Work Measurement
Billed work is captured as relative value units by encounter and procedure, aggregated per provider and period. Billed work is what this measures rather than clinical effort or value. Coding intensity affects it too.
Custom Software
Physician Productivity Analytics Platform
Productivity analytics measures billed clinical work, panel characteristics, and access by provider, models compensation against those measures, and compares to benchmarks you license. It measures and models. It does not evaluate clinical quality, judge effort, or determine anyone’s compensation.
Work relative value units measure billed activity. They do not measure effort, value, or the difficulty of a panel, and treating them as though they do produces two predictable outcomes: physicians who serve complex populations look unproductive, and coding intensity rises. Taction builds productivity analytics with attribution and case mix visible, because a figure without that context invites exactly those distortions.
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What Is Productivity Analytics
It measures clinical work by provider, using billed activity, encounter counts, panel characteristics, and access measures, then supports compensation modelling and benchmark comparison. Every part of it depends on attribution rules deciding who receives credit for shared care. It sits inside a wider healthcare data analytics practice, and our analytics consulting work settles the definitions before anything is measured. Attribution decides every downstream figure, and in a productivity-linked compensation model those figures are money, which is why we settle the rules in writing with your physician leadership before measuring anything.
Attribution Rules
Shared care, supervision, and team models require explicit rules about who receives credit. Attribution rules are a leadership decision with real financial consequences attached. Getting them wrong once damages physician trust for years afterwards.
Panel Characteristics
Panel size, complexity, payer mix, and continuity described alongside our population health analytics practice. Panel context is what makes comparison meaningful. Comparing physicians without panel context is naive rather than rigorous.
Access Measures
Appointment availability, third next available, and template utilisation from your practice management systems. Access measures describe capacity rather than effort. A scheduling constraint should not be read as low productivity.
Compensation Modelling
Existing and proposed compensation models applied to measured work so effects can be seen before adoption. Modelling shows consequences rather than recommending a model. We show consequences rather than recommending which model to adopt.
What Productivity Analytics Does Not Do
It does not measure quality, judge effort, determine compensation, or evaluate a clinician’s performance overall. Those judgements belong to leadership and peer review processes. We state that limitation inside the reporting itself.
Core Productivity Analytics Services
The work that decides whether this survives is attribution and context. Physicians accept measurement they consider fair and reject measurement they consider naive, and case mix without context is naive. We build attribution rules first, agreed in writing, then panel and payer context alongside every productivity figure. Our data quality practice covers the provider and encounter data integrity everything else depends upon. Physicians see their own figures with traceable encounters before any management reporting launches, because measurement they consider unfair produces gaming rather than engagement. Quality programme measures come from our MIPS and MACRA work rather than being recalculated here.
01
Attribution Rule Build
Rules for shared visits, supervision, procedures, and team-based care implemented, versioned, and documented readably. Readable rules are what physicians can check and accept. Physicians can check the rule that produced their own number.
02
Work Measurement
Billed activity captured per provider and period with source encounters traceable and coding context available. Traceable encounters let a physician verify their own figure directly. Coding intensity effects stay visible rather than hidden.
03
Panel and Complexity Context
Panel size, complexity, payer mix, and continuity reported alongside work measures rather than separately. Context alongside rather than in an appendix nobody opens. Context appears with the figure rather than in a separate report.
04
Access and Capacity Reporting
Template utilisation, availability, and cancellation patterns reported as capacity measures. Capacity distinction prevents access problems being read as productivity problems. Template and cancellation patterns are capacity facts rather than effort measures.
05
Compensation Model Simulation
Proposed models applied to historical measured work so distributional effects are visible before adoption. Simulation surfaces the unintended consequences early. Distributional effects appear before adoption rather than in the first payment cycle.
06
Benchmark Comparison
Comparison against benchmark datasets you license, with cohort and specialty caveats stated explicitly. Cohort caveats matter because a mismatched specialty definition or cohort produces a comparison that misleads badly and confidently.
Benefits of Productivity Analytics
We publish no figures on productivity gains, compensation savings, or benchmark movement, because those depend entirely on your specialty mix, your attribution rules, and decisions your leadership makes. What we deliver is instrumentation so your team measures impact against its own data. The benefit is measurement physicians will engage with, because attribution is transparent and case mix is visible. Measurement they consider unfair produces gaming rather than improvement. Read the items below as measurement fairness and traceability rather than as any claim about productivity gains, which follow from decisions and capacity rather than reporting.
Attribution Physicians Can Check
Every figure traces to encounters and the rules that assigned them. Traceable attribution is the precondition for any physician accepting a number. Verification is possible without asking an analyst to explain it.
Context Alongside Every Figure
Panel complexity and payer mix appear with work measures rather than being available on request. Context by default prevents the naive comparison. The naive cross-physician comparison becomes harder to produce accidentally.
Capacity Distinguished From Effort
Access and template measures are reported separately from work measures. Separate reporting stops a scheduling problem being attributed to a physician. Scheduling and template problems are addressed by the right people.
Compensation Effects Visible First
Model changes are simulated against real history before anyone adopts them. Simulation avoids discovering distributional effects after implementation. Unintended distributional consequences surface while there is still time to change them.
Benchmarks Used Carefully
Comparison states the cohort, specialty definition, and period rather than presenting a percentile alone. Stated caveats keep the comparison honest, because a mismatched cohort or specialty definition will mislead you confidently.
An Honest Position
Billed work is not clinical value, and treating it as such penalises complexity. That limitation is stated in the reporting itself rather than only here. We state it rather than implying otherwise.
Our Productivity Analytics Process
We start with attribution, because it determines every downstream figure and because getting it wrong destroys physician trust permanently. Discovery is paid and time-boxed and produces an itemised fixed-scope estimate with a build or configure recommendation. Where your practice management system already reports adequately and the gap is attribution or context, we scope that alone. Delivery runs in short increments with physician leadership reviewing figures each time. Physician leadership reviews figures at every increment, because acceptance is the outcome that determines whether this platform is used or quietly worked around.
Attribution Design
Rules for shared care, supervision, and procedures agreed with physician and administrative leadership in writing. Written agreement precedes implementation without exception. Shared visits, supervision, and procedures each need their own rule.
Source and Coding Assessment
Encounter, charge, and provider data assessed for completeness and attribution feasibility, with our medical coding practice informing coding context. Data reality constrains attribution. Data reality constrains what attribution can honestly be implemented.
Context Definition
Panel attribution, complexity measures, and payer mix definitions agreed so comparison is meaningful. Comparison validity depends entirely on these definitions. Comparison validity depends entirely on how these measures are defined.
Build and Validation
Measurement, attribution, context, and access reporting built in increments and validated against known physicians’ own records. Physician validation catches attribution errors. Individual physicians check their own figures against their own records.
Model Simulation
Existing and proposed compensation models simulated with distributional effects reported to leadership. Distributional reporting is part of the deliverable. Distributional reporting to leadership is part of the deliverable rather than optional.
Rollout and Handover
Phased release with physician-facing views first, then handover with attribution rule ownership transferred. Physician-facing first builds trust before management reporting. Attribution rule ownership transfers to your physician leadership after go-live.
Technology and Compliance
We build measurement and modelling on your data platform, with our credentialing practice supplying provider identity where needed. Benchmark datasets are licensed directly by your organisation, and we integrate what you hold rather than supplying comparative data. Compliance covers HIPAA safeguards, access control appropriate to provider-level financial information, and audit sufficient to reconstruct any published figure or simulation result. We also retain every simulation with its assumptions, because a compensation model discussion months later turns on exactly which version produced which projection and which assumptions were in force. Reporting is delivered through our data visualisation practice.
Attribution Rules Are Versioned
Every figure records the attribution rule version that produced it. Version records explain why a physician’s number changed between periods. A physician’s number changing between periods becomes immediately explicable to them.
No Automated Compensation Adjustment
Compensation decisions are made by leadership and communicated by people. We decline to build automated adjustment or payment triggers from measured productivity. Leadership decides and people communicate those decisions personally.
Context Is Not Optional
Panel complexity and payer mix are attached to provider figures in the data model. Structural context prevents a naive comparison being produced accidentally. Producing a naive comparison requires deliberately removing the context.
No Coding Intensity Prompting
We decline to build prompts encouraging documentation or coding changes to raise measured work. Intensity prompting creates real compliance exposure for you. Gaming rather than improvement is the predictable result of it.
Benchmark Licensing
Comparative datasets are yours under your subscription, and we claim no partnership or endorsement with any benchmarking organisation. Licensing remains entirely yours. We integrate what you hold rather than supplying comparative data ourselves.
Access and Audit
Provider-level data carries role-based access with logging, and simulations are retained with their assumptions. Simulation records matter in compensation disputes. Provider-level financial exposure is controlled deliberately rather than inherited from clinical access.
Why Choose Taction Software
We have been building healthcare software since 2013, which is over 12 years, and we have delivered more than 200 healthcare projects. We built our own EHR platform, Voyant Health, so encounter data, charge capture, and provider attribution mechanics are working knowledge rather than assumptions. We are ISO 27001 certified, our leadership brings more than 20 years of personal experience in the field, and we work from four US offices in Chicago, Cheyenne, Austin, and Sacramento. We will also tell you when your practice management reporting already covers this and only attribution is missing.
01
Attribution First
We settle attribution rules in writing before measuring anything. That sequence costs project time and is the only route to physician acceptance. Physician acceptance has no other route available to it.
02
Physician-Facing Before Management
Physicians see their own figures with traceable encounters before management reporting launches. That order builds trust rather than suspicion. Trust built early survives the first uncomfortable comparison that follows later.
03
Context Structurally Attached
Panel complexity and payer mix travel with provider figures in the model. Structural attachment makes the naive comparison harder to produce. Complexity and payer mix are properties of the figure rather than options.
04
Security Posture
Taction is ISO 27001 certified, with documented access control, encryption, and change control that stands up to a customer security review. Provider-level financial data carries role-based access with full logging.
05
We Refuse Intensity Prompting
We will not build prompts designed to raise measured work through documentation change. That refusal protects you from a compliance exposure. Compliance exposure and physician cynicism are both avoidable outcomes.
06
US Presence
Four US offices in Chicago, Cheyenne, Austin, and Sacramento, with delivery overlapping your hours through attribution design and validation. Escalation reaches a named delivery lead rather than a shared support queue.
Pricing
Pricing turns on attribution complexity, specialty count, and whether a data platform already exists. The tiers below cover engineering. Third-party licensing, cloud infrastructure, data subscriptions, and hardware are separate from engineering cost and itemised clearly. Benchmark and comparative datasets are licensed directly by your organisation, and compensation consulting, which we do not provide, sits outside this estimate entirely at every tier. Where attribution rules are unagreed, that facilitation is quoted openly rather than absorbed into a build estimate that then overruns badly once that disagreement becomes visible in a workshop.
MVP or Single Module
$40,000 to $80,000 for work measurement with agreed attribution rules, physician-facing traceable views, and panel context for one group. Compensation simulation and benchmark comparison can follow in a later phase.
Full Platform Build
$80,000 to $200,000 for measurement, attribution, panel and complexity context, access reporting, compensation simulation, and benchmark comparison. This tier covers most single-group medical programmes that we are asked to scope.
Enterprise Deployment
Starting at $200,000 for multi-entity groups with several specialties, differing compensation models, platform build, and consolidated governance. Attribution complexity and model variety drive the final figure more than provider numbers do.
Discovery Phase Scoping
A paid, time-boxed discovery phase produces an attribution design, source and coding assessment, context definitions, build or configure recommendation, and an itemised estimate. The attribution design is yours whether or not we build.
Cost Drivers to Expect
Attribution complexity, specialty count, compensation model variety, and provider data quality. Team-based attribution costs more than any other single factor. Facilitating attribution agreement is real work that we quote openly and separately.
Ongoing Support Costs
Budget annually for attribution rule review, benchmark refresh, model simulation support, and source system change handling. Rule reviews follow compensation cycle changes. Rule reviews follow your compensation cycle rather than a technical schedule.
Get Started
If your compensation discussions turn into arguments about who got credit for what, start with attribution. A paid discovery phase gives you an attribution design covering shared care, supervision, and procedures for your leadership to agree, an assessment of your encounter and provider data, panel and complexity definitions that make comparison meaningful, a build or configure recommendation, and an itemised fixed-scope estimate. You keep the attribution design regardless of what you build.
FAQs
Frequently Asked Questions
These are the questions medical group leaders, compensation committees, and administrators raise before scoping productivity work. Several concern the limitations of the measure itself, which we would rather state plainly than let a percentile imply otherwise. One concerns something we refuse to build. Where an answer depends on your attribution model, the discovery design settles it quickly. We would rather explain that billed work is not clinical value than hand you percentiles that penalise the physicians carrying your most complex panels. The measure is useful; the percentile alone is not.
No. They measure billed clinical activity, which correlates with some kinds of work and not with complexity, coordination, teaching, or difficult conversations. We report them as what they are and attach panel complexity and payer mix so comparison is informed. Presenting a percentile alone as a performance measure is how this analysis loses physician engagement.
Because in shared care, supervision, and procedural settings, the rule deciding who receives credit determines the figure, and in productivity-linked compensation that figure is money. Getting attribution wrong once destroys physician trust for years. We agree the rules in writing with physician leadership before implementing anything.
No, and we decline to build it. Compensation decisions belong to leadership, informed by measurement and communicated by people who can explain them. Automated adjustment from measured productivity removes the judgement and the conversation that make a compensation model defensible in the first place. That boundary appears in our proposals.
We will make the measurement accurate and show where attribution understates real work, which sometimes raises figures legitimately. We will not build prompts encouraging documentation or coding changes to raise measured work, because that creates compliance exposure and produces gaming rather than any actual change in care delivered.
Carefully, with the cohort, specialty definition, and period stated. Benchmark datasets are licensed by you, and mismatched specialty definitions or cohorts produce comparisons that mislead confidently. We integrate what you hold, state the caveats in the reporting itself, and claim no relationship with any benchmarking organisation.
That is exactly why panel complexity and payer mix are attached structurally to every provider figure rather than being available separately. A physician serving a complex population appears unproductive under raw work measurement, and building the platform without that context would penalise the people doing the hardest work.