Saturday, May 26, 2007

Knowledge, Standards, and the Healthcare Crisis: Part 4

In the previous post, I discussed "care measurement and process standards," which are data standards dealing with diagnosing health problems, determining treatments, and assessing care quality and provider performance. [Click here for first post in series] In this post, I turn to technology standards, and to "messaging format" standards in particular. Whereas data standards focus on making information understandable and useful to humans, messaging format standards focus on enabling the exchange, or interoperability, of data and information (i.e., "transactions") across healthcare systems.

HL7 Messaging Standard

The Health Level Seven (HL7) Messaging Standard is the most recognized. It specifies the technical aspects of sending messages so that one software program can exchange information with another, so the information is "understood" by the receiving machine. This standard handles information related to order entry, scheduling, medical record and image management, patient administration, observation reporting, financial management, and patient care transactions.

For example, an HL7 formatted message delivering data about a patient's EKG would be written like this: "OBX2ST93000.1^VENTRICULAR RATE(EKG)91/MIN60-100". Here's what it means:
  • OBX = The message is a report of an observation/result
  • 2ST = The data value is a two character string
  • 93000.1^VENTRICULAR RATE(EKG) = The code number and name of the EKG test
  • 91/MIN = The observation value and units (beats/minute)
  • 60-100 = The reference or normal range for this test. 
Note that this HL7 message standard just provides a message structure (syntax), i.e., the use of pipe symbols ("") to separate message elements, and the order in which the elements appear; none of the content (codes, terminologies, values) is defined by this HL7 standard. Also note that the next version of HL7 (version 3) will be tied to specific terminologies, thereby adding semantic capabilities that enable different data systems to communicate with each other.

HL7 Version 3 messages are XML documents, which use a very complex and verbose structure of "markup tags" to identify the data values. These tags are strings of characters surrounded by angle brackets, which are depicted in the figure below. The figure is a small section of an HL7 clinical document in XML, which includes the use of the SNOMED CT terminology standard in which the terms "Osteoarthritis", "finding site" and "right knee" are used to define the medical history note that the patient is "complaining of disabling osteoarthritis of the right knee."

The beauty of XML is that anything can be defined using the markup tags. A down side is that XML is very inefficient. For example, in the XML document above, it takes about 700 characters to record an observation that's only about 100 characters in length. Furthermore, such XML documents can be complex to write and difficult for humans to read. This concludes my description of standards used in healthcare. In the next post, I'll delve into the problems with today's standards and will the offer innovative strategies for solving those problems.

Monday, May 21, 2007

Knowledge, Standards, and the Healthcare Crisis: Part 3

In the previous post, I discussed "terminology standards," which deal with the meaning and use of words (terms). In this post, I continue with the discussion of data standards, focusing this time on standards for diagnosing health problems, determining treatments, and assessing care quality and provider performance. This all relates to care measurement and process standards. [Click here for first post in series]

Care Measurement and Process Standards

Care measurement and process standards focus on:
  • Diagnosing health problems
  • Selecting and delivering treatments
  • Evaluating care performance and value.
Diagnosing Health Problems

Physiological (bodily) and psychological (mental-emotional-behavioral) measures are used to diagnose a patient’s health problems.

Physiological Measurement Standards

Physiological measurement standards include vital signs and lab test "reference ranges." For example, the standard measures for hypertension is systolic pressure consistently greater than 140 mm Hg, or diastolic pressure consistently 90 mm Hg or more and a standard measure for diabetes is fasting blood glucose level of 126 mg/dL or higher on two occasions. Genetic markers associated with illnesses may also be considered a type of biologic measurement standard. These standards not only help diagnose a patient's condition, but may also determine one's risk of developing a disease.

Psychological Measurement Standards

Probably the most common psychological measurement standard is the IQ test, which defines a score of 90-110 as being within the "normal" range of intelligence. There are also standardized tests that measure mental status (e.g., awareness, memory and other cognitive functions), as well as depression, anxiety, personality traits and other psychological factors.

Selecting and Delivering Treatments

The diagnostic measurement standards are useful if they help select a particular practice guideline identifying a particular treatment for a particular patient with a particular diagnosis. The guidelines provide recommendations for the prevention, treatment, and maintenance of many nontrivial illnesses, conditions, disorders and other healthcare problems. There are three thorny problems, however:
  1. Today's diagnostic systems often fail to point to the best treatment options.[1]
  2. Few guideline standards are specific enough to account for individual differences in patient with the same diagnosis. For example, a recent study found that a moderately high total cholesterol level is associated with higher survival in certain patients with heart failure.[2]
  3. Constantly evaluating and revising guidelines based on new knowledge is very difficult. But if they do not continually evolve, the guidelines are just "a record of the past, and little more-they should have an expiration date."[3]
Evaluating Care Performance and Value

At least three standards are related to clinician performance and care value:
  1. Process compliance standards
  2. Clinical outcome standards
  3. Care value standards.
Process Compliance Standards Process compliance standards measure provider's performance based on whether they followed prescribed guidelines reflecting preferred care processes. For example, typical Pay for Performance (P4P) programs reward providers who perform certain predefined procedures (processes), such as doing a Hemoglobin A1c test a certain number of times each year for patients with diabetes. These standards measure the degree of compliance to such established procedures.

Clinical Outcomes Standards

Outcomes standards define whether clinical goals are achieved for patients with particular conditions. For example, the Hemoglobin A1c test target goal for diabetic control of blood glucose is defined as less than 7.0%. Unlike process compliance standards, clinical outcomes do not focus on whether specific procedures were followed; instead, they measure the effectiveness of whatever treatments were delivered.

Care Value Standards

If our healthcare system was rational and guided by wisdom, a top priority of healthcare professionals and consumers would be:
  • Gaining valid knowledge about healthy living, the causes and diagnosis of physical and mental health problems, and the highest value treatments.
  • Understanding how to use this knowledge to maximize value by increasing the effectiveness and efficiency of care delivery and self-maintenance.
  • Continuously evolving this knowledge and using it to improve care quality and lower costs continually.
So, what is care "value."

Care value can be measured by dividing the quality if that care by its cost, i.e., V = Q / C:
  • Q (Quality) is defined as the degree to which care is delivered safely, effectively and equitably. The care may include conventional and alternative interventions for treating illness, as well as wellness intervention for prevention and health optimization. Quality can be measured based process compliance standards, clinical outcomes standards, or both.
  • C (Cost) is defined as the degree to which the care is delivered efficiently and economically.
  • V (Value), therefore, can be defined as cost-effectiveness ("bang for the buck").
If there is to be significant improvement in healthcare delivery, a useful and reliable quality standard must be established for every healthcare domain/discipline/field. Only then can care value be determined.

Potential Pitfalls of Care Quality Measurement

While costs can sometimes be tricky to calculate, measuring quality is the major challenge. The potential pitfalls of quality measurement are enormous! Consider the following:
  • We have a long way to go. According to HHS Secretary Mike Leavitt, "Medical associations and others have begun the work of developing quality standards and cost measurement, but we have many years of work ahead of us to achieve the wide-ranging and meaningful quality standards we need."[4]
  • No mater what quality measures are used, there are complex issues to be resolved, such as:
    • At what point is there sufficient confidence in an evidence-based practice guideline that there is no longer any need to spend time or money on the continuous evaluation of its reliable and validity?
    • When is a definition of quality too narrow, e.g., by focusing on cost or symptom reduction, but not considering prevention, recurrence, coordination and continuity of care, or the patient-physician relationship?
    • How do you measure quality when resources are scarce and optimal care for the community may require less than "the best" care for its individual members (e.g., delegating office nurses to perform certain activities that physicians used to do)?
    • What is the best way to measure quality if outcomes are more strongly affected by patient compliance than by physician orders? This may occur, for example, if certain providers have personalities that trigger greater patient compliance, and visa versa.
    • Is it poor quality care if a provider follows the recommended practice guideline, but the patient is atypical and responds poorly? [5]
    • Use of claims (administrative) data to measure care quality is grossly inadequate for many reasons.[6]
  • Assessing care quality using process data may not be valid since they do not necessarily reflect care outcomes.[7]
  • One thorny issue is how to avoid political and ideological biases when determining what evidence to use as the basis for establishing the guidelines. [8]
  • Many areas of healthcare lack care process standards and/or quality measures. Different healthcare disciplines and specialties require different types of data to evaluate quality. For example, it's foolish to measure the quality of mental healthcare services with data appropriate for evaluating cardiologists' performance; and the same is true for a podiatrist, dentist, chiropractor, etc.-each need different measures for determining quality, but they are often lacking.[9]
To summarize this post, it is critical to have useful, reliable standards to assist with diagnosing patient problems, selecting and delivering the best treatment options, evaluating clinical performance and identifying care value. Unfortunately, we have a long way to do before such standards become a reality.

This concludes by review of data standards. In my next post, I'll examine "technology standards," which focus on enabling the exchange, or interoperability, of information across healthcare systems.

[1] Current Diagnostic Codes are Inadequate - WellnessWiki
[2] Reuters (Sep 20, 2006). Elevated cholesterol may benefit failing hearts.
[3] Gawande, A (2004). The Bell Curve. The New Yorker.
[4] Bush's Value-Driven Health Care Plan Gains Steam as More Employers Step Up (May 10, 2007)
[5] Donabedian, A. (2005). Evaluating the Quality of Medical Care. The Milbank Quarterly 83, 691-729.
[6] Use of claims data is inadequate - WellnessWiki
[7] HealthDay (July 5, 2006). Hospital Ratings Don't Fully Reflect Patient Outcomes. [
8] Healy, B. (Sep. 2006).Who Says What's Best? U.S. News and World Report. [
9] Need for specialy measures - WellnessWiki

Saturday, May 12, 2007

Knowledge, Standards, and the Healthcare Crisis: Part 2

In my previous post, I discussed how knowledge is the foundation of healthcare improvement, and how health information exchange is vital for creating and using knowledge. I then introduced the notion that standards are essential for sharing information and implementing knowledge in a way that improves patient care. I also mentioned that, while beneficial, there are substantial challenges to the effective implementation of standards.

Continuing on the topic of Knowledge, Standards and the Healthcare Crisis, I will now begin define what standards actually are.

What are standards?

Standards are models, principles, policies, or rules that provide an agreed-upon framework for doing and understanding things. There are many different types of standards. When it comes to health information exchange, both data and technology standards are important. These standards describe (a) how health data are to be categorized and defined and (b) how different software systems are to communicate with each other when exchanging data. I will now discuss each.

Data standards

Data standards can be divided into at least four categories: terminology, measurement, care process, and messaging format standards. In this post, I describe terminology standards.

Terminology Standards Defined

Health-related terminologies are sets of terms representing a system of concepts within a specified field (domain) of healthcare. In other words, a terminology standard refers to a "nomenclature," i.e., a systemic way of naming and categorizing things in a given category.

Terminology standards include classifications and vocabularies that group together related terms so they can be more easily and consistently understood. Classifications arrange related terms for easy retrieval. Vocabularies use sets of specialized terms to facilitate communication by reducing ambiguity.

Take, for example, the term "high blood pressure" -- the following terms are synonyms of high blood pressure or the names of conditions referring to it:

accelerated hypertension; arteriolar nephrosclerosis; benign hypertension; benign intracranial hypertension; chronic hypertension; essential hypertension; familial hypertension; familial primary pulmonary hypertension; genetic hypertension; hypertension-essential; hypertension-malignant; hypertension-renovascular; hypertensive crisis; idiopathic hypertension; idiopathic pulmonary hypertension; malignant hypertension; nephrosclerosis-arteriolar; pph; pregnancy-induced hypertension; primary obliterative pulmonary vascular disease; primary pulmonary hypertension; primary pulmonary hypertension (pph); primary pulmonary vascular disease; pulmonary arterial hypertension, secondary; pulmonary hypertension; renal hypertension; secondary pulmonary hypertension; severe hypertension; toxemia; toxemia of pregnancy[1], hyperpiesia, and hyperpiesis.

Now imagine two electronic health record systems attempting to exchange patient data. One system is able to recognize the term "high blood pressure" and the other the term "hypertension," but neither can recognize both terms. These two computers would be unable to share the data because they don't "understand" what each other is "saying." This is because computers cannot deal with synonyms (using different words to say the same thing) or homonyms (when the same terms or phrase means different things in different contexts). So, when multiple healthcare providers treat the same patient (who may have multiple health problems), exchanging patient data can be difficult, which is due to the issues of semantics and syntax.

Semantics and Syntax

Semantics and syntax are standards of language. Semantics refers to the meaning of words, expressions and sentences, i.e., how they are defined. Syntax, on the other hand, is the structural or grammatical rules that define how symbols in a language may be combined to form words, phrases, expressions, etc., which includes spelling and word order. For example, in the U.S., this pattern of numbers "###-##-####" could be the syntax for coding a Social Security Number and mmm/dd/yyyy the syntax for a date.

In the situation above, there is semantic confusion since the two software systems define excessive blood pressure using different terms (high blood pressure vs. hypertension). Syntax would be a problem if, for example, both systems used the term high blood pressure, but only one required that the three words be connected, i.e., "high_blood_pressure".

Classifications and vocabulary terminology standards attempt to address these issues.


Terminology classification standards in healthcare use a hierarchical index. The ICD-9 diagnostic standards, for example, classifies high blood pressure using this hierarchical index: Diseases of the circulatory system > Hypertensive disease > Essential hypertension (which includes high blood pressure; hyperpiesia; hyperpiesis; arterial, essential, primary and systemic hypertension; and hypertensive vascular); and it gives it a classification code number of 401.[Update; The ICD-10 is not being used]


Terminology vocabularies standards, on the other hand, often consist of "controlled vocabularies," which are similar to the Library of Congress Subject Headings used by most libraries cataloguing books. Another example is the Yellow Pages in the phone book where, for example, car dealerships are listed under "Automobiles" instead of "Cars" or "Dealerships." Automobiles is, therefore, the "controlled vocabulary" used by the yellow pages.

In healthcare, the MeSH thesaurus is a controlled vocabulary catalog for searching biomedical and health-related information and documents. Searching for "high blood pressure" in the MeSH database returns the heading "Hypertension" and defines it as "Persistently high systemic arterial BLOOD PRESSURE. Based on multiple readings (BLOOD PRESSURE DETERMINATION), hypertension is currently defined as when SYSTOLIC PRESSURE is consistently greater than 140 mm Hg or when DIASTOLIC PRESSURE is consistently 90 mm Hg or more." So, MeSH says "hypertension" should be the term everyone uses to define blood pressure readings within this range; and if they use a different term, it should be translated to "hypertension."

Examples of Existing Terminology Standards

Following are some of the healthcare terminology standards system in use today:
  • International Classification of Diseases (ICD) codes for diagnosis disorders
  • International Classification of Impairments, Disabilities and Handicaps (ICIDH) codes for diagnosis handicaps
  • International Classification of Nursing Practice (ICNP) for class nursing vocabularies
  • Diagnostic and Statistical Manual (DSM) codes for classification of mental disorders
  • Logical Observations: Identifiers, Names, and Codes (LOINC) codes for representing laboratory tests and procedures
  • Current Procedural Terminology (CPT) codes for identifying conventional treatment procedures
  • Advanced Billing Concept (ABC) codes for identifying integrative medicine procedures
  • Digital Imaging and Communications in Medicine (DICOM) for distributing and viewing any kind of medical image
  • Health Care Financing Association (HCFA) that controls Medicare and Medicaid and supports standards for reimbursement
  • Unified Medical Language System (UMLS), a system linking together various medical vocabularies
  • Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT), a system of standardized medical terminology
  • The Medical Subject Headings (MeSH) thesaurus, a controlled vocabulary produced by the National Library of Medicine and used for indexing, cataloging, and searching for biomedical and health-related information and documents
  • Health Plan Employer Data and Information Set (HEDIS) is a standardized set of 60 performance measures for managed care plans.
In my next post, I define measurement, care process and messaging standards.


[1] ICON Health Publications Official Health Sourcebooks

Tuesday, May 08, 2007

Knowledge, Standards, and the Healthcare Crisis: Part 1

There is widespread acknowledgement that our healthcare system needs radical transformation since:
  • All patients “…are at risk for receiving poor health care, no matter where they live; why, where and from whom they seek care; or what their race, gender, or financial status is”[1]
  • Healthcare is increasingly more expensive and less accessible[2], with more than 46 million uninsured in the U.S. from every age group and at every income level, 8 out of 10 being in working families[3]
  • There is a “knowledge gap”—the healthcare community is drowning in oceans of information, yet doesn't know the best ways to prevent health problems and treat them cost-effectively.[4]
In this next series of posts, I will offer an answer to this daunting question: What can be done to drive continuous improvements in care safety, quality and efficiency, which would enable people to remain healthy longer, manage chronic conditions more effectively, and receive the best possible healthcare delivered in the safest and most economical way?

My answer focuses on the creation, use and evolution of valid health knowledge. Why? Because, I contend, the quality of care would improve dramatically and costs would drop precipitously if everyone:
  • Knew the best ways to prevent illness, to avoid complications of chronic diseases, and to treat health problems in the most effective and efficient manner
  • Used this knowledge to promote wellness, self-management, and recovery
  • Participated in evolving this knowledge to make it ever-more useful and effective.
So, what would it take to foster widespread knowledge creation, use and evolution in our healthcare system?

Well, since knowledge emerges from information,[5] it is essential that both consumers/patients and providers have access to useful health information, including patient health data, care outcomes, and evidence-based guidelines. Furthermore, the information must be presented in a way tailored to each person’s needs and be made available whenever it’s needed. Unfortunately, this is much easier said than done for many reasons.

One daunting core problem involves exchanging patient data between disparate electronic record systems. After all, knowledge can’t grow and care can’t improve unless patients share their health information with their providers, providers share patient information with each other, and researchers have access to this information to develop evidence-based guidelines. And this must be done in a convenient and secure manner that protects patient privacy.

With cost estimates for developing a national health record system enabling patient data exchange being between $100-276 billion,[6] the question is, why must it be so expensive? Aren’t there any easy, inexpensive ways to do it? Let’s examine these questions.

One way to reduce health information exchange costs is by developing and using standards that promote interoperability between disparate health record systems.

Standards are models, principles, policies, or rules that provide an agreed-upon framework for doing and understanding things. When it comes to health information exchange and knowledge growth, at least two types of standards come into play: data and technology standards. These standards describe how health data are categorized and defined, how health outcomes and healthcare performance are measured, how healthcare knowledge is used, and how different software systems communicate with each other when exchanging data.

In my next post, I examine this double-edged sword of standards, pointing out their benefits and the thorny problems they create.

[6] Linking Providers Via Health Information Networks by The Alliance for Health Reform (2006) and Dying for Data by R.N. Charette (2006)