TABLE 3
Results of multiple logistic regression modeling* for being up to date†for cancer screening and adult immunization, by sex and demographic characteristics: 2006 Behavioral Risk Factor Surveillance System, adults ≥65 years
| Men | Women | |||||
|---|---|---|---|---|---|---|
| OR | 95% CI | P value | OR | 95% CI | P value | |
| Age 65-69 y (referent) | ||||||
| 70-74 | 1.74 | 1.54-1.97 | <.001 | 1.54 | 1.39-1.70 | <.0001 |
| 75-79 | 2.04 | 1.79-2.32 | <.001 | 1.56 | 1.40-1.74 | <.0001 |
| ≥80 | 1.96 | 1.72-2.23 | <.001 | 1.19 | 1.06-1.32 | .002 |
| White (referent) | ||||||
| Black | 0.52 | 0.41-0.66 | <.001 | 0.55 | 0.46-0.66 | <.0001 |
| Hispanic | 0.37 | 0.26-0.53 | <.001 | 0.56 | 0.42-0.76 | <.0001 |
| Other | 0.53 | 0.40-0.71 | <.001 | 0.55 | 0.43-0.72 | <.0001 |
| Not married (referent) | ||||||
| Married | 1.23 | 1.12-1.37 | <.001 | 1.28 | 1.18-1.38 | <.0001 |
| <high></high></high> | ||||||
| High school | 1.28 | 1.10-1.50 | .002 | 1.28 | 1.14-1.44 | <.0001 |
| Some college | 1.54 | 1.30-1.83 | <.001 | 1.50 | 1.32-1.69 | <.0001 |
| College grad | 1.82 | 1.55-2.13 | <.001 | 1.79 | 1.57-2.05 | <.0001 |
| Health access‡ (“Low” is referent) | ||||||
| Medium | 1.32 | 0.71-2.45 | .378 | 1.72 | 1.03-2.87 | .038 |
| High | 2.41 | 1.32-4.41 | .004 | 3.08 | 1.88-5.05 | <.0001 |
| No checkup§ (referent) | ||||||
| Checkup 2 yr | 2.53 | 2.07-3.10 | <.001 | 2.72 | 2.18-3.40 | <.0001 |
| Fair/poor health (referent) | ||||||
| Ex/v good health | 0.76 | 0.68-0.85 | <.001 | 0.94 | 0.87-1.03 | .167 |
| Nonsmoker (referent) | ||||||
| Current smoker | 0.59 | 0.48-0.72 | <.001 | 0.68 | 0.58-0.79 | <.0001 |
| CI, confidence interval; OR, odds ratio. *N=27,632 for men and 50,024 for women. Includes 50 states plus the District of Columbia and excludes 3324 male respondents and 6295 female respondents with missing values for one or more measures. There were 2 separate models, one for men and one for women. †To be up to date, men required colon cancer screening (fecal occult blood test in past year or endoscopy within 10 years), a flu shot in the past year, and a pneumonia vaccination ever. Women required those same services plus a mammogram within 2 years and Pap test within 3 years (unless prior hysterectomy). ‡Determined from 3 measures: having health insurance, having a personal health care provider, and not reporting a cost barrier. Levels 0 and 1 were combined. Resulting levels were low, medium, and high. | ||||||
Discussion
The key finding in this study is that, although most adults ages 65 and older had high access to health care and recent routine checkups, their rates of being up to date with a recommended cluster of preventive services were only about 45% for men and 37% for women.
More than 91% of men and 93% of women reported they had a routine checkup during this timeframe, and 88.6% of men and 90.2% of women also reported they had high access to health care—ie, they had health insurance, at least 1 personal health care provider, and no cost barrier to seeing a doctor. Improving access to health care or increasing the use of routine medical checkups—even to 100%—would likely have a negligible impact on the delivery of recommended services. Despite the very modest composite delivery rates of recommended preventive services in this group, the rates were still 2 to 4 times higher than those of adults with low health care access or no recent routine checkup.
We also found that being up to date generally improves with age. Granted, there is uncertainty as to the appropriate age at which to stop specific screenings. And very elderly Americans may be receiving some services no longer of benefit. But the significance of our finding is that composite delivery rates were lowest among adults at the age for which broad consensus says services are beneficial. For example, the up-to-date rates for men and women ages 65 to 69 were 32% and 29.8%, respectively, compared with 48.7% and 40.2% for adults ages 75 to 79 (TABLE 2).
Our findings are consistent with research documenting inadequate time to incorporate preventive services into the typical office visit.11,12 Similar barriers have been identified by general practitioners in the United Kingdom.13,14 The time constraint is particularly consequential in high-volume primary care practices.15 Some investigations have calculated the actual or necessary time needed to deliver multiple recommended prevention and health promotion services and have found the requirement to be unrealistically high.16-20 Our study suggests that increased access to and use of health care services is a necessary but insufficient condition for achieving high up-to-date levels.
To improve up-to-date rates, likely actions will include more efficient use of office time, increased reliance on nonphysician clinicians, greater use of electronic medical records, and prioritizing services for a routine checkup. External policy changes, such as pay-for-performance, may also enhance preventive service delivery rates. We hope that, in time, the composite measure used in this analysis will be adopted by both primary care clinicians and public health practitioners in the same way that tracking composite children’s vaccination levels are helpful to family practitioners, pediatricians, and local health departments. However, there is probably no easy answer; even the prompts enabled by electronic medical records are useless when ignored by providers.21 Improving delivery of preventive services in office settings will require multiple strategies sustained over many years.22
Community-based efforts. There is a strong rationale for a more determined policy to expand community-based access. Many community-based approaches to individual preventive services have been developed over the last 10 years.23 For example, the CDC’s National Breast and Cervical Cancer Early Detection Program represents one model of a state-based program that can make local assistance available for uninsured women.24 In addition, an evidence-based model developed by the nonprofit agency SPARC (Sickness Prevention Achieved through Regional Collaboration) suggests ways of creating community-based points of access for multiple preventive services.25-27