Care gap identification measured on precision rather than volume. Gaps validated before anyone is contacted, bundled by patient rather than by measure, matched to the channel most likely to work for that person, and verified in the source the measure actually reads
Most organizations do not have a care gap detection problem. They have twenty thousand open gaps, capacity to work a fraction of them, and a clinical team that stopped trusting the list because too much of it was already done. CaliberFocus builds the engine that turns that into a validated, deduplicated, capacity-matched worklist serving every quality programme at once, so a patient receives one contact rather than four and a physician receives one list rather than four.
A false gap costs more than a missed one. The missed gap costs you one measure. The false gap costs you the clinician.
Every quality programme generates gaps. Each is produced by a different team from different data on a different cadence, and each arrives separately at the same physician and the same patient. The volume exceeds any realistic capacity to act, a meaningful share of it is already closed or was never eligible, and nobody is tracking which contacts actually produced a closure.
Clinicians work the list twice, find work they already did, and stop opening it. Once that happens, improving detection does nothing because the constraint has moved from finding gaps to being believed about them.
A false gap is more expensive than a missed one
A false gap damages the credibility of the entire list, including every future gap that was correct.
Most apparent gaps are data problems
Care delivered elsewhere, narrative documentation, wrong-field data or patients never actually eligible should not be routed to clinicians.
Volume exceeds capacity by an order of magnitude
Twenty thousand gaps with capacity for two thousand contacts is the defining constraint, not a minor prioritization issue.
Organized by measure, experienced by patient
The patient receives separate contacts for things that could have been handled in one conversation.
Closure recorded in the wrong place
An outreach tracker can say “closed” while the measure still reads the gap as open.
Outreach can work best for the already engaged
A programme can raise its overall rate while quietly widening the disparity underneath it.
Precision before recall.
Detection is the easy half. We optimize the opposite way: fewer gaps, each one validated, because a list that is right earns the attention that makes the next one actionable.
Detection is the easy half. We optimize the opposite way: fewer gaps, each one validated, because a list that is right earns the attention that makes the next one actionable.
The order matters. Validation protects trust. Bundling changes the priorities. Matching to capacity prevents a worklist nobody can finish.
Step 1
Detect across every source
Claims, EHR, labs, pharmacy, HIE and payer files, so care delivered elsewhere is not counted as a gap.
Step 2
Validate eligibility
Confirm the patient genuinely belongs in the denominator, including exclusions and exceptions.
Step 3
Classify the gap type
Care not delivered, care not documented, wrong field, mapping error or not eligible.
Step 4
Deduplicate across programmes
The same clinical action serving four measures becomes one gap.
Step 5
Bundle by patient
Group everything closable in one contact or encounter, because contacts are the scarce resource.
Step 6
Prioritize against real capacity
Rank against the contacts and clinical time actually available this period
Step 7
Match the channel to the person
Portal, text, call, letter, in-visit or care management based on what has worked before.
Step 8
Route into existing workflow
Pre-visit planning, the encounter, care management or outreach, in the system the team already uses.
Step 9
Verify and retune
Confirm closure where the measure reads, attribute it to the intervention, and feed precision back into detection.
One engine, every programme.
The same validated gap serves ACO quality, Stars/HEDIS-type measures, MIPS and risk documentation. The programme pages describe the programmes. This is where the work actually gets built.
The same validated gap serves ACO quality, Stars/HEDIS-type measures, MIPS and risk documentation. The programme pages describe the programmes. This is where the work actually gets built.
There is no Computing a measure denominator and finding who is missing from the numerator is straightforward. What determines whether anything closes is validation quality, bundling, capacity-aware prioritization, channel fit and verified closure.
Detect and Validate
Multi-Source Detection
Claims, EHR, laboratory, pharmacy, HIE and payer supplemental data.
Eligibility and Exclusion Validation
Confirm the patient belongs in the denominator and remove false gaps before routing.
Gap Classification
Care not delivered, care not documented, wrong field, mapping error or not eligible.
Cross-Programme Deduplication
One clinical action serving multiple measures becomes one patient-level gap.
Prioritize and Reach
Patient-Level Bundling
Everything closable in one contact or encounter grouped together.
Capacity-Constrained Prioritization
Ranking against real outreach contacts, clinical slots and care-management hours, with the cut line visible.
Channel Matching and Sequencing
Choose and sequence channels based on prior response, preference, language, access and the nature of the gap.
Pre-Visit and In-Workflow Delivery
Surface appropriate gaps where closure costs no extra contact because the patient is already there.
Close and Learn
Closure Verification
Confirm closure in the source system the measure reads, not an outreach tracker.
Intervention Attribution
Connect closures to the contact, channel and message that preceded them.
Funnel Analytics
Track movement from identified through validated, actionable, routed, attempted, completed and verified.
Equity Monitoring
Examine reach and closure by language, geography, coverage and access.
What CaliberFocus does, and does not do?
We do not staff your call centre and we do not run your care management team. We build the engine that decides who those teams should contact, about what, through which channel and in what order, and we verify whether it worked. If your constraint is outreach capacity rather than targeting, we will tell you that.
We do not staff your call centre and we do not run your care management team. We build the engine that decides who those teams should contact, about what, through which channel and in what order, and we verify whether it worked. If your constraint is outreach capacity rather than targeting, we will tell you that.
A detected gap is a hypothesis. It becomes a worklist item only after it survives every gate below. Removing false gaps before distribution is the single highest-value thing this engine does.
| Gate | The Question | What Fails Here |
|---|---|---|
| Eligibility | Is this patient genuinely in the measure population on age, condition, coverage and timing? | Patients never in scope, often from attribution or enrolment timing. |
| Exclusion and Exception | Does a permitted exclusion or documented exception apply? | Exclusions in narrative text, or clinically known and never coded. |
| Completion Elsewhere | Was this already done somewhere we can see if we look? | Care delivered at another organization, visible in claims, HIE or pharmacy data. |
| Documentation Location | Was it done here and recorded where the measure cannot read it? | Results in scanned documents, values in the wrong field, counselling in narrative. |
| Actionability | Is there still time and a realistic route to close it this period? | Gaps needing an intervention and documented result with insufficient time remaining. |
What survives the gates still needs typing, because the destination differs entirely.
Care not delivered
Clinical or care-management workflow
Care not documented
Documentation fix
Wrong field
EHR build / workflow configuration
Mapping error
Data team
Not eligible
Remove from worklist
Only one of the five categories is a clinical gap.
A patient should never receive an outreach call because an interface failed
A patient should never receive an outreach call because an interface failed
The scarce resource is contacts and clinical time, so the unit of prioritization has to be the patient and the ranking has to stop at the capacity line.
Bundle first, then rank
A patient with four closable gaps can outrank four patients with one each because one contact does the work of four.
Rank on value and reachability together
Measure value, distance to threshold, clinical importance and realistic probability of reaching this patient.
Cut at the capacity line, visibly
What sits below the line is recorded, not distributed, so the team is not working an infinite queue.
| Destination | Best Fit | Why |
|---|---|---|
| Pre-visit Planning | Patients with an upcoming encounter | Uses an interaction already happening and is often the lowest-burden closure. |
| Provider Workflow | Gaps needing assessment, order or decision | Outreach cannot resolve a clinical decision. |
| Care Management | Complex patients with interacting needs | The gap is part of a larger picture and will not close in isolation. |
| Patient Outreach | Scheduling, reminders and preventive services | Patient action is genuinely the barrier. |
| Referral Coordination | Services completed externally | Scheduling the referral is not completing the care; the result must return. |
| Data Remediation | Documentation, mapping and structured-field failures | The patient should not be asked to fix a data problem. |
Channel Fit Is a Patient Property, Not a Programme Default
Channel is selected per patient on prior response, stated preference, language, access and the nature of the gap, with a defined escalation sequence when the first attempt does not land.
Check Before You Contact, and Record What Happened
Before a contact goes out, check other open gaps, prior contact, booked appointments, recent declines, active interventions, preferred channel and language. Afterwards, every attempt closes with a disposition rather than a free-text note.
Preference and consent honored per patient
Stated contact preferences, opt-outs and revocations respected across channels and programmes.
Automated outreach governed by contact law
Consent status verified per contact; automated outreach language should be reviewed with legal before launch.
Frequency capped across programmes
A patient in four programmes should not receive four campaigns.
Minimum necessary in the message
Outreach content limited to what the interaction requires, with stricter handling for sensitive conditions.
Verification is the difference between a programme that works and one that reports that it works.
Confirm in the source, not the tracker
Closure is confirmed in the field the measure actually reads, with the tracker updated from that rather than the other way round.
Attribute closure to the intervention
Identify which contact, channel and message preceded the closure so effectiveness is measured rather than assumed.
Measure Effectiveness by Segment, Not in Aggregate
Closure and reach should be examined by language, geography, coverage and access. If outreach works best for people who were already engaged, the overall rate can improve while the underlying disparity widens.
Closure and reach should be examined by language, geography, coverage and access. If outreach works best for people who were already engaged, the overall rate can improve while the underlying disparity widens.
Gap engines built on private extracts diverge from quality reporting. This work should consume the same governed data products as the rest of the performance environment.
Data foundation
- Built on the governed data platform
- Patient identity resolved before detection
- Data freshness visible per gap
Logic and definitions
- One governed measure definition serving detection, reporting and closure
- Validation and classification rules held as configuration
- Specification changes treated as controlled releases
- Lineage from a gap back to the data that generated it
- Programme rules and value sets versioned by effective date
Outreach compliance
- Consent, preference and revocation status verified per contact and channel
- Automated outreach designed with legal before launch
- Contact frequency capped at patient level across programmes
- Sensitive conditions handled under stricter rules where appropriate
Oversight
- Equity monitoring by language, geography, coverage and access
- Clinician feedback route for wrong gaps
- Named owner for list quality, distinct from closure performance
Give list quality its own owner.
When one person owns closure numbers and nobody owns precision, the list grows because adding gaps looks like progress and removing them looks like losing ground. Separating the roles protects list quality.
When one person owns closure numbers and nobody owns precision, the list grows because adding gaps looks like progress and removing them looks like losing ground. Separating the roles protects list quality.
Gap programmes are almost always reported on gaps closed. That number can rise while the list gets less accurate, contacts get less efficient and clinicians disengage.
| Category | What We Measure | Why It Matters |
|---|---|---|
| Precision | False gap rate, gaps dismissed as already done or not eligible, clinician-reported list quality | The measure that protects everything else. It should improve every period. |
| Efficiency | Closures per contact, gaps closed per patient contacted, bundling rate | Contacts are the constraint, so this is the real productivity measure. |
| Verified Closure | Gaps verified in source versus recorded closed in a tracker | The gap between these numbers is how much reporting is not real. |
| Channel Effectiveness | Reach and closure by channel and segment, and cost per verified closure | Directs where outreach capacity should go next period. |
| Equity | Reach and closure by language, geography, coverage and access | Shows whether improvement is distributed or concentrated. |
| Funnel Conversion | Movement through identified, validated, actionable, routed, attempted, completed and verified | The largest stage-to-stage drop is the operating problem, and it names the owner. |
| Clinical Burden | Gaps reaching clinicians per period, duplication removed, in-encounter closure share | The sustainability measure. A programme that costs clinicians more each period will end. |
Expect the reported gap count to fall sharply in the first period.
Removing gaps that were already closed, never eligible or wrongly classified can make the headline number look worse before closure performance improves. A shorter accurate list is the objective.
Removing gaps that were already closed, never eligible or wrongly classified can make the headline number look worse before closure performance improves. A shorter accurate list is the objective.
We will take a sample of your current gaps, run them through validation, and report what fraction fails eligibility, was already completed elsewhere, is documented where the measure cannot see it, or is not actionable in the time remaining. In most organizations that fraction surprises people. It also identifies exactly where the engine needs building.
Bring us a specialty or clinical setting where clinicians are spending too much time creating notes. We will assess where ambient documentation fits, what must remain clinician controlled, how it should integrate with your EHR, and how to measure whether it is actually reducing burden.
One conversation with people who have run these deployments, and a written readiness view you can use with or without us.
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