Electronic Medical Records DA

Notes This is a DA that links to affs that increase privacy regulations of some sort. The evidence on government privacy regulations spilling over and hurting private companies’ abilities to collect data/operate efficiently is pretty good. A lot of the cards for uniqueness/internal link section of the Google DA apply here — I recommend using them for extensions in the block.

These cards are simply those cards but specific to electronic medical records. Also, probably some of the generic disease impact cards/big data solves health care cards may apply here as well.

Good luck! Let me know if I can update/cut/change anything ~Rishika

1NC Shell

1NC — Electronic Medical Records DAPrivacy regulations impose costs on hospitals that prevent them from adopting EMR systemsMiller and Tucker 9 — Amalia R. Miller, Associate Professor of Economics at the University of Virginia, holds a Ph.D. in Economics from Stanford University and an S.B. in Economics from Massachusetts Institute of Technology, and Catherine Tucker, Professor of Marketing at MIT Sloan, Chair of the MIT Sloan PhD Program, received an NSF CAREER Award for her work on digital privacy, the Erin Anderson Award for Emerging Marketing Scholar and Mentor, the Paul E. Green Award for contributions to the practice of Marketing Research and a Garfield Award for her work on electronic medical records, holds a PhD in economics from Stanford University, and a BA from the University of Oxford, 2009 (“Privacy Protection and Technology Diffusion: The Case of Electronic Medical Records,” Management Science, Vol. 55, No. 7, July, Available Online to Subscribing Institutions via JStor, Accessed 7/22/15)At the same time, privacy laws may impose additional network costs on hospitals who wish to transfer information electronically, for example, by demanding more of a paper trail, or by requiring more robust software. The design of networked EMR systems with strong security and confidentiality protections involves well-known challenges. Individual consent requirements that can be limited to particular types of information and provider destinations demand a flexibility that is costly to implement (Win and Fulcher 2007). It is more expensive to design a system that has the additional flexibility to limit the flow of information by the type of detail in a patient medical record and by the type of external destination, irrespective of how many patients refuse to have their records shared. Confidentiality protection that demands prior patient consent, which can be revoked at any time, also increases the costs of information exchange. McCarthy et al. (1999) give details of how privacy legislation that requires subjects to give their consent for each study used in research led to lower response rates. When individual consent was required by state law, it was granted by 19% of individuals, as opposed to 93% of patient records made available directly by providers in states without this privacy protection. Finally, in addition to the fixed costs that are added to the complexity of designing the EMR system, the laws require additional documentation, and that burden increases with the flow of information between providers. Theoretically, therefore, privacy regulation can affect the fixed or the variable costs of EMR adoption, and without detailed breakdowns of the costs involved, we cannot distinguish between the two.Privacy protection inhibits EMR diffusion not by creating a different legal requirement for different record types, but by raising compliance costs. Complying with privacy laws increases the costs of electronic record systems and , in particular, the costs of sharing information. This is particularly important if one of the key benefits of EMRs is the reduced costs of sharing information as compared with paper records. In this sense, the laws may pose an institutional barrier to information flow , which in turn reduces the potential benefits to hospitals from the adoption of EMRs, a technology that would otherwise reduce the physical barriers to information exchange. Although it would be desirable to estimate the effects of privacy regulation on network costs and benefits separately, we observe neither of these outcomes. Using data on adoption decisions, we can identify only the net effect of privacy law on network benefits.

Privately collected data is the backbone of effective health care systems — reduces costs and mortality ratesGoldfarb and Tucker 12 — Avi Goldfarb, Professor of Marketing in the Rotman School of Management at University of Toronto, has published over 50 articles in a variety of outlets in economics, marketing, statistics, computing, and law, holds a PhD from Northwestern, MA from Northwestern, and BAH from Queens University, with Catherine Tucker, Professor of Marketing at MIT Sloan, Chair of the MIT Sloan PhD Program, received an NSF CAREER Award for her work on digital privacy, the Erin Anderson Award for Emerging Marketing Scholar and Mentor, the Paul E. Green Award for contributions to the practice of Marketing Research and a Garfield Award for her work on electronic medical records, holds a PhD in economics from Stanford University, and a BA from the University of Oxford, 2012 (“Privacy and Innovation,” Innovation Policy and the Economy, Chicago Journals, The National Bureau of Economic Research, Vol. 12, No. 1, pp. 65-90, January, Available Online via Subscribing Institutions at JStor, Accessed 7/21/15)The 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act, part of the American Recovery and Reinvestment Act, devoted $19.2 billion to increase the use of electronic medical records (EMRs) by health care providers. Underlying this substantial public subsidy is a belief that creating an electronic rather than a paper interface between patient information and health care providers can improve health care quality, facilitate the adoption of new technologies, and also save money.EMRs are the backbone software system that allows health care providers to store and exchange patient health information electronically. As EMRs diffuse to more medical practices, they are expected to reduce medical costs and improve patient care. For example, they may reduce medical costs by reducing clerical duplication; however, there are no universally accepted estimates concerning how much money EMRs will save. Hillestad et al. (2005) suggest that EMRs could reduce America’s annual health care bill by $34 billion through higher efficiency and safety, assuming a 15-year period and 90% EMR adoption.In contrast, the clinical benefits from EMR systems have been demonstrated in recent empirical work (Miller and Tucker 2011a).1 This research examines effects of the digitization of health care on neonatal outcomes over a 12-year period. Neonatal outcome is a measure commonly used to assess the quality of a nation’s health care system and is important in its own right. As we discuss in depth later, Miller and Tucker (2011a) is also directly relevant to the current chapter, as it measures the relationships among health care outcomes, hospitals’ adoption of information technology, and state-level privacy regulation.Miller and Tucker (2011a) find that a 10% increase in basic EMR adoption would reduce neonatal mortality rates by 16 deaths per 100,000 live births, roughly 3% of the annual mean (521) across counties. Furthermore, they find that a 10% increase in hospitals that adopt both EMRs and obstetric-specific computing technology reduces neonatal mortality by 40 deaths per 100,000 live births. This finding suggests there are increasing gains from the digitization of health care. The paper shows that the reduction in deaths is driven by a decrease in deaths from conditions that can be treated with careful monitoring and data about patient histories . There is no such decrease for conditions where prior patient data are not helpful from a diagnostic standpoint.Overall, Miller and Tucker (2011a) document that the use of patient data by hospitals helps to improve monitoring and the accuracy of patient medical histories. More broadly, even basic EMR systems can

improve the quality of data repositories and ease access to relevant patient information. Adoption of technologies that facilitate data collection and analysis can help hospitals to improve outcomes and perhaps to reduce costs.

Diseases coming now and risk extinction – effective healthcare is key to checkNaish 12 (Reporter for Daily Mail, “The Armageddon virus: Why experts fear a disease that leaps from animals to humans could devastate mankind in the next five years Warning comes after man died from a Sars-like virus that had previously only been seen in bats Earlier this month a man from Glasgow died from a tick-borne disease that is widespread in domestic and wild animals in Africa and Asia” http://www.dailymail.co.uk/sciencetech/article-2217774/The-Armageddon-virus-Why-experts-fear-disease-leaps-animals-humans-devastate-mankind-years.html#ixzz3E5kqxjQI)The symptoms appear suddenly with a headache, high fever, joint pain, stomach pain and vomiting. As the illness progresses, patients can develop large areas of bruising and uncontrolled bleeding. In at least 30   per cent of cases, Crimean-Congo Viral Hemorrhagic Fever is fatal. And so it proved this month when a 38-year-old garage owner from Glasgow, who had been to his brother’s wedding in Afghanistan, became the UK’s first confirmed victim of the tick-borne viral illness when he died at the high-security infectious disease unit at London’s Royal Free Hospital. It is a disease widespread in domestic and wild animals in Africa and Asia — and one that has jumped the species barrier to infect humans with deadly effect. But the unnamed man’s death was not the only time recently a foreign virus had struck in this country for the first time. Last month, a 49-year-old man entered London’s St Thomas’ hospital with a raging fever, severe cough and desperate difficulty in breathing. He bore all the hallmarks of the deadly Sars virus that killed nearly 1,000 people in 2003 — but blood tests quickly showed that this terrifyingly

virulent infection was not Sars . Nor was it any other virus yet known to medical science . Worse still, the gasping, sweating patient was rapidly succumbing to kidney failure, a potentially lethal complication that had never before been seen in such a case. As medical staff quarantined their critically-ill patient, fearful questions began to mount. The stricken man had recently come from Qatar in the

Middle East. What on earth had he picked up there? Had he already infected others with it? Using the latest high-tech gene-scanning technique, scientists at the Health Protection Agency started to piece together clues from tissue

samples taken from the Qatari patient, who was now hooked up to a life-support machine. The results were extraordinary. Yes, the virus is from the same family as Sars. But its make-up is completely new . It has come not from humans, but from animals. Its closest known relatives have been found in Asiatic bats. The investigators also discovered that the virus has already killed someone. Searches of global medical databases revealed the same mysterious virus lurking in samples taken from a 60-year-old man who had died in Saudi Arabia in July. Scroll down for video Potentially deadly: The man suffered from CCHF, a disease transmitted by ticks (pictured) which is especially common in East and West

Africa Potentially deadly: The man suffered from CCHF, a disease transmitted by ticks (pictured) which is especially common in East and West Africa When the Health Protection Agency warned the world of this newly- emerging virus last month, it ignited a stark fear among medical experts. Could this be the next bird flu, or even the next ‘Spanish flu’ — the world’s biggest pandemic, which claimed between 50  million and 100 million lives across the globe

from 1918 to 1919? In all these outbreaks, the virus responsible came from an animal . Analysts now believe that the Spanish flu pandemic

originated from a wild aquatic bird. The terrifying fact is that viruses that manage to jump to us from animals — called zoonoses — can wreak havoc because of their astonishing ability to catch us on the hop and spread rapidly through the population when we least expect it. The virus's power and fatality rates are terrifying One leading British virologist, Professor John Oxford at Queen Mary Hospital, University of London, and a world authority on epidemics, warns that we must expect an animal-originated pandemic to hit the world within the next five years ,

with potentially cataclysmic effects on the human race . Such a contagion, he believes, will be a new strain of super-flu , a highly infectious virus that may originate in some far-flung backwater of Asia or Africa, and be contracted by one person from a wild animal or domestic beast, such as a chicken or pig. By the time the first victim has

succumbed to this unknown, unsuspected new illness, they will have spread it by coughs and sneezes to family, friends, and all those gathered anxiously around them. Thanks to our crowded, hyper-connected world, this doomsday virus will already have begun crossing the globe by air, rail, road and sea before even the best brains in medicine have begun to chisel at its genetic secrets. Before it even

has a name, it will have started to cut its lethal swathe through the world’s population. The high security unit High security: The high security unit where the man was treated for the potentially fatal disease but later died If this new

virus follows the pattern of the pandemic of 1918-1919, it will cruelly reap mass harvests of young and fit people. They die because of something called a ‘cytokine storm ’ — a vast overreaction of their strong and efficient immune systems that is prompted by the virus. This uncontrolled response burns them with a fever and wracks their bodies with nausea and massive fatigue. The hyper-activated immune system actually kills the person, rather than killing the super-virus. Professor Oxford bases his prediction on historical pattern s . The past century has certainly provided us with many disturbing precedents. For example, the 2003 global outbreak of Sars, the severe acute respiratory syndrome that killed nearly 1,000 people, was transmitted to humans from Asian civet cats in China. More... Man, 38, dies from deadly tropical disease after returning to the UK from Afghanistan Nine-year-old who turns YELLOW with anger: Brianna must spend 12 hours a day under UV lights

because of rare condition In November 2002, it first spread among people working at a live animal market in the southern Guangdong province, where civets were being sold. Nowadays, the threat from such zoonoses is far greater than ever, thanks to modern technology and human population growt h. Mass transport such as airliners can quickly fan outbreaks of newly- emerging zoonoses into deadly global wildfires. The Sars virus was spread when a Chinese professor of respiratory medicine treating people with

the syndrome fell ill when he travelled to Hong Kong, carrying the virus with him. By February 2003, it had covered the world by hitching easy lifts with airline passengers. Between March and July 2003, some 8,400 probable cases of Sars had been reported in 32 countries. It is a similar story with H1N1 swine flu, the 2009 influenza pandemic that infected hundreds of millions throughout the world. It is now believed to have originated in herds of pigs in

Mexico before infecting humans who boarded flights to myriad destinations. Once these stowaway viruses get off the plane, they don’t have to learn a new language or new local customs. Genetically, we humans are not very diverse ; an epidemic that can kill people in one part of the world can kill them in any other just as easily . On top of this, our risk of catching such deadly contagions from wild animals is growing massively, thanks to humankind’s relentless encroachment into the world’s jungles and rainforests , where we increasingly come into contact for the first time with unknown viral killers that have been evolving and incubating in wild creatures for millennia. This month, an international research team announced it had identified an entirely new African virus that killed two teenagers in the Democratic Republic of the

Congo in 2009. The virus induced acute hemorrhagic fever, which causes catastrophic widespread bleeding from the eyes, ears, nose and mouth, and can kill in days. A 15-year-old boy and a 13-year-old girl who attended the same school both fell ill suddenly and succumbed rapidly. A week after the girl’s death, a nurse who cared for her developed similar symptoms. He only narrowly survived. The new microbe is named Bas-Congo virus (BASV), after the

province where its three victims lived. It belongs to a family of viruses known as rhabdoviruses, which includes rabies. A report in the journal PLoS Pathogens says the virus probably originated in local wildlife and was passed to humans through insect bites or some other as-yet unidentified means. There are plenty of other new viral candidates waiting in the wings, guts, breath and blood of animals around us . You can, for example, catch leprosy from armadillos, which carry the virus in their shells and are responsible for a third of

leprosy cases in the U.S. Horses can transmit the Hendra virus, which can cause lethal respiratory and neurological disease in people. In a new book that should give us all pause for thought, award-winning U.S. natural history writer David Quammen points to a host of animal-derived infections that now claim lives with unprecedented regularity. The trend can only get worse , he warns. Quammen highlights the Ebola fever virus, which first

struck in Zaire in 1976. The virus’s power is terrifying, with fatality rates as high as 90 per cent. The latest mass outbreak of the virus, in the Congo last month, is reported to have killed 36 people out of 81 suspected cases. According to Quammen, Ebola probably originated in bats. The bats then infected African apes, quite probably through the apes coming into contact with bat droppings. The virus then infected local hunters who had eaten the apes

as bushmeat. Quammen believes a similar pattern occurred with the HIV virus, which probably originated in a single chimpanzee in Cameroon. 'It is inevitable we will have a global outbreak ' Studies of the virus’s genes suggest it may have first evolved as early as 1908. It was not until the Sixties that it appeared in humans, in big African cities. By the Eighties, it was spreading by airlines to America.

Since then, Aids has killed around 30 million people and infected another 33 million. There is one mercy with Ebola and HIV. They cannot be transmitted by coughs and sneezes. ‘Ebola is transmissible from human to human through

direct contact with bodily fluids. It can be stopped by preventing such contact,’ Quammen explains. ‘If HIV could be transmitted by air, you and I might already be dead. If the rabies virus — another zoonosis — could be transmitted by air, it would be the most horrific pathogen on the plane t .’ Viruses such as Ebola have another limitation, on top of their method of transmission. They kill and incapacitate people too quickly. In order to

spread into pandemics, zoonoses need their human hosts to be both infectious and alive for as long as possible, so that the virus can keep casting its deadly tentacles across the world’s population. But there is one zoonosis that can do all the right (or wrong) things. It is our old adversary, flu. It is easily transmitted through the air, via

sneezes and coughs. Sars can do this, too. But flu has a further advantage. As Quammen points out: ‘With Sars, symptoms tend to appear in a person before, rather than after, that person becomes highly

infectious. Isolation: Unlike Sars the symptoms of this new disease may not be apparent before the spread of infection Isolation : Unlike Sars the symptoms of this new disease may not be apparent before the spread of infection ‘That allowed many Sars cases to be recognised, hospitalised and placed in isolation

before they hit their peak of infectivity. But with influenza and many other diseases, the order is reversed.’ Someone who has an infectious case of a new and potentially l ethal strain of flu can be walking about innocently spluttering it over everyone around them for days before they become incapacitated . Such reasons lead Professor

Oxford, a world authority on epidemics, to warn that a new global pandemic of animal-derived flu is inevitable. And, he says, the clock is ticking fast. Professor Oxford’s warning is as stark as it is certain: ‘I think it is inevitable that we will have another big global outbreak of flu ,’ he says. ‘We should plan for one emerging in 2017-2018 .’ But are we adequately prepared to cope? Professor Oxford

warns that vigilant surveillance is the only real answer that we have. ‘ New flu strains are a day-to-day problem and we have to be very careful to keep on top of them,’ he says. ‘We now have scientific processes enabling us to quickly identify the genome of the virus behind a new illness, so that we know what we are dealing

with. The best we can do after that is to develop and stockpile vaccines and antiviral drugs that can fight new strains that we see emerging.’ But the Professor is worried our politicians are not taking this certainty of mass death seriously enough. Such laxity could come at a human cost so

unprecedentedly high that it would amount to criminal negligence. The race against newly-emerging animal-derived diseases is one that we have to win every time. A pandemic virus needs to win only once and it could be the end of humankind.

2NC/1NR Uniqueness

2NC/1NR — UniquenessEMR adoption high in the status quoHealth and Human Services 14 — U.S. Department of Health & Human Services, HHS Press Office, 2014 (“More physicians and hospitals are using EHRs than before: CDC data provides baseline for EHR adoption among health care providers,” Health and Human Services, August 7, Available Online at http://www.hhs.gov/news/press/2014pres/08/20140807a.html, Accessed 7/26/15)Significant increases in the use of electronic health records (EHRs) among the nation’s physicians and hospitals are detailed in two new studies published today by the HHS Office of the National Coordinator for Health Information Technology (ONC).The studies, published in the journal Health Affairs, found that in 2013, almost eight in ten (78 percent) office-based physicians reported they adopted some type of EHR system . About half of all physicians (48 percent) had an EHR system with advanced functionalities in 2013, a doubling of the adoption rate in 2009.About 6 in 10 (59 percent) hospitals had adopted an EHR system with certain advanced functionalities in 2013, quadruple the percentage for 2010 . Unlike the physician study, the hospital study does not have an equivalent, established measure of adoption of some type of EHR system; it only reports on adoption of EHRs with advanced functionalities.“Patients are seeing the benefits of health IT as a result of the significant strides that have been made in the adoption and meaningful use of electronic health records,” said Karen DeSalvo, M.D., M.P.H., national coordinator for health information technology. “We look forward to working with our partners to ensure that people’s digital health information follows them across the care continuum so it will be there when it matters most.”The information in the studies was collected by the Centers for Disease Control and Prevention’s National Center for Health Statistics and the American Hospital Association in 2013.These data provide an early baseline understanding of provider readiness to achieve Stage 2 Meaningful Use of the Medicare and Medicaid EHR Incentive programs. Stage 2 will begin later this year for providers who first attested to Stage 1 Meaningful Use in 2011 or 2012. About 75 percent of eligible professionals and more than 91 percent of hospitals have adopted or demonstrated Stage 1 Meaningful Use of certified EHRs.

2NC/1NR Links/ILs

2NC/1NR — Links/Internal LinksPrivacy restrictions on privately collected data hurt health care effectivenessGoldfarb and Tucker 12 — Avi Goldfarb, Professor of Marketing in the Rotman School of Management at University of Toronto, has published over 50 articles in a variety of outlets in economics, marketing, statistics, computing, and law, holds a PhD from Northwestern, MA from Northwestern, and BAH from Queens University, with Catherine Tucker, Professor of Marketing at MIT Sloan, Chair of the MIT Sloan PhD Program, received an NSF CAREER Award for her work on digital privacy, the Erin Anderson Award for Emerging Marketing Scholar and Mentor, the Paul E. Green Award for contributions to the practice of Marketing Research and a Garfield Award for her work on electronic medical records, holds a PhD in economics from Stanford University, and a BA from the University of Oxford, 2012 (“Privacy and Innovation,” Innovation Policy and the Economy, Chicago Journals, The National Bureau of Economic Research, Vol. 12, No. 1, pp. 65-90, January, Available Online via Subscribing Institutions at JStor, Accessed 7/21/15)Consequences.—Although EMRs were invented in the 1970s, by 2005 only 41% of U.S. hospitals had adopted a basic EMR system. Anecdotal evidence suggests that privacy protection may partially explain this slow pace of diffusion. Expensive state-mandated privacy filters may, for example, have played a role in the collapse of the Santa Barbara County Care Data Exchange in 2007.Miller and Tucker (2009) examine the empirical consequences of privacy regulation and, in particular, how it suppresses network effects in adoption of medical information technology . Network effects may shape the adoption of EMRs because hospitals derive network benefits from EMRs when they can electronically exchange information about patient histories with other providers such as general practitioners. Exchanging EMRs is quicker and more reliable than exchanging paper records by fax, mail, or patient delivery. It is especially useful for patients with chronic conditions when a new specialist requires access to previous tests. Emergency room patients whose records (containing information about previous conditions and allergies) are stored elsewhere also benefit.

Privacy regulations directly inhibit private sector data collection and innovationGoldfarb and Tucker 12 — Avi Goldfarb, Professor of Marketing in the Rotman School of Management at University of Toronto, has published over 50 articles in a variety of outlets in economics, marketing, statistics, computing, and law, holds a PhD from Northwestern, MA from Northwestern, and BAH from Queens University, with Catherine Tucker, Professor of Marketing at MIT Sloan, Chair of the MIT Sloan PhD Program, received an NSF CAREER Award for her work on digital privacy, the Erin Anderson Award for Emerging Marketing Scholar and Mentor, the Paul E. Green Award for contributions to the practice of Marketing Research and a Garfield Award for her work on electronic medical records, holds a PhD in economics from Stanford University, and a BA from the University of Oxford, 2012 (“Privacy and Innovation,” Innovation Policy and the Economy, Chicago Journals, The National Bureau of Economic Research, Vol. 12, No. 1, pp. 65-90, January, Available Online via Subscribing Institutions at JStor, Accessed 7/21/15)The relationship between innovation and privacy policy runs deeper than this superficial similarity suggests. This paper argues that ultimately privacy policy is interlinked with innovation policy and consequently has potential consequences for innovation and economic growth . Drawing on empirical analysis of privacy regulations in online advertising and health care, we summarize evidence that

privacy regulations directly affect the usage and efficacy of emerging technologies in these sectors. Furthermore, because these impacts are heterogeneous across firms and products, regulations affect the direction of innovation.This linkage sets up a tension between the economic value created by the use of personal data and the need to safeguard consumers’ privacy in the face of the use of such data. As discussed by Hui and Png (2006), it is not straightforward to incorporate notions of privacy into economic models, because such notions are often based on consumer emotions as well as on strict economic concerns. As such, it is important for regulators to balance consumer uneasiness with (or repugnance toward) data collection and usage with the consequences such regulations may have on certain types of innovation.More broadly, the extent of privacy regulation should represent a trade-off between the benefits of data-based innovation and the harms caused by violations of consumer privacy. Much of the policy discussion appears to assume substantial harms, perhaps citing survey evidence that people do not like to be tracked (FTC 2010). It is important to measure the size of these harms carefully, ideally in a real-world revealed-preference setting where the costs and benefits can be explicitly traded off. These studies should be conducted across many industries and settings, because such harms likely affect different sectors in different ways. The fact that there may be differential effects in terms of both harm and incentives to innovate across different sectors means that there may be potential adverse consequences of using a single policy tool to regulate all sectors. These adverse consequences should be set against the benefits of simplicity and uniformity of comprehensive cross-sector privacy regulation.

Data driven healthcare is the critical factor in disease prevention – revolutionizes planning and treatmentMarr 15 — Bernard Marr, contributor to Forbes, he also basically wrote the book on internet data – called Big Data – and is a keynote speaker and consultant in strategic performance, analytics, KPIs and big data, 2015 (“How Big Data Is Changing Healthcare”, Forbes, April 21, Available Online at http://www.forbes.com/sites/bernardmarr/2015/04/21/how-big-data-is-changing-healthcare/)If you want to find out how Big Data is helping to make the world a better place, there’s no better example than the uses being found for it in healthcare . The last decade has seen huge advances in the amount of data we routinely generate and collect in pretty much everything we do, as well as our ability to use technology to analyze and understand it. The intersection of these trends is what we call “Big Data” and it is helping businesses in every industry to become more efficient and productive. Healthcare is no different.

Beyond improving profits and cutting down on wasted overhead, Big Data in healthcare is being used to predict epidemics , cure disease , improve quality of life and avoid preventable deaths . With the world’s population

increasing and everyone living longer, models of treatment delivery are rapidly changing , and many of the decisions behind those changes are being driven by data . The drive now is to understand as much about a patient as possible , as early in their life as possible – hopefully picking up warning signs of serious illness at an early enough stage that treatment is far more simple (and less expensive) than if it had not been spotted until later. So to take a journey through Big Data in healthcare, let’s start at the beginning – before we even get ill. Wearable blood pressure monitors send data to a smartphone app, then off to the doctor. (Photo by John Tlumacki/The Boston Globe via Getty Images) Prevention is better than cure Smart phones were just the start. With apps enabling them to be used as everything from pedometers to measure how far you walk in a day, to calorie counters to help you plan your diet, millions of us are now using mobile technology to help us try and live healthier lifestyles. More recently, a steady stream of dedicated wearable devices have emerged such as Fitbit, Jawbone and Samsung Gear Fit that allow you to track your progress and upload your data to be compiled alongside everyone else’s. In the very near future, you could also be sharing this data with

your doctor who will use it as part of his or her diagnostic toolbox when you visit them with an ailment. Even if there’s nothing wrong with you, access to huge, ever growing databases of information about the state of the health of the general public will allow problems to be spotted before they occur , and remedies – either medicinal

or educational – to be prepared in advance This is leading to ground breaking work , often by partnerships between medical and data professionals, with the potential to peer into the future and identify problems before they happen . One recently formed example of such a partnership is the Pittsburgh Health Data Alliance – which aims to take data from various sources (such as medical and insurance records, wearable sensors, genetic data and even social media use) to draw a comprehensive picture of the patient as an individual, in order to offer a tailored healthcare package. That person’s data won’t be treated in isolation. It will be compared and analyzed alongside thousands of others, highlighting specific threats and issues through patterns that emerge during the comparison. This enables sophisticated predictive modelling to take place – a doctor will be able to assess the likely result of whichever treatment he or she is considering prescribing, backed up by the data from other patients with the same condition, genetic factors and lifestyle. Programs such as this are the industry’s attempt to tackle one of the biggest hurdles in the quest for data-driven healthcare: The medical industry collects a huge amount of data but often it is siloed in archives controlled by different doctors’ surgeries, hospitals, clinics and administrative departments. Another partnership that has just been announced is between Apple and IBM. The two companies are collaborating on a big data health platform that will allow iPhone and Apple Watch users to share data to IBM’s Watson Health cloud healthcare analytics service. The aim is to discover new medical insights from crunching real-time activity and biometric data from millions of potential users.

EMRs provide faster and more complete patient data analysis and diagnosisWilson and Bock 12 — John Wilson, MD, Vice President of Clinical Analytics, OptumInsight, and Adam Bock, MD, Chief Medical Information Officer at Minneapolis Veterans Hospital, 2012 (“The benefit of using both claims data and electronic medical record data in health care analysis,” Optum, February, Available Online at https://www.optum.com/content/dam/optum/resources/whitePapers/Benefits-of-using-both-claims-and-EMR-data-in-HC-analysis-WhitePaper-ACS.pdf, Accessed 7/26/15)More complete condition identificationThere are a variety of reasons that physicians may fail to completely record on a claim all the diagnoses from a visit. For one thing, physicians are constantly pressed for time, and every second spent recording billing codes is a second that takes them away from direct patient care. Additionally, in a fee-for-service setting, the payment that a physician receives for an office visit is not directly related to the number or type of conditions for which the physician codes (see Appendix A for more detail). Hence, in many cases, the EMR will have a more complete set of diagnoses for a given patient than claims data.Because of this, claims data is often an imperfect reflection of the actual status of a patient. Several studies support this. One study examined how often people with the condition of chronic kidney disease (CKD) had a claims-based diagnosis code for this condition over a one-year period. In this study,3 results of a blood test (the estimated glomerular filtration rate or eGFR) were used to determine whether or not kidney disease existed. If this test was abnormal on at least two separate occasions over a year, the patients met the definition CKD. The authors then examined all claims data for the patients who had CKD diagnosed by virtue of lab testing. They found that only 20–42 percent of these patients had a diagnosis code for CKD on a claim over the one-year period. Put another way, if one year of claims data was all that had been present, 58–80 percent of people with CKD would not have been identified.Another study published in the Journal of the American Medical Association (JAMA)4 showed that of children with EMR blood pressure values that were high on at least three separate doctor visits, only 26 percent of them had a claim with a diagnosis of hypertension on it.

In addition to showing the shortcomings of claims data in identifying conditions, these data suggest another powerful conclusion: Use of clinical data from the EMR can significantly improve condition identification. The use of lab result data elements can support identification of people with CKD even without a coded diagnosis. In addition, the use of vital sign data can allow identification of people with hypertension despite the lack of a claim-based diagnosis of this condition.In fact, there are a variety of data elements that might be available in the EMR which, when analyzed, can allow the identification of a condition that was either not recognized or not coded for by the physician. So, one way in which EMR data enables better condition identification is by providing access to data elements (e.g., lab results and vital signs) that allow one to impute a diagnosis—even if that diagnosis was never made.Allowing for imputed diagnosis is just one way in which EMR data improves condition identification over and above the use of claims data. The EMR also has something which claims data do not: the concept of a ‘problem list’.Claims data is, by its nature, temporally limited. Meaning the claim reflects only the diagnoses and services that occurred on the date when the claim was submitted. It is not designed to convey information about what happened in the past. So for a patient who had heart surgery or an appendectomy two years ago, there is no reason that those items will appear on a claim today. Similarly, if a patient had a diagnosis of heart failure two years ago, that diagnosis may not appear on a claim during a subsequent time period, even if the condition persists. The EMR, however, has a way to transcend the concept of time by which claims data are constrained: the problem list.The problem list is an area in the electronic record where providers can keep track of the list of medical problems affecting a patient. The EMR maintains this list independently from any particular medical visit/encounter. Hence, use of the EMR problem list allows identification of conditions which may not be identified via claims data.More timelyIn addition to the ability of EMR data to enhance condition identification as discussed above, EMR data has another advantage: timeliness . Sometimes we would like to understand that a patient has experienced a certain event as soon as that event has occurred. For example, we might like a nurse to provide a follow-up call to a patient the day after an emergency room visit. If we are dependent on claims data alone to identify the emergency room visit, there may be a delay (sometimes of months) until a claim for this visit is received and processed. However, providers interact with the EMR during (or soon after) the patient encounter. Hence, EMR data is generated in real time , and a system which evaluates data from the EMR can allow a much more rapid response.

EMRs are based in ObamacareHughes 15 — Jane Lindell Hughes, M.D., F.A.C.S., Clinical Professor in the Department of Ophthalmology at the University of Texas Health Science Center, 2015 (“Obamacare: Why Washington wants your medical file,” Washington Times, February 11, Available Online at http://www.washingtontimes.com/news/2015/feb/11/electronic-medical-records-government-medicine-101/, Accessed 7/26/15)Medicare and Medicaid have served as the template for Obamacare and government-controlled medicine. This began with price controls on doctors and hospitals resulting in cost-shifting to the private sector and spiraling health care costs. Politicians used this predictable outcome to clamor for healthcare

overhaul. The crucial cost-control piece in the final implementation of Obamacare is the centrally connected EMR database . It is to be the vehicle by which the patients’ conditions are monitored and their treatment options elucidated based on centrally determined “best practices” and factors such as age and pre-existing pathology.Physician compliance with recommended treatments will be monitored and corrected when necessary. People the likes of Jonathan Gruber and Ezekiel Emmanuel will be deciding these parameters as appointees to the Council for Comparative Effectiveness Research and the Independent Payment Advisory Board (IPAB).

2NC/1NR Impact

2NC/1NR — ImpactsEMRs key to preventing short term and chronic disease and saves over $10BHillestad et. al. 15 — Richard Hillestad, policy expert RAND Corporation, holds a Ph.D. in engineering and applied science and an M.S. and B.S. in electrical engineering; James Bigelow, Associate Professor in the Department of Pharmaceutical Sciences, holds a B.S. degree in Microbiology and Ph.D. in Biochemistry; Anthony Bower, researcher at Synageva BioPharma with degrees in Business Economics and Microeconomics; Federico Girosi, Associate Professor in Population Health at the School of Medicine, holds a Ph.D. in Health Policy from Harvard and a Ph.D. in Physics; Robin Meili, senior management systems analyst and director of International Programs at the RAND Corporation, holds an M.B.A. from NYU; Richard Scoville, Adjunct Associate Professor at UNC, holds a BA, MA in Education, and a PhD in Psychology; Roger Taylor, holds a Bachelor of Science (BSc), Politics, Philosophy and Economics, 2015 (“Can Electronic Medical Record Systems Transform Health Care? Potential Health Benefits, Savings, And Costs,” Health Affairs, Available Online at http://content.healthaffairs.org/content/24/5/1103.full, Accessed 7/22/15)Using HIT for near-term chronic disease management.The U.S. burden of chronic disease is extremely high and growing. In one study, fifteen chronic conditions accounted for more than half of the growth in health care spending between 1987 and 2000, and just five diseases accounted for 31 percent of the increase.28 Disease management programs identify people with a potential or active chronic disease; target services to them based on their level of risk (sicker patients need more-tailored, more-intensive interventions, including case management); monitor their condition; attempt to modify their behavior; and adjust their therapy to prolong life, minimize complications, and reduce the need for costly acute care interventions.EMR systems can be instrumental throughout the disease management process. Predictive-modeling algorithms can identify patients in need of services. EMR systems can track the frequency of preventive services and remind physicians to offer needed tests during patients’ visits. Condition-specific encounter templates implemented in an EMR system can ensure consistent recording of disease-specific clinical results, leading to better clinical decisions and outcomes. Connection to national disease registries allows practices to compare their performance with that of others. Electronic messaging offers a low-cost, efficient means of distributing reminders to patients and responding to patients’ inquiries. Web-based patient education can increase the patient’s knowledge of a disease and compliance with protocols.For higher-risk patients, case management systems help coordinate workflows , including communication between multiple specialists and patients. In what may prove to be a transformative innovation, remote monitoring systems can transmit patients’ vital signs and other biodata directly from their homes to their providers, allowing nurse case managers to respond quickly to incipient problems. Health information exchange via RHINs or personal health records promises great benefits for patients with multiple chronic illnesses , who receive care from multiple providers in many settings.We examined disease management programs for four conditions: asthma, congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD), and diabetes (Exhibit 4⇓) and estimated the effects of 100 percent participation of people eligible for each program.29 By controlling acute care episodes, these programs greatly reduce hospital use at the cost of increased physician office visits and use of prescription drugs. As shown, the programs could generate potential annual savings of tens of billions of dollars. Keeping people out of the hospital is, of course, a health benefit, but we can also

expect important outcomes such as reductions in days lost from school and work and in days spent sick in bed.

AFF

EMRs are Inefficient/ExpensiveEMRs are inefficient and hurt health care systemsHensley 14 — Scott Hensley, Assistant Professor at the Wistar Institute, holds a PhD in biology from UPenn, 2014 (“Electronic Medical Records, Built For Efficiency, Often Backfire,” National Public Radio, November 7, Available Online at http://www.npr.org/sections/health-shots/2014/11/07/361148976/electronic-medical-records-built-for-efficiency-often-backfire, Accessed 7/26/15)Electronic medical records were supposed to usher in the future of medicine.Prescriptions would be beamed to the pharmacy. A doctor could call up patients' medical histories anywhere, anytime. Nurses and doctors could easily find patients' old lab results or last X-rays to see what how they're doing. The computer system could warn doctors about dangerous drug combinations before it was too late.Many of those things are an everyday reality in doctors' offices and hospitals across the country. But a survey of more than 400 internists with experience using electronic medical records, or EMRs, documents what doctors have complained about for years: computerized records chew up a lot of time.Writing up a patient's visit on the computer can take more time than you might expect. More than 60 percent of the doctors surveyed said that note writing took longer using computerized records than before they were implemented.One reason: There are all kinds of boxes to check that have more to do with the billing department than the patient.Overall, the survey found that attending physicians, the doctors in charge of care, lost an average of 48 minutes a day because of EMRs. Doctors in training lost 18 minutes a day.

EMR implementation is time consuming, ineffective, and wasteful spendingDenning 13 — Steve Denning, Program Director of Knowledge Management at the World Bank, studied law and psychology at Sydney University, worked as a lawyer in Sydney for several years, holds a postgraduate degree in law at Oxford, 2013 (“Why Is Your Doctor Typing? Electronic Medical Records Run Amok,” Forbes, April 25, Available Online at Why Is Your Doctor Typing? Electronic Medical Records Run Amok, Accessed 7/26/15)In the last year or two, there’s been a shift. Much of my time with doctors has been spent watching them type. In one case, the doctor tapped away on his laptop, occasionally looking up to ask questions before returning to the main focus of his attention: his computer. In another case, the doctor intermittently tapped on an iPad while we spoke. In a third instance, the doctor had a conversation with me and then apologized that he would be spending the next half of our session typing up the results of our conversation. All this typing was required, he said, if he was ever going to be reimbursed for his services. It was getting in the way of being a doctor.Surely, I said, computerized medical records generate benefits. They are easily retrievable. They can be transferred from one practice to another and accessible to the many different service providers—hospitals, laboratories, specialists, radiology and so on—that might be involved in any one patient.

“In theory, perhaps,” he replied. “But in practice, it’s a horrible and costly bureaucracy that is being imposed on doctors. I spend less time with patients, and more time filling out multiple boxes on forms that don’t fit the way I work. Often I am filling out the same information over and over again. A lot of it is checking boxes, rather than understanding what this patient really needs.”What about retrieving information? Isn’t that easier?“Again, in theory, retrieval should be easy and quick,” he said, “But you can’t flip through these records the way you do with a paper file and easily find what you want. The other day, for instance, I inherited a new patient along with her electronic records. Her previous care-givers had checked forty-five boxes of problems. There’s no way that I can deal with a patient with forty-five problems. She and I talked for some time and eventually we figured out that she had six real health problems: then we could begin to discuss what to do. And then I had to input that discussion into the computer. The electronic record didn’t save time. It made everything take longer.”But at least now you can get the records electronically?“Sometimes,” he said. “But each network has its own system and often the systems are incompatible. The systems don’t talk to each other. So transferring records from one system to another becomes another nightmare. ” But why do you type while the patient is there?“Filling out these forms and checking all the boxes takes me a lot of time,” he said, “If I don’t do it now, I will spend half the night trying to remember the discussion and typing up the results of the day’s visits. The outcome is that I have less time to spend with patients. Instead of making the system better, it’s making everything more costly.”What we are seeing here is the implementation of Obamacare —the Affordable Care Act—which has provided reimbursement incentives and an electronic medical records deadline for those who adopt electronic medical records (EMR). However, for those who don’t meet the electronic medical records deadline for implementation, the government has laid out a series of penalties. The message to doctors is clear: implement electronic records or pay a price.“The government already is wasting billions on the medical EMR,” my doctor told me. “They are committed to giving each health care system $17,000 per doctor who is successfully using electronic medical records to help them cover their software investment. This money goes to the health care system and not the docs. So it’s basically a very lucrative pass through to the software people for generating an inadequate and burdensome system.”Survey: most doctors lose money with electronic recordsMy doctor is not alone in seeing problems with the way that electronic medical records are being implemented.A recent survey published in Health Affairs by Julia Adler-Milstein, Carol Green and David W. Bates, estimates that doctors who install electronic medical records systems should expect an initial loss of around $44,000 on their investment. Almost two-thirds of the practices using electronic records would lose money even with government subsidies, the researchers said.Having electronic records is in principle a good idea, but only if one imagines implementation as quick and intuitive so that it’s easier for doctors to input and retrieve information rather than from scribbling notes on paper. Reformers imagine some kind of well-tuned iPhone or iPad with lots of cool gadgets and apps that make life easier.

But in practice, implementation of electronic health records today is anything but quick and intuitive or easy to use. It’s mostly like old-style form-filling software that is an aggravating pain to use. It takes forever, involves continuous repetition, is counter-intuitive to use and offers few benefits in return. Along with upfront costs, doctors said they have to work longer hours because of the software. Smaller offices, those with five doctors or fewer, struggled the most.The study shows that 27 percent of practices are projected to gain by seeing more patients or getting more claims approved by insurers, though there is no indication what happened to the quality of care in such accelerated throughput.

Implementing electronic records is expensive and difficult to useDenning 13 — Steve Denning, Program Director of Knowledge Management at the World Bank, studied law and psychology at Sydney University, worked as a lawyer in Sydney for several years, holds a postgraduate degree in law at Oxford, 2013 (“Why Is Your Doctor Typing? Electronic Medical Records Run Amok,” Forbes, April 25, Available Online at Why Is Your Doctor Typing? Electronic Medical Records Run Amok, Accessed 7/26/15)Despite the theoretical potential for quality improvement from computerized records, they found that few physician practices use electronic records. Miller and Sim argue that “the path to quality improvement and financial benefits lies in getting the greatest number of physicians to use the electronic medical records [EMR] (and not paper) for as many of their daily tasks as possible. The key obstacle in this path to quality is the extra time it takes physicians to learn to use the EMR effectively for their daily tasks.”Miller and Sim report:“Interviewees reported that most physicians using EMRs spent more time per patient for a period of months or even years after EMR implementation. The increased time costs resulted in longer workdays or fewer patients seen, or both, during that initial period… Even highly regarded, industry-leading EMRs to be challenging to use because of the multiplicity of screens, options, and navigational aids… Although vendors are slowly improving EMR usability, most vendor interviewees doubted that any “silver bullet” technology (for example, voice recognition, tablet computers, or mobile computing) will dramatically simplify EMR usage. Designing easy-to-use software for knowledge workers is a challenge that spans the software industry beyond health care.”Miller and Sim suggest policy interventions to overcome these barriers, including providing work/practice support systems, improving electronic clinical data exchange, and providing financial incentives for quality improvement.This thinking is fanciful. Paying people to work unintelligently doesn’t work and ultimately will be ineffective. What is needed are systems that actually help doctors do their work.The world didn’t need incentives or support systems to get people to adopt iPhones or iPads. We embraced the iPhones and iPads because they are easy to use and they made our lives better.When the software embedded in electronic records isn’t adapted to the doctor’s needs and the way they work, hopes of major productivity gains through policy fixes like incentives or training are doomed .

EMRs Don’t WorkEMRs don’t improve data sharingCreswell 14 — Julie Creswell, reporter at the New York Times, JD from University of Iowa, 2014 (“Doctors Find Barriers to Sharing Digital Medical Records,” New York Times, September 30, Available Online at http://www.nytimes.com/2014/10/01/business/digital-medical-records-become-common-but-sharing-remains-challenging.html?_r=0, Accessed 7/26/15)Regardless of who is at fault, doctors and hospital executives across the country say they are distressed that the expensive electronic health record systems they installed in the hopes of reducing costs and improving the coordination of patient care — a major goal of the Affordable Care Act — simply do not share information with competing systems .The issue is especially critical now as many hospitals and doctors scramble to install the latest versions of their digital record systems to demonstrate to regulators starting Wednesday that they can share some patient data. Those who cannot will face reductions in Medicare reimbursements down the road.On top of that, leading companies in the industry are preparing to bid on a Defense Department contract valued at an estimated $11 billion. A primary requirement is that the winning vendor must be able to share information, allowing the department to digitally track the medical care of 9.6 million beneficiaries around the globe.The contract is the latest boon to an industry that taxpayers have heavily subsidized in recent years with over $24 billion in incentive payments to help install electronic health records in hospitals and physicians’ offices.While most providers have installed some kind of electronic record system, two recent studies have found that fewer than half of the nation’s hospitals can transmit a patient care document, while only 14 percent of physicians can exchange patient data with outside hospitals or other providers.“We’ve spent half a million dollars on an electronic health record system about three years ago, and I’m faxing all day long. I can’t send anything electronically over it,” said Dr. William L. Rich III, a member of a nine-person ophthalmology practice in Northern Virginia and medical director of health policy for the American Academy of Ophthalmology.

Alt CauseAlt cause to healthcare industry — bureaucratization and bad managementDenning 13 — Steve Denning, Program Director of Knowledge Management at the World Bank, studied law and psychology at Sydney University, worked as a lawyer in Sydney for several years, holds a postgraduate degree in law at Oxford, 2013 (“Why Is Your Doctor Typing? Electronic Medical Records Run Amok,” Forbes, April 25, Available Online at Why Is Your Doctor Typing? Electronic Medical Records Run Amok, Accessed 7/26/15)As Brown points out, the biggest challenge in enterprise software delivery lies not in these software practices themselves, but rather in the overall management culture. If the organization remains in a vertical, hierarchical mode, with an approach of “here’s the system—implement it”, none of the advantages of computerization will accrue. In fact, costs will increase.The problem is that hierarchical bureaucracy is still pervasive in the health sector. Producing easy-to-use software or the agility to make continuous adjustments from experience lies beyond the performance envelope of this type of management.A radically different kind of management is needed. It needs to begin, not with a goal of “introducing electronic medical records”, but rather with the goal of “improving the working lives of doctors through better technology”.Instead of producing outputs in the form of electronic records, the goal needs to be generating positive outcomes for doctors. Once outcomes for doctors are positive, the need for incentives vanishes: doctors will want to improve their working lives. There will be stampede to use the new technology.But this entails a revolution in management thinking. Instead of seeing electronic records as merely a shift in technology from paper to IT, it involves a transformation in the way the health sector thinks about and manages work. It means new goals, new roles for managers, new ways of coordinating work, new values and new ways of communicating.Fortunately, there is a vast experience in thousands of organizations around the world for over a decade to show the way. It’s still the best kept secret in the management world.We need to stop torturing doctors with systems that make work more difficult and generate systems that are better—better for doctors, better for patients and better for the health system overall. And for that to happen, we need a different kind of management.