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The experience of linking Victorian emergency medical service trauma data
Background:
The linking of a large Emergency Medical Service (EMS) dataset with the Victorian Department of Human Services (DHS) hospital datasets and Victorian State Trauma Outcome Registry and Monitoring (VSTORM) dataset to determine patient outcomes has not previously been undertaken in Victoria. The objective of this study was to identify the linkage rate of a large EMS trauma dataset with the Department of Human Services hospital datasets and VSTORM dataset.
Methods:
The linking of an EMS trauma dataset to the hospital datasets utilised deterministic and probabilistic matching. The linking of three EMS trauma datasets to the VSTORM dataset utilised deterministic, probabilistic and manual matching.
Results:
There were 66.7% of patients from the EMS dataset located in the VEMD. There were 96% of patients located in the VAED who were defined in the VEMD as being admitted to hospital. 3.7% of patients located in the VAED could not be found in the VEMD due to hospitals not reporting to the VEMD. For the EMS datasets, there was a 146% increase in successful links with the trauma profile dataset, a 221% increase in successful links with the mechanism of injury only dataset, and a 46% increase with sudden deterioration dataset, to VSTORM when using manual compared to deterministic matching.
Conclusions:
This study has demonstrated that EMS data can be successfully linked to other health related datasets using deterministic and probabilistic matching with varying levels of success. The quality of EMS data needs to be improved to ensure better linkage success rates with other health related datasets.
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Decision Theory Applied to Image Quality Control in Radiology.
Background:
The present work aims at the application of the decision theory to radiological image quality control (QC) in diagnostic routine. The main problem addressed in the framework of decision theory is to accept or reject a film lot of a radiology service. The probability of each decision of a determined set of variables was obtained from the selected films.
Methods:
Based on a radiology service routine a decision probability function was determined for each considered group of combination characteristics. These characteristics were related to the film quality control. These parameters were also framed in a set of 8 possibilities, resulting in 256 possible decision rules. In order to determine a general utility application function to access the decision risk, we have used a simple unique parameter called r. The payoffs chosen were: diagnostic's result (correct/incorrect), cost (high/low), and patient satisfaction (yes/no) resulting in eight possible combinations.
Results:
Depending on the value of r, more or less risk will occur related to the decision-making. The utility function was evaluated in order to determine the probability of a decision. The decision was made with patients or administrators' opinions from a radiology service center.
Conclusion:
The model is a formal quantitative approach to make a decision related to the medical imaging quality, providing an instrument to discriminate what is really necessary to accept or reject a film or a film lot. The method presented herein can help to access the risk level of an incorrect radiological diagnosis decision.
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Underutilization of Information and Knowledge in
Everyday Medical Practice: Computer-based Solutions
Background:
The medical history is acknowledged as the sine qua non for quality medical care because recognizing problems is pre-requisite for managing them. Medical histories typically are incomplete and inaccurate, however. We show here that computers are a solution to this issue of information gathering about patients. Computers can be programmed to acquire more complete medical histories with greater detail across a range of acute and chronic issues than physician histories.
Methods:
Histories were acquired by physicians in the usual way and by a computer program interacting directly with patients. Decision-making of what medical issues were queried by computer were made internally by the software, including determination of the chief complaint. The selection of patients was random from admissions to the Robert-Bosch-Hospital, Stuttgart, Germany. Physician-acquired and computer-acquired histories were compared on a patient-by-patient basis for 45 patients.
Results:
The computer histories reported 160 problems not recorded in physician histories or slightly more than 3.5 problems per patient. The data show that computer histories reported problems across a range of organ systems, that the problems detected by computer but not physician histories were both acute and chronic and that the computer histories detected a significant number of issues important for preventing further morbidity.
Conclusions:
A combination of physician and computer-acquired histories, in non-emergent situations, with the latter available to the physician at the time he or she sees the patient, is a far superior method for collecting historical data than the physician interview alone.
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Construction of an odds model of coronary heart disease using published information: the Cardiovascular Health Improvement Model (CHIME)
Background:
There is a need for a new cardiovascular disease model that includes a wider range of relevant risk factors, in particular lifestyle factors, to aid targeting of interventions and improve population models of the impact of cardiovascular disease and preventive strategies. The model needs to be applicable to a wider population including different ethnic groups, different countries and to those with and without cardiovascular disease. This paper describes the construction of the Cardiovascular Health Improvement Model that aims to meet these requirements.MethodAn odds model is used. Information was taken from 2003 mortality statistics for England and Wales, the Health Survey for England 2003 and published data on relative risk in those with and without CVD and mean blood pressure values in hypertensives. The odds ratios used were taken from the INTERHEART study.
Results:
A worked example is given calculating the 10-year coronary heart disease risk for a 57 year-old non-diabetic male with no personal or family history of cardiovascular disease, who smokes 30 cigarettes a day and has a systolic blood pressure of 137 mmHg, a total cholesterol (TC) of 6.2 mmol/l, a high density lipoprotein (HDL) of 1.3 mol/l, and a body mass index of 21. He neither drinks regularly nor exercises. He can give no reliable information about his mental health or fruit and vegetable intake. His 10-year risk of CHD death is 2.47%.
Conclusion:
This paper demonstrates a method for developing a CHD risk model. Further improvements could be made to the model with additional information. The method is applicable to other causes of death.
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Are decision trees a feasible knowledge representation to guide extraction of critical information from randomized controlled trial reports?
Background:
This paper proposes the use of decision trees as the basis for automatically extracting information from published randomized controlled trial (RCT) reports. An exploratory analysis of RCT abstracts is undertaken to investigate the feasibility of using decision trees as a semantic structure. Quality-of-paper measures are also examined.
Methods:
A subset of 455 abstracts (randomly selected from a set of 7620 retrieved from Medline from 1998 – 2006) are examined for the quality of RCT reporting, the identifiability of RCTs from abstracts, and the completeness and complexity of RCT abstracts with respect to key decision tree elements. Abstracts were manually assigned to 6 sub-groups distinguishing whether they were primary RCTs versus other design types. For primary RCT studies, we analyzed and annotated the reporting of intervention comparison, population assignment and outcome values. To measure completeness, the frequencies by which complete intervention, population and outcome information are reported in abstracts were measured. A qualitative examination of the reporting language was conducted.
Results:
Decision tree elements are manually identifiable in the majority of primary RCT abstracts. 73.8% of a random subset was primary studies with a single population assigned to two or more interventions. 68% of these primary RCT abstracts were structured. 63% contained pharmaceutical interventions. 84% reported the total number of study subjects. In a subset of 21 abstracts examined, 71% reported numerical outcome values.
Conclusion:
The manual identifiability of decision tree elements in the abstract suggests that decision trees could be a suitable construct to guide machine summarisation of RCTs. The presence of decision tree elements could also act as an indicator for RCT report quality in terms of completeness and uniformity.
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Conflicting perceptions of an inter-disciplinary telemedicine project. How a successful project failed.
Background:
Information systems can play a key role in care innovations including task redesign and shared care. Many demonstration projects have presented evidence of clinical and cost effectiveness and high levels of patient satisfaction. Yet these same projects often fail to become part of every-day clinical routines. The aim of the paper is to gain insight into a common paradox that a technology can meet the criteria for success set out at the start of the project yet fail to become part of every-day clinical routines.
Methods:
We evaluated a tele-care service set up to reduce the workload of ophthalmologists. In this project optometrists, in 10 optical shops made digital images to detect patients with glaucoma which were further assessed by trained technicians in the hospital. Over a period of three years, we conducted interviews with the project team and the users about the workability of the system and its integration in practice. Beside the interviews, we analyzed record data to measure the quality of the images. We compared the qualitative accounts with these measurements.
Results:
According to our measurements, the quality of the images was at least satisfactory in 90% of the cases, i.e. the images could be used to screen the patients - reducing the workload of the ophthalmologist considerably. However, both the ophthalmologist and the optometrists became increasingly dissatisfied respectively with the perceived quality of the pictures and the perceived workload.
Through a detailed analysis of how the professionals discussed the quality of the pictures, we re-constructed how the notion of quality of the images and being a good professional were constructed and linked. The IT system transformed into a quality system and, at the same time, transformed the notions of being a good professional. While a continuous dialogue about the quality of the pictures became an emblem for the quality of care, this dialogue was hindered by the system and the way the care process was structured.
Conclusions:
To conceptualize what telemedicine does in interdisciplinary work practices, a fine-tuned analysis is needed to assess how IT systems re-shaped the social relations between professional groups. Such transformations should not be exclusively attributed to the technology itself or to the professionals working with it. Instead we need to assess these technologies through an empirically grounded study of the functioning of telemedicine.
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Pilot Study of an Interactive Voice Response System to Improve Medication Refill Compliance
Background:
Sub-optimal adherence to prescribed medications is well documented. Barriers to medication adherence include medication side effects, cost, and forgetting to take or refill medications. Interactive Voice Response (IVR) systems show promise as a tool for reminding individuals to take or refill medications. This pilot study evaluated the feasibility and acceptability of using an IVR system for prescription refill and daily medication reminders. We tested two novel features: personalized, medication-specific reminder messages and communication via voice recognition.
Methods:
Patients enrolled in a study of electronic prescribing and medication management in Quebec, Canada who were taking chronic disease-related drugs were eligible to participate. Consenting patients had their demographic, telephone, and medication information transferred to an IVR system, which telephoned patients to remind them to take mediations and/or refill their prescriptions. Facilitators and barriers of the IVR system use and acceptability of the IVR system were assessed through a structured survey and open-ended questions administered by telephone interview.
Results:
Of the 528 eligible patients who were contacted, 237 refused and 291 consented; 99 participants had started the pilot study when it was terminated because of physician and participant complaints. Thirty-eight participants completed the follow-up interview. The majority found the IVR system's voice acceptable, and did not have problems setting up the time and location of reminder calls. However, many participants experienced technical problems when called for reminders, such as incorrect time of calls and voice recognition difficulties. In addition, most participants had already refilled their prescriptions when they received the reminder calls, reporting that they did not have difficulties remembering to refill prescriptions on their own. Also, participants were not receptive to speaking to an automated voice system.
Conclusions:
IVR systems designed to improve medication compliance must address key technical and performance issues and target those individuals with reported memory difficulties or complex medication regimens in order to improve the utility of the system. Future research should also identify characteristics of medication users who are more likely to be receptive to IVR technology.
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Integrated personal health records: Transformative tools for consumer-centric care
Background:
Integrated personal health records (PHRs) offer significant potential to stimulate transformational changes in health care delivery and self-care by patients. In 2006, an invitational roundtable sponsored by Kaiser Permanente Institute, the American Medical Informatics Association, and the Agency for Healthcare Research and Quality was held to identify the transformative potential of PHRs, as well as barriers to realizing this potential and a framework for action to move them closer to the health care mainstream. This paper highlights and builds on the insights shared during the roundtable.DiscussionWhile there is a spectrum of dominant PHR models, (standalone, tethered, integrated), the authors state that only the integrated model has true transformative potential to strengthen consumers' ability to manage their own health care. Integrated PHRs through transparency of information and the capacity for iterative communications can improve the quality, completeness, depth, and accessibility of health information provided by both clinicians and patients; provide access to highly specific health knowledge for patients; ensure portability of medical records and other personal health information; and incorporate auto-population of content. Numerous factors impede widespread adoption of integrated PHRs: obstacles in the health care system/culture; issues of consumer confidence and trust; lack of technical standards for interoperability; lack of HIT infrastructure; the digital divide; uncertain value realization/ROI; and uncertain market demand. Recent efforts have led to progress on standards for integrated PHRs, and government agencies and private companies are offering different models to consumers, but substantial obstacles remain to be addressed. Immediate steps to advance integrated PHRs should include sharing existing knowledge and expanding knowledge about them, building on existing efforts, and continuing dialogue among public and private sector stakeholders. SummaryIntegrated PHRs promote active, ongoing patient collaboration in care delivery and decision making. With some exceptions, however, the integrated PHR model is still a theoretical framework for consumer-centric health care. The authors pose questions that need to be answered so that the field can move forward to realize the potential of integrated PHRs. How can integrated PHRs be more rigorously evaluated and moved from concept to widespread practical application? Would a coordinating body expedite this strategy? How can existing initiatives or new policies serve as catalysts to advance integrated PHRs?
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A new scoring system in Cystic Fibrosis: statistical tools for database analysis – a preliminary report
Background:
Cystic fibrosis is the most common fatal genetic disorder in the Caucasian population. Scoring systems for assessment of Cystic fibrosis disease severity have been used for almost 50 years, without being adapted to the milder phenotype of the disease in the 21st century. The aim of this current project is to develop a new scoring system using a database and employing various statistical tools. This study protocol reports the development of the statistical tools in order to create such a scoring system.
Methods:
The evaluation is based on the Cystic Fibrosis database from the cohort at the Royal Children's Hospital in Melbourne. Initially, unsupervised clustering of the all data records was performed using a range of clustering algorithms. In particular incremental clustering algorithms were used. The clusters obtained were characterised using rules from decision trees and the results examined by clinicians. In order to obtain a clearer definition of classes expert opinion of each individual's clinical severity was sought. After data preparation including expert-opinion of an individual's clinical severity on a 3 point-scale (mild, moderate and severe disease), two multivariate techniques were used throughout the analysis to establish a method that would have a better success in feature selection and model derivation: 'Canonical Analysis of Principal Coordinates' and 'Linear Discriminant Analysis'. A 3-step procedure was performed with (1) selection of features, (2) extracting 5 severity classes out of a 3 severity class as defined per expert-opinion and (3) establishment of calibration datasets.
Results:
(1) Feature selection: CAP has a more effective "modelling" focus than DA.(2) Extraction of 5 severity classes: after variables were identified as important in discriminating contiguous CF severity groups on the 3-point scale as mild/moderate and moderate/severe, Discriminant Function (DF) was used to determine the new groups mild, intermediate moderate, moderate, intermediate severe and severe disease. (3) Generated confusion tables showed a misclassification rate of 19.1% for males and 16.5% for females, with a majority of misallocations into adjacent severity classes particularly for males.
Conclusion:
Our preliminary data show that using CAP for detection of selection features and Linear DA to derive the actual model in a CF database might be helpful in developing a scoring system. However, there are several limitations, particularly more data entry points are needed to finalize a score and the statistical tools have further to be refined and validated, with re-running the statistical methods in the larger dataset.
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Sample size determination for bibliographic retrieval studies
Background:
Research for developing search strategies to retrieve high-quality clinical journal articles from MEDLINE is expensive and time-consuming. The objective of this study was to determine the minimal number of high-quality articles in a journal subset that would need to be hand-searched to update or create new MEDLINE search strategies for treatment, diagnosis, and prognosis studies.
Methods:
The desired width of the 95% confidence intervals (W) for the lowest sensitivity among existing search strategies was used to calculate the number of high-quality articles needed to reliably update search strategies. New search strategies were derived in journal subsets formed by 2 approaches: random sampling of journals and top journals (having the most high-quality articles). The new strategies were tested in both the original large journal database and in a low-yielding journal (having few high-quality articles) subset.
Results:
For treatment studies, if W was 10% or less for the lowest sensitivity among our existing search strategies, a subset of 15 randomly selected journals or 2 top journals were adequate for updating search strategies, based on each approach having at least 99 high-quality articles. The new strategies derived in 15 randomly selected journals or 2 top journals performed well in the original large journal database. Nevertheless, the new search strategies developed using the random sampling approach performed better than those developed using the top journal approach in a low-yielding journal subset. For studies of diagnosis and prognosis, no journal subset had enough high-quality articles to achieve the expected W (10%).
Conclusion:
The approach of randomly sampling a small subset of journals that includes sufficient high-quality articles is an efficient way to update or create search strategies for high-quality articles on therapy in MEDLINE. The concentrations of diagnosis and prognosis articles are too low for this approach.
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