A review of methods to measure health-related productivity loss.

BACKGROUND: Annual US health-related productivity losses are estimated to reach some $260 billion, attributable not only to absenteeism but also to presenteeism (being present at work but working at a reduced capacity). The search for remedies has been hampered by the lack of accurate estimates of the loss of productivity and its true costs. To date, little effort has been made to assess the availability of measurement instruments or the validity and reliability of those that exist. OBJECTIVES: To systematically review the instruments used to measure productivity loss and its costs and to assess limitations in current research. DESIGN: A systematic search was conducted of the published and gray-market research literature from 1995 through 2005 on methods for estimating productivity loss and monetizing that loss. RESULTS: Twenty survey instruments were identified that assess the effect of health problems on absenteeism or presenteeism by attempting to quantify self-perceived or comparative impairment or by measuring unproductive work time. Some of the methods have been validated. The challenges of measuring presenteeism far exceed those of measuring absenteeism primarily because many jobs do not have easily measurable output. Methods to estimate the cost of lost productivity were also identified; however, none have been validated, to our knowledge. CONCLUSIONS: The greatest impediment to estimating the cost of productivity lost to illness is the lack of established and validated methods for monetization. The issues raised in this review are intended to stimulate future research to validate and improve such methods.

Effect of disease management on prescription drug treatment: what is the right quality measure?

Measures of medication adherence have become common parameters with which disease management (DM) programs are being evaluated, leading to the question of how this concept should be measured in the particular context of a DM intervention. We hypothesize that DM improves adherence to prescriptions more than the rate with which prescriptions are being filled. We used health plan claims data to construct 13 common measures of medication adherence for five chronic conditions. The measures were operationalized in three different ways: the Prescription Fill Rate (PFR), which requires only one prescription; the Medication Possession Ratio (MPR), which requires a supply that covers at least 80% of the year; and the Length of Gap (LOG), which requires no gap greater than 30 days between prescriptions. We compared results from a baseline year to results during the first year of a DM program. Changes in adherence were quite small in the first year of the intervention, with no changes greater than six percentage points. In the intervention year, three measures showed a significant increase based on all three operational definitions, but two measures paradoxically decreased based on the PFR. For both, the MPR and the LOG suggested either no change or significant improvement. None of the MPR and LOG measures pointed toward significantly lower compliance in the intervention year. Different ways to operationalize the concept of medication adherence can lead to fundamentally different conclusions. While more complex, MPR- and LOG-based measures could be more appropriate for DM evaluation. Our initial results, however, need to be confirmed by data covering longer term follow-up.