Using electronic health record data for substance use Screening, Brief Intervention, and Referral to Treatment among adults with type 2 diabetes: Design of a National Drug Abuse Treatment Clinical Trials Network study.

BACKGROUND: The Affordable Care Act encourages healthcare systems to integrate behavioral and medical healthcare, as well as to employ electronic health records (EHRs) for health information exchange and quality improvement. Pragmatic research paradigms that employ EHRs in research are needed to produce clinical evidence in real-world medical settings for informing learning healthcare systems. Adults with comorbid diabetes and substance use disorders (SUDs) tend to use costly inpatient treatments; however, there is a lack of empirical data on implementing behavioral healthcare to reduce health risk in adults with high-risk diabetes. Given the complexity of high-risk patients' medical problems and the cost of conducting randomized trials, a feasibility project is warranted to guide practical study designs. METHODS: We describe the study design, which explores the feasibility of implementing substance use Screening, Brief Intervention, and Referral to Treatment (SBIRT) among adults with high-risk type 2 diabetes mellitus (T2DM) within a home-based primary care setting. Our study includes the development of an integrated EHR datamart to identify eligible patients and collect diabetes healthcare data, and the use of a geographic health information system to understand the social context in patients' communities. Analysis will examine recruitment, proportion of patients receiving brief intervention and/or referrals, substance use, SUD treatment use, diabetes outcomes, and retention. DISCUSSION: By capitalizing on an existing T2DM project that uses home-based primary care, our study results will provide timely clinical information to inform the designs and implementation of future SBIRT studies among adults with multiple medical conditions.

The accuracy and completeness for receipt of colorectal cancer care using Veterans Health Administration administrative data.

BACKGROUND: The National Comprehensive Cancer Network and the American Society of Clinical Oncology have established guidelines for the treatment and surveillance of colorectal cancer (CRC), respectively. Considering these guidelines, an accurate and efficient method is needed to measure receipt of care. METHODS: The accuracy and completeness of Veterans Health Administration (VA) administrative data were assessed by comparing them with data manually abstracted during the Colorectal Cancer Care Collaborative (C4) quality improvement initiative for 618 patients with stage I-III CRC. RESULTS: The VA administrative data contained gender, marital, and birth information for all patients but race information was missing for 62.1% of patients. The percent agreement for demographic variables ranged from 98.1-100%. The kappa statistic for receipt of treatments ranged from 0.21 to 0.60 and there was a 96.9% agreement for the date of surgical resection. The percentage of post-diagnosis surveillance events in C4 also in VA administrative data were 76.0% for colonoscopy, 84.6% for physician visit, and 26.3% for carcinoembryonic antigen (CEA) test. CONCLUSIONS: VA administrative data are accurate and complete for non-race demographic variables, receipt of CRC treatment, colonoscopy, and physician visits; but alternative data sources may be necessary to capture patient race and receipt of CEA tests.

Investigating the efficiency of fitting Coxian phase-type distributions to health care data

Coxian phase-type distributions are becoming a popular means of representing survival times within a health care environment. They are favoured as they show a distribution as a system of phases and can allow for an easy visual representation of the rate of flow of patients through a system. Difficulties arise, however, in determining the parameter estimates of the Coxian phase-type distribution. This paper examines ways of making the fitting of the Coxian phase-type distribution less cumbersome by outlining different software packages and algorithms available to perform the fit and assessing their capabilities through a number of performance measures. The performance measures rate each of the methods and help in identifying the more efficient. Conclusions drawn from these performance measures suggest SAS to be the most robust package. It has a high rate of convergence in each of the four example model fits considered, short computational times, detailed output, convergence criteria options, along with a succinct ability to switch between different algorithms.

A comparison of self-report and health care provider data to assess surveillance definitions of influenza-like illness in outpatients

Objective: Several surveillance definitions of influenza-like illness (ILI) have been proposed, based on the presence of symptoms. Symptom data can be obtained from patients, medical records, or both. Past research has found that agreements between health record data and self-report are variable depending on the specific symptom. Therefore, we aimed to explore the implications of using data on influenza symptoms extracted from medical records, similar data collected prospectively from outpatients, and the combined data from both sources as predictors of laboratory-confirmed influenza. Methods: Using data from the Hutterite Influenza Prevention Study, we calculated: 1) the sensitivity, specificity and predictive values of individual symptoms within surveillance definitions; 2) how frequently surveillance definitions correlated to laboratory-confirmed influenza; and 3) the predictive value of surveillance definitions. Results: Of the 176 participants with reports from participants and medical records, 142 (81%) were tested for influenza and 37 (26%) were PCR positive for influenza. Fever (alone) and fever combined with cough and/or sore throat were highly correlated with being PCR positive for influenza for all data sources. ILI surveillance definitions, based on symptom data from medical records only or from both medical records and self-report, were better predictors of laboratory-confirmed influenza with higher odds ratios and positive predictive values. Discussion: The choice of data source to determine ILI will depend on the patient population, outcome of interest, availability of data source, and use for clinical decision making, research, or surveillance. © Canadian Public Health Association, 2012.

Use of the child health utility and strengths and difficulties outcome measures in economic evaluations of school-based interventions: data from a cluster-randomised controlled trial in Northern Ireland

Background There is growing evidence linking early social and emotional wellbeing to later academic performance and various health outcomes including mental health. An economic evaluation was designed alongside the Roots of Empathy cluster-randomised trial evaluation, which is a school-based intervention for improving pupils’ social and emotional wellbeing. Exploration of the relevance of the Strengths and Diffi culties Questionnaire (SDQ) and Child Health Utility 9D (CHU9D) in school-based health economic evaluations is warranted. The SDQ is a behavioural screening questionnaire for 4–17-year-old children, consisting of a total diffi culties score, and also prosocial behaviour,
which aims to identify positive aspects of behaviour. The CHU9D is a generic preference-based health-related quality of life instrument for 7–17-year-old children.

Large panel-survey data demonstrated country-level and ethnic minority variation in consent for health record linkage

Objectives
To investigate individual, household and country variation in consent to health record linkage.

Study Design and Setting
Data from 50,994 individuals aged 16-74 years recruited to wave 1 of a large UK general purpose household survey (January 2009 – December 2010) were analysed using multi-level logistic regression models.

Results
Overall, 70.7% of respondents consented to record linkage. Younger age, marriage, tenure, car ownership and education were all significantly associated with consent, though there was little deviation from 70% in subgroups defined by these variables. There were small increases in consent rates in individuals with poor health when defined by self-reported long term limiting illness (adjusted OR 1.11; 95%CIs 1.06, 1.16), less so when defined by General Health Questionnaire score (adjusted OR=1.05; 95%CIs 1.00, 1.10), but the range in absolute consent rates between categories was generally less than 10%. Larger differences were observed for those of non-white ethnicity who were 38% less likely to consent (adjusted OR 0.62; 95%CIs 0.59, 0.66). Consent was higher in Scotland than England (adjusted OR 1.17; 95%CIs 1.06, 1.29) but lower in Northern Ireland (adjusted OR 0.56; 95%CIs 0.50, 0.63).

Conclusion
The modest overall level of systematic bias in consent to record linkage provides reassurance for record linkage potential in general purpose household surveys. However, the low consent rates amongst non-white ethnic minority survey respondents will further compound their low survey participation rates. The reason for the country-level variation requires further study.

Education, gender, and state-level disparities in the health of older Indians: Evidence from biomarker data

Using new biomarker data from the 2010 pilot round of the Longitudinal Aging Study in India (LASI), we investigate education, gender, and state-level disparities in health. We find that hemoglobin level, a marker for anemia, is lower for respondents with no schooling (0.7 g/dL less in the adjusted model) compared to those with some formal education and is also lower for females than for males (2.0 g/dL less in the adjusted model). In addition, we find that about one third of respondents in our sample aged 45 or older have high C-reaction protein (CRP) levels (>3 mg/L), an indicator of inflammation and a risk factor for cardiovascular disease. We find no evidence of educational or gender differences in CRP, but there are significant state-level disparities, with Kerala residents exhibiting the lowest CRP levels (a mean of 1.96 mg/L compared to 3.28 mg/L in Rajasthan, the state with the highest CRP). We use the Blinder–Oaxaca decomposition approach to explain group-level differences, and find that state-level disparities in CRP are mainly due to heterogeneity in the association of the observed characteristics of respondents with CRP, rather than differences in the distribution of endowments across the sampled state populations.

Address inaccuracy in health registration data: determinants and impacts

Access to demographic data that are complete, accurate and up-to-date is fundamental to many aspects of public health, government and academic work and for accurate interpretation of other databases. Health registration data are the prime source of demographic information for health and social care systems; for example, as an indicator of need, as a source of denominators to convert number of events into rates, or in the case of the residential address information as the basis for generating the call-recall invitation letters that are used for most screening programs (e.g. breast, colo-rectal and AAA screening). However, list inflation (ghosts, duplicates or emigrants) and a degree of address inaccuracy are recognised caveats with the health registration data and a recent NILS-related study on breast screening suggests that improved address accuracy might be a fast and efficient means of increasing screening uptake rates in cities and amongst deprived populations. In NI these data are collated by the BSO who uniquely in the UK also have access to data relating to prescribing, dental registrations and use of A&E services. These can be used to supplement the standard demographic and address information by (i) indicating patients who are alive and resident in NI and (ii) providing an independent source of probably improved address information. This study will use the NI Unique Property Reference Number (UPRN), rather than the addresses per se which are difficult to work with, to compare the addresses registered in the BSO with those addresses in the enumerated 2011 census. Assuming that the census is a more accurate source of address information for individuals, a comparison of the health registration addresses with those recorded at the census, the aim of the proposed study will be to (i) characterise the amount and distributions of these differences, (ii) to see what proportion of those who do not attend for screening did not actually receive an invitation letter because the addresses were incorrect, (iii) to determine how much of the social gradient (and urban/rural differences) in screening uptake are due to address inaccuracies, (iv) a comparison of timing of address changes at the BSO will provide information on the delays in updating of addresses.

Using administrative data to understand mental health in Northern Ireland:Results from two exemplar projects

Mental health is unevenly distributed in the Northern Ireland population. Administrative data on psychotropic medication prescribing is increasingly being used in research into population mental health. This paper illustrates how these data indicate concentrations of poor mental health in Northern Ireland, e.g. within deprived neighbourhoods, at interfaces, among older persons admitted to care homes and among persons bereaved through sudden death or suicide. This briefing also aims to widen the debate about mental health from a disorder/service paradigm to a whole population approach.

Modelling health state preference data using fixed and random effects models

The use of preference-based measures of health in the measurement of Health Related Quality of Life has become widely used in health economics. Hence, the development of preference-based measures of health has been a major concern for researchers throughout the world. This study aims to model health state preference data using a new preference-based measure of health (the SF- 6D) and to suggest alternative models for predicting health state utilities using fixed and random effects models. It also seeks to investigate the problems found in the SF-6D and to suggest eventual changes to it.