One of the most popular diet among women, especially housewives – Brazilian diet. The diet of Brazilian actresses quickly able to win recognition of our ladies. All the ingredients easy to buy at each store. The Brazilian diet is divided into 2 types. The first will take 2 weeks time, and the second – four. For your convenience, each Brazilian diet on days already painted.

Brazilian diet for 2 weeks

The basis of this diet are foods that contain protein – meat, fish, eggs and vegetables.

Brazilian diet menu:

Monday
Breakfast – 1 egg, 1 apple + a cup of black coffee
Lunch – 1 egg, 1 apple
Dinner – 1 egg, 1 apple

Tuesday
A similar menu Monday

Wednesday
Breakfast – 2 boiled eggs
Dinner – boiled beef (100 gr.) + Spinach
Dinner – boiled egg + spinach

Thursday
Breakfast – 1 boiled egg
Dinner – boiled sea fish (100 gr.) + Tomato
Dinner – 2 boiled eggs + cup of black coffee

Friday
Breakfast – 1 boiled egg + cup of coffee
Dinner – boiled fish + tomato
Dinner – fish, roasted without fat (100 gr.) + Salad (you can fill with vinegar)

Saturday
Breakfast – 1 boiled egg + cup of coffee
Dinner – boiled beef (100 gr.) Cucumber + cup of coffee
Dinner – 1 cup of coffee, 150-200 grams of beef

SUNDAY
Breakfast – 1 boiled egg and coffee
Lunch – chicken (100 gr.), Tomato and cucumber
Dinner – chicken (100 gr.), Tomato, cucumber, apple + coffee

Brazilian diet for 4 weeks

This option involves separate reception diet foods to 5-6 times. Basis – greens, fruit juices and vegetables.

Diet menu:
Portion of juice – glass, 200 gr.

Monday
Breakfast – banana, orange, orange juice
Lunch – toast of white bread, fresh orange juice (200 g).
Dinner – boiled sea fish (100 gr.) Salad
Before going to bed – lunch menu

Tuesday
Breakfast – 1 boiled egg (boiled), fresh apple
Lunch – fresh apple + toast
Dinner – boiled meat (100 gr.) 2 boiled potatoes
Dinner – salad (10 oz. Lean cooked meat + 1 egg + salad + green peas)
Before going to bed – lunch menu

Wednesday
Breakfast – 200 gr. skim milk + toast
Lunch – 100 grams. low fat cottage cheese
Lunch – 100 grams. rice, salad (lemon pulp + green + white cabbage)
Dinner – boiled meat (100 grams). + Apple

Thursday
Breakfast – pineapple juice, 1 / 4 pineapple
Lunch – orange juice toast +
Dinner – boiled meat (100 gr.), Cheese (30 oz.) + Orange
Dinner – 2 boiled potatoes, grated carrots (150 g). To grow. oil
Before going to sleep – toast + pineapple juice

Friday
Breakfast – mango juice, 1 / 4 pineapple
Lunch – apple and orange
Dinner – boiled fish boiled carrots and 2
Dinner – vegetable soup
Before going to sleep – mango juice + toast

Saturday
Breakfast – apple juice + toast
Lunch – salad of cooked beets
Lunch – vegetable soup with lean meat broth + a slice of bread
Dinner – cooked mushrooms (100 gr.) Salad
Before going to bed – breakfast menu

SUNDAY
Breakfast – a banana and grapes
Lunch – toast + juice of the grape
Dinner – boiled meat (100 gr.), Salad (cabbage + onions + green)
Dinner – fish or mushroom soup + fruit salad
Before going to sleep – grape juice and fresh grapes.

Medication use evaluation (also referred to as drug
use evaluation, or MUE) is a required component
of the medication use quality improvement process.
It is a performance improvement method with the goal
of optimizing patient outcomes (54). The first element
of drug use tracking is global monitoring of organizational
drug use. This can be completed by routine
evaluation of totals and changes in drug use within
a therapeutic drug category. The American Hospital
Formulary Service has created a comprehensive
therapeutic classification system that is often used for
drug use monitoring, but other commercial medication
databases are also available (55).
Figure 26.7 is an example of a global drug use report
that may be used to look for trends and variations in
medication use. This report should be examined for
changes that represent increases or decreases in comparison
to previous reporting periods. A change in any
specific category or group of drugs may be important
and worthy of specific follow up. Smaller changes that
support a trend over time can demonstrate ongoing
changes in drug use patterns. Changes seen in globallevel
monitoring may trigger a focused evaluation to
further assess the appropriateness with which certain
medications are used.
Medication use evaluation has historically been categorized
with regard to how and when data collection
or intervention occurs (Table 26.3). Most medication
use evaluations are retrospective, as exemplified by
an analysis of 8 years of emergency department prescribing
data by Catarino et al. (56). These authors
found that, despite the availability of published lists
of medications that are not generally appropriate for
geriatric patients, one or more of those inappropriate
medications were prescribed for 12.6% of elderly
patients during their emergency department visits.
Table 26.3 also describes concurrent and prospective
reviews classified based on the use and timing of intervention
as part of the process that is used for screening
and incorporation of data.

Collection and use of medication error data at the
hospital level are challenging but important functions.
A key organizational principle in quality improvement
is to make reporting errors a nonpunitive process. This
usually increases the number of errors that will be
reported, but not the number occurring. Making errors
visible is an important step in the process of finding
and fixing system-related problems (41). The ongoing
monitoring of ADE data (both medication errors and
adverse drug reactions) is an important responsibility
of the pharmacy and therapeutics committee. The committee
is the organization’s only convergence point for
all medication-related issues. This convergence allows
for a full review of the medication use process for
system adjustments.
To identify opportunities for reducing medication
errors, it is important that each error be carefully
reviewed by a limited number of individuals to gain
intimate knowledge of each reported incident. Collection
and classification of error data must be followed
by use of a careful epidemiological approach to problem
solving at the system level. Narrative data, which
may not be seen by looking at the categorical data
alone, can be used to provide important details about
proximal causes and latent error that may have contributed
to the event. Success in this type of error
reduction requires the reviewers to read between the
lines, look for common threads between reports, and
link multiple errors that are the result of system
weaknesses.
There is still work to be done in understanding errors
in the medication use process. However, available
information provides suggestions on how to reduce
medication errors. Bates’s (42) ongoing studies of
medication errors led to eight specific error prevention
strategies: (1) unit-dose medication dispensing,
(2) targeted physician education on optimal medication
use, (3) inclusion of the clinical pharmacist in
decision-making patient activities, (4) computerized
medication checking, (5) computerized order entry by
the prescriber, (6) standardized processes and equipment,
(7) automated medication dispensing systems,
and (8) bar-coded medications for dispensing and
administration. Other authors have reached similar
conclusions.
The more complex the patient’s drug therapy regimen,
the greater the likelihood that adverse medication
events will occur. Cullen et al. (43) determined
that the rate of preventable and potential adverse drug
events was twice as high in intensive care units, compared
to nonintensive care units. This was attributed
to the higher number of drugs used in the ICU.
Lesar et al. (44) reviewed medication prescribing errors
over a 9-year period and concluded that the incidence
of prescribing error increased as intensity of care
increased and new drugs became available. Koechler
et al. (45) reported that greater than five current medications,
12 or more doses per day, or medication
regimen changes four or more times in a year were
all predictors for drug therapy problems in ambulatory
patients. Transition between levels of care or
components of the healthcare system put patients at
risk for medication errors. Cornish (46) found that
53% of patients they studied had at least one medication
unintentionally not ordered during the transition
from home status to inpatient admission, but that dose
errors were also a significant problem. Gray et al.
(47) determined that the occurrence of an ADE was
positively related to the number of new medications
received at hospital discharge. The knowledge that
some patients are at higher risk for ADEs suggests possible
high-return intervention targets. When selecting
improvement opportunities, it is wise to look for those
areas most likely to yield results.
Examples of system improvements to reduce medication
errors have been reported in several projects.
Leape et al. (48) reduced medication errors in an
intensive care unit by inclusion of a pharmacist on
the clinical rounding team. Flynn et al. (49) identified
interruptions (telephone calls, conversations, etc.)
during critical phases of pharmacist drug preparation
activities as significant contributors to errors
in medication preparation. Comprehensive efforts to
prevent medication errors include the four-pronged
medication error analysis program from the Institute
for Safe Medication Practices (50). This four-pronged
approach includes evaluation of specific medication
errors, evaluation of aggregated error data and nearmiss
data for the hospital, as well as evaluation of
error reports from other hospitals. In addition, effective
medication error prevention includes ongoing
monitoring of drug therapy trends, changes in medication
use patterns, information from the hospital
quality improvement or risk management program,
and general hospital programmatic information.
Monitoring institutional trends in medication use
can provide clues to possible high-risk or error-prone
therapies. Increased use of drugs with a history of
medication errors, such as patient-controlled analgesia,
should alert organizations to develop safeguards
to protect against errors before, rather than after, they
become problems. Cohen and Kilo (36) describe a
framework for improving the use of high-alert drugs,
which is based on reducing or eliminating the possibility
of error, making errors visible, and minimizing
the consequences of errors. Table 26.2 presents change
concepts for safeguarding against errors when using
high-risk drugs.
Medication error prevention opportunities also may
present themselves in unusual hospital programmatic
information from sources not routinely applied to
medication safety. For instance, reports of laboratoryrelated
incidents or hospital information system
problems may be indicators that medication-related
problems can be expected. Thoughtful use of this
information may prevent medication-related errors
attributed to supplemental systems that are critical
to safe and appropriate medication use. Reports of
staff shortages within an institution (e.g., critical care
nurses, nurse anesthetists) can be used to identify
potential problem areas prior to medication error
reports. Likewise, reports of planned construction or
information system conversions may be an indicator
that routines will be interrupted. Thus, use of hospital
program information in a prospective way can be
used to provide safe alternatives that avoid medication
errors before they occur.
System improvements may improve the quality
of prescribing by standardizing to an expert level.
Morris (51) described the development, testing, and
use of computerized protocols for management of
intravenous fluid and hemodynamic factors in patients
with acute respiratory distress syndrome. Evans et al.
(52) used a computerized anti-infectives management
program to improve the quality of medication use and
reduce costs. In consideration of all that is currently
known, Leape (53) provided a simple set of recommendations
to reduce medical error: reduce reliance
on memory, improve access to information, errorproof
critical tasks, standardize processes, and instruct
healthcare providers on possible errors in processes.
These simple but thoughtful recommendations are an
important concept that can help to reduce medication
errors.

The rate and nature of medication errors has been
studied by several authors. Nightingale et al. found
a medication error rate of 0.7% in a British National
Health Service general hospital (25). Rothschild et al.
(26) found 36.2% preventable adverse events plus an
additional 149.7 serious errors per 1000 patient days.
Medication ordering or execution represented 61%
of the serious errors. Slips and lapses rather than
rule-based or knowledge errors were most common.
Lesar et al. (22) describe the results of a review of 2103
clinically significant medication errors in an academic
medical center. It was determined that 0.4 % of medication
orders were in error: 42% of the errors were
overdosage, and 13% were the result of drug allergies
that were not accounted for prior to prescribing.
This work showed that medication errors result most
frequently from failure to alter dose or drug after
changes in renal or hepatic status, missed allergies,
wrong drug name, wrong dosage form (e.g., IV for
IM), use of abbreviations, or incorrect calculation of a
drug dose. They concluded that an improved organizational
focus on technological risk management and
training should reduce errors and patient risk of ADEs.
Given the latent errors associated with some elements
of human performance, it seems likely that
automation may reduce error. Several studies have
demonstrated the value of computer assistance in the
medication order entry process. Rules-based physician
order systems have been shown to identify and
reduce the chances of adverse medication events due
to drug duplication, calculation errors, and drug–
drug interactions (25, 27–30). Despite these demonstrated
advantages to computer-assisted medication
ordering, the process is still far from error free. Med-
MARx data from 2003 showed that nearly 20% of the
medication errors reported to that national database
were associated with problems in computerization
and automation (31). A large number of these were
order entry errors associated with interruptions during
order entry. Another study showed that an earlygeneration
computerized prescriber order entry system
facilitated some error types due to formatting and
display limitations (32). In still another study, Nebeker
et al. (33) found that ADEs continued to occur following
the implementation of a computer prescriber
order entry system. They concluded that effective
decision support functions are required to prevent
order entry-related medication errors associated with
computerized prescribing systems.
Some therapeutic categories of medications might
be predicted to be prone to error due to narrow
therapeutic index, complexity of therapy, or other
factors. Phillips et al. (13) found that analgesics,
central nervous system agents, and nontranquilizer
psychotropic drugs were most frequently associated
with deaths due to medication errors. Lesar et al. (22)
found antimicrobials and cardiovascular drugs to be
the most error-prone therapeutic categories in an academic
medical center. Calabrese et al. (34) found
vasoactive drugs and sedative/analgesics to be most
problematic in the ICU setting. Based on these nonconverging
findings, it might be concluded that the
specific drugs of concern are unique to the institution
or practice setting, a conclusion that is partially
true. The JCAHO (35) has identified a list of drugs
and drug practices that are associated with high risk
for significant error based upon high report rates, and
the Institute for Safe Medication Practices (36) also has
identified drugs that should generate a high alert due
to risk for medication errors. Lambert and colleagues
(37, 38) have described a series of experiments that test
the likelihood of drug name confusion based on fixed
similarity patterns. This theoretical concept is providing
the basis for selecting drug names that minimize
the chance of sound-alike errors (39).
Research methods on medication error data are not
standardized. Therefore, they are subject to some limitations
in generalizability. Because widespread interest
in developing scientific approaches for reducing
medication error is relatively recent, there are few
well-established methods for conducting research in
this field. However, funding for research in safe medication
use and error reduction is available from several
public and private sources, including the Agency for
Healthcare Research and Quality.
Medication error data collection and analysis for
clinical use and quality improvement are also complex
activities. Observational data, post hoc review of
medical records, and self-reporting have all have been
used with varying degrees of success for research
and functional applications. Each offers strengths and
weaknesses, and the appropriate method for data collection
is in large part a function of its intended use
and the resources available to collect it.
Most hospitals collect internal medication error
data through a voluntary reporting mechanism. This
system is used as the backbone of error reporting
because it requires minimal resources for data collection
and is supported by organizational risk management
programs. Voluntary reporting is presumed
to underreport total errors. It is widely believed that
most significant errors are reported when they are
identified, but many mistakes are never recognized.
Many other errors are determined to be insignificant
and, therefore, not formally reported. For these reasons,
it is difficult to determine in the hospital setting
if changes in a given series of numbers represent a real
change or simply a different level of reporting.
Figure 26.6 illustrates a typical presentation of
aggregated or high-level medication error data in an
institutional setting. This presentation allows for general
trends in total numbers to be plotted and tracked
over time. Review of high-level data shows trends and
provides a framework for the first level of error analysis.
Major changes can be seen, which may trigger
more intense analysis. However, this high-level data
approach does not provide any detail to the analyst
regarding the subcomponents of the composition of
the reported errors. As a result, the pitfalls in drawing
conclusions from aggregated high-level data can
make these conclusions problematic. For instance, one
might presume that administration of medication to
the wrong patient is generally more serious than is
administration of a medication at the wrong time.
However, an increase of five “wrong patient” errors
and a decrease of five “wrong time” errors for a
specific time period will register as a zero change for
that period if only aggregated data are used. If fact, it
may represent a serious degradation in some element
of the medication system that will not be seen through
this level of error analysis.
Classification and analysis of medication error data
by error type are recommended as a method to spot
potentially important changes in system performance.
The National Coordinating Council for Medication
Error Reporting and Prevention system for classifying
medication errors may be used (6). Commercial systems
for cataloging and analyzing medication errors
are available. A potentially valuable element of some
programs is the ability to share anonymous data with
other hospitals for comparison with similar institutions
(40). Regardless of the system used to classify
and analyze medication error data, clear and consistent
classification must be made to avoid confounding
conclusions regarding underlying problems.

Reason (21) has described a model for looking at
human error that portrays a battle between the sources
of error and the system-based defenses against them.
This model is often referred to as the “Swiss cheese
model” because the defenses against error are displayed
as thin layers with holes that are described
as latent error in the system. Figure 26.5 demonstrates
the model as applied to medication error. Each
opportunity for error is defended by the prescriber,
pharmacist, nurse, and patient. When a potential error
is identified and corrected (e.g., dose error, route of
administration error) the event becomes a “near miss”
rather than an ADE. In those cases in which the holes
in the Swiss cheese line up, a preventable medication
error occurs. The Swiss cheese model provides an
interesting framework for research in this field.
The latent errors in the medication use system have
been described in several studies. Major contributors
to errors in medication use were found to be
knowledge gap related to drug therapy (30%);
knowledge gap related to patient factors (30%); errors
in dose calculations, placement of decimal points, and
dosage units (18%); and nomenclature failures, such
as wrong drug name or misinterpreted abbreviation
(13%) (22). Cohen (23) describes six common causes
of medication error based on his review of events
reported to public reporting databases. These causes
of errors include failed communication, poor drug
distribution practices (including verbal orders), dose
miscalculations, drug- and device-related problems
(such as name confusion, labeling, or poor design),
and lack of patient education on the drugs that are
prescribed for their use. Leape et al. (24) identified 13
proximal causes of medication errors in an academic
medical center.

In addition to drug selection, the pharmacy and
therapeutics committee is responsible for considering
formulary tactics to support the overall goal of optimal
medication use. Several of these tactics have been
used successfully to direct drug use toward preferred
agents. The most obvious tactic to direct use away
from a given agent is to exclude it from the formulary.
The use of nonformulary agents usually triggers
some required override, or post hoc review of use by
the committee or designated individual. A second tactic
involves a global management of medication use
by therapeutic class. This tactic can be employed to
minimize the use of drugs with a less clear profile of
therapeutic efficacy or safety. A decision to limit the
number of agents from a given drug class can also
provide some advantages in price contracting, if formulary
inclusion is effective in directing medication
use to lower cost agents.
Limiting prescribing rights for some specific drugs
to a subset of prescribers who possess special expertise
that qualifies them to use these drugs can improve
the quality of drug use. In many cases, drug restriction
is managed by one or more gatekeepers whose
approval is required prior to beginning therapy with
the drug (e.g., infectious disease approval prior to start
of a specified antibiotic). In some cases, direct financial
incentives have been used to encourage use of a given
drug or group of drugs. These formulary tactics have
been used to influence decision-making by prescribers,
pharmacists, and patients.

Effective formulary development is based upon the
scientific evaluation of drug safety, clinical effectiveness,
and cost–impact (20). That information is used
by the committee to determine the specific value and
risk of the drug for the patient population to whom
the drug will be administered. The committee evaluates
a given drug relative to the disease states typically
treated in this population. For instance, the presence
or absence of certain tropical diseases may impact on
the need to include some antimicrobial agents on the
formulary. The evaluation of a drug should include
discussion of what doses and duration of therapy
might be most appropriate in order to establish guidelines
for measuring prescribing quality. In some cases,
it may be necessary to determine which healthcare
professionals are appropriately trained or qualified
to prescribe a particular drug. The committee may
elect to restrict the use of a drug to certain specialists
(e.g., board-trained cardiologists for high-risk antiarrhythmic
agents) or the drug may be restricted by the
manufacturer or FDA to those prescribers who have
received some drug-specific training and have been
approved by the supplier (e.g., thalidomide).
Economic evaluation of medications is a routine
element of formulary development. The development
of many effective but expensive drugs, which are likely
to cost thousands of dollars for a single short course
of therapy or tens of thousands for long-term therapy,
has placed financial impact at center stage in
product selection. The availability of these high-cost
agents has created a new specialty discipline called
pharmacoeconomics. A growing list of academic medical
centers have established units that focus research
and practice efforts on outcomes measurement of drug
therapy. These programs often provide sophisticated
evaluations of the economic or quality-of-life elements
of drug use.
It is noteworthy that drug costs, and their impact,
are perceived differently from different perspectives
in the healthcare system. Each component of the
healthcare system (hospital, home care, ambulatory
provider) may have a different perspective on the
cost of therapy. Hospitals are usually responsible
for all drug-related costs (drug purchase, medication
administration, laboratory monitoring, etc.) for the
finite period of time that a patient is hospitalized.
A stand-alone outpatient drug benefit manager might
only worry about the drug cost for the nonhospitalized
portion of the therapy. The overall health system may
be at financial risk for all elements of outpatient and
inpatient care. Because each element of the system may
be responsible for a different component of the total
cost of care, the cost–impact of a given drug product
selection may be different for each element. The “societal
perspective” often represents yet another view of
drug costs in that it incorporates nonhealthcare costs
and the value of lost days of work and disability. Formulary
inclusion is not routinely based on that level
of evaluation, but public policy may be influenced by
that information.
The cost–impact analysis of two hypothetical drug
choices shown in Figure 26.4 demonstrates the role
of cost perspective in the formulary selection process.
Both regimens offer the same long-term clinical result
and adverse reaction profile. This analysis shows that
the decision as to which drug is the lower cost option
will vary with the perspective of the organization that
is responsible for the different inpatient and outpatient
components of care. This dilemma is a regular element
of the formulary selection process in many institutions.
The puzzle becomes more complex when one
is trying to decide what elements of cost (e.g., laboratory
tests or other monitoring activities) should be
included. Despite this lack of clarity, the cost–impact
of drug therapy on different stakeholders require that
this issue be considered in the decision process.
Most hospitals and healthcare organizations participate
in a purchasing group to leverage volume-driven
price advantages. The makeup and operations of these
groups vary widely, but the price agreements and
changing landscape of drug pricing add an additional
dimension to the drug price factor. A specific drug
may be the lowest price option for a given contract
period, after which the choice may change. In another
variation, a package of prices for bundled items may
cause the price for a given item to change, depending
on the use of yet another item. How this influences formulary
decisions is a function of the drug and many
other factors.

The objective of an active formulary program is
to direct medication use to preferred agents, which
offer a therapeutic or safety benefit or an economic
advantage. This serves as a quality/benefit-driven
opportunity when optimally implemented. A statement
of principles of a Sound Drug Formulary System
was developed in 2000 by a consortium composed of
the U.S. Pharmacopoeia, the Department of Veterans
Affairs, the American Society of Health-System Pharmacists,
the Academy of Managed Care Pharmacists,
and the National Business Coalition on Health (20).
In this statement, a formulary is defined as “a continually
updated list of medications and related information,
representing the clinical judgment of physicians,
pharmacists, and other experts in the diagnosis and or
treatment of disease and promotion of health.” A specific
formulary is intended for use in a defined population.
The defined population may consist of patients in
a single hospital, patients seen within a group practice,
a managed care patient population (local, regional, or
national), or even an entire community.
Historically, formulary drug inclusion or exclusion
has been used as an administrative hurdle to discourage
prescribers from using less desirable drugs.
The historical approach to formulary decision making
was based on a simple “on formulary” or “not-on
formulary” approach. Formulary drugs were available
immediately with no special requirements. Often
a formulary drug was selected by the prescriber to
avoid a prolonged waiting period for the nonformulary
item to be ordered and made available for the
patient. This approach was more effective when the
array of effective drug choices was somewhat limited,
and the principal cost and quality management need
was to reduce the number of “me-too” products.
With the advent of many of the newest generation
of products, including monoclonal antibodies and
cytokine agents, it is not logical to simply limit the
formulary availability of these novel agents. Accordingly,
the standard for most institutions has been to
include these novel drugs with committee approved
restrictions and guidelines for use. In the future,
genomics and genetic diversity, which can influence
toxicity and effectiveness, will play an important role
in formulary drug management. The ability to better
customize patient-specific drug response will require
a more sophisticated approach in selecting the most
appropriate drug.

The pharmacy and therapeutics committee is
expected to oversee important policies and procedures
associated with the use of medications. Medication
policy includes a wide range of issues, from who
may prescribe or administer drugs, to what prescribing
direction and guidance are appropriate to assure
safe and appropriate use of high-risk, high-volume,
high-cost, or problem-prone drugs. Policies are often
needed to identify who may prescribe or administer
medications, to assure consistent supply or quality of
drug products, or to allocate drugs in times of shortage.
Responsibility for developing policies to address
special circumstances or issues is often delegated to the
pharmacy and therapeutics committee by the organization.
Examples of this type of policy are special drug
class restriction, (e.g., antimicrobial agents) and use of
agents for sedation during medical procedures.

Several external organizations and internal elements
of the healthcare system have an interest in
optimizing medication use. These include the hospital
or health system, the medical staff, the group purchasing
organization with which the hospital participates
for the contractual purchase of drugs, and external
regulatory or accreditation organizations (e.g., Joint
Commission on Accreditation of Healthcare Organizations,
HealthCare Financing Agency, National Council
on Quality Assurance, state and local public health
agencies). There is interest in what drugs are used,
when and how they are used, the economic impact of
drug selection, and outcomes that result in safe and
effective use of medications.
The Joint Commission on Accreditation of Healthcare
Organizations (JCAHO) is the organization that
accredits most hospitals, health systems, and home
care agencies. A significant element of the overall
JCAHO review of patient care involves medication use
quality and medication system safety. Accreditation
standards for medication-related activities are applied
across the organization. Hospitals are expected to
present evidence that ordering, dispensing, administering,
and monitoring of medications are overseen
by the medical staff. The organization must be able to
demonstrate that policies for safe medication use practices
are in place. Quality-directed medication use is a
key performance element for accreditation. Ongoing
medication use evaluation, adverse medication event
investigation, medication use performance improvement,
and compliance with National Patient Safety
Goals are required to meet the standards. The National
Council on Quality Assurance accredits many managed
care organizations. State professional boards
(medicine, nursing, or pharmacy) provide oversight
of specialized domains such as prescribing, dispensing,
and administering medications. Most healthcare
facilities are also regulated by local or state health
departments, which often have local regulations on
medication-related issues.
It is the responsibility of the medical staff in a
healthcare organization to oversee medication use
activities, ranging from product selection to long-term
monitoring. This includes development of medication
use policies, selection of drug products that are appropriate
to the needs of the patient population being
served, and oversight of the quality of medication
use. The pharmacy and therapeutics committee is frequently
the focal point for medication-related activities
within the organization. The pharmacy and therapeutics
committee develops policies for managing
drug use and administration, manages the formulary
system, and evaluates the clinical use of drugs (19).
The exact structure of the pharmacy and therapeutics
committee may vary to meet the unique needs and
structure of the organization. It routinely reports to the
medical staff executive committee or other leadership
group within the medical staff organization. The committee
is made up of representatives from the principal
medication-using services (internal medicine, surgery,
pediatrics, etc.) within the organization, plus representatives
from the nursing services, pharmacy services,
quality improvement program, and hospital administration.
The chair of the committee is most frequently a
clinician with experience in systemwide activities and,
most important, an interest in quality use of medications.
It is customary for the director of the pharmacy
department to serve as the executive secretary for the
committee to assure a working link between pharmacy
department and committee activities.
Pharmacy and therapeutics committees usually
meet 6–12 times per year. The schedule is dependent
on the traditions of the organization and the amount
of work included during the full committee meeting.
The agenda should be prepared under the supervision
of the committee chair and distributed well in advance
of the meeting to allow all participants to read formulary
drug monographs and drug use reports before the
meeting. Ongoing elements of many committees are
special standing subcommittees or focused task force
workgroups. Typical standing subcommittees focus on
antimicrobial agents and medication use evaluation.
Standing subcommittees are appropriate for providing
ongoing special expertise on matters that can be
referred back to the full committee for action. The task
force workgroup is used to address special limitedscope
issues, such as ad hoc evaluations of agents
within a given therapeutic drug class.