Context In neonatal intensive care, parents make important
clinical management decisions in conjunction with health care
professionals. Yet little information is available on whether
preferences of health care professionals and parents for the resulting
health outcomes differ.
Objective To measure and compare preferences for selected health
states from the perspectives of health care professionals (ie,
neonatologists and neonatal nurses), parents of extremely
low-birth-weight (ELBW) or normal birth-weight infants, and adolescents
who were either ELBW or normal birth-weight infants.
Design Cross-sectional cohort study.
Setting and Participants A total of 742 participants were
recruited and interviewed between 1993 and 1995, including 100
neonatologists from hospitals throughout Canada; 103 neonatal nurses
from 3 regional neonatal intensive care units; 264 adolescents (aged
12-16 years), including 140 who were ELBW infants and 124
sociodemographically matched term controls; and 275 parents of the
recruited adolescents.
Main Outcome Measure Preferences (utilities) for 4 to 5
hypothetical health states of children were obtained by direct
interviews using the standard gamble method.
Results Overall, neonatologists and nurses had similar preferences
for the 5 health states, and a similar proportion rated some health
states as worse than death (59% of neonatologists and 68% of
nurses;P=.20). Health care professionals
rated the health states lower than did parents of ELBW and term infants
(P<.001). Overall, 64% of health care professionals and
45% of parents rated 1 or more health states to be worse than death
(P<.001). Differences in mean utility scores between health
care professionals and parents and adolescent respondents were most
pronounced for the 2 most severely disabled health states
(P<.001).
Conclusions When asked to rate the health-related quality of life
for the hypothetical conditions of children, health care professionals
tend to provide lower utility scores than do adolescents and their
parents. These findings have implications for decision making in the
neonatal intensive care unit.
With recent
improvements in survival of infants of borderline viability, the issue
of whether to treat such infants actively continues to be
debated.1-9 Both the Canadian Paediatric
Society10 and the American Academy of
Pediatrics11 have issued statements encouraging the
involvement of parents in decision making, and in fact, to support the
primacy of parental decisions for all infants at the threshold of
viability. These statements were developed by health professionals
using data on the mortality and morbidity of infants at each
gestational age, without explicit consideration of the values and
preferences of parents or members of society.
In critical care situations involving newborns, parents often assume
responsibility for making important life-sustaining decisions, along
with neonatologists. Obviously, the preferences of newborns are
unknown, and it is assumed that parents will take the best interests of
the infant and the family
into consideration. But it is not clear whether
parents are influenced by health care professionals, and if they are,
to what extent those decisions are based on the preferences of the very
individuals on whom they rely for information and advice:
neonatologists, neonatal nurses, and their personal physicians. Thus,
it is important to determine whether the preferences of medical
personnel are similar to or differ systematically from patients who
were extremely low-birth-weight (ELBW) infants or their parents and to
measure the direction of these differences, if any.
The principle underlying the measurement of preferences is to allow
individuals to provide their preferences for alternative health
outcomes. Values and utilities are the 2 types of cardinal
preferences.12,13 Values are preferences measured under
conditions of certainty. Conversely, utilities are preferences measured
under conditions of uncertainty. Torrance et al14 suggest
that utility is the appropriate construct for use in health problems
involving uncertainty and should be used as the primary measure of
health-related quality of life (HRQL).
This study seeks to measure and to compare preferences (mean utility
scores) for certain hypothetical health states from the perspective of
neonatologists and neonatal nurses (health care professionals [HPs])
and to compare the utilities of HPs with those obtained from parents of
ELBW and term infants15 and from adolescents who were ELBW
or term infants.16 A secondary objective is to explore
correlates of the above utilities, ie, are there any physician or
parent characteristics that correlate with their preferences for
selected health states? We hypothesized that utility scores obtained
from physicians would be systematically different from those obtained
from neonatal nurses and that the utility scores from HPs would
differ systematically from those obtained from parents and from the
adolescents themselves. A secondary hypothesis was that utility scores
provided by physicians, nurses, and parents would not be significantly
correlated with demographic variables.
A large national sample of physicians working in level 3 (tertiary
care) neonatal referral centers throughout Canada were recruited for
face-to-face interviews from the Canadian Paediatric Society Meeting,
Montreal, Quebec, June 1995 (n=53), 2 neonatal centers
in Winnipeg, Manitoba (n=7), and in 5 neonatal centers
in Ontario (n=27). This sample provided 87
neonatologists or 64% of the neonatologists working in Canadian
tertiary care centers, with representation from all provinces except
Newfoundland and Saskatchewan. An additional 13 physicians were
recruited from level 2 plus units (with capabilities of providing
short-term neonatal intensive care) in Ontario, for a total of 100
physicians. There were no refusals.
A total of 103 neonatal nurses were recruited from 3 tertiary care
centers, with 69 of them working in either an inborn or outborn center
in Toronto and 34 working in a combined inborn and outborn center in
Hamilton, Ontario, representing the 3 types of neonatal intensive care
units in Canada. A list of all nurses was obtained from the respective
units and numbers were assigned from a random number table. The refusal
rate was 18%. The most frequent reason for declining participation was
busy patient assignments during the interview schedule. The HPs were
interviewed between March and September 1995.
Adolescents who were ELBW infants, born between 1977 and 1982 in a
geographically defined region in central-west Ontario, were followed up
longitudinally from birth.16,17 They were matched for
sociodemographic factors with a control group of children who were born
at term and weighed more than 2500 g at birth. The control children
were recruited when they were 8 years old.16,17 Of the 314
adolescents who were asked to participate in the survey, 264 (84%)
were interviewed, 140 (83%) of 169 adolescents who had been ELBW
infants were interviewed, and 124 (86%) of 145 subjects in the control
group were interviewed.16 Both cohorts were between the
ages of 12 and 16 years. Preferences from these 2 groups have been
previously compared.16
Of the parents of adolescents who had been ELBW infants, 149 (88%) of
169 agreed to be interviewed, and 126 (87%) of the 145 parents of
children in the control group agreed to be
interviewed.15-17 Parental preferences have been published
in abstract form.15 The interviews of the children and
their parents took place on the same day during 1993 and 1994.
Measurement of HRQL (Utilities)
We followed the protocol used in our previous study as closely as
possible.16 Respondents were asked to provide utility
scores for 5 hypothetical health states (described below) using the
standard gamble, assisted by a chance board.13,18 Given
that standard gamble responses include the risk preferences of
respondents and that risk is intrinsic to clinical decision making for
infants who require neonatal intensive care, the standard gamble is an
appropriate technique for preference measurement in this context. The
reliability of the utility measures was not assessed within the study.
Published evidence indicates acceptable levels of reliability but a
lack of precision at the level of individual scores.18 The
instrument was extensively pilot tested on nonstudy subjects.
Hypothetical Health States
Five hypothetical health states were preselected from those reported by
ELBW survivors when they were 8 years old19,20 as
methodologic reference states for assessment by HPs. Four of these
health states were common to a previous study.16 A fifth
health state was selected from the same source for HPs, while parents
were asked to consider the fifth health state as if it were their
child's health state. The health-state descriptions were written in
the format of
the Mark 2 version of the Health Utilities
Index.21,22 Each hypothetical health state was given a
unisex name (Jamie, Chris, Pat, Sandy, and Alex) (Table
1). The HPs and parents were asked to
imagine themselves living in each of the above states of health for the
next 60 years. This time frame was considered the duration of the
projected life expectancy of the adolescents in our previous
study.16
Each parent and HP was interviewed in a private room by a
trained, professional, nonmedical interviewer. Parents and HPs were
asked to provide preference measurements for the hypothetical health
states using the chance board. At the end of the study, the
interviewers evaluated the respondent's comprehension and
concentration on the tasks assigned, using a 5-point Likert scale. The
respondents also were asked whether they encountered any difficulties
and whether the measurement tasks allowed them to represent their
opinions. These data were subsequently analyzed to assess the quality
of interviews. The entire interview took an hour.
Demographic information was obtained from the HP and parent respondents
by a self-administered questionnaire that collected information about
each respondent's age, sex, marital status, number of children,
education, professional experience, and participation in religious
services. Information on prior experience with children with
disabilities (personal and/or professional) was obtained from HPs only.
These data were used in the analyses to test whether there were any
correlations between these variables and the preference scores for
health states.
Consent and Ethics Approval
Written informed consent was obtained from all respondents who
agreed to participate in the study. The study was approved by the
ethics review board of the Hamilton Health Sciences Corporation,
Hamilton, Ontario.
Sample Size and Statistical Testing Power. Based on variability of previously measured utility scores, a
conventional difference of 0.10 utility units (10% of full-scale) was
considered to represent a clinically important difference between
groups for use in power analyses.12,13 A sample of 100
physicians and 100 nurses provides greater than 80% power on 2-tailed
tests of significance to detect a difference of at least 0.10 utility
units between groups.
Standardization of Preference Scales. Preference scores were standardized across raters to a scale, in
which perfect health equals 1.0 and being dead equals 0, to ensure
comparability when aggregating results across individuals. Briefly, in
cases in which the rater considered the health state to be worse than
death, the negative utility for the state was determined directly from
the standard gamble.18 The negative utilities were then
rescaled to a −1.0 to 0.0 interval using the nonlinear transformation,
y=x/(1 − x), first
described by Patrick et al.23 Positive scores were not
transformed. The utility scores have interval-scale properties.
We used the t test to analyze equality of mean utility scores
between nurses and pediatricians and between HPs and parents. This test
was also used for comparison of mean scores among demographic groups.
The variance ratio test was used to test homogeneity of variance
between mean utility scores, and 2-way analysis of variance was used to
test for relationships between utility scores and demographic
variables. Pearson χ2 with Yates correction for
continuity was used to test for differences in proportions of nurses
and pediatricians who considered states to be worse than death.
Demographic Characteristics
of Respondents
The demographic information on HPs and parents is shown in Table
2. The nurses were younger than the
neonatologists, all were female, and a smaller proportion were married
or had children. A significantly lower proportion of the physicians
were born in Canada, the duration from graduation was longer than for
nurses, and the majority were working full-time. Although a higher
proportion of pediatricians than nurses reported professional
experience with disabled patients, there were no differences in the
proportion with personal experience with such
persons. There were no differences in the
proportion who participated in religious activities such as going to a
church or synagogue and participating in other religious activities.
The academic rank of the physicians was professor, 17%; associate
professor, 34%; assistant professor, 39%; and other, 10%. Nursing
qualifications were nursing diploma, 75%; bachelor of science degree
in nursing, 22%; postgraduate, 1%; and other, 2%.
The demographic variables of parents of ELBW and control infants are
presented as combined data to represent consumers. The mean age of
parents was 42 years, and 71% were born in Canada. The proportion of
married persons was 88%, and the respondents were primarily mothers
(89%). Maternal education was as follows: less than high school, 26%;
high school diploma, 27%; and postsecondary and college or university,
47%. There were no differences between HPs and parents in the
proportion of those who participated in religious activities.
The mean (SD) age of the adolescents at the time of the interview was
14.2 (1.6) years.16 All children were attending school.
Comparison of Preference Scores for Hypothetical Health States
Physicians and Nurses. Descriptive statistics of mean utility scores on the chance board
for the 5 hypothetical scenarios provided by physicians and nurses are
presented in Table 3. There were no
statistically significant differences in the mean or median scores
between physicians and nurses, except for health state for Alex. For
this reason, data for physicians and nurses are combined for the rest
of the analyses. Mean and median utility scores for Pat and Sandy were
equivalent to death or lower. There was considerable variability in the
scores provided by both groups. Overall, 59% of physicians and 68% of
nurses rated 1 or more hypothetical health states to be worse than
death (P=.20).
HPs and Parents. Four of the 5 hypothetical health states (Alex excluded)
rated by HPs were also rated by parents and adolescents in our previous
studies.15,16 Because there were no significant differences
in the mean utility scores for the hypothetical health states between
physician and nurses and between the 2 groups of parents,15
combined data for parents and HPs are presented in Table
4.
Overall, HPs rated the hypothetical health states lower than parents
(P<.001). There were no differences between HPs and parents
in the mild to moderately disabled hypothetical health states (Jamie
and Chris). However, HPs rated the 2 most severely disabled health
states significantly lower than parents (mean [SD] utility scores for
Pat: HPs, −0.05 [0.53]; parents, 0.20 [0.51]; P<.001;
for Sandy: HPs, 0.05 [0.50]; parents 0.23 [0.51];
P<.001) (Table 4).
Figure 1 shows the comparison of
mean utility scores and 95% confidence intervals (CIs) between parents
and HPs. As can be seen, the mean utility scores
were similar for Jamie and Chris. However, the mean utility score
provided by HPs for Pat was below 0 (or worse than death), and the CIs
were below 0 for both Pat and Sandy. Overall, 64% of HPs and 45% of
parents rated 1 or more health states to be worse than death
(P<.001).
HPs and Adolescents. Data from ELBW and Control Adolescents were combined for purposes of
comparisons with HPs (Table 4). The mean utility scores of adolescents
for the 2 more morbid health states (Pat and Sandy) were significantly
higher than the mean utility scores of HPs. However, the mean utility
scores of adolescents were significantly lower than those of parents
and HPs for health states with milder impairments (Jamie and Chris).
Overall, 50% of adolescents rated at least 1 of the health states as
worse than death, significantly fewer than the health professionals
(P=.004).
Association Between Demographic Variables and Utility Scores
We did not find interactions between the demographic factors of
HP and individual health states. The following demographic variables
were not associated with preference scores: age of respondent, marital
status, country of birth (Canada or other), participation in religious
services, and personal and professional experience with children with
disabilities. Female HPs (P=.003) and those
who were childless (P=.04) tended to assign
lower scores to the health states. The effect of sex on preference
scores was also significant among physicians, with women providing
lower ratings than men (P=.01). However, the
Pearson correlation between utility scores and statistically
significant demographic variables showed that very little of the total
variability in utility scores was explained by these factors,
r less than 10%.
The following demographic variables of parents were associated with
lower scores: female sex (P=.03); age older
than 40 years (P=.007); and country of birth
other than Canada (P<.001). Parental educational background,
income, marital and employment status, and participation in religious
services were not associated with preference scores.
Current financial constraints on health care resources make it
imperative to define better both health care outcomes achieved and the
costs of achieving those outcomes. It is also necessary to obtain
information on the relative desirability of outcomes. One way to do
this is to measure preferences (or utilities) of health state outcomes.
The greater the gain in utility achieved by a program, all other things
being equal, the more deserving the program becomes for consideration
for implementation.
However, it is unclear whose preferences for health states
should be considered in program evaluation and resource allocation
decisions. The possibilities are many—people such as consumers
(patients themselves, or their parents in the case of children), health
care providers (physicians, nurses, and allied HPs), or members of
society (community members, taxpayers). If the preferences of these
groups are similar, then for programmatic decisions (as opposed to
patient management), it may not matter whose preferences are used. If,
however, preferences differ systematically, a number of implications
follow. First, it is important to document descriptively any
differences that exist. Second, the results of program evaluations such
as cost-utility analyses may depend on whose preferences are
considered. Third, systematic differences in preferences may affect
decisions concerning patient care. Thus, the determination of whether
significant differences exist is an important step in formulating
strategies to align
better the practice of neonatal intensive care
with the preferences of interested parties. Such comparisons have not
been made before in the pediatric population. Our research is directed
toward these issues.
First, we measured preferences for hypothetical health states from the
perspective of physicians and neonatal nurses. Our concern was that if
the preferences of physicians and nurses differed, this may contribute
to some conflict in the formulation and execution of treatment
policies. Contrary to the literature24 and the prevailing
perception, no statistically significant differences were observed
between the HRQL ratings provided by physicians and nurses. On the
whole, HRQL ratings of HPs were consistent with the severity of the
health states. Both physicians and nurses reported the 2 most disabled
health states as having mean scores near 0 or below. This consistency
in valuation of HRQL by health care providers working as a team in the
neonatal intensive care unit is reassuring.
Comparison of preferences for the same health states obtained from HPs
and parents revealed that although the overall HRQL scores provided by
HPs were lower, differences in mean scores were most pronounced for the
2 most morbid health states (Pat and Sandy). It appears that HPs and
parents view the mild to moderately disabled health states similarly,
but parents were more accepting of the severely disabled health states
than HPs. Our findings support the observation that HPs tend to provide
lower HRQL scores for patients than other respondents.25,26
We have shown previously that as a group, adolescents who were ELBW or
term infants rated the same hypothetical health states lower than their
parents.27 However, there appears to be more consistency
between adolescents and their parents for the severely disabled health
states than between adolescents and HPs. This finding lends support to
the concept that parents are the most appropriate agents when making
decisions on behalf of their infants in the neonatal intensive care
unit.
The literature on preferences of health care providers and
consumers in the pediatric population is sparse.18,28-30
Our findings of differences in valuation between HPs and patients are
in accord with studies on adult subjects. Churchill et al26
compared mean visual analog scale value scores for health states of
adult patients with end-stage renal disease as reported by patients,
physicians, and nurses. The trend appeared for patients to value their
own health conditions more highly than did nurses and physicians. In
another study, patients with cancer were reported to be more willing to
opt for radical treatment with minimal chance of benefit than subjects
without cancer, including HPs.31 Currently, we have limited
knowledge of the processes by which individuals arrive at these
judgments, but it appears that the perceived value of life changes
appreciably when a person has to cope with a disability or when faced
with a life-threatening situation.
This is the first time, to our knowledge, that comparisons of
preferences (utilities) have been made between HPs, health care
consumers, and members of the community in a pediatric context. We have
shown that adolescents, parents of ELBW infants, and parents from the
community provide higher ratings for the HRQL of severely disabled
children than do HPs. Although a significant proportion of HPs are also
parents themselves, the discrepancy in valuation between them and other
respondents may reflect their clinical bias. It is possible that this
might affect the choice of management options offered to parents in the
neonatal intensive care unit.
The findings of this study are of potential practical as well as
conceptual importance, particularly with the current shift to
patient-centered care in all areas of medical care.32 Of
the various models of the patient-physician relationship, Emanuel and
Emanuel33 argue that the "deliberative model," in which
the patient's perspective is incorporated when determining the
preferred course of action, embodies the optimal patient-physician
interaction. The results of this study could be used to make HPs
and parents aware of the differences in preferences within and between
groups. They further underscore the need for deliberations at an
individual level in counseling future parents facing complex decisions
about neonatal intensive care. The regional nature of our adolescent
and parent subjects, the large sample size of the respondents, and the
national input from neonatologists are strengths of our study findings,
making them generalizable to the Canadian population. Whether these
results are generalizable to other populations remains to be
studied.34
1.Stahlman MT. Ethical issues in the
nursery: priorities versus limits.
J Pediatr.1990;116:167-170.Google Scholar 2.Silverman WA. Overtreatment of neonates? a personal
retrospective.
Pediatrics.1992;90:971-976.Google Scholar 3.Harrison H. The principles for family-centered neonatal
care.
Pediatrics.1993;92:643-650.Google Scholar 4.Doyal L, Wilsher D. Towards guidelines for withholding
and withdrawal of life prolonging treatment in neonatal medicine.
Arch Dis Child.1994;70:F66-F70.Google Scholar 5.Lantos JD, Tyson JE, Allen A.
et al. Withholding and
withdrawing life sustaining treatment in neonatal intensive care:
issues for the 1990s.
Arch Dis Child.1994;71:F218-F223.Google Scholar 6.de Leeuw R, de Beaufort AJ, de Kleine MJK, van Harrewijn K, Kollée LAA. Foregoing intensive care treatment in newborn
infants with extremely poor prognoses: a study in four neonatal
intensive care units in the Netherlands.
J Pediatr.1996;129:661-666.Google Scholar 7.Wall SN, Partridge JC. Death in the intensive care
nursery: physician practice of withdrawing and
withholding life support.
Pediatrics.1997;99:64-70.Google Scholar 8.van der Heide A, van der Maas PJ, van der Wal G, Kollée LAA, de Leeuw R, Holl RA. The role of parents in
end-of-life decisions in neonatology: physicians' views and practices.
Pediatrics.1998;101:413-418.Google Scholar 9.Doron MW, Veness-Meehan KA, Margolis LH, Holoman EM, Stiles AD. Delivery room resuscitation decisions for extremely
premature infants.
Pediatrics.1998;102:574-582.Google Scholar 10.Fetus and Newborn Committee, Canadian Paediatric
Society, Maternal-Fetal Medicine Committee, and Society of
Obstetricians and Gynaecologists of Canada. Management of the woman
with threatened birth of an infant of extremely low gestational age.
CMAJ.1994;151:547-553.Google Scholar 11.American Academy of Pediatrics, Committee on Fetus and
Newborn, American College of Obstetricians and Gynecologists, and Committee on Obstetric Practice. Perinatal care at the threshold of
viability.
Pediatrics.1995;96:974-976.Google Scholar 12.Torrance GW, Boyle MH, Horwood SP. Application of
multi-attribute utility theory to measure social preferences for health
states.
Operations Res.1982;30:1042-1069.Google Scholar 13.Furlong W, Feeny D, Torrance GW, Barr R, Horsman J. Guide to Design and Development of Health-State Utility
Instrumentation. Hamilton, Ontario: Centre for Health Economics and
Policy Analysis, McMaster University; 1990. Working Paper Series 90-9.
14.Torrance GW, Furlong W, Feeny D, Boyle M. Multi-attribute preference functions: Health Utilities Index.
PharmacoEconomics.1995;7:503-520.Google Scholar 15.Saigal S, Furlong WJ, Feeny DH, Rosenbaum PL. Parents' perceptions of the health-related quality of life of teenage
extremely low birthweight and control children [abstract].
Pediatr Res.1995;37(part 2):40a.Google Scholar 16.Saigal S, Feeny D, Rosenbaum P, Furlong W, Burrows E, Stoskopf B. Self-perceived health status and health-related
quality of life of extremely low-birth-weight infants at adolescence.
JAMA.1996;276:453-459.Google Scholar 17.Saigal S, Szatmari P, Rosenbaum P, King S, Campbell D. Cognitive abilities and school performance of extremely low birth
weight children and matched term control children at age 8 years: a
regional study.
J Pediatr.1991;118:751-760.Google Scholar 18.Torrance GW. Measurement of health state
utilities for economic appraisal.
J Health Econ.1986;5:1-30.Google Scholar 19.Saigal S, Rosenbaum P, Stoskopf B.
et al. Comprehensive
assessment of the health status of extremely low birth weight children
at eight years of age: comparison with a reference group.
J
Pediatr.1994;125:411-417.Google Scholar 20.Saigal S, Feeny D, Furlong W, Rosenbaum P, Burrows E, Torrance G. Comparison of the health-related quality of life of
extremely low birth weight children and a reference group of children
at age eight years.
J Pediatr.1994;125:418-425.Google Scholar 21.Feeny D, Furlong W, Barr RD, Torrance GW, Rosenbaum P, Weitzman S. A comprehensive multiattribute system for
classifying the health status of survivors of childhood cancer.
J
Clin Oncol.1992;10:923-928.Google Scholar 22.Feeny DH, Torrance GW, Furlong WJ. Health utilities
index. In: Spilker B, ed. Quality of Life and PharmacoEconomics in
Clinical Trials. 2nd ed. Philadelphia, Pa: Lippincott-Raven Press;
1996:239-252.
23.Patrick DL, Starks HE, Cain KC, Uhlmann RF, Pearlman RA. Measuring preferences for health states worse than death.
Med
Decis Making.1994;14:9-18.Google Scholar 24.Lee SK, Penner PL, Cox M. Comparison of the attitudes
of health care professionals and parents toward active treatment of
very low birth weight infants.
Pediatrics.1991;88:110-114.Google Scholar 25.Schneiderman LJ, Kaplan RM, Pearlman RA, Teetzel H. Do physicians' own preferences for
life-sustaining treatment influence their perceptions of patients'
preferences?
J Clin Ethics.1993;4:28-33.Google Scholar 26.Churchill DN, Torrance GW, Taylor DW.
et al. Measurement of quality of life in end-stage renal disease: the time
trade-off approach.
Clin Invest Med.1987;10:14-20.Google Scholar 27.Saigal S, Rosenbaum P, Hoult L.
et al. Conceptual and
methodological issues in assessing health-related quality of life in
children and adolescents: illustration from studies of extremely low
birthweight survivors. In: Drotar D, ed.Measuring Health-Related
Quality of Life in Children and Adolescents: Implications for Research
and Practice. Mahwah, NJ: Lawrence Erlbaum Associates;
1998:151-169.
28.Boyle MH, Torrance GW, Sinclair JC, Horwood SP. Economic evaluation of neonatal intensive care of very-low-birthweight
infants.
N Engl J Med.1983;308:1330-1337.Google Scholar 29.Cadman D, Goldsmith C, Bashim P. Values, preferences,
and decisions in the care of children with developmental disabilities.
Dev Behav Pediatr.1984;5:60-64.Google Scholar 30.Cadman D, Goldsmith C, Torrance G, Boyle M, Furlong W. Development of a Health Status Index for Ontario Children: Final
Report to the Ontario Ministry of Health. Toronto: Ontario Ministry
of Health; 1986. Research grant DM 648 (00633).
31.Slevin ML, Stubbs L, Plant HJ.
et al. Attitudes to
chemotherapy: comparing views of patients with cancer with those of
doctors, nurses, and general public.
BMJ.1990;300:1458-1460.Google Scholar 32.Laine C, Davidoff F. Patient-centered medicine: a
professional evolution.
JAMA.1996;275:152-156.Google Scholar 33.Emanuel EJ, Emanuel LL. Four models of the
doctor-patient relationship.
JAMA.1992;267:2221-2226.Google Scholar 34.Tyson JE, Broyles RS. Progress in assessing the
long-term outcome of extremely low-birth-weight infants [editorial].
JAMA.1996;276:492-493.Google Scholar