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Medical Record Data (medical + record_data)
Selected AbstractsCombining Information from Cancer Registry and Medical Records Data to Improve Analyses of Adjuvant Cancer TherapiesBIOMETRICS, Issue 3 2009Yulei He Summary Cancer registry records contain valuable data on provision of adjuvant therapies for cancer patients. Previous studies, however, have shown that these therapies are underreported in registry systems. Hence direct use of the registry data may lead to invalid analysis results. We propose first to impute correct treatment status, borrowing information from an additional source such as medical records data collected in a validation sample, and then to analyze the multiply imputed data, as in Yucel and Zaslavsky (2005,,Journal of the American Statistical Association,100, 1123,1132). We extend their models to multiple therapies using multivariate probit models with random effects. Our model takes into account the associations among different therapies in both administration and probability of reporting, as well as the multilevel structure (patients clustered within hospitals) of registry data. We use Gibbs sampling to estimate model parameters and impute treatment status. The proposed methodology is applied to the data from the Quality of Cancer Care project, in which stage II or III colorectal cancer patients were eligible to receive adjuvant chemotherapy and radiation therapy. [source] Estimates of Pregnancies Averted Through California's Family Planning Waiver Program in 2002PERSPECTIVES ON SEXUAL AND REPRODUCTIVE HEALTH, Issue 3 2006Diana Greene Foster CONTEXT: During its first year of operation (1997-1998), California's family planning program, Family PACT, helped more than 750,000 clients to avert an estimated 108,000 pregnancies. Given subsequent increases in the numbers of clients served and contraceptive methods offered by the program, updated estimates of its impact on fertility are needed. METHODS: Claims data on contraceptives dispensed were used to estimate the number of pregnancies experienced by women in the program in 2002. Medical record data on methods used prior to enrollment were used to predict client fertility in the absence of the program. Further analyses examined the sensitivity of these estimates to alternative assumptions about contraceptive failure rates, contraceptive continuation and contraceptive use in the absence of program services. RESULTS: Almost 6.4 million woman-months of contraception, provided primarily by oral contraceptives (57%), barrier methods (19%) and the injectable (18%), were dispensed through Family PACT during 2002. As a result, an estimated 205,000 pregnancies,which would have resulted in 79,000 abortions and 94,000 births, including 21,400 births to adolescents,were averted. Changing the base assumptions regarding contraceptive failure rates or method use had relatively small effects on the estimates, whereas assuming that clients would use no contraceptives in the absence of Family PACT nearly tripled the estimate of pregnancies averted. CONCLUSIONS: Because all contraceptive methods substantially reduce the risk of pregnancy, Family PACT'S impact on preventing pregnancy lies primarily in providing contraceptives to women who would otherwise not use any method. [source] Prenatal drug use and the production of infant healthHEALTH ECONOMICS, Issue 4 2007Kelly Noonan Abstract We estimate the effect of illicit drug use during pregnancy on two measures of poor infant health: low birth weight and abnormal infant health conditions. We use data from a national longitudinal study of urban parents that includes postpartum interviews with mothers, hospital medical record data on the mothers and their newborns, and information about the neighborhood in which the mother resides. We address the potential endogeneity of prenatal drug use. Depending on how prenatal drug use is measured, we find that it increases low birth weight by 4,6 percentage points and that it increases the likelihood of an abnormal infant health condition by 7,12 percentage points. Copyright © 2006 John Wiley & Sons, Ltd. [source] Measuring the Quality of Diabetes Care Using Administrative Data: Is There Bias?HEALTH SERVICES RESEARCH, Issue 6p1 2003Nancy L. Keating Objectives. Health care organizations often measure processes of care using only administrative data. We assessed whether measuring processes of diabetes care using administrative data without medical record data is likely to underdetect compliance with accepted standards for certain groups of patients. Data Sources/Study Setting. Assessment of quality indicators during 1998 using administrative and medical records data for a cohort of 1,335 diabetic patients enrolled in three Minnesota health plans. Study Design. Cross-sectional retrospective study assessing hemoglobin A1c testing, LDL cholesterol testing, and retinopathy screening from the two data sources. Analyses examined whether patient or clinic characteristics were associated with underdetection of quality indicators when administrative data were not supplemented with medical record data. Data Collection/Extraction Methods. The health plans provided administrative data, and trained abstractors collected medical records data. Principal Findings. Quality indicators that would be identified if administrative data were supplemented with medical records data are often not identified using administrative data alone. In adjusted analyses, older patients were more likely to have hemoglobin A1c testing underdetected in administrative data (compared to patients <45 years, OR 2.95, 95 percent CI 1.09 to 7.96 for patients 65 to 74 years, and OR 4.20, 95 percent CI 1.81 to 9.77 for patients 75 years and older). Black patients were more likely than white patients to have retinopathy screening underdetected using administrative data (2.57, 95 percent CI 1.16 to 5.70). Patients in different health plans also differed in the likelihood of having quality indicators underdetected. Conclusions. Diabetes quality indicators may be underdetected more frequently for elderly and black patients and the physicians, clinics, and plans who care for such patients when quality measurement is based on administrative data alone. This suggests that providers who care for such patients may be disproportionately affected by public release of such data or by its use in determining the magnitude of financial incentives. [source] Development and Validation of Quality Indicators for Dementia Diagnosis and Management in a Primary Care SettingJOURNAL OF AMERICAN GERIATRICS SOCIETY, Issue 3 2010Marieke Perry MD OBJECTIVES: To construct a set of quality indicators (QIs) for dementia diagnosis and management in a primary care setting. DESIGN: RAND modified Delphi method, including a postal survey, a stakeholders consensus meeting, a scientific expert consensus meeting, and a demonstration project. SETTING: Primary care. PARTICIPANTS: General practitioners (GPs), primary care nurses (PCNs), and informal caregivers (ICs) in postal survey and stakeholders consensus meeting. Eight national dementia experts in scientific consensus meeting. Thirteen GPs in the demonstration project. MEASUREMENTS: Mean face validity and feasibility scores. Compliance rates using GPs' electronic medical record data. RESULTS: The initial set consisted of 31 QIs. Most indicators showed moderate or good face validity and feasibility scores. Consensus panels reduced the preliminary set used in the demonstration project to 24 QIs. The overall compliance to the QIs was 45.3%. Discriminative validity of the set was good; significant differences in adherence were found between GPs with high and low levels of patients aged 65 and older in their practice, with and without PCNs, and with positive and negative attitudes toward dementia (all P<.05). Based on the demonstration project, one QI was excluded. The final set consisted of 23 QIs; 15 QIs contained innovative quality criteria on collaboration between GPs and PCNs, referral criteria, and assessment of caregivers' needs. CONCLUSION: This new set of dementia QIs is feasible, reliable, and valid and can be used to improve primary dementia care. Because of the innovative quality criteria, the set is complementary to the existing dementia QIs. [source] Comparisons of Self-Reported and Chart-Identified Chronic Diseases in Inner-City SeniorsJOURNAL OF AMERICAN GERIATRICS SOCIETY, Issue 7 2009John Leikauf BA OBJECTIVES: To examine agreement between self-report of chronic disease and medical record data for inner-city seniors, their sensitivity and specificity, and the association between patient characteristics and accuracy of self-reports. DESIGN: Cross-sectional analysis. SETTING: Two hospital-based primary care practices serving a low-income inner-city population. PARTICIPANTS: Adults aged 65 and older (n=323). MEASURES: Data on self-reported asthma, depression, diabetes mellitus, and hypertension were collected through interviewer-administered surveys (in English and Spanish) and chart abstraction. Chart-based disease was defined in two ways: physician documentation and physician documentation plus use of a medication to treat that condition. Sensitivity, specificity, and agreement were calculated. Univariate and multivariable regression analyses were used to determine the associations between patient characteristics and patient,chart agreement. RESULTS: Agreement between self-report and chart data was high for diabetes mellitus (kappa=0.94) intermediate for asthma (kappa=0.66), and hypertension (kappa=0.54) and low for depression (kappa=0.4). Sensitivity and specificity were high for diabetes mellitus (0.99 and 0.96, respectively) and low for depression (0.74 and 0.72, respectively). Specificity for hypertension was lowest (0.67). Age, education, health literacy, and other patient characteristics did not have clear associations across conditions. CONCLUSION: Self-reports may be most reliable for diabetes mellitus and least reliable for depression for surveys involving older, inner-city adults. Survey research with older adults should include confirmatory data when assessing presence of depression, hypertension, and asthma. [source] Quality of Care for Acute Myocardial Infarction in Elderly Patients with Alcohol-Related DiagnosesALCOHOLISM, Issue 1 2006David A. Fiellin Background: Elderly adults with alcohol-related diagnoses represent a vulnerable population that may receive lower quality of treatment during hospitalization for acute myocardial infarction. We sought to determine whether elderly patients with alcohol-related diagnoses are less likely to receive standard indicators of quality care for acute myocardial infarction. Methods: We conducted a retrospective cohort analysis using administrative and medical record data from the Cooperative Cardiovascular Project. Subjects were Medicare beneficiaries with a confirmed principal discharge diagnosis of acute myocardial infarction from all acute care hospitals in the United States over an 8-month period. Our primary outcome was the receipt of 7 guideline-recommended care measures among all eligible patients and patients who were ideal candidates for a given measure. Results: In all, 1,284 (1%) of the 155,026 eligible patients met criteria for an alcohol-related diagnosis. Among the alcohol-related diagnoses, 1,077/1,284 (84%) were for the diagnoses of alcohol dependence or alcohol abuse. Patients with alcohol-related diagnoses were less likely than those without alcohol-related diagnoses to receive ,-blockers at the time of discharge (55% vs. 60%, p=0.02). We found no other significant differences in performance of the quality indicators after stratifying by indication and adjustment for baseline characteristics. Conclusions: Alcohol-related diagnoses are not a barrier to receiving most quality of care measures in elderly patients hospitalized for acute myocardial infarction. [source] Measuring the Quality of Diabetes Care Using Administrative Data: Is There Bias?HEALTH SERVICES RESEARCH, Issue 6p1 2003Nancy L. Keating Objectives. Health care organizations often measure processes of care using only administrative data. We assessed whether measuring processes of diabetes care using administrative data without medical record data is likely to underdetect compliance with accepted standards for certain groups of patients. Data Sources/Study Setting. Assessment of quality indicators during 1998 using administrative and medical records data for a cohort of 1,335 diabetic patients enrolled in three Minnesota health plans. Study Design. Cross-sectional retrospective study assessing hemoglobin A1c testing, LDL cholesterol testing, and retinopathy screening from the two data sources. Analyses examined whether patient or clinic characteristics were associated with underdetection of quality indicators when administrative data were not supplemented with medical record data. Data Collection/Extraction Methods. The health plans provided administrative data, and trained abstractors collected medical records data. Principal Findings. Quality indicators that would be identified if administrative data were supplemented with medical records data are often not identified using administrative data alone. In adjusted analyses, older patients were more likely to have hemoglobin A1c testing underdetected in administrative data (compared to patients <45 years, OR 2.95, 95 percent CI 1.09 to 7.96 for patients 65 to 74 years, and OR 4.20, 95 percent CI 1.81 to 9.77 for patients 75 years and older). Black patients were more likely than white patients to have retinopathy screening underdetected using administrative data (2.57, 95 percent CI 1.16 to 5.70). Patients in different health plans also differed in the likelihood of having quality indicators underdetected. Conclusions. Diabetes quality indicators may be underdetected more frequently for elderly and black patients and the physicians, clinics, and plans who care for such patients when quality measurement is based on administrative data alone. This suggests that providers who care for such patients may be disproportionately affected by public release of such data or by its use in determining the magnitude of financial incentives. [source] Combining Information from Cancer Registry and Medical Records Data to Improve Analyses of Adjuvant Cancer TherapiesBIOMETRICS, Issue 3 2009Yulei He Summary Cancer registry records contain valuable data on provision of adjuvant therapies for cancer patients. Previous studies, however, have shown that these therapies are underreported in registry systems. Hence direct use of the registry data may lead to invalid analysis results. We propose first to impute correct treatment status, borrowing information from an additional source such as medical records data collected in a validation sample, and then to analyze the multiply imputed data, as in Yucel and Zaslavsky (2005,,Journal of the American Statistical Association,100, 1123,1132). We extend their models to multiple therapies using multivariate probit models with random effects. Our model takes into account the associations among different therapies in both administration and probability of reporting, as well as the multilevel structure (patients clustered within hospitals) of registry data. We use Gibbs sampling to estimate model parameters and impute treatment status. The proposed methodology is applied to the data from the Quality of Cancer Care project, in which stage II or III colorectal cancer patients were eligible to receive adjuvant chemotherapy and radiation therapy. [source] | ||||||||||