Indicator Logic
Each indicator defines a numerator, denominator, and exclusions using diagnosis and procedure coding drawn from ICD-10. Indicator logic operates on codes, not on clinical narrative or judgement. Coding accuracy therefore drives it.
Custom Software
AHRQ Patient Safety Indicators (PSI) Services
Patient safety indicator software identifies cases that meet an indicator’s administrative criteria, routes each one for clinical and coding review, and reports rates with exclusions and risk adjustment applied. It flags and organises review. It does not determine that harm occurred or that care was substandard.
Patient safety indicators are computed from administrative coding, which means they measure documentation and coding at least as much as they measure care. A flagged case is a question, not a finding, and many resolve as coding accuracy or a condition present on admission. Taction builds the review workflow that answers those questions properly, and refuses to build the shortcut around them.
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What Is PSI Software
Indicator software applies published indicator logic to coded encounter data, surfaces the resulting cases, and supports the review that establishes what actually happened. It then reports rates with exclusions, risk adjustment, and comparison where you have benchmark data. It sits inside a wider healthcare compliance programme and connects to your incident reporting and risk management systems rather than duplicating them. The honest framing is that these indicators describe your coded data, and a review programme exists to establish what the coded data actually meant in each case rather than to defend a number.
Present on Admission
Conditions present at admission are excluded from several indicators, and that flag decides many cases. Present on admission accuracy is a documentation and coding problem before it is anything else.
Case Review Workflow
Flagged cases route to clinical review and to documentation and coding review, with findings recorded separately. Separate findings matter because the two reviews answer different questions. Reviewers see the record assembled rather than hunting it.
Exclusions and Risk Adjustment
Exclusions apply per indicator, and rates are risk adjusted for comparison against expected performance. Risk adjustment makes comparison possible and obscures individual case detail. Case-level detail stays available beneath every adjusted rate.
Benchmark Comparison
Observed and expected rates compare against whatever benchmark dataset your organisation subscribes to. Benchmark data is licensed by you rather than supplied by us. We integrate what you hold rather than supplying comparative data.
What PSI Software Does Not Do
It does not determine harm, judge care quality, suggest code changes, or attribute a case to a clinician. Those conclusions require clinical review by qualified people. A flag is a question rather than a finding.
Core PSI Services
The value here is in review throughput and honest classification. A programme that reviews cases weeks after coding is closed can correct nothing and learn little. A programme that reviews concurrently, while the record is still open, can address both documentation accuracy and genuine safety questions. We build for concurrent review, with the clinical and coding findings recorded distinctly so nobody later conflates a coding correction with a care improvement. Our clinical data integration practice supplies the coded data and timing that concurrent surfacing depends on, since working codes have to be available before final coding closes.
01
Concurrent Case Surfacing
Indicator logic applied against working coding during the stay or before final coding closes. Concurrent surfacing is what makes documentation clarification possible at all. Working codes have to be accessible before final coding closes.
02
Clinical Review Workflow
Cases routed to reviewers with the record assembled, findings captured, and harm assessment recorded by a clinician. Harm assessment is a clinical determination recorded rather than computed. Harm is never computed from codes.
03
Documentation and Coding Review
Parallel review of coding accuracy and documentation specificity, supported by our clinical documentation quality practice. Coding review answers a different question from clinical review. Conflating the two answers produces a misleading improvement story.
04
Query and Clarification Support
Documentation clarification tracked where the record is genuinely ambiguous, alongside our medical coding work. Clarification must seek accuracy rather than a particular answer. Leading questions create compliance exposure rather than accuracy.
05
Rate and Trend Reporting
Observed, expected, and stratified rates reported with case-level drill-down through our data analytics practice. Case-level detail is what clinicians require before accepting a rate. Committees reject rates they cannot examine case by case.
06
Correction and Rebilling Workflow
Where review establishes a genuine coding error, correction and any resulting rebilling follow your compliance process. Corrections follow the record, never the desired rate. Corrections are driven by the record rather than by a target.
Benefits of PSI Software
We publish no figures on indicator rates, review throughput, or benchmark position, because those depend entirely on your case mix, your documentation practice, and your coding quality. What we deliver is instrumentation so your team measures impact against its own data. The benefit is a review process that runs concurrently and classifies honestly, distinguishing coding accuracy from safety findings. Conflating those two is how organisations improve a rate while learning nothing about their care. Read the items below as review discipline and honest classification rather than as any claim about your indicator rates or public rating position.
Review Happens Concurrently
Cases surface while documentation can still be clarified accurately. Concurrent review is the only version that affects both accuracy and learning. Once coding closes, a documentation ambiguity becomes permanent and unfixable.
Coding and Care Separated
Findings record whether a case was a coding issue, a documentation gap, or a genuine safety event. Separate classification prevents a rate improvement masquerading as safety work. Both explanations get reported separately.
Rates You Can Interrogate
Every rate drills to its cases, exclusions, and review findings. Drill-down is what makes a rate credible to the clinicians it describes. A rate nobody can examine will simply be disputed instead.
Exclusions Documented
Applied exclusions carry their evidence rather than appearing as an unexplained adjustment. Documented exclusions withstand review by an auditor or a committee. An unexplained adjustment invites exactly the scrutiny it was avoiding.
Findings Reach Safety Work
Genuine safety events connect to your event reporting and improvement processes. Connected findings stop the indicator programme running parallel to safety work. An indicator programme running parallel to safety work benefits nobody.
An Honest Position
An indicator flags a coding pattern, not a harm event. We build classification that keeps that distinction visible rather than letting a rate imply harm. That distinction protects your credibility internally.
Our PSI Process
We start with a review of your current flagged case volume and how those cases were resolved historically, because that distribution tells us whether your problem is coding accuracy, review capacity, or genuine safety events. Discovery is paid and time-boxed and produces an itemised fixed-scope estimate with a build or configure recommendation. Delivery runs in short increments with your quality reviewers and coding staff using working software each time. The historical analysis is worth having on its own, because a programme discovering that most flagged cases were coding issues has a documentation problem rather than a safety problem.
Historical Case Analysis
Previous flagged cases reviewed for how they resolved: coding, documentation, present on admission, or genuine event. Resolution distribution tells us where the work is. That distribution decides where the software should concentrate.
Data and Timing Assessment
Coding availability, working code timing, and present on admission capture assessed for concurrent feasibility. Timing precision determines whether concurrent review is possible. Retrospective review remains possible where concurrent review is not.
Review Workflow Design
Clinical and coding review paths, reviewer assignment, and finding taxonomy designed with both teams. Finding taxonomy is agreed before any build begins. Both teams have to accept the taxonomy for reporting to mean anything.
Build and Integration
Surfacing, review workflow, exclusion documentation, and reporting built in increments with our EHR and EMR integration services. Integration avoids a parallel register. Events and indicator findings reference each other rather than duplicating.
Parallel Review Period
New workflow runs alongside the current process for a full coding cycle. Parallel running proves throughput and finding consistency under real conditions. Finding consistency between reviewers is what the parallel period tests.
Rollout and Handover
Live running with rate monitoring and finding distribution reporting, then handover with named owners. Distribution monitoring watches for classification drift. Classification drift is the thing worth watching after the first year.
Technology and Compliance
We implement published indicator specifications for the versions you report against, and we apply exclusions and risk adjustment as the specification defines rather than as convenience suggests. Benchmark datasets are licensed by your organisation rather than supplied by us. Compliance covers HIPAA safeguards, audit sufficient to reconstruct any reviewed case and its findings, and clear allocation of every determination to a qualified person. We also record which indicator version and which risk adjustment model produced every reported rate, because comparing this year against last year is otherwise an argument rather than an analysis.
Specification Versions
Indicator logic and risk adjustment models are versioned, and historical rates retain the version that produced them. Version retention explains year-on-year movement. Comparing across versions is stated rather than quietly assumed.
No Code Change Suggestions
We decline to build features suggesting code changes to avoid an indicator. Coding must reflect the record, and anything else creates real compliance exposure for you. That refusal precedes contracting.
Determinations Stay With People
Harm assessment is a clinician’s determination and coding accuracy is a certified coder’s. The software records both and produces neither. No conclusion in the system originates from software rather than a person.
Clarification Seeks Accuracy
Documentation clarification is built to resolve ambiguity, not to obtain a particular code. Leading clarification is a compliance risk we design against explicitly. Compliance review of query templates is part of the build.
No Clinician Attribution Scorecards
Indicators reflect systems and documentation rather than individual performance. We decline to build punitive individual scorecards from indicator cases. Punitive use suppresses the documentation honesty the programme depends on entirely.
Stratified Reporting
Rates are reported by subgroup so uneven safety outcomes become visible rather than averaged away. Stratification is standard output rather than a request. Findings go to clinical governance rather than into an appendix.
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 coded data, documentation timing, and the relationship between the record and the codes derived from it are working knowledge. 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 problem is documentation practice rather than software.
01
Honest Classification
We separate coding findings from safety findings in the data model. That separation costs a simpler dashboard and prevents a misleading improvement narrative. Leadership can then see which explanation a rate change reflects.
02
Concurrent by Design
We build for review before coding closes rather than retrospective analysis. Concurrent timing is what makes the programme useful rather than descriptive. Retrospective reporting describes a problem you can no longer address.
03
Platform Perspective
Building Voyant Health means we understand documentation timing and how present on admission capture actually behaves in practice. Present on admission capture behaves differently across units and different admission routes.
04
Security Posture
Taction is ISO 27001 certified, with documented access control, encryption, and change control that stands up to a customer security review. Review findings carry role-based access and a full audit trail.
05
We Refuse Coding Optimisation
We will not build features suggesting codes to avoid indicators. That refusal loses work and keeps you clear of a genuine compliance exposure. Coding has to reflect the record, without exception.
06
US Presence
Four US offices in Chicago, Cheyenne, Austin, and Sacramento, with delivery overlapping your hours during parallel review periods. Escalation reaches a named delivery lead rather than a shared support queue.
Pricing
PSI pricing turns on how many indicators are in scope, whether review is concurrent, and how many facilities report. 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 their subscription cost sits outside our estimate entirely at every tier. Concurrent review in particular depends on working coded data being available during the stay, and where it is not we scope retrospective review honestly rather than promising a capability your data cannot support.
MVP or Single Module
$40,000 to $80,000 for indicator surfacing with clinical and coding review workflow, finding classification, and rate reporting at one hospital. Concurrent surfacing can follow later where coding timing permits it.
Full Platform Build
$80,000 to $200,000 for concurrent surfacing, dual review paths, clarification tracking, exclusion documentation, risk-adjusted and stratified reporting, and event system integration. This tier covers most single-hospital indicator programmes that we are asked to scope.
Enterprise Deployment
Starting at $200,000 for multi-facility programmes with central indicator governance, site variation reporting, shared reviewer worklists, and benchmark integration. Facility count and indicator scope drive the figure more than case volume.
Discovery Phase Scoping
A paid, time-boxed discovery phase produces a historical case resolution analysis, timing feasibility assessment, build or configure recommendation, and an itemised estimate. The historical analysis is yours whether or not we build.
Cost Drivers to Expect
Indicator count, concurrent review scope, facility count, and present on admission capture quality. Concurrent review costs more than retrospective reporting. Poor present on admission capture shifts effort onto documentation work first.
Ongoing Support Costs
Budget annually for specification and risk adjustment version updates, finding taxonomy review, and EHR upgrade regression testing. Version updates arrive on the publisher’s schedule. Risk adjustment models are revised on the publisher’s own schedule.
Get Started
If your indicator cases are reviewed weeks after coding closes and nobody can say how many were coding rather than care, start with a historical analysis. A paid discovery phase gives you a review of how previous flagged cases actually resolved, an assessment of whether your coding timing supports concurrent review, a finding taxonomy your clinical and coding teams can adopt, a build or configure recommendation, and an itemised fixed-scope estimate. You keep the analysis regardless.
FAQs
Frequently Asked Questions
These are the questions quality directors, documentation leaders, and coding managers raise before scoping this work. Several concern a distinction we insist on: an indicator flags a coding pattern rather than establishing harm. One concerns a feature we refuse to build. Where an answer depends on your coding timing or documentation practice, the discovery analysis settles it quickly and is worth having regardless. We would rather lose work to a vendor willing to suggest codes that avoid indicators than help you build something a compliance review would treat as an optimisation scheme.
No. The indicator identifies a case meeting administrative criteria from coded data. Whether harm occurred requires clinical review of the record, and many flagged cases resolve as coding accuracy issues or conditions present on admission. Treating a flag as a finding misrepresents both your care and your data.
We will help you review cases accurately and concurrently, which often reveals that documentation understated conditions present on admission. That is legitimate accuracy work. We will not build features suggesting code changes to avoid indicators, because coding must reflect the record and anything else is a compliance exposure.
Through the finding taxonomy, agreed with your clinical and coding teams before build. Each reviewed case records what the clinical review concluded and what the coding review concluded, separately. Reporting then shows the distribution, so a rate change is attributable to accuracy or to care rather than left ambiguous.
Because retrospective review can correct nothing. Once coding closes, a documentation ambiguity is permanent and the case is a statistic. Reviewing while the record is open allows genuine clarification and lets clinical findings reach safety processes while people still remember the case in question. Learning fades with the memory of the case.
No. Comparative and benchmark datasets are licensed by your organisation from whichever provider you use, and we integrate what you hold. We calculate observed rates and apply the published risk adjustment, and we make no claim of partnership or endorsement with any benchmarking or data provider.
We decline to build punitive individual scorecards from indicator cases. Indicators reflect documentation practice and system factors as much as individual care, and attributing them punitively suppresses the documentation honesty the whole programme depends on. Case review for learning and peer review is legitimate and different.