ABF in Tasmania Where are we?

1. ABF in TasmaniaWhere are we? Wednesday 7 March 2012 Sydney

2. Current ABF activities • Risk Identification • Issues in classification • Tasmania is the outlier in undercoding • Costing developments • All product costing • Making the costing results accessible • Web based package with cost results • Funding Model development • Shadow Model • Interim Funding arrangements

3. The funding risk problem Basically broken down into 3 main areas Outliers systematic outliers can cause disadvantage especially to more complex services and cases Need to identify risk associated with burden of disease and any management process LOS is not the only issue – cost/day is quite variable Per diem adjustments may introduce errors where daily cost is not consistent Evidence from costing data suggests that there can be significant peaks in daily cost outside trim points for complex cases Adjustments will need to be made in the State part of the funding equation Care typing Issues Tasmania poor at care typing Coding Issues Undercoding is a problem for Tasmania

4. Types of Outliers Low outliers Risk to funder – if paying full price for a partial episode Boundary issues Non admitted classes Change in treatment E.g. SD cholecystectomy High Outliers Risk to provider – insufficient funding for episode cost Tertiary procedural cases Presence of multiple concurrent morbidity Delayed care typing Failure to care type High inliers Cases do not have to be outliers to present a funding risk Systematic errors of classification are still likely to be inliers – just higher cost ones Possibility of undercoding Documentation Application of standards

5. The basic Funding model EQUALISING EACH DRG Increasing the inlier base to make up for losses on long stay Outliers - $ Increase to compensate Long Stay Outlier Loss Modelled Cost Actual Cost Revised Modelled Cost LOS L3 Mean H3

6. Tertiary Procedural Work Previous work undertaken in Tasmania suggests that even within a single DRG, cases that have the presence of a tertiary procedure, will generally have higher costs than cases in the same DRG that do not have such a procedure undertaken. Tertiary procs based on the NHS highly specialised procedures list The effect is variable across the range of DRGs but for 2008-09 there were 1,269 Cases of acute patients where a “Tertiary” procedure was undertaken in Tasmanian public hospitals. These cases had a combined length of stay of 1497 days longer than the national average length of stay for the major hospital. Tasmania has slightly less than the national average length of stay in the acute data for this year. The cost was consistently higher for these cases c/w non tertiary cases At a conservative estimate of $1400/ day this works out to be $2.1M.

7. The presence of Multiple Morbidity A study of Tasmanian 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 acute expenditure They are not reflected in increased AR-DRG classification severity as the classification no longer responds to increasing morbidity past a certain 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 They are almost invariably different cases than the tertiary procedural cases.

8. LOS vs no. of Distinct conditions

9. Impact of increasing morbidity on cost

10. Cost disadvantage of increasing morbidity

11. Where is the large part of the problem?

12. What about misadventure?

13. Characteristics of Multimorbid cases In 2008-09 Tasmanian patients with complex multimorbidity amounted to 11,725 days greater than the National Average for acute cases in the R13 Australian NHCDC data. Assuming $1400/day, this works out at $16M more than the national average cost per episode or $18,421 per case there the patient has such a burden of disease c/w the average for the DRG. However the share of Critical Care resources is substantial There were only 73 patients where they had both a tertiary procedure and 6 or more distinct diseases in the same acute episode. They had some 1,593 excess days (21.8 per patient) accounting for $30,568 per case

14. 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 • Larger hospitals have more of these cases • The public sector has many more of these cases • Although just how many needs to be determined • Funding models need to be developed to accommodate this group. • But without causing wrong incentives • These are generally not cases of poor care.

15. Care type and boundary Coding • Care type indicates clinical intent • Acute – to Cure or treat • Rehabilitation • Palliative care • Maintenance • Psycho-Geriatric • Boarders • Organ donations • Unqualified Neonates • When the Episode Starts and ends is critical • ED notes are always relevant to coded inpatient episode • Patient not discharged until they physically leave the ward if episode ended in death • OPD referral and GP referral notes are relevant to coding • Anything that happens within the episode is within scope • Anything that is relevant to the episode (go to the OPD notes if that has an appropriate lead in into the episode) • E.g. pain from IF ironwork leading to removal – this detail may be clarified in the OPD notes as much as the episode notes. Clarifies purpose of removal.

16. Accurate units of activity ‘REHABILITATION SERVICES’ % INPUTS BY CARE TYPE ‘ACUTE SERVICES’ DAY OF EPISODE OF CARE OR SPELL

17. Delayed or no Care Typing Substantial differences in care typing practice across jurisdictions Tasmania is poor at typing Not consistent across jurisdiction B70A (Stroke) Hospital 1 = 9 days Hospital 2 – 30 days (Acute stroke unit) Concept of rehab sensitive DRGs >10 days LOS as acute episode in selected DRGs Profile of potential risk can be estimated Assuming a standard cost/bed day Issue of poor performance against some KPIs HSMR will be impacted if there low palliative care typing

18. Failure to care type

19. Dealing with Undercoding • Tasmania has a significant issue with undercoding • Overcoding does not appear to be a real issue in Public Hospitals in Australia • Not simply a coding problem • Documentation • Interpretation of coding standards • Close liaison between costing group and coding auditor/educator • A number of initiatives being developed • Coding plan • Education, including clinicians • Admission policy • Audit plan including =focussed/targeted audits

20. 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

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

22. Rectification of Undercoding Coding Audit Good standard tools are available PICQ - Etc Scattergun approach Sample data Select random sample of data from all records Stratified Audit Pick a problem MDC and audit random cases 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

23. Coder / Clinician • Coding information is critical to ABF • Tasmania is the outlier for undercoding • 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

24. Key documentation for coding • Most important is the Principal Diagnosis • For admitted cases it is The reason for Admission After Study • Additional Diagnoses- comorbidities • Conditions that require Increased clinical care, monitoring (with evidence or description of how) • Complications • Conditions that require increased clinical care monitoring • Make clear additional care provided – not just noted • External causes • Injuries and/or poisoning as well as activities and place • Procedural intervention • Past history • If referring to past history please make clear if the past history items make impact on current episode

25. 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

26. Prevalence of Diabetes Coding

27. Reasons for the anomalies Limited explanation for the increased and material LOS. Therefore one of several problems potentially exists; The documentation has been deficient The records has not been fully coded (possible with the Scanned Medical Record) There is a social reason for the increased LOS There has been a clinical problem Re-coding of such targeted cases is likely to result in substantial increase in AR-DRG cost weight. Examinations of the cause will also be useful

28. Identification of an “at risk” cohort Diabetes is an example of high risk group. Similar effect with COAD, Hypertension, CCF, etc Diabetes is recognised as a major healthcare issue in Australia advice from clinical specialists is that it is always important in the care of a patient – no matter for what purpose. These patients often cost more to provide care Increased nursing, investigation, etc. We have some undercoding of diabetes in Australia How material is the problem? A simple dataset has been created any patient with any coded mention of diabetes in any episode has been identified. All episodes related to these patients during 2008-09 were identified and compared against all episodes in the major hospitals. 305,000 individual patients over 10 years 5% incidence of diabetes ever coded in the patient group Consistent with incidence in total Tasmanian population from Diabetes From this the level of diabetes undercoding can be seen. – this represents a risk to funding the additional morbidity.

29. 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 • O60Z is 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

30. Costing Efforts in Tasmania

31. Costing Efforts in Tasmania • Validation of costing process • Several audits of process • Expert review • KPMG review • Huge increase in effort required • Consumption costing • All-Product methodology • What do we mean? • Who undertakes and where based • Improving processes • Data aggregation processes • Data warehousing • Dealing with new PAS • Seems odd that no one is really happy with modern PAS systems

32. Risks to costing reliability • Risks arise from four major areas • Costing • Poor Methods or over-reliance on external RVUs (technologically backward, no longer best practice) • Failure to cost all products • Reliance on Patient Fractioning techniques • Inconsistent approaches (centralised vs distributed costing effort) • E.g. NHCDC different by state causing major differences • Continuity of staff • Insufficient resolution • Poor QA (and QA at inappropriate level) • Classification • Boundaries (Mental health as an acute DRG for Funding…..?) • Increasing (and somewhat inappropriate) heterogeneity • Communication • Failure to involve clinicians • Failure to pitch correct level of costing to correct audience (DON’T tell doctors about DRGs or HRGs) • Counting • uncaptured data (entire service not collected (easy to spot!) • Incomplete data capture (inconsistent data capture (a trap!)

33. Calculation error Costing (compression) problem

34. Under payment Cost and Fund Problem

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

36. The Management of Costing • Software • The package is not so important – there are several perfectly acceptable products • How driven is critical • Technical environment • Workstation vs Server based costing • Several larger systems take a server based approach to costing • Very good at establishing a standardised approach over many hospitals • However rules are the critical part of the environment • Expensive to establish • Inflexible • Potential to degrade costing knowledge • Workstation based approach is possible as modern workstations are far more powerful than servers from a relatively few years ago • Now possible to undertake full consumption costing at the micro level in hospitals over 3,000 beds from workstation class machines • Allows • QA is vital

37. Where it goes wrong? • Accounting issues • The name of the cost centre is not always what it seems • For 6 years We reported an Oncology cost centre as mental health – up to the level of Treasury. • Completeness of the GL • Missing and additional costs • Accrual rules • There is some variation between jurisdictions on accrual processes. • Data matching • Missing costs – double costing • WIP • Becomes more critical as the level of detail increases • External demands on staff • Need to be vigilant to stop “Other urgent work” swamping costing staff

38. Auditing process • The PC template (NHCDC) • Reconciliation to the GL • Clinical interaction • Dept to Site interaction (for centralised models. Danger of desktop only costing) • Transaction sensibility checks (all Medical led OP clinics have Med salary costs at sensible levels?)

39. Next Steps • ABF scope and data set coverage • Identify ABF in-scope services • Develop and implement ABF data set specifications and data collection processes • Classification system development • Enhancements to proxy classifications • Counting rules and unit of count • Develop and implement counting and unit of count rules for non admitted services • Costing • Complete NHCDC Round 15 data collection (2010-11) • Refine the Finance One general ledger structure& implement costing practices and procedures to allocate actual costs to the areas of activity within the Finance One general ledger • Undertake costing studies to develop cost weights for proxy classifications

40. Next Steps • Funding Models • Development of Tasmanian Purchasing Service Agreements for 2012-13 • Operate Shadow ABF Funding Model – update for national funding model and national efficient prices • Finalise the costing and funding treatment of Teaching Training & Research, Rural Hospitals • Model proposed funding scenarios under a national ABF using nationally efficient prices when determined. • Support Infrastructure • Enhance capability of hospital computer systems to support clinical costing and ABF • Develop and implement an education and training program to support ABF implementation • Data Quality Assurance • Finalise the development of the NHCDC Quality Framework • Develop and implement national and state/territory level data quality assurance program

41. Funding Models

42. Issues • Scope of activity • Classification systems in Use • Data collection and provision • Quarterly • Cost collection • Template • Volume of records • Full product costing • PFRAC and Non pfrac systems

43. Steps in the Model • Extract and cleanse the NHCDC Round 14 cost data. • Merge the NHCDC cost and APC activity data sets and complete data preparation.(eg Allocation of unequal neonate costs to mothers and checking DRG groupings) • Remove ED and depreciation costs from Patient Costed and Cost Modelled data. • Restrict APC and NHCDC data to ABF hospitals. • Classify APC and NHCDC data into non-paediatric and paediatric hospitals (including splitting SA Women and Children’s Hospital depending on age and MDC of separation). • Derive L3H3 inlier bounds for paediatric and non-paediatric separations from APC data. • Stratify ABF hospitals and derive stratified population weighting of Patient Costed sample hospital data up to ABF population (excluding Cost Modelled hospitals). • Classify Patient Costed NHCDC data into categories depending on the paediatric hospital status, same-day DRG list and L3H3 inlier bounds: same-day separation; short-stay outlier separation; inlier separation; and long-stay outlier separation. • Derive same-day model parameters. • Derive short-stay outlier model parameters. • Derive inlier model parameters. • Derive long-stay outlier model parameters. • For each DRG (and paediatric hospital status), adjust inlier model parameters so that inlier and long-stay outlier predicted costs align with actual costs. • For each DRG, adjust model parameters so that all model predicted costs align with actual costs across both (population-weighted) Patient Costed and Cost Modelled data. • Derive Indigenous loading. • Derive Level 3 ICU hourly rate model parameters based on supplied ICU data. • Deflate out Level 3 ICU costs from model parameters based on modelled ICU costs by paediatric hospital status, DRG and separation category (same-day, short-stay outlier, inlier and long-stay outlier).