Article Figures & Data
Figures
- Figure 1.
Effect of academic detailing on percentage of women recommended for screening with mammography using chart audit data: b, 2 years preintervention; c, at follow-up after completion of academic detailing intervention; d, repeated measures ANOVA (P = .01); e, repeated measures ANOVA (P = .01).
- Figure 2.
Effect of academic detailing on percentage of women recommended for screening with clinical breast examination (CBE) using chart audit data: b, 2 years preintervention; c, at follow-up after completion of academic detailing intervention; d, repeated measures ANOVA (P = .98); e, repeated measures ANOVA (P = .95).
Tables
- Table 1.
Sociodemographic and medical practice characteristics of the primary care physician sample at baseline (N = 168)
All Intervention Comparison N Age, mean years (SD) 47 (45) 48 (12) 46 (12) 167 Female, % 31 28 36 168 African Americans/Hispanics, % 74 79 67 168 Graduate US medical school, %* 39 51 18 168 Number of years practice, mean (SD) 16 (12) 16 (12) 15 (11) 167 Number of pat contacts/week 80 (75) 80 (36) 75 (29) 163 Insurance, %‡ Medicaid and Medicare, mean % (SD)* 40 (31) 47 (31) 30 (28) 151 Private indemnity, mean % (SD) 40 (31) 15 (25) 8 (20) 150 Managed care, mean % (SD)† 21 (31) 27 (34) 12 (23) 151 Uninsured, mean % (SD) 11 (21) 13 (24) 8 (17) 152 Other insurance, mean % (SD)*§ 13 (31) 6 (20) 23 (42) 154 Practice with non-Hispanic white patients, mean % (SD) 7 (16) 9 (18) 4 (14) 156 Implementation score, mean (SD)‖ 4.5 (2.44) 4.68 (2.71) 4.27 (2.04) 168 * P < .0001.
† P < .001.
‡ Columns do not sum to 100% because of participant under-reporting or over-reporting.
§ Columns do not sum to 100% because of participant under-reporting or over-reporting; other, eg, self-pay, Worker’s Compensation.
‖ Collected at followup only. The score is a total count of the following individual items: manual or computerized prompting or tracking of preventive services (eg, chart reminders or stickers), computerized reminders to patients for follow-up, pamphlets, wall posters, or printed materials for patient education, and/or performance targets, incentives, and feedback for breast cancer screening, whether office staff are involved in tracking or counseling women for breast cancer screening.
- Table 2.
Multiple linear regression analysis of the effect of academic detailing on (1) knowledge of risk factors at post-test and (2) barriers to breast cancer screening (N = 168 for both)*
Effect of Academic Detailing on Knowledge of Risk Factors at Post-test Effect of Academic Detailing on Barriers to Breast Cancer Screening Beta† 95% CI‡ R2Δ§ P Beta† 95% CI‡ R2Δ§ P No. years of medical practice −0.10 −0.03, 0.007 .25 −0.02 −2.75, 2.65 .81 Medical school 0.08 −0.21, 0.62 .33 −0.01 −0.90, 0.78 .89 Percentage of patients insured by Medicaid or Medicare −0.18 −0.02, 0.00 .04 0.05 −0.009, 0.02 .52 Percentage of patients insured by managed care 0.03 −0.005, 0.008 .70 −0.09 −0.02, 0.005 .24 Baseline knowledge of risk factors for breast cancer‖ 0.35 0.24, 0.68 0.18 <.00001 n/a Baseline barriers to breast cancer screening¶ n/a 0.60 0.44, 0.77 0.2 <.0001 Intervention**†† f,g 0.23 −0.14, 1.06 0.04 .01 −0.48 −1.62, 3.75 0.13 <.00001 * Using self-report data, after completion of academic detailing intervention.
† Beta is the standardized regression coefficient, ie, a standardized measure of the change in outcome attributable to one predictor with the remaining predictors held constant.68
‡ 95% confidence intervals
§ R2Δ is the change in the percentage of variation in the outcome explained by all of the predictors in the model. R2Δ is for the full model including all of the listed factors except intervention.
‖ Range, 1 to 7.
¶ Range, 0 to 8.
** Intervention model with knowledge of breast cancer risk factors as outcome adjusted for baseline knowledge of breast cancer risk factors, number of years of practice, whether attended US medical school, follow-up barriers to breast cancer screening, percentage of patients enrolled in managed care, percentage of patients enrolled in Medicare or Medicaid, percentage of patients with other insurance, overall model, P < .00001.
†† Intervention model with barriers to breast cancer screening as outcome adjusted for baseline barriers to breast cancer screening, follow-up knowledge of breast cancer risk factors, number of years of practice, whether attended US medical school, percentage of patients enrolled in managed care, percentage of patients enrolled in Medicare or Medicaid, percentage of patients with other insurance, overall model, P < .00001
- Table 3.
Linear mixed models analysis of the effect of academic detailing on physician recommendations for (1) mammography at follow-up and (2) clinical breast examination (CBE) at follow-up (N = 710 for both)*
Effect of Academic Detailing on Physician Recommendation of Mammography at Follow-up Effect of Academic Detailing on Physician Recommendation of CBE at Follow-up Beta† SE t OR‡ 95% CI§ P Beta† SE t OR‡ 95% CI§ P Years of practice‖ −0.003 0.006 −0.48 .63 Medical school 0.19 0.23 0.86 .39 −0.40 0.30 −1.35 .18 Percentage of patients insured by Medicaid or Medicare −0.03 0.006 −4.47 <.0001 −0.04 0.007 −5.26 <.0001 Barriers to screening‖ −0.48 0.26 −1.87 .06 Knowledge of risk factors for breast cancer 1.32 0.23 5.79 <.0001 1.62 0.24 6.83 <.0001 Age (40 to 49, >50) 0.97 0.58, 1.62 .91 1.09 0.57, 2.05 .80 Baseline mammography proportion 5.17 3.15, 8.46 <.0001 n/a Baseline CBE proportion n/a 1.37 0.73, 2.56 .33 Intervention¶** 1.85 1.25, 2.74 .002 2.13 1.31, 3.46 .002 * Using medical audit data, after completion of academic detailing intervention; analyzed via GLIMMIX in SAS, to account for clustering of patients.
† Beta is the standardized regression coefficient, ie, a standardized measure of the change in outcome attributable to one predictor with the remaining predictors held constant.68
‡ The reference is the control group.
§ 95%confidence intervals.
‖ The contribution of this factor was null so it was deleted from the model.
¶ Intervention model with mammography screening as outcome adjusted for baseline rates of recommendations for mammography screening, whether attended US medical school, follow-up knowledge of breast cancer risk factors, follow-up barriers to breast cancer screening, percentage of patients enrolled in Medicare or Medicaid, percentage of patients enrolled in other insurance.
** Intervention model with CBE as outcome adjusted for baseline CBE rates, number of years of practice, whether attended US medical school, follow-up knowledge of breast cancer risk factors, follow-up barriers to breast cancer screening, percentage of patients enrolled in Medicare or Medicaid, percentage of patients enrolled in other insurance.
