Healthcare Data Analytics Services
Our healthcare data analytics services turn EHR, claims, lab, and device data into dashboards, predictive models, and analytics inside your product. Before the first chart, we build a pipeline for each source and link records for the same patient across them. We work on the warehouse and BI tools you already run. The first release is scoped to answer one or two decisions before the full platform is finished.
Healthcare Analytics Services Built on One Data Model
Plus8Soft provides healthcare analytics services to digital health companies, provider groups, and payers: data platforms, EHR and claims pipelines, BI dashboards, and predictive models on one data model. We build the data layer that off-the-shelf healthcare data analytics solutions report from: source connections, patient matching across sources, and shared metric definitions.
Four questions shape the first release, and we settle them in the first weeks of discovery:
- Which decisions come first. Discovery lists three to five decisions the analytics must support, such as staffing, no-shows, care gaps, or denied claims. The first release covers one or two of them.
- Where the data lives. EHRs, claims feeds, lab systems, device platforms, and spreadsheets each get their own pipeline, quality checks, and an owner on your side.
- What each metric means. Definitions for a readmission, an active patient, or a completed program are written once in a shared metrics layer and versioned.
- Who sees patient-level data. Analysts and vendors get de-identified data or a limited data set.
Analytics often follows an app or an EHR integration. See our healthcare app development services, our guide to EHR integration with HL7 v2 and FHIR R4, and the healthcare software development hub.
Healthcare Analytics Solutions We Build
Most projects start with the data platform and add one or two of the others: descriptive BI, predictive models, or analytics inside the product.
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Healthcare Data Platforms
One place your analysts, dashboards, and models read from, with EHR, claims, lab, scheduling, and device data in a shared model. Your analysts answer new questions from data already loaded.
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One place your analysts, dashboards, and models read from, with EHR, claims, lab, scheduling, and device data in a shared model. Your analysts answer new questions from data already loaded.
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Real-World Data Platforms for Life Sciences
Platforms that turn lab results, claims, and clinical records from many data providers into one dataset. Schemas are aligned, units and codes mapped to LOINC and ICD-10, and the same patient matched across sources on privacy-preserving tokens generated at each data provider. The linked dataset is certified de-identified under Expert Determination before release.
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Platforms that turn lab results, claims, and clinical records from many data providers into one dataset. Schemas are aligned, units and codes mapped to LOINC and ICD-10, and the same patient matched across sources on privacy-preserving tokens generated at each data provider. The linked dataset is certified de-identified under Expert Determination before release.
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Healthcare BI Solutions for Provider Operations
Dashboards for scheduling, no-shows, capacity, staffing, revenue cycle, and denials, built in Power BI, Tableau, or Looker, or embedded in your own systems. Operations and finance leaders work from one weekly view with matching numbers.
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Dashboards for scheduling, no-shows, capacity, staffing, revenue cycle, and denials, built in Power BI, Tableau, or Looker, or embedded in your own systems. Operations and finance leaders work from one weekly view with matching numbers.
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Predictive Analytics
Models for no-shows, program drop-off, unusual claims, and readmission risk for care management, tested before launch on past data the model never saw. Teams get a ranked list of patients or claims to act on. Models that inform clinical decisions are signed off by a clinician before launch.
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Models for no-shows, program drop-off, unusual claims, and readmission risk for care management, tested before launch on past data the model never saw. Teams get a ranked list of patients or claims to act on. Models that inform clinical decisions are signed off by a clinician before launch.
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Healthcare Data Integration Services
Ingestion from EHRs, claims files, lab systems, and device platforms, each mapped into the shared data model and monitored for gaps and late arrivals. Your team hears about a late or changed feed before a dashboard shows wrong numbers.
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Ingestion from EHRs, claims files, lab systems, and device platforms, each mapped into the shared data model and monitored for gaps and late arrivals. Your team hears about a late or changed feed before a dashboard shows wrong numbers.
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Analytics Inside Digital Health Products
What your users see in the app: health summaries, risk assessments, and program progress for patients and clinicians. Revvel, for example, analyzes multi-year medical records, labs, and imaging in under 60 seconds.
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What your users see in the app: health summaries, risk assessments, and program progress for patients and clinicians. Revvel, for example, analyzes multi-year medical records, labs, and imaging in under 60 seconds.
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Payer and Value-Based Care Analytics
Healthcare payer data analytics on claims and eligibility data: cost and utilization trends, risk stratification, care-gap lists, and internal tracking against value-based contract measures. Finance and care management teams track cost and care gaps during the contract period.
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Healthcare payer data analytics on claims and eligibility data: cost and utilization trends, risk stratification, care-gap lists, and internal tracking against value-based contract measures. Finance and care management teams track cost and care gaps during the contract period.
Healthcare Data Analytics Capabilities
Analytics Consulting and Discovery
Our healthcare analytics consulting services start with a discovery that ends in a costed plan. It lists the decisions in scope, the data access requests to file, the team, and the order of releases. Your side brings a data owner and the people who will use the answers.
Data Engineering and Pipelines
Pipelines with scheduled and incremental loads, automated data-quality tests, and a trace from each chart back to its source. They run on the warehouse you already have, or one we set up on AWS, Azure, or Google Cloud.
Healthcare Data Models
A clinical data model based on FHIR resources, mapped to OMOP, the research community's standard model, when the data also feeds studies. Codes from ICD-10-CM, CPT, LOINC, SNOMED CT, and RxNorm are normalized so reports group them correctly.
De-identification and Access Control
De-identification follows one of HIPAA's two methods, Safe Harbor or Expert Determination, and date-level work uses a limited data set under a data use agreement. Patient data runs only on services covered by the vendor's business associate agreement.
Machine Learning and Model Monitoring
We build model inputs in the warehouse, test on past records the model never saw, and compare accuracy across patient groups such as age, sex, and payer type. After launch, monitoring flags drift, when accuracy drops as patient mix or coding changes.
Self-Serve Analytics
A governed metrics layer that business users query through BI tools or plain-language questions. Business users answer routine questions themselves from approved definitions.
Our healthcare analytics consulting services start with a discovery that ends in a costed plan. It lists the decisions in scope, the data access requests to file, the team, and the order of releases. Your side brings a data owner and the people who will use the answers.
Our Data and AI Case Studies
Revvel
Revvel
Medical claims automation for a US healthcare IPA.
We built an internal platform that replaces spreadsheet-driven claims work with an automated pipeline: payer CSV imports with upsert logic, automatic validation of paid amounts against provider contracts, dispute tracking, payment batching, and EOP generation.
InfiniHealth IPA
InfiniHealth IPA
AI-powered women’s health platform.
We developed an AI platform that turns elite health experts into digital twins and reviews years of patient data in under 60 seconds, delivering risk assessments up to 10x faster and cutting time-to-care from days to minutes.
Hola Salud
Hola Salud
Digital healthcare platform for Mexico.
We built a complete healthcare ecosystem, including a patient app, a doctor’s portal, and an admin backend, with self-registration, appointment booking, medical records, and integrated Stripe and Oxxo payments.
Shift.AI
Shift.AI
AI support tool for clinicians, built for Inclusive Health.
We built a mobile app that gives clinicians brief, trauma-informed AI support in real time, with bidirectional voice chat, guided meditation and grounding flows, and conversation memory across sessions. The MVP was delivered in 3 weeks.
Flexible Developer Hiring Model
Your priorities define the way we work together — from how much control you want to the level of flexibility your project demands.
Team Augmentation
Quickly scale your workforce with skilled developers who integrate seamlessly into your in-house team, filling talent gaps and boosting productivity.
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Dedicated Development Team
A whole, cross-functional team working exclusively on your project, providing end-to-end development, management, and long-term support.
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Software Development Outsourcing
Delegate your entire project to our specialists and focus on business growth, while we handle development, delivery, and quality.
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Why Plus8Soft?
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Experience
Multiplied by AI
Multiplied by AI
We blend deep engineering expertise with cutting-edge AI acceleration. By integrating intelligent tools into our workflow, we don't just write code—we engineer solutions faster and with higher precision.
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Business-First
Transparency
Transparency
We look beyond the ticket. Our team operates with hyper-transparency, treating your budget and goals as our own. We align technical decisions with your business strategy to create real, measurable value.
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Committed to
Overdelivery
Overdelivery
Meeting requirements is our baseline; exceeding them is our culture. Whether it's optimizing performance, refining UX, or anticipating future scalability, we consistently go the extra mile.
Healthcare Data Analytics Services FAQ
How much do healthcare data analytics services cost with Plus8Soft?
Cost depends on how many sources feed the platform, how clean they are, and whether the work goes past dashboards to predictive models. Discovery produces a costed plan for the first release. Subscription fees for the warehouse and BI tools are paid to those vendors directly.
How long does a healthcare analytics project take with Plus8Soft?
We plan the first release around the first decisions and the sources they need, so the first dashboards can ship before the full platform is finished. Access to data usually sets the pace. EHR and claims extracts often take longer to approve than the pipelines take to build, so we file those requests in the first weeks.
How do you get data out of Epic, Oracle Health, or Athenahealth for analytics?
Through the routes the health system already supports. FHIR bulk export pulls patient groups that the health system defines and authorizes, which suits initial loads and periodic refreshes. Reporting databases, such as Epic's Clarity and Caboodle or Athenahealth's Data View, are reached through the health system's own analytics team. HL7 v2 feeds from the health system's interface engine carry near-real-time events such as admissions and results. For a digital health company without direct EHR access, we work through the health system partner's integration team.
How do your medical data analytics services protect patient privacy?
By default, analysts and vendors work on de-identified data or a limited data set. Date-level work such as readmission tracking usually needs Expert Determination or a limited data set under a data use agreement, because Safe Harbor removes dates. When our engineers need identifiable data, access is granted per task, and we sign a business associate agreement with you. Whether HIPAA or another health-privacy law applies is your counsel's call; we design access to match.
How do you make sure different dashboards show the same numbers?
Every metric is defined once in a shared metrics layer, with the definition, the source fields, and the owner written down. Dashboards and reports read from that layer instead of computing their own versions. When a definition changes, the change is versioned and the affected reports are listed.
How do you decide when a predictive model is ready to use?
We compare it against the rule or judgment it would replace, on a recent period the model has not seen. A model gets a named owner on your side and a threshold at which it is switched off. Any model that informs care is signed off by a clinician before launch and retrained on a set schedule.
Can you work with the BI tools and warehouse we already use?
Yes. We build on the warehouse and BI tools your team already runs, including Power BI, Tableau, and Looker, and set up a new stack only where none exists.
Can you build analytics into our digital health product?
Patient and clinician insights can run inside your app on the same data model as your internal reporting. Users then see the numbers your team sees.
