Sunday, July 6, 2014

Cost Effectiveness Analysis

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Cost-effectiveness analysis (CEA) is an alternative to cost-benefit analysis (CBA). The technique compares the relative costs to the outcomes (effects) of two or more courses of action. 
CEA is most useful when analysts face constraints which prevent them from conducting cost-benefit analysis. The most common constraint is the inability of analysts to monetise benefits. CEA is commonly used in healthcare, for example, where it is difficult to put a value on outcomes, but where outcomes themselves can be counted and compared, e.g. ‘the number of lives saved’.
CEA measures costs in a common monetary value (££) and the effectiveness of an option in terms of physical units. Because the two are incommensurable, they cannot be added or subtracted to obtain a single criterion measure. One can only compute the ratio of costs to effectiveness in the following ways:
CE ratio = C1/E1
EC ratio = E1/C1
where: C1 = the cost of option 1 (in £); and E1 = the effectiveness of option 1 (in physical units).
The first equation above represents the cost per unit of effectiveness (e.g. £s spent per life saved). Projects can be rank ordered by CE ratio from lowest to highest. The most cost-effective project has the lowest CE ratio. The second equation is the effectiveness per unit of cost (e.g. lives saved per £ spent). Projects should be ranked from highest to lowest EC ratios.
The outputs to be ranked by cost-effectiveness analysis will often be social or environmental in nature. For example, work in health economics looking at the cost-effectiveness of different treatments. As with CBA, the level of detail for the analysis will typically depend on the specific issue being addressed, but should take a broad view of costs and benefits to reflect all stakeholders.
Source: (Prime Minister's Strategy Unit, 2004)

Example

In 2005 the UK Government undertook a value for money analysis of Government investment in different types of childcare. The choice was between higher cost "integrated" childcare centres, providing a range of services to both children and parents, or lower cost "non-integrated" centres that provided basic childcare facilities.
The analysis used a variant of cost-effectiveness analysis to allow the comparison of the cost-effectiveness of childcare to other policy areas such as employment, education and crime, where the evidence allowed the analysts to quantify intermediate outputs from the policy (e.g. improved educational attainment aged 18) but not the final outcomes of the policy (e.g. better overall life chances, higher skilled workforce and higher economy wide productivity growth).
Source: (Prime Minister's Strategy Unit, 2004)
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from: http://betterevaluation.org/evaluation-options/CostEffectivenessAnalysis
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Introduction to Cost-Effectiveness Analysis (CEA)

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from: http://www.herc.research.va.gov/methods/cea.asp
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Cost-Effectiveness and Cost-Benefit Analysis

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from: http://home.gwu.edu/~scellini/CelliniKee21.pdf
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Cost-Effectiveness Analysis Tool

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from: http://ec.europa.eu/europeaid/evaluation/methodology/examples/too_cef_res_en.pdf
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Generalized Cost Effectiveness Analysis

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A number of guidelines on cost-effectiveness analysis (CEA) already exist.
There are two reasons for producing another set. The first is that
traditional analysis has focused on assessing new or additional
interventions in comparison with current practice in that area. It is
difficult to use this type of “incremental” analysis to determine if the
current mix of interventions represents an efficient use of resources.
Secondly, for all but the richest countries, the cost and time required to
evaluate the large number of interventions and identify opportunities to
enhance efficiency are prohibitive. It is important to maximize the
possibility of generalizing results from one setting to another. The
approach of generalized CEA (GCEA) proposed in this Guide seeks to
provide analysts with a method of assessing whether the current mix of
interventions is efficient as well as whether a proposed new technology or
intervention is appropriate. It also seeks to maximize the generalizability
of results across settings.
The WHO Guide to Cost-Effectiveness Analysis should be considered
as complementary to existing guidelines on CEA. GCEA proposes the
evaluation of interventions against the counterfactual of “doing
nothing”, thereby providing decision-makers with information on what
could be achieved if they could start again to build the health system, i.e.
reallocate all health resources. As will be shown in the Guide, this
information is a prerequisite to the definition of an efficient mix of
interventions, achievable in the long run. This specific feature—not
addressed in traditional CEA which typically evaluates new interventions
in comparison with the current mix (intervention mix constrained CEA
or IMC-CEA)—categorizes GCEA as a different, more fundamental, type
of economic analysis. For many narrower applications of CEA, such as
the appraisal of a new version of an existing drug in a specific country,
the currently practised CEA remains an appropriate method although it
should be realized that this does not inform decision-makers on the best
use of health resources in general.i It is also possible to undertake a
traditional analysis as part of a GCEA.
The main objective of this Guide is to provide policy-makers and
researchers with a clear understanding of the concepts and benefits of
GCEA. It provides guidance on how to undertake studies using this form
of analysis and how to interpret the results. The main focus is on those
methodological issues which make GCEA different from traditional CEA,
such as the definition of the counterfactual for analysis. In addition,
attention is paid to controversial issues in CEA where choices are
required, such as the inclusion or exclusion of productivity costs.
Furthermore, the Guide provides some detailed discussions on issues
which are little debated in the literature but nevertheless important, for
example, the technical approach to the transferability of cost estimates
across settings. On all these matters, the Guide has benefited from a
meeting of experts in cost-effectiveness analysis convened by WHO in
Geneva in early 2002. In that meeting, the first version of the Guide was
presented, and this published version builds on some of the discussion in
that meeting.
Since GCEA and IMC-CEA are both embedded in the same economic
framework, they share many of the same techniques which are discussed in
detail elsewhere, such as the methods for the allocation of hospital costs. In
those instances, the reader is referred to the other literature. This Guide
proposes a standard set of methodological choices on how to perform
GCEA to enhance the comparability and generalizability of results. The
intended audience are those analysts with some background in CEA.
The Guide, in Part One, begins with a brief description of GCEA and
how it relates to the two questions raised above. It then considers issues
relating to study design, estimating costs, assessing health effects,
discounting, uncertainty and sensitivity analysis, and reporting results.
Detailed discussions of selected technical issues and applications are
provided in a series of background papers, originally published in
journals, but included in this book for easy reference in Part Two.
The first paper by Murray et al., on “Development of WHO
Guidelines in Generalized Cost-Effectiveness Analysis” formally lays out
the motivation and framework for GCEA. It highlights the use of GCEA
for improving sectoral efficiency, based on the comparative analysis of
current as well as proposed new interventions against a common
counterfactual.
The second paper, “PopMod: A longitudinal population model with
two interacting disease states”, is a detailed technical description of the
multi-state dynamic life table that calculates the health and mortality
experience of a population with two interacting conditions or disease
states, as well as other causes of mortality and morbidity. It was
developed by WHO in a spreadsheet format, and subsequent
collaboration with a scientific consultancy group and Statistics Canada
allowed the model to be transferred into various programming
environments including a microsimulation version.
The next two papers, “Programme costs in the economic evaluation of
health interventions” and “Econometric estimation of country-specific
hospital costs”, describe how cost estimates can be derived for different
subregions. The programme cost paper describes how one category of
costs, those which represent resources consumed at all levels aside from

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from : http://www.who.int/choice/publications/p_2003_generalised_cea.pdf
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Tuesday, December 14, 2010

Cost-Effectiveness Analysis

Cost-Effectiveness Analysis

http://docs.google.com/viewer?a=v&pid=explorer&chrome=true&srcid=1gJnVFbQ7w3ta1Z5AQ_PyODt4qhwcFAr81UW3VTcNVPsFhfeNndVEfDFWAVzv&hl=en

Human health improved dramatically during the last century, yet
grave inequities in health persist. To make further progress in health,
meet new challenges, and redress inequities, resources must be deployed
effectively. This requires knowledge about which interventions actually
work, information about how much they cost, and experience with their
implementation and delivery (DCP2, chapters 14 and 15).

WHY USE COST-EFFECTIVENESS ANALYSIS?

The 1993 edition of Disease Control Priorities in Developing Countries
(Jamison and others 1993) was among the first efforts to guide choices
about public health policies in developing countries by systematically
combining information about effective interventions with information
about their costs. It was motivated, in part, by a sense that developing
countries were neglecting numerous opportunities for improving
health and that better allocation of scarce resources could achieve
better health outcomes. The publication presented cost-effectiveness
analysis as an important tool for identifying these neglected opportu-
nities and redirecting resources to better use.

Cost-effectiveness analysis helps identify neglected opportunities by
highlighting interventions that are relatively inexpensive, yet have the
potential to reduce the disease burden substantially. For example, each
year more than a million young children die from dehydration when they
become ill with diarrhea. Oral rehydration therapy (ORT) does not
diminish the incidence of diarrhea, but dramatically reduces its severity
and the associated mortality rate. The scientific evidence that ORT can
save lives was an important step in identifying this as a neglected
opportunity for improving health. Demonstrating that it could cost only
US$2 to US$4 per life year saved helped make the case that this was some-
thing public policy should promote, and many countries responded by
promoting ORT, saving millions of lives (DCP2, chapters 8 and 19).
Cost-effectiveness analysis helps identify ways to redirect resources
to achieve more. It demonstrates not only the utility of allocating
resources from ineffective to effective interventions, but also the utility
of allocating resources from less to more cost-effective interventions.
For example, a study by the National Center for Policy Analysis at
Harvard University focused on 185 life-saving interventions that take
place in the United States each year, costing US$21.4 billion and saving
592,000 life years. The study investigated different ways of allocating
these funds and found that the number of life years saved could be
doubled if resources were reallocated to more cost-effective interven-
tions (DCP2, chapter 2, box 3).

DCP2 tells a similar story. It identifies dozens of interventions for a
wide range of diseases and risk factors that are costly relative to the
health gain they provide. These include hospital-based interventions,
such as surgery for recurrent stroke, and community-based interven-
tions for schizophrenia and bipolar disorder. Other interventions that
are not particularly cost-effective include treating latent TB infections
with isoniazid and regulations aimed at reducing alcohol abuse. If a
country were to reallocate funds and efforts from these kinds of inter-
ventions and instead apply them to relatively more cost-effective inter-
ventions, substantially more people would be able to live longer and
healthier lives. If reallocating funds from less cost-effective interventions
is not feasible or appropriate, perhaps future increases in spending can
be directed toward activities that will yield more health gains.
Studies of cost-effectiveness have multiplied since 1993, and the
techniques have become more widely disseminated.

DCP2 has bene-
fited from this expanding literature and has aimed for consistent com-
parisons across diseases and interventions. For example, wherever pos-
sible, the cost-effectiveness analyses in DCP2 have used the same price
units, health indicators, and definitions of included costs (box 3.1).
This chapter introduces the basic concepts and methods of cost-
effectiveness analysis, considers some of its limitations, and explains
how it has been and can be put to use. The chapter also considers some
of the other contextual factors that must complement cost-effectiveness
analysis in the decision-making process if policy makers are to make
the best use of the findings provided in DCP2.

Cost-effectiveness Interventions in Ethiopia Analysis of Health Care Meskanena Mareko Wereda

http://docs.google.com/viewer?a=v&pid=explorer&chrome=true&srcid=1Gadx799PNDbfMZjz45AchcLF0YBeR4OwMYzRMjjY6hTpmMl-JBEkAaIE99LD&hl=en

Abstract
Background: Decisions concerning the implementation of health programs are usually made on the basis of descriptive assessment. There are only few attempts to review whether returns from investment on these programs worth the effort.

Objectives: To analyze and evaluate the cost-effectiveness of health care interventions in terms of lessening disease burden and improving health status in a rural community.

Methods: The evaluation was conducted in health institutions in Meskana Mareko Wereda and in Shashemene Hospital that were purposively selected. Study subjects were people utilizing these facilities. Data on inputs of interventions were analyzed using the Disease Burden Modeling System and Disability Adjusted Life Years (DALYs) gained was used as a measure of effectiveness of interventions.

Results: Interventions at health stations level were most cost-effective compared to those at health center and the hospital. Generally, community and preventive interventions were found to be more cost-effective in lessening existing burden of disease (BOD) in the local community and in improving the general health status of the populations with cost of less than 5 Birr per DALY gained.

Conclusions: Implementing 22 health care interventions with cost of less than 100 Birr per DALY gained at the health stations level will avert 52% of the BOD in the area. On the other hand implementing 17 interventions at the hospital and 18 interventions at the health center level will avert only about 22 to 34% of the BOD. Given the availability of information pertaining to the local BOD and cost-effective intervention options, there appears to be a dire need to review local health priorities and intervention strategies. [Ethiop.J.Health Dev. 2002;16(3):267-276]

Understanding Cost-Effectiveness Analysis in Health Care

Description
The primary objective of this content is to prepare students to read and interpret cost-effectiveness studies. The students will first be introduced to basic economic concepts that are needed in order to understand the recommendations from the United States Panel on Cost Effectiveness in Health and Medicine. One example is the distinction between opportunity costs and budgetary costs. The recommendations will then be reviewed, particularly as they apply to what students should expect to read in cost-effectiveness research reports. Next, the relationship between cost-effectiveness results and other elements of the health care policy decision-making process will be discussed. More information will be provided on several aspects of how to conduct cost-effectiveness analyses. A critical discussion of several current articles demonstrating cost-effectiveness analyses will be an integral part of this course. When a student has completed this course, he or she will be able to read, comprehend, and perform a basic critique of cost-effectiveness papers and take part in discussions of planned cost-effectiveness research.

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Breast cancer screening

Breast cancer screening

From Wikipedia, the free encyclopedia
http://en.wikipedia.org/wiki/Breast_cancer_screening (2010-12-13)

Breast cancer screening refers to testing otherwise-healthy women for breast cancer in an attempt to achieve an earlier diagnosis. The assumption is that early detection will improve outcomes. A number of screening test have been employed including: clinical and self breast exams, mammography, genetic screening, ultrasound, and magnetic resonance imaging.

A clinical or self breast exam involves feeling the breast for lumps or other abnormalities. Evidence however does not support its use.[1] Mammographic screening for breast cancer is also controversial. The Cochrane collaboration in 2009 concluded that it is unclear whether screening does more good than harm.[2] Many national organizations still however recommend it. If mammography is decided up it should only be done every two years in women between the ages of 50 and 74.[3] Several tools are available to help target breast cancer screening to older women with longer life expectancies.[4]

Abnormal findings on screening are further investigated by surgically removing a piece of the suspicious lumps (biopsy) to examine them under the microscope. Ultrasound may be used to guide the biopsy needle during the procedure. Magnetic resonance imaging is used to guide treatment, but is not an established screening method for healthy women.

Women with a family history of breast and ovarian cancer have a higher risk of mutations of the BRCA1 and BRCA2 genes. These mutations result in a higher risk of breast cancer. Testing for these genes is expensive and not done routinely. However those with this mutation should be screened more aggressively: starting at an earlier age, with greater frequency, and possibly with magnetic resonance imaging.

Contents
1 Breast exam
2 Mammography
2.1 Enhancements
2.2 Health programs
2.3 Criticisms
3 Ultrasonography
4 Breast MRI
5 BRCA testing
6 References
7 External links

Breast exam
See also: Breast self-examination

An pictorial example of breast self-examination in six steps. Steps 1-3 involve inspection of the breast with the arms hanging next to the body, behind the head and in the side. Step 4 is palpation of the breast. Step 5 is palpation of the nipple. Step 6 is palpation of the breast while lying down.Breast examination ( either clinical breast exams (CBE) by a health care provider or by self exams ) were once widely recommended. They however are not supported by evidence and may contribute to harm. Their use in women without symptoms and at low risk is thus controversial.[5]

A 2003 Cochrane review found no benefit in terms of mortality from screening by breast self-examination or by clinical exam, but rather that they do possible harm in terms of increased numbers of benign lesions identified and an increased number of biopsies performed. They conclude "screening by breast self-examination or physical examination cannot be recommended." [1]

Mammography
Main article: Mammography

Normal (left) versus cancerous (right) mammography image.Mammography is a common screening method, since it is relatively fast and widely available in developed countries. When detected by mammography breast cancers are usually smaller (in an earlier stage) than those detected by patients or doctors as a breast lump, and presumably treatment in an earlier stage will improve outcome. This assertion however has been challenged by recent reviews which have found the significance of these benefits to be questionable.

A 2009 Cochrane review estimated that mammography in women between 50 and 75 years old results in a relative risk reduction of death from breast cancer of 15% or an absolute risk reduction of 0.05%. Those who have mammograms however end up with increased surgeries, chemotherapy, radiotherapy and other potentially procedures resulting from the over-detection of harmless lumps. The authors also note that many women will experience important psychological distress for many months because of false positive findings.[2] Consequently, the value of routine mammography in women at low or average risk is controversial.[2] With unnecessary treatment of ten women for every one woman whose live was prolonged, the authors concluded that routine mammography may do more harm than good.[2].

A 2009 U.S. Preventive Services Task Force analysis come to similar conclusions: for women in their 40s 2000 would need to be screened for 10 years, resulting in 1000 people with false results and 250 unnecessary biopsies to prevent 1 breast cancer death, for women in their 50s 1339 would need to be screened for 10 years to prevent a single breast cancer related death, and for women in their 60s 377 women would need to be screened for 10 years.[6]

An analysis of Norwegians published in 2010 found a 10% reduction in breast cancer mortality (2.4 deaths per 100,000 person-years) attributable to screening but this difference was non significant.[7]

For places that recommend screening the age at which this should begin and how frequently women differ around the world. In the UK, all women are invited for screening once every three years beginning at age 50. As of 2009 the US Preventive Services Task Force recommends that women over the age of 50 receive mammography once every two years.[8]

Women at higher risk may benefit from earlier or more frequent screening. Women with one or more first-degree relatives (mother, sister, daughter) with premenopausal breast cancer often begin screening at an earlier age, perhaps at an age 10 years younger than the age when the relative was diagnosed with breast cancer.

Mammography is not generally considered as an effective screening technique for women less than 50 years old. A systematic review by the American College of Physicians concluded that, for women 40 to 49 years of age, the risks of mammography outweighed the benefits,[9] and the US Preventive Services Task Force says that the evidence in favor of routine screening of women under the age of 50 is "weak".[8] Part of the difficulty in interpreting mammograms in younger women stems from breast density. Radiographically, a dense breast has a preponderance of glandular tissue, and younger age or estrogen hormone replacement therapy contribute to mammographic breast density. After menopause, the breast glandular tissue gradually is replaced by fatty tissue, making mammographic interpretation much more accurate. Some authors speculate that part of the contribution of estrogen Hormone replacement therapy to breast cancer mortality arises from the issue of increased mammographic breast density.

Enhancements
In general, digital mammography and computer-aided mammography have increased the sensitivity of mammograms, but this may come at the cost of more numerous false positive results.[citation needed].

Computer-aided diagnosis(CAD) Systems may help radiologists to evaluate X-ray images to detect breast cancer in an early stage.[citation needed] CAD is especially established in US and the Netherlands. It is used in addition to the human evaluation of the diagnostician.

Health programs
In 2005, 67.9% of all U.S. women age 40–64 had a mammogram in the past two years (74.5% of women with private health insurance, 56.1% of women with Medicaid insurance, 38.1% of currently uninsured women, and 32.9% of women uninsured for > 12 months).[10] All U.S. states (except Utah) mandate that private health insurance plans and Medicaid provide some coverage for breast cancer screening.[11] Section 4101 of the Balanced Budget Act of 1997 required that Medicare (available to those aged 65 or older or who have been on Social Security Disability Insurance for over 2 years), effective January 1, 1998, cover and waive the Part B deductible for annual screening mammography in women aged 40 or older.

All organized breast cancer screening programs in Canada offer clinical breast examinations for women aged 40 and over and screening mammography every two years for women aged 50–69.[12] In 2003, about 61% of women aged 50–69 in Canada reported having had a mammogram within the past two years.[13]

The NHS Breast Screening Programme, the first of its kind in the world, began in 1988 and achieved national coverage in the mid-1990s, provides free breast cancer screening mammography every three years for all women in the UK aged 50 and over.[14] As of March 31, 2006, 75.9% of women aged 53–64 resident in England had been screened at least once in the previous three years.[15]

The Australian national breast screening program, BreastScreen Australia, was commenced in the early 1990s and invites women aged 50–69 to screening every 2 years. No routine clinical examination is performed, and the cost of screening is free to the point of diagnosis.

The Singapore national breast screening program, BreastScreen Singapore, is the only publicly funded national breast screening program in Asia, and enrols women aged 50–64 for screening every two years. Like the Australian system, no clinical examination is performed routinely. Unlike most national screening systems however, clients have to pay half of the cost of the screening mammogram; this is in line with the Singapore health system's core principle of co-payment for all health services.

Criticisms
Some scientific groups however have expressed concern about the public's perceptions of the benefits of breast screening.[16]

Data reported in the UK Million Woman Study indicates that if 134 mammograms are performed, 20 women will be called back for suspicious findings, and four biopsies will be necessary, to diagnose one cancer. Recall rates are higher in the U.S. than in the UK.[17] The contribution of mammography to the early diagnosis of cancer is controversial, and for those found with benign lesions, mammography can create a high psychological and financial cost. For those diagnosed with cancer, mammography can be the difference between a lumpectomy versus metastatic disease.

Screening leads to false positive results and subsequent invasive procedures.[18]

Nevertheless, surveys have shown that most women participating in mammography screening programs accept the risk of false positive recall and the majority do not find this highly distressing. The majority of women recalled will undergo additional imaging only, without any further intervention. There is some debate over how harmful such noninvasive recall assessment truly is.

A major effect of routine breast screening is to greatly increase the rate of early breast cancer detection, in particular for preinvasive ductal carcinoma in situ (DCIS), which is almost always impalpable and which cannot, for the most part, be detected reliably by any other test. While this ability to detect such very early breast malignancies is at the heart of claims that screening mammography can improve survival from breast cancer, it is also controversial. This is because a large percentage of such cases will almost certainly not progress to kill the patient, and thus mammography cannot be genuinely claimed to have been beneficial in such cases; in fact, it would lead to increased morbidity and unnecessary surgery for such patients.

It has thus been claimed that finding and treating many cases of DCIS represents "overdiagnosis" and "overtreatment". However, it is not possible to accurately predict which patients with DCIS will have an indolent nonfatal course, and which will inevitably progress to invasive cancer and death if left untreated. Consequently, all patients with DCIS are treated in much the same way, with at least wide local excision, and sometimes mastectomy if the DCIS is very extensive. The cure rate for DCIS if treated appropriately is extremely high. Thus, it can be argued that some women with DCIS detected by screening mammography do in fact benefit from screening, even if others do not. Any refinement of this therapeutic approach to breast malignancy requires further research and the development of methods that accurately predict the future cellular fate and biological behaviour of early cancers.

It is salient to note that the phenomenon of finding preinvasive malignancy or nonmalignant benign disease is commonplace in all forms of cancer screening, including pap smears for cervical cancer, fecal occult blood testing for colon cancer, and prostate-specific antigen testing for prostate cancer. All of these tests have the potential to detect very early malignancy before it becomes symptomatic, and to potentially lead to long term cure. All of them have false positives, and can lead to invasive procedures that may not benefit the patient.

Given current limitations in knowledge and technology, the only way to avoid "overdiagnosis" and "overtreatment", and to eliminate all harms inherent in breast cancer screening is not to screen at all, and thus to eliminate any benefit to at least some of the screened population that screening entails. In the case of breast cancer, cessation of screening would lead to an increase in the size and stage of breast cancers at diagnosis, since most cancers would only be detected when they become symptomatic.

Ultrasonography
Medical ultrasonography (Ultrasound) is a diagnostic aid to mammography.

Breast MRI
Magnetic resonance imaging (MRI) has been shown to detect cancers not visible on mammograms. The chief strength of breast MRI is its very high negative predictive value. A negative MRI can rule out the presence of cancer to a high degree of certainty, making it an excellent tool for screening in patients at high genetic risk or radiographically dense breasts, and for pre-treatment staging where the extent of disease is difficult to determine on mammography and ultrasound. MRI can diagnose benign proliferative change, fibroadenomas, and other common benign findings at a glance, often eliminating the need for costly and unnecessary biopsies or surgical procedures. The spatial and temporal resolution of breast MRI has increased markedly in recent years, making it possible to detect or rule out the presence of small in situ cancers, including ductal carcinoma in situ.

However, breast MRI has long been regarded to have disadvantages. For example, although it is 27–36% more sensitive, it has been claimed to be less specific than mammography.[19]. As a result, MRI studies may have more false positives (up to 30%), which may have undesirable financial and psychological costs. It is also a relatively expensive procedure, and one which requires the intravenous injection of gadolinium, which has been implicated in a rare reaction called nephrogenic systemic fibrosis. Although NSF is extremely uncommon, patients with a history of renal disease may not be able to undergo breast MRI. Further, an MRI may not be used for screening patients with a pacemaker or breast reconstruction patients with a tissue expander due to the presence of metal.

Proposed indications for using MRI for screening include:[20]

Strong family history of breast cancer
Patients with BRCA-1 or BRCA-2 oncogene mutations
Evaluation of women with breast implants
History of previous lumpectomy or breast biopsy surgeries
Axillary metastasis with an unknown primary tumor
Very dense or scarred breast tissue
In addition, breast MRI may be helpful for screening in women who have had breast augmentation procedures involving intramammary injections of various foreign substances that may mask the appearances of breast cancer on mammography and/or ultrasound. These substances include:

Silicone oil
Polyacrylamide gel
Two studies published in 2007 demonstrated the strengths of MRI-based screening:

In March 2007, an article published in the New England Journal of Medicine demonstrated that in 3.1% of patients with breast cancer, whose contralateral breast was clinically and mammographically tumor-free, MRI could detect breast cancer. Sensitivity for detection of breast cancer in this study was 91%, specificity 88%.[21]
In August 2007, an article published in The Lancet compared MRI breast cancer screening to conventional mammographic screening in 7,319 women. MRI screening was highly more sensitive (97% in the MRI group vs. 56% in the mammography group) in recognizing early high-grade Ductal Carcinoma in situ (DCIS), the most important precursor of invasive carcinoma. Despite the high sensitivity, MRI screening had a positive predictive value of 52%, which is totally accepted for cancer screening tests.[22] The author of a comment published in the same issue of The Lancet concludes that "MRI outperforms mammography in tumour detection and diagnosis."[23]
Based on this evidence, and the lack of effective alternative methods for screening in young women of very high genetic risk (either an extremely strong first degree family history or proven BRCA1 or BRCA2 oncogene mutation carrier status) for breast cancer, the Australian federal government decided to routinely reimburse annual breast MRI scans for such women under the age of 50 from January 2009 onwards.

BRCA testing
A clinical practice guideline by the US Preventive Services Task Force :[24]

"recommends against routine referral for genetic counseling or routine breast cancer susceptibility gene (BRCA) testing for women whose family history is not associated with an increased risk for deleterious mutations in breast cancer susceptibility gene 1 (BRCA1) or breast cancer susceptibility gene 2 (BRCA2)" The Task Force gave a grade D recommendation.[25][verification needed]
"recommends that women whose family history is associated with an increased risk for deleterious mutations in BRCA1 or BRCA2 genes be referred for genetic counseling and evaluation for BRCA testing." The Task Force gave a grade B recommendation.[25][verification needed]
The Task Force noted that about 2% of women have family histories that indicate increased risk as defined by:

For non–Ashkenazi Jewish women, any of the following:
"2 first-degree relatives with breast cancer, 1 of whom received the diagnosis at age 50 years or younger"
"3 or more first- or second-degree relatives with breast cancer regardless of age at diagnosis"
"both breast and ovarian cancer among first- and second- degree relatives"
"a first-degree relative with bilateral breast cancer"
"a combination of 2 or more first- or second-degree relatives with ovarian cancer regardless of age at diagnosis"
"a first- or second-degree relative with both breast and ovarian cancer at any age"
"a history of breast cancer in a male relative."
"For women of Ashkenazi Jewish heritage, an increased-risk family history includes any first-degree relative (or 2 second-degree relatives on the same side of the family) with breast or ovarian cancer."
References
Gilberto Schwartsmann (2001) "Breast Cancer in South America: Challenges to improve early detection and medical management of a public health problem." J Clin Oncol 19 118-124
1.^ a b Kösters JP, Gøtzsche PC (2003). "Regular self-examination or clinical examination for early detection of breast cancer". Cochrane Database Syst Rev (2): CD003373. doi:10.1002/14651858.CD003373. PMID 12804462.
2.^ a b c d Gøtzsche PC, Nielsen M (2009). "Screening for breast cancer with mammography". Cochrane Database Syst Rev (4): CD001877. doi:10.1002/14651858.CD001877.pub3. PMID 19821284.
3.^ "Breast Cancer: Screening". United States Preventive Services Task Force. http://www.ahrq.gov/clinic/USpstf/uspsbrca.htm.
4.^ Schonberg M. Breast cancer screening: at what age to stop? Consultant. 2010;50(May):196-205.
5.^ Saslow D, Hannan J, Osuch J, et al. (2004). "Clinical breast examination: practical recommendations for optimizing performance and reporting". CA Cancer J Clin 54 (6): 327–44. doi:10.3322/canjclin.54.6.327. PMID 15537576.
6.^ Nelson HD, Tyne K, Naik A, Bougatsos C, Chan BK, Humphrey L (November 2009). "Screening for breast cancer: an update for the U.S. Preventive Services Task Force". Ann. Intern. Med. 151 (10): 727–37, W237–42. doi:10.1059/0003-4819-151-10-200911170-00009. PMID 19920273.
7.^ Kalager M, Zelen M, Langmark F, Adami HO (September 2010). "Effect of screening mammography on breast-cancer mortality in Norway". N. Engl. J. Med. 363 (13): 1203–10. doi:10.1056/NEJMoa1000727. PMID 20860502.
8.^ a b US Preventive Services Task Force (November 2009). "Screening for breast cancer: U.S. Preventive Services Task Force recommendation statement". Ann. Intern. Med. 151 (10): 716–26, W–236. doi:10.1059/0003-4819-151-10-200911170-00008. PMID 19920272.
9.^ Armstrong K, Moye E, Williams S, Berlin JA, Reynolds EE (2007). "Screening mammography in women 40 to 49 years of age: a systematic review for the American College of Physicians". Ann. Intern. Med. 146 (7): 516–26. PMID 17404354.
10.^ Ward E, Halpern M, Schrag N, Cokkinides V, DeSantis C, Bandi P, Siegel R, Stewart A, Jemal A (Jan-February 2008). "Association of insurance with cancer care utilization and outcomes". CA Cancer J Clin 58 (1): 9. doi:10.3322/CA.2007.0011. PMID 18096863. http://caonline.amcancersoc.org/cgi/content/full/CA.2007.0011v1.
11.^ Kaiser Family Foundation (December 31, 2006). "State Mandated Benefits: Cancer Screening for Women, 2006". http://www.statehealthfactsonline.org/comparemaptable.jsp?ind=488&cat=10&yr=17&typ=5.
12.^ Canadian Cancer Society (August 10, 2007). "Breast cancer screening in your 40s". http://www.cancer.ca/ccs/internet/standard/0,3182,3172_573785695_2026817819_langId-en,00.html.
13.^ Canadian Cancer Society (April 2006). "Canadian Cancer Statistics, 2006" (PDF). http://www.cancer.ca/vgn/images/portal/cit_86751114/31/21/935505792cw_2006stats_en.pdf.pdf.
14.^ NHS Cancer Screening Programmes (2007). "NHS Breast Screening Programme". http://cancerscreening.org.uk/breastscreen/.
15.^ The Information Centre (NHS) (March 23, 2007). "Breast Screening Programme 2005/06". http://www.ic.nhs.uk/statistics-and-data-collections/screening/breast-cancer/breast-screening-programme-2005-06-%5Bns%5D?.
16.^ "Women 'misjudge screening benefits'". BBC. 15 October 2001. http://news.bbc.co.uk/1/hi/health/1601267.stm. Retrieved 2007-04-04.
17.^ Smith-Bindman R, Ballard-Barbash R, Miglioretti DL, Patnick J, Kerlikowske K (2005). "Comparing the performance of mammography screening in the USA and the UK". Journal of medical screening 12 (1): 50–4. doi:10.1258/0969141053279130. PMID 15814020.
18.^ Croswell JM, Kramer BS, Kreimer AR, et al. (2009). "Cumulative incidence of false-positive results in repeated, multimodal cancer screening". Ann Fam Med 7 (3): 212–22. doi:10.1370/afm.942. PMID 19433838.
19.^ Hrung J, Sonnad S, Schwartz J, Langlotz C (1999). "Accuracy of MR imaging in the work-up of suspicious breast lesions: a diagnostic meta-analysis.". Acad Radiol 6 (7): 387–97. doi:10.1016/S1076-6332(99)80189-5. PMID 10410164.
20.^ Morrow M (2004). "Magnetic resonance imaging in breast cancer: one step forward, two steps back?". JAMA 292 (22): 2779–80. doi:10.1001/jama.292.22.2779. PMID 15585740.
21.^ Lehman CD, Gatsonis C, Kuhl CK, Hendrick RE, Pisano ED, Hanna L, Peacock S, Smazal SF, Maki DD, Julian TB, DePeri ER, Bluemke DA, Schnall MD (2007). "MRI evaluation of the contralateral breast in women with recently diagnosed breast cancer.". N Engl J Med. 356 (13): 1295–1303. doi:10.1056/NEJMoa065447. PMID 17392300.
22.^ Kuhl CK, Schrading S, Bieling HB, Wardelmann E, Leutner CC, Koenig R, Kuhn W, Schild HH (2007). "MRI for diagnosis of pure ductal carcinoma in situ: a prospective observational study". The Lancet 370 (9586): 485–492. doi:10.1016/S0140-6736(07)61232-X.
23.^ Boetes C, Mann RM (2007). "Ductal carcinoma in situ and breast MRI". The Lancet 370 (9586): 459–460. doi:10.1016/S0140-6736(07)61207-0.
24.^ U.S. Preventive Services Task Force (2002). "Screening for breast cancer: recommendations and rationale". Ann. Intern. Med. 137 (5 Part 1): 344–6. PMID 12204019. http://www.annals.org/cgi/content/full/137/5_Part_1/344.
25.^ a b "Guide to Clinical Preventive Services, Third Edition: Periodic Updates, 2000-2003". Agency for Healthcare Research and Quality. US Preventive Services Task Force. http://www.ahrq.gov/clinic/3rduspstf/ratings.htm. Retrieved 2007-10-07.

A cost effectiveness study of integrated care in health services delivery: a diabetes program in Australia

A cost effectiveness study of integrated care in health services delivery: a diabetes program in Australia

http://docs.google.com/viewer?a=v&pid=explorer&chrome=true&srcid=1wDZFkfGx2T8bQgKXRyt7Zou_8RgR4XB8z0Vm2eV3f0YR4Tn3V6JIV768IneP&hl=en

Saturday, April 11, 2009

Having Healthy Babies




Having Healthy Babies 
Publisher: New York Avenue | ISBN: 0871686946 | edition 2003 | PDF | 77 pages | 1,90 mb

This booklet summarizes what health professionals know about healthy babies and mothers. It shows women how to avoid or reduce the health risks of pregnancy, provides information about the development of healthy infants and toddlers, and outlines the steps of pregnancy from conception to labor and delivery to postnatal care. Having Healthy Babies directs readers to more sources of information and to the latest scientific research

Primary Care Medicine: Office Evaluation and Management of the Adult Patient




Primary Care Medicine: Office Evaluation and Management of the Adult Patient 
Lippincott Williams & Wilkins; 5 edition | 078177456X | 1328 pages | December 1, 2006 | CHM | 14 Mb

This revised reprint of Primary Care Medicine, Fifth Edition gives you a complete print and online package: the book plus access to a Website offering the fully searchable text, monthly text updates, and patient and physician advisories. In 239 problem-oriented chapters, this Fifth Edition provides essential information on medical diagnosis, lab tests, treatment options, and health maintenance and offers authoritative guidance on decision-making in primary care medicine. Every chapter was revised to include more images, tables, and bulleted lists. Practical recommendations that incorporate the best available evidence, expert consensus guidelines, and clinical judgement are listed in bulleted items at the end of every chapter. 

Wednesday, November 12, 2008

Free Preview Interpreting Epidemiologic Evidence: Strategies for Study Design and Analysis

Evaluating the strength or persuasiveness of epidemiologic evidence is inherently challenging, both for those new to the field and for experienced researchers. There are a myriad of potential biases to consider, but little guidance about how to asses the likely impact on study results. This book offers a strategy for assessing epidemiologic research findings, explicitly describing the goals and products of epidemiologic research in order to better evaluate it successes and limitations. The focus throughout is on practical tools for making optimal use of available data to assess whether hypothesized biases are operative and to anticipate concerns at the point of study design in order to ensure that needed information is generated. Specific tools for assessing the presence and impact of selection bias in both cohort and case-control studies, bias from non-response, confounding, exposure measurement error, disease measurement error, and random error are identified and evaluated. The potential value of each approach as well as its limitations are discussed, using examples from the published literature. Such information should help those who generate and interpret epidemiologic research to apply methodological principles more effectively to substantive issues, leading to a more accurate appraisal of the current evidence and greater clarity about research needs.

More details

Interpreting Epidemiologic Evidence: Strategies for Study Design and Analysis
By David A. Savitz
Published by Oxford University Press US, 2003
ISBN 019510840X, 9780195108408
321 pages

Interpreting Epidemiologic Evidence: Strategies for Study Design and Analysis (Hardcover)




Interpreting Epidemiologic Evidence: Strategies for Study Design and Analysis (Hardcover)
by David A. Savitz (Author) "This book was written for both producers and consumers of epidemiologic research, though a basic understanding of epidemiologic principles will be necessary at the outset..." (more)
Key Phrases: New York, Oxford University Press, United States (more...)

Interpreting Epidemiologic Evidence: Strategies for Study Design and Analysis. David A Savitz.

Book Review

Interpreting Epidemiologic Evidence: Strategies for Study Design and Analysis. David A Savitz. Oxford: Oxford University Press, 2003, pp. 336, £34.50 (HB). ISBN: 0-19-510840-X.

Isobel Bray
My first impressions of this book were that while the topic seemed important, the text was perhaps too wordy to be easily accessible. By the end, however, I was convinced that this is a book every epidemiologist should read, or at least use as a reference text when designing and analysing studies. My initial judgement that it would be heavy-going for a new student of epidemiology remains unchanged, but the author states from the outset that this was not intended to be yet another standard text on epidemiology. Rather, the aim is to offer a comprehensive strategy for assessing the results of epidemiological studies.

The book focuses on the potential sources of bias in any study. For example, what are the most likely magnitude and direction of bias due to non-response, confounding, measurement error in the exposure variable, and misclassification of the outcome of interest? This text provides the knowledge and tools necessary to answer these questions, and many more, so that a researcher can make the most of limited resources when planning a study and learn as much as possible from existing data. The author draws heavily on the published literature (particularly in the fields of environmental and occupational epidemiology) to illustrate each point, which makes the text much easier to understand and digest. There are also plenty of methodological references for those wishing to study the issues raised in more detail.

The 12 chapters are quite long, but they are broken down into clearly labelled sections listed in the Contents. This, and the detailed index, should ensure that researchers find the sections of most interest to them quite quickly. Also, each of the central chapters (4–11) ends with a summary of the proposed strategies, referred to as an integrated assessment. To those who have the time, however, I would recommend reading the book cover to cover as the chapters form a logical sequence and cover a range of important issues barely touched on in most taught courses in epidemiology.

The Introduction provides a clear justification for the book and introduces the major themes of bias and confounding. The key message is that just because we cannot quantify these potential problems in our study, we should not fail to attempt to assess their impact. Chapter 2 (The Nature of Epidemiologic Evidence) begins by elucidating the differences between public health and epidemiology. Though this chapter is not a clear introduc-tion to epidemiology for a novice, it makes many important points (e.g. evidence of no association between two variables is equally valid as evidence for a positive association). Chapter 3 (Strategies for Drawing Inferences from Epidemiologic Evidence) sets out the goal of making evaluation of epidemiological evidence more objective. To this end, we should concentrate on the most likely sources of error rather than those that are easiest to measure. There follow substantial chapters on each of the following major themes—selection bias in both cohort and case-control studies, bias due to loss of study participants, confounding, measurement and classification of both exposure and disease, and random error. Chapter 11 (Integration of Evidence Across Studies) introduces the concepts of comparative analysis, meta-regression and narrative review. The final chapter discusses issues such as how epidemiologists should present their results to those who are interested (e.g. policy makers) but may not have the time or inclination to consider the complex assessments of bias described in this book, and how we should interpret conflicting evidence. It also revisits Hill's criteria for causality,1 setting them in a wider context which involves scrutinizing possible sources of error for all studies conducted, not just those which provide evidence of an association.

In conclusion, this book raises many important points that, currently, are largely overlooked in the interpretation of epidemiological data. In this age of data overload, Savitz encoura-ges us to scrutinize the quality of these data in as objective way as possible. I will certainly be referring to this text in the future, and would recommend it as highly relevant to any practising epidemiologist.

Reference

1 Hill AB. The environment and disease: association or causation? Proc R Soc Med 1965;58:295–300.[ISI][Medline]

Thursday, October 30, 2008

GUIDELINES ON CONFIDENTIALITY

A medical practitioner registered with the Malaysian Medical Council has rights, privileges and responsibilities. The practitioner is expected to meet the standards of competence, care and conduct set by the Malaysian Medical Council.
This booklet sets out the MMC’s guidelines on confidentiality. It is an extension of the principles described in the booklet `Good Medical Practice’.

read more: http://www.permai.gov.my/panduan/GUIDELINES%20ON%20CONFIDENTIALITY.pdf

Patient Confidentiality Is Priority With Electronic Practice Records

Patient Confidentiality Is Priority With Electronic Practice Records, Says Medical Defence Union, UK

The Medical Defence Union (MDU), the UK's leading medical defence organisation, says that GP practices are regularly seeking its advice on how to ensure patient confidentiality when using electronic records. In an article published in its latest In Practice1 journal for practice managers, MDU medico-legal adviser, Dr James Armstrong, answers some of the most common questions on the subject to the MDU's medico-legal advice helpline in recent years.

Dr Armstrong said: "Electronic records and communications are an increasing feature of GP practice and members may justifiably feel they are a valuable and efficient tool. However, compared to paper records, they do pose slightly different challenges when it comes to safeguarding patient confidentiality and MDU members regularly contact us for risk management advice about this."

Areas addressed by Dr Armstrong include emailing correspondence about patients; protecting information when transferring records electronically; upgrading computer systems; and the need to scan hospital correspondence. One example and the key points of his advice is set out below:

Can we send correspondence about patients by email?

- where an email contains patient information, you must consider the risk of the email being intercepted and ensure that it is effectively protected against improper disclosure at all times.

- any email exchange with or about a patient should take place only with the patient's full agreement, in line with the Data Protection Act 1998.

- you have a responsibility to ensure robust security measures are in place, such as encryption of data.

- it is prudent to satisfy yourself that adequate security is in place at the receiving end.

- The GMC says2 that if necessary you should seek appropriate authoritative professional advice on how to keep information secure and you should record the fact you have taken such advice.

Elsewhere in this issue, MDU medico-legal adviser, Sue Parker, explains how to set up protocols in general practice to define roles and responsibilities within the healthcare team. She said: "As nurses' roles have extended to include more complex medical services and healthcare assistants have become more involved in the delivery of care, protocols can clarify what is expected of those involved and define when they should seek advice from a doctor."


Employees Can be Liable for Violating Patient Confidentiality

Employees Can be Liable for Violating Patient Confidentiality
Clifford’s Notes, Chicago Lawyer, 05/01/2006
By Robert A. Clifford

Suzanne Bagent, a patient at Quincy Medical Group in September 2003, had blood samples drawn, which were sent to Illini Hospital. Misty Young, a phlebotomist and employee of the hospital, examined the results and later, at a tavern, told Bagent’s sister that the patient was pregnant.

Bagent filed a lawsuit against Illini Hospital and Young, alleging breach of health care practitioner/patient confidentiality, invasion of privacy, and negligent infliction of emotional distress, as well as intentional infliction of emotional distress as to Young.

The plaintiff’s action was grounded in statute (735 ILCS 5/8-802, 2004; 210 ILCS 85/6.17(b) (West, 2004) (patient’s medical information must be protected from disclosure), as well as common law right-to-privacy theories.

Admitting that she revealed the test results in a private conversation, Young filed a motion for summary judgment and accepted the hospitals’ offer of resignation in lieu of termination. Illini Hospital also moved for summary judgment, arguing that Young’s statements were not attributable to the hospital because her actions were not within the scope of her employment and because Young had been trained in confidentiality.

The trial court granted both of the defendants’ motions for summary judgment, but granted plaintiff’s motions for summary judgment against Young on the issue of whether she had improperly revealed confidential information. The issues of intentional infliction of emotional distress and damages also were to be determined at trial. On appeal, the rulings in favor of the defendants were reversed.

The appellate court found that Young had a continuing duty to maintain the confidentiality of patient records. "An employee entrusted with confidential information in the course of his or her employment has a duty not to disclose the information – without limitation as to time or space." Bagent v. Illini Community Hospital, and Misty Young, No. 4-05-0495 (4th Dist., decided March 3. 1006).

As for whether the hospital was liable under the doctrine of respondeat superior, the court said: "Hospital employees, as well as employees of lawyers, therapists, and other employers who maintain confidential information, have a constant duty to keep confidentiality." Therefore, the court held, it is up to a jury to decide whether Young was acting within the scope of employment, on the basis that her disclosure was actuated in part by a purpose to serve the employer. Id.



Although the plaintiff did not specifically plead the federal patient privacy statute, the Health Insurance Portability and Accountability Act of 1996 (HIPPA) (Pub. L. No. 104-191, 110 Stat. 1936), the act would expose the hospital to liability for fines by the Department of Health and Human Services for the actions of its employees.

Patients have a right to insist on privacy. It is their lives that become open books to medical professionals who count on openness and honesty in order to make proper diagnoses.

Take, for instance, the recently filed case of a Palm Beach, Fla., woman who sued Walgreens for defamation. Fifty-three-year-old Janey Karp has battled depression for years with the help of prescription drugs. She felt the need to be private about her problem because of the stigma she sensed in the general for those who needed medical to be "normal."

Much to her shock, when she picked up her prescription about a year ago, she noticed that in the patient information field someone had typed "CrAzY!" In looking at a previous prescription, she read that someone had typed, "She’s really a psycho!! Do not say her name too loud, never mention her meds by names & try to talk to her when..." The information continued on another page that was not attached.

When Karp read this, she knew her worst fears had been realized. She contacted a lawyer who said she made dozens of calls to Walgreens but received a "generic" response. Given that pharmacists and pharmacy technicians across the country have access to these records, Karp said she does not know how many people could have read these notes.

She said she was humiliated, embarrassed, and devastated, so she sued the Deerfield-based company in March, alleging defamation, negligent supervision, and intentional inflection of emotional distress. At the time of the filing, a Walgreens representative stated, "We want to ensure that our pharmacy employees are acting in a proper and professional manner, so we are looking into this matter."

The duty to maintain patient confidences traces back as far as ancient Greece, when the Hippocratic oath established a duty of confidentiality for the medical profession. ("Whatever, in connection with my professional practice, or not in connection with it, I see or hear in the live of men, which ought not be spoken of abroad, I will not divulge as reckoning that all such should be kept secret.")

Modern medical practice continued this ethical obligation of confidentiality through the American Medical Association’s Code of Medical Ethics, which provides that a "physician shall respect the rights of patients – and shall safeguard patient confidences within the constraints of the law." (Preamble Part IV, June 2001).

The notion of confidentiality is grounded in encouraging full uninhibited disclosure by the patient to receive proper treatment and to fulfill the purpose of the doctor/patient relationship. Over time, that has extended to medical professionals surrounding the doctor who must accomplish the patient’s medical goals. Violating these confidences has led to lawsuits brought on common law invasion of privacy grounds, breach of the fiduciary relationship between doctor and patient, intentional and negligent infliction of emotional distress, medical malpractice, defamation, libel, slander, and even breach of express or implied contract theories.

Certainly, a patient’s personal medical information should be controlled by the patient. In holding for the patient, as in Bagent, the court sends a clear message that patient confidentiality must be taken seriously by both employer and employees, particularly in t his age of electronically stored and managed data.

Confidentiality of Medical Information

A matter of growing importance. 

Confidentiality of MedicalInformation.

The subject of this paper is theconfidentiality of medical recordinformation. This is a concern for manypersons, including myself, when visiting ahealth professional. My goal is to talk aboutsome of the issues involved in protectingmedical information, particularly in theelectronic age. I also intend to inform youof recent state (Virginia) and federal effortsto regulate the transmission of medicalinformation. Finally, I plan to share a fewanecdotes and observations regardingcurrent legislative efforts to protect medicalinformation.I recently saw the 1997-1998 premiereof a television program. The program ERis one which many of you may have seen.For those of you who have not, it portraysthe lives of physicians, nurses, and other hospital personnel in a Chicago publicteaching hospital emergency room.

The premiere episode was shot “live” to capture the effect of having cameras recording a documentary in an emergency department.The premiere episode of ER providedmany examples of how medical recordinformation can be released unintentionally,and with significant detrimental impact.Cameras captured images and names ofpatients, and revealed their infections withAIDS and other diseases. Health carepractitioners openly discussed a patient’spersonal history and medical informationon film. These statements of patientidentifying information, if released to thepublic at large, would be breaches ofconfidential information under common law and as codified by various state statutes andfederal regulations.

read more: http://www.mellettepc.com/pdf/fall99.pdf

Malaysian Medical Council “Good Medical Practice”



A medical practitioner registered with the Malaysian Medical Council (MMC) has rights,
privileges and responsibilities.

The practitioner is expected to meet the standards of competence, care and conduct set by
the Malaysian Medical Council.

This document sets out the MMC's guidelines on confidentiality. It is an extension of the
principles described in the guideline “Good Medical Practice”.


CONTENTS
1. Principles of Confidentiality
2. Protecting information
3. Sharing information with patients
4. Electronic medical records
5. Disclosure of confidential information with the patient’s consent
6. Disclosure within health care teams
7. Disclosure to employers, insurance companies and other third parties including
managed care organizations
8. Disclosure without the patient’s consent
Disclosure in the patient’s medical interests
Disclosure in relation to the treatment sought by children or others who lack
capacity to give consent
Disclosures where a patient may be a victim of neglect or abuse
Disclosure after a patient’s death
9. Disclosure for medical teaching, medical research, and medical audit
10. Disclosure in the interest of others
Disclosures in the public interest
Disclosures to protect others
11. Disclosure in connection with judicial or other statutory proceedings
Disclosures required by law
Disclosures in the courts
Disclosure to statutory regulatory bodies
12. Media inquiries about patients