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If information on single items in the Short Form–12 health survey (SF-12) is missing, the analysis of only complete cases causes a loss of statistical power and, in case of nonrandom missing data (MD), systematic bias. This study aimed at evaluating the concordance of real patient data and data estimated by different MD imputation procedures in the items of the SF-12 assessment. For this ends, MD were examined in a sample of 1,137 orthopedic patients. Additionally, MD were simulated (a) in the subsample of orthopedic patients exhibiting no MD ( n = 810; 71%) as well as (b) in a sample of 6,970 respondents representing the German general population (95.8% participants with complete data) using logistic regression modelling. Simulated MD were replaced by mean values as well as regression-, expectation-maximization- (EM-), and multiple imputation estimates. Higher age and lower education were associated with enhanced probabilities of MD. In terms of accuracy in both data sets, the EM-procedure (ICC2,1 = .33-.72) outperformed alternative estimation approaches substantially (e.g., regression imputation: ICC2,1 = .18-.48). The EM-algorithm can be recommended to estimate MD in the items of the SF-12, because it reproduces the actual patient data most accurately.

Background The ratings of physician-patient communication are an important indicator of the quality of health care delivery and provide guidance for many important decisions in the health care setting and in health research. But there is no gold standard to assess physician-patient communication. Thus, depending on the specific measurement condition, multiple sources of variance may contribute to the total score variance of ratings of physician-patient communication. This may systematically impair the validity of conclusions drawn from rating data. Objective To examine the extent to which different measurement conditions and rater perspectives, respectively contribute to the variance of physician-patient communication ratings. Methods Variance components of ratings of physician-patient communication gained from 32 general practitioners and 252 patients from 25 family practices in Germany were analyzed using generalizability theory. The communication dimensions “shared decision making”, “effective and open communication” and “satisfaction” were considered. Results Physician-patient communication ratings most substantially reflect unique rater-perspective and communication dimension combinations (32.7% interaction effect). The ratings also represented unique physician and rater-perspective combinations (16.3% interaction effect). However, physicians’ communication behavior and the observed communication dimensions revealed only a low extent of score variance (1% physician effect; 3.7% communication dimension effect). Approximately half of the variance remained unexplained (46.2% three-way interaction, confounded with error). Conclusion The ratings of physician-patient communication minimally reflect physician communication skills in general. Instead, these ratings exhibit primarily differences among physicians and patients in their tendency to perceive shared decision making and effective and open communication and to be satisfied with communication, regardless of the communication behavior of physicians. Rater training and assessing low inferential ratings of physician-patient communication dimensions should be considered when subjective aspects of rater perspectives are not of interest.