data collection
Haider AH, Pronovost PJ. Joint Commission Journal on Quality and Patient Safety, 37(10)
Racial disparities in health care delivery and patient outcomes exist and persist unabatedly in the health care system in the United States. One potentially modifiable mechanism for disparities attributed to health care is the quality of care provided to minorities. Minorities tend to receive lower-quality health care even when insurance status and income are controlled. Black patients receive less intensive hospital care, for example, receiving fewer cardiac procedures, lung resections for cancer, and kidney and bone marrow transplants.
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Published:
1 October 2011 |
Keyword(s): Data Collection, Disparities, Health Information Technology, United States
Weissman JS, Hasnain-Wynia R. N Engl J Med, 364(24)
Health care reform’s promise will not be realized if it fails to reduce racial and ethnic disparities in care. The first step toward monitoring, identifying, and targeting the underlying causes of disparities is for health care organizations to collect and analyze data that adequately describe their populations. No single entity has the capacity to analyze disparities for the entire country, and one of the largest and most comprehensive sources of utilization — health insurance claims — lacks basic demographic data on the race and ethnic background of enrollees. It is therefore worthwhile to examine the status of data collection and future options.
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Published:
16 June 2011 |
Keyword(s): Data Collection, Ethnic Disparities, United States
Miller AR, Tucker CE. Journal of Policy Analysis and Management, 30(3)
Fast-paced IT advances have made it increasingly possible and useful for firms to collect data on their customers on an unprecedented scale. One downside of this is that firms can experience negative publicity and financial damage if their data are breached. This is particularly the case in the medical sector, where we find empirical evidence that increased digitization of patient data is associated with more data breaches. The encryption of customer data is often presented as a potential solution, because encryption acts as a disincentive for potential malicious hackers, and can minimize the risk of breached data being put to malicious use.
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Published:
24 May 2011 |
Keyword(s): Breach, Confidentiality, Data Collection, Electronic Health Records, Hospital Information Systems, Security, United States
D'Avolio LW et al, The American Journal of Medicine
As is the case for environmental, ecological, astronomical, and other sciences, medical practice and research finds itself in a tsunami of data. This data deluge, due primarily to the introduction of digitalization in routine medical care and medical research, affords the opportunity for improved patient care and scientific discovery. Medical informatics is the subdiscipline of medicine created to make greater use of information in order to improve healthcare.
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Published:
December 2010 |
Keyword(s): Data Collection, Effectiveness, Medical Informatics, Research
Bennett K et al, J Med Internet Res, 12(5)
Security considerations are an often overlooked and underfunded aspect of the development, delivery, and evaluation of e-mental health interventions although they are crucial to the overall success of any eHealth project. The credibility and reliability of eHealth scientific research and the service delivery of eHealth interventions rely on a high standard of data security. This paper describes some of the key methodological, technical, and procedural issues that need to be considered to ensure that eHealth research and intervention delivery meet adequate security standards.
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Published:
16 December 2010 |
Keyword(s): Computer Security, Confidentiality, Data Collection, Healthcare Technology, Implementation, Internet, Mental Health, Privacy
Kew ST. BMC Research Notes, 3(1)
BACKGROUND:
The ubiquitous use of mobile phones in sending and receiving text messages has become a norm for young people. Undeniably, text messaging has become a new and important communication medium not only in the social realm but in education as well. The aim of this study is to evaluate the effectiveness of using text messaging as a means to collect data for a medical research project.
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Published:
20 December 2010 |
Keyword(s): Cellular Phone, Data Collection, Malaysia, mHealth, Research, SMS
Bexelius C et al, J Med Internet Res, 12(1)
Background:
Physical activity is associated with reduced risks of many chronic diseases. Data collected on physical activity in large epidemiological studies is often based on paper questionnaires. The validity of these questionnaires is debated, and more effective methods are needed.
Objective:
This study evaluates repeated measures of physical activity level (PAL) and the feasibility of using a Java-based questionnaire downloaded onto cell phones for collection of such data. The data obtained were compared with reference estimates based on the doubly labeled water method and indirect calorimetry (PALref).
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Published:
29 January 2010 |
Keyword(s): Cellular Phone, Chronic Diseases, Data Collection, Epidemiology, Physical Activity, Sweden
Tomlinson, Mark et al, BMC Medical Informatics and Decision Making, 9(1)
Background
To investigate the feasibility, the ease of implementation, and the extent to which community health workers with little experience of data collection could be trained and successfully supervised to collect data using mobile phones in a large baseline survey.
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Published:
23 December 2009 |
Keyword(s): Benefits, Data Collection, Mobile phones, Mobile Technology, South-Africa, Web
Aanensen, David M. et al, PLoS ONE, 4(9)
Background
Epidemiologists and ecologists often collect data in the field and, on returning to their laboratory, enter their data into a database for further analysis. The recent introduction of mobile phones that utilise the open source Android operating system, and which include (among other features) both GPS and Google Maps, provide new opportunities for developing mobile phone applications, which in conjunction with web applications, allow two-way communication between field workers and their project databases.
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Published:
16 September 2009 |
Keyword(s): Cellular Phone, Data Collection, Epidemiology, GPS, Open Source
Haller, Guy et al, J Am Med Inform Assoc, 16(5)
Objective
To compare users’ speed, number of entry errors and satisfaction in using two current devices for electronic data collection in clinical research: handheld and laptop computers.
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Published:
30 June 2009 |
Keyword(s): Accuracy, Clinical Research, Data Collection, Handheld, Laptop, Trial
Yu, Ping et al, International Journal of Medical Informatics, 78(8)
Background and purpose
EpiData and Epi Info are often used together by public health agencies around the world, particularly in developing countries, to meet their needs of low-cost public health data management; however, the current open source data management technology lacks a mobile component to meet the needs of mobile public health data collectors. The goal of this project is to explore the opportunity of filling this gap through developing and trial of a personal digital assistant (PDA) based data collection/entry system. It evaluated whether such a system could increase efficiency and reduce data transcription errors for public surveillance data collection in developing countries represented by Fiji.
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Published:
5 March 2009 |
Keyword(s): Cost-Benefit Analysis, Data Collection, Disease Surveillance, Handheld, PDA, Public Health, Randomized Controlled Trials
Richesson, Rachel L. et al, J Med Syst, Published online: 3 April 2009
The National Institutes of Health has proposed a roadmap for clinical research. Test projects of this roadmap include centralized data management for distributed research, the harmonization of clinical and research data, and the use of data standards throughout the research process. In 2003, RxNorm was named as a standard for codifying clinical drugs.
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Published:
3 April 2009 |
Keyword(s): Biomedical Research, Data Collection, Data Management, Drugs, Medication Systems, RxNorm, Standards, Terminology, United States
Katz, James E. et al, International Journal of Medical Informatics, 78(2)
A 2007 national public opinion survey of 1404 Americans revealed variations in sentiments concerning the desirability of several mobile healthcare technologies based on RFID. The survey appears to be the first reasonably national public opinion survey of US adults concerning their attitudes towards mobile healthcare technology.
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Published:
10 July 2008 |
Keyword(s): Applications, Cellular Phone, Consumer Satisfaction, Data Collection, Healthcare Technology, Medical Informatics, mHealth, RFID, United States
Seebregts, Christopher J. et al, International Journal of Medical Informatics, Corrected Proof
Objective
Handheld computers (personal digital assistant, PDA) have the potential to reduce the logistic burden, cost, and error rate of paper-based health research data collection, but there is a lack of appropriate software. The present work describes the development and evaluation of PDACT, a Personal Data Collection Toolset (www.healthware.org/pdact/index.htm) for the Palmâ„¢ Pilot handheld computer for interviewer-administered and respondent-administered data collection.
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Published:
19 January 2009 |
Keyword(s): Data Collection, Electronic Health Records, Handheld, Personal Digital Assistant, Research, Software
Idriss, Shereene Z. et al, Arch Dermatol. 2009;145(1)
Objective
To determine the demographics, usage patterns, attitudes, and experiences of online support site users.
Design
Online survey.
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Published:
January 2009 |
Keyword(s): Data Collection, Education, Internet, Online Communities, Psoriasis, Quality of Life, Self-Help Groups, Social Networks, Social Support, United States
Reti, Shane R., J Am Med Inform Assoc, 16(1)
Personal health records (PHR) are a modern health technology with the ability to engage patients more fully in their healthcare. Despite widespread interest, there has been little discussion around PHR governance at an organizational level. We develop a governance model and compare it to the practices of some of the early PHR adopters, including hospitals and ambulatory care settings, insurers and health plans, government departments, and commercial sectors.
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Published:
24 October 2008 |
Keyword(s): Ambulatory Care, Data Collection, Electronic Health Records, Hospital Information Systems, Medical Records, Patient Record Access, United States
Kummervold PE et al, J Med Internet Res, 10(4)
Background:
In the last decade, the number of Internet users worldwide has dramatically increased. People are using the Internet for various health-related purposes. It is important to monitor such use as it may have an impact on the individual’s health and behavior, patient-practitioner roles, and on general health care provision.
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Published:
17 November 2008 |
Keyword(s): Automation, Consumer Health Information, Data Collection, e-Mail, Europe, Health Education, Information Services, Internet, Literacy, Patient Education, Survey, Telemedicine
Mitiku, Tezeta F., and Karen Tu, Healthcare Quarterly, 11(4)
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.
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Published:
2008 |
Keyword(s): Canada, Data Collection, De-identify, Electronic Health Records, Electronic Medical Records, Primary Care
Ash JS et al, J Am Med Inform Assoc, 14(4)
Background:
Computerized provider order entry (CPOE) systems can help hospitals improve health care quality, but they can also introduce new problems. The extent to which hospitals experience unintended consequences of CPOE, which include more than errors, has not been quantified in prior research.
Objective:
To discover the extent and importance of unintended adverse consequences related to CPOE implementation in U.S. hospitals.
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Published:
25 April 2007 |
Keyword(s): CPOE, Data Collection, Decision Support Systems, Failure, Hospital Administration, Hospitals, Workflow
