A comparison of a multistate inpatient EHR database to the HCUP Nationwide Inpatient Sample

Background The growing availability of electronic health records (EHRs) in the US could provide researchers with a more detailed and clinically relevant alternative to using claims-based data. Methods In this study we compared a very large EHR database (Health Facts©) to a well-established population estimate (Nationwide Inpatient Sample). Weighted comparisons were made using t-value and relative difference over diagnoses and procedures for the year 2010. Results The two databases have a similar distribution pattern across all data elements, with 24 of 50 data elements being statistically similar between the two data sources. In general, differences that were found are consistent across diagnosis and procedures categories and were specific to the psychiatric–behavioral and obstetrics–gynecology services areas. Conclusions Large EHR databases have the potential to be a useful addition to health services researchers, although they require different analytic techniques compared to administrative databases; more research is needed to understand the differences

A comparison of a multistate inpatient EHR database to the HCUP Nationwide Inpatient Sample

Background The growing availability of electronic health records (EHRs) in the US could provide researchers with a more detailed and clinically relevant alternative to using claims-based data. Methods In this study we compared a very large EHR database (Health Facts©) to a well-established population estimate (Nationwide Inpatient Sample). Weighted comparisons were made using t-value and relative difference over diagnoses and procedures for the year 2010. Results The two databases have a similar distribution pattern across all data elements, with 24 of 50 data elements being statistically similar between the two data sources. In general, differences that were found are consistent across diagnosis and procedures categories and were specific to the psychiatric–behavioral and obstetrics–gynecology services areas. Conclusions Large EHR databases have the potential to be a useful addition to health services researchers, although they require different analytic techniques compared to administrative databases; more research is needed to understand the differences

An interactive and user-centered computer system to predict physician’s disease judgments in discharge summaries

AbstractPurpose: This article describes a formative natural language processing (NLP) system that is grounded in user-centered design, simplification, and transparency of function. Methods: The NLP system was tasked to classify diseases within patient discharge summaries and is evaluated against clinician judgment during the 2008 i2b2 Shared Task competition. Text classification is performed by interactive, fully supervised learning using rule-based processes and support vector machines (SVMs). Results: The macro-averaged F-score for textual (t) and intuitive (i) classification were 0.614(t) and 0.629(i), while micro-averaged F-scores were recorded at 0.966(t) and 0.954(i) for the competition. These results were comparable to the top 10 performing systems. Discussion: The results of this study indicate that an interactive training method, de novo knowledge base with no external data sources, and simplified text mining processes can achieve a comparably high performance in classifying health-related texts. Further research is needed to determine if the user-centered advantages of a NLP system translate into real world benefits

Impact of HbA1c Measurement on Hospital Readmission Rates: Analysis of 70,000 Clinical Database Patient Records

Management of hyperglycemia in hospitalized patients has a significant bearing on outcome, in terms of both morbidity and mortality. However, there are few national assessments of diabetes care during hospitalization which could serve as a baseline for change. This analysis of a large clinical database (74 million unique encounters corresponding to 17 million unique patients) was undertaken to provide such an assessment and to find future directions which might lead to improvements in patient safety. Almost 70,000 inpatient diabetes encounters were identified with sufficient detail for analysis. Multivariable logistic regression was used to fit the relationship between the measurement of HbA1c and early readmission while controlling for covariates such as demographics, severity and type of the disease, and type of admission. Results show that the measurement of HbA1c was performed infrequently (18.4%) in the inpatient setting. The statistical model suggests that the relationship between the probability of readmission and the HbA1c measurement depends on the primary diagnosis. The data suggest further that the greater attention to diabetes reflected in HbA1c determination may improve patient outcomes and lower cost of inpatient care

Health Care Providers' Acceptance of a Personal Health Record: Cross-sectional Study

Background: Personal health records (PHRs) are eHealth tools designed to support patient engagement, patient empowerment, and patient- and person-centered care. Endorsement of a PHR by health care providers (HCPs) facilitates patient acceptance. As health care organizations in the Kingdom of Saudi Arabia begin to adopt PHRs, understanding the perspectives of HCPs is important because it can influence patient adoption. However, no studies evaluated HCPs’ acceptance of PHRs in the Kingdom of Saudi Arabia.Objective: The aim of this study was to identify predictors of HCPs’ acceptance of PHRs using behavioral intention to recommend as a proxy for adoption.Methods: This cross-sectional study was conducted among HCPs (physicians, pharmacists, nurses, technicians, others) utilizing a survey based on the Unified Theory of Acceptance and Use of Technology. The main theory constructs of performance expectancy, effort expectancy, social influence, facilitating conditions, and positive attitude were considered independent variables. Behavioral intention was the dependent variable. Age, years of experience, and professional role were tested as moderators between the main theory constructs and behavioral intention using partial least squares structural equation modeling.Results: Of the 291 participants, 246 were included in the final analysis. Behavioral intention to support PHR use among patients was significantly influenced by performance expectancy (β=.17, P=.03) and attitude (β=.61, PConclusions: This study identified performance expectancy and attitude as predictors of HCPs’ behavioral intention to recommend PHR to patients. To encourage HCPs to endorse PHRs, health care organizations should involve HCPs in the implementation and provide training on the features available as well as expected benefits. Future studies should be conducted in other contexts and include other potential predictors.</p

Publication trends in the medical informatics literature: 20 years of "Medical Informatics" in MeSH

<p>Abstract</p> <p>Background</p> <p>The purpose of this study is to identify publication output, and research areas, as well as descriptively and quantitatively characterize the field of medical informatics through publication trend analysis over a twenty year period (1987–2006).</p> <p>Methods</p> <p>A bibliometric analysis of medical informatics citations indexed in Medline was performed using publication trends, journal frequency, impact factors, MeSH term frequencies and characteristics of citations.</p> <p>Results</p> <p>There were 77,023 medical informatics articles published during this 20 year period in 4,644 unique journals. The average annual article publication growth rate was 12%. The 50 identified medical informatics MeSH terms are rarely assigned together to the same document and are almost exclusively paired with a non-medical informatics MeSH term, suggesting a strong interdisciplinary trend. Trends in citations, journals, and MeSH categories of medical informatics output for the 20-year period are summarized. Average impact factor scores and weighted average impact factor scores increased over the 20-year period with two notable growth periods.</p> <p>Conclusion</p> <p>There is a steadily growing presence and increasing visibility of medical informatics literature over the years. Patterns in research output that seem to characterize the historic trends and current components of the field of medical informatics suggest it may be a maturing discipline, and highlight specific journals in which the medical informatics literature appears most frequently, including general medical journals as well as informatics-specific journals.</p

Predicting Patients’ Intention to Use a Personal Health Record Using an Adapted Unified Theory of Acceptance and Use of Technology Model: Secondary Data Analysis

BackgroundWith the rise in the use of information and communication technologies in health care, patients have been encouraged to use eHealth tools such as personal health records (PHRs) for better health and well-being services. PHRs support patient-centered care and patient engagement. To support the achievement of the Kingdom of Saudi Arabia's Vision 2030 ambitions, the National Transformation program provides a framework to use PHRs in meeting the triple aim for health care - increased access, reduced cost, and improved quality of care - and to provide patient- and person-centered care. However, there has been limited research on PHR uptake within the country.ObjectiveUsing the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, this study aims at identifying predictors of patient intention to utilize the Ministry of National Guard-Health Affairs (MNG-HA) PHR (MNGHA Care) application.MethodsUsing secondary data from a cross-sectional survey, data measuring intention to use the MNGHA Care application along with its predictors, were collected from adults (N=324) visiting MNG-HA facilities in Riyadh, Jeddah, Dammam, Madinah, Al Ahsa, and Qassim. The relationship of predictors (main theory constructs) and moderators (age, gender, experience with health applications) with the dependent variable (intention to use MNGHA Care) was tested using hierarchical multiple regression.ResultsOf the eligible population, a total of 261 adult patients were included in the analysis with a mean age of 35.07 years (± 9.61), male (n=132, 50.6%), university-educated (n=118, 45.2%), and at least one chronic medical condition (n=139, 53.3%). The model explained 48.9% of the variance in behavioral intention to use the PHR (P=.377). Performance expectancy, effort expectancy, and positive attitude were significantly associated with behavioral intention to use the PHR (PConclusionsThis research contributes to the existing literature on PHR adoption broadly as well as in the context of the Kingdom of Saudi Arabia. Understanding which factors are associated with patient adoption of PHRs can guide future development and support the country's aim of transforming the health care system. Similar to other studies on PHR adoption, performance expectancy, effort expectancy, and positive attitude are important factors, and practical consideration should be given supporting these areas.</p

Predicting patients' intention to use a personal health record using an adapted unified theory of acceptance and use of technology model : secondary data analysis

Background: With the rise in the use of information and communication technologies in health care, patients have been encouraged to use eHealth tools such as personal health records (PHRs) for better health and well-being services. PHRs support patient-centered care and patient engagement. To support the achievement of the Kingdom of Saudi Arabia’s Vision 2030 ambitions, the National Transformation program provides a framework to use PHRs in meeting the 3-fold aim for health care—increased access, reduced cost, and improved quality of care—and to provide patient- and person-centered care. However, there has been limited research on PHR uptake within the country. Objective: Using the Unified Theory of Acceptance and Use of Technology (UTAUT) as the theoretical framework, this study aims at identifying predictors of patient intention to utilize the Ministry of National Guard-Health Affairs PHR (MNGHA Care) app. Methods: Using secondary data from a cross-sectional survey, data measuring the intention to use the MNGHA Care app, along with its predictors, were collected from among adults (n=324) visiting Ministry of National Guard-Health Affairs facilities in Riyadh, Jeddah, Dammam, Madinah, Al Ahsa, and Qassim. The relationship of predictors (main theory constructs) and moderators (age, gender, and experience with health apps) with the dependent variable (intention to use MNGHA Care) was tested using hierarchical multiple regression. Results: Of the eligible population, a total of 261 adult patients were included in the analysis. They had a mean age of 35.07 (SD 9.61) years, 50.6 % were male (n=132), 45.2% had university-level education (n=118), and 53.3% had at least 1 chronic medical condition (n=139). The model explained 48.9% of the variance in behavioral intention to use the PHR (P=.38). Performance expectancy, effort expectancy, and positive attitude were significantly associated with behavioral intention to use the PHR (P Conclusions: This study contributes to the existing literature on PHR adoption broadly as well as in the context of the Kingdom of Saudi Arabia. Understanding which factors are associated with patient adoption of PHRs can guide future development and support the country’s aim of transforming the health care system. Similar to previous studies on PHR adoption, performance expectancy, effort expectancy, and positive attitude are important factors, and practical consideration should be given to support these areas

Psychopathology and HIV diagnosis among older adults in the United States: disparities by age, sex, and race/ethnicity

In 2016, 17% of new HIV infections in the US were among adults aged 50 and older. Differences by age, sex, and race/ethnicity exist among older people living with HIV. Co-morbid mental health and substance use disorders (SUD) are also major challenges for this population. This study examined the association between generalized anxiety disorder (GAD), posttraumatic stress disorder (PTSD), SUD, depression, and HIV diagnosis among adults aged 50 and older, and the disparities by age, sex, and race/ethnicity. Data were obtained from Cerner Corporation’s Health Facts® database. Multivariable logistic regression models were used to determine the associations between GAD, PTSD, SUD, and depression, and HIV diagnosis. Results were also stratified by age group, sex, and race/ethnicity. Overall, there were positive associations between SUD, depression, GAD, PTSD and HIV; and differences by age, sex and race/ethnicity existed in these associations. For example, after adjusting for age, race/ethnicity and marital status, men who were diagnosed with GAD were 10 times more likely (adjusted OR: 10.3; 95% CI: 8.75–12.1) to have an HIV diagnosis compared to men who were not diagnosed with GAD. Women who were diagnosed with GAD were five times more likely (adjusted OR: 5.01; 95% CI: 3.81–6.58) to have an HIV diagnosis compared to women who were not diagnosed with GAD. HIV prevention and intervention programs for older adults should address GAD, PTSD, SUD and depression and consider the age, sex and racial/ethnic disparities in the association between psychopathology and HIV