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| back 1 pg 4 of: Chapter 5. Understanding Adverse Events: A Human Factors Framework “Human Error—A Troublesome Term While one frequently finds references to human error in the mass media, the term has actually fallen into disfavor among many patient safety researchers. The reasons are fairly straightforward. The term lacks explanatory power by not explaining anything other than a human was involved in the mishap. Too often the term ‘human error’ connotes blame and a search for the guilty culprits, suggesting some sort of human deficiency or lack of attentiveness. When human error is viewed as a cause rather than a consequence, it serves as a cloak for our ignorance. By serving as an end point rather than a starting point, it retards further understanding. It is essential to recognize that errors or preventable adverse events are simply the symptoms or indicators that there are defects elsewhere in the system and not the defects themselves. In other words, the error is just the tip of the iceberg; it's what lies underneath that we need to worry about. When serious investigations of preventable adverse events are undertaken, the error serves as simply the starting point for a more careful examination of the contributing system defects that led to the error. However, a very common but misdirected response to managing error is to “put out the fire,” identify the individuals involved, determine their culpability, schedule them for retraining or disciplinary action, introduce new procedures or retrofixes, and issue proclamations for greater vigilance. An approach aimed at the individual is the equivalent of swatting individual mosquitoes rather than draining the swamp to address the source of the problem. “ Human-system interfaces include medical devices, controls, displays, equipment location, software controls, design and usability. Can increase medical error if design and usability are not ideal, particularly in emergency situations. Must take into account capability and knowledge of users, including users in a home setting. Implementation of new systems is not only an IT project, the users must master use. Can decrease medical errors with software controls and easy to understand displays. External factors - economic pressures such as increase in outpatient care, versus inpatient care. Science and technology advances that make devices smaller, easy to use. Changing demographics with consumers with more computer literacy. External representations: quickly determine the state of the device |
front 2 2. A large medical technology company decides to develop a state of the art electronic health record. Briefly describe the functional components of an EHR. The company is exploring both traditional and novel ways for physicians to enter data. Describe some of the options available for recording physician entered data. The company would like to increase the flexibility and expressivity of the system relative to conventional EHRs and are looking at cutting-edge solutions. How do you think this may be achieved? | back 2 Functional components of an EHR (p.394)
Options for recording physician entered data Three current mechanisms (p.406)
How to achieve cutting edge solutions? (pp. 417-9)
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front 3 3. Computer decision support (CDS) is a set of methods for providing relevant knowledge to bear on the health care and well-being of a patient. Explain two of the primary purposes of CDS systems. Explain the difference between the concepts of evoking strengths and frequency weights as used in an early CDS (Internist-I). How can CDS tools be used in public health contexts or to further public health goals? | back 3 Primary purposes of CDS systems (pp.644-5):
Difference between evoking strengths and frequency weights
“I may have to remove that question or more likely, that subquestion. Internist was an important topic and system in the history of CDS, but seems to have been removed from the updated text. What a shame.” http://www.fpnotebook.com/mobile/Manage/Computer/ClnclDcsnSprt.htm “Internist-I (1974) followed by Quick Medical Reference (1980)
CDS in public health contexts:
Dr. Murcko’s presentation CDS purposed:
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front 4 4. In 1993, the city of Milwaukee was afflicted with a water-borne parasitic infection, Cryptosporidium. Over 400,000 people became ill and more than 100 died as a result of this outbreak. There have been similar outbreaks reported in other cities affecting a large number of people. How can a surveillance system such as RODS (realtime outbreak and disease surveillance) be used to detect or predict future outbreaks? What are some of the early indicators of a public health outbreak reported in prior studies? Describe one of the detection algorithms. How can data mining of social media be used for early detection of outbreaks? | back 4 Researchers study detectability using real surveillance data collected during real disease outbreaks. RODS can be used to gather continuous data collection, organize the data for analysis, perform data analysis, outbreak or case detection, make a decision, and implement a response action. Detection systems looking for abnormalities - ED complaints (easy to attain, early in disease process, low diagnostic precision), OTC drug sales (available early in the disease process, and electronically available on a daily basis), school absenteeism, internet searches, provider hotline volumes, lab results. Prior studies have taken note of correlations between thermometer sales during influenza outbreaks along with pediatric electrolytes for pediatric respiratory and diarrheal outbreaks. Another example is seen by Stirling et al in which a large waterborne outbreak of a parasite (Cryptosporidium) led to a peak in the sales of OTC diarrhea remedies weeks before precautionary drinking water advisories were released. Mining of social media can foster a faster detection of an outbreak, wouldn’t have to wait for ED complaint reports. Detection Algorithms Include: Univariate, Multivariate, Spatial Scanning, Specialized Algorithms Multivariate algorithms search for anomalies using multiple data streams. An example of this can be seen through GI emergency department visits and the sale of OTC antidiarrheal products. Challenges include false alerts and the computation time. |
front 5 5. According to Porter (2010), “value should always be defined around the customer, and in a well-functioning health care system, the creation of value for patients should determine the rewards for all other actors in the system. Value in healthcare is measured by outcomes achieved. Describe Porter’s three-tiered outcome measures hierarchy. What are some of the elements of a preferred outcomes measure? | back 5 Tier 1 is the health status that is achieved which varies depending on illness or injury. The first level with in this tier is survival/mortality rate. The second level is the degree of health recovery. The second Tier revolves around the recovery process. The first tier is the time it takes to obtain best recover outcome, while the second tier addressed the short-comings of the the quality of care. This second level may involve a misdiagnosis, anxiety, discomfort, failed treatment, etc. The third tier involves the sustainability of health. The first level addresses recurrence of the original disease or associated longer term complications. Measures of time to recurrence and the seriousness of recurrence would fall here. The second level addressed additional complications or illness that were due to the original treatment, hospital visit, surgery, etc. Staff infection pandemic for example. [http://www.nejm.org/doi/suppl/10.1056/NEJMp1011024/suppl_file/nejmp1011024_appendix2.pdf] A few of the elements in outcome measurements efforts should should be to include at least one outcome dimension at each tier of the hierarchy, and ideally one at each level. Measures should be important to the patient, variability, frequency, and practicality. [http://www.nejm.org/doi/suppl/10.1056/NEJMp1011024/suppl_file/nejmp1011024_appendix2.pdf] Elements of preferred outcome measure - value (cost compared to outcomes), efficiency, quality care process, health circumstances (patient’s initial condition), short and long term health.
Shortened: health status: 1. survival 2. degree retained recovery: 1. time required 2. "disunity of care" sustainability: 1. recurrence 2. new problems |
front 6 6. How can methods and theories from human-computer interaction meaningfully inform and shape design, development and implementation of health care information systems? What are some of the steps one can take to promote clinician adoption of new health information technologies? What are some of the consequences of developer’s failure to take into account the workflow of clinicians prior to system implementation? | back 6 Methods and Theories from HCI (pp. 111-2)
Steps to promote adoption
Consequences of failure to take workflows into account
From Dr. Kaufman’s presentation
Steps can include requirements analysis, usability testing, interviewing users, understand the environment. Design process should be iterative. Failure to do so can lead to unintended consequences, including problems with adoption, productivity and patient safety. |
front 7 7. Thirty-forty cents of every dollar spent on health care (half a trillion dollars per year) is spent on costs due to “overuse, underuse, misuse, duplication, system failures, poor communication and inefficiency”. In addition, over 98,000 patients die and more than one million suffer injuries each year as a result of broken health care processes and system failures. What are some of the primary causes of the health-care crisis according to the Institute of Medicine (IOM)? Describe some of the dimensions of quality for healthcare systems according to the IOM. What are some of the concrete measure we can take to improve quality? | back 7 “The Institute of Medicine’s (IOM) National Roundtable on Health Care Quality documents three types of quality problems—overuse, underuse, and misuse” “Four key aspects of the current context for health care delivery help explain the quality problems outlined above: the growing complexity of science and technology, the increase in chronic conditions, a poorly organized delivery system, and constraints on exploiting the revolution in information technology.” “Six specific aims for improvement. Health care should be:
Source: (You’ll need to make a free account on the site to download, Chapters 1 and 2) http://iom.edu/Reports/2001/Crossing-the-Quality-Chasm-A-New-Health-System-for-the-21st-Century.aspx -------- or Dr. Kaufman’s Systems Engineering presentation Primary causes: rapid advances (increasing complexity), increase in specialization (disconnected silos), patient population needing chronic care. Also structure of US market for health care services, underinvestment in information and communications technology, inability or unwillingness to take advantage of engineering based system design analysis and management tools. Dimensions of quality: Safe, effective, patient-centered, timely, efficient, equitable Measures we can take: Measures to improve quality - use concurrent engineering to overcome silos, use teams of specialists. Understand stakeholder needs, streamline processes. Systems control |
front 8 8. Describe three of the tasks involved in the radiologic process. How can these tasks be augmented or enhanced by information technologies? According to Dr. Liang, “the performance of a CAD system does not have to be comparable to or better than that by physicians, but it needs to be complementary to that by physicians”. Explain what is meant by this statement. | back 8 Radiologic Process Tasks:
How can these tasks be enhanced through IT? 4<==Technology largely impacts the manner in which groups operate and think. When using an effective medical information system, physicians should be able to gather information more systematically and efficiently. Information technologies may alleviate some of the cognitive load associated with a given task and permit them to focus on higher-order thinking skills, such as diagnostic hypothesis generation and evaluation. 5<==Information technology can significantly improve the manner in which radiologists create patient reports. Within the healthcare field, comprehensive, longitudinal, clinical databases (i.e. a paperless, complete medical record) significantly enhance the integration of healthcare delivery. Will provide a complete picture of the patient's medical history and will assist in avoiding duplicate tests being performed and unfavorable drug interactions. 7<== In an attempt to continue physician education and training, computer-assisted learning systems can be utilized in order to to provide physicians with quick access to references and new content. Most importantly, these lessons are highly individualized and may exercise a physician's knowledge and decision-making capabilities within a nonthreatening environment.
Needs to be complementary
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front 9 9. The goal of Translational Medicine Research is to better understand the underlying biological and environmental factors that influence disease with the aim of developing practical applications to directly benefit the outcome of patient care. Describe some of the ways in which bioinformatics can impact practice of medicine. Will the introduction of DNA and protein sequence information change the way that medical records are managed in the future? | back 9 Bioinformatics create new diagnostic and prognostic information sources that influence clinical care. Single nucleotide polymorphisms (SNPs) and other genetic markers from a patient will be highly specific and sensitive indicator of the subtype of disease and of that subtype’s probable responsiveness to different therapeutic agents. They also use as prognostic tools to guide health management based on individualized risk of disease in the future. Historically, guidelines for a healthy lifestyle have been presented as universal. Clinical care guideline have been based primarily on macroscopic symptoms and qualities that can be observed in the course of a physical exam or reported by the patient. (BMI book ch 24 Bioinformatic p.697-698, ch 25 translational bioinformatics p.724, 726) Due to large genetic sequence information, the EHRs need to adopt new standards for describing clinically significant genomic information as well as, to develop the way to;
(any other suggestion?) (http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3328607/) |
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| back 10 GINA - Genetic Information Nondiscrimination Act of 2008 HIPAA protects an individual identifiable health information held by covered entities and give patients right in respect to that information. However the privacy rule also allows researchers access to this information after it has been de-identified. The same thing will probably happen with GINA which is to assure that health coverage and employment will not be allowed to discriminate based on genomic information. To build trust with its patients and meet HIPAA requirements, a healthcare organization (HCO) should adopt a three-pronged approach to securing information. First, HCO need to designate a security officer and develop uniform security and confidentiality policies, including specification of sanctions and to enforce these policies rigorously. Second the HCO needs to train employees so they understand the appropriate uses of patient-identifiable information and the consequences of violations. Third, the HCO must use electronic tools such intrusion detection, access control and audit trails not only to discourage misuse of information but also to inform employees and patients that people who access confidential information without proper authorization or a “need to know” can be tracked and will be held accountable. (Ref BMI book ch 14 p. 454-455) |
front 11 11. Characterize how the model of immunization registries can be used in other domains of public health. What are the limitations to its generalizability? | back 11 “Immunization registries are public health tools that facilitate high immunization coverage rates and minimize children being over immunized.” Contain record of children from specific geographic area, info about what immunizations they have had. Usually entered in to record at birth or first immunization(first immunization is for Hep.B at birth). Registry model could be used to also classify those with diseases and track prevalence and spread of disease. Could contain registry of people with AIDS or common chronic spreadable disease. Registry could also be applied to people’s genomic information. Could be used to track people’s health patterns - how often they see the doctor, what their diet is like, how often they exercise, how many hours a week they work ect. This info could be quantified and mined to produce a relationship of patient’s habits to their health. Other thoughts?? Registry model has ethical limitations and considerations, like if patients want their information in a format like that. Who would have access to it and for what reasons ect. |
front 12 12. If a patient’s entire genome were present in their medical record how would one go about interpreting it clinically? Similarly, if we had an entire electronic health record database that included human genomes, how would a researcher go about finding new or novel genetic associations? | back 12 (Textbook p:697) The sequence of a gene involved in disease may provide the critical information that we need to select appropriate treatments. For example, the set of genes that produces essential hypertension may be understood at a level sufficient to allow us to target antihypertensive medications based on the precise configuration of these genes. Clinical trials now use information about genetic sequence to define precisely the population of patients who would benefit from a new therapeutic agent. Finally, clinicians may learn the sequences of infectious agents (such as of the Escherichia coli strain that causes recurrent urinary tract infections) and store them in a patient’s record to record the precise pathogenicity and drug susceptibility observed during an episode of illness. Raw sequence information, whether from the patient or the pathogen, is meaningless without context and thus is not well suited to a printed medical record Like images (CAT scans, MRIs), sequence data can come in high information density and must be presented to the clinician in novel ways. As there are for laboratory tests, there may be a set of nondisease (or normal) values to use as comparisons, and there may be diffi culties in interpreting abnormal values. Fortunately, most of the human genome is shared and identical among individuals; less than 1 % of the genome seems to be unique to individuals. Nonetheless, the effects of sequence information on clinical databases will be significant. As an example, Kaiser Permanente and UCSF recently completed identifying genome wide genetic variants in 100,000 individuals linked to their electronic health records. 1 The EMERGE research network is specifically focused on genetic discovery and replication using electronic medical records and genetics. |
front 13 13. The Mayo Clinic has just completed a large scale implementation of comprehensive electronic health record systems. However, the intensive care unit is complaining that the new system has caused significant disruptions in the coordination of patient care. Develop a plan for a stepwise usability evaluation which should include both usability inspection and usability-testing methods. What are some of the other factors that you would consider (aside from usability) that may explain the substandard performance in the ICU setting. | back 13 Plan for usability evaluation: start with quick low-cost methods, increase in rigor as necessary (see pp.128-133)
Other factors to consider: maybe the problem is not really the software. The problems could have to do with the physical environment, work processes, lack of training, staff resistance, location and number of EHR workstations, etc.
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front 14 14. Researchers are increasingly turning to social media as a source of real-time data for biomedicine. Describe some of the information researchers may be able to extract and how it could be useful. What informatics techniques do researchers use to extract that information? | back 14 Info: There are numerous benefits to real-time data which includes a larger information platform in which large quantity of data may be garnered in real-time. Such sites include popular blogspots along with Twitter or Facebook. In considering adverse Drug Reactions(ADR) Public Health info like spreading of diseases or disease prevalence Technique: Text mining - Machine Learning==> machine learns a model by generalinzing from training data Process of discovering and extracting new knowledge from unstructured data |
front 15 15. Personal technology is ever expanding and becoming more and more sophisticated. What was once solely a tool for communication is expanding to be able to do much more including tracking our locations, speeds, heart rate, etc. along with other pieces of technology we can wear to gather even more information. What do these mobile and wearable technologies mean for our health? What are some benefits and disadvantages of these technologies? Explain some of the challenges. | back 15 Mean: Wearable computers creates new opportunities for local environment data collection, personal vital sign and activities and more through disease monitoring. Advantages: We can expect the use of these massive data sets from wearable devices to impact how medical care is personalized and patient decision making. Disadvantages: However they posing threats to personal privacy and reliable health data. Challenges: Interoperability, security, quality, health literacy, availability (digital divide) |
front 16 16. The gap in quality of healthcare in the United States is staggering - some of the world’s best and worst healthcare is found here. What are some of the reasons for this extreme variability? Why do some states, regions or hospitals do so well and others do so poorly? Use concepts from the systemic view of healthcare to explain the stark differences. Briefly explain how large data sets may help us better understand the problem and fashion appropriate solutions. | back 16 Other factors: socio-economic, genetics, behavior Reasons for variability: Why some regions do well and others poorly:
Explain the differences:
How big data can help:
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front 17 1. According to Cortese (lecture), what are the elements required to have a functioning high value healthcare system? | back 17 Value (value=quality/cost=(outcomes, safety, service)/(cost over time)) Individualized medicine (for the individual, and targeted populations) Science of health care delivery (systematic coordination for complex conditions) Integration and coordination (of people & data) He also mentions: insurance for all (equal access to care), and pay for value Cortese lecture, slide 4: Components of a Learning Healthcare System:
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front 18 2. Briefly explain an advantage and a disadvantage to increasing the number of physicians in the United States. | back 18 An advantage of increasing the number of physicians within the United States is that there will be a decrease in the amount of time that patients will have to wait for any appointments or elective surgeries. A disadvantage of such an action includes the fact that through an increase in the number of physicians, there will also be an increase in the number of fee-for-services which largely requires for patients to pay for services out of pocket. Along with such a disadvantage, there will also be a higher health cost per capita. |
front 19 3. What are some of the dimensions that differentiate the field of human factors from human computer interaction? | back 19 Human factors deals with safety in a system and how people work with the system. Human factors includes information about human behavior, abilities, limitations, and design of tools for human use (p. 133 in book). Human computer interaction deals specifically with design and usability (p. 128 in book). |
front 20 4. Explain the difference between public health informatics and clinical informatics. | back 20 Public health informatics focuses upon the health of a population, while clinical informatics is focused upon individual health In considering the strategy of public health, it is prevention while clinical informatics strategy is based upon treatment. Public health informatics may take place in any setting while clinincal informatics is an encounter. Lastly, public health informatics operates with the government while clinical informatics operates with both the government and private sectors. |
front 21 5. Describe some of the principle assumptions of a cognitive walkthrough. | back 21 It emphasizes sequential processes. It also assumes that the reviewer understands something of the typical user's existing knowledge and practices. ---The cognitive walkthrough (CW) is a cognitive task-analytic
method that has been |
front 22 6. Briefly explain why shared decision making may be important in the treatment of cancer patients. | back 22 Shared decision-making (SDM) is an approach where clinicians and patients communicate together using the best available evidence when faced with the task of making decisions, where patients are supported to deliberate about the possible attributes and consequences of options, to arrive at informed preferences in making a determination about the best action and which respects patient autonomy, where this is desired, ethical and legal.(Wikipedia) It is important when treating a cancer patient because the patient may value living the rest of their life without treatment, rather than being treated - living a little longer - but having their quality of life be worse during those years they are alive/being treated. Kaufman’s presentation on Systems Engineering - breaking down silos, distributed decision making. Book chapter 4 - limitations of each decision making, cognitive load, different levels of medical cognition, different levels of expertise min medicine and the reasoning process, distributed cognition. Kaufman’s Consumer Health presentation - clinical decisions involve judgment, interventions have risks and benefits, no single right answer for everyone, health care providers cannot guess at what patients value, health care providers cannot assume what is in patient’s best interest, evidence-based practice movement. |
front 23 7. What factors contribute to the increasing pressure for health consumers and patients to actively participate in their health care? | back 23 Cost is a major pressure that is being put on consumers and patients, and the more the actively participate in maintaining their health the less they will have to pay out in the future. Modern technological advances give them the obligation to become more involved through education, biosensor, medical portals etc. it says factors plural it is s stretch though. thoughts? Partitioning of patient care and coordination of medical records? |
front 24 8. Explain the different between active and latent failure. | back 24 (p. 135 in book) Active failures are immediately felt, are at the “sharp end” of the process. Latent conditions are less visible, may not be evident for some time, and weaken the system’s defenses, make errors possible. |
front 25 9. Identify 3 different ways (or forms) to deliver clinical decision support. | back 25 According to Dr. Murcko’s presentation: alerts, reminders clinical guidelines order sets and checklists reports and summaries dashboards templates pertinent references at key points in the workflow - info buttons |
front 26 10. Describe 2 or 3 needs for clinical decision support in medicine. | back 26 Clarified this with Dr. Kaufman, he says this question is “What are three purposes or uses for clinical decision support.” from Dr. Murcko’s presentation: find information, help make decisions, perform a computation, manage and optimize process and workflow, monitor (alerts, reminders, feedback), organize information, focus attention. According to Dr. Murcko’s presentation: personal/professional - need perceived value of CDS organizations - need workflow, smoothness of integration, leadership business - incentives for users, ROI technical - software, hardware, interoperability |
front 27 11. Explain the concept of selective attention and its relation to medical error. | back 27 According to Dr.Kaufman`s presentation: (Human Factors and HCI):
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front 28 12. Explain the concept of dashboards and how they may improve the EMR user experience. | back 28 A dashboard is a graphical summary, and can be used in an EMR to provide a summary of a patient’s health and healthcare alerts. Dashboards can also be targeted to show information relevant to the clinician's concerns; a neurologist will be looking for different information than an endocrinologist. |
front 29 13. Explain the differences among contrast, spatial and temporal resolution (in the context of imaging). | back 29 Contrast - difference in image intensity, bits per pixel Spatial - ability to distinguish, sharpness, pixels per area Temporal - time needed to create, frames per second |
front 30 14. What does the term “mental model” refer to and why is it an important construct in human-computer interaction? | back 30 --A form of mental representation that enables one to understand how something in the world works. One can run a mental model to predict future states of a system (what happens when I click this link) or to explain the cause of a change in the state of a system (why did my computer crash) A mental model is an explanation of someone's thought process about how something works in the real world. (p. 119 in book) Mental model refers to how individuals form internal models of systems. They are always incomplete, imperfect, and subject to the processing limitations of the cognitive system. They are useful in understanding HCI. |
front 31 15. Explain how ontologies can be used in the biosurveillance process. | back 31 Ontologies are used in the process of organizing biosurveillance data to set up infrastructures for data analysis. The data comes from various source such as laboratories, hospitals, pharmacy etc. Ontologies set up concepts for different data types and define the relationships between those concepts in order to effectively utilize and retrieve data. (BMI 501 Biosurveillance slide page 3 + opinion) |
front 32 16. Discuss three barriers to technology transfer among healthcare institutions. | back 32 Lack of standards for interoperability (Greenes lecture) Lack of common incentives / conflicting goals (Porter paper) Interoperability patient privacy ethical concerns (who has access, when, and why) big data (storage/retrieval negotitive concerns) |
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| back 33 Concurrent engineering is an approach in which a particular problem may be cut into separate fragments to be worked on by various groups and ultimately the problem will be solved through the collective development of an effective solution. It can be used to overcome silos of function and responsibility and additional benefits include: a decrease in the number of design changes, a reduction in the design-to-delivery time, a decrease in defects, lower costs, improved teamwork, cross-training, improved quantitative and qualitative characterization of processes and systems. |
front 34 18. Explain the term failure-mode effects analysis. | back 34 Systematic technique for failure analysis. developed in 1950s to study problems with military systems. First step in system reliability study. Reviews as many components, assemblies and subsystems as possible to identify failure modes and their causes and effects. Failure modes: ways, or modes, that something might fail(any error/defects) Effect Analysis: refers to study of consequences of failures Definition of failure-mode effects analysis - systematic, proactive method to evaluate processes to identify where and how it might fail. Asses the impact of these failures Source : http://www.ihi.org/resources/Pages/Tools/FailureModesandEffectsAnalysisTool.aspx |
front 35 19. Banner Health (hospital) would like to be able to predict 30 day readmission rates. Briefly explain what is necessary to accomplish this goal. | back 35 To accomplish this goal, people need to develop data mining process by: -Must first define what readmission is (i.e. it is within x amount of days) -Understanding data which is understand what data is in EHR. -Preparation for data which is identify what risks for readmission are such as age, comorbidity, critical laboratory results. -Modeling algorithm which is use of machine learning to develop a predictive model. -Evaluation of algorithm which is evaluate performance of the learn model in test data and redevelop the learn model. - Cooperation to obtain “loss to follow-up:” when the patient is readmitted, but somewhere else and we don't know about it. -use past cases and data on readmission to infer about the future |
front 36 20. Name and give a brief description of two of the three classifications of subtasks for text-mining activities. | back 36
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front 37 21. How does pragmatic analysis differ from semantic analysis? | back 37 Pragmatic: subfield of linguistics and semiotics studies ways in which context contributes to meaning Semantic Analysis: process of relating syntactic structures to the level of writing as a whole. Also involves removing features specific to particular linguistics and cultural contexts. -So: Pragmatics = impact of context and of intent of the speaker on meaning Semantics = meaning of words, phrases, and sentences |
front 38 22. What are some of the NLP challenges in dealing with clinical language? | back 38 (p. 257 in book) Abbreviated words, misspelled words, typographical errors, word sense disambiguation, semantics, |
front 39 23. Explain pharmacogenomics. | back 39 Science that seeks to explain how variations in the human genome can affect the individual response to drugs. |
front 40 24. How can personalized medicine be used to reduce the risk of Warfarin-associated bleeding (or another problem of your choice). | back 40 Due to variability in patient response to this drug, including genetic variations, the dose is based on an algorithm that includes the gene encoding for a specific enzyme that metabolizes the drug and a gene encoding for the target receptor of the drug. |
front 41 25. Define or briefly explain the significance of single nucleotide polymorphisms (SNPs). | back 41 SNP is the DNA sequence variation that occurs when a single
nucleotide in the genome sequence is altered. In other words, it is a
mutation. An SNP can cause the transcribed amino acid to differ and
intern the translated protein to slightly differ, possibly changing
structure and function.
--A DNA sequence variation, occurring when a single nucleotide in the genome is altered. For example, an SNP might change the nucleotide sequence AAGCCTA to AAGCTTA. A variation must occur in at least 1% of the population to be considered an SNP. |
front 42 26. What are problems associated with analyzing biological sequence, structure and function? | back 42 Noise in samples which needs lots of steps in preprocessing samples and noise in sequencing data which needs several analytical steps to quantify differentially expressed genes High error rates (Sequencing errors and alignment errors) for long reads of base pair (3-7000 bp) (BMI 501 Bioinformatic lecture slide p.37, 44-46 + opinion) From Peng’s presentation slide 26/27 - data deluge, computational limitations, incomplete sequences, cost |
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| back 43 Problems are the lacks of ability to interchange or transfer images and associated information between devices manufactured by different vendors that display a variety of digital image format. (BMI book chapter 7 page 238-239) Prior to Digital Imaging and Communications in Medicine (DICOM), the public was in need of a standard method that would enable them to transfer their images and associated information between devices that featured a broad range of digital imaging formats. Such a high level of variety resulted from the fact that these products were being manufactured by various vendors. DICOM provides a specified image-related management information exchange, with the potential to interface to hospital and radiology information systems. |
front 44 28. What are the three main parameters of image quality? Briefly explain each one. | back 44 - Spatial Resolution (Sharpness of the image); A measure of the ability to distinguish between two close objects on an image, related to the number of pixels per image area – Contrast Resolution; A measure of the ability to distinguish small differences in image intensity. Generally, related to the number of bits per pixel – Temporal Resolution; A measure of the time needed to create an image. Generally, related to the number of frames per second (BMI 501 imaging informatics slide page 40-45) lectured on 11/25/14 |
front 45 29. EHR data is central for patient care. Identify three other purposes of this data. | back 45
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front 46 30. Describe difficulties with the current approach to measuring health outcomes. | back 46 1.Outcome measures in different contexts, such as quality improvement, public reporting, and incentive programs, can be different.
3.The need to account for all factors that influence a patient's health outcome such as comorbidities, behaviors and other important technical questions such as the sample sizes. (This is the best source I can find. Not sure it is a good answer.) (http://www.qualitymeasures.ahrq.gov/tutorial/HealthOutcomeMeasure.aspx) Porter article - current measures dead @ discharge, readmission w/in 30 days. Not included mortality after 30 days, sustainable health, functional capacity, health related costs, problems with prescription drugs. |
front 47 31. Describe an advantage and a limitation to Big Data. | back 47 Advantages and disadvantages of Big Data + Big data can be used to support knowledge discovery and associations of health factors such as finding biomarkers and prediction of disease outbreaks in biosurveillance in timely manner. Disadvantage - Unknown population representation - Issues of data quality - Typically not very multivariate (at the person level) - Privacy and confidentiality issues - Difficult to assess accuracy and uncertainty (http://www.cdc.gov/nchs/data/bsc/bscpres_schenker_091913.pdf) + opinion |
front 48 32. What are some of the difficulties in measuring healthcare outcomes? | back 48 Same as question 30 Don’t follow patients, don’t share information. |
front 49 33. Identify three challenges listed by Sitting and colleagues to improve clinical decision support systems | back 49 -Summary of the grand challenges of clinical decision support Improve the human-computer interface Disseminate best practices in CDS design, development, and implementation Summarize patient-level information Prioritize and filter recommendations to the user Create an architecture for sharing executable CDS modules and services Combine recommendations for patients with co-morbidities Prioritize CDS content development and implementation Create internet-accessible clinical decision support repositories Use freetext information to drive clinical decision support Mine large clinical databases to create new CDS Sittig DF1, Wright A, Osheroff JA, Middleton B, Teich JM, Ash JS, Campbell E, Bates DW. Grand challenges in clinical decision support. J Biomed Inform. 2008 Apr;41(2):387-92. Epub 2007 Sep 21. http://www.ncbi.nlm.nih.gov/pubmed/18029232 |
front 50 34. Describe 3 types of clinical decision support. | back 50 (pp. 643-4)
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front 51 35. Distinguish between an EHR, EMR and PHR. | back 51 EMR - Electronic medical record, information about a patient’s health status and health care, also includes information management tools, clinical reminders, links to knowledge sources, analysis of aggregate data. Maintained by one health care organization. EHR - Electronic health record, lifetime health status, multiple users, evidence based decision support, outcome reporting, quality management.(interoperable between health care organization) PHR - Personal health record, patient oriented instead of provider oriented, benefits include empowerment, partnership, better decisions, more engaged patients. |
front 52 36. Identify three of the primary components of an EHR | back 52 (from book) - Integrated view of patient data - clinical order entry - clinical decision support - access to knowledge resources - integrated communication and reporting support (from notes) - lab results - notes - discharge summary |
front 53 37. List three advantages of free text records | back 53 -user choice; prefered mode of data entry by clinicians -expressivity; narrative note to express patient history and other observations -flexibility; captures clinical reasoning and idiosyncratic aspects of patient record -more accurate (few errors due to drop down menu selection or checking boxes) (BMI 501 EHR slides lecture on 9/18/14) |
front 54 38. Identify 3 basic sources of biomarkers other than DNA. | back 54 RNA mRNA Proteins Pathways (from my notes) Bile(found it in an article) |
front 55 39. What are some of the barriers to EHR adoption? | back 55 Costs Leadership Usability Privacy and Security Standards Meeting users’ information needs (additional points - From the slides)
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front 56 40. What are advantages and disadvantages of the clinical use of gene expression data? | back 56 Advantages: genetic related disease diagnosis, individualized therapy Disadvantages: discriminating people based on genetic data, selection of newborns (by trial and errors) (my opinion) Disadvantage: some people do not want to know their genetic predispositions; ignorance is bliss |
front 57 41. What is the primary purpose for HL7 standards? | back 57 The purpose is to standardized communicating and exchanging health information between independent computer applications (EHRs). They reduce cost of interfacing between different systems. (p 12 and 220 in BMI book) |
front 58 42. How can text mining methods be used to automatically extract adverse reactions from health postings? | back 58 Researchers use text mining methods to build predictive models from social media posts. They use keywords to collect social media posts containing medication and adverse events words. Then they annotate terms to develop training data and use them to develop lexicon based, rule based or machine learning based algorithms that can classify and extract actual adverse drug reactions from posts. (Ref: NPL in biomedical text mining lecture, slide page 41 -46) |