CareFlow
One platform for a Management Services Organization to manage its patients. A single record across every provider, a risk score on every panel, care plans that are actually followed up, and the statistics leaders need to decide. Revenue-cycle functions integrate into the same platform when an MSO needs them.
CareFlow is a platform built by CodeREM Labs for healthcare Management Services Organizations. It is built around the work an MSO does for patients: consolidating a patient's record across every provider in the network, stratifying panels by risk score, holding a structured care plan for each patient who needs one, and driving the follow-up that closes care gaps, with quality reporting produced from the same data instead of assembled by hand. Where an MSO also carries the revenue cycle, credentialing, payer contracts, prior authorization, coding, claims, billing and denial management integrate into the same platform as modules. It was built prototype-first, so every workflow could be proven as a working screen before it was hardened into a product.
01 · The challenge
Nobody holds the whole patient.
Healthcare has a simple contract at its core: consumers are entitled to care, and providers are entitled to be paid for the services they render. Management Services Organizations exist to make sure both halves of that promise are kept. But the half that decides whether patients actually get better is care management, knowing who in the panel is at risk, what plan they are on, and whether anyone followed up.
That is far harder than it sounds, because the information is scattered by design. One patient touches several providers, each running its own system, so no one holds the complete record. Risk gets judged by whoever happens to be looking. Care plans live as free text in a note, follow-up depends on somebody remembering, and quality reporting for HEDIS, Stars and the rest is reconstructed by hand at month end, consuming hundreds of hours.
Because each function is a specialty, MSOs typically carry large, deeply specialized teams to cover it, and care gaps still slip through. Alongside all of it sits the revenue cycle, credentialing through denial management, usually in yet another set of systems that never speaks to the clinical side.
02 · Approach
Research the domain, prove it in a prototype.
Care management is a famously deep domain. We researched as we built and proved each workflow as a working screen before hardening it into the product.
- Mapped care-coordination workflows, risk models and regulatory requirements onto a single patient-centred data model.
- Architected a HIPAA-compliant platform with end-to-end encryption and comprehensive audit logging.
- Built integrations with major EHR systems (Epic, Cerner) using HL7 FHIR, so one record follows the patient across providers.
- Developed risk stratification and a care-gap identification engine using rule-based logic and ML models.
- Turned care plans into tracked work: goals, interventions, an owner, due dates and escalation, not free text in a note.
- Created automated reporting pipelines for HEDIS, Stars and other quality measures.
- Kept revenue-cycle functions as separate modules that plug into the same record when an MSO needs them.
03 · The platform
Every patient, one view.
The platform is organized around the patient: what is known about them, how much risk they carry, what the plan is, and who is chasing it.
Unified patient record
Encounters, conditions, medications and results from every provider in the network, pulled over HL7 FHIR into one longitudinal record instead of a dozen partial ones.
Risk stratification
Every patient carries a risk score built from clinical signals, utilization and history. Panels sort by who needs attention first, and each score explains the factors behind it.
Care plans
Each patient who needs one gets a structured plan: goals, interventions, an owner and due dates. A plan is a tracked object in the system, not a paragraph someone typed into a note.
Follow-up & outreach
Scheduled touchpoints, appointments, reminders and escalation when a plan slips. The platform does the chasing, so closing the loop never depends on someone remembering.
Care-gap engine
An intelligent engine combining rule-based logic and ML proactively identifies care gaps across the panel, turning missed opportunities into scheduled work.
Statistics & reporting
Automated pipelines for HEDIS, Stars and other quality measures, with live statistics that turn months of manual reporting into hours.
Product view
Inside the product.
A few of the real screens we shipped. Browse with the arrows or dots — click the front screen to open it full screen.
A risk score is only worth as much as the follow-up behind it. CareFlow makes the follow-up the product.
04 · The loop
Score, plan, follow up, close.
Every patient in the network is continuously scored as new data arrives from any provider. The score is not a black box: it surfaces the conditions, utilization patterns and open gaps that drove it, so a care manager can see in seconds why this patient rose to the top of the panel.
From that score, CareFlow opens a care plan with goals, interventions, an assigned owner and dates. Outreach and appointments are scheduled against the plan, each touchpoint is recorded, and a plan that stalls escalates rather than quietly ageing. When the intervention lands, the gap it was opened against closes, the score moves, and the whole trail stays on the record.
That loop is what an MSO is actually paid to run, and it is the part that usually lives in spreadsheets and memory. Here it runs as tracked work with an audit trail, which is also what turns quality reporting from a month-end reconstruction into a query.
05 · Outcome
A platform that knows the patient.
CareFlow ships a care-management platform where an MSO can see every patient in its network as one record, know which of them are at risk and why, hold a real plan for each of them, and prove the follow-up happened, with quality reporting falling out of the same data rather than being rebuilt each month.
Revenue-cycle work integrates into the same platform as modules when an organization carries it, so the clinical and operational sides finally read from one record instead of two, and the hardest work in healthcare gets meaningfully lighter.
Managing patients across a network?
Well begun is half done.
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