The Kaiser Family Foundation and the Health Research and Educational Trust (KFF/HRET) conduct this survey of employer-sponsored health benefits. For many years the international consulting and accounting firm, Bearing Point (formerly known as KPMG), supported the study. In 1998, KPMG divested itself of its Compensation and Benefits Practice, and part of that divestiture included donating the annual survey of health benefits to HRET. HRET is a nonprofit research organization affiliated with the American Hospital Association. The Kaiser Family Foundation provides financial support and conducts this survey in partnership with HRET. The Foundation provides independent research and analysis on health policy issues, and is not affiliated in any way with the Kaiser Permanente health plan.

Kaiser/HRET asked each participating company as many as 400 questions about its largest conventional or indemnity, health maintenance organization (HMO), preferred provider organization (PPO) and point-of service (POS) health plans. This year’s survey included questions on the cost of health insurance, offer rates, coverage, eligibility, health plan choice, enrollment patterns, premiums, employee cost sharing, covered benefits, prescription drug benefits, retiree health benefits and general policy perceptions and activities. Throughout this report, we use the term ‘in-network’ to refer to services received from a preferred provider and ‘out-of-network’ to refer to services received from a nonpreferred provider. This year Kaiser/HRET survey added two additional sections to the questionnaire to collect information about high-deductible health plans (HDHP) that are offered along with a health reimbursement account (HRA) or are health savings account (HSA) qualified.¹ Questions in these sections were asked of all firms offering these plan types, regardless of enrollment.

Kaiser/HRET retained National Research LLC (NR), a Washington, D.C.-based survey research firm, to conduct telephone interviews with human resource and benefits managers. NR conducted interviews from January to May 2005.

Response Rate

Kaiser/HRET drew its sample from a Dun & Bradstreet list of the nation’s private and public employers with three or more workers. To increase precision, Kaiser/HRET stratified the sample by industry and the number of workers in the firm. Kaiser/ HRET attempted to repeat interviews with prior years’ survey respondents (with at least ten employees) who also participated in 2003 and/or 2004. As a result, 1,122 firms in this year’s total sample of 2,013 firms participated in either the 2003 and 2004 surveys.² The overall response rate was 48%. Exhibit M.1 shows the respondent status by region and state.

The vast majority of questions are asked only of firms that offer health benefits. A total of 1,832 responding firms indicated that they offered health benefits. The overall response rate of firms that offer health benefits was 51%.

From previous years’ experience, we have learned that firms that decline to participate in the study are more likely not to offer health benefits. Therefore, we asked one question to all firms in the study with which we made phone contact where the firm declined to participate. The question was, “Does your company offer or contribute to a health insurance program as a benefit to your employees?” A total of 2,995 firms responded to this question (including 2,013 who responded to the full survey and 982 who responded to this one question). Their responses are included in our estimates of the percentage of firms offering health benefits.³ The response rate for this question was 72%.

Firm Size Definitions, Rounding, and Imputation

Throughout the report, exhibits categorize data by industry, size of firm, and region. Firm size definitions are as follows: 3-199, All Small; and 200 or more workers, All Large. Occasionally, firm size categories will be broken into finer groups. The All Small group may be categorized by: 3-24 workers and 25-199 workers; or 3-9 workers, 10-24 workers, 25- 49 workers, and 50-199 workers. The All Large group may be categorized by: 200-999 workers, midsize; 1,000-4,999 workers, large; and 5,000 or more workers, jumbo. Exhibit M.2 shows detailed characteristics of the sample.

Exhibit M.3 displays the distribution of the nation’s firms, workers, and covered workers (of employees receiving coverage from their employer). Among the over three million firms nationally, approximately 60% are firms employing 3-9 workers. In contrast, jumbo firms, defined as firms with 5,000 or more workers, employ and cover about 35% of employees. Therefore, the smallest firms dominate any national statistics about what employers in general are doing. In contrast, jumbo employers are the most important employer group in calculating statistics regarding covered workers, since they employ the largest percentage of the nation’s workforce.

Some exhibits in Health Benefits 2005 do not sum up to totals due to rounding effects. Also due to rounding, numbers in the text may be slightly different from those in the exhibits. Throughout the report, while overall totals as well as totals for size and industry are statistically valid, some breakdowns may not be available due to limited sample sizes. In instances where the sample size is less than 30, exhibits include the notation NSD (Not Sufficient Data).

To control for item nonresponse bias, Kaiser/HRET has identified a set of variables as needing complete information from all surveyed firms. These variables include percentage changes in premium costs for family coverage, premium amounts, worker contribution amounts, self-insurance status, level of benefits, prescription drug cost sharing, copay and coinsurance amounts for prescription drugs, and firm workforce characteristics such as average income and part-time status. On average, less than five percent of these observations are imputed for any given variable. The imputed values are determined based on the distribution of the reported values within stratum defined by firm size and region.

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Weighting and Statistical Significance

Because Kaiser/HRET selects firms randomly, it is possible through the use of statistical weights to extrapolate the results to national (as well as regional, industry, and firm size) averages. These weights allow Kaiser/HRET to present findings based on the number of workers covered by health plans, the number of total workers, and the number of firms. Specific weights were created to analyze the HDHP plans that are offered along with HRAs or are HSA qualified. These weights represent the proportion of employees enrolled in each of these arrangements.

Calculation of the weights follows a common approach. First, the basic weight is determined, followed by a nonresponse adjustment. As part of this nonresponse adjustment, Kaiser/HRET again conducted a small follow-up survey of those firms with 3-49 workers that refused to participate in the full survey. We applied an additional nonresponse adjustment to the weight to reflect the findings of this survey.

Next we trimmed the weights in order to reduce the influence of weight outliers. First, the weights were ranked from largest to smallest based on their proportion of the total weight sum. Next, we identified trimming cut points such that the observations to be trimmed contribute no more than five percent towards the total weight sum. We also minimized the number of nontrimmed observations that exceed the cut point after the trimming adjustment. This method reduced the variability in the weights and maintained, with few exceptions, the ordinal integrity of the observation weights.

Finally, we applied a post-stratification adjustment. We used the Statistics of the U.S. Census Bureau as the basis for the stratification and the post-stratification adjustment for firms in the private sector, and we used the Census of U.S. Governments as the basis for post stratification for public sector firms. This year we updated our data to reflect the 2002 Census of Governments. We also removed federal government employee counts from our post-stratification. Although these updates had only a small impact on the number of government firms, they reduced the number of government workers in the weights by approximately 7 million. This may have a small effect on our coverage and enrollment estimates.

The data are analyzed with SUDAAN, which computes appropriate standard error estimates by controlling for the complex design of the survey. All statistical tests are performed at the .05 level unless otherwise noted. For figures with multiple years, statistical tests are conducted for each year against the previous year shown. No statistical tests are conducted for years prior to 1999, meaning that the year prior to 1999 shown on the exhibits is the last year for which standard errors are available. Two types of significance tests performed are the t-Test and the Chi-square test.

Historical Data

Data in this report focus primarily on findings from surveys jointly authored by the Kaiser Family Foundation and the Health Research and Educational Trust, which have been conducted since 1999. Prior to 1999, the survey was conducted by the Health Insurance Association of America (HIAA) and KPMG using the same survey instrument, but data is not available for all the intervening years. Following the survey’s introduction in 1988, HIAA conducted the survey through 1990, but some data are not available to us. KPMG also conducted the survey from 1991-1998. However, in 1991, 1992, 1994, and 1997, only larger firms were sampled. In 1993, 1995, 1996, and 1998, KPMG interviewed both large and small firms.

This report uses data from the 1993, 1996, and 1998 KPMG Surveys of Employer-Sponsored Health Benefits and the 1999-2004 Kaiser/HRET Survey of Employer-Sponsored Health Benefits. For a longer-term perspective, we also use the 1988 survey of the nation’s employers conducted by the HIAA, on which the KPMG and Kaiser/ HRET surveys are based. Many questions in the HIAA, the KPMG, and Kaiser/HRET surveys are identical. The survey designs among the three surveys are also similar.

For more information regarding survey methodology, click here to view the Survey Design and Methods section.