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EHRs And Disease Prediction

EHRs And Disease Prediction | healthcare technology | Scoop.it

Much of the chatter around electronic health records (EHRs) revolves around efficiency and cost cutting in clinical practice. There is even a bit of discussion about the use of EHRS to improve population health. But is there more benefit to be found in individual patient health?


Perhaps the greatest potential of the EHR, (and the concept applied to a broader application, the EMR) lies in the role it can play in predicting clinical outcomes around a range of diseases and conditions.


This application is still very much in its fledgling stage, but here are just a few examples of how data analytics, when applied to EHRs in mindful ways, can bring about positive changes in patient health.


Predicting Sepsis


One of the most recent examples we saw came out of UC Davis. Researchers there found that, by compiling and analyzing routine information — blood pressure, respiratory rate, temperature, and white blood cell count — as pulled from EHRs, they were able to predict early stages of sepsis, a condition that is a leading cause of hospitalization and death in the U.S. It took them only three measures — lactate level, blood pressure, and respiratory rate — to calculate the likelihood that a patient would die from the condition.

Progressing Kidney Disease


Data from EHRs has also played a key role in predicting the need for dialysis after a patient with chronic kidney disease progresses into kidney failure.


The Journal Of The American Medical Association in 2011 studied patients who were referred to nephrologists between April 1, 2001, and December 31, 2008, in an effort to develop and validate predictive models for the progression of chronic kidney disease.


According to the study, “Our models use laboratory data that are obtained routinely in patients with CKD and could be easily integrated into a laboratory information system or a clinic EHR.” It also notes that emerging literature suggests that the methods lead to “improved patient outcomes with individualized risk prediction and with advances in information technology that allow for easy implementation of risk prediction models as components of EHRs.”


All data for the study where pulled from nephrology clinic EHRs.


Cardiovascular Risk


EHRs have also been used to improve cardiovascular risk prediction. A study (available from the National Institutes Of Health), analyzed whether internal EHR data (using flexible, adaptive statistical methods) could improve clinical risk prediction. The study used the fact that EHRs have been extensively implemented in the VA system as an opportunity for exploration.


It found that, “despite the EHR lacking some risk factors and its imperfect data quality, health care systems may be able to substantially improve risk prediction for their patients by using internally developed EHR-derived models and flexible statistical methodology.”


Controlling Hypertension


Another prevalent health issue in the U.S., hypertension, has seen researchers apply predictive analytics using EHR data to gain more insight into the disease. This study, from the Journal Of Informatics In Health And Biomedicine, sought to identify transition points at which hypertension is brought in, as well as pushed out of, control, through the use of EHR data.


The study of 1294 patients with hypertension (who were enrolled in a chronic disease management program at the Vanderbilt University Medical Center) found that accurate prediction of transition points from a control status could be achieved

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EHR Analysis More Effective, Cost Efficient Than Clinical Trials

The use of electronic health records to identify the best treatment option for patients is more efficient and less costly than the current clinical trial process, according to a study published in the journal Health Technology Assessment

Study Details

For the study, which was funded in part by the National Institute for Health Research and the Welcome Trust, researchers from several universities in the United Kingdom, used a new computer program in 23 approved general practitioners across England and Scotland.


The first part of the study used 300 patients' electronic health records, which are stored in the Clinical Practice Research Datalink and updated during routine medical visits, to monitor the effects of their prescribed treatments.


A second part of the study, which involved 31 participants, looked at the use of antibiotics among patients with chronic obstructive pulmonary disease.

Study Findings

The researchers determined that they were able to understand health patterns related to specific prescribed medications and determine which treatments were more effective by analyzing EHRs.


They added that the EHR analysis offers a larger and more diverse overview of the general population than current clinical trial methods.

The researchers also noted that using EHRs allows the analysis to be conducted with minimal effects on the lives of the patients, whose involvement in the process stops after their initial consent.


According to the researchers, 26 out of 27 general practitioners who participated in the study expressed strong support for the use of patients' EHRs for research purposes. In addition, 10 patients who were interviewed by the researchers all said that their involvement in trial was an acceptable practice

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EHRs Detect Depression When Many PCPs Can’t

EHRs Detect Depression When Many PCPs Can’t | healthcare technology | Scoop.it

Depression is one of the hardest disorders to diagnose, yet it affects 14 percent of the world’s population. Researchers have found factors in EHRs may be key to predicting a diagnosis of depression.


While depression comes at a high cost to those who suffer from it, the actual price tag in the United States reaches over $44 billion annually. This takes into account, among other things, lost productivity and direct expenses. Depression is a diagnosis that is often missed by primary care physicians, despite the fact that it is the second most common chronic disorder they treat.


According to EHR Intelligence, researchers from Stanford University have worked to use EHR systems as a tool to help predict depression diagnoses. In the study, published by the Journal of the American Medical Informatics Association, researchers say valuable information already stored in the EHR can be used to predict depression up to a year in advance.


“Depression is a prevalent disorder difficult to diagnose and treat. In particular, depressed patients exhibit largely unpredictable responses to treatment,” explain researchers. “Many depressed patients are not even diagnosed … primary care physicians, who deliver the majority of care for depression, only identify about 50 percent of true depression cases.”


The Stanford team used EHR data including demographic data, ICD-9, RxNorm, CPT codes, progress notes, and pathology, radiology, and transcription reports. From these, they used a model which factored in three criteria: the ICD-9 code, the presence of a depression disorder term in the clinical text, and the presence of an anti-depressive drug ingredient term in the clinical text.


These factors were then compared to predict a diagnosis of depression, response to treatment, and determine the severity of the condition.


more at http://www.healthitoutcomes.com/doc/ehrs-detect-depression-when-many-pcps-can-t-0001


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Automated safety checklists prevent hospital-acquired infections, Stanford team finds

Automated safety checklists prevent hospital-acquired infections, Stanford team finds | healthcare technology | Scoop.it

Pilots, astronauts and workers in other high-risk industries follow rigorous safety checklists to help them avoid hazards. Checklists have shown potential to reduce risk in health care, too, but the challenge is figuring out how to incorporate them into physicians’ and nurses’ work flow.


A Stanford team has built a solution: an automated checklist that pulls data directly from patients’ electronic medical records and pushes alerts to caregivers. The checklist, and a dashboard-style interface they used to interact with it, caused a three-fold drop in the rates of a serious type of hospital-acquired infection, the team found. The work has just been published in Pediatrics.


From our press release about the study:

“Electronic medical records are data-rich and information-poor,” said Natalie Pageler, MD, the study’s lead author. Often, the data in electronic medical records is cumbersome for caregivers to use in real time, but the study showed a way to change that, said Pageler, who is a critical care medicine specialist at the hospital and a clinical associate professor of pediatrics. “Our new tool lets physicians focus on taking care of the patient while automating some of the background safety checks.”


Working in the pediatric intensive care unit at Lucile Packard Children’s Hospital Stanford, the researchers focused on bloodstream infections that occur via central lines, which are catheters inserted in major veins. The automated alerts were designed to help physicians and nurses follow an established set of best practices for caring for central lines. For example, alerts were generated when the dressing on a patient’s central line was due to be changed.


The drop in the rate of central line infections – from 2.6 to 0.7 infections per 1,000 days of central line use – not only protected patients from harm; it also saved money. The team estimated that the savings in the pediatric intensive care unit were about $260,000 per year.


Next, the researchers hope to adapt the automated checklists to other uses, such as helping to guide the recovery of patients who have received organ transplants.

- See more at: http://scopeblog.stanford.edu/2014/02/24/automated-safety-checklists-prevent-hospital-acquired-infections-stanford-team-finds/#sthash.g2pYygq4.dpuf


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Justine Campagna's curator insight, July 17, 4:57 AM

What a great way to improve health and safety within hospitals!

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How does patient engagement transform into useful EHR data?

How does patient engagement transform into useful EHR data? | healthcare technology | Scoop.it

Patient engagement represents the next aim of healthcare reform through the adoption of health IT systems and services. It just received a boost from PCORI which awarded $93.5 million for the creation of 29 clinical research data networks that will combine to form its National Patient-Centered Clinical Research Network (PCORnet).


A major aim of establishing these networks is to enable the patient population to play an active role in how their care is delivered. “One of the reasons people think we should be engaging patients more actively is to make sure that as we do research we’re measuring and assessing the kinds of things they want to know when they’re making medical decisions,” says Elizabeth McGlynn, PhD, Director of the Center for Effectiveness & Safety Research at Kaiser Permanente.


“While we appreciate that more traditional biometric information may be important,” she continues, “there are a number of other things that any of us who have had to make decisions about whether or not to have a surgical procedure or take a particular drug would like to know beyond some of that information.”
McGlynn and her team of researchers will rely on its network, Partners Patient Outcomes Research To Advance Learning (PORTAL), to change how a healthcare organization learns from its patients, namely in bridging the gap between the latter and researchers. “The whole area of engaging patients more actively and comprehensively in research is an evolving one. 

At a high level, the challenges for the project are two-fold. On the one hand, researchers need to be able to understand how patients want to be engaged:

We know that patients aren’t homogenous; we know that there’s a range of opinion. These kinds of tools give us the chance to continue to appreciate the diversity of ideas and opinions and avoid trying to just get to the one or the two leading ideas but really to think. As people are exploring the notion of what personalized medicine means, how do we make sure that we’re eliciting information from people about what’s important to them personally?

On the other hand, they must tackle the challenge of making this feedback available to clinicians in a meaningful way:

One of our big challenges is finding ways to effectively integrate that information into the electronic health record. We have some work underway right now that’s given us some early insights into what patients are willing to provide if their doctors are going to see it and use it but if it’s just a hypothetical exercise, not so interested.



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Mike Vassel's curator insight, January 15, 10:54 AM

Interesting article.  I believe that a healthy patient is engaged and proactive in their own wellbeing. 

Renzogracie academy's curator insight, January 17, 3:03 AM
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Drug Companies Could Use EHR Systems for Targeted Marketing

Drug Companies Could Use EHR Systems for Targeted Marketing | healthcare technology | Scoop.it

Pharmaceutical companies increasingly are using electronic health records to analyze patient data and market their products to consumers and physicians through advertisements and email campaigns.


Electronic health record systems could be used by pharmaceutical companies to market their products to physicians and consumers,Reuters reports.


Pharmaceutical companies historically have gathered patients' de-identified data from insurers, pharmacies and public records to improve their marketing strategies.


However, drug companies can collect and analyze data through EHR systems and use that information to reach out to consumers and doctors.

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EHR Promotes Better Understanding of Multiple Sclerosis

EHR Promotes Better Understanding of Multiple Sclerosis | healthcare technology | Scoop.it

Researchers at Vanderbilt University Medical Center have used natural language processing technology in an electronic medical records system to identify patients with multiple sclerosis and collect data on traits of their disease course.


The work is significant, researchers say, because much remains unknown about the course of the disease, which varies widely among patients. “Most research studies have focused on the origin of the disease, partly because of the difficulty in ascertaining sufficient longitudinal clinical data to study the disease course,” according to the study published in the Journal of the American Medical Informatics Association.


“Electronic medical records may provide such a tool. We have previously shown that genomic signals of MS risk may be replicated using EMR-derived cohorts. In this paper, we evaluated algorithms to extract detailed clinical information for the disease course of MS.”


The study used algorithms based on ICD-9 codes, text keywords and medications to identify 5,789 patients with MS, and collected detailed data on the clinical course of the patients’ disease to measure progression of disability. “For all clinical traits extracted, precision was at least 87 percent and specificity was greater than 80 percent.”


 
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Tech4MD's curator insight, December 27, 2013 11:52 AM

Good benefit of using a good EHR!

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The Use Of Tablets In the World of EMRs ~ EMR, EHR & Health Care Technology

The Use Of Tablets In the World of EMRs ~ EMR, EHR & Health Care Technology | healthcare technology | Scoop.it

With a growing number of physicians adopting tablet PCs for their EMR implementations, EMR vendors and IT manufacturers are looking to build compatible native systems to facilitate user-friendly and efficient EMR execution.

 

From table desktops to thin clients and now the tablet, EMRs have been tried and tested on a variety of hardware, each bringing its own benefits and drawbacks. However, the striking surge in EMR adoption on tablet PCs has made providers sit up and take notice of this remarkably promising technology.

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Who are EMRs for, anyway

Who are EMRs for, anyway | healthcare technology | Scoop.it
Ongoing resistance to EMR implementation is backwards, and reflects the confusion that many in the industry have about who should be at the center of the industry.
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Technoclinics- Upcoming scenario in India

Technoclinics- Upcoming scenario in India | healthcare technology | Scoop.it

Medical industry in India is proud to have adopted the latest medical equipments in every specialization and has achieved tremendous results in terms of rapid and effective treatment. The benefits that the Indian IT sector has made in the global village the past 15 years, are now being extended to the Indian Healthcare industry too!

 

Taking advantage of these some clinics are transforming into “technoclinics” by smartly using technology and software in their practice.

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EHR + Geography = Population Health Management

EHR + Geography  = Population Health Management | healthcare technology | Scoop.it

Duke University Medicine is using geographical information to turn electronic health records (EHRs) into population health predictors. By integrating its EHR data with its geographic information system, Duke can enable clinicians to predict patients' diagnoses.


According to Health Data Management, Sohayla Pruitt was hired by Duke to run this project; “I thought, wow, if we could automate some of this, pre select some of the data, preprocess a lot and then sort of wait for an event to happen, we could pass it through our models, let them plow through thousands of geospatial variables and [let the system] tell us the actual statistical significance,” Pruitt says. “Then, once you know how geography is influencing events and what they have in common, you can project that to other places where you should be paying attention because they have similar probability.”


iHealth Beat explains that the system works by using an automated geocoding system to verify addresses with a U.S. Postal Service database. These addresses are then passed through a commercial mapping database to geocode them. Finally, the system imports all U.S. Census Bureau data with a block group ID. This results in an assessment of socioeconomic indicators for each group of patients.


“When we visually map a population and a health issue, we want to give an understanding about why something is happening in a neighborhood,” says Pruitt. “Are there certain socioeconomic factors that are contributing? Do they not have access to certain things? Do they have too much access to certain things like fast food restaurants?”


Duke is working to develop a proof of concept and algorithms that would map locations and patients. They are also working on a system to track food-borne illnesses.

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Electronic health records ripe for theft

Electronic health records ripe for theft | healthcare technology | Scoop.it

America’s medical records systems are flirting with disaster, say the experts who monitor crime in cyberspace. A hack that exposes the medical and financial records of hundreds of thousands of patients is coming, they say — it’s only a matter of when.


As health data become increasingly digital and the use of electronic health records booms, thieves see patient records in a vulnerable health care system as attractive bait, according to experts interviewed by POLITICO. On the black market, a full identity profile contained in a single record can bring as much as $500.


“What I think it’s going to lead to, if it hasn’t already, is an arms race between the criminal element and the people trying to protect health data,” said Robert Wah, president of the American Medical Association and chief medical officer at the health technology firm CSC. “I think the health data stewards are probably a little behind in the race. The criminal elements are incredibly sophisticated.”


The infamous Target breach occurred last year when hackers stole login information through the retailer’s heating and air system. Although experts aren’t sure what a major health care hack would look like, previous data breaches have resulted in identity and financial theft, and health care fraud.



Significant breaches are already occurring. Over the course of three days, hackers using a Chinese IP address infiltrated the St. Joseph Health System in Bryan, Texas, and exposed the information of 405,000 individuals, gaining names, address, Social Security numbers, dates of birth and other information.


It was the third-largest health data breach tracked by the federal government.


The L.A. Gay & Lesbian Center reported late last year that hackers attacked its computer systems over a course of two months trying to steal credit card, Social Security and other financial information. About 59,000 clients and former clients were left vulnerable.


While a stolen credit card or Social Security number fetches $1 or less on the black market, a person’s medical information can yield hundreds of times more, according to the World Privacy Forum. Thieves want to hack the data to gain access to health insurance, prescription drugs or just a person’s financial information


The Identify Theft Resource Center — which has identified 353 breaches in 2014 across industries it tracks, says almost half occurred in the health sector. Criminal attacks on health data have doubled since 2000, according to the Ponemon Institute, an industry leader in data security.


Health care is the industry sector least prepared for a cyberattack, according to security ratings firm BitSight Technologies. The industry had the highest volume of threats and the slowest response time, leading the FBI in April to issue a warning to health care providers.



Read more: http://www.politico.com/story/2014/07/electronic-health-records-theft-108856.html#ixzz37SDFnUKa

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Incorporate patient-generated health data into the EMR

Incorporate patient-generated health data into the EMR | healthcare technology | Scoop.it

Though the industry has made outstanding progress in adopting EMRs, the practice of data acquisition from patients remains cloudy.


A recommendation from the HITSC Meaningful Use Workgroup would require practices with electronic health records (EHRs) to allow 10 percent of patients to report PGHD electronically.


If approved in meaningful use stage 3, the final stage of HealthIT.gov’s EHR incentive program, it could push hospitals to incorporate patient-generated data.


This requirement may seem like a relatively simple intervention, but the ramifications are quite significant. If clinical decision-making is made on the basis of data supplied by patients and documented in the EMR, how can clinicians be sure that such data is complete, correct and valid? And will clinicians like me learn to rely on it, or will we disregard it due to concerns about its validity or barriers to integrating it into care flow?


Furthermore, if a patient is in control of her health data entry, who is ultimately responsible for its completeness and accuracy — the patient or the clinician?


Incorporating biometric data into the EMR, an exciting prospect, is even more complex. Though clinicians are quite familiar with data entry from FDA-approved medical devices such as blood glucose meters, pacemakers and pulmonary function units, data from a myriad of consumer-driven health devices (Fitbit and others) will soon seek to flex their way into EMRs.


Patients clearly value these data; a recent Pew Research report noted that 60 percent of adults claim to track their exercise routine, weight or diet, meaning providers have some catch-up to do in order to meet patients halfway. Some health systems, such as Partners HealthCare, have already been experimenting with the incorporation of PGHD from remote devices into the EMR, and other institutions should follow.


Consumer health data devices are moving ahead at a staggering pace, and while the health care system can’t quite keep up, strategic planning should be happening now.


Despite the challenges, incorporating PGHD is a necessary evolutionary step for health care. Intelligently designed, well-executed systems that fully incorporate and display PGHD in a meaningful way will improve shared decision-making and enable patients as active care partners. Keen clinicians and patients will stay closely tuned to the numerous transformations to come.

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Safety Assurance Factors for EHR Resilience (SAFER Guides)

Safety Assurance Factors for EHR Resilience (SAFER Guides) | healthcare technology | Scoop.it

The safety and safe use of electronic health records (EHRs) is a priority for healthcare organizations.


The SAFER guides consist of nine guides organized into three broad groups. These guides enable healthcare organizations to address EHR safety in a variety of areas. Most organizations will want to start with the Foundational Guides, and proceed from there to address their areas of greatest interest or concern.


The guides identify recommended practices to optimize the safety and safe use of EHRs. The content of the guides can be explored here, at the links below, or interactive PDF versions of the guides can be downloaded and completed locally for self-assessment of an organization’s degree of conformance to the Recommended Practices. The downloaded guides can be filled out, saved, and transmitted between team members.


To download the guides as well as to viewa  video explaining how to use the SAFER Guides visit: http://www.healthit.gov/policy-researchers-implementers/safer

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What’s missing from the electronic health record

What’s missing from the electronic health record | healthcare technology | Scoop.it

Patient adherence and the EHR


This clinical vignette reflects the reality that only one-quarter to one-third of patients follow up as directed after ED visits.1 Thus, dependence on patient adherence to care recommendations will continue to result in missed opportunities for both health maintenance and disease prevention. The EHR, which might have provided a safety net in this instance, failed to do so because an otherwise conscientious physician did not document a suspected diagnosis. In this case, the EHR’s utility was significantly limited by incomplete data entry.


How might the EHR have altered the course of events that led to the adverse reproductive outcome in this patient? Had the suspected diagnosis of diabetes been recorded, subsequent caregivers would have had the opportunity to see it in the problem list and to have acted upon it. Incomplete ED documentation effectively thwarted one of the putative “virtues” of this technology, namely, linkage of health information directly to the patient rather than to the provider of care.


Data not entered in the electronic chart or hidden from view are equivalent to a paper record locked in a medical office filing cabinet or a hospital’s health records department. In either circumstance, important patient information is unavailable precisely because it is sequestered by the care provider.


Disease prevention and the EHR


In response to anecdotal evidence as well as evidence supporting the effectiveness of prenatal health promotion,2,3 we evaluated our own EHR for its potential to help our patients avoid adverse outcomes.
Recognizing the frequency of unplanned pregnancy and the fact that 30% of women who conceive have modifiable risk factors that could be treated to improve pregnancy outcome,3 we created a case-finding algorithm to screen all outpatient encounters from our health system’s unified EHR (EPIC, Verona, WI).


Patient data are routinely transferred each evening into an enterprise-wide data warehouse (EPIC Clarity with Oracle and IBM COGNOS) allowing for subsequent data mining for quality improvement, care innovation and research.


We sought to identify reproductive-age women of child-bearing potential and use their data entries to identify risk factors for adverse maternal or fetal outcome. Child-bearing potential was defined as women of reproductive age lacking a history of either sterilization or hysterectomy, and without documented contraceptive use, while the preconception risk factors chosen included morbid obesity, hypertension, poorly controlled diabetes, anemia, renal insufficiency, teratogen exposure, and alcohol, tobacco and illicit drug use.
The algorithm was designed to mitigate incomplete charting by cross-referencing multiple electronic data fields (problem lists, medical and surgical histories, clinical diagnoses, laboratory results, medication orders, and ICD-9 codes), so that multiple dimensions of the record for each risk factor were queried.4


Where the EHR falls short


Although our case-finding strategy showed promise, accurate identification of women of child-bearing potential was problematic because up to 25% of patients were incorrectly classified due to incomplete electronic records.4 Poor data quality has been noted by others to confound the EHR5,6 and administrative databases from insurance claims and birth certificates are also notorious for missing information.7


In the domain of funded clinical research, a standard for precise data entry has existed for decades. Agencies including the National Institutes of Health place great emphasis on complete data capture and auditing, often insisting on robust data monitoring committees for just this purpose.


One needs only to reflect on the new norm of electronic banking to realize how important data precision is to our wealth, but, apparently, not yet to our health.


We believe it is time to insist that electronic medical records are assiduously created and carefully maintained so that they are more than just expensive versions of their paper ancestors. We suggest that caregivers need to conceptualize data entered on behalf of patients as of the highest value to their current and future health status, making accurate completion of the EHR an act of professionalism.


It is not a coincidence that Stage I meaningful use criteria include proper utilization of the problem list as an essential element in electronic recordkeeping.8 Accurate and comprehensive charting is no different than other measures designed to improve patient health and safety. While the activity may not feel particularly important on its face, our clinical vignette should leave no doubt as to the potential consequences of getting this wrong.



- See more at: http://contemporaryobgyn.modernmedicine.com/contemporary-obgyn/news/what-s-missing-electronic-health-record#sthash.3xGtRfc6.dpuf


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Lets Get Industrial Engineers to Design EHRs

Lets Get Industrial Engineers to Design EHRs | healthcare technology | Scoop.it

Many EMR designers are seduced by the idea that since users are already familiar with paper forms that the paper form metaphor is a good user interface. It is not.EMRs that try to mimic traditional paper medical records are not well designed for high-usability, high-productivity data and order entry.


An EMR designed and implemented using industrial engineering principles and techniques is a fundamentally different EMR that the traditional EMR. Instead of starting with a user interface that looks like a paper form, the user interface is essentially derived, using scientific and engineering principles, from the human body’s response to physical, physiological, and cognitive workload.


Perception, attention, cognition, motor control, memory storage and retrieval all interact with work environment and job demands to result in a body of knowledge about mental workload, vigilance, decision making, skilled performance, human error, human-computer interaction, and training. (This is not dissimilar to the way in which medical knowledge is derived using scientific methods from the structure and function of the human body.)

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EHR, clinical decision support help identify autism earlier

EHR, clinical decision support help identify autism earlier | healthcare technology | Scoop.it

Researchers from the Regenstrief Institute and Indiana University have demonstrated the potential of an automated system to help primary care physicians screen for autism spectrum disorders (ASDs) more effectively and efficiently, according to an article published in Infants & Young Children.


The work of the research team centered on the implementation of the Child Health Improvement through Computer Automation (CHICA) system, an open source tool that comprises an EHR and aclinical decision support system (CDSS) for pediatric preventive care anddisease management.


“Autism isn’t like strep throat where you can do a quick throat swab and then have a diagnosis,” lead author Nerissa Bauer, MD, of the Regenstrief Institute and Indiana University School of Medicine said last Friday.


“Autism is a behavioral diagnosis and can look very different depending on the child. Some behaviors are subtle, especially early on. CHICA prompts parents to think about whether they have concerns about certain health risks, such as autism, which makes it easier for the doctor to focus on key issues during a hectic visit.”


According to Bauer et al., the purpose of the tool is to address limitations commonly present in primary care practices when it comes to screening children for ASD. “Limited visit time, low reimbursement, logistics of the clinic workflow, and lack of appropriate staff to implement these tools continue to be major barriers to implementing clinical guidelines in primary care practice,” the authors write.


The CHICA system works by producing a personalized 20-question prescreening form in either English or Spanish for the patient linked to the patient’s EMR and completed by the patient’s parents in the waiting at each visit and scanned back into the system. Then at the 24-month visit system scores these results and alerts the physician to intervene if sufficient concerns are raised.
Prior to the implementation of the CHICA system, only eight out of 5,128 children had an ASA ICD-9 billing code assigned to them. During the two-year study (Nov. 15, 2010–July 25, 2012), a total of 857 were deemed eligible for screening with two-thirds (567) having the autism screening instrument, called the Modified Checklist for Autism in Toddlers (M-CHAT), completed.  Of these, CHICA identified 171 (30%) as having concerning results, which led to 73 (43%) of these patients having their physicians receive and respond to an alert, and leading to the following decisions:

• 50 (68%)children were considered not to have an ASD;
• 13 (18%) were referred for a more comprehensive workup;
• 8 (11%) children were suspected of having an ASD, but not referred; and
• 2 (3%) were referred for an audiology evaluation.
Bauer et al. are optimistic that similar approaches to screening for chronic diseases have the potential to improve detection and ensure that proper intervention occurs sooner rather than later.
While the results are encouraging, the willingness of physicians to take the necessary steps in adapting their clinical workflows still remains an obstacle that needs to be overcome.
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Mikaila Ludvik's curator insight, November 18, 2013 8:17 AM

Its interesting that studies are coming closer to finding a way to detect Austism earlier than we are able to currently.The sooner autism can be detected, then the sooner that child can get help, which is always a good thing. More research studies like this should be funded and should be happening.

Tech4MD's curator insight, December 27, 2013 11:39 AM

Yes, while the results are encouraging, the willingness of physicians to take the necessary steps in adapting their clinical workflows still remains an obstacle that needs to be overcome.

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What EMR & Medical Software Options are available for doctors who use an Apple Mac !

What EMR & Medical Software Options are available for doctors who use an Apple Mac ! | healthcare technology | Scoop.it

Very few vendors actually support the Mac. Many doctors over the years have wanted a Mac, but would’nt get one due to the lack of Medical Softwares for it. Though lately there has been a surge in the number of vendors promising native Mac versions in the future.

 

"Technology for Doctors is a blog on Healthcare IT by Plus91 Technologies Pvt Ltd."

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Improving Patient Care through EMRs

Improving Patient Care through EMRs | healthcare technology | Scoop.it

EMRs-Electronic Medical Records are a modern revolution in the field of healthcare improving the standards of quality in healthcare and raising it to a higher level. With all the numerous benefits of EMRs to doctors, it eventually signifies the benefits to patients and thereby improves patient care.


Using EMR in medical practice can improve patient care in the following ways:

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EMR'S: PROVIDING INDIAN DOCTORS WITH AN EDGE: VOL 1

EMR'S: PROVIDING INDIAN DOCTORS WITH AN EDGE: VOL 1 | healthcare technology | Scoop.it

Typically, a patient's record is just a folder with his details and probably a photograph on the front cover, coupled with sheets and sheets of data recording his previous visits. While some of this data, especially prescriptions may be recorded in a hospital, can you imagine the long hard search that one endures to locate them when required. Also, this search by no means guarantees a consolidated view of a patient's information which would equip the doctor with a complete overview of the patient's health history

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