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Supplemental Material for HIT

Mark has gone to great lengths to fill the instructor's notes on many of the videos with supplemental material. Please pay close attention to those. Some general resources can be found below.

Lesson 0

Video Transcript

Welcome. This course is about health informatics — the applications of information technology to healthcare delivery. This is distinct from bioinformatics, a related field with which it is often confused, that is about building computational models and using other approaches to analyze and understand the complex intracellular biochemical mechanisms within most of our cells. The term biomedical informatics is often used to denote the merger of these two fields into one training and/or research program. As you’ll learn, even though healthcare delivery is a very data dependent activity, here in the US it has long resisted adopting the information technologies that are in common use in other industries. Partially as a result, the US has many problems delivering efficient, high quality care. Many feel that the solutions, at least in part, are through the widespread adoption and proper use of the information technologies we’ll discuss.

There are 10 lessons in the course and they correspond with the 10 chapters in the text.  We’ve split lesson 5 into two sections because of its length.  While the material is not technically difficult there is quite a lot of it.  More, in fact, than can be covered in the lectures so reading the text and other suggested materials is key to success.  Lessons 1-2 provide background on US health care delivery and the role the federal government is playing to foster adoption of information technology. Lessons 3-5 cover the core technologies that all contemporary health informatics systems and tools rely on. Lessons 6-8 show how health informatics is being used in real world applications from electronic records for providers and patients to managing the health of large populations of patients over an entire region or state to understanding and improving public health. Lessons 9-10 show how data can be aggregated from these systems and analyzed to gain new knowledge and even improve the health delivery system that generated the data. During this course we’ll hear from experts in various segments of the field who should help you see how the knowledge and concepts you’re learning about are actually being applied. Along the way you’ll be able to test your knowledge with frequent quizzing, so I want you to get used to the interaction formats. Try out an easy question to start with, QUESTION: Which of these fields involves the use of computing: a) Health Informatics b) Bioinformatics c) Both d) Neither. ANSWER: The correct answer is c) Both, they both use computing but in different ways for different purposes although these are merging as genomic data is increasingly being incorporated into medical records and practice in order to personalize care so that may not be as true in the future as it is today.

As we’ve said, healthcare Informatics serves healthcare delivery — the translation of medical knowledge into the care of actual patients. The key components of health informatics are: electronic medical records created and used by licensed professionals; patient-generated personal health records and a technology called health information exchange which can be used to share information among providers caring for the same patient; to aggregate information to create a more comprehensive and holistic electronic health record; to manage patient populations and the public health at large; and to support research of various kinds. Accomplishing this data exchange demands technologies to assure privacy and security of health data, as required by law, and other technologies to define standards so that data from diverse sources can be meaningfully combined.

In the next lesson we’ll meet Marla, a fictional character who will help me explain health care delivery and health informatics and how they interact.

You can use the course forum to interact with other students and get clarification on any points from the videos or text. It can also be a place to help find answers to questions you find difficult or where you can help others who are having trouble. As a practice example, look for a link to the forum under the Discussion heading on this page to get the answer to the following.

Each lesson in this course corresponds to a chapter from my textbook Contemporary Health Informatics. A link to purchase it at a discount is in the instructor’s notes. … I also strongly suggest you subscribe to iHealthBeat, a free, daily e-newsletter published by the California Health Foundation. Just reviewing it each day will give you a good understanding of what’s happening in healthcare and health informatics. There are also some other suggested blogs and newsletters I recommend you refer or subscribe to in order to enrich your learning experience. You can find this information in the text or in the Instructor’s Notes on this page, and it will also be collected in the course materials page. Now, let’s get started with Health IT.

Key Concepts/Vocabulary

● Healthcare ● Health Informatics ● Bioinformatics ● Discussion Forum, Instructor’s Notes, and Quizzes

Lesson 1

Video Transcript (Lessons 0 and 1)

In this lesson we’ll explore the unique characteristics of the US healthcare system with a particular emphasis on the mis-match between what its good at and its structural issues that contribute to poor management of chronic disease, the problems that account for most healthcare costs. You’ve previously met Marla, the chronic disease patient who will help us explore this. Now let’s learn more about her.

[Series of videos about Marla]

By now you should have a clear picture of the key differences between chronic and acute diseases. Unlike acute medical problems, chronic diseases are more often caused by behavior, generally can’t be cured and, particularly if not well managed, can cause other chronic diseases and complications that are difficult and expensive to treat. Now we’ll turn again with Marla’s help to what, for our purposes, is probably the key issue with respect to chronic disease — though they are very common, our healthcare system is not well designed to manage them.

[Series of videos about Marla]

So, now you understand a bit about the alternate models of care delivery, but you may be asking why this matters so much. For the answers to that we return again to Marla to explore some of the serious problems facing US healthcare. This will also set the stage for understanding the key role that health IT may play in improving our healthcare system.

[Series of videos about Marla]

So, with Marla’s help, we’ve covered some of the key problems in US healthcare and some of the principal arguments for the increased use of health IT: a.  Most healthcare is concerned with the management of chronic diseases b.  Proper management requires a highly coordinated, more continuous approach to care that welds together many providers into a seamless delivery system c.  At the center of such a patient-centered system of care is the Primary Care Physician whose role is knowing everything about their patients so they can coordinate their care d.  In practice this is very difficult to achieve because of the shortage of PCP’s here in the US and the large number of providers who are involved, particularly in the care of patients like Marla who have multiple chronic disease e.  Coordinating this requires electronic records, ideally for the providers and patients, and the seamless exchange of the information in them f.  That same information can be used to manage the health of populations of patients or the public at large g.  It can also be used for research to gain new medical knowledge and even learn how we can improve healthcare delivery

There are historical reasons why our healthcare system is the way it is and why we’ve been so slow to adopt health IT. For more on that and more details on the US healthcare system refer to Chapter 1 in the text. Now that we have the background to understand why fixing healthcare is a national priority, we’ll look at what the US federal government is doing to foster the adoption of health IT and create new financial incentives to encourage more use of patient-centered care.

Key Concepts/Vocabulary

● Rescue Care ● Acute disease ● Chronic disease ● Organisation for Economic Co-operation and Development (OECD) ● Health Maintenance Organizations (HMOs)

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Lesson 2

Video Transcript

In Lesson 1 we introduced the disconnect between what is required to successfully manage the chronic diseases that drive most healthcare costs and the structure of the US healthcare system. We also suggested that health IT could be a key tool for restructuring healthcare delivery to help address these issues. We’ll review that in this lesson before turning to the policies the US federal government has adopted in recent years to encourage adoption of health information technology and new models of patient-centered care.

From an engineering perspective chronic disease care presents a data logistics problem. Here’s a more dramatic “network depiction” of the complex, highly specialist driven care of the chronic disease patients in the typical Primary Care Physician’s practice. As you k.now, the average patient with multiple chronic diseases — the 20% of Medicare patients that drive half of the costs — is seen each year by 14 providers who are mostly specialists, as shown here. In aggregate, all the multiple chronic disease patients in a typical PCP’s practice are seen by 86 providers, again mostly specialists. Keep in mind that each of those specialists mostly focuses only on the particular organ or body system they have special knowledge of and are trained to treat.  In total, the average PCP is involved with over 200 other providers.

This situation is reminiscent of the network of specialized suppliers to a manufacturing company. One makes seats, but not radiators while another makes dashboards, but not tires. But, somehow, it all needs to come together seamlessly to produce a great car. Those industries long ago recognized the need for automation to help coordinate their supplier network starting with the automobile industry in the 1980’s. Until very recently — and this only started to change as a result of the federal programs we’ll discuss in this lesson — the healthcare industry tried to operate its complex care network using paper records and fax machines.

Again, quickly reviewing because this is so key to what follows, US healthcare is highly uncoordinated because so many specialized physicians are involved in the care of patients with multiple chronic diseases. One reason is that we have a much smaller percentage — around 12% --of primary care physicians than other countries. Note that in these countries its around 50%.  The resulting problems are not theoretical. Chronic disease patients report more often being seen with incomplete or missing records the more providers they see.

Recall that the typical multiple chronic disease patient, like Marla, fills around 50 prescriptions per year because, for most chronic diseases, medications are the main therapy. Misuse of medications, including in particular duplicates because of poor care coordination, is a major problem that accounts for nearly a third of all hospitalizations.  Surveys by the Commonwealth Fund in 2008 and 2011 show progress but many patients from all countries (28% in the US) report that no provider has reviewed their medications with them in the past year. Such a review could help ensure that patients are taking only the medications they need and are taking them properly. One reason for the absence of review is that physicians may not even know the medications that other physicians have prescribed for a patient like Marla. We’ll return to it later on but this process, called medication reconciliation, is a clear opportunity for health IT once the underlying records are digita. Here is a screenshot from an actual commercial HIT system showing the medications in this physician’s EMR on the right and those out in other EMRs on the left.  The patient is taking this medication [point to it]but it isn’t in this physician’s record.

As we’ll see later on, electronic prescribing (e-Prescribing) is a key requirement of the new federal adoption programs. Because electronic prescriptions are clear and legible and an EMR can often spot potential problems as prescriptions are written, e-Prescribing has been shown to dramatically reduce medication errors within a year of being adopted. As you can see here they declined from 42.5 per 100 prescriptions to 6.6. Someday soon, hopefully, each provider will have a full medication record including whether patients are filling their prescriptions and then refilling them at the proper interval - both are currently major problems. Currently patient privacy concerns, a topic we’ll discuss in Lesson 4, are an impediment to routinely and automatically providing this information.

Since these problems have been around for a long time why are we only now getting around to solving them? One reason is the increasing incidence of chronic disease for least the two reasons shown here. People are living longer as we can see by comparing the green bars from 1999-2000 with the blue bars from only 10 years later.  Chronic disease rates increase with age. Moreover, in large part due to behavioral issues such as increasing obesity, the rates of chronic disease have increased significantly over this same relatively short period of time.

This lesson is about the policies and programs the US federal government has created to encourage the adoption of electronic records and other health IT tools and to provide incentives for their use in ways that will improve the quality and efficiency of care.  Healthcare providers have had a financial incentive to do all available tests and procedures once someone is sick and have had little or no incentive to keep their patients well. Until recently there was no incentive — except for special situations like HMOs that we discussed in Lesson 1 — to invest money in HIT systems that might actual reduce income by helping avoid unnecessary or duplicative tests and procedure. These incentives are often referred to as “pay-for-performance” or PFP. In the typical PFP system providers are rewarded for doing the tests and procedures that scientific evidence suggests are beneficial for either managing or preventing chronic disease. For diabetes, this might be an annual blood test called HbA1c that we’ll discuss later. It might also be screening their patients for obesity and smoking and counseling them to lose weight or quit.

An advanced PFP system rewards providers who are able to produce higher care quality at a lower cost. There is evidence that these programs can work. Here are key results of the Physician Group Practice or PGP demonstration, a well-known Medicare pilot in 10 practices. All of the groups achieved improvements in 25 of 27 quality metrics for the key diseases shown here. Four practices earned a bonus for outstanding performance.

Marshfield Clinic earned half of the total bonus and, in explaining how they did it, their CEO cited “a well-developed electronic health record” and went on to describe how it reduced unnecessary duplication of services by making information available to all provider caring for each patient.

Accountable Care Organizations are a key feature of the new Affordable Care Act whose design is in part derived from the PGP demo.  There are currently a few hundred ACOs being formed or in operation. 32 select Pioneer ACOs are piloting an even more advanced approach. Like the Marshfield Clinic, Pioneer ACOs must use advanced health IT to manage entire populations of chronic disease patients in a coordinated manner, to exchange data, to report on results, to engage patients and to coordinate care.

In 2004, in his State of the Union Address, President George W Bush made universal adoption of electronic records a 10 year national goal. He tasked a new Office of the National Coordinator for Health IT with achieving the goal. In 2009, the Obama administration’s Health Information Technology for Economic and Clinical Health (HITECH) act provided funding of from $20 - $30 billion (the exact amount depends on adoption levels) to reimburse hospitals and eligible providers for adopting an electronic health record system. Providers are eligible based on the amount of Medicare or Medicaid patients they manage.

The adoption program has three co-dependent components: EHR Certification, Meaningful Use, and Incentive Payments. We’ll spend the rest of this lesson understanding these in more detail. CHANGE (1) EHR certification defines the minimal acceptable requirements for an EHR that, if used according to the requirements of Meaningful Use, would qualify an eligible provider for incentive payments. (2) Meaningful Use defines how eligible providers must use their certified EHR to be eligible to receive incentive payments. (3) Incentive payments from either Medicare or Medicaid compensate hospitals and eligible providers for implementing a certified EHR and achieving Meaningful Use.

Requirements for commercial EHR systems is an important development. For decades the grand challenge for health IT here in the US has been interoperability — the ability of the hundreds of commercial EMR products and tools to exchange and meaningfully share data. Even with universal adoption, without this, we can’t coordinated care among the many providers who care for the same patients. The EHR Certification process supports a basic interoperability capability.  Systems must record key demographic and clinical data, provide tools to measure and improve care quality, and protect data confidentiality, integrity and availability. We’ll now look at each of these in some detail.

Here’s a list of the kinds of data that must be collected. The reasons for some of these should be clear from our prior discussions.  Keep this list in mind as we later discuss Meaningful Use, the EHR usage requirements placed on eligible providers.

Just recording data isn’t sufficient. Certified EHRs must provide tools to use that data to improve care quality through functions like these. We earlier discussed the key role medications play in managing chronic disease and the many problems they currently create so note that the first four requirements relate directly to improved medication management. Also, note that the EHR must be able to calculate and report quality measures. Remember that as we discuss the key role that quality measures play in determining Meaningful Use.

Finally, none of this can be done legally or would be accepted unless EHRs can insure privacy so that patient data is accessible only to people to whom the patient grants access; they must also provide security from unauthorized access.  Other systems for information exchange must provide a means to establish trust — to know that the persons or entities with whom information is being exchanged are who they claim to be. The technologies to help meet these challenges will be the topic of Lesson 4.

Vendors become certified through a formal testing process developed by the National Institute of Standards and Technology (NIST) and administered by one of several companies. We’ll now take a closer look at that using one of the required items for data collection. You should recall that a certified EHR must “maintain a current problem list” but what does that mean? Medical problems are usually coded in a global data standard called the International Classification of Disease (ICD). A vendor can demonstrate that they meet this criteria by showing that their EHR can store test ICD codes and supplement them with problem status and the date diagnosed. The testing would include asking the vendor to change a problem’s status, for example from active to resolved, and demonstrating that this change is posted and displayed at appropriate places throughout their EHR.

Quality Reporting is a particularly interesting and challenging area generally done through Process and Outcome measures. While Outcome measures are usually preferable we often don’t have practical ones available. HbA1c, a test done on a blood sample can serve both as a process and an outcome measure for diabetes care. Hemoglobin, the red stuff in your blood cells, is the oxygen carrying molecule. The level of its A1c variant tracks with the amount of glucose, the molecular that is not properly regulated in diabetes, entering the red blood cells. The more glucose, the higher the A1c level but this increase occurs over time so HbA1c is proportional to the average blood glucose level over the prior couple of months. This is great since the goal of diabetes therapy is to keep that same average glucose level within normal ranges over time. As you can see here, the blood glucose level is volatile based on food that is eaten, exercise and other factors. However, it may go up and down but here the HbA1c level is remains at 7.0 indicating good control. In fact, good control is defined as a HbA1c level under 9 by many organizations but the highly regarded Mayo Clinic uses 7 as its benchmark.

The other two components of HITECH are Meaningful Use and Incentive Payments.  First, a basic overview of electronic medical records. Physicians are in the data business. They collect data, make treatment decisions based on it and follow patients through data in order to make treatment adjustments as needed. They collect subjective information from the patient including their chief complaint, their medical history and the history of the problem that brought them to the doctor including any symptoms they have observed. Physicians collect objective data by doing a physical exam and ordering images, laboratory tests or other diagnostic procedures. The resulting data may be free text, structured data such as ICD codes, continuous waveforms such as an electrocardiogram, images, sound recordings or even videos.  Moreover, data from chronic disease patients is increasingly coming from Smartphones or physiologic measurement devices to track their own health from home. Storing and presenting this rich data set is an EMR design challenge. Many EMRs simply mimic the organization of the paper chart even simulating the tabs that divide the sections where these data types are stored. Despite its key role in medicine, physicians have historically focused far more on collecting the right data than they have on recording it completely, accurately and legibly. As we’ve seen, in a fragmented system of care where many physicians treat aspects of a single patient’s care, this can lead to duplicate testing or even errors. Here’s a particularly dramatic example.

Meaningful Use is a very important and highly visible, even controversial at times, program divided into three stages that phase in over a period of years. Stage 1 is about Data Capture and Sharing, which depends on EHR Certification; Stage 2 adds Advanced Clinical Processes and is similar but more ambitious and sophisticated than Stage 1; Stage 3 aims for Improved Outcomes, which depends on more advanced EMR functionality such as clinical decision support to guide providers and tools to assist patients. Stage 3 is ambitious has recently been pushed out to at least 2017. A majority of providers and hospitals participating in Meaningful Use have achieved Stage 1 and are now focused on Stage 2, which only a small percentage have achieved at present.

We earlier discussed quality measures and now you’ll see why. Providers demonstrate that they have achieved MU Stage 1 by submitting measures in three categories: Core measures, Menu set measures, and Clinical quality measures. There are 15 mandatory core measures. Providers must also submit 5 of 10 “menu set” measures as well as six clinical quality measures. Three of these are mandatory and providers can select the other 3 from a list of 41. The core measures are divided into the four groups shown here: 1. Improve quality, safety, and efficiency, and reduce health disparities; 2.Engage patients and families; 3. Improve care coordination; and 4. privacy and security.

Menu set measures are similarly grouped, as shown here. As with the core measures, you should easily be able to see a close alignment with the coordinated management of chronic diseases along with other key priorities such as ensuring privacy and security and improved population and public health. The three mandatory clinical quality measures are screening for weight, screening for and diagnosing hypertension and preventive care and screening for smoking — all also closely related to chronic disease.

Stage 2 is similar to Stage 1 but raises the bar both quantitatively and qualitatively. It also introduces some striking requirements with respect to patient’s participation in their care. Here we see the bar going up using e-Prescribing as an example. Note the quantitative increase from 40 to 50% of e-prescriptions and the qualitative addition of checking the medication against a formulary — a list of medications usually reviewed by experts and felt to be cost effective treatments for their target condition.

I feel that no aspect of MU Stage 2 is more interesting and potentially impactful to the management of chronic disease than the requirement that “more than 5 percent of all unique patients seen by the EP during the EHR reporting period (or their authorized representatives) View, Download, or Transmit to a third party their health information”. This is referred to as VDT and ONC has released specific guidance as to what electronic patient summaries should be made available to patients under various care scenarios as described here. The first one is Transitions of Care where, for example, a patient goes from a hospital to a nursing home or back to their home.  Errors often occur at these transition points because information is not passed on completely and accurately. In Lesson 5 we’ll look in detail at the electronic clinical summary specified at transitions of care. You may wonder why providers are measured on activities actually done by their patients. Research shows that patients are far more likely to embrace electronic self care tools if their provider encourages them to do it and even provides some help in getting started. As a result of VDT many more provider practices will be offering encouragement and even the needed tools integrated with their EHR. We will return to VDT in Lesson 7 when we discuss these patient-facing tools.  Later, you’ll also obtain and use Marla’s clinical summary record in some activities.

Beyond these programs there is a clear need to change incentives that can be divided into at least three components. The first is reimbursement for the expense of the system and the second is some ongoing financial incentive to use the system properly. The Medicare and Medicaid Incentive Payments programs were designed to do the first. The Medicare payment program may do the second through penalties for providers and hospitals who don’t achieve meaningful use. It is also possible that private health insurance companies may start funneling patients to providers who have achieved meaningful use and the prospect of that is another incentive. The third needed incentive is changing reimbursement to some form of pay-for-performance, to further reward providers for improving care efficiency and quality.

The Medicare and Medicaid Incentive Payments are based on achieving the stages of Meaningful Use. The a mount providers can earn is tied to the number of Medicare patients in their practice. 30% of a practice must be in the Medicaid program 30% to qualify except for pediatricians where the threshold is 20%. The details for Medicare are shown here and you can review them if you are interested. The earlier a provider starts the more they can earn. Not shown here are the reductions in Medicare payments for providers that haven't achieved Meaningful Use by 2015. There are no penalties under the Medicaid program.

These programs have succeeded to a greater degree than many observers (including your instructor) thought possible.  As of March, 2014 more than 371,000 eligible hospitals and professionals received incentive payments for achieving at least Stage 1. This is over 90 of some 5,000 eligible hospitals and nearly 70% of the estimated 527,200 eligible professionals.

Here you see the composition of those adopters As you might expect, younger providers are more likely to adopt but the difference isn’t striking. What is striking (and has been in all prior studies) is the difficulty smaller practices have in adopting, presumably due to lack of financial as well as technical resources since many of these are in rural, poor, underserved areas. ONC funded a special Regional Extension Center program to provide special help to these providers.  Note that practice ownership can also be a significant factor.

Once they adopt, substantial majorities of providers report administrative, financial and, most importantly, clinical benefits.  Around 70% of non-surgical specialists report improved clinical communication — a key result given what you’ve learned about our fragmented approach to managing chronic disease. Another recent survey reports that, despite shortcomings in their current EHR, less than 20% of providers would revert to paper if that option was available.

Time to take a deep breath! We’ve covered a lot of territory in this lesson. We’ve learned about the core rationales for HIT adoption and deepened our understanding of the link between it and success in managing chronic disease. We’ve even seen evidence linking this success to HIT that has resulted in the federal policies to encourage adoption that occupied most of this lesson. We’ve learned that those policies are divided into three linked efforts to: 1) assure that EHRs have key capabilities; 2) that they are used in a manner that is believed will lead to improved care coordination and, ultimately, to improved outcomes; and that 3) financial incentives are there to reimburse providers and hospitals for the cost of these systems and to provide ongoing incentives to use them properly. We’ve seen that adoption levels are quite high but that survey data reveals some dissatisfaction with current EHR systems. We’ll look more deeply into why that is the case in Lesson 6 as we begin to look at real world applications of health IT in the second half of the course.

Next we delve into the technologies that power real world HIT systems. You’ve now heard of one of them — data standards — when we looked at ICD codes and their role in EHR certification. You’ve also heard hints of the importance of the other two — technologies for assuring privacy, security and trust and for supporting health information exchange. We now begin a three lesson sequence in which we’ll cover these in the reverse order to which I’ve just introduced them — beginning with health information exchange.

Key Concepts/Vocabulary

● “Pay-for-performance” ● Office of the National Coordinator for Health IT (ONC) ● EHR certification ● Meaningful Use and Its Three Stages ● Incentive payments for Medicare/Medicaid Providers ● Process and Outcome Quality Measures ● Secondary Use of Clinical Data

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Lesson 3

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Lesson 4

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Lesson 5A

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Lesson 5B

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Lesson 6

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Lesson 7

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Lesson 8

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Lesson 9

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Lesson 10

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Suggested Blogs:

Geek Doctor
John D. Halamka, MD, MS, is Chief Information Officer of the Beth Israel Deaconess Medical Center, Chief Information Officer and Dean for Technology at Harvard Medical School, Chairman of the New England Health Electronic Data Interchange Network (NEHEN), CEO of MA-SHARE (the Regional Health Information Organization), Chair of the US Healthcare Information Technology Standards Panel (HITSP), and a practicing Emergency Physician.

HIS Talk
The anonymous author says he works for a non-profit hospital that has vendor relationships with some of the companies he writes about. He says that his objectivity (and potentially his job security) could be compromised if vendors or anybody else worked that connection to muzzle him.

HIT Sphere
This is an attempt to create a one-stop shop where people can get blogs, news, tools, and other items of interest to the healthcare IT community. It was founded and is operated by Shahid N Shah, an enterprise software analyst who specializes in healthcare IT. Over the past 15 years he has been CTO for CardinalHealth’s CTS unit (now CareFusion), CTO of two Electronic Medical Records (EMR) companies, a Chief Systems Architect at American Red Cross, Architecture Consultant at NIH, and SVP of Healthcare Technology at COMSYS.

InformationWeek Healthcare
A group of regular bloggers (including your instructor) comment on contemporary issues in healthcare and health IT.

John Lynn
John has written over 1,500 articles on the topics of EMR, EHR, HIPAA, and healthcare IT. He was the EMR Manager for the University of Nevada Las Vegas’ Health and Counseling Center. In this capacity he led the conversion from paper charts to a full electronic medical record. He has also worked on a variety of EMR consulting opportunities.

Wes Rishel
Wes is a vice president and distinguished analyst in Gartner’s healthcare provider research practice. He covers electronic medical records, interoperability, health information exchanges and the underlying technologies of healthcare IT, including application integration and standards.

Some of these blogs may accept advertising from the HIT industry so consider that when you read them!