A PROCESS FOR ACHIEVING COMPARABLE DATA FROM HETEROGENEOUS DATABASES

The current state of health and biomedicine includes an enormity of heterogeneous data ‘silos’, collected for different purposes and represented differently, that are presently impossible to share or analyze in toto. The greatest challenge for large-scale and meaningful analyses of health-related data is to achieve a uniform data representation for data extracted from heterogeneous source representations. Based upon an analysis and categorization of heterogeneities, a process for achieving comparable data content by using a uniform terminological representation is developed. This process addresses the types of representational heterogeneities that commonly arise in healthcare data integration problems. Specifically, this process uses a reference terminology, and associated "maps" to transform heterogeneous data to a standard representation for comparability and secondary use. The capture of quality and precision of the “maps” between local terms and reference terminology concepts enhances the meaning of the aggregated data, empowering end users with better-informed queries for subsequent analyses. A data integration case study in the domain of pediatric asthma illustrates the development and use of a reference terminology for creating comparable data from heterogeneous source representations. The contribution of this research is a generalized process for the integration of data from heterogeneous source representations, and this process can be applied and extended to other problems where heterogeneous data needs to be merged.

Automated soldier medical readiness: Prevalence of " medically not ready" using data from the electronic soldier readiness processing system (ESRP)

Identifying accurate numbers of soldiers determined to be medically not ready after completing soldier readiness processing may help inform Army leadership about ongoing pressures on the military involved in long conflict with regular deployment. In Army soldiers screened using the SRP checklist for deployment, what is the prevalence of soldiers determined to be medically not ready? Study group. 15,289 soldiers screened at all 25 Army deployment platform sites with the eSRP checklist over a 4-month period (June 20, 2009 to October 20, 2009). The data included for analysis included age, rank, component, gender and final deployment medical readiness status from MEDPROS database. Methods.^ This information was compiled and univariate analysis using chi-square was conducted for each of the key variables by medical readiness status. Results. Descriptive epidemiology Of the total sample 1548 (9.7%) were female and 14319 (90.2%) were male. Enlisted soldiers made up 13,543 (88.6%) of the sample and officers 1,746 (11.4%). In the sample, 1533 (10.0%) were soldiers over the age of 40 and 13756 (90.0%) were age 18-40. Reserve, National Guard and Active Duty made up 1,931 (12.6%), 2,942 (19.2%) and 10,416 (68.1%) respectively. Univariate analysis. Overall 1226 (8.0%) of the soldiers screened were determined to be medically not ready for deployment. Biggest predictive factor was female gender OR (2.8; 2.57-3.28) p<0.001. Followed by enlisted rank OR (2.01; 1.60-2.53) p<0.001. Reserve component OR (1.33; 1.16-1.53) p<0.001 and Guard OR (0.37; 0.30-0.46) p<0.001. For age > 40 demonstrated OR (1.2; 1.09-1.50) p<0.003. Overall the results underscore there may be key demographic groups relating to medical readiness that can be targeted with programs and funding to improve overall military medical readiness.^

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.

Cost-effectiveness of intensified interventions to control healthcare-associated MRSA infections -- A systematic literature review

Methicillin Resistant Staphylococcus aureus healthcare-associated infections (MRSA HAIs) are a major cause of morbidity in hospitalized patients. They pose great economic burden to hospitals caring for these patients. Intensified Interventions aim to control MRSA HAIs. Cost-effectiveness of Intensified Interventions is largely unclear. We performed a review of cost-effectiveness literature on Intensified Interventions , and provide a summary of study findings, the status of economic research in the area, and information that will help decision-makers at regional level and guide future research.^ We conducted literature search using electronic database PubMed, EBSCO, and The Cochrane Library. We limited our search to English articles published after 1999. We reviewed a total of 1,356 titles, and after applying our inclusion and exclusion criteria selected seven articles for our final review. We modified the Economic Evaluation Abstraction Form provided by CDC, and used this form to abstract data from studies.^ Of the seven selected articles two were cohort studies and the remaining five were modeling studies. They were done in various countries, in different study settings, and with different variations of the Intensified Intervention . Overall, six of the seven studies reported that Intensified Interventions were dominant or at least cost-effective in their study setting. This effect persisted on sensitivity testing.^ We identified many gaps in research in this field. The cost-effectiveness research in the field is mostly composed of modeling studies. The studies do not always clearly describe the intervention. The intervention and infection costs and the sources for these costs are not always explicit or are missing. In modeling studies, there is uncertainty associated with some key model inputs, but these inputs are not always identified. The models utilized in the modeling studies are not always tested for internal consistency or validity. Studies usually test the short term cost-effectiveness of Intensified Interventions but not the long results.^ Our study limitation was the inability to adjust for differences in study settings, intervention costs, disease costs, or effectiveness measures. Our study strength is the presentation of a focused literature review of Intensified Interventions in hospital settings. Through this study we provide information that will help decision makers at regional level, help guide future research, and might change clinical care and policies. ^

CHARACTERIZING, ASSESSING AND IMPROVING HEALTHCARE REFERRAL COMMUNICATION

Similar to other health care processes, referrals are susceptible to breakdowns. These breakdowns in the referral process can lead to poor continuity of care, slow diagnostic processes, delays and repetition of tests, patient and provider dissatisfaction, and can lead to a loss of confidence in providers. These facts and the necessity for a deeper understanding of referrals in healthcare served as the motivation to conduct a comprehensive study of referrals. The research began with the real problem and need to understand referral communication as a mean to improve patient care. Despite previous efforts to explain referrals and the dynamics and interrelations of the variables that influence referrals there is not a common, contemporary, and accepted definition of what a referral is in the health care context. The research agenda was guided by the need to explore referrals as an abstract concept by: 1) developing a conceptual definition of referrals, and 2) developing a model of referrals, to finally propose a 3) comprehensive research framework. This dissertation has resulted in a standard conceptual definition of referrals and a model of referrals. In addition a mixed-method framework to evaluate referrals was proposed, and finally a data driven model was developed to predict whether a referral would be approved or denied by a specialty service. The three manuscripts included in this dissertation present the basis for studying and assessing referrals using a common framework that should allow an easier comparative research agenda to improve referrals taking into account the context where referrals occur.

Towards a Hybrid Method to Categorize Interruptions and Activities in Healthcare

Objective Interruptions are known to have a negative impact on activity performance. Understanding how an interruption contributes to human error is limited because there is not a standard method for analyzing and classifying interruptions. Qualitative data are typically analyzed by either a deductive or an inductive method. Both methods have limitations. In this paper a hybrid method was developed that integrates deductive and inductive methods for the categorization of activities and interruptions recorded during an ethnographic study of physicians and registered nurses in a Level One Trauma Center. Understanding the effects of interruptions is important for designing and evaluating informatics tools in particular and for improving healthcare quality and patient safety in general. Method The hybrid method was developed using a deductive a priori classification framework with the provision of adding new categories discovered inductively in the data. The inductive process utilized line-by-line coding and constant comparison as stated in Grounded Theory. Results The categories of activities and interruptions were organized into a three-tiered hierarchy of activity. Validity and reliability of the categories were tested by categorizing a medical error case external to the study. No new categories of interruptions were identified during analysis of the medical error case. Conclusions Findings from this study provide evidence that the hybrid model of categorization is more complete than either a deductive or an inductive method alone. The hybrid method developed in this study provides the methodical support for understanding, analyzing, and managing interruptions and workflow.

Towards a hybrid method to categorize interruptions and activities in healthcare.

OBJECTIVE: Interruptions are known to have a negative impact on activity performance. Understanding how an interruption contributes to human error is limited because there is not a standard method for analyzing and classifying interruptions. Qualitative data are typically analyzed by either a deductive or an inductive method. Both methods have limitations. In this paper, a hybrid method was developed that integrates deductive and inductive methods for the categorization of activities and interruptions recorded during an ethnographic study of physicians and registered nurses in a Level One Trauma Center. Understanding the effects of interruptions is important for designing and evaluating informatics tools in particular as well as improving healthcare quality and patient safety in general. METHOD: The hybrid method was developed using a deductive a priori classification framework with the provision of adding new categories discovered inductively in the data. The inductive process utilized line-by-line coding and constant comparison as stated in Grounded Theory. RESULTS: The categories of activities and interruptions were organized into a three-tiered hierarchy of activity. Validity and reliability of the categories were tested by categorizing a medical error case external to the study. No new categories of interruptions were identified during analysis of the medical error case. CONCLUSIONS: Findings from this study provide evidence that the hybrid model of categorization is more complete than either a deductive or an inductive method alone. The hybrid method developed in this study provides the methodical support for understanding, analyzing, and managing interruptions and workflow.

THE INTERACTION BETWEEN INTERNAL AND EXTERNAL INFORMATION ON RELATIONAL DATA SEARCH

People often use tools to search for information. In order to improve the quality of an information search, it is important to understand how internal information, which is stored in user’s mind, and external information, represented by the interface of tools interact with each other. How information is distributed between internal and external representations significantly affects information search performance. However, few studies have examined the relationship between types of interface and types of search task in the context of information search. For a distributed information search task, how data are distributed, represented, and formatted significantly affects the user search performance in terms of response time and accuracy. Guided by UFuRT (User, Function, Representation, Task), a human-centered process, I propose a search model, task taxonomy. The model defines its relationship with other existing information models. The taxonomy clarifies the legitimate operations for each type of search task of relation data. Based on the model and taxonomy, I have also developed prototypes of interface for the search tasks of relational data. These prototypes were used for experiments. The experiments described in this study are of a within-subject design with a sample of 24 participants recruited from the graduate schools located in the Texas Medical Center. Participants performed one-dimensional nominal search tasks over nominal, ordinal, and ratio displays, and searched one-dimensional nominal, ordinal, interval, and ratio tasks over table and graph displays. Participants also performed the same task and display combination for twodimensional searches. Distributed cognition theory has been adopted as a theoretical framework for analyzing and predicting the search performance of relational data. It has been shown that the representation dimensions and data scales, as well as the search task types, are main factors in determining search efficiency and effectiveness. In particular, the more external representations used, the better search task performance, and the results suggest the ideal search performance occurs when the question type and corresponding data scale representation match. The implications of the study lie in contributing to the effective design of search interface for relational data, especially laboratory results, which are often used in healthcare activities.

Can prospective usability evaluation predict data errors?

Increasing amounts of clinical research data are collected by manual data entry into electronic source systems and directly from research subjects. For this manual entered source data, common methods of data cleaning such as post-entry identification and resolution of discrepancies and double data entry are not feasible. However data accuracy rates achieved without these mechanisms may be higher than desired for a particular research use. We evaluated a heuristic usability method for utility as a tool to independently and prospectively identify data collection form questions associated with data errors. The method evaluated had a promising sensitivity of 64% and a specificity of 67%. The method was used as described in the literature for usability with no further adaptations or specialization for predicting data errors. We conclude that usability evaluation methodology should be further investigated for use in data quality assurance.

Comparison of clinical knowledge management capabilities of commercially-available and leading internally-developed electronic health records.

BACKGROUND: We have carried out an extensive qualitative research program focused on the barriers and facilitators to successful adoption and use of various features of advanced, state-of-the-art electronic health records (EHRs) within large, academic, teaching facilities with long-standing EHR research and development programs. We have recently begun investigating smaller, community hospitals and out-patient clinics that rely on commercially-available EHRs. We sought to assess whether the current generation of commercially-available EHRs are capable of providing the clinical knowledge management features, functions, tools, and techniques required to deliver and maintain the clinical decision support (CDS) interventions required to support the recently defined "meaningful use" criteria. METHODS: We developed and fielded a 17-question survey to representatives from nine commercially available EHR vendors and four leading internally developed EHRs. The first part of the survey asked basic questions about the vendor's EHR. The second part asked specifically about the CDS-related system tools and capabilities that each vendor provides. The final section asked about clinical content. RESULTS: All of the vendors and institutions have multiple modules capable of providing clinical decision support interventions to clinicians. The majority of the systems were capable of performing almost all of the key knowledge management functions we identified. CONCLUSION: If these well-designed commercially-available systems are coupled with the other key socio-technical concepts required for safe and effective EHR implementation and use, and organizations have access to implementable clinical knowledge, we expect that the transformation of the healthcare enterprise that so many have predicted, is achievable using commercially-available, state-of-the-art EHRs.

Improving follow-up of abnormal cancer screens using electronic health records: trust but verify test result communication.

BACKGROUND: Early detection of colorectal cancer through timely follow-up of positive Fecal Occult Blood Tests (FOBTs) remains a challenge. In our previous work, we found 40% of positive FOBT results eligible for colonoscopy had no documented response by a treating clinician at two weeks despite procedures for electronic result notification. We determined if technical and/or workflow-related aspects of automated communication in the electronic health record could lead to the lack of response. METHODS: Using both qualitative and quantitative methods, we evaluated positive FOBT communication in the electronic health record of a large, urban facility between May 2008 and March 2009. We identified the source of test result communication breakdown, and developed an intervention to fix the problem. Explicit medical record reviews measured timely follow-up (defined as response within 30 days of positive FOBT) pre- and post-intervention. RESULTS: Data from 11 interviews and tracking information from 490 FOBT alerts revealed that the software intended to alert primary care practitioners (PCPs) of positive FOBT results was not configured correctly and over a third of positive FOBTs were not transmitted to PCPs. Upon correction of the technical problem, lack of timely follow-up decreased immediately from 29.9% to 5.4% (p<0.01) and was sustained at month 4 following the intervention. CONCLUSION: Electronic communication of positive FOBT results should be monitored to avoid limiting colorectal cancer screening benefits. Robust quality assurance and oversight systems are needed to achieve this. Our methods may be useful for others seeking to improve follow-up of FOBTs in their systems.

The relationship between risk perception and ethnicity as an explanation for late stage skin cancer diagnosis in Black and Hispanic populations: An analysis using data from the 2005 Health Information and National Trends Survey

Objective. The purpose of this study was to determine the relationship between ethnicity and skin cancer risk perception while controlling for other risk factors: education, gender, age, access to healthcare, family history of skin cancer, fear, and worry. ^ Methods. This study utilized the Health Information National Trends Survey (HINTS) dataset, a nationally representative sample of 5,586 individuals 18 years of age or older. One third of the respondents were chosen at random and asked questions involving skin cancer. Analysis was based on questions that identified skin cancer risk perception, fear of finding skin cancer, and frequency of worry about skin cancer and a variety of sociodemographic factors. ^ Results. Ethnicity had a significant impact on risk perception scores while controlling for other risk factors. Other risk factors that also had a significant impact on risk perception scores included family history of skin cancer, age, and worry. ^

Latino perceptions of and barriers to preventive healthcare maintenance in the southwest United States

Between the 1990 and 2000 Censuses, the Latino population accounted for 40% of the increase in the nation’s total population. The growing population of Latinos underscores the importance for understanding factors that influence whether and how Latinos take care of their health. According to the U.S. Department of Human Health Service’s Office of Minority Health (OMH), Latinos are at greater risk for health disparities (2003). Factors such as lack of health insurance and access to preventive care play a major role in limiting Latino use of primary health care (Institute of Medicine, 2005). Other significant barriers to preventive health care maintenance behaviors have been identified in current literature such as primary care physician interaction, self-perceived health status, and socio-cultural beliefs and traditions (Rojas-Guyler, King, Montieth and 2008; Meir, Medina, and Ory, 2007; Black, 1999). Despite these studies, there remains less information regarding interpersonal perceptions, environmental dynamics and individual and cultural attitudes relevant to utilization of healthcare (Rojas-Guyler, King, Montieth and 2008; Aguirre-Molina, Molina and Zambrana, 2001). Understanding the perceptions of Latinos and the barriers to health care could directly affect healthcare delivery. Improved healthcare utilization among Latinos could reduce the long term health consequences of many preventable and manageable diseases. The purpose of this study was to explore Latino perceptions of U.S. health care and desired changes by Latinos in the U.S. healthcare system. The study had several objectives, including to explore perceived barriers to healthcare utilization and the resulting effects on health among Latinos, to describe culturally influenced attitudes about health care and use of health care services among Latinos, and to make recommendations for reducing disparities by improving healthcare and its utilization. The current study utilized data that were collected as part of a larger study to examine multidimensional, cross-cultural issues relevant to interactions between healthcare consumers and providers. Qualitative methods were used to analyze four Spanish-language focus group transcripts to interpret cultural influences on perceptions and beliefs among Latinos. Direct coding of transcript content was carried out by two reviewers, who conducted independent reviews of each transcript. Team members developed and refined thematic categories, positive and negative cases, and example text segments for each theme and sub-theme. Incongruities of interpretations were resolved through extensive discussion. Study participants included 44 self-identified Latino adults (16 male, 28 female) between age 18 and 64 years. Thirty seven (84.1%) of the participants were immigrants. The study population comprised eight ethnic subgroups. While 31% of the participants reported being employed on a full-time basis, only 18.4% had medical insurance that was private or employee sponsored. Five major themes regarding the perceptions and healthcare utilization behaviors of Latinos were consistent across all focus groups and were identified during the analysis. These were: (1) healthcare utilization, experience, and access; (2) organizational and institutional systems; (3) communication and interpersonal interactions between healthcare provider, staff, and patient; (4) Latinos’ perception of their own health status; (5) cultural influences on healthcare utilization, which included an innovation termed culturally-bound locus of control. Healthcare utilization was directly influenced by healthcare experience, access, current health status, and cultural factors and indirectly influenced by organizational systems. There was a strong interdependence among the main themes. The ability to communicate and interact effectively with healthcare providers and navigate healthcare systems (organizational and institutional access) significantly influenced the participant’s health care experience, most often (indirectly) impacting utilization negatively. ^ Research such as this can help to identify those perceptions and attitudes held by Latinos concerning utilization or underutilization of healthcare systems. These data suggest that for healthcare utilization to improve among Latinos, healthcare systems must create more culturally competent environments by providing better language services at the organizational level and more culturally sensitive providers at the interpersonal level. Better understanding of the complex interactions between these impediments can aid intervention developments, and help health providers and researchers in determining appropriate, adequate, and effective measurers of care to better increase overall health of Latinos.^

Determining the association between nativity status and mammography utilization among women in the United States using 2000 and 2005 NHIS data

Objective. To determine the association between nativity status and mammography utilization among women in the U.S. and assess whether demographic variables, socioeconomic factors healthcare access, breast cancer risk factors and acculturation variables were predictors in the relationship between nativity status and mammography in the past two years. ^ Methods. The NHIS collects demographic and health information using face-to-face interviews among a representative sample of the U.S. population and a cancer control module assessing screening behaviors is included every five years. Descriptive statistics were used to report demographic characteristics of women aged 40 and older who have received a mammogram in the last 2 years from 2000 and 2005. We used chi square analyses to determine statistically significant differences by mammography screening for each covariate. Logistic regression was used to determine whether demographic characteristics, socioeconomic characteristics, healthcare access, breast cancer risk factors and acculturation variables among foreign-born Hispanics affected the relationship between nativity status and mammography use in the past 2 years. ^ Results. In 2000, the crude model between nativity and mammography was significant but results were not significant after adjusting for health insurance, access and reported health status. Significant results were also reported for years in U.S. and mammography among foreign-born born women. In 2005, the crude model was also significant but results were not significant after adjusting for demographic factors. Furthermore, there was a significant finding between citizenship and mammography in the past 2 years. ^ Conclusions. Our study contributes to the literature as one of the first national-based studies assessing mammography in the past two years based on nativity status. Based on our findings, health insurance and access to care is an important predictor in mammography utilization among foreign-born women. For those with health care access, physician recommendation should further be assessed to determine whether women are made aware of mammography as a means to detect breast cancer at an early stage and further reduce the risk of mortality from the breast cancer.^

The movement toward patient safety: State action related to reporting and disclosure of healthcare-associated infections

Increasing attention has been given to the problem of medical errors over the past decade. Included within that focused attention has been a strong interest in reducing the occurrence of healthcare-associated infections (HAIs). Acting concurrently with federal initiatives, the majority of U.S. states have statutorily required reporting and public disclosure of HAI data. Although the occurrence of these state statutory enactments and other state initiatives represent a recognition of the strong concern pertaining to HAIs, vast differences in each state’s HAI reporting and public disclosure requirements creates a varied and unequal response to what has become a national problem.^ The purpose of this research was to explore the variations in state HAI legal requirements and other state mandates. State actions, including statutory enactments, regulations, and other initiatives related to state reporting and public disclosure mechanisms were compared, discussed, and analyzed in an effort to illustrate the impact of the lack of uniformity as a public health concern.^ The HAI statutes, administrative requirements, and other mandates of each state and two U.S. territories were reviewed to answer the following seven research questions: How far has the state progressed in its HAI initiative? If the state has a HAI reporting requirement, is it mandatory or voluntary? What healthcare entities are subject to the reporting requirements? What data collection system is utilized? What measures are required to be reported? What is the public disclosure mechanism? How is the underlying reported information protected from public disclosure or other legal release?^ Secondary publicly available data, including state statutes, administrative rules, and other initiatives, were utilized to examine the current HAI-related legislative and administrative activity of the study subjects. The information was reviewed and analyzed to determine variations in HAI reporting and public disclosure laws. Particular attention was given to the seven key research questions.^ The research revealed that considerable progress has been achieved in state HAI initiatives since 2004. Despite this progress, however, when reviewing the state laws and HAI programs comparatively, considerable variations were found to exist with regards to the type of reporting requirements, healthcare facilities subject to the reporting laws, data collection systems utilized, reportable measures, public disclosure requirements, and confidentiality and privilege provisions. The wide variations in state statutes, administrative rules, and other agency directives create a fragmented and inconsistent approach to addressing the nationwide occurrence of HAIs in the U.S. healthcare system. ^