PHM Glossary: A


Absenteeism is the act of physical absence from the workplace on the part of an employee. Absenteeism generally applies to the situation in which an employee is frequently or chronically absent (often as a result of a health condition) rather than infrequent or random absence. Absenteeism is often addressed through progressively stricter disciplinary measures that can result in termination of the individual's employment, as determined by the organization's attendance policy.

See also employee productivity.

Accountable Care Organization (ACO)

The concept of an "Accountable Care Organization" (ACO) was established in federal law with passage of the 2010 Patient Protection and Affordable Care Act (ACA). In section 3022, an ACO is defined as "an organization of health care providers that agrees to be accountable for the quality, cost, and overall care of Medicare beneficiaries who are enrolled in the traditional fee-for-service program who are assigned to it."

In order to qualify for Medicare contracting as an ACO, the organization will need to have a formal legal structure that can receive and distribute shared savings as well as manage clinical and administrative systems, have a sufficient mass of primary care providers, care for at least 5,000 beneficiaries, have "sufficient information" about their providers, promote, support and report quality and cost measures and practice patient centered care.

Organizations that may become ACOs are: 1. Physicians and other professionals in group practices, 2. Physicians and other professionals in networks of practices, 3. Partnerships or joint venture arrangements between hospitals and physicians/professionals, 4. Hospitals employing physicians/professionals, and 5. Other forms that the Secretary of Health and Human Services may determine appropriate. It is slated to begin January 1, 2012.

For ACO purposes, "assigned" means those beneficiaries for whom the professionals in the ACO provide the bulk of primary care services. Assignment will be invisible to the beneficiary, and will not affect their guaranteed benefits or choice of doctor. A beneficiary may continue to seek services from the physicians and other providers of their choice, whether or not the physician or provider is a part of an ACO.


Medicare "Accountable Care Organizations" Shared Savings Program—New Section 1899 of Title XVIII. Available at


The process of an impartial organization providing assessment, recognition and certification to a group or organization that demonstrates and maintains the standards set by the accrediting organization.


The Care Continuum Alliance recognizes the role that accreditation organizations play in developing industry standards and assessing adherence to adopted standards. Accreditation initiatives have the potential to promote industry standards and encourage best practice-based improvement across an industry. Ultimately, this leads to better information, improved performance, and higher quality for customers and participants.
Examples of accrediting organizations include National Committee for Quality Assurance (NCQA), Joint Commission on Accreditation of Healthcare Organizations (Joint Commission), and Utilization Review Accreditation Commission (URAC).

Actuarial Adjustments

Statistical modifications or transformations applied to underlying data to adjust for nonequivalence between groups or populations in a measurement calculation.


Measurement of disease management outcomes requires comparing with a reference population an intervention population. An essential component for validity in measurement is equivalence. However, even in randomized control trials, equivalence between the reference and intervention populations is not assured. Some degree of adjustment may be necessary so that the measurements are valid and generalizable to the overall population from which the study population is drawn.

Adjustments should be made to correct for differences between the populations. However, in some circumstances correction or adjustment is not possible. Generally, it is not possible to correct for bias.
Health care actuaries have considerable experience with health claims data and the adjustments needed to ensure equivalence. Their training in risk management and exposure and responsibility for health care pricing and underwriting have given them experience in actuarial adjustment.


The pricing and underwriting function in a health plan (or self-insured group) has many parallels to the measurement process used in chronic care management evaluation. The pricing/underwriting process includes the following steps:

  1. Assemble and reconcile reference population and underwriting population data.
  2. Data validation: Are the absolute levels of key metrics, such as costs per member per month or admissions per 1,000 per year, reasonable?
  3. On the basis of key metrics, how comparable are the reference population and the underwriting population?
  4. What changes are expected in the projection period in population and utilization? What Trend assumptions are appropriate for utilization and cost components?
  5. What adjustments to the reference population are necessary to conform to the underwriting population? For underwriting purposes, these adjustments may include, but not be limited to:
    • Age/sex;
    • Geography;
    • Plan design, product, or network;
    • Morbidity;
    • Disease burden;
    • Maturity of the group (i.e., how long since members have been in the group or how long since identification with the chronic condition);
    • Maturity of the data (i.e., runout);
    • Member turnover; and/or
    • Large claims or outliers.

The underwriting or pricing actuary will adjust the baseline population experience until he or she is confident that the adjusted population matches the risk profile of the group being underwritten or priced. A similar process may be used in disease management measurement.


1. The simplest and most common change adjusts for temporal differences between the baseline and intervention periods. In this example,

  • Baseline period cost per member per month is $95. Baseline population metrics are measured over the period 1/1/2000 to 12/31/2000.
  • The intervention period begins 1/1/2001 and the first measurement period runs from 1/1/2001 to 12/31/2001.
  • The populations for comparison are selected using exactly the same criteria.
  • Baseline cost per member per month is $100, and intervention cost per member per month is $95. What is the estimated savings due to the intervention?

It is appropriate to apply a Trend adjustment to the baseline cost per member per month. We use the capitalized term Trend to distinguish the specific, actuarial use of the word, from the general use (trend, or tendency to change over time). Because an intervention program has been applied to the population, measuring Trend on the intervention population would not provide an unbiased estimate of the effect of the passage of time on health care costs.

A Trend estimate, external to the population whose cost is being estimated, is sought. This could be obtained from a non-chronic population of the same sponsor, or it could be from an external source, such as one of the actuarial firms that maintain these statistics. Assume that the Trend estimate is 5% for the period in question.

Then the estimated program savings are:

$100 * 1.05 = $105 - $95 = $10

2. Another common methodology is to use a control group that is measured at the same point in time but differentiated from the intervention group by geography. Adjusting for geographic differences is more difficult.

For example:

  • In geography A (reference population), the baseline cost per member per month is $100, and intervention period cost per member per month is $110.
  • In geography B (intervention population), the baseline cost per member per month is $90 and the intervention period cost per member per month is $90.
  • What is the estimated savings due to the program?

The first estimate of savings due to the program would be derived by applying geography A Trend (110/100 = 1.10) to the geography B cost.

Thus estimated savings are:

$90 * 1.10 - $90 = $9.

However, investigation of hospital contracting in geography B shows that new hospital contracts were effective on 1/1/2001, and reimbursement increased 5% across the board. Geography A was not subject to these increases. Thus, the $90 cost per member per month in the intervention year in geography B represents an increase relative to the baseline and the Trend in geography A. This may most easily be adjusted by applying a separate cost-adjustment factor to the intervention year.

The adjusted estimated savings are:

$90 * 1.10 * 1.05 = $103.95 - $90 = $13.95

3. In many underwriting or pricing situations, age and sex are proxies for other risk factors, and are among the most frequently encountered risk factors for which actuaries make adjustments. A common (and simple) adjustment that illustrates the principle is as follows:

  • Baseline population metrics are measured over the period 1/1/2000 to 12/31/2000.
  • The intervention period begins 1/1/2001 and the first measurement period runs from 1/1/2001 to 12/31/2001.
  • The populations for comparison are selected using exactly the same criteria. However, it is found that the baseline period population has an average age of 45, while the intervention period average age is 49.
  • Baseline cost per member per month is $100, and intervention period cost per member per month is $100. What is the estimated savings due to the intervention?
  • External Trend estimate is 5%.

Initially, it would appear as though estimated savings are:

$100 * 1.05 = $105 - $95 = $10

However, the intervention period population is older than the baseline period population in terms of risk profile. (We should investigate the reason for this sudden change, but that is beyond the scope of this definition.) A simple estimate of the effect of 4 additional years of the average age of the comparison population on per member per month costs (age 49 – 45) is (1.03)4 * $100 = $ 112.60. (The observed increase in health care utilization for a year of life is approximately 3%, compounded.)

Adjusting for the effect of this difference in risk profile changes the estimated savings calculation to:

$112.60 * 1.05 = $ 118.23 - $95 = $23.23


Bluhm, W. (ed) (2003). Group insurance (4th ed.). Winsted, CT: Actex Publishers.


Acute literally means sharp. In clinical terms, an acute illness is one that has severe symptoms of rapid onset and relatively short duration. While most acute illnesses may be self-limiting or respond well to treatment, some also result in death or permanent disability. Acute conditions or disease stand in contrast to chronic illnesses, the focus of most chronic care management initiatives, which persist over long periods of time (generally years) and are frequently incurable.


Acute. (n.d.) (2004). Dorland's pocket medical dictionary (27th ed.). Philadelphia: Elsevier Sciences.

Acute. (n.d.) (2009). Mosby's medical dictionary (8th ed.). Philadelphia: Elsevier Sciences.


Adherence is one measure to describe the extent to which patients follow their care plan (or regimen) as prescribed by their health care provider. While usually used in the context of medication taking, adherence can be used to describe or measure conformance (the generic term) to the requirements of any regimen that can be characterized in terms of frequency, intensity, duration, and timing.

See also conformance to treatment and care plans, medication adherence.

Administrative Data

Administrative data refers to data collected for the primary purpose of administering health insurance benefits usually via a claim or encounter. This may include patient demographics, service dates and industry codes associated with the service rendered (e.g. diagnosis, procedure, etc.).


In recent years, due to its accessibility and conformity of codesets, administrative data has been used to identify patients for population health programs. For example, a claim for a physician's office visit indicates a diagnosis of diabetes. This patient is identified to the Care Manager as a diabetic. The Care Manager contacts the patient and educates them on the management of their condition and advises them that they need an A1C test. Subsequent claims indicate the patient had an A1C lab test and is compliant under their program.

Enhanced administrative data includes data supplemented with other medical information such as lab outcomes, health risk assessment data, biometrics data, etc. For example, the patient in the prior example with an A1C higher than 7 may be considered a higher risk.

Adverse Event (AE)

Adverse event (AE) is defined as "any untoward medical occurrence in a patient or clinical investigation subject administered a pharmaceutical product and which does not necessarily have to have a causal relationship with this treatment." Techniques to evaluate AEs can include case control studies, post-marketing surveillance programs, prescription-event monitoring, prescription-sequence analyses, etc.


Adverse clinical event is considered any undesirable experience occurring to a subject during a clinical treatment, whether or not the event is considered related to the product(s).


When an AE has been assessed and there are reasonable grounds for the suspicion that it is causally related to the drug(s), it must be considered as an adverse drug reaction (ADR). For regulatory reporting purposes, if an event is spontaneously reported, even if the relationship is unknown or unstated, it meets the definition of an ADR.


Nahler G. (2009). Dictionary of pharmaceutical medicine (2 ed.). New York, NY: Springer.


A step-by-step problem-solving procedure (i.e., recursive computational procedure) for solving a problem in a finite number of steps. Thus, an algorithm is a logical sequence of rules. In population health management, algorithms typically guide care teams in providing support to members or directing members to an alternative treatment setting or community resource.


Algorithms may express processes or workflows (sequences of processes assigned to tools or people to perform). A common expression of an algorithm is a flowchart—a series of steps and decision points linked by arrows. The first choice point is labeled, "Does the patient state they take the medication as prescribed all or nearly all of the time?" If the answer is yes, the algorithm advises continuing to some other activity (e.g., reinforcing the behavior and/or asking if the patient anticipates any problems adhering in the future). If the answer is no, the algorithm guides the user to ask several questions about nonadherence; the answers to these questions bring the user to further points in the algorithm.

American Recovery and Reinvestment Act (ARRA)

Enacted in 2009, the ARRA's purpose was to stimulate the economy by creating new jobs, spurring economic activity, investing in long-term economic growth, and fostering accountability and transparency in governmental spending. The act also expanded the Health Insurance Portability and Accountability Act (HIPAA – PL 104-191) privacy requirements and included the provisions of the Health Information Technology for Economic and Clinical Health (HITECH) Act.


American Recovery and Reinvestment Act of 2009, Pub. L. no. 111-5, 123 Stat. 115 (2009).


An association exists when the likelihood (or probability) that one event, characteristic, or other variable will occur is related to the likelihood that another event, characteristic, or other variable will occur. This signifies statistical dependence between the two variables. An association may be positive—when the value of one variable increases as the value of the second variable increases—or negative—when the value of one variable increases as the value of the second variable decreases.

It is important to note that an association does not indicate causality. Associations are also classified into two broad groups: (1) causal or asymmetrical, and (2) noncausal or symmetrical. Association is also called correlation or relationship.

An artifactual association is a false or fictitious correlation that can result from chance or be due to the presence of bias that is present in the study methods.


Abramson, J. H. (1988). Making sense of data. Oxford: Oxford University Press.

Audit Trail

Audit trail is a record showing who has accessed an information system and what operations the user has performed during a given period.


The act or process of giving someone permission to do or have something. It includes a wide range of medical uses, such as the permission by parents or guardians to provide for emergency treatment of children, approval by an insurer to a provider to provide covered treatment, or permission granted by institutional review boards to researchers to work on human subjects.


For authorship to be claimed, significant contribution to a document is required.

Average Cost

Average total cost or average unit cost is the ratio of an entity's total cost to the quantity it produces.

Average total cost = Total cost / Quantity of output


In health care, the average unit cost is often referred to as cost per member per period.
This is defined as

  Total claims cost in one year  
  Number of member months of enrolled members in one year  


Spencer, M. H. (1983). Contemporary economics (5th ed.). New York: Worth Publishers, Inc.