Continuity of Care and the Physician-Patient Relationship

Bivariate Analyses

In bivariate analyses, ratings of the physician-patient relationship were compared across continuity of care categories. Individuals who “always” saw the same doctor or provider were compared with a category of “less than always,” which had been collapsed across “most of the time,” “sometimes,” and “rarely or never.” On average, respondents rated provider communication and patient influence between “good” and “very good.” Both persons who did and did not have asthma who saw the same doctor or provider for all their health care visits rated provider communication and patient influence significantly higher than did individuals who had less continuity (P <.01). This is shown in Table 3.

Regression Analyses

We computed separate linear regression models for individuals who did and did not have asthma to assess the contribution of continuity of care in the presence of control variables in predicting ratings of provider communication and patient influence for these groups. All 4 response levels were included in the continuity of care variable. The correlation matrix for the independent variables produced no correlations between independent variables that exceeded 0.5, suggesting that these variables could be included in the same analysis. The P values and standardized regression coefficients for the independent variables in the asthmatic and nonasthmatic models are presented for the provider communication models in Table 4 and for the patient influence models in Table 5. All models were significant at P <.05.

For persons with asthma, continuity of care was the only variable (P=.01) that significantly contributed to the provider communication model (Table 4, Model 1) and the only variable (P=.02) other than life satisfaction (P=.04) that contributed to the patient influence model (Table 5, Model 1). In the provider communication and patient influence models, the standardized estimates for the continuity parameter were 0.15 and 0.14, respectively, higher than any other estimates in the models. The nonstandardized parameter estimates for continuity were 0.26 and 0.25, respectively.

For persons who did not have asthma, continuity of care significantly contributed (P=.001) to both the provider communication (Table 4, Model 2) and patient influence models (Table 5, Model 2). Unlike the models for persons with asthma, 5 additional variables significantly contributed to these models (P≤.01): age, number of visits, general health, health improvement, and life satisfaction. The standardized parameter estimates for continuity were similar to those in the asthmatic models (0.14 for each). Continuity ranked only third among the estimates in the provider communication model and second among the estimates in the patient influence model. The nonstandardized parameter estimates for continuity were 0.24 and 0.23, respectively.

The linear regression models combining all respondents were significant in predicting provider communication (P=.001) and patient influence (P=.001). Continuity of care, age, number of visits, general health, health improvement, and life satisfaction significantly contributed to the models (P≤.01 for each). Asthma status and the interaction terms between that status and the other independent variables were not significant, with the exception of the interaction term between that status and number of visits, which predicted provider communication (P=.03). With the asthma interaction terms largely nonsignificant, subsequent discussion will address only the separate asthmatic and nonasthmatic models.

Discussion

Our results confirm earlier findings that continuity of care is important in health care delivery. For both respondents with and without asthma, continuity of care with an individual provider significantly predicted their ratings of provider communication and patient influence alone and in the presence of control variables. Also, the results suggest that continuity of care may be particularly important in certain populations. Differences in the regression models for the respondents with and without asthma suggest a particularly important role of continuity of care in the physician-patient relationship for patients with this disease. Among those persons, continuity of care was the only variable predicting patient perceptions of physician-patient communication after controlling for many other relevant variables; it was 1 of only 2 variables predicting perceptions of patient influence. Among persons who did not have asthma, continuity shared its importance with several other variables.

Our results do not suggest that continuity is important only to patients with asthma. For both patients with and without asthma, continuity of care was an important predictor of provider communication and patient influence. However, it is the unique prominence of continuity of care in the asthma models that is interesting, in the context of several likely predictive variables that were nonsignificant.

If a sample did not have sufficient size and power to detect significant effects, such differences could have been an artifact of differences in sample size. However, the results of a power analysis show that in the group of patients with asthma (the smaller sample) there was 80% power to detect with 95% confidence a correlation as small as 0.06, which is a miniscule effect. Thus the sample with asthma offered sufficient power to detect the effects of all the independent variables, but only the effect of continuity of care emerged as significant for that group.