Data Accuracy in Medical Record Abstraction

Clinical Research Data Quality Literature Review and Pooled Analysis We present a literature review and secondary analysis of data accuracy in clinical research and related secondary data uses. A total of 93 papers meeting our inclusion criteria were categorized according to the data processing methods. Quantitative data accuracy information was abstracted from the articles and pooled. Our analysis demonstrates that the accuracy associated with data processing methods varies widely, with error rates ranging from 2 errors per 10,000 files to 5019 errors per 10,000 fields. Medical record abstraction was associated with the highest error rates (70–5019 errors per 10,000 fields). Data entered and processed at healthcare facilities had comparable error rates to data processed at central data processing centers. Error rates for data processed with single entry in the presence of on-screen checks were comparable to double entered data. While data processing and cleaning methods may explain a significant amount of the variability in data accuracy, additional factors not resolvable here likely exist. Defining Data Quality for Clinical Research: A Concept Analysis Despite notable previous attempts by experts to define data quality, the concept remains ambiguous and subject to the vagaries of natural language. This current lack of clarity continues to hamper research related to data quality issues. We present a formal concept analysis of data quality, which builds on and synthesizes previously published work. We further posit that discipline-level specificity may be required to achieve the desired definitional clarity. To this end, we combine work from the clinical research domain with findings from the general data quality literature to produce a discipline-specific definition and operationalization for data quality in clinical research. While the results are helpful to clinical research, the methodology of concept analysis may be useful in other fields to clarify data quality attributes and to achieve operational definitions. Medical Record Abstractor’s Perceptions of Factors Impacting the Accuracy of Abstracted Data Medical record abstraction (MRA) is known to be a significant source of data errors in secondary data uses. Factors impacting the accuracy of abstracted data are not reported consistently in the literature. Two Delphi processes were conducted with experienced medical record abstractors to assess abstractor’s perceptions about the factors. The Delphi process identified 9 factors that were not found in the literature, and differed with the literature by 5 factors in the top 25%. The Delphi results refuted seven factors reported in the literature as impacting the quality of abstracted data. The results provide insight into and indicate content validity of a significant number of the factors reported in the literature. Further, the results indicate general consistency between the perceptions of clinical research medical record abstractors and registry and quality improvement abstractors. Distributed Cognition Artifacts on Clinical Research Data Collection Forms Medical record abstraction, a primary mode of data collection in secondary data use, is associated with high error rates. Distributed cognition in medical record abstraction has not been studied as a possible explanation for abstraction errors. We employed the theory of distributed representation and representational analysis to systematically evaluate cognitive demands in medical record abstraction and the extent of external cognitive support employed in a sample of clinical research data collection forms. We show that the cognitive load required for abstraction in 61% of the sampled data elements was high, exceedingly so in 9%. Further, the data collection forms did not support external cognition for the most complex data elements. High working memory demands are a possible explanation for the association of data errors with data elements requiring abstractor interpretation, comparison, mapping or calculation. The representational analysis used here can be used to identify data elements with high cognitive demands.

Does Immediate Access to Birth Control Help Prevent Pregnancy? A Comparison of Onsite Provision Versus Off Campus Referral for Contraception at Two School-Based Clinics

PURPOSE: The purpose of this study was to assess the impact of different policies on access to hormonal contraception and pregnancy rates at two high school-based clinics. METHODS: Two clinics in high schools (Schools A and B), located in a large urban district in the southwest US, provide primary medical care to enrolled students with parental consent; the majority of whom have no health insurance coverage. The hormonal contraceptive dispensing policy of at School clinic A involves providing barrier, hormonal and emergency contraceptive services on site. School clinic B uses a referral policy that directs students to obtain contraception at an off-campus affiliated family planning clinic. Baseline data (age, race and history of prior pregnancy) on female students seeking hormonal contraception at the two clinics between 9/2008-12/2009 were extracted from an electronic administrative database (AHLERS Integrated System). Data on birth control use and pregnancy tests for each student was then tracked electronically through 3/31/2010. The outcomes measures were accessing hormonal contraception and positive pregnancy tests at any point during or after birth control use were started through 12/2009. The appointment keeping rate for contraceptive services and the overall pregnancy rates were compared between the two schools. In addition the pregnancy rates were compared between the two schools for students with and without a prior history of pregnancy. RESULTS: School clinic A: 79 students sought hormonal contraception; mean age 17.5 years; 68% were > 18 years; 77% were Hispanic; and 20% reported prior pregnancy. The mean duration of the observation period was 13 months (4-19 months). All 79 students received hormonal contraception (65% pill and 35% long acting progestin injection) onsite. During the observation period, the overall pregnancy rate was 6% (5/79); 4.7% (3/63) among students with no prior pregnancy. School clinic B: 40 students sought hormonal contraception; mean age 17.5 years; 52% > 18 years; 88 % were Hispanic; and 7.5% reported prior pregnancy. All 40 students were referred to the affiliated clinic. The mean duration of the observation period was 11.9 months (4-19 months). 50% (20) kept their appointment. Pills were dispensed to 85% (17/20) and 15% (3/20) received long acting progestin injection. The overall pregnancy rate was 20% (8/40); 21.6% (8/37) among students with no prior pregnancy. A significantly higher frequency of students seeking hormonal contraception kept their initial appointment for birth control at the school dispensing onsite contraception compared to the school with a referral policy for contraception (p<0.05). The pregnancy rate was significantly higher for the school with a referral policy for contraception compared to the school with onsite contraceptive services (p< 0.05). The pregnancy rate was also significantly higher for students without a prior history of pregnancy in the school with a referral policy for contraception (21.6%) versus the school with onsite contraceptive services (4.7%) (p< 0.05). CONCLUSION: This preliminary study showed that School clinic B with a referral policy had a lower appointment keeping rate for contraceptive services and a higher pregnancy rate than School clinic A with on-site contraceptive services. An on-site dispensing policy for hormonal contraceptives at high school-based health clinics may be a convenient and effective approach to prevent unintended first and repeat pregnancies among adolescents who seek hormonal contraception. This study has strong implications for reproductive health policy, especially as directed toward high-risk teenage populations.