CODE OF ETHICS

The International Society for Pharmacoeconomics and Outcomes Research (1SPOR) has published a code of ethics that is vital to the honesty and transparency of the discipline [8]. The code encourages pharmacoeconomists to maintain the highest ethical standards because the organization recognizes that activities of its members affect many constituencies. These include but are not limited to: (1) patients, caregivers, and patients’ associations, who are ultimately going to experience the greatest impact of the research; (2) healthcare professionals who will be treating or not treating patients with therapies, medications, and procedures made available or not made available because of the research; (3) healthcare organizations; (4) decision makers and payers, including governments, employers, and administrators, who must decide what is covered so as to optimize the health of the patient and resource utilization; (5) professional outcomes researchers;

  • (6) industries/manufacturers, whose products are often the subject of this research;
  • (7) academic institutions where research is conducted and students are trained;
  • (8) colleagues, whose relationships in conducting research and related activities are particularly critical; (9) research employees concerned about how they are regarded, compensated, and treated by the researchers for whom they work;

(10) students, whose respect and appropriate behavior are important; and (11) clients for whom the research is conducted, and researcher relationships are developed and maintained.

The ISPOR code of ethics lists many standards for researchers, but a (paraphrased) sample section of the code related to “research design considerations,” divided into primary and secondary concerns, is as follows:

1. Primary;

A. In terms of participant recruitment, researchers should provide potential subjects information about study intentions, funding, and Institutional Review Board (IRB)/Ethics Committee (EC) rulings;

B. In terms of population and research setting, researchers should describe and justify the chosen population;

C. Sample size and site selection should be adequate to meet the study objectives and be statistically justified;

D. Safety and adverse event reporting should be followed, as appropriate; and,

E. Any incentive/honorarium should be appropriate, vetted with the 1RB/EC, and not so large as to induce study participation.

2. Secondary:

A. When using secondary data sources, such as large administrative datasets, ensure that intellectual property rights are respected and referenced, with all permissions being secured;

B. Ensure reasonableness and transparency to minimize bias;

C. Appropriate statistical and other methods should be employed and disclosed to ensure data completeness and validity, as well as study result reproducibility 9;

D. In terms of transparency, consider study registration in clinical- trials.gov or other appropriate source; and,

E. In terms of modeling studies that often make use of secondary data, typically through incorporation into a decision-analytic model, ensure that inputs are derived via a comprehensive review of the literature, be transparent about assumptions, and employ sensitivity analyses to examine the impact of assumptions and data inputs on model outcomes.

OVERVIEW OF ECONOMIC EVALUATION METHODS

This section will give the reader a brief overview of the methodologies based on the two core pharmacoeconomic approaches, namely cost-effectiveness analysis (CEA) and cost-utility analysis (CUA). Table 1.1 provides a basic comparison of the following methods: cost-of-illness, cost-minimisation, and cost-benefit analysis (CBA). One can differentiate between the various approaches according to the units used to measure the inputs and outputs, as shown in the table. In general, the outputs in CEA are related to various natural units of measure, such as

Comparison of Pharmacoeconomic Methods and Calculations

Method

Abbr

Basic Formula

Discounting

Math

Input

Output

Results Expressed

Coal

Determine:

Advantage/

Disadvantage

Example

Cost of Illness

COI

DC+IC

In,= ,[Ct/(l+r)‘]

S

s

Total cost of illness

Total cost of illness

Docs not look at TXs separately

Cost of migraine in U.S.

Cosl-

Minimisation

Analysis

CMA

c, -c2

or

[Preferred Formula] (DCi+IC,) - (DC,+IC2)

rV.IQ/d+r)']

s

Assumed eq ual

Net cost savings

Lowest cost TX

Assume both TXs have same

effectiveness

Assume two antibiotics have the same effects for killing infection but differ on nursing and intravenous cost

Cost-

Eirectiveness

Analysis

CEA

(Ci-C2)/(E|-E2)

or

[Preferred Formula] (DCi+ICi)- (DC2+IC2)/(E, -E2)

Гр^СДНг)']/

In1=1[Et/(l+r)1]

s

Health

elfect

Incremental cost against change in unit of outcome

TX attaining е!Гес1 for lower cost

Compare TXs that have same type of effect units

Compare two HTN prescriptions for life years gained

(Continued)

Method

Abbr

Basic Formula

Discounting

Math

Input

Output

Results Expressed

Goal

Determine:

Advantage/

Disadvantage

Example

Cost-Benefit

Analysis

or

Net Benefit

CBA

(B, - B,)/ (DCi+ICi)- (DCn-IC,) or

[Preferred Formula] Net Benefit =

(В,-Вз) -(DC,+IC,) - (DC2+IC2)

X%,[B,/(l+r)‘]/

Xn,=i[C1/(l+r)‘]

or

Г,=.[(В,-С,У

(1+r)']

S

Dollars

Net benefit or ratio of incremental benefits to incremental costs

TX giving best net benefit or higher B/C ratio (or return on investment)

TXs can have different effects, but must be put into dollars

Compare two cholesterol prescriptions and convert life years to wages

Cost-

Utility

Analysis

CUA

(C,-C,)/(U ,-U2) or

[Preferred Formula] (DC.+IC,)- (DC2+IC2)/ (U,-U2)

X"i=i[Cl/(l+r)t]/

Int=i[Ul/(l+r)']

s

Health

effect,

including

Patient

Preference

Incremental cost against change in unit of outcome adjusted by patient preference

TX attaining effect (adjusted for patient preference) for lower cost

Preferences arc difficult to measure

Compare two cancer prescriptions and use QoL adjusted life years gained (QALYs)

Note: DC = Direct Cost; IC = Indirect Cost; R = Discount Rate; T = Time; HTN = Hypertension; QoL = Quality of Life; TX = Treatment or Intervention.

lives saved, life years added, disability days prevented, blood pressure (change in mmHg), lipid level, and so on. CBA uses monetary values (e.g., euros, dollars, pounds, yen) to measure both inputs and outputs of the respective interventions. Further discussion and examples of these techniques have been presented elsewhere [9]. It is hoped that the evaluation mechanisms delineated further in this book will be helpful in managing pharmaceutical interventions toward improving societal value and generate greater acceptance by health authorities, administrators, and the public. The first edition of this book used the human papillomavirus vaccine as an example for case studies. This has been supplemented with additional examples outside of that narrow focus. Other chapters in this book will further illustrate the various analytical methodologies related to CEA, CUA, CBA, etc. See Chapters 2, 4, 7, and 9 for more information on these techniques.

 
Source
< Prev   CONTENTS   Source   Next >