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      Willing to wait?: The influence of patient wait time on satisfaction with primary care

      research-article
      1 , , 1 , 2
      BMC Health Services Research
      BioMed Central

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          Abstract

          Background

          This study examined the relationship between patient waiting time and willingness to return for care and patient satisfaction ratings with primary care physicians.

          Methods

          Cross-sectional survey data on a convenience sample of 5,030 patients who rated their physicians on a web-based survey developed to collect detailed information on patient experiences with health care. The survey included self-reported information on wait times, time spent with doctor, and patient satisfaction.

          Results

          Longer waiting times were associated with lower patient satisfaction (p < 0.05), however, time spent with the physician was the strongest predictor of patient satisfaction. The decrement in satisfaction associated with long waiting times is substantially reduced with increased time spent with the physician (5 minutes or more). Importantly, the combination of long waiting time to see the doctor and having a short doctor visit is associated with very low overall patient satisfaction.

          Conclusion

          The time spent with the physician is a stronger predictor of patient satisfaction than is the time spent in the waiting room. These results suggest that shortening patient waiting times at the expense of time spent with the patient to improve patient satisfaction scores would be counter-productive.

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          Most cited references13

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          The relationship between patient's perceived waiting time and office-based practice satisfaction.

          The amount of waiting time a patient experiences in a primary care or specialty care outpatient setting may have an effect on patient satisfaction and may depend on other visit characteristics. We sought to investigate and quantify the association between waiting time and satisfaction outcomes in clinics belonging to the Wake Forest University Baptist Medical Center and assess how this relationship varies by time spent with the provider. Cross-sectional survey data was collected at point of care from 18 primary and specialty care clinics at the Center Overall satisfaction with provider care, the office ratings, and willingness to return were each rated on a 0-to-10-point scale. Multivariate and logistic regressions were performed to examine the relationship between waiting time and outcomes. Covariates included visit time spent with physician, patient care processes, visit convenience, and demographics. 2,444 cases were analyzed Waiting time significantly predicted provider ratings. When time spent with the physician was five minutes or less, provider ratings decreased by 0.3 rating points for each 10-minute increase in waiting time. When time spent with the physician was greater than five minutes, provider ratings decreased by 0.1 rating points for each 10-minute increase in waiting time. The association between waiting time and office satisfaction showed a similar pattern; increased waits also decreased willingness to return (odds decrease by 2% per minute). Results may be affected by unreliability of the measures used and from possible selection bias. There is also concern over missing confounders. Our findings confirm that reduced waiting time may lead to increased patient satisfaction and greater willingness to return in primary and specialty care outpatient settings. Furthermore, increased waiting time combined with reduced time spent with the physician coincide with noticeable drops in patient satisfaction.
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            Performance of generalized estimating equations in practical situations.

            Moment methods for analyzing repeated binary responses have been proposed by Liang and Zeger (1986, Biometrika 73, 13-22), and extended by Prentice (1988, Biometrics 44, 1033-1048). In their generalized estimating equations (GEE), both Liang and Zeger (1986) and Prentice (1988) estimate the parameters associated with the expected value of an individual's vector of binary responses as well as the correlations between pairs of binary responses. In this paper, we discuss one-step estimators, i.e., estimators obtained from one step of the generalized estimating equations, and compare their performance to that of the fully iterated estimators in small samples. In simulations, we find the performance of the one-step estimator to be qualitatively similar to that of the fully iterated estimator. When the sample size is small and the association between binary responses is high, we recommend using the one-step estimator to circumvent convergence problems associated with the fully iterated GEE algorithm. Furthermore, we find the GEE methods to be more efficient than ordinary logistic regression with variance correction for estimating the effect of a time-varying covariate.
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              Waiting time is a major predictor of patient satisfaction in a primary military clinic.

              Patient satisfaction has emerged as an increasingly important parameter in the assessment of health care quality. Determination of the most important contributors of overall satisfaction can assist health care providers in improving care. However, simple patient satisfaction surveys are difficult to compartmentalize and fail to fully explain patient satisfaction or disapproval. We generated a model with an isolated, single intervention and evaluated patient satisfaction before and after the intervention. Documenting a significant change in postintervention general satisfaction, after changing only one aspect of patient care, can give us valuable data about the importance of this intervention. We hypothesized that in our population of young obligatory service recruits, "time factor" (time spent at scheduling an appointment and waiting in the clinic) is a major contributor of overall satisfaction. Hence, we modified this factor by intervening in clinic scheduling and waiting times. Clinic availability on the phone was improved. Clinic waiting times have been shortened significantly. This single intervention generated a significant rise in overall patient satisfaction. Our model proved that clinic availability and waiting times are significantly correlated to overall satisfaction. Statistical analysis of the satisfaction survey showed similar results, further stressing the importance of the "time factor" in soldiers' satisfaction. Measuring patient satisfaction before and after a lone intervention in one aspect of satisfaction is an effective tool. This allows us to analyze satisfaction and evaluate its major contributors.
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                Author and article information

                Journal
                BMC Health Serv Res
                BMC Health Services Research
                BioMed Central (London )
                1472-6963
                2007
                28 February 2007
                : 7
                : 31
                Affiliations
                [1 ]Department of Public Health Sciences, Wake Forest University Health Sciences, Medical Center Boulevard, Winston-Salem, NC, 27157 USA
                [2 ]College of Pharmacy and School of Public Health, The Ohio State University, Columbus, OH, 43210 USA
                Article
                1472-6963-7-31
                10.1186/1472-6963-7-31
                1810532
                17328807
                1e448cff-f1cf-4b56-846a-f97dd8030641
                Copyright © 2007 Anderson et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 6 September 2006
                : 28 February 2007
                Categories
                Research Article

                Health & Social care
                Health & Social care

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