Patient attitudes toward using computers to improve health services delivery

BACKGROUND: The aim of this study was to examine the acceptability of point of care computerized prompts to improve health services delivery among a sample of primary care patients. METHODS: Primary data collection. Cross-sectional survey. Patients were surveyed after their visit with a primary care provider. Data were obtained from patients of ten community-based primary care practices in the spring of 2001. RESULTS: Almost all patients reported that they would support using a computer before each visit to prompt their doctor to: "do health screening tests" (92%), "counsel about health behaviors (like diet and exercise)" (92%) and "change treatments for health conditions" (86%). In multivariate testing, the only variable that was associated with acceptability of the point of care computerized prompts was patient's confidence in their ability to answer questions about their health using a computer (beta = 0.39, p = .001). Concerns about data security were expressed by 36.3% of subjects, but were not related to acceptability of the prompts. CONCLUSIONS: Support for using computers to generate point of care prompts to improve quality-oriented processes of care was high in our sample, but may be contingent on patients feeling familiar with their personal medical history

Conversion of urine protein-creatinine ratio or urine dipstick to urine albumin-creatinine ratio for use in CKD screening and prognosis

Background: Although measuring albuminuria is the preferred method for defining and staging chronic kidney disease (CKD), total urine protein or dipstick protein is often measured instead. Objective: To develop equations for converting urine protein–creatinine ratio (PCR) and dipstick protein to urine albumin–creatinine ratio (ACR) and to test their diagnostic accuracy in CKD screening and staging. Design: Individual participant–based meta-analysis. Setting: 12 research and 21 clinical cohorts. Participants: 919 383 adults with same-day measures of ACR and PCR or dipstick protein. Measurements: Equations to convert urine PCR and dipstick protein to ACR were developed and tested for purposes of CKD screening (ACR ≥30 mg/g) and staging (stage A2: ACR of 30 to 299 mg/g; stage A3: ACR ≥300 mg/g). Results: Median ACR was 14 mg/g (25th to 75th percentile of cohorts, 5 to 25 mg/g). The association between PCR and ACR was inconsistent for PCR values less than 50 mg/g. For higher PCR values, the PCR conversion equations demonstrated moderate sensitivity (91%, 75%, and 87%) and specificity (87%, 89%, and 98%) for screening (ACR >30 mg/g) and classification into stages A2 and A3, respectively. Urine dipstick categories of trace or greater, trace to +, and ++ for screening for ACR values greater than 30 mg/g and classification into stages A2 and A3, respectively, had moderate sensitivity (62%, 36%, and 78%) and high specificity (88%, 88%, and 98%). For individual risk prediction, the estimated 2-year 4-variable kidney failure risk equation using predicted ACR from PCR had discrimination similar to that of using observed ACR. Limitation: Diverse methods of ACR and PCR quantification were used; measurements were not always performed in the same urine sample. Conclusion: Urine ACR is the preferred measure of albuminuria; however, if ACR is not available, predicted ACR from PCR or urine dipstick protein may help in CKD screening, staging, and prognosis. Primary Funding Source: National Institute of Diabetes and Digestive and Kidney Diseases and National Kidney Foundation