A randomized trial of telephone counseling to promote screening mammography in two HMOs

Cancer Detection and Prevention 27 (2003) 442–450

A randomized trial of telephone counseling to promote screening mammography in two HMOs Roger Luckmann, MD, MPH a,∗ , Judith A. Savageau, MPH a , Lynn Clemow, PhD b , Anne M. Stoddard, ScD c , Mary E. Costanza, MD a a

University of Massachusetts Medical School, Worcester, MA, USA Robert Wood Johnson School of Medicine, New Brunswick, NJ, USA University of Massachusetts School of Public Health, Amherst, MA, USA b

c

Accepted 11 September 2003

Abstract Tailored telephone counseling (TTC) is effective in increasing utilization of screening mammography, but has received limited testing on a large scale in a contemporary HMO setting in which most eligible women get regular screening. We conducted a randomized controlled trial comparing TTC to an active control (mailed reminders) among women aged 50–80 enrolled in two HMOs in New England (n = 12,905). Over a 1-year period counselors attempted to contact women in the intervention arm who had not had a mammogram within the last 15 months. The absolute increase in mammography use due to the intervention was 4.9% (OR 1.3, 95% CI 1.0–1.6) in one HMO and 3.1% (OR 1.2, 95% CI 1.0–1.3) in the other. We estimated that one additional woman was screened for each 10.9 women eligible for counseling. An intervention process analysis documented a high level of acceptance of TTC and identified subgroups that could be targeted for counseling to improve the efficiency of TTC. © 2003 International Society for Preventive Oncology. Published by Elsevier Ltd. All rights reserved. Keywords: Screening mammography; Breast cancer prevention; Telephone counseling; Randomized controlled trial; Health behavior

1. Introduction Over the last 10 years a national effort to promote regular mammography screening for breast cancer among women aged 50 and older has provided the impetus for dozens of descriptive studies of screening knowledge, attitudes, and beliefs and numerous trials of a wide variety of interventions aimed at increasing the use of mammography [1,2]. Interventions have targeted individual women, communities, medical care providers and their office staff. Some early studies of tailored telephone counseling (TTC) to promote mammography showed that brief, scripted counseling calls focused on a woman’s barriers to getting a mammogram could substantially increase utilization [3]. Several other studies of similar tailored telephone interventions that followed also showed promising results, although the content and duration of counseling and the study populations varied considerably across studies [4–6]. Recent studies of TTC targeting underusers of mammography, have found that TTC was most effective among women who were sporadic ∗ Corresponding author. Tel.: +1-508-856-4150; fax: +1-508-856-1212. E-mail address: [email protected] (R. Luckmann).

users of mammography and least effective among those who had never had a mammogram [7–11]. Overall, the magnitude of the effect of TTC among underusers studied recently was lower than the effect size among unselected women studied during the early phases of adoption of screening mammography in the United States. Costanza et al. have suggested that the effectiveness of TTC for mammography may have declined over time, as increasing numbers of women have become regular mammography users [7]. They postulate that TTC may be most effective during the early and middle phases of adoption of a screening test, when most individuals have not yet had the test, and there are few competing promotional efforts. Once most individuals have adopted regular screening habits, and reminders for repeat screening are being regularly provided by preventive care systems, the pool of people who become overdue for screening becomes increasingly dominated by individuals who are highly resistant to the adoption of the test. These resistant individuals are not likely to respond to brief TTC. According to the 1995 behavioral risk factor surveillance survey [12], the percent of US women with a self-reported mammogram within the past 2 years by age group was 76.8% (age 50–59), 74.3% (age 60–69), and 64.9% (age ≥70). These high rates of

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screening prevalence suggest that the US population in 1995 was in a relatively late phase of adoption of mammography so we might expect that many of those who have not adopted screening may be resistant to mammography promotions. Our main objective in this study was to determine how much TTC could increase screening rates over a routine reminder system in a population that already had a very high level of mammography utilization. A secondary, but very important objective was to identify characteristics of women for whom TTC is effective through an intervention process analysis involving subjects receiving TTC. Previous studies of TTC and mammography have provided little process information on intervention implementation. Such information can be very helpful to practitioners attempting to develop comparable applications of the counseling protocol for other populations.

2. Methods This study was conducted in conjunction with a study of mammography underutilizers with some overlap of study populations [7] (see Fig. 1). The population for this study included all women age 50–80 continuously enrolled for 12 months from May 1995 to April 1996 in selected primary care practices (number of physicians in group ≤10) in two HMOs in central Massachusetts. HMO administrative databases were used to identify eligible subjects. The study sample included 338 primary care practice groups comprising 480 internists and family physicians. Women (12,905) in the practice sample were eligible for this study. Women were clustered by their primary care practice group and randomized to an intervention (TTC) and active control group (mailed reminders) by physician practice. The practice size limitation and the cluster randomization were necessary because the companion study of underutilizers included an intervention aimed at small to moderate sized group practices. Practices that received the physician intervention in the underutilizer study were excluded from this study. The women in both the control group and the TTC group received annual computer generated reminders about mammograms, and their primary care physicians (PCP) received quarterly reports on women who had not received a mammogram within designated time intervals (15 and 26 months). Physicians were encouraged to use the reports to contact patients about getting a mammogram, but we did not collect data on actual physician use of the reminders. At the time of the study both HMOs recommended mammograms every 1–2 years for all women aged 50 and older. The date of the last mammogram in the HMO databases determined when the next annual mammogram would be due, but when there was no previous mammogram, the date of enrollment in the plan was used as a proxy. Reminders were mailed out 10–11 months after the date of the last mammogram or

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date of enrollment. Women who were already overdue for a mammogram (>12 months since last mammogram or date of enrolment) at the beginning of the study also received a mailed reminder. The quarterly reports to physicians in both the TTC and control groups listed women (and their telephone numbers) who had become overdue for a mammogram during the quarter by a period of 15 months or a period of 26 months. The reminder and reporting systems were initiated 6 months before telephone counseling was started. Women in the TTC group became eligible to receive a counseling call when the HMO computer system indicated that 15 months or more had elapsed since a prior mammogram or since the HMO enrollment proxy date. Two TTC counselors made up to 15 attempts at a variety of times to reach each eligible woman and initiate counseling. Counselors had received 30–40 h of training in the application of a TTC protocol developed for use in studies by the National Cancer Institute Breast Cancer Screening consortium [7]. The protocol included scripted responses to common barriers to screening as well as opening and closing statements. Counselors could refer to the script as they tailored their efforts to respond to a subject’s barriers, both those explicitly stated and those inferred by the counselor from the subject’s statements. Women received limited TTC (brief, positive reinforcement of their efforts to get screened) if they reported they were on a biannual rather than annual screening schedule and would not be due for several months or if they had received a mammogram within the last 12 months which had not been recorded in the HMO database. Women on a biannual schedule who had not had a mammogram in the last 24 months did receive counseling. 2.1. Data analysis For the primary intention-to-treat analysis including all subjects, the outcome was evidence in the HMO databases of a bill submitted for one or more mammograms during the 12-month study period. HMO databases provided information on potential covariates, including age, number of years with their current primary care physician, and number of visits to primary care and obstetrician-gynecologists over the study period. Unadjusted bivariate analyses compared outcomes in the intervention and control groups stratified by HMO. A logistic regression model was constructed which adjusted for the cluster randomization and included the three available covariates noted above. Separate models were constructed for each HMO. We used a mixed-model logistic regression analysis to assess the associations of the four independent variables with obtaining a mammogram, controlling for clustering of women in practices [13]. Generalized estimating equation methods were used for the logistic regression analysis [13]. Absolute benefit increase (ABI) was calculated in the standard fashion [14,15] based on the unadjusted mammography rates, since adjustment did not significantly affect the point estimate of the odds ratios. Number needed to treat (NNT) was estimated in the

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Fig. 1. Derivation of subject samples for main ITT analysis in this study, for intervention process analyses and relationship of samples in this study and companion study of underusers of mammography: (1) communication problems occurred primarily with non-English speaking subjects; (2) other reasons included cognitive impairment and subject time constraints.

standard fashion [14]. Modified NNT was calculated by dividing selected denominators (total number of women eligible for counseling and total number of women receiving counseling) by the estimated number of additional women receiving mammograms attributable to the intervention in the intervention group based on the following formula:

number of additional women receiving mammograms = MamInt − (CtrlMamProp × NSubjInt) where MamInt is the number of women obtaining a mammogram in the intervention group, CtrlMamProp the proportion of women in the control group receiving a

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mammogram, NSubjInt the total number of subjects in the intervention group. 2.2. Intervention process analyses The intervention process analyses focused on the cohort of women that became eligible for counseling during the study (i.e., last mammogram ≥15 months before baseline or at time of monthly reminder assessment). Counselors recorded data on the number of women reached by phone, those who were found to be ineligible at the time of the call or could not be counseled for other reasons. For women who received full TTC, counselors recorded each subject’s history of mammography utilization, her intention to obtain a mammogram at the start and finish of the call and the number and types of barriers encountered in each counseling effort. At the beginning of the call, women were asked if they were planning on getting a mammogram, and if they said yes they were asked if they had already scheduled one. At the end of the call, counselors read a standardized intention statement to the participant that the counselor felt best characterized their level of intention to get or not to get a mammogram. Other statements were read if necessary until the participant agreed that a standardized statement accurately reflected her intention. Responses to statements were post-coded into four categories of intention to get a mammogram: (1) not planning; (2) thinking about it; (3) planning on it; and (4) already scheduled for one. Counselors had a list of common barriers available at the end of the phone call and checked off those barriers they believed were expressed by the woman during the call. The barriers on the initial list were combined into five broad categories based on shared characteristics of the barriers as perceived by the investigators. The five categories were: anxiety and/or fear of pain related to a mammogram, procrastination or logistical problem, health problem that prevents or distracts a woman from getting a mammogram, the belief that a mammogram is not needed, and “other”. For the intervention process analyses, univariate and bivariate statistics were generated for the variables collected by the counselors on intention and barriers. Stratified analy-

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ses assessing the associations of age and prior mammography experience with barriers and intentions were performed. The process outcome was the receipt of a mammogram within 15 weeks of the counseling call as determined from information in the HMO administrative databases. The chi-square statistic was calculated to determine p values for bivariate and stratified analysis. A logistic regression model was developed to assess the independent contributions of age, mammography experience, type of barrier and number of barriers, and counselor on the process outcome.

3. Results Of all women continuously enrolled in the study practices for 12 months from baseline (n = 12,905), 65.0% were aged 50–59, 28.1% were 60–69 and 6.9% were 70–80 years old. The age distribution was comparable for both TTC and reminder control (RC) groups, but HMO2 had a higher percentage of younger women (68% versus 53%). Table 1 shows the proportion of women in TTC and RC groups that received one or more mammograms during the study period by HMO. At baseline and over the 12-month study period, we identified 2634 women in the HMO administrative database who had not had a mammogram over a 15-month period or longer and were thus eligible for TTC. Fig. 1 (lower section on sample selection for intervention process analysis) shows the outcomes of efforts to contact and counsel these women. Counselors were able to contact 2307 women (87.6%) and only 176 (7.6% of those reached) refused counseling. In HMO1, 4.9% more women in the TTC group received a mammogram than in the RC group (ABI = 0.049). For HMO2, the ABI was 0.031. Odds ratios from logistic regression models controlling for clustering of women by physician and several possible confounders were statistically significant (P < 0.05) for both HMOs and are consistent with the bivariate odds ratios (1.22 and 1.14 for HMO1 and HMO2, respectively) (Table 1). The number needed to treat calculated in the conventional fashion (including all subjects) was 20.4 for HMO1 and 32.3 for HMO2, respectively.

Table 1 Unadjusted and adjusted comparison of 12-month rates of mammography utilization for women aged 50–80 for tailored telephone counseling and control groups by HMO (n = 12,905) Total enrolled for 12 months (n)

≥1 mammogram over 12 months n

Percent

HMO1 TTC Control

1871 1055

1021 524

HMO2 TTC Control

4811 5168

3038 3108

a

Adjusted ORa

95% CI

P-valueb

54.6 49.7

1.26

(1.00, 1.58)

0.048

63.2 60.1

1.15

(1.01, 1.30)

0.03

Odds ratio from logistic regression model controlling for clustering of women by physician group, age, years with PCP, and number of visits to primary care and obstetrician-gynecologists providers during intervention year. b Related to OR.

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However, since only selected women in the TTC arm actually became eligible for counseling over the 12 months of the study (i.e., those overdue for a mammogram by 15 months or more), a more appropriate, modified NNT estimate would take this into account. Using an intention to treat analysis based on the 2634 women eligible for counseling in the TTC arm, attempting to call 10.9 women overdue for a mammogram is required to generate one additional mammogram. If the NNT analysis is further restricted to only those who actually received counseling (n = 1108), we estimate that for every 4.6 women counseled, one additional mammogram was generated.

Table 2 Characteristics, intention, and barriers for women who received full TTC during the first intervention year (n = 1108)

3.1. Intervention process analyses The process analyses focused on the cohort of women who became eligible for counseling during the 12-month study period and included a flow chart showing the outcomes of attempts to reach these women, a descriptive analysis of those who received full TTC, and a mammography utilization analysis for those who had 15-week follow-up data in the HMO database. Fig. 1 (lower section on sample selection for intervention process analysis) shows how the 1108 women who received full TTC were selected from among the 2634 women in the TTC arm who became eligible for counseling during the study period. Some women (872) received only limited counseling because they were not overdue for a mammogram and 654 received no counseling, mostly because of inability to make a phone contact. Most women who were found not overdue for a mammogram at the time of a counseling call had obtained a mammogram around the time they were selected for counseling or a month later, but the mammogram had not yet been recorded in the HMO database. Of the 1108 women receiving full TTC, 971 remained enrolled in the HMO for at least 15 weeks following the counseling and could be included in the final process outcome analysis based on receiving a mammogram in that time period. Table 2 shows the demographic characteristics, barriers, and intentions before and after the counseling for all women counseled. Most (71.6%) had had a previous mammogram and 10.7% had a mammogram already scheduled in the near future. Before the counseling, 59.9% were not planning to get another mammogram compared to only 5.3% after the call. Most women had one or two barriers, and the most common barriers were procrastination and logistical barriers and anxiety related to screening or the mammography procedure. Overall, 27.2% of women counseled obtained a mammogram over the 15-week follow-up period. Table 3 shows the proportion of counseled women who obtained a mammogram within 15 weeks of the TTC call by selected predictor variables. The first eight variables were included in a logistic regression model, and the odds ratios from that model are also shown in the table. When controlling for other variables, age was not associated with obtaining a mammogram. Having had a previous mammogram was the strongest

na

Percent

Age 50–59 60–69 ≥70

581 379 147

52.5 34.2 13.3

≥1 previous mammogram

792

71.6

Intention before counseling Mammogram scheduled Planning to get a mammogram Not planning a mammogram

119 336 652

10.7 30.4 58.9

Intention after counseling Mammogram scheduled Planning to get a mammogram Thinking about a mammogram Not planning a mammogram

119 650 274 59

10.8 59.0 24.8 5.3

Number of barriers 0 1–2 ≥3

101 685 321

9.1 61.9 29.0

383

34.6

618 177 302 219

55.8 16.0 27.3 19.8

Type of barrier Anxiety about mammography or fear of pain from procedure Procrastination or logistical problem Health problem Believe that mammogram is not needed Other a

For some subcategories total number of subjects may be less than 1108 because of missing data.

predictor of the outcome (OR = 4.0). In the bivariate analysis of types of barriers, all barriers appeared to have a modest effect on the outcome, although health concerns did not reach a traditional level of statistical significance. Women with health-related or logistical barriers were actually more likely to obtain a mammogram than those without these barriers while women with the anxiety and/or “mammogram not needed” barrier were less likely to receive screening. Estimates of the effect of barriers in the logistic model were somewhat imprecise but generally confirmed the bivariate findings. Women counseled by counselor B were less likely to get a mammogram. Intention to get a mammogram (scheduled or planning) both before and after counseling was a strong predictor of short-term mammography utilization. Most of those who had an appointment for a mammogram followed-through with it within 15 weeks (77.9%), while none of those who stated an intention not to get a mammogram after counseling got one. Women who reported planning to get a mammogram were also more likely to get one than those who stated they were “thinking about it”. Table 4 shows the distribution of intention to get a mammogram and selected barriers stratified by age and mammography history. Intention and most of the barriers in the table show substantial independent variation by both age and mammography history. The percent planning a mammogram

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Table 3 Mammogram utilization within 15 weeks of counseling for women who received full TTC by age, mammography history, intention, barriers and counselor (unadjusted and adjusted by logistic regression) (n = 971) Subgroup (n)

Mammogram (na )

Percent

P-valueb

ORc

95% CI

Age 50–59 60–69 ≥70

511 329 131

143 92 29

28.0 28.0 22.1

0.38

0.93 1.16 1

(0.56, 1.54) (0.69, 1.95)

≥1 previous mammogram Number of previous mammogram

688 283

238 26

34.6 9.2

0.001

4.0 1

(2.50, 6.27)

Counselor A B

413 558

135 129

32.7 23.1

0.001

1 0.70

(0.51, 0.96)

Number of barriers 0 1–2 ≥3

91 595 285

31 170 63

34.1 28.6 22.1

0.039

1 0.51d

(0.27, 0.97)

Anxiety/pain barrier Yes No

325 646

57 207

17.5 32.0

0.001

0.64 1

(0.43, 0.93)

Procrastination/logistics barrier Yes No

545 426

177 87

32.5 20.4

0.001

1.39 1

(0.92, 2.11)

Health barrier Yes No

150 821

49 215

32.7 26.2

0.083

1.26 1

(0.83, 1.91)

Mammogram not needed barrier Yes No

264 707

41 223

15.5 31.5

0.001

0.75 1

(0.48, 1.15)

Intention before counseling Mammogram scheduled Planning a mammogram Not planning a mammogram

95 298 578

74 94 96

77.9 31.5 16.6

0.001

Intention after counseling Mammogram scheduled Planning a mammogram Thinking about a mammogram Not planning a mammogram

95 567 250 59

74 163 27 0

77.9 28.7 10.8 0

0.001

a

Number of women who received a mammogram. Applied to bivariate analysis. c Odds ratios from logistic regression model including age, mammography history, number of barriers, type of barriers and counselor. d Barrier categories 1–2 and ≥3 combined in the logistic model. b

Table 4 Mammography intention and barriers by mammography experience and age (n = 971) ≥1 mammogram in past

No mammogram ever

Planning before counseling Planning after counseling Logistic/procras tination barrier Anxiety/pain barrier Mammogram “not needed” barrier a

50–59, n = 112 (%)

60–69, n = 112 (%)

≥70, n = 59 (%)

P-valuea

50–59, n = 399 (%)

60–69, n = 217 (%)

≥70, n = 72 (%)

P-valuea

13.4 43.2 48.2 55.4 42.9

9.8 30.3 32.1 48.2 50.9

3.4 29.3 13.6 32.2 59.3

0.11 0.07 <0.01 0.02 0.11

42.9∗∗ 74.4∗∗ 69.9∗∗ 25.6∗∗ 15.0∗∗

34.6∗∗ 62.2∗∗ 62.2∗∗ 32.7∗∗ 18.0∗∗

33.8∗∗ 53.5∗∗ 46.5∗∗ 23.9∗ 33.8∗∗

0.08 <0.01 <0.01 0.02 <0.01

For comparison across age groups within each mammography experience category. P < 0.05 for comparison of corresponding age group with no mammogram ever. ∗∗ P < 0.01 for comparison of corresponding age group with no mammogram ever. ∗

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increases by about 20–30% points from before to after the call for all groups. Older women are less likely to state intention regardless of mammography history, and women who have had a mammogram are more likely to state intention that those without one, regardless of age. Logistic and anxiety barriers become less common as age increases among those without a mammogram. Holding the belief that a mammogram is “not needed” becomes more common with increasing age in both mammography groups. For each age group, women who have had a mammogram have a lower prevalence of the anxiety/pain barrier and the belief that a mammogram is not needed while they have a higher prevalence of logistic barriers.

4. Discussion Compared to other studies of telephone counseling to promote mammography, this study involved a larger population (the majority of mammography-eligible women in two HMOs) over a longer period of time (one full year) than others have. Thus, our findings may reasonably reflect the results that could be expected from implementing a counseling intervention in most HMOs today, assuming that findings in Massachusetts can be generalized to other states. The 12-month mammography utilization rate in the control groups (49.7 and 60.1%) are high and consistent with the assertion that the study population, like the US population in 1995 was in a late phase of adoption of mammography. These 12-month utilization rates are considerably lower than the age-specific rates reported in the BRFSS (76.3, 75.2 and 64.9%), because they cover only a 12-month period. Two year cumulative rates would likely be comparable. We found modest increases in mammography utilization in the telephone counseling groups in both HMOs (ABI = 4.9 and 3.1%). These effect sizes may slightly understate the true effect size because of a modest amount of misclassification of the outcome. Based on self-reported recent mammography use by women who were called for counseling, we estimate that a maximum of about 6% of women in the study may have had a mammogram within the 15-month time frame that was not captured by the HMO database because of error, delay or use of an alternative insurance plan to cover the cost of the mammogram. The effect of such misclassification would be to bias the odds ratio for the outcome towards the null. In addition, it is important to note that the control group for this study received mailed reminders for mammograms and physicians in the control practices also received information about women overdue for mammograms. Thus, the effect size for the TTC intervention indicates how much additional effect the TTC had over and above the effect of mailed reminders, which have been shown to be effective in many studies [1]. NNT estimates ranged from 4.6 to 20.4 depending on the denominator used. Most of the costs of this intervention in practice would be limited to the costs of attempting to reach and counsel

women deemed eligible for counseling based on administrative data. Thus, the NNT based on those eligible for counseling (10.9) may be the most reasonable upper estimate of NNT. Counseling 4.6 is a reasonable lower estimate of NNT which could theoretically be achieved if administrative data was more accurate and complete, reducing calls to women who had had a recent mammogram, were not interested in counseling, or were on a biennial schedule. Based on a pooled estimate of intervention effect from a recent systematic review on behavioral interventions to promote mammography (+5.6%) [1], our telephone counseling protocol is about as effective as the average behavioral intervention compared to an active reminder control. In a study in an HMO, Davis et al. [4] found telephone counseling, which included the opportunity to schedule a mammogram, was the most effective of three interventions studied (28% screened over 6 months) compared to 15% for a reminder mailing and 9% for a physician reminder. In another HMO study by Davis et al. [5], 45.7% in the telephone counseling group received a mammogram in 5 months compared to 30.2% in a control group. We did not offer women the option of scheduling a mammogram, which may have an effect on mammography rates. In another HMO intervention, Saywell et al. [6] reported 6-week mammography rates of 35.6, 23.1 and 18.2% for a telephone counseling plus reminder letter, counseling only, and control groups, respectively. Counseling calls were on average more than 30 min long. The 4.9% increase in mammography use attributed to telephone counseling alone in this study is similar to our results although duration of follow-up is shorter. 4.1. The TTC process: issues in implementation Our intervention appeared to be acceptable to most women and somewhat effective in changing self-report of health beliefs and stated level of intention to get a mammogram. Only 6.7% of those eligible refused counseling (7.6% of those reached by phone). Telephone counseling also appeared to be successful in moving women’s self-reported intentions closer to the action stage. For example, the percentage of women who reported they were “planning to get a mammogram” nearly doubled following counseling (from 30.4% before to 59.0% after counseling). However, of these women who stated they were “planning to get a mammogram”, only 28.7% received one within 15 weeks. It appears that single-session telephone counseling (especially counseling done without the opportunity to book an appointment on the spot) may be influencing self-reported attitudes in women, but this often does not culminate in near-term action. It is likely that the counseling calls, when effective, may have primarily performed a reminder function or set in motion the steps required for women to overcome procrastination and logistical barriers. Of women who reported procrastination and logistical problems as barriers (32.5%) obtained a mammogram during the follow-up period

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compared to 20.4% for those without these barriers. The importance of the reminder function of a counseling call is underscored by a finding that a scripted counseling call was no more effective than a reminder call in a recent study by Taplin et al. [16]. The process analysis suggests that targeting sporadic users of mammography, especially those citing logistics and procrastination as barriers, would likely improve the efficiency of TTC. Never users constituted 28.4% of the counseled sample and only 9.4% received a mammogram during follow-up while 34.6% of sporadic users obtained a mammogram. Increased mammography utilization among sporadic users receiving TTC likely accounts for most of the increase in utilization attributable to TTC in the whole sample. Different and likely more intensive interventions will be needed to reach the subset of women who have never had a mammogram or believe that one is not needed. Several other studies have found relatively low rates of response to mammography interventions among those who have never had a mammogram [17]. In general, the associations of other barriers (e.g., anxiety/pain, health problem) with mammography in this study parallel the findings of others [18]. The process analysis also suggests that simple classifications of intention both before and after the call can be useful in predicting mammography utilization. Women reporting “thinking about” getting a mammogram had about half the rate of mammography as those reporting “planning” to get a mammogram after the call. Women with lower rates of predicted mammogram completion could be targeted for more intensive follow-up counseling or other services, if future studies identified effective means of motivating these women. The two counselors in this study had substantially different levels of success as measured by 15-week mammography utilization (37.7% versus 23.1%). This could be due in part to differences in counseling style despite the common training and common use of a detailed protocol and in part due to differences in the women assigned to each for counseling. Women were not assigned randomly to the counselors so the groups were likely not comparable in some important characteristics beyond those that were adjusted in the model that included counselor as a covariate. In future studies of telephone counseling, assigning subjects randomly to counselors would help to determine the effect of different counseling styles. There are several notable limitations of this study. Barriers were not ascertained through systematic queries about each possible barrier as in some surveys, but through post-coding of the recalled narrative of the subject/counselor dialogue by the counselors themselves and then combining of similar barriers into broad descriptive categories. No reliability assessment of barrier coding was performed, and thus barrier designations may be relatively imprecise and should be interpreted cautiously. The relatively short follow-up period for the counseled cohort analysis may have had an effect on the differences reported in mammography performance for

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selected subgroups. The loss of significant number of women to follow-up, because they left their HMO could have biased some of the results of the process analysis. The limitation on the size of practice group to 10 or fewer physicians could conceivably limit generalization of the findings to groups of that size if women cared for by larger groups differed significantly from women cared for by smaller groups, or if larger groups more effectively promoted mammography in a way that left fewer women eligible for telephone counseling. Limiting generalization to groups of 10 or fewer physicians means the study findings are still potentially relevant to the vast majority of primary care physicians and practices in the United States. In 2001 only 18.5% of family physicians and 19.7% of general internists in the United States practiced in groups of more than eight physicians [19].

5. Conclusion Our study confirms others’ findings that telephone counseling of women overdue for mammograms in an HMO is well accepted and, like other similar behavioral interventions, can modestly increase mammography utilization. The effectiveness of the call in our study may have been primarily due to its reminder and nonspecific motivational function. One reason for the relatively limited effect of counseling in this study compared to some other studies may be the absence of an opportunity to schedule a mammogram in our study. In future studies, we need to learn more about how to motivate women who have never had a mammogram to consider getting one and to explore more intensive combinations of mailed and telephone interventions to reach this population. For less resistant women, we need to study the impact of repeated reminders such as follow-up telephone calls or mailings.

Acknowledgements This study was funded by the National Cancer Institute (RO1 CA60130). The authors are grateful to Harvard Pilgrim Health Care and CIGNA Health Care of Massachusetts for their generous cooperation and assitance. The authors gratefully acknowledge Mary Jo White for her many contributions as Project Director. References [1] Yabroff KR, Mandelblatt JS. Interventions targeted toward patients to increase mammography use. Cancer Epidemiol Biomarkers Prev 1999;8:749–57. [2] Mandelblatt JS, Yabroff KR. Effectiveness of interventions designed to increase mammography use: a meta-analysis of provider-targeted strategies. Cancer Epidemiol Biomarkers Prev 1999;8:759–67. [3] King ES, Rimer BK, Seay J, Balshem J, Engstrom PF. Promoting mammography use through progressive interventions: is it effective? Am J Public Health 1994;84:104–6.

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