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Department of Health and Human Services

ABF From a Funding Perspective. Kevin Ratcliffe Principal Consultant Clinical Costing Dept Health and Human Services Tasmania. Department of Health and Human Services. ABF funding approach. ABF funding relies on several attributes Good Counting

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Department of Health and Human Services

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  1. ABF From a Funding Perspective Kevin Ratcliffe Principal Consultant Clinical Costing Dept Health and Human Services Tasmania Department of Health and Human Services

  2. ABF funding approach ABF funding relies on several attributes Good Counting Boundaries (admited:nonAdmitted) are a confounder Good Costing The cost calculation does not introduce systematic errors of averaging Good Classification The Classes are able to provide cost homogeneity within sufficient classes to ensure similar cost for similar DRGs in different locations The classification and coding rules are clear and sensible Good Funding model development The Funding system should ensure that systematic outliers are neither advantaged or disadvantaged

  3. Background • There is a view that swings and roundabouts will even out in terms of ABF approaches • This is correct unless there are systematic confounding issues • Current finding model development locally and nationally is concerned with dealing with systematic outliers • H3:L3 • Short stay policy • Trimming off Admitted ED • Short stay trim points • Long stay policy • Extra per diem payments for stay longer than some point • Adjustments for “Tertiary” or complex services • Recognition of high complexity with major metro hospitals that provide state-wide referral services • Usually an adjustment to ICU payment rates or infrastructure loadings

  4. The Current IHPA Model • Decreased payment for Private cases • No payment for out of scope and ineligible cases • Payment by classification • AR-DRGv6.0X – URG - OPD clinics Tier2 NHCDC • Standardized WEIS type calculation • All product streams into a common weight (NWAU) • H3:L3 • Same day and One day Weights • Indigeneity and remoteness allowances for all classes • Adjustment for Private cases (removal of hralth fund contribution) • Sub and Non Acute – Block funded initially • Critical Care adjustment • MH Block and then New classification

  5. Counting Problem • When is a patient admitted? • Depends on who funds? • Qualification of Neonates • By care delivered or by facility (e.g. does entry to Special care nursery work? • Not all countries require qualification • HRGs cover IP, ED, OP, ICU within the same classification • The only advantage they offer – many other weaknesses • AR-DRGs are one of several classification schemas in Australia • AR-DRG Inpatients • URG – Emergency departments • Tier II OPD clinics – outpatients incl Outreach and sub-acute) • AN-SNAP – sub-acute (in Designated unit??) • Mental health – a distinct group when in designated units?? • How do we make sure patients are not moved to a better funding classification • Prescribe – use policy to determine admitable cases – e.g. Ireland, Germany • Set prices that create no advantage to admission practice - Australia?

  6. Calculation error Problems with Costing

  7. Improving the Costing • Validation of costing process • Obvious place to start is the result - is it different? • Several audits of process • External expert review – R14 KPMG • Increase in NHCDC data validation • Huge increase in effort required • Consumption costing • All-Product methodology – episode level for all products • Improving national processes • Data aggregation processes • Data warehousing • Dealing with new data systems

  8. Key to solution - Good Costing • Not driven by Service weights • Variations on coding will impact on reliability of cost allocation • Based on consumption • Full cost allocation (All-product costing) • Product costs defined by output not product fractioning • End-to-end costing approach • Control of entire process • Errors at beginning of process fixed at beginning and entire process re-run • To patch at end will lead to inconsistencies

  9. Good Classification • The AR-DRG is as good a classification as is available anywhere • Adequate number of classes • 667 in AR-DRGv4.2 when Germany Adopted • Now 705 in AR-DRGv6.0X • Germany now has over 1,200 in G-DRG • Highly developed coding standards • Robust review is essential • Considers complexity explicitly • PCCL process • AR-DRG Adopted in numerous countries – based on objective analysis and comparison with other competing classifications • Ireland, Germany, Slovenia, Romania, Qatar, Singapore etc. • Ongoing work is required • CCL list is becoming old and requires updating • AR-DRGv7.0 2013 – does not include work on CCLs

  10. Establishment of another DRG class /split Or Complimentary Funding Arrangements? Classification and Funding Problem

  11. Classification error in practice • High cost cases not identified in Classification • Average cost within class underpays hospital where the cases occur • Yet overpays low cost hospital • A06Z was a very large problem in Australia • Fixed partially in AR-DRGv6.0X (Still requires work) • O60Z was a problem area in AR-DRGv6.0 • Results in overpayment for regional centre • Underpayment in largest Hospital - $0.5M in state funding model work • Rectified by reverting to AR-DRGv5.2 coding logic • AR-DRGv6.0X

  12. The presence of Multiple Morbidity A study of episode data over several years indicates that about 1% of episodes have substantial coexisting morbidity encompassing several body systems (6 +). These patients absorb about 10% of the hospitals total acute expenditure They are not reflected in increased AR-DRG classification severity as the classification no longer responds to increasing morbidity past a point. They absorb a significant proportion of the Critical care ventilated hours (40%) and have a 33% mortality rate within 12 months. LOS differences alone do not account for the additional cost LOS increases with more coexisting distinct diagnoses The issue is not related to procedures but the complexity of medical conditions. It is the patient who as the attribute of multi morbidity – not the facility With complex procedures the facility is more important

  13. LOS vs no. of Distinct conditions

  14. Cost disadvantage of increasing morbidity

  15. Implications for Funding • If a standard tariff is established using DRG payments, then these cases will be underfunded • H3:L3 funding is part of the solution but not all • They are small in number but are material in use of resources such as ICU beds • The ICU part of the National model will assist here ($168/hour in Some but not all DRGs in Some ICUs i.e. LIII) • Larger hospitals have more of these cases • Funding models need to be developed to accommodate this group. • But without causing wrong incentives • These are generally not cases of poor care.

  16. What about misadventure?

  17. The capture of Coding

  18. Dealing with Undercoding • Is there a variation in coding across the country • Overcoding does not currently appear to be a real issue in Public Hospitals in Australia • Not simply a coding problem • Documentation • Quality, structure, availability • Interpretation of coding standards • Coding workforce will be an issue • Increase in quality in ABF will increase time taken to code records • Quantity – Quality – Cost dilemma

  19. Why this is important For Stroke this would equal $670,000 loss of revenue at $4,500/wtd separation to Tasmania c/w the national average coding rate

  20. A Surgical example For Craniotomy, this would equal $750,000 loss of revenue at $4500/wtd separation to Tasmania c/w the national average coding rate

  21. Coder / Clinician liaison is the Key Coding information is critical to ABF The problem is ensuring that the documentation supports the assignment of Diagnosis codes Secondary and additional diagnoses are critical to DRG hierarchy of severity All clinician notes are relevant for coding Not just the doctors summary Nursing and Allied health are clinicians and relevant to coded record E.g. incontinence, pressure sore grading bedside sheets/notes are part of the patient record for coding purposes Clinical pathway sheets, Observation sheets, Drug sheets, Fluid balance charts etc Behaviours when unclear Simply operating as “don’t code if not clear” will diminish coding If unclear ask the clinician ACS require the clinician to be consulted

  22. Documentation for Clinicians The key points on documentation Clinical terms Rather than narrative E.g. fracture distal radius – include the angulation/displacement/rotation/shortening attributes Atelectasis vs. decreased air entry Causal relationship 24 hour urine testing for Proteinuria Particular condition due to a drug Specificity The actual causative organism E.g E.Coli UTI rather than UTI Confusion or Delirium – (it is important to differentiate as delirium will move the DRG) Site, character, what was observed E.g. The actual grade of the pressure sore Coma scales – state coma if the GCS is low as the Coders cannot interpret the GCS Authoritative Relevant to discipline Nursing refers to nursing attributes Medical refers to diagnoses Documenting Clinician Should know the patient But often never saw them Complete Concise Accurate

  23. Rectification of Undercoding Coding Audit Good standard tools are available for ongoing audit PICQ - Etc Stratified Audit Estimates coding c/w best practice Focussed Audit Examination of data with following attributes; Inliers - LOS >1.5 times AR-DRG average but less than 3 times average (high inliers) Outliers LOS >3 times National ALOS LOS >6 days (material LOS therefore worth looking at) <3 Diagnosis codes (the level of coding is not likely to explain the additional LOS) or PCCL = 0 NO tertiary procedure undertaken Good forms A good discharge summary will guide the documentation for reliable coding

  24. Funding model impacts • Making a model safe • Problem is multi-factorial • Boundary issues must be managed • Remove incentives to alter admission practice • All products must be considered • Not necessarily by single price for all product streams • Simple DRG model will create problems • Data are R) skewed • More LS outliers than SS • LS outliers are unbounded – SS is bounded • Requires at least a High trim outlier • SD vs 1 day episodes • Specific issues – e.g. Critical care use in multimorbidity • ICU or HMV adjustment • State model will be dealing with risk • States wear the risk • Uncapped nature of the National model • Price/volume schedule • Targets at SRG level will be set prior to 2015

  25. How we will manage risk • Establishment of a Risk unit within the Purchasing and Commissioning area • Distinct to Clinical Costing group • Classification issues • Coding Auditor / Educator • Admissions/discharge policy • Coding Policy • Activity projections • Local Funding models • Reporting

  26. Thank You • Kevin Ratcliffe • kevin.ratcliffe@dhhs.tas.gov.au • 03 6233 3306

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