• Promoting a Healthier Workforce

    Health and Productivity Management

  • Health and Productivity Management Center


    In January 2002, the ACOEM Expert Panel also discussed and identified the core characteristics that a productivity measurement instrument should possess to adequately assess the workplace productivity loss of migraineurs and of workers suffering from other diseases. The key characteristics were grouped into four categories: 1) supporting scientific evidence, 2) applicability to a variety of occupations and disease states, 3) ability to support business decision-making (i.e., ability for data to be translated into a monetary unit) and 4) practicality
    (Table 1).

    The first key characteristic - the scientific evidence supporting each instrument - includes the evidence for reliability and validity of the measures, along with the scales or factors that are targeted by these measures (1). Reliability is primarily a question of the consistency of a measurement tool. For the purposes of this review, we have focused on questions of validity of the instrument:

    1. independent of all other factors, i.e. the performance of individual items, and factors or scales in the instrument, irrespective of any characteristics of the sample, and
    2. in context of health impairment, work, and other relevant experiences of participants, how the instrument works in context:
      1. Does the instrument distinguish between conceptually different issues? and
      2. Does it agree with different kinds of measures of the same concept?

    The second key characteristic, applicability, was defined as the ability of the instrument to be used across a broad spectrum of industries, occupations, and disease states. It also refers to an instrument’s ability to measure work loss and productivity attributed to a specific disease or health condition that the instrument might have been designed to assess. The development of a standardized instrument that can capture productivity measures across disease states, industries and occupations will have more appeal to the business community. Effectiveness in a broad marketplace and for various demographics -- blue and white-collar occupations -- is a desired quality in any instrument. Further the Expert Panel noted that the usefulness of any instrument to an employer will be determined in part by its ability to assess various disease states/conditions and one that can be used across a number of occupations within the company. Thus the emphasis is not only on an instrument’s ability to assess the impact of migraines on productivity, but also the instrument’s ability to be broadly applied in the workplace.

    In order to support business decision-making, the third characteristic, the value of lost productivity, needs to be estimated and appraised. Therefore, the data generated from each instrument were examined for their ability to be translated into a monetary unit. Employers who want to build a case for analyzing productivity and instituting interventions must be able to make a business case for their analysis and demonstrate a return on investment. However, there are numerous other business metrics, for example in the trucking industry the number of labor hours per truck, that are also important for effective business decision-making.

    The last criterion, practicality, relates to the tool’s ease of administration (i.e., self-administered vs. interview-administered), availability in multiple languages, and administration costs.

    1. Shadish WR, Cook TD, Campbell DT. (2002). Experimental and quasi-experimental design for generalized causal inference. Boston, Houghton, Mifflin.

    Table 1: Key Characteristics of Health-Related Productivity Instruments


    • Reliable
    • Valid
    • Across industries and occupations
    • Across disease states and conditions
    • Specific to migraines
    Supports effective business decision-making
    • Metrics can be translated into dollars
    • Easy administration
    • Low costs of administration
    • Reading level
    • Available in multiple languages