Notice of Privacy Practices for Protected Health Information. Also, some patients may share their health data to third party apps and expose themselves to a possible breach of privacy. This risk can be mitigated by ensuring that the electronic access request interface provides individuals with an opportunity to approve the electronic transmission of health information in accordance with applicable legal requirements like the HIPAA right of access.
  • Organizations need to establish privacy and security policies which are consistent with the PMI Privacy Principles or Security Principles to effectively address any privacy or security risks.
  • A service provider’s infrastructure, security practices, and technical capabilities for hosting implementations of APIs and apps that store, and access health information will need evaluation. The API will need to be protected using Transport Layer Security (TLS) Version 1.27 or higher with strong cipher suites (such as the Advanced Encryption Standard [AES] or higher) to protect health information in transit via the API from the EHR to the third-party.
  • Technical and administrative policies should ensure that the identities of both users and contributors are established and verified before granting credentials for access to or contribution of health information. Similar policies need to control the actions of anyone who wishes to issue credentials to third parties, permitting them to access their own health information.
  • Establish risk-based authentication controls which correspond to the organization’s security risk assessment, and are commensurate with the type of data, level of sensitivity of the information, and user type. Technical authorization controls need to support individual privacy preferences, but limit API access, use, or disclosure based on need.
  • Data integrity protection controls need to detect any unauthorized alterations made to health information which is accessible through the API. EHR patient portals which interact with the API need to be secured and protected against all known and exploitable vulnerabilities.

There is no doubt that with appropriate privacy and security safeguards in place, APIs can add value to individual-directed sharing of health information. As a matter of fact, properly managed APIs provide better security than any legacy or proprietary integration technology. By ensuring authentication, authorization, certification, encryption, and signatures, we secure and manage healthcare API exchanges better.

How eHealth is Making Primary Care More Efficient and Patient-focused

How eHealth is Making Primary Care More Efficient and Patient-focused

Today, clinicians and administrators are surrounded by digital offerings designed to improve patient experience and clinic efficiency. While healthcare delivery has been disrupted by many eHealth and digital initiatives, it’s widely acknowledged that carefully-planned digital transformation can help make primary care more efficient and patient-focused. Here is how eHealth applications are making the right impact and pushing the needle in the primary care arena:

Online appointment booking

Optimizing a clinician’s schedule is a major priority at any primary care site. Online appointment bookings, therefore, offer patients the ease of booking their own time slots as per their own convenience. Patients can now search for their doctor’s availability on their devices which significantly reduces the inbound call volumes for clinic administrators. Apart from appointment bookings, most online solutions also provide automated appointment reminders along with cancellation and rescheduling functionalities. These solutions, therefore, help reduce patient no-shows, which leads to better handling of clinicians’ schedule.

Virtual Care

Virtual care refers to the ability of the clinic staff to offer one-on-one interactions without the patient physically present at the clinic. Be it a prescription renewal or a lab test, virtual care is providing patients the freedom to skip their appointments by opting for real-time virtual care. This not only increases the productivity of the primary care clinic but also allows the physicians to spend more time on complex cases which require their urgent attention. Today, mobile video along with text and voice messaging is used by many eHealth solutions to deliver virtual care.

Access to personal health records

Many virtual care mobile applications now provide the patients access to their own health records. Since virtual and in-clinic patient experiences are integrated, there’s no mismatch between the continuity and transition of health care records. With the ever growing demands from regulatory bodies to make access to patients’ data seamless and easy, eHealth applications are playing an important role in opening access to health data and making the process more transparent.

Care collaboration through new tools

Collaboration applications are an important aspect of eHealth initiatives. Since most EHR solutions are too complex for most physicians, platforms such as Microsoft Teams are making life easier for them. One such solution is Dapasoft’s ‘Corolar FHIR Server for Teams’. This solution brings clinical EHR data, in HL7 format, into Teams in FHIR format for efficient care coordination.  Thus, it enables clinicians at adopting provider facilities to leverage the incredible collaborative capability of Teams while easily accessing clinical data from EHR systems like MEDITECH, Epic, Cerner, etc. using FHIR APIs.

The Benefits of Harnessing the Power of Blockchain in Healthcare

The Benefits of Harnessing the Power of Blockchain in Healthcare

Blockchain is not just about cryptocurrencies and bitcoin. It is about technology which makes it possible to record digital events, creating immutable and distributable data which is secure from any fraudulent manipulation and data breach threats.

Hospitals today are turning to technology to change the way they work, with more efficient healthcare record systems, wearable devices, and medical examination systems implementing artificial intelligence and cryptography.

Blockchain technology, therefore, has interesting use cases in the healthcare domain. As users share the data between networked database systems, a blockchain’s decentralized register of ownership stores all details, starting from the formation of each data block. Its inner SHA256 calculator generates a unique cryptographic hash every time a modification is made to the data, helping to identify the owner of a data block at any time. This fully protected data sharing method is obviously very useful in managing transactions and records in various healthcare systems.

Among other things, blockchain can help in managing patient data and in ensuring drug security in clinical trials and drug traceability. Let’s discuss some of the business and operating model opportunities offered by blockchain for the healthcare industry.

  • Health information exchanges powered by blockchain could help realize the true value of interoperability and integration for disparate health IT systems. Benefits of such HIE’s include reduced costs of current intermediaries, improving efficiencies, and supporting better health outcomes for patients.
  • Irrespective of the volumes of data handled, hospitals can process and store patient data and be assured of data provenance and integrity with blockchain. This protection would extend to patient health information (PHI), electronic health records, data collected from IoT devices (Internet of Things) or monitoring systems and medical insurance claims. When patients need to share their medical records with third parties, each PHI block gets a hash which includes the patient’s ID. Using an API, covered entities receive the necessary information through full or partial access. If the patient is not able to provide or withhold such access, the eligibility to do so may be vested with a reliable third party.
  • Blockchain eliminates the need for a central administrator, offering access security, scalability, and data privacy. It can validate a clinicians’ credentials, control access to patients’ records, secure the medical supply chain and verify clinical tests, without any fear of patient data being mismatched or duplicated.
  • Healthcare data gets anchored to the public blockchain, enabling data integrity to be proven with data timestamps; to authenticate the PHI or clinical research result integrity, allow medical audits and ensure regulatory compliance. Its secure information sharing methods ensure data safety even as healthcare providers and their covered entities provide appropriate medical services.
  • Blockchain does not allow intermediation in data sharing and protects data with more than ordinary encryption, establishing higher levels of data safety when managing insurance claims, PHI, and medical records.
  • Counterfeit drugs are the bane of existence for many in developing countries, while causing losses of over $200 billion to genuine pharma companies in US alone. Timestamped and immutable transactions using blockchain could help track a medicine from the manufacturer to retail and offer the assurance of authenticity and quality needed. It can also restrict access to verified drug dealers and help in detecting all the fraudulent drug dealers.
  • All the statistics, test results, quality reports, etc. generated and recorded during a clinical trial can be made transparent and tamper-free as the whole outcome of the research gets registered and preserved securely in the system.

It is estimated that the use of blockchain in healthcare would grow at a CAGR of 63.85% from 2018 to 2025 and solve all the issues it currently faces with the non-standardized data silos and healthcare data interoperability. With its secure and reliable method of recording, storing, and sharing sensitive data, blockchain can also help prevent data breaches in the healthcare industry. According to a report by BIS research, by 2025, the healthcare industry stands to save up to $100 billion per year by 2025 in data breach-related costs, IT costs, operations costs, support function and personnel costs, counterfeit-related frauds and insurance frauds by turning to blockchain technology. This does not even look at the benefits offered by the snowballing effects of innovation using blockchain.

Data Lakes – The Next Big Thing in Healthcare IT ?

Data Lakes – The Next Big Thing in Healthcare IT ?

In the age when every keystroke on your keyboard or swipe on your phone is tracked the era of Big Data is thriving. The advent of Microsoft Azure in 2008 allowed the Healthcare Industry to finally have access  information that, up until that point, had only been accessible via large companies such as IBM. The ability for the Healthcare Industry to pull information based on mass amounts of accurate data was nothing short of revolutionary.

The advent of this mammoth data machine altered the face of both the for-profit and non-profit sector.  It changed the way nearly all organizations worked and created entirely new industries. With the addition and popularity of mobile applications in the late 2000’s the business of tracking data all but exploded. Soon preventative health was being tackled by companies such as Fitbit which created a personal activity tracker which measures and tracks heart rate, sleep activity and number of steps walked.

Data Lakes - The Next Big Thing

The flood of data coming in, literally, from all corners of the world was organized into countless institutional Data Warehouses. Early industry predictors indicated that this mass amount of data would lead to healthcare researchers quickly uncovering information that could lead to cures or treatments. While this newfound data assisted greatly, flaws in the Data Warehouse concept were soon discovered.

The modern concept of the Data Warehouse began in the late 1980’s. IBM’s Systems Journal article published in 1988 coined the term “business data warehouse”. Bill Inmon (the ‘father’ of data warehousing) began to discuss Data Warehouses as far back as the 1970’s and in the early 1990’s published the industry bible Building the Data Warehouse. Inmon’s model for data warehousing concentrates on a centralized data repository.

Healthcare providers and researchers began to realize that this model meant accessing the data proved much more difficult and often it was not helpful to their research.  The main issue they faced was that the Data Warehouses were designed and controlled by a diverse range of operators. These individual operators could range from hospitals to research centres. These Data Warehouses employed the concept of ‘schema on write’, meaning that the data is organized as it is added to the warehouse. In fact, data is not even loaded until its eventual use is determined. For healthcare providers and researchers this method meant that they had to rely on countless institutions and their respective warehouse designs.  The information culled from disparate Data Warehouses produced at times inconsistent and conflicting data. Also, the ‘schema on write’ method prevented data from being entered in a timely manner; all information would first have to be surveyed and analyzed through individual systems. Healthcare leaders realized what they needed was access to unstructured data that they could analyze on their own timeline.

The concept of Data Lakes was born.

Data Lakes - DapasoftA Data Lake is a storage system that is able to hold mass amounts of data, but unlike the Data Warehouse with its structured, hierarchical format, the Data Lake holds raw data intentionally eschewing up-front formatting to provide users unfiltered access to the most up to date information. Data Lakes use the concept of ‘schema on read’; data is not analyzed until the end-user accesses it.

Therefore, with Data Lakes at their disposal the Healthcare Industry are not constrained by institutional schemas. While it is logical that hospitals worldwide have created their own Data Warehouses based on their own understanding of what was required by the front-end user, naturally each institutional Data Warehouse would be managed by different teams of people whose intake process for the Data Warehouse can inherently cause wide gulfs in how information is analyzed. In contrast, the Data Lake allows users to pull raw healthcare data unburdened by (if well meaning) ineffective filters.

Data Lakes provide numerous advantages over Data Warehouses for the Healthcare Industry beyond data capture.

Healthcare spending in Canada now runs into the billions of dollars annually. A portion of this cost is infrastructure spending to operate Canadian healthcare institutions including their IT operations and data storage. Adopting the use of Data Lakes greatly minimizes the costs associated with data capture and storage. Not only do operators save costs on the physical assets required for storage, but they can avoid the cost of hiring specialized staff for schematic design and data input.

Data Lakes also allows practitioners to provide patients with Precision Medicine.  Precision Medicine is an emerging medical concept that proposes tailoring healthcare to individual patients. Using Data Lakes and previously mentioned health applications such as the Fitbit personal health tracker, the ability for capturing unfiltered health information from individuals and its timely analysis can now have immediate impact for patients. By its very definition, Data Lakes provide the most open, agile format for end users.

The Healthcare Industry can now take advantage of Data Lakes supported by Microsoft Azure.

Azure Data Lakes will enable the Healthcare Industry to create repositories where their data can be held without constraint. Data of any size or format can be held at a much lower cost, and these savings can be used toward providing improved patient care. Health practitioners and researchers can also access data in real-time increasing the speed in which to apply this knowledge to produce real-world results. The Azure Data Lakes also enable users to invest in new technology without concern that this investment will not sync with their current Data Warehouse.

Big Data provided the Healthcare Industry volumes of structured information that influenced practitioners and researchers alike.  Azure Data Lakes is the bold next step and the future of Healthcare Data.

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App and Data Integration Trends in Healthcare

App and Data Integration Trends in Healthcare

The US healthcare market is fast evolving from a pay for service model to pay for performance/outcome model. New legislations such as MACRA, MIPs, and Meaningful Use has accelerated this evolution recently.  MACRA specifically calls for identifying, measuring, and reporting treatment outcomes based on clinical procedures. Therefore it very pertinent to have relevant app and data integration for healthcare providers.

In this infographic, we look at the state of data and app integration in healthcare.

App and Data Integration Trends in Healthcare

Infographic showing App and Data Integration Trends in healthcare

App and Data Integration Trends in healthcare