0 200 400 600 800 1000 1200
1985 1990 1995 2000 2005 2010 2012
N. 85+
-- 85 -- 75 -- 65 -- 55 -- 45 -- 35 -- 25
< 15
TL 05.13 Figure 1 Persons who received RRT in Norway at end of 2012 (1).
21 Background
Figure 2 Renal replacement therapy in Norway, status by end of year-patients pr mill.
inhabitants (1).
The number of dialysis patients in Norway has increased from 241 in 1990 to 1240 in 2012 (1). With the expected demographic development, with increased number of elderly people, people with high blood pressure, cardiovascular diseases and/or di-abetes, one can anticipate an increase in the number of people with chronic renal failure in need of RRT in the future (1;5).
Generally, there are two different types of dialysis: hemodialysis (HD) and peritone-al diperitone-alysis (PD). In hemodiperitone-alysis the circulating blood is filtered through a semiper-meable membrane in a machine which removes waste products and water from the blood. In peritoneal dialysis the patient's own peritoneal membrane inside the ab-dominal cavity is used as the dialysis membrane (5). Hemodialysis can be performed in hospitals, different medical institutions or at home, whereas peritoneal dialysis (PD) is a home based dialysis. Hemodialysis is usually performed 3-5 hours 3 times a week (5), whereas PD at home is continuously performed with change of fluid 4 times per 24 hours (CAPD) or by use of a machine that exchanges the fluid during the night (APD) (5).
In Norway hemodialysis performed in hospitals (satellites included) is the most fre-quently used modality (84.2%), whereas PD at home makes up for 15.8%. Only 11 patients (0.8%) received HD at home by the end of 2012 (1). The choice of dialysis modality depends on patients comorbidity, suitability for renal transplantation and for those on the waiting list, expected time to transplantation.
All counties, except one, have a central renal unit and some have two, further some counties have satellite units run in close contact with the central unit. There is only one transplant centre in Norway at Oslo University Hospital, Rikshospitalet. Pre-transplant work-up, as well as post-Pre-transplant follow-up beyond 10 weeks, is han-dled by the county-centres.
To compare efficacy and cost-effectiveness of the different dialysis modalities for patients with end-stage renal failure requiring dialysis in Norway, The Norwegian
22 Background
Directorate of Health requested The Norwegian Knowledge Centre for the Health Services (NOKC) for a health technology assessment (HTA). This request has its background in "Handlingsplan for forebygging og behandling av kronisk nyresyk-dom/The action plan for prevention and treatment of chronic kidney disease (2011-2015)" (5).
This plan aims that patients with chronic kidney disease should be offered good and individual renal replacement therapy, independent of residence, socioeconomic sit-uation and ethnicity, and furthermore that the traveling distance between home and dialysis centre should not be more than one hour.
With the increasing number of dialysis patients expected, there is a need to compare both cost-effectiveness- and safety data for the different dialysis modalities used in Norway today.
Introduction to health technology assessment (HTA)
The basis of an HTA is a systematic review and evaluation of scientific literature on efficacy and safety of different therapeutic interventions or diagnostics. The HTA may also include economic evaluations and a discussion regarding ethical, social, legal and organizational aspects depending on the question under evaluation.
This HTA consists of data from a systematic review summarizing efficacy and safety data and an economic model-based evaluation relevant for the Norwegian set-ting.
Introduction to Economic Evaluations of Health Care Programmes
The basic task of any economic evaluation is to identify, measure and compare costs and consequences of the alternatives under consideration in an incremental analy-sis—one in which the differences in costs are compared with differences in conse-quences (6). Hence, results of economic evaluations can be expressed as an incre-mental cost-effectiveness ratio (ICER), which is defined by the following equation:
Because the health care sector, like society in general, is restricted by scarce re-sources and budget constraints, economic evaluations are important tools for deci-sion makers facing questions of how to prioritize treatments and maximize health benefits using scarce resources. For an economic evaluation to be meaningful in a decision making process, the ICER must be judged with regard to a ceiling ratio that
E C Effect
Effect
Cost ICER Cost
comparator on
interventi
comparator on
interventi
23 Background
reflects the decision maker’s maximum willingness to pay (WTP) for a health gain.
The decision rule for an economic evaluation can therefore be expressed as
where λ equals WTP, and means that if the ICER of an intervention is below the ceil-ing ratio, introducceil-ing the intervention represents good value for money. Because the ICER has poor statistical properties, ICERs are often rearranged to express either incremental net monetary benefit (INMB) or incremental net health benefit (INHB), which yields the following decision rules related to INMB or INHB.
INMB: λ•∆E - ∆C > 0 INHB: ∆E – (∆C/λ) > 0
An intervention can in other words be considered cost-effective if it yields a positive INHB or INMB.
Economic evaluations are often based on decision models (such as decision trees, Markov models, etc.) that calculate results based on various input parameters in the model. Because there are always uncertainties related to the values of these parame-ters, sensitivity analysis is an important feature of any economic evaluation based on a decision model framework. In short, sensitivity analysis illustrates how much the results vary when model parameters are changed. Sensitivity analyses can be per-formed in many ways, with one-way or two-way sensitivity analysis being common approaches. These entail changing, respectively, one or two model-parameters at a time while all of the other model-parameters are held constant in order to determine how much impact the variation in these parameters has on the results. One-way sen-sitivity analyses are often presented as tornado-diagrams, which identify and illus-trate the model-parameters that have the highest impact on the results.
Another important kind of sensitivity analysis is referred to as probabilistic sensitivi-ty analysis (PSA). The advantage of PSA is that it makes it possible to take the uncer-tainties of all of the model-parameters into account simultaneously. The basic ap-proach in PSA is to assign appropriate probability distributions to the model-parameters, which makes it possible to replace the “fixed” values of the parameters with values generated by random draws from the distributions. Doing this repeated-ly, with a specified number of iterations, makes it possible to estimate the probabili-ties that alternative interventions are cost-effective subject to different ceiling values of WTP. The calculation is based on the alternative that renders the highest values of NMB or NHB. Results from PSAs are often presented as scatter plots, which show point estimates of the ICER for all iterations in the cost-effectiveness plane, and also
E C
24 Background
as cost-effectiveness acceptability curves (CEACs), which show the probability of the alternatives being cost-effective subject to changing values of WTP.
Another result from PSA is the expected value of perfect information (EVPI). This is a number that indicates the value to society of having more accurate information about the decision, given a WTP. If EVPI for a given population seems large, it might be of interest to determine for which parameters it would be most useful to obtain additional data. Expected value of perfect information for parameters is a more time-consuming analysis that can help determine for which single parameters or groups of parameters it is most cost-effective to conduct new research.
In short, making a model probabilistic means that it is possible to estimate the un-certainty associated with a decision to implement alternative interventions, and also provides a possibility of estimating the value of collecting additional information from new research.
Priority setting criteria
According to Norwegian policy documents (7;8), a treatment should be prioritized if the following criteria are met:
The disease is severe: A disease is considered severe to the degree that it causes pain and discomfort, loss of physical, psychological and social function and if it limits the individual in his or her daily activities. Severity is also evaluated according to the risk increase the disease entails in terms of death, disability and discomfort, if treatment is postponed.
The treatment is effective: The patient should be expected to benefit from treatment in terms of longevity or improved quality of life of certain duration.
The treatment effectiveness should also be well documented.
The treatment is cost-effective: The additional costs of the treatment should be reasonable compared to the additional benefits.
The policy documents mentioned above give no guidance as to what constitutes a
“reasonable” relationship between costs and effectiveness for a given health inter-vention. The Directorate of Health, however, has recommended a preliminary esti-mate of NOK 500 000 per statistical life year in full health (9;10). This value was based on Norwegian price levels in 2005, and translates to 588 000 for 2012 (9).
However, there is no consensus regarding this threshold value, nor has it been sub-ject to a political process and can therefore be regarded as nothing more than a ten-tative suggestion.
25 Clinical evaluation - Methods