Health Information – Making Sense of it all

Jan 11, 2002Article, Other

Title Health Information – Making Sense of It All
Author Bryan Hall
AAMS Webmaster
Publication Status 1. Published: January 2002
Review Status GR
Copyright Copyright of this article is vested in the author. Permissions for reprints or republications must be obtained in writing from the copyright holder. This article has been republished here with permission from the copyright holder.

Health Information – Making Sense of it all

Some Facts

  • In OECD countries, a woman born today has an expectation of life of 78 years, a man 72 years; in many less-developed countries, especially Africa, the figure is around 50.
  • The OECD countries, with one sixth of the world’s population, produce three quarters of the world’s industrial production.
  • Only 11 per cent of the world’s land is used for arable farming. National differences range from 77 per cent in Barbados to 0.2 per cent in several Middle East countries.
  • Of the world’s 1,000 largest banks, 205 are in the US, 110 in Italy, 109 in japan, 104 in West Germany. The UK has 31.
  • By the end of this century, it is estimated that there will be 1 billion illiterate people in the world, three quarters of them in the five most populous Asian countries – China, India, Indonesia, Pakistan and Bangladesh.
  • Every year, over half a million women die from causes related to pregnancy and childbirth.
  • In Africa a woman has a one in 15 chance of dying from a pregnancy related cause.
  • According to the UN Development Program, the differences between the developed and developing world in maternal mortality rates are greater than for any other social indicator.
  • Although a country’s wealth is normally the prime determinant of its health performance, some countries – including Sri Lanka, China, Jamaica and Costa Rica have succeeded in providing a significantly better level of health care than their income levels would suggest.
  • Safe water is only one element of adequate sanitary conditions, which should also include sewage disposal and hygenic washing and cleaning facilities.
  • Prenatal care and attended birth rates depend not only on the facilities a country can afford but also on social traditions surrounding the issue.(all of the above from Claus Moser – Vital World Statistics – © Economist Books Ltd 1990)
  • AIDS spending in developing countries must rise to US$ 7-10 billion a year. AIDS is taking a grim toll in sub-Saharan Africa where it killed 2.3 million people this year and an estimated 28.1 million people are infected with the virus (WHO)

Multiple Observations & Evidence

  • Data Attributes & Generalisation
  • Information Systems

Data Attributes & Generalisation

Health Care Policy must be seen in the broader economic, cultural and political context. The complex nature of health policy and administration has inevitably led to a reliance on theories of mathematical statistics for setting spending priorities.

To formulate information in a scientific manner it is essential to have basic facts stated in numerical terms. However, it is not necessary to enumerate each unit in the universe in order to arrive at an acceptable estimate for the total. A carefully designed sample may provide the necessary information (Raj; 1968). Statistical methods can be relied upon on only in so far as a rigorous and competent analysis is conducted on a carefully designed sample space that is representative of the characteristics of either the total population or a specific subset of the population for which indicative information is sought. The theory of Mathematical Statistics is concerned with obtaining all and only those conclusions for which multiple observations are evidence. Mathematical statistics is not merely the handling of facts stated in numerical terms (Kaplan; 1961).

The purpose of inductive statistics is to provide methods for making statistical inferences about a population based on a collection of sampled individuals. Statistical inferences are necessarily probabilistic in nature. The testing of an appropriate hypothesis relating to measurable characteristics is central to statistical decision making and consequently, when applying statistical methods, it is essential to carefully and precisely define the problem to be solved.

To change a casual observation into useful information or data requires the detailed reporting of at least the following attributes of the observation:

  • Theme – The phenomenon or object being observed or measured must be recorded in some measurable or defined units;
  • Location – The simple observation of a phenomenon without a record of the location of the phenomenon rarely generates useful information; and
  • Time – A record of observation for which there is no concurrent record of time has minimal information content (Sinton; 1978).

At least three important types of data generalisation commonly take place:

  • Aggregation – This usually involves the definition of spatial location and the counting of thematic characteristics for that location. Generated data is interval in nature and may be manipulable by mathematical or statistical techniques;
  • Classification – In this case observations are matched and categorised with other observations exhibiting like characteristics; and
  • Induction – This is the process by which a series of sample measurements are generalised to include a much larger group of phenomenon or locations assumed to have the same characteristics as the sample measurements (Sinton; 1978).

These procedures of abstraction and generalisation significantly affect the utility of data for analytic purposes. Certain types of detail present in the original data may be lost. It is important to establish the extent and characteristics of the detail lost in the process of generalisation as this affects the nature of the thematic content of the information (Sinton; 1978).

Information Systems

The US Congress Office of Technology Assessment report Protecting Privacy in Computerised Medical Information advises that in addition to patient data confidentiality and security considerations, according to the Institute of Medicine, content, data-exchange, and vocabulary standards must be developed in order to implement a computerized system for health care information. Such standards are necessary for transmitting records and aggregating information from many sources, either for longitudinal records for individual patients or for databases of secondary records to be used for research or epidemiologic purposes.

  • Content standards provide a description of data elements to be captured in automated medical records. Thus ensuring uniformity in records having different origins.
  • Data-exchange standards are formats for uniform electronic transmission of data, establishing the order and sequence of data during transmission.
  • Vocabulary standards establish common definitions for medical terms and determine how information will be represented in medical records. Vocabulary standards are intended to lead to consistent descriptions of medical conditions. Currently, terms used to describe the diagnosis and procedures may vary.

The Report A National Model for the Collection and Analysis of a Minimum Data Set with Outcome Measures for Private, Hospital-based, Psychiatric Services contains a most insightful analysis concerning the development of new information systems. Section 8.2 from this report is paraphrased below:

Any attempt to develop complete and comprehensive information systems … is likely to entail considerable risk of failure. Gilb has discussed alternative development methodologies in detail and presents a convincing argument that in such circumstances an evolutionary approach is the only way to proceed. By this, Gilb means that we should identify key stake-holders core information requirements and the critical performance attributes of the system that, were they not to be met, could render the system unacceptable. A system which meets those requirements should be developed and implemented first and then used as the basis for further developments.

The recommended systems development strategy is therefore based on Gilb’s model of evolutionary software development. Under this approach, the initial prototype applications are built on the basis of the most well understood components of the stake-holders’ requirements. This provides a solid architectural foundation for building the software tools as the full requirements become clearly defined.

The development and implementation of information systems is in any case, an inherently iterative process. The initial specification of an information model and functional requirements is essentially an hypothesis about what might be required. The implementation of a system based on those requirements is to some extent an experiment. By using an evolutionary model of software development, with close attention being paid to users’ experience with the new system, developers are better able to build effective systems which meet user’s needs. Any expectations that a system can be built and implemented “once and for all” must be abandoned for, once implemented, use of the system by the key stake-holders will change their understanding of their functional requirements. This is the principal reason why the implementation of the MMS will not be complete at the end of the first phase. At that point, the system the key stake-holders, through their representatives on the Working Group, thought was required will have been implemented. The key task in the second phase is to refine that first version of the system on the basis of Hospitals’ Funds and other stake-holders’ experience of using an actual system.

International Diseases and Health Classifications

The United Nations Statistical Commission maintains and develops economic and social classifications across a broad range of areas, including economics, demographics, labour, health, education, social welfare, geography, environment and tourism. The classifications are partitioned into Reference, Derived and Related classifications.

  • Reference classifications are necessarily a product of international agreements approved by the United Nations Statistical Commission or another competent intergovernmental board, such as that of the International Labour Organization (ILO), the International Monetary Fund (IMF), the United Nations Educational, Scientific and Cultural Organization (UNESCO), World Health Organization (WHO), or the World Customs Organization (WCO)
  • Derived classifications are based upon reference classifications .
    Derived classifications may be prepared either by adopting the reference classification structure and categories, and then possibly providing additional detail beyond that provided by the reference classification, or they may be prepared through rearrangement or aggregation of items from one or more reference classifications. Derived classifications are often tailored for use at the national or multi-national level.
  • Related classifications are those that partially refer to reference classifications, or that are associated with the reference classification at specific levels of the structure only.
    (Hoffmann and Chamie; 1999)

Relevant classifications include:

  • International Statistical Classification of Diseases and Related Health ProblemsThis classification is a Reference Classification and its purpose is to permit the systematic recording, analysis, interpretation and comparison of mortality and morbidity data collected in different countries or areas and at different times. It is available in: Arabic, Chinese, English, French, Russian, Spanish and the WHO are the custodian agency. The meta data record for this classification is maintained by the UN Statistical commission and it refers to additional classifications in the areas of Oncology (ICD-O), Dentistry and Stomatology (ICD-DA), Neurology (ICD-NA), Psychiatry (clinical descriptions and diagnostic guidelines, diagnostic criteria for research, primary care, primary health care), clinical modifications (ICD-10-AM, ICD-10-CM)
  • International Classification of Impairments, Disabilities, and Handicaps This classification is a Reference Classification and its purpose is to classify consequences of health conditions with three classifications of functioning and disablement at the body, whole person and person in social context levels – impairments, disabilities and handicaps. The ICIDH provides a framework and an international common language for the organization and compilation of disability data, the international comparison of these data, and forms the basis for assessment instruments.

Related Links

World Health Organization

US Centers for Disease Control and Prevention

United Nations Statistics Division

Sources of International Data & Statistics

WHO Statistical Information System

  • Basic Health Indicators,
  • Burden of Disease,
  • International Classifications,
  • HIV/AIDS, Links to National Health-Related Websites,
  • Member States of WHO, Links to
  • Causes of death, infant death, life expectancy and age-standardized death rates. Healthy life expectancy and national health accounts
  • Statistical Annex of the World Health Report
  • Health Systems Performance
  • Global Programme on Evidence for Health Policy – Discussion Papers
  • Geographic Information Systems (GIS) in connection with health.
  • Infectious Diseases
  • The Weekly Epidemiological Record
  • International Travel and Health — vaccination requirements and health advice for travelers
  • AIDS/HIV Statistics
  • WHO Vaccine Preventable Diseases Monitoring System
  • Global Oral Data Bank

Australian Bureau of Statistics

  • Australian Standard Research Classification
  • Australian Standard Geographical Classification
  • Australian Standard Classification of Drugs of Concern
  • National Health Surveys

In Australia the Australian Bureau of Statistics (ABS) are responsible for Demography Statistics, which the Macquarie Dictionary defines as, the science of vital and social statistics, as the births, deaths, diseases, marriages, etc of populations. The ABS conducts a national census every five years which collects a range of personal, family and household information about the Australian population. The ABS recognise that classification is one of the cornerstones of statistics and that without the accurate and systematic arrangement of data according to common properties, statistical output can not be comparable. Consequently the ABS have published standardised classification systems and methods in many disparate fields.

Australian Standard Research Classification

The Australian Standard Research Classification (ASRC) is the collective name for a set of three related classifications developed for use in the measurement and analysis of research and experimental development (R & D) undertaken in Australia, both in the public and private sectors. Use of these classifications ensures that R & D statistics and statistics collected from higher education institutions are useful to governments, educational institutions, and other organisations such as scientific, professional business and community groups and private individuals.

Australian Standard Geographical Classification

The Australian Standard Geographical Classification (ASGC) provides a common framework of statistical geography and thereby enables the production of statistics which are comparable and can be spatially integrated. In practice, statistical units such as households and businesses are first classified or assigned to a geographical area in one of a number of ASGC structures. Data collected from these statistical units are then compiled into ASGC defined geographic aggregations which, subject to confidentiality restrictions, are then available for publication. The classification structures used by the ASGC are:

  • Main Structure;
  • Local Government Area Structure;
  • Statistical District Structure;
  • Statistical Region Structure;
  • Urban Centre/Locality Structure;
  • Section of State Structure; and
  • Remoteness Structure.

The various geographical areas, or spatial units, which build the different classification structures are as follows:

  • Census Collection District (CD);
  • Statistical Local Area (SLA);
  • Statistical Subdivision (SSD);
  • Statistical Division (SD);
  • State and Territory (S/T);
  • Statistical District (S Dist);
  • Local Government Area (LGA);
  • Statistical Region Sector (SRS);
  • Statistical Region (SR);
  • Major Statistical Region (MSR);
  • Urban Centre/Locality (UC/L);
  • Section(s) of State (SOS); and
  • Remoteness Area (RA).

Australian Standard Classification of Drugs of Concern

The ABS have also developed the Australian Standard Classification of Drugs of Concern (ASCDC) for use with data relating to drugs of concern. Generally, the ASCDC is designed to classify chemical substances which are of concern because they alter physiological processes to produce a psychoactive effect, to enhance performance or image, or to act as a detoxifying agent or antidote. Drugs of concern are defined as:

Any chemical substances for which policies and programs aimed at reducing drug related harm or reducing the availability of drugs have been developed, or which have otherwise been identified by key stake-holders in the health, welfare, and crime and justice sectors to be of current concern in the Australian context.

This definition clearly includes not only drugs subject to legal restrictions but also legally obtainable drugs for which there may or may not be harm reduction strategies are in place.

National Health Surveys

The ABS periodically publish a review of statistical information arising from the National Health Survey. The most recent review provides an overview of results from the 1995 National Health Survey (NHS) it includes very broad indicators of

  • health status – prevalence of illness,
  • factors which may influence health (e.g. smoking & exercise)
  • information on health-related actions taken by people in response to illness/injury or for other reasons associated with their health.

Related Links

Australian Bureau of Statistics

Australian Institute of Health and Welfare

  • National Health Data Dictionary
  • National Minimum Data Set
  • Australian Institute of Health and Welfare Data Online
    • The Knowledgebase
    • National Cardiovascular Disease Database
    • National Hospital Morbidity Data Cubes

The Australian Institute of Health and Welfare were set up in 1987 under the Australian Institute of Health and Welfare Act. AIHW generate data and publish reports and discussion papers concerning the health and welfare of Australians.

Data capture collection and processing procedures vary among the States and Territories. The AIHW manage a number of projects to reduce data variation and ensure the collection of uniform information.

National Health Data Dictionary

The NHDD contains the data definitions currently formally approved by the National Health Information Management Group (NHIMG). Under the National Health Information Agreement (NHIA), the NHDD is the authoritative source of health data definitions used in Australia where National consistency is required. It is designed to improve the comparability of data across the health arena.

National Minimum Data Set

The NMDS is a core set of data definitions agreed by the relevant national information management group for collection and reporting at a national level. A NMDS is contingent upon a national agreement to collect uniform data and to supply it as part of the national collection, but does not preclude agencies and service providers from collecting additional data to meet their own specific needs.

The AIHW run a number of information portals dealing with:

 Aged Care, Burden of Disease, Cancer, Cardiovascular Health, Children and Youth, Collaborating Units , Data Development, Data Standards, Dental Health, Disability, Drugs and Alcohol, Expenditure, General Practice, Hospital Data, Housing & Homelessness, Indicators, Immunisation Research, Indigenous People, Injuries, Knowledgebase, Labour Force, Mental Health, NHPA – Health Priorities, Perinatal Health, Population Health, Rural Health

The Knowledgebase

The Knowledgebase is an electronic register of Australian health, community services, housing and related data definitions and standards maintained by the AIHW. The Knowledgebase contains both the definitions themselves and tools for searching and grouping data definitions with the National Health Information Model and National Minimum Data Sets.

Related Links

Australian Institute of Health and Welfare

Australian Institute of Health and Welfare Data Online

National Cardiovascular Disease Database

The NCDD provides access to the data held by the National Centre for Monitoring Cardiovascular Disease at the Australian Institute of Health and Welfare

Related Links:

National Cardiovascular Disease Database

National Hospital Morbidity Data Cubes

  • The Interactive National Hospital Morbidity Data page contains links to a number of data cubes containing information on the principal diagnoses and diagnosis related groups (DRGs) of patients admitted to Australian hospitals.
  • Disability Agreement-funded services – data about consumers of Commonwealth/State funding
  • Cancer Cases – new cases and age-specific rates for selected cancers

Related Links:

Australian Institute of Health and Welfare Data Online

Other Health Databases

  • Australian Drug Information Network
  • Health Wiz
  • Health Promotion
  • Adolescent Health Promotion Database

Australian Drug Information Network

The Australian Drug Information Network (ADIN) was funded for four years from May 1999 to May 2003 by the Commonwealth Government as part of its National Illicit Drug Strategy. ADIN provides a central point of access to quality Internet-based alcohol and drug information provided by prominent organisations in Australia and Internationally.

Related Links:

Australian Drug Information Network

Health Wiz

HealthWIZ is a Social Health Database application package distributed on CD-ROM. It combines social health data with graphing and mapping tools into a single package. Tables can be constructed based on a large number of constituent data variables such as age, sex, birthplace, cause of death, etc). Most of these variables have national coverage. HealthWIZ is used for analysing statistical / health patterns in its constituent data sets which include or are derived from data sets originating from:

  • Population Censuses
  • Medicare Claims
  • Medicare Cancer Screening
  • Immunisation status
  • Deaths
  • Hospital Use
  • DSS-Centrelink
  • Veterans’ Affairs
  • Aged Care
  • Child Care
  • National Cancer
  • State Cancer
  • Dementia
  • Hospital Capacity (Establishments)
  • Social Health Atlas
  • Standardisation data

 

Health Wiz

Health Promotion

The Health Promotion Projects website contains a database listing of Australian and New Zealand health promotion projects. The database contains over 6,000 entries covering a wide range of health promotion activities including programs for:

  • Indigenous Australians;
  • Rural and Regional Australia;
  • Youth;
  • Ethnic Communities;
  • Women’s Health; and
  • General Practice.

 HEAPS Database

Adolescent Health Promotion Database

This database provides access to articles relating to adolescent health promotion.

Adolescent Health Promotion Database

Health & Ageing

The Australian Government Department of Health of Ageing Website provides an extensive list of publications, reports and reviews. Some of these reports are related to data modeling and statistical reviews. Publications of particular relevance to the current topic include:

  • An overview of health status, health care and public health in Australia
    This paper gives a detailed description of Australia’s health system including health financing, population health strategies, the health care reform agenda, the relationship between health care regulation and the health industry and also sets out some priorities for the future.
  • A study into levels of and attitudes towards information technology in general practice
  • The Australian Health Care System: An Outline
    This report describes how treatment of illness and injury is delivered and paid for in Australia, with emphasis on the funding role of the Federal Government.
  • The Australian Medical Workforce
    The paper describes the medical workforce and sets out a range of issues that currently have influence.
  • Australian Statistics on Medicines
    The Australian Statistics on Medicines aims to provide comprehensive and valid statistics on the Australian use of medicines.
  • Health and Aged Care Budget Papers 1996 to 2002
  • Chief Medical Officer’s Reports 1999 to 2001
    Issues include: Research, Aboriginal and Torres Strait Islander peoples, Safety and Quality in Health Care, vCJD, exotic human diseases, antibiotic resistance, Depression, Asthma, drinking water guidelines, childhood vaccination, Health Online.
  • Communicable Diseases
    Essential information on topics such as the National Notifiable Diseases Surveillance System
  • Population Health Division Publications
    Cancer, Child and Youth Health, Environmental Health, HIV/AIDS, Hepatitis C, Immunisation, Injury Prevention, Physical Activity/Nutrition, Tobacco, Alcohol and Other Drugs
    Women’s Health
  • Quality in Australian Health Care
    This report makes startling claims as to the prevalence of adverse events in the Australian Health Care System. Further information concerning this report is available below.
  • Health Sector Performance Indicators – Public Hospitals – The State of Play
    This First National Report on Health Sector Performance Indicators outlines the development of performance indicators for the health sector in Australia and brings together national data to report against these indicators.
  • National Health Priority Areas 1996
    This publication provides a summary of the status of Australia’s health in terms of four initial priority areas: cardiovascular health, cancer control, injury prevention and control, mental health and diabetes mellitus. It outlines deficiencies in our understanding of the impact of these conditions on the community. The publication provides a framework for national collaborative action between Commonwealth, State and Territory Governments in dealing with the priority areas. It also provides a framework for monitoring health outcomes.
  • Health Financing in Australia: The Objectives and the Players
    Examines the role of government in health systems and the rationale for that involvement and the way in which financing and organisational arrangements implemented by players in the health care sector underpin the delivery of health services in Australia
  • Measuring Remoteness: Accessibility/Remoteness Index of Australia (ARIA)
    Describes a geographic approach to measuring the concept of remoteness and the creation of a standard classification and index of remoteness that covers the whole of the country. The ARIA index is a valuable tool that can be used in policy development, implementation and evaluation to assist in targeting of programs to the various regions of Australia.
  • Health Expenditure: Its Management and Sources
    Examines the overall growth in health expenditure in Australia and compares it with the growth experienced overseas. It discusses the reasons to manage health expenditure and canvasses some evidence of less-than-optimal use of resources both in Australia and overseas. Areas of growth in the Australian health system and the approaches that have been used to moderate that growth are then examined.
  • Health Financing and Population Health
    Examines population health in the context of health care financing and looks at how much should be spent on population health; where funds for population health could be derived and how population health ‘products’ could be purchased
  • Hospital Casemix Data and the Health of Aboriginal and Torres Strait Islander Peoples
    Aboriginals and Torres Strait Islander peoples make relatively more use of public hospitals and community health centres, and relatively less use of private hospitals, nursing homes, and the private services available under Medicare and the Pharmaceutical Benefits Scheme. Researchers concerned with Indigenous health have used hospital separations data to comment on differences in utilisation rates, and also the diseases/disorders responsible for hospital stays. However, up to now, they have tended to neglect casemix data. This paper is intended to encourage greater use of casemix-based information for both research and policy purposes.
  • Technical Advisory Committee on Antibiotic Resistance
    The Commonwealth Government Response to the Report of the Joint Expert Technical Advisory Committee on Antibiotic Resistance (JETACAR). Infections caused by antibiotic-resistant bacteria are difficult to treat with first-line antibiotics and are often associated with increased morbidity, increased time in hospital and higher mortality rates.
  • Medicare Statistics
    Analysis of Major Aggregates by State/Territory and by Broad Type of Service
  • The Ageing Australian Population and Future Health Costs:1996-2051
    This paper projects future health costs attributable to the progressive ageing of the Australian population based on extensive administrative data on medical practitioner visits (to GPs and specialists), prescription drug consumption and hospital admissions.
  • Health services in the city and the bush: Measures of access and use derived from linked administrative data
    The paper explores differences in service availability, utilisation and health status between people living in urban and remote areas and comments on some of the reasons why these differences exist.
  • Quality and Outcome Indicators for Acute Healthcare Services
    This Project identifies issues surrounding indicator use and potential quality of care indicators for an initial minimum set of performance indicators for the acute healthcare sector in Australia. Various dimensions of quality of care were identified following a preliminary review of available, feasible quality of care indicators. In selecting the final list of dimensions of quality of care they weighed the need to encompass aspects of care relevant to patients, providers and purchasers with the amenity of various aspects of care to quantitative representation as indicators. Dimensions of quality of care were selected to minimise their potential for overlap within a comprehensive framework encompassing relevant aspects of acute healthcare quality.
  • A National Model for the Collection and Analysis of a Minimum Data Set with Outcome Measures for Private, Hospital-based, Psychiatric Services
    A description of a National Model for the collection and analysis of a minimum data set with Outcome Measures for private, hospital-based, psychiatric services. The Report was developed under the auspices of the Strategic Planning Group for Private Psychiatric Services (SPGPPS). The goal underlying the development and implementation of a National Model for Data Collection and Analysis is to provide a reliable, valid and timely source of information to support improvements in the quality, effectiveness and efficiency of private sector Hospital-based psychiatric services. Section 8.2 of this report describes a proposal for the development of information systems consistent with the recommendations of the report. It has been paraphrased earlier in this review.

Related Links:

Health & Ageing

Quality in Australian Health Care

This report advances a number of obvious arguments of principle and makes a number of assertions concerning proposed benefits deriving from computerised information systems including:

  • There should be regular and consistent monitoring of the safety and quality of the health care system and its component parts.
  • As a matter of principle this kind of performance information should not be withheld but should be freely available.
  • No effort to improve safety and quality will be successful unless those at the workface are fully involved.
  • Appropriate use of computerised technology, with suitable safeguards regarding confidentiality, has the potential to dramatically improve safety for individual consumers.
  • A patient-centred computerised clinical information system which links health care providers is the only practical way to ensure that relevant information is available to help managers and clinicians identify problem areas requiring special attention and prevent patients suffering preventable injury, disability or death as a result of their health care.

There are a number of parrallels between the Quality in Australian Health Care Study and the Harvard Medical Practice Study, which also drew attention to medical errors. The Harvard Medical Practice Study was first published in 1991 and was based on 1984 case records. The researchers have subsequently written a number of articles and a book, and popular discussion of “the Harvard study” has come to refer to these collective works 1, 2, 3, 4, 5, 6. Both the Harvard study and the Quality in Australian Health Care study examined medical records to detect evidence of adverse events. By extrapolating from the adverse event analysis both the studies drew extraordinary conclusions concerning the frequency and totality of hosptial treatment derived injuries and fatalities. Richard E. Anderson, a specialist medical oncologist and professor of medicine at the University of California San Diego, offers valuable critiques of the Harvard Medical Practice Study:

  • An “Epidemic” of Medical Malpractice? A Commentary on the Harvard Medical Practice Study. Richard E. Anderson, M.D., F.A.C.P. (see: http://www.thedoctors.com/)
  • Harvard Study Continues to Distort Health Care Quality Debate. Richard E. Anderson, M.D., F.A.C.P. (see: http://www.thedoctors.com/)

There are a number of conflicting points of view concerning Quality in Health Care Studies. Hayward and Hofer have recently released a book titled: “Estimating Hospital Deaths Due to Medical Errors: Preventability Is in the Eye of the Reviewer,” the full text of which available, to registered users, on the JAMA Internet Site (http://jama.ama-assn.org).

Rand have also produced a number of discussion papers concerning measuring Quality in Health Care:

  • Quality of Care for General Medical Conditions: A Review of the Literature and Quality Indicators
  • Quality of Care for Oncologic Conditions and HIV: A Review of the Literature and Quality Indicators
  • Quality of Care for Cardiopulmonary Conditions: A Review of the Literature and Quality Indicators
  • Quality of Care for Children and Adolescents: A Review of Selected Clinical Conditions and Quality Indicators
  • Quality of Care for Women: A Review of Selected Clinical Conditions and Quality Indicators

Related Links

The Doctors Company

JAMA

RAND

Some References

  • Kaplan A. Sociology Learns the Language of Mathematics. In The World of Mathematics. Edited by JR Newman. Published by Allen and Unwin; Britain; 1961.
  • Raj D. Sampling Theory. Published by Tata McGraw-Hill Publishing Company Ltd. New Delhi; 1968.
  • Sinton D. The Inherent Structure of Information as a Constraint to Analysis: Mapped Thematic Data as a Case Study. Harvard Papers on GIS. First International Advanced Study Symposium on topological data structures for Geographic Information Systems. Edited by G Dutton. Volume 7; 1978.
  • U.S. Congress. Office of Technology Assessment, Protecting Privacy in Computerised Medical Information, OTA-TXT-576 (Washington, DC: US Government Printing Office, September 1993 (ISBN: 0-016-042074-1)
  • A National Model for the Collection and Analysis of a Minimum Data Set with Outcome Measures for Private, Hospital-based, Psychiatric Services. Allen Morris Yates and the Strategic Planning Group for Private Psychiatric Services Data Collection and Analysis Working Group. May 2000. (ISBN 0-642-41614-1)
  • Standard Statistical Classifications: Basic Principles 11. Eivind Hoffmann, Bureau of Statistics, International Labour Office and Mary Chamie, United Nations Statistics Division. Februaru 1999. Statistical Commission Thirtieth session New York, 1-5 March 1999 Items 8 of the provisional agenda. (http://www.un.org/Depts/unsd/class/bestprac.pdf)

Numbered Refererences for the Harvard Medical Practice Study

  1. Brennan RA, Leape LL, Laird MM, Hebert L, Localio AR, Lawthers AG, et al.
    Incidence of Adverse Events and Negligence in Hospitalized Patients: Results of the Harvard Medical Practice Study. New England Journal of Medicine. 1991; 324: 370-6.
  2. Localio AR, Lawthers AG, Brennan TA, Laird NM, Hebert LE, Peterson LM, et al.
    Relation Between Malpractice Claims and Adverse Events Due to Negligence. New England Journal of Medicine. 1991; 325: 245-51.
  3. Leape LL, Brennan TA, Laird N, Lawthers AG, Localio AR, Barnes BA, et al.
    The Nature of Adverse Events in Hospitalized Patients. New England Journal of Medicine. 1991; 324: 377-84.
  4. Weiler PC, Hiatt HH, Newhouse JP, Johnson WG, Brennan TA, Leape LL.
    A Measure of Malpractice. Cambridge: Harvard University Press; 1993: 175.
  5. Weiler PC, Newhouse JP, Hiatt HH.
    Proposal for Medical Liability Reform. Journal of the American Medical Association. 1992; 267: 2355-8.
  6. Weiler PC, Brennan TA, Newhouse JP, Leape LL, Lawthers AG, Hiatt HH, et al.
    The Economic Consequences of Medical Injuries. Journal of the American Medical Association. 1992; 267: 2487-92.(these references cited from the articles attributed to Richard E. Anderson referenced in the text)