UK health records should not be flogged off

“Harry Cayton was only appointed head of the health service data watchdog on 6 November, but he has wasted no time in putting the boot into how the NHS wants to treat patient data.
Cayton, the man who won UK citizens the right to opt out of having a centrally stored medical record, is unhappy with proposals which would allow medical researchers to trawl databases looking for people with certain medical conditions. They would then be allowed to write to these patients asking if, given their condition, they would like to take part in trials of new drugs or treatments.”
Article
John Oates, The Register, 17 November 2008

ICES Report: Using Data from Electronic Medical Records: Theory versus Practice

“In Canada, the measurement of quality of healthcare has historically focused on specialized hospital-based care. Considerably less is known about the quality of care provided in the offices of primary care physicians. Primary care research has relied on data collected manually from physicians’ offices or from administrative databases. Manual data collection from paper-based patient charts in primary care physicians’ offices is costly and time consuming, and often only a small portion of the information in the charts is useable due to the lack of uniform documentation. Although data from administrative databases are more readily accessible and encompass the entire population, they are limited in their depth of clinical information.”
Article
Tezeta F. Mitiku and Karen Tu, Healthcare Quarterly, 11(4) 2008: 23-25

Software ontwikkeld om privacy patiënt te garanderen

“Patiëntgegevens die worden gebruikt voor onderzoek kunnen nu via software gezuiverd worden van informatie die de identiteit van de patiënt verraadt.”
Article (Dutch)
Hein Bosman, ICTZorg, 29 July 2008

Automated De-Identification of Free-Text Medical Records

“We have developed a pattern-matching de-identification system based on dictionary look-ups, regular expressions, and heuristics. Evaluation based on two different sets of nursing notes collected from a U.S. hospital suggests that, in terms of recall, the software out-performs a single human de-identifier (0.81) and performs at least as well as a consensus of two human de-identifiers (0.94). The system is currently tuned to de-identify PHI in nursing notes and discharge summaries but is sufficiently generalized and can be customized to handle text files of any format. Although the accuracy of the algorithm is high, it is probably insufficient to be used to publicly disseminate medical data. The open-source de-identification software and the gold standard re-identified corpus of medical records have therefore been made available to researchers via the PhysioNet website to encourage improvements in the algorithm.”
Article
Ishna Neamatullah, Margaret M. Douglass, Li-wei H. Lehman, Andrew Reisner, Mauricio Villarroel, William J. Long, Peter Szolovits, George B. Moody, Roger G. Mark and Gari D. Clifford, BMC Medical Informatics and Decision Making 2008, 8: 32, doi:10.1186/1472-6947-8-32

Swedish centre mines drug reaction data

“A Swedish monitoring centre is using data mining techniques to help identify adverse drug reactions based on Yellow Card patient records.
The Yellow Card is the UK’s Medicines and Healthcare products Regulatory Agency (MHRA) scheme, which has been used for over 40 years to collect information on suspected side effects from all types of medicines.”
Article
eHealth Europe, 23 April 2008

The coming surveillance of our health records by the government

“There’s a long-standing belief that one of the guiding principles of medicine is that our medical records are confidential, and that our health matters are not disclosed to anyone other than ourselves, another physician who is consulting or taking over our care, a person we specifically give permission to see our record and - in the case of certain infectious diseases - the local health department, if it’s mandated by law.”
Article
Thorswitch, TeamSugar, 13 April 2008

Perlegen strikes back on privacy

“Last week, patient privacy advocate Deborah Peel, MD, wrote a letter to Healthcare IT News attacking Perlegen Sciences’ plans to work with an EMR vendor to use patient data for genetics research. In a new letter, Perlegen strikes back at Peel.”
Article
Bryan L. Walser, Perlegen Sciences, Inc., Healthcare IT News, 27 March 2008

EMR vendor to share patient data with genetics research firm

“Perlegen Sciences, Inc., a company exploring the clinical application of genetic research, plans to collaborate with an undisclosed electronic medical records vendor to identify and develop genetic markers that predict how patients are likely to respond to specific medical treatments.”
Article
Richard Pizzi, Healthcare IT News, 20 March 2008

Using Business Intelligence to Bring out the Value of EHRs

“The big issue with electronic medical records is trying to evaluate the return on investment and this article take things one step further. Many EHRs have what is now called a “patient registry” which is the first step towards full Business Intelligence management.”
Article
The Medical Quack, 10 February 2008

States and V.A. at Odds on Cancer Data

“Until recently, the nation’s cancer surveillance program was humming along. In every state, investigators were getting reports from every hospital describing every cancer patient they had seen.
The data, which include the name, address, age, race and medical history of patients, are used to compile cancer rates. They also are used to investigate survival and other issues, like unusual cancer clusters and whether patients’ experiences are different depending on their racial or economic group.”
Article
Gina Kolata, The New York Times, 10 october 2007

State-of-the-art Anonymization of Medical Records Using an Iterative Machine Learning Framework

“The anonymization of medical records is of great importance in the human life sciences because a de-identified text can be made publicly available for non-hospital researchers as well, to facilitate research on human diseases. Here the authors have eveloped a de-identification model that can successfully remove personal health information (PHI) from discharge records to make them conform to the guidelines of the Health Information Portability and Accountability Act.”
Abstract
György Szarvas, Richárd Farkas and Róbert Busa-Fekete, J Am Med Inform Assoc. 2007;14:574-580

Rapidly Retargetable Approaches to De-identification in Medical Records

“This paper describes a successful approach to de-identification that was developed to participate in a recent AMIA-sponsored challenge evaluation.”
“We were able to achieve good performance on the de-identification task by the rapid retargeting of existing toolkits. For the Carafe system, we developed a method for tuning the balance of recall vs. precision, as well as a confidence score that correlated well with the measured F-score.”
Abstract
Ben Wellner, Matt Huyck, Scott Mardis, John Aberdeen, Alex Morgan, Leonid Peshkin, Alex Yeh, Janet Hitzeman, and Lynette Hirschman, J Am Med Inform Assoc. 2007;14:564-573

Evaluating the State-of-the-Art in Automatic De-identification

“To facilitate and survey studies in automatic de-identification, as a part of the i2b2 (Informatics for Integrating Biology to the Bedside) project, authors organized a Natural Language Processing (NLP) challenge on automatically removing private health information (PHI) from medical discharge records. This manuscript provides an overview of this de-identification challenge, describes the data and the annotation process, explains the evaluation metrics, discusses the nature of the systems that addressed the challenge, analyzes the results of received system runs, and identifies directions for future research. The de-indentification challenge data consisted of discharge summaries drawn from the Partners Healthcare system.”
Abstract
Özlem Uzuner, Yuan Luo and Peter Szolovits, J Am Med Inform Assoc. 2007;14:550-563

Preventive Medicine and the Electronic Health Record

“Preventive medicine appears to be emerging as a powerful force to enhance the lives of Americans. Information on disease prevention and health promotion comes to us in a constant stream from the news media these days. With so much information available, it can be challenging for physicians to function wisely during these times of growing enlightenment. One key element of future healthcare, the electronic health record (EHR), will help patients and providers meet the challenges of having too little or too much information. EHRs, which will place the patient or consumer at the center of the health system, are coming of age and gaining momentum.”

George K. Anderson, Medscape Public Health & Prevention, 11 December 2004

Article

Patient participation in EHR benefits - Thought Leaders

“The electronic health record (EHR) should be designed to reflect all activity relevant to the healthcare of an individual citizen. Because healthcare activity occurs in a variety of settings over one’s lifetime, it is essential that EHR technology allows access from all healthcare locations. Authorship of the EHR must also extend beyond traditional healthcare workers to include patients and their agents.”

Thomas M. Jones, Health Management Technology, October 2003

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