A relationship maintenance model: A comparison between managed health care and traditional fee-for-service

ELSEVIER

A Relationship Maintenance Model: A Comparison Between Managed Health Care and Traditional Fee-For-Service Hiram C. Barksdale, Jr. GEORGIA STATE UNIVERSITY

Julie T. Johnson WESTERN CAROLINA UNIVERSITY

Munshik Suh PUSAN NATtONALUNIVERS,TY

This article proposes and tests a model of the patient-physician relationship maintenance process. The model is based on constructs .from social exchange theory and Rusbult's im,cstment model. A patient's commitment to their relationship with their physician is conceptualized based on a threecomponent model ~1 commitment. The three components o.f commitment (c{fJective, continuance, and obligation commitmenO are examined in an interpersonal setting. A general model of the patient-physician relationship maintenance process is first lested. Then the model is tested separately on a traditional fee:/i)r-service subsample and a managed health care subsample (HMO, PPO). The restdts indicate that the relationship maintenance process is d!l.fi'rent in the traditional fee-for-service group than the managed health care group. Specifically, afje:ctive commitment is more important for traditional .feeTlbr-sen'ice patients and satisfaction and continuance commitment are more important for managed health care patients. j Bt~SN~ES 1997. 40.237-247 © 1997 Elsevier Science Inc.

ong-term patient-physician relationships benefit both patient and physician. One benefit from the patient's perspective is that a long-term relationship may allexqate concerns regarding the patient's inability to evaluate the quality of treatment. Additionally, a relationship may permit the patient to reduce the cost of medical care. This is because time and money spent with one physician is not readily transferable to a different physician (DiMatteo, Prince, and Taranta, 1979). Physicians also benefit from long-term relationships with patients. Retaining existing patients reduces the physician's need to continually attract new patients. Given an overAddress correspondence to Hiram C. Barksdale, Jr., Georgia State University,

Department of Marketing, University Plaza, Atlanta, GA 30303. E-mail: [email protected] Journal of Business Research 40, 237-247 (1997) © 1997 Elsevier Science inc. All rights reserved. 655 Avenue of the Americas, New York, NY 10010

supply of physicians in most major markets, attracting new patients has become increasingly difficult (Wright, 1995). Therefore, developing long-term patient relationships results in greater financial returns for physicians (Nelson, 1992). Long-term relationships are generally important in professional services. However, there has been little research effort devoted to understanding the nature of consumer relationships in which an individual consumer establishes a longterm relationship with a service provider (5heth and Parvatiyar, 1995). The purpose of this article is to identify factors that influence a patient's decision to continue a relationship with a physician and to provide referrals to the physician. Specifically, we develop and test a general model of relationship maintenance. We then split the sample into two groups to determine if the relationship maintenance process is the same in a managed health care setting (HMO, PPO) as in a traditional fee-for-service environment. The results should shed insight on ways that both physicians and managed health care providers can attract new patients and retain existing ones. -[he type of medical service setting (traditional fee-forsen'ice versus managed health care) may influence the relationship maintenance process. Some researchers maintain that managed health care has a detrimental effect on the patientphysician relationship (Rimler and Morrison, 1993). Other researchers suggest that lower cost options in managed physician networks may severely test the patient's loyalty to a traditional fee-for-service provider (MacStravic, 1994). Differences in the level of satisfaction between HMOs and traditional feefor-service plans have been found (McCombs, Kasper, and Riley, 1990; Leventhal, 1992). However, a comparison of the nature of the relationship maintenance process has not been conducted in the two different health care settings. ISSN 0148-2963/97/$17.00 PII S0148-2963(96)00240-8

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Relationship Maintenance Process Patient-Physician Relationship Studies in Medical Literature There are several streams of research in the medical literature that focus on the patient-physician relationship. The first examines the role of the physician and patient in the treatment process and how the role each plays improves the outcome of the medical treatment (e.g., Smith and Thompson, 1993). The second stream of research investigates the physician's communication style in the patient-physician relationship (e.g., Cleary and McNeil, 1988). The last stream of research explores the patient's satisfaction with medical treatment (e.g., Ware, Snyder, Wright, and Davies, 1983; Like and Zyzanski, 1987). The research that has been conducted helps us to better understand the patient-physician interaction. However, these studies provide little guidance regarding patients' decisions to continue their relationship with their physicians or their willingness to refer other patients to their physician.

Patient-Physician Relationship Studies in Health Care Marketing Literature Prior studies in the health care marketing literature have examined the patient-physician relationship. Typically, such studies have focused on patient satisfaction (e.g., Fisk, Brown, Cannizzaro, and Naftal, 1990), the patient's propensity to complain (e.g., Dolinsky, 1995; Henthorne, Henthorne, and Alcorn, 1994; Singh, 1990) and patient "doctor shopping behaviors" (e.g., Hays, 1987). These types of studies have addressed some important issues in the patient-physician relationship. However, research on the patient-physician relationship is incomplete. Little research has been conducted on factors influencing the relationship, such as the availability of alternative physicians to a patient. Other factors that may yield insight into the relationship maintenance process are a patient's investment in the relationship; a patient's personal relationship with the physician; or a patient's commitment to the relationship.

Relationship Maintenance Model We propose a general model of relationship maintenance which is shown in Figure 1. Because there is no theoretical basis for hypothesizing differences between the two groups, the model is the same for both the managed health care and traditional fee-for-service subsamples. The model proposes that four antecedent constructs (satisfaction, investment, alternatives, and personal relationship) affect a patient's commitment to a physician. A three-component commitment construct made up of affective commitment, continuance commitment, and obligation commitment is proposed to assess a patient's overall commitment to the relationship with the physician. Two relationship outcome constructs (return intention and referral intention) address the patient's future behavior

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as a result of experiences in the relationship with a physician. Conceptual development of the model and the hypothesized relationships among constructs are discussed in the following sections.

Social Exchange Theory Social exchange theory (Thibaut and Kelley, 1959) explains why individuals remain in a relationship. Thibaut and Kelley (1959) maintain that there is a difference between a person's satisfaction with a relationship and a person's commitment to maintain that relationship. They state that it is possible for an individual to be satisfied but not committed, or committed but not satisfied, with a relationship. Thibaut and Kelley (1959) also maintain that individuals constantly evaluate: (1) the quality of their relationships; (2) their commitment to their relationships; and (3) their satisfaction with their relationships. They state that individuals do this by comparing current relationships with potential alternative relationships they perceive to be available. Social exchange theory provides the theoretical .justification for including commitment, satisfaction, and the perceived availability of alternative physicians in our model.

Rusbult's Investment Model Rusbult's (1980) investment model extends Thibaut and Kelley's (1959) social exchange theory by adding the investment construct. Rusbuh (1980) states that relationship commitment is a function of satisfaction with the relationship, the perceived availability of alternatives to the relationship, as well as the individual's investment in that relationship. An individual's investment in a relationship, according to Rusbult, is made up of the time, energy, effort, or money put into making a personal relationship work. Rusbuh's model indicates that high investment and the perception that only poor alternatives are available will tend to keep an individual in a relationship that is dissatisfying. In such a situation, commitment to continue the relationship may be high even though relationship satisfaction is low. Rusbult's (1980) model provides the theoretical basis for including the patient's commitment to the relationship, their investment in the relationship and the patient's personal relationship with the physician in our model. The three dimensions of commitment and the hypothesized relationships among the antecedent constructs to commitment will be discussed in the following sections.

Three Dimensions of Commitment Morgan and Hunt (1994) have shown commitment to be an integral construct to the relationship maintenance process. Researchers in both organizational behavior (Allen and Meyer, 1990) and marketing (Kumar, Scheer, and Steenkamp, 1995) have conceptualized commitment as having three distinct components: affective commitment, continuance commitment, and obligation commitment. Affective commitment represents the degree to which a patient feels an emotional attach-

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HIO HI Af[ective

Conm~unent Renlm Intentions H5 Alternatives _ H6 HI7

inRelalion ) H15

!.~FPersonal ' Relationship

H7 v

HI6 HI4

Figure 1. Relationship maintenance model.

ment to his or her doctor. Continuance commitment refers to the extent to which a patient feels the need to continue a relationship with a doctor. Obligation commitment addresses the extent to which a patient feels that he or she is obligated to continue the relationship with a doctor. In other words, patients with strong affective commitment remain with their physician because they want to; those with a strong continuance commitment remain because they need to; and those with a strong obligation commitment remain because they feel that they ought to (Meyer, Allen, and Smith, 1993).

Antecedents to Commitment We propose that patient satisfaction, the patient's investment in the relationship with their physician, the patient's perception of the availability of alternative physicians, and the patients' personal relationship with their physician are important antecedents to commitment. The theoretical bases for the antecedents in the proposed model are derived from social exchange theory (Thibaut and Kelley, 1959) and Rusbult's (1980) investment model.

T

ponent model of commitment, the commitment constructs they used are conceptually similar to Allen and Meyer's (1990) affcctive commitment dimension. Allen and Meyer (1990) maintain that satisfaction has a direct and positive relationship with affective commitment. In other words, patients who are satisfied want to continue seeing their physician. Therefore, we hypothesize: HI: Greater patient satisfaction will be associated with greater levels of affective commitment to the physician.

Researchers have also examined the relationship between satisfaction and continuance commitment. The organizational commitment results indicate that continuance commitment and job satisfaction are negatively related (Jenkins and Tomlinsort, 1992). In other words, individuals who are satisfied are less likely to feel that they need to remain in the relationship (continuance commitment). Therefore, we hypothesize that: H2: Patient satisfaction will be negatively associated with continuance commitment to the physician.

Investment Satisfaction Patient satisfaction is a patient's attitude toward their previous interactions with their physician. The organizational behavior literature has documented a positive relationship between an employee's job satisfaction and commitment to the organization (e.g., Brooke and Price, 1989; DeCottis and Summers, ]987). While these researchers did not examine a three-corn-

The investment construct was conceptualized by Rusbult (1980) to include "sunk costs" in the relationship. These sunk costs include resources such as time, emotional involvement, self-disclosure, and money (Rusbuh, 1980). Consistent with Rusbult (1980), we define investment as the resources a patient has put into a relationship with his or her physician that would be lost if the relationship ended.

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According to social penetration theory (Altman and Taylor, 1973), partners will continue to deepen a relationship as long as they are satisfied with the relationship (Altman and Taylor, 1973). Thus, the more satisfied a patient is with their physician relationship, the more willing the patient will be to invest in the current relationship. Therefore, we hypothesize that:

H3: The greater a patient's satisfaction with a physician, the greater the patient's investment in the relationship. However, satisfaction may not be necessary for a patient to continue a physician relationship. As discussed previously, a patient may not be fully satisfied with the doctor, but may feel he/she has invested too much time and money with the current doctor to terminate the relationship. This is because the time and money previously invested are not easily recovered (Rusbult, 1980). For example, revealing personal medical information to a physician and spending time and money for treatment are likely to be viewed as a significant investment by a patient. High investments in an unsatisfactory patient-doctor relationship may cause the patient to remain in the relationship. In other words, the investment in the relationship causes the patient to need (continuance commitment) for the relationship to continue. Therefore, we hypothesize that:

H4: High perceived investments on the part of a patient will be associated with higher levels of continuance commitment.

Available Alternatives Rusbult (1980) maintains that the alternatives available to an individual will influence whether or not an individual remains in the relationship. If the individual perceives that there are few alternatives, then he or she will be more committed to continue the relationship. A patient will likely continue a relationship with his or her current doctor if the patient perceives there are no other available physicians. Thus, the patient needs (continuance commitment) to remain in the relationship because of the lack of alternatives and may be willing to invest more to keep the relationship. Therefore, we hypothesize:

HS: The greater the perceived availability of alternative physicians, the lower the patient's continuance-commitment. H6: The greater the perceived availability of alternative physicians, the lower the patient's investment in the relationship.

Personal Relationship A patient's personal relationship with the physician refers to the extent to which a patient interacts socially with his or her physician. This construct addresses the extent that nonbusiness relationships affect client-provider relationships. Organizational behavior research has found that personal relation-

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ships are positively related to an employee's obligation commitment to the organization (Allen and Meyer, 1990; Wiener, 1982). If a personal relationship exists between a patient and physician, the patient will feel obligated to continue the relationship. For example, a patient and their physician may belong to the same country club and socialize on occasion. This personal bond may create a feeling of obligation that the patient ought to continue to patronize the doctor. If patients feel that they ought to continue their relationship with their physician, then they are likely to invest more in that relationship. In a similar vein, if a patient feels they ought (obligation commitment) to continue a relationship, then they will likely feel that they need (continuance commitment) to continue the relationship. Therefore, we hypothesize that:

HT: The stronger a patient's personal relationship with their physician, the greater the patient's obligation commitment to the relationship. H8: The stronger a patient's personal relationship with their physician, the greater the level of investment the patient will make in the relationship. H9: The greater a patient's level of obligation commitment (ought to continue) to the relationship, the greater the patient's continuance commitment (need to continue).

Outcome Variables: Return Intention and Referral Intention Our proposed relationship maintenance model includes two important marketing outcomes of professional service relationships: return intentions and referral intentions. Return intention captures the likelihood the patient will see their doctor in the future. Referral intention measures a patient's willingness to refer other potential patients to their physician. Intention to return and intention to refer are cognitive measures of loyalty (Fisk, et al., 1990). Patient loyalty can produce direct, measurable value to physician's practices fortunate enough to enjoy high levels of patient commitment (MacStravic, 1994). In a managed health care system, loyal patients can make the difference between financial success and disaster for the physician (Bricklin, 1994; Coile, 1993). Return intentions and patient satisfaction are related. If physicians fail to keep their patients satisfied, patients are likely to have plenty of other, often less expensive, options (Pincus, 1995). Patient satisfaction with physician care is one factor that contributes to the longevity of patient-physician relationships (Gebel, kucas, and Westbury, 1993). A positive relationship between satisfaction and intention to return to the same doctor has been found in the health care marketing literature (Fincham and Wertheimer, 1986; Ware, Davies-Avery, and Stewart, 1978). In a dental health care setting, satisfaction had a significant effect on the patient's intention to return to the dentist (McAlexander, Kaldenburg, and Koenig, 1994). Therefore, we hypothesize that: RETURN INTENSIONS.

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HIO: Higher levels of patient satisfaction will be associated

with greater levels of patient return intentions. Satisfaction plays an important role in a consumer's decision to return. However, satisfaction, by itself, is not a sufficient predictor of customer loyalty (Reichheld, 1993). The health care literature maintains that patient loyalty results from the patient's commitment to the physician (MacStravic, 1987). The organizational behavior literature has found a positive relationship between affective, continuance, and obligation commitment and an employee's intention to remain in the employment relationship (e.g., Ferns and Aranya, 1983; Jaros, Jermier, Koehler, and Sincich, 1993). Therefore, we hypothesize that: Hl1: Greater levels of affective commitment will be associ-

ated with higher levels of patient return intentions. H12: Higher levels of continuance commitment will be

associated with greater levels of patient intention to return. HI3: Higher levels of obligation commitment will be asso-

ciated with higher levels of patient return intentions. Patient referral may be very important to the long-term financial well-being of a physician's practice. In a study conducted by Jensen (1986), almost 45% of all patients were referred to their current doctor by a friend, acquaintance, or family member. Other than physician referrals, referrals from satisfied patients may be one of the most important factors in selecting a physician (Peterson, 1988). Therefore, we hypothesize that: REFERRAL INTENTION.

H14: Higher amounts of patient satisfaction with their phy-

sician will be associated with higher levels of referral intentions. Rusbult (1980) maintains that an individual who is highly invested in a relationship will be more likely to be loyal to that relationship. Loyal patients perform an essential role in bringing in new patients by referring people to their physician (MacStravic, 1994). Therefore, we expect that: H15: Higher levels of patient investment in their physician

relationship will be associated with higher levels of referral intentions. The personal relationship that exists between the patient and the physician can also influence the ongoing nature of the relationship. However, it may be difficult for the patient to separate the personal relationships from the business relationship (Ford, 1980). Patients who have a personal relationship with the physician may be hesitant to refer other individuals to that physician. This is because patients may perceive that they receive better care from a physician they are friends with or because they realize that their personal relationship with their physician may influence their evaluation. They may also feel that other patients will think they have something

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to gain from referring business to someone with whom they have a social relationship. Therefore, we hypothesize that: H16: The stronger the personal relationship between a

patient and physician, the lower the patient's intention to provide referrals. Mowday, Porter, and Steers (1982) argue that an individual who exhibits high levels of attitudinal commitment to an organization will show a willingness to exert considerable effort on behalf of the organization. Thus, clients with affective commitment toward their professional service provider are likely to refer their friends or family members even though they are not required to do so. Therefore, we expect that: H17: Greater levels of affective commitment will be posi-

tively related to a patient's intention to return. This concludes the discussion of our relationship maintenance model. The next section describes the research methodology used to test our model.

Methodology Sample and Data Collection Procedure Data were collected from a random sample of employees of a large organization. One thousand eight hundred questionnaires were mailed. Two weeks after the first mailing, a followup letter was sent to each subject who had not returned a completed questionnaire. Five hundred and seventy-five individuals returned the questionnaire. However, only 413 responses were usable (23% response rate). Usable responses were those in which the patient answered two screening questions. The first screening question asked if the respondent bad a regular physician. If the respondent answered yes, the second question asked if the respondent had seen their physician in the past year. In other words, only those respondents who indicated they had a personal physician and had seen their physician during the previous year were kept for data analysis. The respondents' type of health insurance was categorized into two groups: (1) traditional fee-for-service type health insurance and (2) prepaid managed health care insurance (HMO, PPO). The principle difference between these two types of health insurance is whether or not patients have freedom to choose their own physicians without restriction. Th~s difference may affect the nature of the patient-physician relationship. The usable sample size for traditional fee-forservice group was 240 and the managed health care group was ] 73.

Measure Development All scale items were adapted from existing measures. All items were measured with a 5-point Liken scale format, ranging from ]-strongly disagree to 5-strongly agree. Each of the measures is described below.

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The 14-item commitment scale (or = .79) was adapted from Allen and Meyer (1990). Affective commitment and obligation commitment were conceptualized as first-order factors. Sample items include "I feel good about seeing my doctor" for affective commitment and "I feel a sense of obligation to stay with my doctor" for obligation commitment. Consistent with the literature, continuance commitment was conceptualized as a second-order factor, consisting of two first-order factors (McGee and Ford, 1987). One first-order factor represents personal sacrifice that results from leaving the relationship. A sample item is "Leaving my doctor would mean considerable personal sacrifice." The other first-order factor represents the necessity of continuing the relationship. A sample item is "Staying with my doctor is largely a matter of necessity." The l l - i t e m overall patient satisfaction measure (e~ = .82) was adapted from the Patient Satisfaction Questionnaire (PSQ II) developed by Ware et al., (1983). Overall patient satisfaction was conceptualized to be a second-order factor with three first-order factors. The first-order factors are satisfaction with access, satisfaction with technical care, and satisfaction with interpersonal care. Sample questions include statements such as "My doctor seldom explains why lab tests are ordered" and "My doctor's office is conveniently located." The 3-item perceived availability of alternatives measure (cx = .83) was adapted from Rusbult, Farre[1, Rogers, and Mainous (1988). A sample item is "My choices for a new doctor are likely to be at least as good as current ones." The 4-item measure of the patient's investment in the relationship (or = .90) was adapted from previous studies that tested the investment model (Farrell and Rusbult, 1981; Rusbult and Farrell, 1983; Rusbult et al., 1988). The items have been rewarded to reflect a patient's investment in their relationship with a physician. Sample items include "I have a great deal invested in the relationship," The 4-item personal relationship scale (e~ = .69) was inspired by Wiener (1982). A sample item is "I do not see my doctor on a social basis." A 1-item measure of a patient's referral intention was adapted from Sewall's (1981) consumer purchase intention scale. The item is, "If a friend or family member needed a doctor for primary health care, I would recommend my doctor." The 3-item return intention scale (cx = .82) was adapted from Swan, Sawyer, Van Matre, and McGee (1985). A sample item is "The next time I need to see a doctor, I plan to use my current doctor."

Analysis Data were analyzed using LISREL VII. Analysis proceeded in accordance with Anderson and Gerbing's (1988) two-step procedure. The measurement model and the hypothesized structural model were analyzed for both groups combined (traditional fee-for-service and managed health care). Then the hypothesized structural model was analyzed for each group.

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MEASUREMENT MODEL. To deal with the second-order continuance commitment and patient satisfaction constructs, the items were examined in a second-order confirmatory factor analysis. Continuance commitment was conceptualized as a secondorder factor consisting of two first-order factors. The regression factor scores for the second-order latent construct were used to calculate a second-order composite for continuance commitment. The regression equation is:

Y -- (.056)X1 + (.187)X2 4- (.110)X3 4- (.081)X4 + (.161)X5 + (.197)X6 where Y is a second-order composite factor, continuance commitment. X1 and X3 represent the first-order continuance commitment factor, personal self-sacrifice. X4 through X6 represent the first-order continuance commitment factor, necessity of continuing the relationship. Patient satisfaction was also conceptualized to be a secondorder factor consisting of three first-order factors. Again, the regression factor scores for the second-order latent construct were used to calculate a second-order composite for patient satisfaction. The regression equation is: Y = (.020)X1 + (.077)X2 + (.010)X3 + (.011)X4 + (.215)X5 + (.039)X6 + (.334)X7 4- (.068)X8 4- (.038)X9 + (.234)X10 + (.296)Xll where Y is a second-order composite factor, patient satisfaction. X1 through X4 represent the first-order patient satisfaction factor, satisfaction with access. X4 through X7 represent the first-order factor, satisfaction with technical care. X8 through X l l represent the first-order patient satisfaction factor, satisfaction with interpersonal care. The measurement model was analyzed using 22 items. The error variance of the single-item indicators were fixed to 0. ls 2 (S6rbom and J6reskog, 1982). The initial fit statistics of the measurement model were: X2 = 613.25; (p = .000) with 176 df; GFI = .88; AGFI = .83; RMR = .08. The fit statistics indicated that the model could be improved by deleting problematic items (one perceived availability of alternative item, one personal relationship item, two investment in the relationship items, one affective commitment item, one obligation commitment item, and one return intention item). The measurement model was respecified and an acceptable fit was achieved: X2 = 87.39; p = .006 with 57 df; GFI = .97; AGFI = .94; RMR = .03. Once an acceptable measurement model was achieved, we proceeded to test the structural model for both groups combined. The correlation matrix used in the structural model is shown in Table 1. The structural model for the combined groups achieved a good fit: X2 = 138.40 (p = .000) with 73 dr; GFI = .96: AGFI = .93; RMR = .04. The results shown in Table 2 indicate that 14 hypotheses were supported and three hypotheses were COMBINED GROUPS STRUCTURAL MODEL RESULTS.

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Table 1. Correlation Matrix

INVEST AFFCOM CONCOM OBLCOM RETR REFER PATSAT ALT PERSEL

1

2

3

4

1.000 0.494 0.119 0.333 0.422 0.585 0.561 -0.483 0.662

1.000 -0.201 0.258 0.771 0.767 0.881 -0.274 0.513

1.000 0.366 - 0.063 -0.124 -0.228 -0.435 0.079

0.152 0.248 0.293 -0.150 0.503

5

6

7

8

1.000 0.613 0.721 -0.303 0.407

1.000 0.765 -0.310 0.492

1.000 -0.311 0.582

-0.299

1.000

not supported for the combined groups (H4, H13, H16). The t-values for two hypotheses (H4, H16) were not significant. The t-value for the other hypotheses (H13) was significant but in the opposite direction than hypothesized.

1.000

1.000

TRADITIONAL FEE-FOR-SERVICE GROUP STRUCTURAL MODEL RESULTS. Next, we tested the same structural model as above

using only the 240 respondents that indicated their physician relationship was in the context of traditional fee-for-service.

Table 2. LISRELResults

Hypothesis

SAT---*AFFC (H1) SAT---*CONC (H2) SAT---*INV (H3) 1NV---*CONC (H4) ALT---*CONC (H5) ALT---*INV (H6) PREL---+OBLC (H7) PREL----,INV (H8) OBLC--,CONC (H9) SAT---+RETR (H 10) AFFC--,RETR (HI 1) CONC----,RETR (H12) OBLC--+RETR (H13) SAT--*REFR (H 14) INV--+REFER (H15) PREL----*REFR (H16) AFFC---+REFR (H17) * t-values are in p a r e n t h e s e s

Both Groups Combined Paramter Hypothesis Estimate Results*

0.754 -0.327 0.255 0.008 -0.326 -0.347 0.366 0.56 l 0.370 0.165 0.440 0.173 -0.124 0.287 0.208 -0.058 0.485

Supported (20.43) Supported (-8.76) Supported (3.53) Rejected (.22) Supported (-8.49) Supported (-5.51) Supported (6.86) Supported (7.01 ) Supported (6.21) Supported (2.05) Supported (4.83) Supported (2.97) Rejected (opposite dir.) (-2.08) Supported (2.72) Supported (4.48) Rejected (-0.907) Supported (4.29)

Traditional Fee-For-Service Parameter Hypothesis Estimate Results*

0.480 -0.244 0.129 0.118 -0.307 -0.286 0.334 0.462 0.383 0.028 0.558 0.015 -0.064 0.240 0.082 -0.023 0.386

Supported (10.71) Supported (-5.03) Rejected (1.23) Supported (2.77) Supported (-6.41) Supported (-3.32) Supported (4.59) Supported (4.38) Supported (4.54) Supported (0.42) Supported (5.72) Rejected (0.21) Rejected (-0.81) Supported (2.29) Rejected (1.37) Rejected (-0.29) Supported (2.95)

Managed Health Care Parameter Hypothesis Estimate Results*

0.968 -0.301 0.130 -0.179 -0.393 -0.403 0.482 0.674 0.426 0.772 -0.024 0.435 -0.231 0.772 0.499 -0.310 0.329

Supported (15.53) Supported (-4.86) Rejected (1.25) Rejected (-1.98) Supported (-4.96) Supported (-4.54) Supported (6.14) Supported (5.48) Supported (4.03) Supported (2.14) Supported (-0.07) Supported (4.29) Rejected (opposite dir.) (-2.25) Rejected ( 1.46) Supported (4.15) Supported (-2.11) Rejected (0.97)

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The results indicate that the model also achieves a good fit: X2 = 119.47 (p = 0.00) with 73 df; GFI = .94; AGFI = .90; RMR = .06. The results (also shown in Table 1) indicate that 11 hypotheses were supported and six hypotheses were not supported. The six that were not supported were H3, H10, H 12, H 13, H 15, H 16. The t-values for the six hypotheses that were not supported were not significant. Again, we tested the same structural model on the 173 respondents that indicated their physician relationship was in the context of a managed health care group. The results indicate that the model also achieves a good fit: ×2 = 99.00 (p = 0.00) with 73 dr; GFI = .93; AGFI = .89; RMR = .05. The results (also shown in Table 1) indicate that 11 hypotheses were supported and six hypotheses were not supported. The six that were not supported are H3, H4, H l l , H13, H14, H17. Five of the six hypotheses not supported had t-values that were not significant. The five hypotheses that had insignificant t-values were H3, H4, H l l , H14, H17. The t-value for one hypothesis was significant but in the opposite direction to what had been hypothesized (H13). MANAGED HEALTH CARE STRUCTURAL MODEL RESULTS.

Summary of Findings between Traditional Fee-for-service and Managed Health Care Groups The results of the models indicate that the relationship maintenance process is different for traditional fee-for-service and managed health care settings. Of the 17 total hypotheses, the traditional fee-for-service and managed health care groups had similar significant findings for seven of the hypotheses. The seven hypotheses are H1, H2, H5, H6, H7, H8, H9. Eight hypotheses yielded conflicting findings when the two patient groups were compared. The disparate results were for H4, H10, H l l , H12, H14, H15, H16, H17. Additionally, two hypotheses were rejected in both the traditional fee-for-service and managed health care groups. The two rejected hypotheses are H3, H13. These similarities and differences will be discussed in the following sections. Seven hypotheses yielded significant positive findings for both the traditional fee-for-service and managed health care groups. Greater patient satisfaction was found to lead to greater affective commitment in both groups (H 1). Higher patient satisfaction levels resulted in lower continuance commitment in both groups. In other words, patients who are satisfied do not feel that they remain in the relationship because they need to (H2). In addition, the findings indicate the more physician/ alternatives patients perceive to be available, the less likely they are to feel that they need to remain in the relationship (continuance commitment) (H5). The more options (physician alternatives) patients perceive are available to them, the less likely patients are to invest in their relationship with their physician (H6). Both groups indicated that a personal relationship with the physician results in greater levels of

SIMILAR SIGNIFICANT FINDINGS BETWEEN GROUPS.

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obligation commitment (H7). Additionally, a patient's personal relationship with the physician results in greater investment by the patient in their physician relationship (H8). Finally, both patient groups indicated that higher amounts of obligation commitment result in greater levels of continuance commitment (Hg). DIFFERENT FINDINGS BETWEEN GROUPS. W h i l e seven hypotheses yielded similar findings between the traditional fee-forservice and managed health care groups, eight of the hypotheses yielded conflicting results. In general, the findings indicate that the two groups have different reasons for returning to their physician and referring other patients to their physician. Perhaps the most interesting finding of the fee-for-service versus managed health care comparison is the difference in the relationship between return intention, satisfaction, affective, and continuance commitment. The positive relationship between affective commitment and return intention was supported in the traditional fee-for-service group but not in the managed health care group (H11). Conversely, the positive relationship between continuance commitment and return intention (H12) and satisfaction and return intention (H10) was supported in the managed health care group but not in the traditional fee-for-service group (H12). These findings suggest the reason that patients decide to return to their doctor differ according to whether their health care can be characterized as managed health care or traditional fee-for-service. Specifically, because the traditional fee-forservice relationship permits patients greater freedom of choice, being satisfied with the physician may not be enough to keep the patient in the relationship. It a patient does not want to stay (affective commitment) with one doctor, he or she can switch to another doctor. However, in managed health care relationships, the insurance provider restricts the patient's freedom by limiting the approved physician providers. A patient may feel that he or she needs (continuance commitment) to return to the same physician. Whether satisfied or not, patients may perceive they must continue in a relationship that they have been assigned to by their managed health care provider. Another fundamental difference between the managed care patients and fee-for-service patients is in the antecedents to referral intention. In the traditional fee-for-service patient subgroup, positive relationships between satisfaction to referral intention (H 14) and affective commitment to referral intention (H17) were both supported. Neither relationship was supported in the managed health care patient subgroup. Conversely, in the managed health care subgroup, a positive relationship between the investment in the relationship and referral intention (H14) was found. Additionally, a negative relationship between a patient's personal relationship with the physician and referral intentions (H14) was found. However, neither of these relationships were supported in the traditional fee-for-service group. This difference in intention to refer other patients may also

A Relationship Maintenance Model

be explained by the degree of freedom a patient has in selecting a physician under the two different types of health care plans. In the managed health care situation, patients understand that their physician's options are limited because of restrictions imposed by the health care plan. Managed health care patients may assumed that their physician treats only those patients who have their same prepaid insurance plan. They may feel that referring other patients to their physician would be useless. On the other hand, patients with traditional fee-forservice insurance are likely to refer patients to their physician if they are satisfied with the relationship and want (affective commitment) the relationship to continue. The final difference between the two groups was that in the traditional fee-for-service setting, a patient's investment in the relationship with a physician was positively related to the patient's feeling that he or she needs (continuance commitment) to continue the relationship. However, this relationship was insignificant and in the opposite direction than hypothesized in the managed health care group. An explanation for this finding is that patients in traditional fee-for-service relationships typically are required to pay more "out of pocket" money to see a physician than individuals in a managed health care setting. This "out of pocket money" may be perceived to be largely wasted and not readily transferable to a different physician (DiMatteo, Prince, and Taranta, 1979). In a managed health care setting, however, the patient's per visit investment (copayment) in the relationship is lower. Therefore, the managed care patient may feel less of a need to continue the relationship. SIMILAR INSIGNIFICANT FINDINGS BETWEEN GROUPS. Only two

of the hypotheses were rejected in both the traditional feefor-se~,ice and managed health care groups (H3, H13). In both groups, patient satisfaction did not cause the patient to invest in their physician relationship. Additionally, the hypothesis that obligation commitment results in a greater intention to return was rejected in both cases. In the traditional fee-for-service group, the path between obligation commitment and return intention was not significant. In the managed health care group, the path was significant but in the direction opposite to that which had been hypothesized. One explanation for this finding is that the relationship between obligation commitment and return intentions is indirect, through continuance commitment.

Implications for Physicians The most important managerial implication for physicians can be surmised from the two relationship outcome variables: return intentions and referral behavior. These two variables are critical to physicians' success in today's intensely competitive market. Findings related to return intentions suggest possible ways that physicians can retain current patients and prevent patient turnover. Findings related to referral intentions, on the other hand, suggest insights into ways that physicians can

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expand their patient base and attract new patients. Thus, physicians need to understand the behaviors that determine referral and return intention. Physicians need to recognize that patients who continue in their physician relationships may do so for different reasons. Traditional fee-for-service patients may continue in a relationship with a physician because of affective commitment toward the physician. Patients in managed health care may return because they have no choice. Our findings suggest that affective commitment is a more accurate and consistent predictor of patient's return behavior than satisfaction for the traditional fee-for-service patient. However, for managed care patients, satisfaction and continuance commitment are more accurate predictors of the patient's return intention. Continually monitoring and analyzing patients' attitudes toward their physician is necessary. What should be measured depends on whether the patient is a traditional fee-for-service patient or a managed care patient. In a traditional fee-for-service setting, physicians should focus on increasing patients' affective commitment. It may be difficult for patients to judge the physician's technical skills, but they can judge his or her interpersonal skills. Physicians should remember to focus on the "'human side" of medicine by making the service encounter as pleasant an experience as possible. The goal is to enhance affective commitment and create loyal patients who want to return. Other important managerial implications for physicians are the positive relationships between referral intention and its antecedents. These relationships suggest ways to expand the patient base. Attracting new patients is one of the most important tasks facing physicians in an increasingly competitive market. The results from this study suggest that in traditional fee-for-service settings, referral intentions are positively influenced by both patient satisfaction and affective commitment. Both satisfaction and affective commitment may be influenced by the way doctors treat their patients. However, in a managed heah:h care environment, physicians must locus on encouraging patients to invest more in the relationship to increase referrals. Physicians should encourage patients to become active partners in the health care process. Physicians may spend more time with patients informing them of their health care options. By enabling patients to make informed choices, patients are likely to feel more invested in the relationship. Patient investment in the relationship, in turn, should produce increased physician referrals.

Implications for the Managed Health Care Administrators The findings of this study also have managerial implications for administrators of managed health care plans. Managed health care patients did not evidence a positive relationship between affective commitment and return intention. However, continuance commitment was found to have a positive effect on a patient's return intention. This finding suggests that

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patients in managed health care settings continue their relationship because they have to. In a managed health care setting a patient's affective commitment does not influence their intention to return. However, our findings suggest that the availability of physician alternatives influences whether patients feel they need to remain in the relationship with their physician. If patients are unhappy with their physician alternatives, they may consider increasing their physician alternatives by moving their insurance coverage to a managed health care plan that offers more physician options. Managed health care administrators need to develop methods that monitor patients continuance commitment and satisfaction levels. Ongoing monitoring of continuance commitment and patient satisfaction levels must then be translated into specific systems and programs that will help retain patients. As discussed above, patient's affective attitude and satisfaction can be influenced by the manner in which physicians treat patients. Managed health care administrators should engage in internal marketing to educate their participating physicians on the importance of personal care. When patients are assigned to different physicians every time they visit the managed health care facilities, patients may not feel invested in the relationship. Therefore, administrators need to develop a system that can guarantee that patients will see the same physician each time if they choose to do so.

Limitations of the Study While this study helps us to better understand patientphysician relationships, it is not without limitations. First, data were gathered from employees of a single large organization which somewhat limits the generalizability of our findings. However, the organization did offer employees a broad choice of health care options. A traditional fee-for-service health care option was offered as well as several managed health care options (HMO, PPO). While this does not ensure generalizability, it does provide us with greater confidence in the results. A second limitation is that our study was based on cross-sectional data. The cross-sectional nature of the study caused us to examine patient return and referral intentions rather than actual patient behavior. A longitudinal study would yield additional insight into the relationship maintenance process and would allow actual return/referral behavior to be examined.

Areas for Future Research Future research should evaluate whether customer return/ referral intentions actually predict patient behavior. Research should also be conducted to determine whether patients are satisfied with their managed health care plans or if they merely tolerate the plans because they have no other alternatives. Additionally, this study should be replicated in other companies to see if the patient-physician relationship is similar. Finally, the relationship maintenance model should be tested

H.C. Barksdale et al.

in other settings to see if the model is generalizable beyond the patient-physician setting. Authors are listed in alphabetical order; each contributed equally to this project.

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A Relationship Maintenance Model

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