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Paul schreyer

Paul schreyer






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    Paul schreyer Paul schreyer Presentation Transcript

    • Jornadas de economia de la salud June 2010 Valencia Measuring health services (in the national accounts) Paul Schreyer, OECD
    • Background • Much effort spent on measuring the value of GDP at current prices • Even more important: volumes. • Difficult when – Products are complex with changing quality – There are no economically significant prices
    • Background • Health services are a prime example: – Rapid technological change – Provision often by non-market suppliers • So how are health services measured in the NA? • And should this be done differently?
    • Background • Recent work: – Eurostat (2001) & EU Regulation – Atkinson report (2005) and work by UKCMGA – United States: Triplett and Bosworth 2004, Abraham and Mackie 2006 – OECD: • Handbook 2010 • Data development: health PPPs – Stiglitz-Sen-Fitoussi Commission (September 2009)
    • This presentation • A few concepts • Capturing health services and quality change • Conclusions
    • Terminology • Inputs • Outputs – Processes without explicit quality adjustment – Processes with explicit quality adjustment • Outcomes – Direct outcomes – Indirect outcomes • Best explained by way of a graph
    • Inputs Outputs Outcomes Process without Process with Direct Indirect explicit quality explicit quality outcome outcome adjustment adjustment Example Example education: education: quality- Knowledge number of adjusted number and skills as pupils/pupil hours of pupils/pupil measured by Future real by level of hours by level of scores earnings, education education growth rate Labour, capital, of GDP, intermediate well- inputs Example health: rounded Example health: quality-adjusted citizens number of number of Health status etc. complete of population complete treatments by treatments by type type of disease of disease Inhereted skills, socio-economic Environmental factors background, etc. Hygene, lifestyle, infrastructure etc.
    • Terminology →National accounts should strive at measuring outputs →in the form of quality-adjusted processes →or as the marginal contribution to outcomes →Outcomes (as used here) is indicative of results of the health system as a whole →Although outcome ≠ output, they are not independent
    • Non-market production • Nothing special in terms of the basic service provided, but mode of provision is different • In particular: prices not economically significant • Traditional way of dealing with this: – Value of output = value of inputs (sum of costs) – Volume of output = volume of inputs – Problem: defines away productivity change
    • From inputs to outputs • Efforts to capture volume change of outputs, not of inputs • What exactly is output of health industry? • Target definition: • Health service = complete treatment of a disease or medical service to prevent a disease • But what exactly is a ‘complete treatment’? • And how to deal with quality change?
    • • The long (& still incomplete) answer is here: OECD (2010); Towards Measuring the Volume Output of Education and Health Services: A Handbook • The short answer in the slides to follow.
    • Completed treatment • Pathway that an individual takes through heterogeneous institutions in the health industry in order to receive full and final treatment for a disease or condition. • Not easily applicable, conceptually and empirically: – E.g., chronic diseases, data limitations • After reality check: treatment of one episode of disease by a particular institution • Main point: towards disease-based estimates
    • Measuring treatments • Required to construct disease-based output measures: – number of treatments by type of disease or – costs per treatment by type of disease • Administrative sources (e.g. DRGs) have significantly facilitated access to such information (Germany, Denmark, Australia, France,…) • Volume indices can then be constructed: • Weighted average of # of treatments • Weights: cost share of type of disease
    • Denmark: Input price index and output price index for general hospital services based on ~ 800 DRGs 120.0 115.0 110.0 105.0 Input based Output based 100.0 95.0 90.0 2000 2001 2002 2003 2004 2005
    • Quality change • Via stratification (implicit quality adjustment) • Explicit quality adjustment • Capturing quality by measuring marginal contribution to outcomes
    • Capturing quality change via stratification (1) • Basic idea: matching products: services are stratified such that only similar services are compared • Criterion for classification: similarity in effects on patients, and not similarity in how services are produced • Example: different treatments for the same disease (in a particular type of establishment) should be in one stratum, and not similar medical procedures for different diseases • Implies: most detailed stratification = not necessarily best choice with cost weights and imperfect markets
    • Capturing quality change via stratification (2) • 2 treatments, traditional and laser surgery Same effect on outcome Laser is cheaper Laser surgery diffuses progressively Traditional surgery Laser surgery Period 0 Period 1 Period 2 Period 0 Period 1 Period 2 Unit cost 100 100 100 - 90 90 Number of interventions 50 40 5 0 10 45 Total cost 5000 4000 500 0 900 4050 Laspeyres volume index period 1 to period 2: [sT(5/40)+sL(45/10)]-1=-7.1% where sT=82% and sL=18% are the period 1 cost shares
    • Capturing quality change via stratification (3) • Measured output declines! →Counter-intuitive • Problem: 2 medical procedures have been treated as 2 different services • Note also implicit assumption: – consumer valuation of the two ‘products’ is captured by the relative unit costs, – so if laser surgery is cheaper than traditional surgery, this method implicitly quality-adjusts downward the quantity of laser surgery when it is combined with traditional surgery.
    • Capturing quality change via stratification (4) • In a perfect market, the price of the traditional treatment would instantaneously adjust downward and/or traditional treatment would disappear • In practice and in a non-market context, this does not happen →2 treatments should be treated as the same product →no cost weighting, volume change = zero
    • Capturing quality change via stratification (5) • A more sophisticated method would be to keep both treatments in the same stratum but explicitly adjust one of the treatments • For example put a coefficient of 0.8 on the traditional treatment • Such adjustments would have to rely on medical effectiveness studies • There is some way to go before practical implementation • For more on this, see Triplett (2001): What’s different about health? Human repair and car repair in national accounts and in national health accounts
    • Capturing quality change via stratification (6) • Note: even if we do not explicitly quality-adjust products, the decision how to group them cannot be made without some reference to effects on outcome • Otherwise, no statement can be made about substitutability of services and how they should be classified • Nearly everything that has been said about quality adjustment via stratification applies also to market production • Only difference: price statisticians or national accountants who have to deal with it
    • Capturing quality change via explicit adjustment • If stratification is too granular, explicit quality adjustment may be needed • Basic problems: – Quality is multidimensional: how to aggregate across dimensions? (waiting times, risk of suboptimal treatment...) – How to aggregate change in quality variable(s) with change in quantity (process) variables?
    • Capturing quality change via measuring marginal contribution to outcome • Example: QUALYs, DALYs • Problems: – Making sure factors other than health care are controlled for; – Timing – lag between service and outcome – Putting monetary value on human lives • Very useful avenue of research but unlikely to be implemented in official statistics soon
    • Conclusions (1) • Output and outcome are different and should not be confused • National accounts and productivity studies of establishments need measures of output, not of outcome • But output and outcome are not independent • In the presence of quality change, all existing methods require some implicit or explicit information or reasoning about outcome. • Output or medical services should be based on treatment of disease unit of production
    • Conclusions (2) • Problems of quality adjustment arise whether services are provided by market or non-market producers. • A pragmatic approach will be called for to proceed with services measurement – no reason to approach every type of service with the same method for quality adjustment – methodologies should be robust and transparent
    • Conclusions (3) • Measuring output for complex services is difficult • But conclusion should not be that it is simply too difficult to do anything. • Visible progress in the area of health due to availability of administrative data • It may take a while before consensual and internationally comparable methods are agreed upon but active research and data development is vital to achieve this objective.
    • Thank you for your attention!