Identification of Patients in Need of Advanced Care for Depression Using Data Extracted From a Statewide Health Information Exchange: A Machine Learning Approach.

BACKGROUND: As the most commonly occurring form of mental illness worldwide, depression poses significant health and economic burdens to both the individual and community. Different types of depression pose different levels of risk. Individuals who suffer from mild forms of depression may recover without any assistance or be effectively managed by primary care or family practitioners. However, other forms of depression are far more severe and require advanced care by certified mental health providers. However, identifying cases of depression that require advanced care may be challenging to primary care providers and health care team members whose skill sets run broad rather than deep. OBJECTIVE: This study aimed to leverage a comprehensive range of patient-level diagnostic, behavioral, and demographic data, as well as past visit history data from a statewide health information exchange to build decision models capable of predicting the need of advanced care for depression across patients presenting at Eskenazi Health, the public safety net health system for Marion County, Indianapolis, Indiana. METHODS: Patient-level diagnostic, behavioral, demographic, and past visit history data extracted from structured datasets were merged with outcome variables extracted from unstructured free-text datasets and were used to train random forest decision models that predicted the need of advanced care for depression across (1) the overall patient population and (2) various subsets of patients at higher risk for depression-related adverse events; patients with a past diagnosis of depression; patients with a Charlson comorbidity index of ≥1; patients with a Charlson comorbidity index of ≥2; and all unique patients identified across the 3 above-mentioned high-risk groups. RESULTS: The overall patient population consisted of 84,317 adult (aged ≥18 years) patients. A total of 6992 (8.29%) of these patients were in need of advanced care for depression. Decision models for high-risk patient groups yielded area under the curve (AUC) scores between 86.31% and 94.43%. The decision model for the overall patient population yielded a comparatively lower AUC score of 78.87%. The variance of optimal sensitivity and specificity for all decision models, as identified using Youden J Index, is as follows: sensitivity=68.79% to 83.91% and specificity=76.03% to 92.18%. CONCLUSIONS: This study demonstrates the ability to automate screening for patients in need of advanced care for depression across (1) an overall patient population or (2) various high-risk patient groups using structured datasets covering acute and chronic conditions, patient demographics, behaviors, and past visit history. Furthermore, these results show considerable potential to enable preventative care and can be easily integrated into existing clinical workflows to improve access to wraparound health care services.

Toward Timely Data for Cancer Research: Assessment and Reengineering of the Cancer Reporting Process.

BACKGROUND: Cancer registries systematically collect cancer-related data to support cancer surveillance activities. However, cancer data are often unavailable for months to years after diagnosis, limiting its utility. OBJECTIVE: The objective of this study was to identify the barriers to rapid cancer reporting and identify ways to shorten the turnaround time. METHODS: Certified cancer registrars reporting to the Indiana State Department of Health cancer registry participated in a semistructured interview. Registrars were asked to describe the reporting process, estimate the duration of each step, and identify any barriers that may impact the reporting speed. Qualitative data analysis was performed with the intent of generating recommendations for workflow redesign. The existing and redesigned workflows were simulated for comparison. RESULTS: Barriers to rapid reporting included access to medical records from multiple facilities and the waiting period from diagnosis to treatment. The redesigned workflow focused on facilitating data sharing between registrars and applying a more efficient queuing technique while registrars await the delivery of treatment. The simulation results demonstrated that our recommendations to reduce the waiting period and share information could potentially improve the average reporting speed by 87 days. CONCLUSIONS: Knowing the time elapsing at each step within the reporting process helps in prioritizing the needs and estimating the impact of future interventions. Where some previous studies focused on automating some of the cancer reporting activities, we anticipate much shorter reporting by leveraging health information technologies to target this waiting period.

Dietary intake of isoflavones and coumestrol and the risk of prostate cancer in the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial.

Experimental studies have revealed that phytoestrogens may modulate the risk of certain sites of cancer due to their structural similarity to 17ß-estradiol. The present study investigates whether intake of these compounds may influence prostate cancer risk in human populations. During a median follow up of 11.5 years, 2,598 cases of prostate cancer (including 287 advanced cases) have been identified among 27,004 men in the intervention arm of the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Dietary intake of phytoestrogens (excluding lignans) was assessed with a food frequency questionnaire. Cox proportional hazards regression analysis was performed to estimate hazard ratios (HRs) and 95% confidence intervals (CI) for dietary isoflavones and coumestrol in relation to prostate cancer risk. After adjustment for confounders, an increased risk of advanced prostate cancer [HR (95% CI) for quintile (Q) 5 vs. Q1] was found for the dietary intake of total isoflavones [1.91 (1.25-2.92)], genistein [1.51 (1.02-2.22), daidzein [1.80 (1.18-2.75) and glycitein [1.67 (1.15-2.43)] (p-trend for all associations ≤0.05). For example, HR (95% CI) for comparing the Q2, Q3, Q4 and Q5 with Q1 of daidzein intake was 1.45 (0.93-2.25), 1.65 (1.07-2.54), 1.73 (1.13-2.66) and 1.80 (1.18-2.75), respectively (p-trend: 0.013). No statistically significant associations were observed between the intake of total isoflavones and individual phytoestrogens and non-advanced and total prostate cancer after adjustment for confounders. This study revealed that dietary intake of isoflavones was associated with an elevated risk of advanced prostate cancer.

What Do They Mean by "Health Informatics"? Health Informations Posts Compared to Program Standards.

There is a lack of alignment between and within the competencies and skills required by health informatics (HI) related jobs and those present in academic curriculum frameworks. This study uses computational topic modeling for gap analysis of career needs vs. curriculum objectives. The seven AMIA-CAHIIM-accepted core knowledge domains were used to categorize a corpus of HI-related job postings (N = 475) from a major United States-based job posting website. Computational modeling-generated topics were created and then compared and matched to the seven core knowledge domains. The HI-defining core domain, representing the intersection of health, technology and social/behavioral sciences matched only 45.9% of job posting content. Therefore, the authors suggest that bidirectional communication between academia and industry is needed in order to better align educational objectives to the demands of the job market.

The Impact of Information Technology on Patient Engagement and Health Behavior Change: A Systematic Review of the Literature.

BACKGROUND: Advancements in information technology (IT) and its increasingly ubiquitous nature expand the ability to engage patients in the health care process and motivate health behavior change. OBJECTIVE: Our aim was to systematically review the (1) impact of IT platforms used to promote patients' engagement and to effect change in health behaviors and health outcomes, (2) behavior theories or models applied as bases for developing these interventions and their impact on health outcomes, (3) different ways of measuring health outcomes, (4) usability, feasibility, and acceptability of these technologies among patients, and (5) challenges and research directions for implementing IT platforms to meaningfully impact patient engagement and health outcomes. METHODS: PubMed, Web of Science, PsycINFO, and Google Scholar were searched for studies published from 2000 to December 2014. Two reviewers assessed the quality of the included papers, and potentially relevant studies were retrieved and assessed for eligibility based on predetermined inclusion criteria. RESULTS: A total of 170 articles met the inclusion criteria and were reviewed in detail. Overall, 88.8% (151/170) of studies showed positive impact on patient behavior and 82.9% (141/170) reported high levels of improvement in patient engagement. Only 47.1% (80/170) referenced specific behavior theories and only 33.5% (57/170) assessed the usability of IT platforms. The majority of studies used indirect ways to measure health outcomes (65.9%, 112/170). CONCLUSIONS: In general, the review has shown that IT platforms can enhance patient engagement and improve health outcomes. Few studies addressed usability of these interventions, and the reason for not using specific behavior theories remains unclear. Further research is needed to clarify these important questions. In addition, an assessment of these types of interventions should be conducted based on a common framework using a large variety of measurements; these measurements should include those related to motivation for health behavior change, long-standing adherence, expenditure, satisfaction, and health outcomes.

Data Quality at the Indiana State Cancer Registry: An Evaluation of Timeliness by Cancer Type and Year.

BACKGROUND: Central cancer registries collect tumor-related data to monitor incidence rates and support population- based research. One concern with using registry data for research is timeliness of reporting. Timeliness has been recognized as an important data characteristic by both the Centers for Disease Control and Prevention and the National Academy of Medicine. Yet, few studies in the United States have systematically measured timeliness. The purpose of this study is to evaluate timeliness in cancer-case reporting to a state population-based cancer registry. METHOD: Using the Indiana State Department of Health Cancer Registry, 66,395 breast, colorectal, and lung cancer diagnoses recorded during the years 2001­2009 were examined for timeliness. Timeliness was measured from the date the cancer was diagnosed to when the data were available at the state registry. Differences over time and among the 3 cancer types were examined. RESULT: Timeliness of reporting improved since 2003. Mean reporting time ranged from 426 days in 2003 to 253 days in 2009. We found significant difference in reporting time between the 3 cancer types. CONCLUSION: Timeliness of reporting has improved over time. Advances in health information technologies may have contributed to this improvement. However, achieving even more timely reporting for research purposes and care intervention may require moving away from traditional reporting methods.

Infection preventionists' awareness of and engagement in health information exchange to improve public health surveillance.

BACKGROUND: Advances in electronic health record (EHR) systems and health information exchange (HIE) are shifting efforts in public health toward greater use of information systems to automate notifiable disease surveillance. Little is known about infection preventionists' (IPs) awareness, adoption, and use of these technologies to report information to public health. METHODS: To measure awareness and engagement in EHR and HIE activities, an online survey of IPs was conducted in states with HIE networks. A total of 63 IPs was invited to participate; 44 IPs (69%) responded. The survey asked about the adoption and use of EHR systems, participation in regional HIE initiatives, and IP needs with respect to EHR systems and public health reporting. RESULTS: Over 70% of responding IPs reported access to an EHR system, but less than 20% of IPs with access to an EHR reported being involved in the design, selection, or implementation of the system. Just 10% of IPs reported that their organizations were formally engaged in HIE activities, and 49% were unaware of organizational involvement in HIE. IPs expressed a desire for better decision support, paperless reporting methods, and situational awareness of community outbreaks. CONCLUSION: Many IPs lack awareness and engagement in EHR and HIE activities, which may limit IPs ability to influence or utilize key information technologies as they are implemented in health care organizations.

Visualization of usability and functionality of a professional website through web-mining.

Functional interface design requires understanding of the information system structure and the user. Web logs record user interactions with the interface, and thus provide some insight into user search behavior and efficiency of the search process. The present study uses a data-mining approach with techniques such as association rules, clustering and classification, to visualize the usability and functionality of a digital library through in depth analyses of web logs.

Telehealth interventions to improve clinical nursing of elders.

This chapter reviews reports of research conducted worldwide from 1966 to January 2001 on telehealth interventions in clinical nursing for elders. Reports were identified through a systematic search of MEDLINE, CINAHL, PsychInfo, ERIC, and ACM using the search terms Telemedicine or Health Information Networks, Nursing, and Research, and were restricted to those published in English. Reports of research using interactive computer technology to assess or intervene with nursing problems commonly observed in persons age 65 and older were sought. Only published reports presenting the findings of an exploratory or experimental study and exploring the association between one intervention variable and technology were included. The search resulted in 18 research reports describing eight research projects. Due to the preponderance of demonstrations and feasibility reports, the dearth of experimental investigations, and the heterogeneous nature of the few studies identified, statistical summarization was not attempted. Telehealth interventions have the potential to improve the clinical nursing care of elders because they provide alternative, equivalent approaches to assess key indicators of the physical and psychological state of elders; are acceptable to nurses, elders, and family caregivers; and may prove less costly than face-to-face interventions. Telehealth approaches provide not only acceptable substitutes for discrete nursing actions but also can serve as a context within which a large range of professional gerontological nursing services can be delivered in a manner that is timely and convenient for elders.