Our Platform

Loopback Data
Platform

Before the first insight can be acted on, there must be a common understanding of the data. The Loopback Data Platform consumes clinical, prescribing, and dispensing systems used by major integrated delivery networks into a common data model. It standardizes and normalizes the data to enable advanced analytics.

Ingestion & Normalization
Enrichments & Insights
Operations & Security
Integration Partners

Aggregating clinical and specialty pharmacy data for patient and population insights

The Loopback Data Platform is built to assemble clinical, pharmacy, enterprise and social data for insight and action across the specialty pharmacy and life sciences value chain.

Data Ingestion & Normalization

Master Patients​
Locations
Medications
Labs​
Meds Matcher
Device Matcher
  • All data ingested by Loopback is standardized into a common data model. Important metadata about patients, encounters, procedures, etc. is mapped to a common set of metadata. This common data model and metadata are critical to establishing a standardized understanding of the data so that it can be useful for benchmarking across health systems and used in a research setting.
  • When importing data from an Electronic Health Record (EHR), pharmacy dispense system, etc. the same patient may have multiple records. This causes significant confusion during data analysis because the analyst cannot see the full picture of diagnoses, encounters, medications, etc. and because the patient IDs do not match. Loopback’s Master Patient Index uses a combination of probabilistic and deterministic processes to deduplicate and connect patient records across the health system or geographic region.
  • The Loopback platform includes a data transformation process to establish a standardized view of every encounter the patient has with the health system so that a true longitudinal record can be established. The platform also establishes a true longitudinal record for all medications that were ordered and/or dispensed for a patient. The platform utilizes a proprietary algorithm to map the dispensed medication to the provider’s order for that medication - a particularly important feature when the pharmacy dispensing system is not integrated with the EHR.
The Loopback Data Platform applies complex text matching algorithms to connect non-standard data domains to industry standards.

For example:

  • Medication data is mapped to the World Health Organization’s Anatomical Therapeutic Chemical (ATC) Classification, First Databank’s Specialty Pharmacy Module, and the National Library of Medicine’s RxNorm terminology.
  • Lab Results are mapped to LOINC from the Regenstrief Institute.
  • Medical Device data is particularly challenging because although device manufacturers are required to submit all device data to the FDA’s Global Unique Device Identification Database (GUDID), however adoption within health systems EHR systems is sparse. Loopback’s processes can connect non-standard EHR device data with the GUDID as well as the FDA’s pre-market approval databases (PMA and 510K) enabling analysts and researchers to find the devices they are looking for.
Pricing Engine​
Socioeconomics
Tagging Engine​
Deidentification​
NLP Engine​
Tokenization
  • Building upon the EHR clinical data, Loopback calculates key pharmacy operational performance metrics to enable optimization of clinical and financial outcomes.
  • Aggregate analytics on patient diagnoses, procedures, medications, and outcomes.
  • Loopback builds statistical models based on health system dispensing records and industry standards that will predict an estimated revenue number for each prescribed medication. Health systems can take proactive actions such as identifying patients that may need patient assistance programs and create granular revenue opportunity forecasts.
  • Loopback uses NLP to convert unstructured data like a clinical note into valuable structured elements that can be leveraged by other analytics engines or human analysts and researchers. NLP provides the ability to find symptoms, conditions, diseases, specific lab results, etc. in a clinical note as well as understanding the context of the note and asserting whether that symptom or condition is present or not present.
  • It is widely understood that the environmental, social, psychological and economic factors affecting a patient can be just as important as the clinical factors, yet this information is not widely captured across patient populations within an EHR. Loopback’s data platform will consume any patient level social determinants of health available but also uses census data to fill in the blanks when that information is not captured.
  • Using social determinants of health in a deidentified research setting is complicated because the combination of these factors can be very identifiable and patient privacy must be protected at all times. Even using SDoH factors at a census tract level can be identifiable, as demonstrated in this paper. “De-identifying Socioeconomic Data at the Census Tract Level for Medical Research Through Constraint-based Clustering” Loopback utilizes the novel approach described in this paper to be able to address this issue and dramatically improve the specificity and accuracy of SDoH factors in a deidentified dataset.
  • The drawback of a common data model means you can’t have everything. However, Loopback’s flexible tagging architecture solves this problem and allows for the capture of any population attribute necessary for downstream analytics and research. For example, # of ED visits in the last 6 months, PDC score below 80, diagnosed with Multiple Sclerosis, prescribed Humira in the last 6 months, etc. Tags can also be stacked on each other to create a specific population, such as patients that received a specific diagnosis and a specific medication within 3 weeks of that diagnosis.

Data Operations

Loopback Analytics excels when it comes to securing your patient’s healthcare records. A team of people, policies, procedures, and technology ensure your data is met with the highest industry-leading security standards. This would include, but is not limited to, the following:

Data Operations

Extract, Transform, Load

Extract, Transform, Load

Pipeline monitoring

Pipeline monitoring

Data quality checks

Data quality checks

Maintaining pipeline amidst source system changes

Maintaining pipeline amidst source system changes

Loopback’s platform and its related system components are hosted in Microsoft Azure Cloud

Annually obtain a SOC 2 Type II attestation report, performed by an independent CPA audit firm, to align with industry standards and security best practices

Assigning access permissions in Active Directory based on job roles, and requiring Single Sign-On (SSO) with Multi-factor Authentication (MFA) for access to network resources

Continually updating vulnerability testing and threat analysis to monitor all our systems for software vulnerabilities and misconfigurations in real-time

Establishing secure connections via encrypted transport methods for data transfers to/from the platform and Loopback’s customers

Training to ensure all employees are kept up to date on the ever-changing landscape of healthcare regulations

Integration Solutions

Loopback has integrated with clinical, prescribing, and dispensing systems used by major integrated delivery networks.

To learn more about the Loopback
platform, visit our Trust Center

People

People

Ensure all team members uderstand the critical role play in data security.

Procedure

Procedure

Enable people and processes with techniques that promote good business practices.

Policy

Policy

Educate all team members on proper data and safe computing practices.

Technology

Technology

Continuously review and adopt technology to support our security obligations to clients

The Loopback Commitment to Data Security

The Loopback platform is secured through a combination of best practices and technology that meet or exceed federal and state regulations.

Physical Safeguards: Limited access to tangible devices, information, and infrastructure:
  • Electronic card access control systems, key locks, and/or biometric devices restrict physical access to only authorized employees
  • Conducting regular datacenter access reviews
  • Security surveillance and environmental protection systems
Administrative Safeguards: Actions, policies and procedures designed to manage and maintain data security:
  • Information system reviews and network penetration tests at least annually
  • Formal risk management program with regular internal risk assessments
  • Sanctioned information security and data privacy policies and procedures
Technical Safeguards: Enables security through a combination of software, hardware and infrastructure:
  • All data in Loopback’s platform is encrypted in transit and at rest
  • Utilizing identity federation authentication (e.g., SAML 2.0, ADFS, etc.) services with client organization’s single-sign-on (SSO) and group policy objects (GPO)
  • Advanced Threat Protection (ATP) and Data Loss Prevention (DLP) tools to protect confidential and sensitive information
  • Providing 24x7 “eyes on glass” monitoring on network security tools, authentication logs, and endpoint devices to identify security threats and suspicious activity
  • Audit logs (log-ins, failed log-ins, user activity, etc.) around user access to patient records to detect instances of non-compliant behavior or improper access of PHI

Learn more about the Loopback platform

Whitepaper on Patient Privacy & Deidentification

Whitepaper on Data Security

Whitepaper on Data Quality and Normalization

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