Moving from passive to active provider payment systems: DRG-based financing

Transcription

1 International Conference Markets in European Health Systems: Opportunities, Challenges, and Limitations, Kranjska Gora/ Slovenia Moving from passive to active provider payment systems: DRG-based financing Reinhard Busse, Prof. Dr. med. MPH FFPH Dept. Health Care Management, Berlin University of Technology (WHO Collaborating Centre for Health Systems Research and Management) & European Observatory on Health Systems and Policies

2 Ministry of Health/ NHS Before Resource allocation based on geographical and (more often) institutional basis Hospitals Advantage: providers know budget in advance Disadvantage: not based on actual workloads, outcomes or new technologies

3 Purchaser (region, sickness fund...) now & future Purchasing based on contracts based incorporating needs, costeffectiveness, quality... Providers Advantage: services get financed according to population need and health gain Disadvantages: requires information which is often not available or comparable

4 Weaknesses of traditional ways of paying hospitals Fee-for-service * Ill patients usually attractive * Over-provision of services * Under-referral referral * No incentives for high quality DRG payments Can they be used to overcome the weaknesses of FFS and budgets? Budget * (ill) Patients not attractive * Under-provision of services/ waiting lists * Over-referral referral * Quality: bad results -> more work

5 Diagnosis-related groups (DRGs): What are they? Primarily a patient classification system Grouping of cost-homogeneous admissions Related to diagnosis (ICD-9/10) but also procedures and severity (Australian DRGs, newer European versions) Useful as a management and evaluation tool Initially developed by Robert Fetter at Yale as an information management tool and a device for adjusting hospital performance for patients characteristics ( includin g clinical ones)

6 Diagnosis-related groups (DRGs): What are they? Eventually used as a payment mechanism Later adopted by Medicare to move reimbursement from retrospective (fee for service) to prospective (DRG tariff per-case) Eventually migrated to other payers in the US and to most healthcare systems in affluent countries (both SHI- and NHS-based systems) often with different starting points (per diems, budgets)

7 18 out 19 OECD countries have introduced DRG-like classification systems Gilardi et al

8 DRG system DRG system: The family tree of DRG systems (selection) Yale DRG HCFA DRG Classification adopted without or with minor modifications Classification adopted with major modifications GHM 1 (France) 1988 AP DRG 1991 APR DRG 1992 AN DRG 1993 Hungary 1995 Italy Nord 1996 DRG GHM Spain (France) EfP 1999 AR DRG (France) 2002 Denmark HRG (England) Germany PPS (France)

9 Development paths from one DRG system to the other Foreign DRG system e.g. the Netherlands 2005 e.g. Hungary 1993 DRG logic (grouping criteria, basic algorithm) adopted D modified E developed Patient classification system adopted C modified e.g. France 1997 e.g. Spain 1997 e.g. Italy 1995 Calculation of A B DRG-cost weights adopted modified e.g. Germany 2004 e.g. Spain 1999 Steps in the development of DRG-systems

10 DRG classification systems in Europe Codin g system Classification system Austria ICD-9 DRG Belgium ICD-9-CM LDF Danemark ICD-10 Nomesko APR-DRG England ICD-10, OPCS HBG, HRG, PbR Finland ICD-10 Nomesko Nord-DRG France ICD-10 GHS Germany ICD-10 G-DRG Island ICD-10 Nomesko Nord-DRG Italy ICD-9-CM DRG Netherlands ICD-9-CM DBC Norway ICD-10 Nomesko Nord-DRG Portugal ICD-9-CM DRG Spain ICD-9-CM DRG Sweden ICD-10 Nomesko Nord-DRG Nonis and Rosati (2008).

11 DRGs for reimbursement DRG payment Loss Profit Costs Hospital Green area: Hospitals to produce more services (previously provided in hospitals D+E) Red area: Reduce costs or stop providing that service (DRG, department, entire hospital) In the long run: Reduction of expenditure (if DRG payments follow costs); but what about access to services around red hospitals?

12 Expected effects of DRGs DRGs vs. fee-for-service (USA): hospital activity and length-of-stay (and costs!) will go down DRGs vs. budgets: hospital activity will go up (no cost savings!); activities iti not included d in DRGs (e.g. teaching; emergency care at night) might be abolished Danger of up-coding (documenting higher severity) and gaming (changing the treatment towards better paid DRGs)

13 Dealing with DRG effects Calculation of DRG fee level should include anticipated effects, especially through regular recalculation of DRG weights (and possibly the classification) Expected effects should be explicitly counterbalanced (e.g. through supplements for teaching, emergency care) Regulation/ incentives/ controls are needed to ensure that t hospitals treat t appropriately and of high h quality and not only respond to the economic incentives of DRGs!

14 Calculating DRGs in Germany Annual cost sheet from accountancy department Seperation of costs into DRG relevant/ not relevant extra-ordinary expenditure DRG relevant costs not DRG-relevant (e.g. investment) Overhead costs unit costs (e.g. implants) Cost centers (e.g. departments/ wards) Direct cost centers Indirect cost centers (kitchen)

15 How many DRGs are appropriate to capture differences in patient severity? (e.g. Germany) 2003: 664 DRGs Administratively easy 2004: 824 DRGs 2005: 878 DRGs 2006: 954 DRGs 2007: 1082 DRGs but: may lead to creamskimming (rejection of severely ill patients) t Rejection of severely ill 2008: 1137 DRGs patients less likely but gaming more likely

16 Problem: Relative time lag of bringing innovations into DRG systems (here: Germany) Application for Specific procedure (OPS) code Acceptance of OPS code Adaption/ split of DRGs Cases concerned can be separately calculated Specific data collection of procedure utilization (using the OPS code) at national level year 0 year 1 year 2 year 3 Potential ti reimbursement time lag

17 NUB (New Diagnostic and Treatment Methods) the political l instrument to bridge the time lag in Germany Adaption/ split of DRGs Cases concerned can be separately calculated Specific data collection of procedure utilization (using the OPS code) at national level year 0 year 1 year 2 year 3 application of NUB by hospital bridge the gap via NUB payments (negotiated hospital specific) Other approaches: new DRGs (e.g. for drugeluting stents in Italy) extra reimbursement of new technologies if indicated (France)

18 DRGs in a European perspective: Results from HealthBASKET project Case vignettes for episodes of care Need for care Age group Type of Care ECHI* Appendectomy In-patient Surgery Emergency - Normal delivery In-patient Obstetrics Elective + Hip-replacement In-patient Surgery Elective + Cataract Out-patient (day case) Surgery Elective + Stroke In-patient Medical Emergency + AMI (PTCA) In-patient Medical Emergency + Cough 2 Out-patient Paediatrics/GP Emergency - Colonoscopy Out-patient Diagnostic Elective + Tooth filling Out-patient Dental Emergency + Physiotherapy (knee) 12 Out-patient Rehabilitative - - *ECHI: related to European Community Health Indicators set (+ yes/ - no)

19 Costs and reimbursement of European hospitals: hip replacement (Euros) 8000 Reim mbursement Denmark England France Germany Hungary Italy Netherlands Poland Spain HealthBASKET project final report Total cost (Euros)

20 8000 Costs and reimbursement of European hospitals: stroke Reimbursem ment (Euros) Denmark England France Germany Hungary Italy Netherlands Poland Spain Total cost (Euros) HealthBASKET project final report

21 8000 Costs and reimbursement of European hospitals: stroke 7000 Open question 1: If costs differ so much within countries, why do countries develo p their own DRG systems (rather than a European one)? What data would be necessary for this? Italy Netherlands Poland Spain Total cost (Euros) HealthBASKET project final report

22 Acute myocardial infarction: Hospitals performin g PCI ( PTCA/ Stenting) in 9000,00 none mixed all 9374, , , , , , , , , , , ,00 0,00 Hungary (N=2) 395,97 483,05 308,88 Poland (N=5) Factor , ,76 592,15 Spain (N=5) 2541, , ,55 Denmark (N=3) 2733, , ,40 Germany (N=13) 4161, , ,53 England (N=3) 5013, ,16 France (N=3) 6225, , ,53 Netherlands (N=6) 5599, ,88 Italy (N=5) 4384,72

23 9 8000, ,00 Open question 2: If costs differ so g ( g) much with treatment, what about the quality of care? -> EuroDRG 8282, ,89 74, , , , , , , ,00 0,00 Hungary (N=2) 395,97 483,05 308,88 Poland (N=5) Factor , ,76 592,15 Spain (N=5) 2541, , ,55 Denmark (N=3) 2733, , ,40 Germany (N=13) 4161, , ,53 England (N=3) 5013, ,16 France (N=3) 6225, , ,53 Netherlands (N=6) 5599, ,88 Italy (N=5) 4384,72

24 Acute Myocardial Infarction

25 Technology/ procedure ** (non- cemented vs. cemented) Stroke * (% with thrombo- lysis) Acute myocardial infarction ** (% of PTCA with stenting) Hip replacement Normal Appen- Cataract Tooth delivery dectomy filling ** (laparo- scopic vs. open surgery) * (soft vs. hard lens) Personnel input *** (time) *-** (% with imaging) Length-of-stay * ** ** * ** (treatment time) Hospital charcteristics Beds/ hospital * ** Nurses/ bed (*) Urbanity * Setting *** Cost of personnel/ hour Purchasing power parities (PPP) ** (nurses *** only) *** # *** *** # * significant at.05 level, ** significant at.01 level, *** significant at.001 level, (*) only in one model, # PPP not used as explanatory variable but to adjust costs as dependent variable

26 Care episode/ Country Conversion approach Germany England France Hungary Italy Netherlands Poland Spain Hip Exchange rate 6,365 5,691 6,101 1,294 6,982 5,605 2,125 3,599 GDP per head 6,365 5,372 5,985 4,251 7,771 5,016 9,866 4,929 GDP PPP 6,365 5,551 5,979 2,260 7,152 5,609 4,065 4,174 Medical care PPP 6,365 5,146 6,245 2,782 5,709 5,633 5,121 4,269 ESPPP 6,365 5,646 7,880 4,979 6,924 7,687 5,334 5,770 AMI Exchange rate 2,866 5,014 5, ,450 5,599 1,026 1,861 GDP per head 2,866 4,732 5,803 1,301 8,292 5,011 4,762 2,549 GDP PPP 2,866 4,891 5, ,632 5,603 1,962 2,158 Medical care PPP 2,866 4,533 6, ,092 5,627 2,472 2,208 ESPPP 2,866 2,403 2,728 2,060 4,804 2,481 2,154 2,006 Appendectomy Exchange rate 1,922 2,037 2, ,632 1, GDP per head 1,922 1,923 1,988 1,541 1,816 1,698 2, GDP PPP 1,922 1,987 1, ,672 1, case by Medical care PPP 1,922 1,842 2,074 1,008 1,334 1,907 1, ESPPP country Delivery 1,922 2,203 2,872 1,362 2,246 1,979 2,429 1,454 Exchange rate 2,365 1,638 2, , GDP per head 2,365 1,546 2,067 1,124 1, , GDP PPP 2,365 1,598 2, , episode Medical care PPP 2,365 1,481 2, , ESPPP 2,365 3,868 4,751 5,239 4,226 2,552 2,538 2,257 Stroke Exchange rate 3,456 6,123 4, ,588 6,872 1,238 1,932 GDP per head 3,456 5,779 4,255 2,065 5,106 6,150 5,746 2,645 GDP PPP 3,456 5,972 4,250 1,098 4,700 6,877 2,367 2,240 Medical care PPP 3,456 5,536 4,440 1,352 3,751 6,907 2,983 2,291 ESPPP 3,456 5,378 3,859 3,220 5,072 4,473 3,337 2,486 Average adjusted costs per and care

27 Care episode/ Country G E l F H I l N l P l S Open question 3: Does this adjustment hold with better data? Euro-DRG: (1) routine cost and activity it data for broader patient categories and GDP PPP (2) hospital benchmarking club. If yes, has more emphasis to be put on exogeneous factors (such as wages) r when using DRGs for reimbursement? Could this lead to a European system with differing cost weights (as in US)? GDP per head 3,456 5,779 4,255 2,065 5,106 6,150 5,746 2,645 GDP PPP 3,456 5,972 4,250 1,098 4,700 6,877 2,367 2,240 Medical care PPP 3,456 5,536 4,440 1,352 3,751 6,907 2,983 2,291 ESPPP 3,456 5,378 3,859 3,220 5,072 4,473 3,337 2,486

28 taking up the open questions, based on the observation that costs differ due to three groups of factors: ( 1) Patient characteristics, i.e. main diag nosis, ag e, sex, secondary diagnoses (upon admission) (2) Medical/ treatment variables, i.e. procedures/ technologies used, type of ward (e.g. intensive care), intensity of inputs (e.g. personnel), length of stay, secondary diagnoses (-> complications) between (2) and (3): activity levels ( 3) Exogenous factors - at hospital level: size (beds, personnel), emergency room, teaching status - at regional/national n level: l wage level, costs of other inputs (OFTEN NEGATED OR FORGOTTEN TODAY)

29 Thank Th k you for your attention Analysing Health Systems and Policies