Browsing by Subject "Health informatics"

Now showing 1 - 14 of 14

Deriving value from health information technology: impact of prior clinical information from an accessible electronic health record on laboratory and radiology testing in a pediatric population
(2014-12) Knighton, Andrew John
Repetition by clinicians of the same or similar tests with a given patient is common and varies by patient age. However, not all repeat tests are necessary or appropriate for care. Outcomes associated with over-testing include unnecessary emotional hardship and economic cost that may justify efforts to eliminate unnecessary or potentially redundant tests. Limited evidence suggests that the presence of an electronic health record (EHR) may reduce potentially redundant medical tests by making previous test results accessible to clinicians at the point of care. This population-based research characterizes multiple test instances of the same test in a pediatric population, including significant risk factors associated with repeat testing. Using a guideline-based criteria for classifying problematic repeat lead tests, we demonstrate the effect that multiple health system use by patients has on the incidence of problematic repeat lead testing. The results suggest that approximately 50% of repeat lead testing performed in the population was of questionable clinical value. Lead tests repeated within the same health system where a clinician had reasonable access to prior test results had significantly lower odds of being problematic.
Enhancing biomedical terminologies to include behavioral health: a prerequisite to improving the quality of healthcare
(2013-05) Svensson, Piper Allyn
Developing high quality information systems capable of supporting research and clinical care in behavioral health requires the existence of robust clinical terminologies and information models. These terminologies and information models must be capable of representing the same breadth and depth of constructs in the psychological domain that we demand of terminologies in the medical domain. Focusing specifically on psychological assessment instruments and their role in healthcare, we present three distinct studies assessing the extent to which existing healthcare terminologies can be used to capture, code, aggregate, and retrieve information in this domain. We begin with the premise that representation of psychological assessments instruments and instrument-related data must be addressed early in the terminology enhancement process. Psychometric instruments are, by definition, the foundation upon which all empirical knowledge in this domain is based. These instruments play a central role in shaping current understanding of both clinically relevant phenomena and specific mental health conditions. Moreover, results obtained using instruments are the grounds upon which clinical practice in this domain is designated as "evidence based". The results of the each of the three studies demonstrate significant gaps in terminologies relative to behavioral health; gaps that hamper the application of health information technology (HIT) in this domain and undermine efforts to improve the quality of healthcare. We discuss the details and implications of these findings and recommend a more aggressive, interdisciplinary effort to enhance healthcare terminologies to include behavioral health.
Exploring factors that influence progression of diabetes complications: a study of medicare and dual eligible beneficiaries
(2014-12) Abujamra, Ramzi
This dissertation will explore the factors that influence development of Diabetes complications for Medicare and dual eligible beneficiaries, for three Diabetes complications: retinopathy, nephropathy and neuropathy. Both predictive and explanatory models are explored. Predictive models focus on finding factors most predictive of Diabetes complications among Medicare and dual eligible beneficiaries. Explanatory models seek to answer the three hypothesis of this study. The first hypothesis states that higher treatment investment is associated with lower rates of Diabetes complications in Medicare and dual eligible beneficiaries. The second hypothesis states that physicians who are specialists (vs. primary care) and urban (vs. rural) are associated with lower rates of Diabetes complications among Medicare and dual eligible beneficiaries. Finally, the third hypothesis associates higher patient total cost sharing with improvement in Diabetes complications outcomes among Medicare and dual eligible beneficiaries. For dual eligible beneficiaries, patient cost sharing is defined as state Medicaid investment per beneficiary for the state where each beneficiary resides in. The results for the predictive models are strongest for nephropathy complication, and weakest for retinopathy complication. The results for the explanatory models show that for the first hypothesis, nephropathy has lower rate of Diabetes complication for higher total treatment investment. For the second hypothesis, rural providers have lower rate of Diabetes complications for nephropathy (non-dual beneficiaries) and neuropathy (for dual beneficiaries). Also, primary care providers have lower rates of Diabetes complication for retinopathy and neuropathy (non-dual beneficiaries) and retinopathy (dual beneficiaries). For neuropathy, specialists have lower rates of Diabetes complications (for non-dual beneficiaries). Finally, for the third hypothesis, no complications are associated with lower Diabetes complication rates with higher patient total cost sharing for non-dual beneficiaries. For dual beneficiaries, retinopathy and nephropathy (to a lesser extent) show evidence of lower Diabetes complication rates with higher State Medicaid investment per beneficiary. Model performance results based on the C-statistic are moderate overall, with nephropathy showing the best performance and retinopathy the lowest performing among all of the Diabetes complications.
A framework for the multilevel integration of molecular, clinical, and population data in the context of breast cancer: challenges and considerations of socioecological conditions and pharmacogenomics
(2015-01) Breitenstein, Matthew K.
Despite medicine's rigorous pace of advancement, clinical research remains limited by scalability and portability issues. As we think about the needs of cancer epidemiology, we see the need for multilevel modeling powered by scalable and portable informatics-driven approaches. Of novelty in this dissertation is the `Multilevel Framework for Translational Informatics' that enabled pursuit of a line of scientific inquiry regarding the pharamacogenomics and pharmacoepidemiology of metformin in breast cancer and type 2 diabetes mellitus (T2DM). Metformin is an oral biguanide and is a widely prescribed anti-diabetic medication that is considered to be a first-line treatment for T2DM. While metformin is generally well tolerated it displays wide variation in efficacy and rare adverse reactions; its pharmacogenomics are not clearly understood. Due to the epidemic growth of T2DM in the US and the accumulating evidence highlighting potential repurposing of metformin for cancer prevention and treatment it is imperative to understand molecular mechanisms and clinical impacts of metformin. Further, in order to appropriately separate effects due to metformin and breast cancer from social stress, a known modifier of breast cancer biology, it is necessary to incorporate these characteristics into the model in a way that does not lead to overfitting. To highlight this framework I presented my work in three parts: 1) metformin and insulin pharmacoepidemiology, which as a baseline operated on clinical data only; 2) the modifying impact of socioecological context on breast cancer prevalence, which integrated population measures into clinical context; and finally, 3) translational biomedical informatics of metformin pharmacogenomics, which integrated molecular variation within clinical context. While this work elucidated aspects of metformin pharmacogenomics, it primarily aimed to demonstrate the utility of this framework for integrating multilevel data into future cancer epidemiology and translational biomedical informatics research. As we now see the field of biomedical informatics approaching data mining and data science we see a tantalizing opportunity for utilizing and advancing techniques such as these to power clinical research.
Interview with Christopher G. Chute
(2014-12-04) Chute, Christopher G.; Tobbell, Dominique
Christopher Chute begins by discussing his educational background and his decision to move to the Mayo Clinic in the late 1980s. Next, he discusses some of the health informatics research and educational projects that the Mayo Clinic and the University of Minnesota have collaborated on. Dr. Chute describes in detail the main research projects that he and the Division of Biomedical Informatics have worked on since the late 1980s, including research in the areas of biomedical terminology and ontology and the management of patient data in electronic medical records. He discusses his role in the University of Minnesota’s National Library of Medicine Research Training Program and the eventual formal incorporation of the Mayo Clinic into the training program. He discusses the changes in the training program over the course of the 1990s and early 2000s in the context of broader changes in the field of health informatics in particular and biomedical research more generally. Dr. Chute next discusses the efforts, beginning in the mid-2000s, to establish a collaborative health informatics training program between the Mayo Clinic, Arizona State University, and the University of Minnesota. He also discusses the process by which both the Mayo Clinic and the University of Minnesota secured Clinical Translation Science Awards. Finally, Dr. Chute reflects on the interprofessionalism that has characterized health informatics at the University of Minnesota.
Interview with Donald Connelly
(2015-04-01) Connelly, Donald; Tobbell, Dominique
Donald Connelly begins by discussing his educational background, including his early interest in biomedical computing. He describes his first years in the Department of Laboratory Medicine and Pathology including the state of computing in laboratories in the 1970s, the atmosphere of the Department, and his experiences as director of the Laboratory Data Division and acting director of the Outpatient Laboratory. Next, Dr. Connelly discusses his experiences as a Ph.D. student in the Division of Health Computer Sciences. He goes on to describe his early research developing ways to graphically display laboratory data to clinicians, and his subsequent research with Theodore Thompson, MD, to develop a clinical workstation for the University of Minnesota’s Neonatal Intensive Care Unit. He also describes his work developing an automated decision support system for blood bank personnel assessing requests for platelets. Dr. Connelly next discusses the courses he taught in the Division of Health Computer Sciences; the National Library of Medicine Training Grant programs; and the interdisciplinarity and interprofessionalism of health informatics. He reflects upon the leadership of Eugene Ackerman and Laël Gatewood, the challenges each faced due to the lack of strong institutional support for the Division of Health Computer Sciences, and the increased status of health informatics within the University following the establishment of the Clinical and Translational Science Institute. He also discusses his experiences directing the Division of Health Computer Sciences. Dr. Connelly briefly discusses the relationships between the Division of Health Computer Sciences and the Mayo Clinic, the Biomedical Library, and the Minnesota Department of Health. He next discusses work that he has done in the area of electronic health records. Dr. Connelly goes on to discuss the establishment of the Institute for Health Informatics; the directorship of Julie Jacko; and the establishment of the Master’s in Health Informatics. Finally, Dr. Connelly reflects on some of the major changes he has in health informatics observed over his career.
Interview with Lynda Ellis
(University of Minnesota, 2014-10-21) Ellis, Lynda; Tobbell, Dominique
Lynda Ellis begins by discussing her educational background and her arrival at the University of Minnesota. She describes her first years in the Division of Health Computer Sciences, the atmosphere of the Department of Laboratory Medicine and Pathology, and her colleagues in the Department. She then discusses her initial research in computer-based patient education; the graduate program in Biometry and Health Information Systems; and her year of leave at 3M. Dr. Ellis next describes her collaborative work with Larry Wackett and the development of the University of Minnesota Biocatalysis/Biodegradation Database, and then returns to the subject of her work on computer-based patient education. She discusses the National Library of Medicine Training Grant program; the development of the Health Sciences Instructional Computing Laboratory; the important role of the Biomedical Library in the history of health informatics at the University; the leadership styles of Eugene Ackerman and Laël Gatewood; and the number of women in health informatics.
Interview with Martin LaVenture
(2015-03-22) LaVenture, Martin; Tobbell, Dominique
Martin (Marty) LaVenture received his BS in Natural Science from St. John’s University in Collegeville, Minnesota in 1973, and a Masters in Public Health in Epidemiology in 1976 and Ph.D. in Health Informatics in 2004 from the University of Minnesota. From 1976 to 1978, Dr. LaVenture served as epidemiologist and surveillance coordinator in the Immunization Program Section of the Minnesota Department of Health. In 1978, Dr. LaVenture joined the Wisconsin Division of Health in Madison, where he held the position of assistant state epidemiologist and communicable disease coordinator until 1987. Between 1987 and 1990, he served as director of the Cohort Public Health Division of Epic Systems Corp., in Minneapolis where he worked as a developer of software systems for health information management. In 1990, Dr. LaVenture returned to the Minnesota Department of Health where he held the position of supervisor, Immunization Assessment and Registries Unit in the Division of Disease Prevention and Control. From December 1995 through December 1997, he served as manager, Acute Disease Prevention Services Section in the Division of Disease Prevention and Control. Since December 1997, Dr. LaVenture has served as Director of Health Informatics and since 2009 he has served as Director of the Office of Health Information Technology and e-Health at the Minnesota Department of Health. As part of this, he leads the statewide Minnesota e-Health Initiative, a public-private collaborative chartered in 2004 to advance health information technology adoption and use in Minnesota. In 1992, Dr. LaVenture joined the graduate program in Health Informatics at the University of Minnesota, receiving his Ph.D. in 2004. Since 2004, he has served as a core member of faculty at the University of Minnesota in Health Informatics. In 2011, Dr. LaVenture was elected as a fellow of the American College of Medical Informatics.
Interview with Milton Corn
(2014-11-21) Corn, Milton; Tobbell, Dominique
Milton Corn begins the interview discussing the definition of health informatics and the early National Library of Medicine Research Training in Medical Informatics programs, including the University of Minnesota’s training program. Dr. Corn describes his first introduction to medical informatics while serving as dean of Georgetown University School of Medicine and his decision to join the NLM in 1990. He describes at length the evolution of the NLM Research Training Program and the related history of the University of Minnesota’s training program based on the evaluations the NLM performed of the training program every five years. He discusses the University of Minnesota and Mayo Clinic’s efforts to establish a collaborative training program with Arizona State University. He also discusses the implications of Minnesota’s decision not to fully pursue bioinformatics when the NLM shifted the focus of its training program in the 1990s. Dr. Corn goes on to discuss the development of the Clinical and Translational Science Awards and the influence of the awards on health informatics research.
Interview with Norrie Thomas
(University of Minnesota, 2013-11-21) Klaffke, Lauren E.; Thomas, Norrie
Norrie Thomas was born in Detroit, Michigan but grew up in Rochester, Minnesota. She completed two years at a junior college in Rochester and transferred to the University of Minnesota in 1971. She earned her bachelor’s in pharmacy in 1976. She worked as a staff pharmacist at Saint Mary’s Hospital and the Mayo Clinic before returning to the University of Minnesota as a graduate student. She earned her master’s and doctorate in pharmacy administration in 1980 and 1983, respectively. She made important strides in developing the field of pharmacy benefit management (PBM) over the course of her career, co-founding one of the first PBM companies, Clinical Pharmacy Advantage, in 1990. Over the course of her career, Dr. Thomas has held senior management positions at all of the following companies: MedCenters Health Plans, Aetna, McKesson, PCS, Eli Lilly, St. Jude Medical, Schering-Plough, and Magellan Health Services. She also helped establish the Academy of Managed Care Pharmacy. From 2009 to 2010, Dr. Thomas served as an adjunct professor at the University, coordinating Dialogues in Managed Care Pharmacy Leadership, which sought to highlight leadership within the pharmacy profession. She currently serves president and managing director of Manchester Square Group.
Interview with Stanley Finkelstein
(University of Minnesota, 2014-11-06) Finkelstein, Stanley; Tobbell, Dominique
Stanley Finkelstein begins by discussing his educational background and his arrival at the University of Minnesota. He describes at length his research in the field of home monitoring and telehealth, including his research with Jay N. Cohn on the development of a device to measure and monitor arteriovascular compliance in order to diagnose and monitor hypertension and congestive heart failure; his research with Warren Warwick and the development of the first home monitoring system for cystic fibrosis patients; and the subsequent development of home monitoring of lung transplant patients in collaboration with Marshall Hertz. Dr. Finkelstein goes on to discuss the NLM training grant program; the lack of institutional support provided to the Division of Health Computer Sciences; the development of the Institute for Health Informatics; the leadership of Eugene Ackerman and Laël Gatewood; the number of women in the field of biomedical engineering and health informatics; the relationship between the Division of Health Computer Sciences and the Biomedical Library; the collaborative relationship between the University of Minnesota and the Mayo Clinic; and the development of the Masters in Health Informatics.
Interview with Stuart Speedie
(2015-01-29) Speedie, Stuart; Tobbell, Dominique
Stuart Speedie begins by discussing his educational background and his early career spent first at the Northwest Regional Educational Laboratory in Portland, Oregon, and then at the University of Maryland School of Pharmacy where he served as Director of Education. He discusses his early interest in information systems and technology and his five-year NSF-funded research project on the development of expert systems on the appropriate use of drugs in hospital settings, which he developed during a sabbatical year at Stanford University. He describes his responsibilities disseminating information technology at the University of Maryland and the information systems research he conducted there. Next he discusses his move to the University of Minnesota, his appointment in the Division of Health Computer Sciences and in the office of the Provost of the Academic Health Center, and his role on the Provost’s Reengineering Task Force on Information Technology. He discusses his role within the Division of Health Computer Sciences (subsequently renamed the Division of Health Informatics); his work in telehealth and telemedicine; and his collaboration with Stanley Finkelstein on the use of telehealth technologies in homecare. He next discusses the NLM Research Training in Medical Informatics program. He describes the efforts to establish the terminal Masters in Health Informatics; the influence of different directors—Laël Gatewood, Donald Connelly, Julie Jacko—on the Division and later, the Institute for Health Informatics; his collaborations with Donald Connelly on the impact of health information exchange on patients and hospital emergency departments; the influence of Connie Delaney’s appointment to the Institute for Health Informatics; and the Division and Institute’s long-term relationship with the Mayo Clinic.
Patient driven clinical decision support instrument for predicting cardiovascular complications of non-cardiac surgery - creation, implementation, and evaluation
(2014-04) Manaktala, Sharad
In the wake of increasingly frequent surgical interventions, it is a significant challenge for a clinical practitioner to provide proper evidence based preoperative evaluations, given the constantly changing clinical evidence and the broad realm of specialty literature pertinent to preoperative testing and risk management. There is a critical need for patients to identify their clinical risk factors to effectively identify and manage surgical risk. However, there is a paucity of tools for patient driven self-identification of clinical risk factors, as many evidence driven tools have not readily translated from disparate research studies into patient and clinician use at the point of care. With the ultimate goal of creating a patient-driven cardiac self-assessment tool for preoperative risk assessment and planning, we executed a combination of three separate research studies, leveraging clinical guidelines and best practice recommendations, informatics and usability principles. Utilizing the results and inference from these respective studies, we successfully created the foundations for a patient driven information acquisition tool based on recommendations of evidence based research. The examination and validation of patient reported self-assessment of pre-operative cardiac risk against gold standard provider assessment cardiovascular risk provided important data for objective risk assessment. The comparison of patient risk perceptions to provider perceived risk for post-operative complications created data on patient appreciation of surgical risk. The evaluation of end clinician-user attitudes, satisfaction and ease of use for using the web based decision support yielded data on clinical usefulness. The results from the observations and analysis of these three studies will serve to create and validate a patient driven health information acquisition and decision support tool, and contribute to clarify provider experience and attitudes on the use of patient reported health information.
Understanding and assessing the usefulness of present on admission indicators as a predictor of hospital readmission
(2014-08) Rosenthal, James Edward
The objective of this study is to evaluate Present on Admission (POA) indicators as a new data source for which to model hospital readmissions. POA indicators for have been in administrative claims data since 2008. POA indicators' primary purpose is to identify Hospital Acquired Conditions (HACs), which represent 0.14% of overall claims. The remaining non-HAC POA data then falls into a category called “other.” This study attempts to gage the secondary usefulness of POA indicators in aiding hospital readmission modeling. Methods This study used Medicare inpatient 5% Limited Data Sets (LDSs) for the years 2008 through 2011. Patient histories were assembled, index and readmission events were established, and datasets representing the primary diagnosis conditions of Acute Myocardial Infarction (AMI), Heart Failure (HF), and Pneumonia (PN) were extracted. CMS methodologies were followed consistent with the limitations of the source data. A base logistic regression model was created to approximate the CMS hospital readmission models. Three readmission periods were examined: 7 days, 15 days, and 30 days. To this base, three POA variables were developed to address the following research questions: P1) Does the presence of any POA=no indicator (condition occurred after admission to hospital) found on an administrative claim correlate to readmission? P2) Does the number of POA=no indicators found on administrative claim correlate to readmission? P3) Does the hospital-specific POA usage rate per year across all available claims correlate to readmission? These three POA variables were added to the three primary diagnosis datasets, and modeled across the three readmission periods, yielding a total of 27 individual statistical models. Results For variable P1, all three readmission periods for AMI were statistically significant at the 95% confidence level indicating an increased likelihood of readmission with odds ratios for 7-day: 1.276 (1.051, 1.547); 15-day: 1.269 (1.076, 1.494); 30-day: 1.316 (1.139, 1.520). HF 15-day odds ratio just exceeded statistical significance at 1.061 (1.009, 1.115). For variable P2, results were at the cusp of statistical significance, but probably not clinical significance at all readmission periods. For variable P3, HF and PN were significant, but showed a reduced likelihood of hospital readmission. The data for 2008 showed the widest errors, 2011 the narrowest, indicating an evolution toward more consistent POA use by providers. The odds ratio for 2011 30-day readmission in the HF dataset returned 0.604 (0.476, 0.765), and PN returned 0.730 (0.539, 0.987).Conclusions POA indicators are not a homogeneous form of data. POA indicators offer an added insight of patient complexity not previously available. POA has personalities based on the primary diagnostic condition. For AMI, there is a link between any POA=no condition during a patient stay and hospital readmission, but this is not true for HF nor PN. When aggregating POA data at the hospital level, HF and PN show a reduced likelihood of hospital readmission, but this does not hold for AMI. This effect could capture the provider's documentation maturity, which is linked to better discharge practices, which in turn reduces readmission.

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