Screening for diabetes mellitus in high-risk patients: cost, yield, and acceptability.

CONTEXT: Although universal screening for diabetes mellitus is generally not recommended, recent reports suggest that screening individuals with multiple diabetes risk factors may be worthwhile. Little is known about the cost, yield, or acceptability of this kind of screening. PRACTICE PATTERN EXAMINED: Screening of high-risk patients for diabetes mellitus using a two-step, glucose-based screening protocol: Patients were initially screened with a random glucose test; those with abnormal results received a follow-up fasting, 2-hour, 75-gram oral glucose tolerance test. CLINIC SELECTION: Three volunteer clinics from a large medical group in Minnesota. PATIENT SELECTION: Of 38,989 adults receiving care at the three clinics, we identified 1548 high-risk patients with evidence of both dyslipidemia and hypertension in laboratory and administrative databases. Many of these 1548 patients were not eligible for screening: Twenty-five percent already had diagnosed diabetes; 41% had been screened for diabetes in the past year; and 3% had died, disenrolled, or changed clinics before screening commenced. The remaining 30% (n = 469) were invited for diabetes screening. RESULTS: Of the 469 high-risk patients invited, 206 (44%) initiated screening; 176 (38%) completed diabetes screening. Five new patients with diabetes were identified in this high-risk group (one from the random glucose test and four from the glucose tolerance test). One new patient with diabetes was identified for every 40 high-risk patients screened. The program cost $4064 per new case of diabetes identified (screening costs alone). CONCLUSION: In this high-risk managed care population, the yield and acceptability of systematic diabetes screening were low, and the costs were relatively high. The acceptability of office-based diabetes screening may be improved by using a one-step screening test, such as glycosylated hemoglobin, during routine visits.

A comparison of costs of universal versus targeted lead screening for young children.

The purposes of this study were to compare universal blood lead screening for young children versus targeting by a risk assessment questionnaire and to examine the cost implications of each approach. Costs reflect the total number of blood tests required and cost of specimen collection, handling, and testing per elevated case. The setting included the metropolitan areas of Minneapolis and St. Paul, Minnesota. Children (N=9603) from 17 community organizations had blood tests. In addition, each child's parent or guardian completed a questionnaire assessing potential risk for lead poisoning. Four different screening approaches are presented. Each screening approach is presented with associated costs of overall screening and cost per child identified at blood levels of >/=10 microg/dl (N=1140) and >/=15 microg/dl (N=317). Based on the screening strategy selected and an estimate of $17 per blood test, total screening costs ranged from $91,596 to $165,945. The cost per child identified with elevated lead levels ranged from $361 to $523 at >/=15 and $105 to $146 at >/=10. Nine to 13% of children would not have been detected by policies other than universal screening. A geographically based approach was able to detect 90% of children with elevated blood levels at two-thirds the cost of universal screening. Blood tests would be taken for all children living within city limits. Those residing elsewhere would be tested only if answers to questionnaire items pertaining to age of housing, prior history of lead poisoning, or eating paint chips indicated risk. The new CDC guidelines suggest that screening be based on an assessment of housing, population demographics, and community risk and resources. This paper presents such an assessment.

Is having a regular provider of diabetes care related to intensity of care and glycemic control?

BACKGROUND: We investigated whether having a regular health care provider for diabetes was related to the intensity of care, use of preventive services, or glycemic control in a well-defined population of adults with diabetes. METHODS: Adults with diabetes who were continuously enrolled in a health maintenance organization (HMO) for 1 year were identified by diagnostic and pharmacy databases (estimated sensitivity = 0.91, positive predictive value = 0.94). In a stratified random sample, 1828 patients were sent a survey by mail that had a corrected response rate of 85.6%. Further data on utilization of services and glycosylated hemoglobin values were obtained from administrative databases and linked to survey responses. RESULTS: HMO members who reported having a regular health care provider (RP) for their diabetes (N = 1243) were comparable with those (N = 144) who denied having such a provider (NRP) in age, race, sex, comorbidity, and years of education, but had longer-duration diabetes (10.9 years vs 8.3 years; P = .002). After adjusting for age, sex, education level, duration of diabetes, and type of HMO clinic (owned vs contracted), RP subjects were more likely than NRPs (all P < .001) to follow a special diet for patients with diabetes (55% vs 33%), regularly monitor glucose levels at home (68% vs 47%), have greater frequency of glycosylated hemoglobin (Hb A1c) testing (65% vs 38%), have more foot examinations (42% vs 17%), have recommended cholesterol checks (77% vs 63%), and have had a recent preventive examination (86% vs 68%). Smaller differences favoring having a regular provider were noted for insulin use (48% vs 33%, odds ratio [OR] = 1.71, P = .013), for an influenza immunization within 1 year (65% vs 51%, P = .029), and for dilated retinal examinations (64% vs 51%, P < .027). No differences between groups were noted for dental checkups (69% vs 67%, P = .724) or likelihood of endocrinology referral (17% vs 10%, P = .104). Mean Hb A1c level was 8.2% (normal is < 6.1%) in the RP group and 8.6% in the NRP group (P = .182). Twelve percent of RPs and 24% of NRPs had an Hb A1c level of greater than 10% (chi 2 = 3.7, OR = 0.48, P = .05) after adjusting for age, sex, duration of diabetes, and education level. CONCLUSIONS: After adjustment for case mix, patients with diabetes who identified a regular primary health care provider for their diabetes were more likely to receive most recommended elements of diabetes care and to have better glycemic control than patients without such a provider. This effect was partially, but not completely, mediated by a higher number of clinic visits for those with a regular health care provider. Innovators seeking to improve diabetes care should be mindful of the relationship between having a regular primary health care provider and the quality of diabetes care.

Identifying diabetes mellitus or heart disease among health maintenance organization members: sensitivity, specificity, predictive value, and cost of survey and database methods.

We conducted a study of the sensitivity, specificity, positive predictive value, and cost of two methods of identifying diagnosed diabetes mellitus or heart disease among members of a health maintenance organization (HMO). Among 3186 adult HMO members who were attending one primary care clinic, 2326 were reached for a telephone survey (efficiency = 0.73). Among these members, 1991 answered standardized questions to ascertain whether they had diabetes or heart disease (corrected response rate = 0.85). Linkage was then made to computerized diagnostic databases. By means of both a database method and a survey method, the 1976 members with complete data for analysis were classified as having or not having diabetes or heart disease. When results with the two methods disagreed, charts were reviewed to confirm the presence or absence of diabetes or heart disease. Diabetes was identified among 4.7% of adult members, and heart disease was identified among 3.7%. Identification of diabetes differed between the database method and the survey method (sensitivity 0.91 vs 0.98, specificity 0.99 vs 0.99, positive predictive value 0.94 vs 0.83). Identification of heart attach history was similar for the database method and the survey method (sensitivity 0.89 vs 0.95, specificity 0.99 vs 0.99, positive predictive value 0.79 vs 0.81). The cost of obtaining data was $13.50 per member for the survey method and $0.30 per member for the database method. Database methods or survey methods of identifying selected chronic diseases among HMO members may be acceptable for various purposes, but database identification methods appear to be less expensive and provide information on a higher proportion of HMO members than do survey methods. Accurate identification of chronic diseases among patients supports clinic-level measures for clinical improvement, research, and accountability.

Using continuous quality improvement to improve diabetes care in populations: the IDEAL model. Improving care for Diabetics through Empowerment Active collaboration and Leadership.

BACKGROUND: The care of patients with chronic diseases, especially those with diabetes mellitus, has been less than ideal. However, despite clear national guidelines, various examples of better care models, and multiple attempts to improve care, an effective process for facilitating and replicating diabetes care improvements in typical primary care practices has been elusive. METHODS: On the basis of the approach and lessons from developmental work at the Minnesota Diabetes Control Program and a trial of continuous quality improvement for clinical preventive services (IMPROVE), a clinic-based intervention processes (IDEAL) has been developed to improve the system and process of care for patients with diabetes as a model for all chronic diseases. The intervention incorporates facilitation of leadership actions in support of change, training for the leader and facilitator of an intraclinic multidisciplinary continuous quality improvement (CQI) team, and consultative and networking support of the change process. Each element of this intervention emphasizes a seven-step process improvement approach and a system for care of patients with diabetes. This model is being developed and tested in a unique partnership between the Minnesota Department of Health and HealthPartners, a large managed care organization (MCO). RESULTS: A prepilot demonstration has succeeded in improving glycemic control, three primary care clinics affiliated with HealthPartners have succeeded in a pilot of the intervention, and an additional 13 clinics are participating in a randomized controlled trial of a refined intervention. CONCLUSIONS: The IDEAL model holds promise for substantial improvements in care, not only for diabetes but for all chronic diseases and for other settings.