International Journal of Health Care Quality Assurance Patient assessment of primary care physician communication: segmentation approach Elena A. Platonova Richard M. Shewchuk

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Patient assessment of primary care physician communication: segmentation approach

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Elena A. Platonova Department of Public Health Sciences, University of North Carolina at Charlotte, Charlotte, North Carolina, USA, and

Received 25 November 2013 Revised 25 August 2014 Accepted 12 January 2015

Richard M. Shewchuk Downloaded by Carleton University At 16:41 30 January 2016 (PT)

Department of Health Services Administration, University of Alabama at Birmingham, Birmingham, Alabama, USA Abstract Purpose – The purpose of this paper is to examine how patient assessment of primary care physician (PCP) communication is related to patient satisfaction with the PCP, patient perception of PCP professional competence, patient assessment of the relationship with the doctor and patient demographic characteristics using a segmentation approach. Design/methodology/approach – The authors surveyed 514 adult patients waiting for appointments with their PCPs in two US primary care clinics. A latent class analysis was used to identify mutually exclusive unobserved homogeneous classes of patients. Findings – The authors identified three distinct classes/groups with regard to patient assessment of physician communication and the physician-patient relationship. The largest group (53 percent of the sample) assessed their PCP communication and other doctor-patient relationship aspects as excellent. However, 37 percent provided mostly negative assessments, expressed high general dissatisfaction with the physician and disagreed with the statement that their PCP was well qualified to manage their health problems. These patients were on average more educated and affluent and the group included more males. About 10 percent of patients expressed generally lower satisfaction with the PCP, though their dissatisfaction was not as extreme as in the highly dissatisfied group. Research limitations/implications – Further studies are needed to help physicians develop skills to communicate with different patients. Originality/value – Patient segmentation can be an important tool for healthcare quality improvement particularly for emerging approaches to primary care such as patient-centered care. Keywords Patient centredness, Doctor-patient interpersonal relationship, Primary care physician communication, Segmentation approach Paper type Research paper

International Journal of Health Care Quality Assurance Vol. 28 No. 4, 2015 pp. 332-342 © Emerald Group Publishing Limited 0952-6862 DOI 10.1108/IJHCQA-11-2013-0136

Introduction Effective physician-patient communication is the foundation of compassionate and competent healthcare and a major contributor to high-quality medical services and patient satisfaction (Kaplan et al., 1989; Levinson et al., 2010; Levinson and Pizzo, 2011; Swenson et al., 2004). Effective physician communication helps patients understand their health issues, actively solicit information from providers and other sources and make more informed treatment decisions. Effective communication is particularly important in the management of chronic conditions since chronicity brings considerable patient responsibility in self-management of the disease (Mercieca et al., 2014); the primary care physician (PCP) should communicate to the patient the importance of correct treatment adherence (Bodenheimer et al., 2002; Kaplan et al., 1989).

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Recently, the meaning of physician-patient communication has been expanded to include more than just a discussion of current health issues; it implies the development and maintenance of a personal relationship between the provider and the patient (Lezzoni et al., 2012). Emerging healthcare models, such as patient-centered care and the patient-centered medical home emphasize each patient’s uniqueness and personalization (Stange et al., 2010; Starfield, 1998). Honest, clear, and two-way communication is an integral patient-centered care component; this implies information exchange between PCPs and patients and patients’ active involvement in healthcare decision-making (Levinson et al., 2010; Lezzoni et al., 2012; Starfield, 1998). Current research explicitly recognizes that healthcare services should be organized around patients’ needs and expectations to improve treatment adherence, trust, confidence in the healthcare system and ultimately patient health outcomes (Mercieca et al., 2014). Despite physician communication’s obvious benefits, studies assessing provider-patient communication and its impact on patient satisfaction and other patient outcomes remain limited (Caiata-Zufferey and Schulz, 2012). Thus, this study examined how patient PCP communication assessment was related to patient satisfaction with the PCP and patients’ PCP professional competence perceptions and patient demographic characteristics, using a segmentation approach. This study also explored patient segmentation as a potential managerial tool for healthcare quality improvement. Effective physician communication: definition Effective physician communication can be defined as active listening, appropriate questioning and provision of adequate instructions and relevant information to the patient (Levinson et al., 2010; Peters et al., 2008). Active listening requires intense physician listening to patients’ description of their illnesses and how the illnesses affect their lives (Levinson and Pizzo, 2011). Empathy and caring are other essential characteristics of effective physician communication (Levinson and Pizzo, 2011). Finally, the information is provided in a way easily understood by patients and their families (Tulsky, 2010). Thus, physician-patient communication is a multidimensional, dynamic and sophisticated process that has many determinants, including the ways in which patients and doctors assess their communication and the specific situations in which care is provided (Caiata-Zufferey and Schulz, 2012; Levinson et al., 2010; Street et al., 2007). Effective physician communication and patient outcomes Effective physician communication has been linked to several positive patient outcomes. For example, recent ambulatory and hospital studies have reported a strong positive relationship between effective physician communication and patient satisfaction (Clever et al., 2008; Napoles et al., 2009). In a prospective study, Thom and the Stanford Trust Study Physicians (2001) found that effective physician communication was strongly related to patient satisfaction and a significant predictor of patient trust. A positive relationship has also been found between effective provider communication and patient adherence to treatment (Street et al., 2007). A recent meta-analysis of 127 empirical studies showed that patient adherence was 19 percent higher when physicians were communicating well (Zolnierek and DiMatteo, 2009). Additionally, patient’s medical understanding and recall have been found to be higher due to effective provider communication (O’Keefe et al., 2001). Physician communication and quality of care There is increasing recognition that PCPs’ communication skills can also affect the quality of care. Both physicians and patients believe that physicians’ ability to

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communicate with patients is the most important factor in high-quality care (Rider and Perrin, 2002). Recent hospital studies (Clever et al., 2008) have found that the doctor’s ability to communicate effectively may also have a significant impact on patients’ hospital quality perceptions. One study (Chang et al., 2006), for example, reported that healthcare quality assessments by older adults were not related to technical quality; however, they were strongly associated with provider communication. In ambulatory care, patient-centered communication has been associated with improved patient outcomes (Kaplan et al., 1989; Swenson et al., 2004). Kaplan et al. (1989) found that more information given by physicians during the initial visit was associated with better psychological and physiological health of a patient at follow-up. Brown et al. (2004) found that effective physician communication resulted in a significant decline in emergency room use among low-income children with asthma. Poor physician communication is often associated with diagnostic errors for common conditions such as cancer, ischemic heart disease and infections (Singh, 2010) and compromised patient safety (Manias, 2010). Additionally, it may be a major barrier to patient adherence (Buxton, 2013). One study (Newcomb et al., 2010) found that 31 percent of patients reported poor communication as a key barrier to routine asthma management. About 60 percent of the patients in that study did not comply with PCPs’ recommendations; patients explained that physicians did not bring up the topic of adherence even if patients had visible asthma symptoms. These studies imply that doctor-patient communication is a powerful component of medical care and should be considered for healthcare quality improvement interventions. Possible solutions to improve physician and patient communication To develop and maintain long-term trusting relationships with patients, physicians should use patient-centered communication approaches that are congruent with patient needs and preferences for diagnostic and treatment information (Mercieca et al., 2014). Physicians should be aware that some patients are highly sensitive to deficits in physician communication; such patients are less likely to engage in relationships that are conducive to collaboration with doctors. Such behavior and attitudes may result in less treatment compliance, trust and satisfaction with providers (Buxton, 2013; Mercieca et al., 2014). Previous research suggests that physicians can benefit from training in communication (Clever et al., 2008; Hietanen et al., 2007; Levinson et al., 2010; Levinson and Pizzo, 2011). For instance, one study (Hietanen et al., 2007) found that a short course in communication for healthcare providers improved patient satisfaction and the quality of informed consent in a clinical trial. There are indications that communication training for office staff may improve patient experiences (Mercieca et al., 2014). While the role of the patient in the communication process has not been examined extensively, there are some indications that patients who receive basic training in communication may have better treatment adherence and improved health outcomes (Tai-Seale et al., 2007). Method Measures We developed a survey using five items from the patient satisfaction with general practitioners questionnaire (Grogan et al., 1995) to identify the latent heterogeneity in patients’ assessment of communication with their PCP. To measure overall patient satisfaction with the PCP, we used the following statement “Overall, I am very satisfied

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with my primary care doctor.” The item “I have developed a personal relationship with this doctor” was used to measure the interpersonal relationship between the patient and the PCP. Finally, patient assessment of physician competence “This doctor is well qualified to manage medical problems like mine” was adapted from Morgan and Hunt (1994). All items used a seven-point response rating scale (1 ¼ strongly disagree to 7 ¼ strongly agree). Our survey also asked for basic demographic information including age, education, gender, income and insurance status. Sample The study was carried out in two primary care clinics at a large urban university healthcare system in the southeastern USAin 2005 and involved adult patients waiting for appointments with their PCPs. Patients waiting for their first appointment with the physician were not recruited. One investigator was always present in the lobby of the clinics to address participants’ questions and concerns. Not to interrupt clinical appointments, patients were given a choice to complete the survey after the appointment in case the survey had not been completed by the time patients were called in. As a result, missing data were trivial. Institutional Review Board approval for the study was obtained from the authors’ university. The study included data from 514 completed surveys. Analysis We first used a latent class analysis (LCA) to model the unobserved heterogeneity that we hypothesized would characterize how patients assessed various aspects of physician communication. LCA, also called finite mixture modeling, is a probabilistic model-based clustering procedure that can be used to identify mutually exclusive categorical, latent (unobserved) homogeneous classes of cases. The derivation of classes (clusters) in a population is based on common patterns that individuals have for an indicator set. It can be assumed that class membership is unknown but can be inferred from data that are generated by a mixture of underlying response probability distributions (McCutcheon, 2002; McLachlan and Peel, 2000; Vermunt and Magidson, 2005). Items reflecting patients’ assessments of their PCP communication was used as the basis for deriving latent class membership. The parameters for our LCA models included conditional response probabilities and class membership probabilities and were estimated using a maximum likelihood criterion based on the expectation maximization algorithm (Dempsey et al., 1977). Conditional response probabilities indicated the likelihood of endorsing different response categories for each of the five PCP communication satisfaction indicators, given a respondent’s latent class membership. The pattern of conditional response probabilities across items used as the basis for determining class membership provided an interpretational framework for understanding derived classes. Generally, the conditional response probability pattern is relatively homogeneous for respondents in a given class but different from the patterns individuals who are members of the other classes. To examine each item’s utility for clustering respondents, class differences in conditional probabilities item responses were tested using the Wald statistic. The class membership probability parameter indicated the proportional membership (relative frequency of respondents) assigned to each derived class. The adequacy of different models with varying classes was based on several goodness-of-fit measures, including the log-likelihood ratio χ2 (LR), Akaike’s information criteria (AIC) and Bayesian information criterion (BIC). These fit measures

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are calculated as a function of the correspondence between observed and expected cell frequencies for multi-way frequency tables. The BIC and AIC are fit indices that are adjusted for model complexity (i.e. more classes). Consequently, these measures apply a penalty to the LR based on model complexity and sample size and are therefore reflective of both fit and model parsimony, with lower values being preferred. To further characterize different classes, we compared class membership with respect to several covariates, including overall patient satisfaction with the primary care doctor, patient assessment of a personal relationship with the PCP and the doctor’s professional competence, as well as some demographic characteristics (patient age, gender, education and annual income). All data were analyzed using SPSS and Latent GOLD software (Vermunt and Magidson, 2005).

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Results Model-based cluster analysis Respondents were categorized as belonging to one of three classes based on Bayesian posterior probabilities estimates (Table I). Although the goodness-of-fit measures were similar for the three-class and four-class models, the three class solution was selected as the final model because of its parsimony and because it provided a better balance for the four-class solution in regard to total patients in each class. Each of the five items on patient satisfaction with different physician communication aspects was a statistically significant differentiator between at least two classes. The conditional response probability patterns for the three classes relative to the response pattern for the overall sample are shown in Figure 1. There were 273 patients identified as members Class 1 (about 53 percent of the total sample). The profile of conditional response probabilities for patients in this class (range ¼ 0.78-0.98) revealed consistently high satisfaction levels with all PCP communication facets (Table II). Consequently, these patients could be viewed as belonging to a highly satisfied group. Most patients (96 percent) expressed high overall satisfaction with their PCPs; 92 percent agreed with the statement that their doctors were well qualified to deal with patient problems like theirs; and 48 percent indicated that they had developed a personal relationship with the PCP (Table III). Patients in the highly satisfied group had on average, less education and lower incomes than patients in the other classes: approximately 71 percent had achieved, at best, only some college education and only 19 percent reported annual incomes of $65,000 or more. There were 191 patients (37 percent of the sample) assigned to Class 2. In contrast to patients in Class 1 (the highly satisfied group), the conditional response probabilities for patients in this class revealed consistently low (range ¼ 0.03-0.10) satisfaction levels for all PCP communication indicators. Because their response profile reflected consistently low satisfaction, these patients were assigned to a highly dissatisfied group. Only about 26 percent of the patients in this group expressed high overall satisfaction with the PCP; about 29 percent agreed that the doctor was well qualified

Table I. Model fit summary

1-Cluster 2-Cluster 3-Cluster 4-Cluster

LL

BIC(LL)

AIC(LL)

Npar

L²

df

p

Class. Err.

−1,538.43 −1,065.57 −1,044.39 −1,040.11

3,114.32 2,206.05 2,201.15 2,230.03

3,088.87 2,155.15 2,124.79 2,128.21

6 12 18 24

1,005.63 59.92 17.56 8.98

25 19 13 7

o0.00 o0.00 o0.17 o0.25

0.00 0.02 0.08 0.07

Cluster 1

Cluster 3

Cluster 2

Overall

Patient assessment of PCP

1.0 0.8 0.6

337

0.4 0.2

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0.0 Always gives me every chance to talk about all my problems

Shows a genuine interest in my problems

Always gives me every chance to talk about all my problems Shows a genuine interest in my problems Clearly explains what is wrong before giving any treatment Fully explains how the illness will affect my future health Always asks about how my illness affects everyday life Note: n ¼ 514

Clearly Fully Always explains explains asks about what is how the how my wrong illness will illness before affect my affects giving any future everyday treatment health life

Figure 1. Profile plot

1 (n ¼ 273)

Cluster (%) 2 (n ¼ 191)

3 (n ¼ 50)

Overall (n ¼ 514)

0.98 0.99

0.10 0.03

0.76 0.84

0.63 0.62

0.96

0.10

0.73

0.62

0.97

0.08

0.44

0.57

0.78

0.03

0.11

0.41

professionally; but only 4 percent indicated that they had developed a personal relationship with the doctor. Patients in the highly dissatisfied group were on average more educated (51 percent had at least a college degree) and more affluent (28 percent reported annual incomes of $65,000 or more) than patients assigned to the other classes. In total, 50 patients (10 percent of the sample) were assigned to Class 3. Unlike patients in the larger highly satisfied and highly dissatisfied groups, the conditional response probabilities for these patients revealed a mixed profile with respect to level of satisfaction with PCP communication. For three indicators, “always gives me every chance to talk about all my problems,” “shows a genuine interest in my problems” and “clearly explains what is wrong before giving any treatment,” levels of satisfaction expressed by patients in Class 3 were similar, although not quite as positive as those expressed by patients in the highly satisfied group. However, patients in Class 3 were more like patients in the highly dissatisfied group in their levels of satisfaction in other indicators: “fully explains how the illness will affect my future health” and

Table II. Patients PCP communication assessment: indicator profiles

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Table III. Covariate profiles

Cluster (%) 1 2 3 Overall (n ¼ 273) (n ¼ 191) (n ¼ 50) (n ¼ 514) Covarites Overall, I am very satisfied with my primary care doctor* I have developed a personal relationship with this doctor* This doctor is well qualified to manage (diagnose and treat or make an appropriate referral) medical problems like mine*

0.96 0.48

0.26 0.04

0.78 0.18

0.68 0.27

0.92

0.29

0.73

0.66

Patient education level* ⩽High school Some college ⩾College

0.35 0.36 0.28

0.20 0.28 0.51

0.18 0.39 0.42

0.27 0.34 0.38

Patient income ($)a ⩽25,000 25,000-65,000 ⩾65,000

0.39 0.28 0.19

0.31 0.34 0.28

0.36 0.33 0.22

0.36 0.31 0.23

0.64 0.29

0.61 0.32

Gendera Female 0.62 0.59 Male 0.31 0.35 Notes: aDo not sum to 100 percent owing to missing values. *Significant at 0.5

“always asks about how my illness affects everyday life.” Given the variability in the way patients assigned to Class 3 viewed the different aspects of PCP communication, we considered these patients to form a mixed group. As in the highly satisfied group, high percentages of patients in the mixed group expressed overall satisfaction with their PCP (78 percent) and felt their doctor was well qualified to address their problems (73 percent). However, only 18 percent of the patients in this group indicated that they had developed a personal relationship with their doctor. These patients were on average more educated than patients in the highly satisfied group: 42 percent of patients had a college or higher education compared to 28 percent in the highly satisfied group. The mixed group opinions were closer to the highly dissatisfied group in terms of advanced education; 81 percent of mixed group patients and 79 percent of highly dissatisfied patients had some college or higher than college education. However, they were closer to the highly satisfied group in income: about 36 percent of the patients in the mixed group reported incomes of $25,000 or less (39 percent in the highly satisfied group) and only 22 percent reported incomes $65,000 or more (19 percent in the highly satisfied group). The mixed group was also similar to the highly satisfied group in gender composition: 64 percent were females in the mixed group and 62 percent in the highly satisfied group. All three groups significantly differed from each other with regard to patient education, satisfaction with the PCP, assessment of physician qualification and whether patients had developed a personal relationship with their PCP (Table III). Patient age, gender and time as a patient with the PCP were not significantly associated with patient perception of physician communication. Discussion In this study, we examined the latent heterogeneity in patient reported satisfaction with five elements of PCPs’ communication. Across these five elements, we identified three

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distinct groups with regard to patient assessment of physician communication. The largest group (highly satisfied) representing 53 percent of the total sample assessed their PCP communication as excellent. This relatively low satisfaction should not be surprising in light of recent studies related to PCP communication (Clever et al., 2008; Schenker et al., 2009). Patients in the highly satisfied group felt that their primary care doctors showed not only genuine interest in their health problems and provided comprehensive and clear descriptions of the diseases and future health consequences, but also gave the patients ample opportunities to talk about their health and asked the patients how the disease affected their everyday life. Patients in the highly satisfied group were also generally satisfied with their physicians and they provided favorable assessments of his/her professional competence. Over a third of patients (37 percent) in our sample (highly dissatisfied group) provided mostly negative assessments of PCP communication, expressed high general dissatisfaction with the physician and disagreed with the statement that their PCP was well qualified to manage their health problems. These patients were on average more educated and affluent and the group included more males. These findings may be an indication that some patients who believed that their doctors did not communicate well, carried over this perception to other aspects of their relationship with the PCP. Finally, about 10 percent of patients expressed generally lower satisfaction with PCP communication and other doctor-patient relationship aspects, though their dissatisfaction was not as extreme as in the highly dissatisfied group. Our analyses revealed that assessments of PCP communication differed sharply between the highly satisfied and highly dissatisfied groups. However, practically all patients in the sample had similar opinions about one physician communication aspect: most patients, including 22 percent in the highly satisfied group, disagreed with the statement that the doctor always asked how the patient’s illness affected her/his everyday life. This finding is a clear indication that the patients not only expect clear explanations and instructions but would also like their PCPs to show genuine interest and concern about their patients’ health and life. This finding may also mean that this component of effective communication should be included more often in patient-PCP discussions (Levinson and Pizzo, 2011). It also suggests an opportunity for providers to emphasize the importance of treatment adherence and to identify ways in which adherence requirements may be modified to address patient needs/daily schedule. A most interesting finding is patients’ response to whether they had developed a personal relationship with their PCPs. It was not surprising to find that only very few patients in the highly dissatisfied and mixed groups developed a personal relationship with their primary care doctors. What was unexpected that only about half (48 percent) in the highly satisfied group developed a personal relationship with their PCPs. This finding may suggest that at least for some patients in our sample having a personal relationship with the doctor was not essential for being satisfied with the doctor and the care they receive; this finding is worthy of future research. Previous research emphasized the importance of physician-patient communication and its relationship to patient satisfaction and clinical outcomes. Our study contributed to research by using a person-centered method instead of a variable-centered approach to analyze patient satisfaction data. The patient-centered segmentation

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approach we used allowed us to identify and characterize groups/clusters providing distinctly different assessment of their PCP’s communication and other relationship aspects with the doctor. If we had used a variable-centered approach (i.e. based on averaged aggregated data), our results would have indicated that patient assessment was quite positive (Figure 1). Thus, findings based on averages are potentially misleading. In light of these findings, caution should be exercised in using averaged patient satisfaction data for quality improvement interventions. Given the increased need to improve healthcare quality and patient-centered communication, our results indicate that patient segmentation may be an effective managerial tool for more accurate and focussed healthcare quality improvement efforts. There are some limitations to our work. Although we collected basic information on patient demographics, clearly there are other patient-level variables that could be collected to provide additional insights for characterizing the clusters (i.e. co-morbidities, chronic and acute illnesses). Moreover it would also be interesting to collect information regarding patient overall health status and examine how it may potentially affect their PCP communication assessment and the relationship with the doctor. Future research would benefit from patient assessment of physician communication based on patient race/ethnicity. Conclusions and recommendations We assessed the latent heterogeneity that exists in the population and identified several distinct homogenous patient groups with respect to assessment of PCP communication and other physician-patient relationship aspects. These results are in line with previous research emphasizing the heterogeneity of patient expectations and experiences with respect to physician communication. For instance, Swenson et al. (2004) found that about a third (31 percent) of the patients in their study preferred a traditional/instructional physician communication style. Healthcare providers thus need to understand how their communication approach affects different groups/ segments of their patients. Physician-patient communication is a two-way process, in which providers send and receive information from patients. To communicate effectively, physicians should actively reflect on their own and patients’ reactions/behavior and body language and adjust his/her communication approach accordingly (Caiata-Zufferey and Schulz, 2012). The incremental progression to optimal communication engaging patients in communication including prompts such as “Would you like to talk about it more?” or “Anything else you would like to discuss?” Thus, patient needs and preferences for communication should be explicitly addressed by physicians during their encounters. Our findings suggest patient age, education, gender and socio-economic status may facilitate further understanding of patient needs and preferences for communication but such information should not be used by itself to make decisions about how to communicate with patients. Healthcare professionals should be aware that some patients may have different information needs and demands. Clearly more work needs to be done to characterize different groups/clusters to shed light on how physicians should accommodate and satisfy various communication needs and demands of patients. Further studies are needed to help physicians understand the effects that their communication strategies have on patients and develop requisite skills to adjust how they communicate with different patients.

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Corresponding author Dr Elena A. Platonova can be contacted at: [email protected]

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