Human Reproduction, Vol.29, No.4 pp. 712–719, 2014
Advanced Access publication on February 18, 2014 doi:10.1093/humrep/deu023
ORIGINAL ARTICLE Infertility
Fertility clinicians and infertile patients
in China have different preferences
in fertility care
Q.F. Cai 1, F. Wan 2, X.Y. Dong 1, X.H. Liao3, J. Zheng 4, R. Wang 1,
L. Wang 1, L.C. Ji1, and H.W. Zhang 1,*
1
Reproductive Medicine Centre, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei
430030, China 2Centre for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, PA 19104, USA 3Reproductive
Medicine Centre, Women and Children’s Hospital of Fujian Province, Fuzhou, Fujian 350000, China 4Reproductive Medicine Centre, Women and
Children’s Hospital of Hubei Province, Wuhan, Hubei 430070, China
*Correspondence address. Reproductive Medicine Centre, Tongji Hospital, Tongji Medical College, Huazhong University of Science and
Technology, 1095 Jiefang Avenue, Wuhan, Hubei 430030, China. Tel: +86-13986151967; E-mail: [email protected]
Submitted on October 27, 2013; resubmitted on January 18, 2014; accepted on January 23, 2014
study question: Do the preferences for fertility care of infertile Chinese patients differ from those of fertility care providers?
summary answer: Infertile Chinese patients attached the greatest importance to physicians’ attitude but, in contrast, fertility care providers in China considered treatment effectiveness to be the most important factor in fertility care.
what is known already: In Europe, physicians underestimate the importance of patient-centred infertility care.
study design, size, duration: A conjoint survey was distributed among 417 female infertile Chinese patients and 83 fertility care
providers from February 2013 to August 2013.
participants/materials, setting, methods: In this pilot study, 389 patients and 83 fertility care providers completed the
survey at three reproductive medicine centres. Rating-based conjoint analysis was performed to elicit patients’ and their caregivers’ preferences
regarding fertility care. Cluster analysis was used to explore the heterogeneity among patients’ preferences.
main results and the role of chance: When searching for fertility care, patients valued the physicians’ attitude the most, followed by success rates, distance from home to the fertility centre, physician continuity throughout the treatment period and type of fertility centre.
Fertility care providers considered success rates (effectiveness) to be the most important factor when recommending a fertility centre. Fertility
patients and care providers had significantly different views on the value of treatment effectiveness, physician attitude and physician continuity
(P-values ,0.05). Cluster analysis revealed that patients’ preferences were heterogeneous.
limitations, reasons for caution: The sample size is relatively small, and there is insufficient power for heterogeneity analysis.
Two levels for each of five design factors (25) may not fully capture the characteristics of realistic fertility centres. Rating-based conjoint analysis
could be inferior to choice-based conjoint analysis in terms of predictive accuracy.
wider implications of the findings: Fertility care providers in China significantly underestimate the importance of patientcentredness to infertile patients. To deliver optimal fertility care to infertile Chinese patients, fertility care providers need to understand the importance of patient-centred care, such as a friendly attitude, sympathy for patients’ suffering, respect for patients’ right to informed consent and a
transparent treatment process.
study funding/competing interest(s): This study was not funded, and there are no conflicts of interest.
trial registration number: None.
Key words: patient-centredness / treatment effectiveness / fertility care / patient preferences / conjoint survey
& The Author 2014. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved.
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713
Patients and clinicians view fertility care differently
Introduction
The relationship between healthcare providers and patients in China has
worsened for decades and has caused numerous social problems. The
increasing tension between providers and patients has transformed
Chinese hospitals into ‘battle’ grounds, resulting in injuries and even
deaths among doctors and nurses (Lancet Editorial, 2010, 2012). In
2006, which was the last year that China’s Ministry of Health published
statistics on hospital violence, .5500 medical workers were injured
or disabled by patients or their relatives (Xinhua News, 2007; The
New York Times, 2010). The dramatic marketisation of the public
healthcare system is considered to be a major reason for the chaos
and violence (Liebman, 2013). Under such circumstances, fertility care
providers are not safe either.
Most medical disputes in China are caused not by medical malpractice
but by providers’ negligent attitude, unethical conduct and poor communication with patients (Wang et al., 2012). Since 1996, China’s State
Council and Ministry of Health have advocated patient-centred healthcare to ease the tension between providers and patients and to foster
a harmonious relationship between the two groups. However, from
the perspective of medical care providers, the effect of this campaign is
questionable (Jie, 2012).
Infertility is a growing problem in China. According to statistics
released by the China Population Association, .40 million Chinese
people, 12.5% of the country’s reproductive population, suffer from infertility, and the number is increasing (Xinhua News, 2012). Incomplete
statistics showed that in 2011 alone, .180 000 fresh IVF cycles were
performed in over 200 fertility centres in China. Fertility treatment
is not covered by public or private insurance, and the average cost of
a standard IVF treatment is $4000, which is higher than the annual
family income of many infertile Chinese couples. Nevertheless, current
IVF success rates are still relatively low, especially for older patients.
Because of the immense traditional value of having a baby among
Chinese families, infertile couples endure tremendous familial and
social pressure. With high treatment costs, uncertain treatment
outcomes and significant stress among infertile patients, it is pressing
for fertility care providers to understand patients’ perspectives on
fertility care.
The importance of patient-centred healthcare has been recognized in
other countries, but this approach has often been minimized by healthcare providers (Wensing and Elwyn, 2003; Ham, 2010). van Empel et al.
(2011) performed a large comparative study among physicians and infertile patients in Europe, measuring physicians’ and patients’ preferences
for fertility care using a discrete choice experiment, also known as
choice-based conjoint analysis. Five dimensions were studied, including
pregnancy rate, physicians’ attitude, travel time, information on treatment and physician continuity. They found physicians in Europe underestimated the importance of patient-centredness to patients.
Rating-based conjoint analysis is another popular instrument for eliciting preferences for healthcare service, including fertility care (Ryan, 1999;
Ryan and Farrar, 2000; Palumbo et al., 2011). Various scenarios, each of
which describes a hypothetical service with both desirable and undesirable attributes, are presented to participants to elicit their preferences.
Participants have to make a trade-off between the desirable and undesirable characteristics of these services, which allows researchers to determine the relative importance of the attributes (Novotorova and
Mazzocco, 2008; Ng and Sargeant, 2012).
Prior to the present study, no data were available regarding fertility
care preferences from either patients or care providers in China. Thus,
the primary objective of this pilot study was to determine the relative importance of key attributes of fertility care separately for care providers
and patients, using rating-based conjoint analysis. The secondary objective was to evaluate how patients’ characteristics, such as age, education
level and infertility history, may correlate with patient preferences.
Materials and Methods
Ethics statement
The Institutional Review Board at Huazhong University of Science and Technology, Wuhan City, China, approved this study (No. 20130401). Written
informed consent was obtained from all participants.
Study design
We conducted a conjoint analysis of infertile Chinese patients seeking fertility
treatment as well as fertility care providers (physicians, nurses and interns).
Questionnaires were distributed to participating patients and care providers.
Participants were asked to rate how likely they would be to choose or recommend a hypothetical, but realistic, fertility centre based on the characteristics
described in each scenario.
Definitions of attributes
The centre attributes and levels were identified through a comprehensive literature review (Ryan, 1999, Dancet et al., 2010, 2011; van Empel et al., 2011)
and consultation with clinical experts. Based on the literature and clinicians’
input, potential ranges for each attribute were determined. Each attribute
was assigned two levels that represented the most favourable and the least
favourable conditions. Five attributes were finally selected: (i) success rates
(50 versus 35%) (Chen et al., 2007), the clinical pregnancy rate per embryo
transfer cycle (routinely two to three embryos are transferred in China);
(ii) physicians’ attitude towards patients (friendly, willing to listen and
answer questions from patients versus rude, no patience with either listening
to or answering questions from patients); (iii) distance from home to the fertility centre (home city versus other cities); (iv) physician continuity (the same
physician during the complete treatment cycle versus different physicians);
and (v) type of fertility centre (university-affiliated versus not universityaffiliated). The first attribute represents the treatment effectiveness. The
second and fourth attributes represent patient-centred care. The last attribute is intended to measure the technological level of a fertility centre.
University-affiliated hospitals in China are more likely to have better
medical equipment, better trained and more experienced staff members,
and newer technology that is adopted at a faster rate.
Experimental design
The combination of five attributes with two levels produced 32 (25) possible
scenarios, and it would have been quite a cognitive burden on participants to
rate all 32 profiles using a full factorial design. Instead, an orthogonal and
balanced fractional factorial design was generated, and consequently, only
eight scenarios were needed, which ensured no colinearity among attributes
and independent estimation of the coefficient of each attribute (Xu and Yuan,
2001). The selected design for the study was 100% efficient and optimal
(Kuhfeld, 2005).
Questionnaire
The questionnaire was composed of two sections. For patients, the first
section assessed patients’ socio-demographic characteristics, including age,
714
Cai et al.
education level, family income, and treatment and infertility history. For fertility care providers, the first section asked only about patients’ occupations.
The second section included eight scenarios about a hypothetical fertility
centre (Table I). Participants were asked to rate the likelihood that they
would choose or recommend the fertility centres on a scale of 1 – 9, where
1 means ‘definitely no’, 5 means ‘cannot decide’ and 9 means ‘definitely yes’.
Data collection
The questionnaires were distributed on site to 417 female patients and 83
medical staff (physicians, nurses and interns) at the three fertility centres in
Wuhan City and Fuzhou City in China between February and August,
2013. Patients undergoing assisted reproduction techniques (ART) (e.g.
IVF) as well as non-ART were included.
Statistical analysis
In this conjoint analysis, the participants’ preference was the dependent variable (1 –9) and the attributes were the independent variables. Each attribute
was coded as ‘21’ for the least desirable condition and ‘1’ for the most desirable condition. A linear regression model was used to estimate the association between the attributes and the rating of likelihood of choosing a fertility
centre. Because every participant answered multiple questions, a generalized
estimating equation with a compound symmetry structure was used to adjust
for the correlation between eight conjoint scenarios nested within each participant. The estimated regression coefficients are also called aggregated
‘part-worth’ utilities for the study population.
To compare the contribution of the five attributes, the relative importance
of each attribute was computed in the following steps: (i) subtract the smallest
utility from the largest utility to obtain the range for each attribute; (ii) derive
the total range by calculating the sum of the ranges of all attributes; and (iii)
compute the relative importance value of an attribute by dividing the range
of this attribute by the total range.
To examine the difference in preferences between patients and care providers, interaction terms between a dummy variable (‘patient’ versus ‘care
providers’) and each of five attributes were included in the regression
model. Lack of statistical significance in interaction terms can be interpreted
as no statistically significant difference in preferences between patients and
care providers. To test whether patients visiting university-affiliated fertility
centres may have different preferences from patients visiting non-teaching
centres, a dummy variable representing the status of three fertility centres
(‘teaching’ versus ‘non-teaching’) was also included in the model together
with its interaction terms with five main factors.
To explore the potential heterogeneity in preferences among patients, we
fitted a regression model for each patient separately such that every patient
Table I Example Scenario of the Conjoint Survey of
preferences in fertility care in China.
If one IVF centre has the following characteristics:
Distance to IVF centre:
Home city
Type of IVF centre:
University-affiliated hospital
Continuity of physician:
Same physician during the complete
treatment process
Attitudes towards patients:
Rude, no patience in acquiring information
from patients and answering patients’
questions about treatment
Success rate:
50%
How likely are you to choose this centre for treatment? (1– 9)
had a unique set of regression coefficients or utilities scores. These scores
were used to cluster the patients into different subgroups with relatively
homogeneous preferences using the K-Means method (Hartigan and
Wong, 1979). The optimal number of clusters can be selected as the one
that gives the maximum GnRH-associated protein (gap) statistics (Tibshirani
et al., 2001). To better reveal such heterogeneity, the data along with identified clusters were plotted using the first two principal components of utilities scores. Patients’ demographic information was summarized and
compared according to the identified clusters to identify the factors that
may explain the observed heterogeneity in patients’ preferences. The analysis of variance method was used to test the differences in continuous variables among clusters, and the Pearson chi-square test was used to test the
differences in proportions for categorical variables.
The statistical analyses and plotting graphics were performed using the SAS
9.2 statistical software package (SAS, Inc., Cary, NC, USA) and R statistical
package (www.r-project.org). A P , 0.05 was considered significant.
Results
Participants
Three hundred and eighty-nine patients and 83 fertility care providers
returned the survey forms, giving response rates of 93.3 and 100%, respectively. The data from 78 patients and 1 care provider were
removed because of inconsistent or missing answers to conjoint questions after an initial quality check (i.e. rate all 9’s or all 1’s). One possible
reason may be that some participants, who were not willing to take
surveys, agreed upon our on-site requests out of courtesy. Thus, 311
patients and 82 care providers were used in the final analysis. Among
care providers, 49 (59.8%) were physicians, 27 (32.9%) were nurse practitioners and 6 (7.3%) were interns. Two hundred and ten (67.5%)
patients and 42 (51.2%) providers were from the teaching hospital,
and 101 (32.5%) patients and 40 (48.8%) providers were from the
other two non-teaching centres. The patient characteristics are illustrated in Table II.
Differences in preferences between patients
and fertility care providers
Table III lists the results from conjoint regression analysis for both
patients and fertility care providers. All five attributes were important
to patients (P-value ,0.0001). Taking account of the attributes’ range
presented, patients ranked the attitude of physicians as the most important attribute (importance score 34.3%), success rates as the second most
important attribute (24.8%), followed by distance to fertility centre
(15.4%), physician continuity (13.5%) and type of fertility centre
(12.0%). The four most important attributes considered by care providers (P-value ,0.0001) were success rates (46.8%), attitude of physicians (27.4%), distance to the fertility centre (12.6%) and type of
fertility centre (9.7%). Fertility care providers considered physician continuity during the treatment cycle to be the least important fertility care
component (3.6%). Fertility care providers and patients held similar
views regarding two attributes: travel distance and type of fertility
centre. However, these two groups held different views regarding
three attributes: success rates (P-value ,0.0001), physicians’ attitude
(P-value ¼0.0079) and physician continuity (P-value ,0.0001). The
dummy variable for fertility centre type and its interaction terms were
not significant in the model (data not shown).
715
61 (20.00%)
No
244 (80.00%)
Is husbandc a single child
Yes
69 (22.48%)
No
238 (77.52%)
How do you know of the fertility centre
Friends and relatives
222 (72.31%)
Advertisements
29 (9.45%)
Other Ways
56 (18.24%)
a
There are a few missing values for some variables; therefore the total is not always
n ¼ 311. We computed the percentages and P-values using only the cases with
complete data, and thus, we made an assumption that these missing values are random
and did not impute missing values.
b
1 euro equals 8.28 Chinese Yuan.
c
In China, only legally married couples are permitted fertility treatment in
state-licensed IVF centres.
20.66 (20.85,20.47)
46.8
,0.0001
21.45
1.45
0.24 (0.06, 0.42)
27.4
,0.0001
20.85
0.85
,0.0001
20.79
0.79
34.3
0.32 (0.20, 0.43)
3.6
0.08 (20.05, 0.21)
0.09 (20.04, 0.22)
20.63 (20.85,20.40)
12.6
9.7
,0.0001
0.013
20.11
0.11
13.52
Importance
(% utility range)
24.8
P-values were computed from Z-tests.
Yes
a
109 (35.86%)
Is wifec a single child
35%
50%
195 (64.14%)
No
Success rate
Yes
,0.0001
26 (8.47%)
Previous treatment
21.09
1.09
84 (27.36%)
≥10
Rude, no patience with information
Friendly, patience with information
126 (41.04%)
≥5, ,10
Attitude of physicians
≥2, ,5
,0.0001
71 (23.13%)
20.43
0.43
,2
Different physicians
Same physician
Duration of infertility (years)
P-value
12 (4.01%)
Utility
16 (5.35%)
≥20 000
a
[10 000– 20 000)
............................................................
78 (26.09%)
Patients
73 (24.41%)
[5000–10 000)
Level
[3500–5000)
Attribute
38 (12.71%)
82 (27.42%)
Table III Relative importance of factors for patients and fertility care providers.
,2000
[2000–3500)
Continuity of physician
20 (6.54%)
Family income per month (Chinese Yuanb)
20.30
0.30
Graduate school
70 (22.88%)
124 (40.52%)
12.0
College
,0.0001
Senior high school and professional school
92 (30.07%)
20.38
0.38
Junior high school and below
Not university affiliated
University affiliated
11 (3.57%)
Education of husband
Type of fertility centre
128 (41.56%)
,0.0001
Graduate school
,0.0001
College
4.79
71 (23.05%)
20.39
0.39
98 (31.82%)
Senior high school and professional school
Fertility care providers
Junior high school and below
15.4
52 (17.05%)
,0.0001
Other
Education of wife
,0.0001
99 (32.46%)
4.16
Home maker
20.49
0.49
109 (35.73%)
Not local
Local
45 (14.75%)
Private sector employee
Intercept
Public sector employee
............................................................
Occupation of wife
Distance to IVF centre
31.63 (4.60)
Importance
(% utility range)
Mean (SD) age (years)
P-value
........................................................................................
Utility
Patients (an 5 311),
n (%)
a
Characteristic
Difference (95%
confidence interval)
Table II Descriptive statistics for patient
characteristics.
..........................................................................................................................................................................................................................................................
Patients and clinicians view fertility care differently
716
Figure 1 Cluster plot. The x-axis and y-axis are the first and second
principal components of utility scores (regression coefficients) of all
patients. Cluster 1 represents the patients who rank success rates as
the most important attribute; Cluster 2 represents the patients who
rank distance from clinic, attitude of physician, type of fertility centre
and physician continuity as equally important; Cluster 3 represents
the patients who rank the attitude of physician as the most important
attribute.
Differences in preferences among patients
Figure 1 reveals the heterogeneity in patients’ preferences for fertility
care, and three distinct clusters emerge. Descriptive statistics by the
three clusters are shown in Table IV. The patients of the first cluster
(n ¼ 95), which attached the greatest importance to success rates, had
the longest duration of infertility and most likely had previously failed
attempts. The second cluster of patients (n ¼ 104), who were relatively
highly educated, had more balanced views on fertility care. They ranked
distance, attitude of physician, type of fertility centre, and physician continuity to be approximately equally important. Success rate was considered to be the least important attribute. The patients in the third cluster
(n ¼ 112) rated physician’s attitude as three times more important than
success rate. This cluster had a relatively low level of education, had relatively low family income or were less likely to work in the public sector.
Female patients without siblings focused more on patient-centred care
(clusters 2 and 3), while couples that included a husband without any siblings focused slightly more on treatment success rate (cluster 1). The
P-values for the comparisons in Table IV were all .0.05.
Discussion
This study investigates the preferences of infertile Chinese patients and
their care providers regarding fertility care. It demonstrates that infertile
Chinese patients have noticeably different views from their care providers about the relative importance of five attributes of fertility care.
When searching for fertility care, patients ranked the physicians’ attitude
as the highest priority relative to other attributes, whereas fertility care
providers overvalued treatment effectiveness and underestimated the
importance of physicians’ attitude. The subgroup analysis reveals that infertile patients’ preferences are heterogeneous.
Cai et al.
Various studies have investigated patients’ preferences for fertility care
in western countries (Lass and Brinsden, 2001; Marcus et al., 2005; van
Empel et al., 2011), but very few studies have compared physicians’
and patients’ preferences. Researchers van Empel et al. performed the
first study to compare infertile patients’ preferences with those of physicians using a choice-based conjoint analysis; these authors showed that
both patients and physicians in Europe ranked success rates as the
most important attribute, but patients valued patient-centred care
more than physicians would recommend (van Empel et al., 2011). In
our study, infertile Chinese patients attached the greatest importance
to physicians’ attitudes, and nearly 10% more important than treatment
effectiveness. In contrast, fertility care providers in China considered
treatment effectiveness to be the most important factor in fertility
care. The discrepancy between our study and that of van Empel et al.
(2011) may be attributed to the different social and healthcare systems
of the two regions. It is helpful to interpret our findings in the context
of China’s current healthcare environment.
Since the late 1970s, market-oriented economic reforms have brought
profound changes to every part of society in China, including the healthcare
sector. Most health facilities in China are state-owned, but subsidies
received from the government have been shrinking and have accounted
for merely 10% of these facilities’ total revenues since the early 1990s
(Yipa and Hsiaob, 2009). To survive financially, public health facilities
have to rely on revenues from medical services to cover expenditures.
Excessive testing, unnecessary treatment procedures and the overprescribing of expensive medicines are widespread (Yipa and Hsiaob,
2009; Sun and Wang, 2011). Rapidly rising healthcare costs are a significant financial burden to many Chinese families. Even though health
reforms initiated in 2009 have succeeded in extending healthcare coverage to more than 90% of the population (The New York Times, 2010),
coverage is restricted, in particular for major injury or illness, and many
patients incur high financial risks (Yip and Mahal, 2008; Laurance,
2010). These economic reforms also caused the rise of consumerism
in the health sector. Healthcare providers and patients can be likened
to service providers and customers. While public health facilities have
become more profit-oriented, Chinese patients are becoming more aggressive in demanding a better quality of medical services not only in technical terms and outcomes, but also in terms of humanity; patients expect
more humane interactions, more transparency in treatment and
informed consent, among other essentials (Yip and Mahal, 2008).
It is no surprise that fertility care providers in China emphasize treatment effectiveness. Chinese doctors’ social status and reputations in the
medical field are measured mainly by medical skills and contribution to
scientific research, not by humanistic skills. Even employment and promotion for doctors in public hospitals are contingent upon the number
of scientific articles they publish (Ye and Liu, 2013; Yuan et al., 2013).
Chinese doctors rely more on a doctor-centred approach and consider
it their sole responsibility to plan treatment strategies to achieve the best
health benefits for patients. Patients’ involvement is limited to compliance with doctors’ orders. Chinese medical care providers have a long
history of undervaluing patient-centred care. Most medical workers in
China are public employees, and this personnel system has not been
affected by economic reforms in the healthcare sector (Li and Zhang,
2012). The working style that is commonly present and widely criticized
in the public sector remains unchanged; attitudes and behaviours, such as
indifference to patients’ suffering, patient humiliation, rushed service and
poor communication, persist (Yin, 2005).
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Patients and clinicians view fertility care differently
Table IV Characteristics of patients by three clusters.
Variable
Cluster 1 (n 5 95)a
Cluster 2 (n 5 104)a
Cluster 3 (n 5 112)a
P-valueb
.............................................................................................................................................................................................
Mean utility of
Success rate
1.655
0.344
0.467
Continuity of physician
0.287
0.825
0.183
Type of fertility centre
0.155
0.772
0.194
Attitude of physician
0.639
0.743
1.804
Distance
0.324
1.017
Age (years) (SD)
0.132
31.3 (4.0)
31.8 (5.0)
31.8 (4.7)
0.628
Yes
24 (26.1%)
24 (23.3%)
21 (18.8%)
0.445
No
68 (73.9%)
79 (76.7%)
91 (81.3%)
Yes
15 (16.5%)
24 (23.3%)
22 (19.8%)
No
76 (83.5%)
79 (76.7%)
89 (80.2%)
Yes
63 (69.2%)
62 (61.4%)
70 (62.5%)
No
28 (30.8%)
39 (38.6%)
42 (37.5%)
Yes
39 (42.4%)
32 (31.1%)
39 (34.8%)
No
53 (57.6%)
71 (68.9%)
73 (65.2%)
Husband is a single child
Wife is a single child
0.495
Treated for infertility before
0.475
Duration of infertility . 5 years
0.248
Income higher than 5000 Chinese Yuan per month
Yes
34 (37.8%)
37 (37.4%)
35 (31.8%)
No
56 (62.2%)
62 (62.6%)
75 (68.2%)
Yes
44 (48.4%)
53 (51.0%)
47 (42.3%)
No
47 (51.7%)
51 (49.0%)
64 (57.7%)
Yes
42 (45.7%)
53 (51.0%)
44 (39.3%)
No
50 (54.4%)
51 (49.04%)
68 (60.7%)
0.604
College education for Husband
0.43
College education for Wife
0.225
How knew of fertility center
Internet, ads and other ways
29 (31.5%)
33 (32.0%)
23 (20.5%)
Referred by a friend
63 (68.5%)
70 (68.0%)
89 (79.5%)
Public sector
16 (16.8%)
21 (20.2%)
14 (12.5%)
Private industry
61 (64.2%)
70 (67.3%)
77 (68.8%)
Other
18 (19.0%)
13 (12.5%)
21 (18.8%)
0.105
Employment category
0.435
a
There are a few missing values for some variables; therefore the total n is not always as stated. We computed the percentages and P-values using only the cases with complete data, and thus,
we made an assumption that these missing values are random, and did not impute missing values.
b
Analysis of variance method was used to compute P-values for continuous variables and Chi-square test was used for categorical variables.
In contrast to their care providers, infertile Chinese patients valued
the patient-centredness of care the most. Although infertility is not a
life-threatening and emergent health issue, women undergoing fertility
treatment are generally regarded as a group at high risk for anxiety and
depression due to their infertility and the uncertainties of treatment
(Demyttenaere et al., 1998; Smeenk et al., 2001). Infertile Chinese
couples may endure increasing familial and peer pressures after years
of infertility. To qualify to practice medicine, China’s Ministry of Health
requires doctors to graduate from an accredited medical school and to
be licensed to practice after passing a national qualification examination.
Patients generally have poor knowledge of medicine. Because of this information asymmetry, patients most likely judge the competence and reliability of their care providers based on the attention they receive and the
way in which doctors interact and communicate with them (Yin, 2005).
Physician continuity is a critical component of patient-centred care.
Patients in Europe are more satisfied when they are able to visit the
same doctor (Guthrie et al., 2008; Uijen et al., 2012). The patients in
our study also desired such service. The reason may be that physicians
accumulate knowledge regarding the patients’ medical conditions, and
therefore, patients can place more trust in them. However, fertility
718
care providers in our study significantly downplayed the importance of
this attribute. This finding reflects the reality that top-ranking fertility
centres in China are treating a high volume of patients annually, but the
size of staff is small. Therefore, it is not practical, from the point of
view of providers, for every patient to have the same physician be responsible for her complete treatment procedure. In today’s increasingly competitive market for fertility treatment, fertility centres with such capacity
may incorporate this attribute into individualized patient-centred care
plans to optimize the quality of service.
It is known that different patients make different choices in different
situations (Victoor et al., 2012). Our subgroup analysis identified three
clusters of patients with different preferences and priorities. While
some patients valued treatment effectiveness the most, others overwhelmingly emphasized physicians’ attitudes, and still others had more
balanced preferences. Some patient characteristics could potentially
explain such heterogeneity. For instance, patients with lower levels of education and less family income tended to emphasize physician’s attitude. In
contrast, patients with higher levels of education, more family income or
those who worked in the public sector had more concerns regarding
either success rate or other attributes, such as distance to an IVF
centre. The reason may be that patients with higher social status have
better communication with their care providers. It is interesting to note
that the effect of the level of education on patients’ preferences found in
our study is consistent with the findings of a previous study (van Empel
et al., 2011). Our study also found that patients with previous failed IVF
attempts and longer infertility duration are more likely to favour treatment
effectiveness the most. We also examined how the one-child policy may
affect patients’ preferences. Several trends suggest that couples in which
the husband is a single child focus more on success rates, which reflects
traditional Chinese family values. However, when a female patient is a
single child, she is more likely to value the patient-centredness of care.
The present study has some limitations. First, two levels for each of five
design factors were chosen (25) because a fractional factorial design with
eight runs is optimal. However, such design, although adequate for a
pilot study, may not fully capture the characteristics of realistic fertility
centres. We also chose rating-based conjoint analysis because it is relatively simple to design and implement, but this method is shown to be inferior
to choice-based conjoint analysis in terms of predictive accuracy (Karniouchina et al., 2009). Second, the patient sample size is relatively small. The
study is underpowered to establish any statistically significant trend in heterogeneity of patients’ preferences, although the magnitudes of some differences are noticeable. Third, previous diagnostic and treatment
information for participants was not collected because of anonymity,
and some of these variables may explain some of the heterogeneity in
patients’ preferences. Fourth, the sample size for fertility care providers
is small, and no variables describing care providers’ characteristics were
collected. The current study could not explore further the possible heterogeneity in preferences among care providers. Finally, only three centres
from two cities in moderately economically developed regions agreed to
participate in this study and may not be representative of the more than
200 centres in China. Variation in the composition of the study population
may affect estimates of the relative importance of attributes. For instance,
centres in economically advanced large cities may have more patients with
high-level education and high income, but centres in underdeveloped
regions tend to have more patients with low education levels and less
income. A large study with more centres from well-represented geographic regions is necessary to validate the conclusions of this study.
Cai et al.
The current study reveals the noticeably different views between infertile Chinese patients and their care providers on the relative importance of treatment effectiveness and physicians’ attitudes in fertility
care. To bridge the gap, care providers should treat each patient as a
unique individual and not simply a medical case. Doctors should have
more patience in listening to patients about their concerns, disclose
more information on diagnosis, share more information on the pros
and cons of different treatment options and give honest details about
prognosis (Yang et al., 2010). A good provider– patient relationship
could win more tolerance from patients for occasional lapses and
could result in fewer malpractice actions (Lings et al., 2003). New instruments for measuring patient-centredness may be implemented by fertility care centres in China (van Empel et al., 2010). Such information, along
with centres’ pregnancy rates, should be made publicly available to
patients. However, endeavours by care providers alone are far from sufficient. Conflicts between providers and patients are only part of the
larger picture of social conflict brought by transformations that have
been underway in Chinese society since the beginning of marketoriented reforms in the 1970s (Tang et al., 2008). In general, healthcare
providers in China have a much heavier workload with much lower pay
compared with their counterparts in western countries (Li and Xie,
2013). Patient-centredness in healthcare was promoted by administrative
power. In the events of provider–patient conflicts, the public media always
demonized healthcare providers. Such unfair treatment could provoke
‘revolt’ from medical workers, resulting in an exodus from medical
careers and a shortage of healthcare professionals (Jie, 2012).
China has 20% of the world’s population and the second largest
economy, but its total expenditure on healthcare is only 4.3% of gross domestic product. To reduce profit-seeking activities by public hospitals,
the government should increase funding for public health facilities
(Wang et al., 2012). In addition, considering the fact that the one-child
policy is still strictly implemented in China and any violation will incur a
large fine, either some subsidies from the government to low-income infertile couples on fertility treatment or having treatment covered under a
national health insurance scheme may be a more effective solution to the
tension between patients and fertility care providers.
In summary, Chinese fertility care providers need to understand the
large gap between their understanding of what constitutes ideal fertility
care and patients’ perspectives and should strive to improve the
tenuous provider–patient relationship by treating patients more empathetically, improving communication skills, respecting patients’ right
to be informed about treatment options and prognosis, and obtaining
more patient involvement.
Authors’ roles
Q.F.C.: Substantial contributions to study conception and design, draft
development, article revision and final approval of the version to be published. F.W.: Substantial contributions to study design, data analysis and
interpretation, manuscript draft development and final approval of the
version to be published. X.Y.D.: Substantial contributions to data acquisition, article revision for important intellectual content and final approval
of the version to be published. X.H.L., J.Z., R.W., L.C.J.: Substantial contributions to data acquisition, article revision and final approval of the
version to be published. H.W.Z.: Substantial contributions to study conception, data acquisition, article revision for important intellectual
content and final approval of the version to be published.
Patients and clinicians view fertility care differently
Funding
There is no funding support relevant to the subject of this article.
Conflict of interest
All authors report no conflict of interest in relation to this work.
References
Chen SL, Yin MN, Sun L, Li H, Chen X, Song HD, He JX, Zhu L, Xing FQ.
Clinical application of gonadotropin-releasing hormone antagonist in
Chinese women undergoing controlled ovarian hyperstimulation for in
vitro fertilization and embryo transfer. Nan Fang Yi Ke Da Xue Xue Bao
2007;27:588 – 590.
Dancet EA, Nelen WL, Sermeus W, De Leeuw L, Kremer JA, D’Hooghe TM.
The patients’ perspective on fertility care: a systematic review. Hum Reprod
Update 2010;16:467 – 487.
Dancet EA, Van Empel IW, Rober P, Nelen WL, Kremer JA, D’Hooghe TM.
Patient-centred infertility care: a qualitative study to listen to the patient’s
voice. Hum Reprod 2011;26:827– 833.
Demyttenaere K, Bonte L, Gheldof M, Vervaeke M, Meuleman C,
Vanderschuerem D, D’Hooghe T. Coping style and depression level
influence outcome in in vitro fertilization. Fertil Steril 1998;69:1026– 1033.
Guthrie B, Saultz JW, Freeman GK, Haggerty JL. Continuity of care matters.
BMJ 2008;337:a867.
Ham C. The coalition government’s plans for the NHS in England. BMJ 2010;
341:c3790.
Hartigan JA, Wong MA. A K-means clustering algorithm. Appl Stat 1979;
28:100– 108.
Jie L. New generations of Chinese doctors face crisis. Lancet 2012;379:1878.
Karniouchina EV, Moore WL, van der Rhee B, Verma R. Issues in the use of
ratings-based versus choice-based conjoint analysis in operations
management research. Eur J Oper Res 2009;197:340– 348.
Kuhfeld WF. 2005. Marketing Research Methods in SAS: Experimental Design,
Choice, Conjoint, and Graphical Techniques. Cary, NC: SAS Institute
(Online). Available at: www://support.-sas.com/techsup/technote/
ts722title.pdf (1 May 2013, date last accessed).
Lass A, Brinsden P. How do patients choose private in vitro fertilization
treatment? A customer survey in a tertiary fertility center in the United
Kingdom. Fertil Steril 2001;75:893 – 897.
Laurance J. A Chinese puzzle. Lancet 2010;376:1819.
Li Q, Xie P. Outpatient workload in China. Lancet 2013;381:1983– 1984.
Li H, Zhang H. Ways out of the crisis behind Bribegate for Chinese doctors.
Lancet 2012;379:e16.
Liebman BL. Malpractice mobs: medical dispute resolution in China.
Columbia Law Rev 2013;113:181 – 264.
Lings P, Evans P, Seamark D, Seamark C, Sweeney K, Dixon M, Gray DP. The
doctor-patient relationship in US primary care. J R Soc Med 2003;
96:180– 184.
Marcus HJ, Marcus DM, Marcus SF. How do infertile couples choose their IVF
centers? An Internet-based survey. Fertil Steril 2005;83:779 –781.
Ng V, Sargeant JM. A quantitative and novel approach to the prioritization of
zoonotic diseases in North America: a public perspective. PLoS One 2012;
7:e48519.
Novotorova NK, Mazzocco MA. Consumer preferences and trade-offs
for locally grown and genetically modified apples: a conjoint analysis
approach. Int Food Agribusiness Manage Rev 2008;11:31 – 53.
Palumbo A, De La Fuente P, Rodrı́guez M, Sánchez F, Martı́nez-Salazar J,
Muñoz M, Marqueta J, Hernández J, Espallardo O, Polanco C et al.
Willingness to pay and conjoint analysis to determine women’s
719
preferences for ovarian stimulating hormones in the treatment of
infertility in Spain. Hum Reprod 2011;26:1790 – 1798.
Ryan M. Using conjoint analysis to take account of patient preferences and go
beyond health outcomes: an application to in vitro fertilisation. Soc Sci Med
1999;48:535 – 546.
Ryan M, Farrar S. Using conjoint analysis to elicit preferences for health care.
BMJ 2000;320:1530 – 1533.
Smeenk JM, Verhaak CM, Eugster A, van Minnen A, Zielhuis GA, Braat DD.
The effect of anxiety and depression on the outcome of in-vitro
fertilization. Hum Reprod 2001;16:1420– 1423.
Sun S, Wang W. Violence against Chinese health-care workers. Lancet 2011;
377:1747.
Tang S, Meng Q, Chen L, Bekedam H, Evans T, Whitehead M. Tackling the
challenges to health equity in China. Lancet 2008;372:1493 – 1501.
The Lancet. Chinese doctors are under threat. Lancet 2010;376:657.
The Lancet. Ending violence against doctors in China. Lancet 2012;
379:1764.
The New York Times. Chinese Hospitals Are Battlegrounds of Discontent.
http://www.nytimes.com/2010/08/12/world/asia/12hospital.html?_r=0
(16 October 2013, date last accessed).
Tibshirani R, Walther G, Hastie T. Estimating the number of data clusters via
the Gap statistic. J R Stat Soc B 2001;63:411 – 423.
Uijen AA, Schers HJ, Schellevis FG, van den Bosch WJ. How unique is
continuity of care? A review of continuity and related concepts. Fam
Pract 2012;29:264 – 271.
van Empel IW, Aarts JW, Cohlen BJ, Huppelschoten DA, Laven JS,
Nelen WL, Kremer JA. Measuring patient-centredness, the neglected
outcome in fertility care: a random multicentre validation study. Hum
Reprod 2010;25:2516 – 2526.
van Empel IW, Dancet EA, Koolman XH, Nelen WL, Stolk EA, Sermeus W,
D’Hooghe TM, Kremer JA. Physicians underestimate the importance of
patient-centredness to patients: a discrete choice experiment in fertility
care. Hum Reprod 2011;26:584 – 593.
Victoor A, Delnoij DM, Friele RD, Rademakers JJ. Determinants of patient
choice of healthcare providers: a scoping review. BMC Health Serv Res
2012;12:272.
Wang XQ, Wang XT, Zheng JJ. How to end violence against doctors in
China. Lancet 2012;380:647 – 648.
Wensing M, Elwyn G. Methods for incorporating patients’ views in health
care. BMJ 2003;326:877 –879.
Xinhua news. More than 5,500 medical personnel hurt in medical brawls
last year. http://news.xinhuanet.com/english/2007 –04/18/content_
5990621.htm (22 January 2014, date last accessed).
Xinhua News. China Focus: increasing infertility concerns Chinese couples.
http://news.xinhuanet.com/english/health/2012–12/18/c_132048349.htm
(14 October 2013, date last accessed).
Xu G, Yuan Y. Conjoint analysis in pharmaceutical marketing research.
Quirk’s Mark Res Rev. http://www.quirks.com/articles/a2001/20010
602.aspx?searchID=901941472&sort=9 (7 February 2014, date last
accessed) 2001.
Yang Y, Zhao JC, Zou YP, Yan LN. Facing up to the threat in China. Lancet
2010;376:1823.
Ye B, Liu AH. Inadequate evaluation of medical doctors in China. Lancet 2013;
381:1984.
Yin D. Law-regulated practice and evidence-based self-protection. Chinese J
Evidence-Based Med 2005;5:1– 2.
Yip W, Mahal A. The health care systems of China and India: performance
and future challenges. Health Aff 2008;27:921– 932.
Yipa W, Hsiaob W. China’s health care reform: a tentative assessment. China
Econ Rev 2009;20:613 – 619.
Yuan HF, Xu WD, Hu HY. Young Chinese doctors and the pressure of
publication. Lancet 2013;38:e4.