Faecal occult-blood screening in Burgundy.
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Aged↗
Biomedical subjects
Michael Pignone
Publications and source records attributed to Michael Pignone.
Identifying depression in primary care: a literature synthesis of case-finding instruments.
We evaluated the usefulness of case-finding instruments for identifying patients with major depression or dysthymia in primary care settings using English language literature from Medline, a specialized trials registry and bibliographies of selected papers. Studies were done in primary care settings with unselected patients and compared case-finding instruments with accepted diagnostic criterion standards for major depression were selected. A total of 16 case-finding instruments were assessed in 38 studies. More than 32,000 patients received screening with a case-finding instrument; approximately 12,900 of these received criterion standard assessment. Case-finding instruments ranged in length from 1 to 30 questions. Average administration times ranged from less than 2 min to 6 min. Median sensitivity for major depression was 85% (range 50% to 97%); median specificity was 74% (range 51% to 98%). No significant differences between instruments were found. However for individual instruments, estimates of sensitivity and specificity varied significantly between studies. For the combined diagnoses of major depression or dysthymia, overall sensitivity was 79% (CI, 74% to 83%) and overall specificity 75% (CI, 70% to 81%). Stratified analyses showed no significant effects on overall instrument performance for study methodology, criterion standard choice, or patient characteristics. We found that multiple instruments with reasonable operating characteristics are available to help primary care clinicians identify patients with major depression. Because operating characteristics of these instruments are similar, selection of a particular instrument should depend on issues such as feasibility, administration and scoring times, and the instruments' ability to serve additional purposes, such as monitoring severity or response to therapy.
Antidepressive Agents↗
The relationship between literacy and glycemic control in a diabetes disease-management program.
PURPOSE: This study examined the role of literacy in patients with poorly controlled diabetes who were participating in a diabetes management program that included low-literacy-oriented interventions. METHODS: A before-after analysis was performed of a pharmacist-led diabetes management program for 159 patients with type 2 diabetes and poor glycemic control (hemoglobin A1c [A1C] > or = 8.0%). Clinic-based pharmacists offered one-to-one education and medication management for these patients using techniques that did not require high literacy. Literacy was measured by the Rapid Estimate of Adult Literacy in Medicine (REALM) test and dichotomized at the 6th-grade level. The A1C values were collected prior to enrollment, at enrollment, and approximately 6 months after enrollment. RESULTS: Of the 111 patients with follow-up data, 55% had literacy levels at the 6th-grade level or below. Lower literacy was more common among African Americans, older patients, and patients who required medication assistance. There was no significant relationship between literacy status and A1C prior to enrollment or at enrollment. Over the 6-month study period, patients with low and high literacy had similar improvements in A1C. CONCLUSIONS: This diabetes care program, which used individualized teaching with low-literacy techniques, significantly improved A1C values independent of literacy status.
Age Factors↗
The Spoken Knowledge in Low Literacy in Diabetes scale: a diabetes knowledge scale for vulnerable patients.
PURPOSE: The purpose of this study was to develop and validate a new knowledge scale for patients with type 2 diabetes and poor literacy: the Spoken Knowledge in Low Literacy patients with Diabetes (SKILLD). METHODS: The authors evaluated the 10-item SKILLD among 217 patients with type 2 diabetes and poor glycemic control at an academic general medicine clinic. Internal reliability was measured using the Kuder-Richardson coefficient. Performance on the SKILLD was compared to patient socioeconomic status, literacy level, duration of diabetes, and glycated hemoglobin (A1C). RESULTS: Respondents' mean age was 55 years, and they had diabetes for an average of 8.4 years; 38% had less than a sixth-grade literacy level. The average score on the SKILLD was 49%. Less than one third of patients knew the signs of hypoglycemia or the normal fasting blood glucose range. The internal reliability of the SKILLD was good (0.72). Higher performance on the SKILLD was significantly correlated with higher income (r = 0.22), education level (r = 0.36), literacy status (r = 0.33), duration of diabetes (r = 0.30), and lower A1C (r = -0.16). When dichotomized, patients with low SKILLD scores (< or = 50%) had significantly higher A1C (11.2% vs 10.3%, P < .01). This difference remained significant when adjusted for covariates. CONCLUSION: The SKILLD demonstrated good internal consistency and validity. It revealed significant knowledge deficits and was associated with glycemic control. The SKILLD represents a practical scale for patients with diabetes and low literacy.
Adult↗
Pharmacist-led, primary care-based disease management improves hemoglobin A1c in high-risk patients with diabetes.
We developed and evaluated a comprehensive pharmacist-led, primary care-based diabetes disease management program for patients with Type 2 diabetes and poor glucose control at our academic general internal medicine practice. The primary goal of this program was to improve glucose control, as measured by hemoglobin A1c (HbA1c). Clinic-based pharmacists offered support to patients with diabetes through direct teaching about diabetes, frequent phone follow-up, medication algorithms, and use of a database that tracked patient outcomes and actively identified opportunities to improve care. From September 1999, to May 2000, 159 subjects were enrolled, and complete follow-up data were available for 138 (87%) patients. Baseline HbA1c averaged 10.8%, and after an average of 6 months of intervention, the mean reduction in HbA1c was 1.9 percentage points (95% confidence interval, 1.5-2.3). In predictive regression modeling, baseline HbA1c and new onset diabetes were associated with significant improvements in HbA1c. Age, race, gender, educational level, and provider status were not significant predictors of improvement. In conclusion, a pharmacist-based diabetes care program integrated into primary care practice significantly reduced HbA1c among patients with diabetes and poor glucose control.
Academic Medical Centers↗
Numeracy and the medical student's ability to interpret data.
CONTEXT: Although the ability to work with numbers is important to the practice of medicine, little is known about physician numeracy (basic skill with numbers). OBJECTIVE: To test medical students' numeracy and how it relates to the ability to interpret risk-reduction information. DESIGN: Randomized, cross-sectional survey. SAMPLE: 62 first-year medical students at the University of North Carolina at Chapel Hill medical school who attended a risk-communication seminar and had usable survey data (46% of the 134 students who received the survey). INTERVENTION: Students were given information about the baseline risk for developing a hypothetical disease and were randomly assigned to one of four risk-reduction presentations-relative risk reduction, absolute risk reduction, number needed to treat (NNT), or a combination of these three formats-about how two drugs would reduce this risk. OUTCOME MEASURES: Number of correct answers to three numeracy questions (stating that 500 heads would be expected in 1000 coin flips; converting "1% of 1000" to 10; and converting "1 in 1,000" to 0.1%). Correct data interpretation was judged with two tasks: a comparative task (i.e., state which drug provides greater benefit) and a quantitative task (i.e., calculate how much one of the drugs reduces disease risk). RESULTS: 77% of students answered all three numeracy questions correctly; 18% answered two correctly; and 5% answered one or none correctly. While 90% correctly stated which drug worked better, only 61% accurately interpreted the quantitative data. The ability to interpret data varied with numeracy: 71% of students who answered all three numeracy questions correctly also accurately interpreted the quantitative data, compared with 36% who answered two questions correctly and 0% who answered one or no questions correctly (P < 0.01). Correct quantitative interpretation was lower with the NNT format than with the other three formats (25% vs. 75%; P = 0.01). CONCLUSIONS: Almost one quarter of first-year medical students in our study had trouble performing basic numerical tasks. Those who had trouble also seemed to have difficulty interpreting medical data. This difficulty seemed to be exacerbated by presenting data in the NNT format.
Adult↗