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Biomedical subjects

J J Forsström

Publications and source records attributed to J J Forsström.

17 recordsLinked to original sources
PubMed1999

Considerations on the quality of medical software and information services.

Fast developments in information and communication technology have made it possible to develop new services for citizens. One of the most interesting areas is health care. Medical knowledge is usually valid all over the world that makes the market global. Information services and decision support software are becoming important tools for medical professionals but also ordinary citizens are interested in health related information. It has been estimated that by the year 2010 the turnover of health care telematics industry may be close to that of the drug industry today. The nature of this global information industry is very different from any industry in history. Since there are no frontiers, no clear products and no shops in the information market, it is difficult to develop any effective legislation. However, the history of medicine has shown that health care sector cannot be free from regulation without risking citizens' health. The huge commercial potential of the Internet has already been used to promote products and services that have no proven effect on health and that may sometimes be even dangerous. In this paper we discuss the needs and possibilities to assess the quality of medical decision support software and information services. For brevity the terms medical software and medical knowledge are used, but the issues also relate to informatics systems used by any health professional, and to computerised systems used to schedule care or to organise record systems.

Decision Support Systems, Clinical↗
PubMed1998

Methodology for security development of an electronic prescription system.

Data security is an essential requirement in all health care applications. Developers of medical information systems should utilize the existing security development and evaluation methods to foresee as many of the technical and human factors that may endanger data security as possible and apply appropriate precautions. Modern smart card technology facilitates the building of robust security framework for interorganizational shared care systems. In this article, we describe the way we utilized the existing security evaluation criteria in developing the security concept of our electronic prescription system.

Clinical Pharmacy Information Systems↗
PubMed1997

Computerized monitoring of potentially interfering medication in thyroid function diagnostics.

OBJECTIVE: Many drugs are known to affect the results of laboratory tests. This may cause problems in the interpretation of clinical laboratory data and lead to wrong diagnoses, unnecessary further tests and additional costs. A computerized monitoring system of potential drug effects on laboratory tests was developed in Turku University Central Hospital. In the present study the incidence and nature of potentially interfering drug effects in thyroid function diagnostics was examined in order to ease the clinical implementation of the system. METHODS: Computerized medication data of 754 hospital in-patients whose thyroid function was tested were combined with a knowledge base of drug effects on laboratory tests. All medications that potentially affected the levels of serum thyrotropin or free thyroxin in study patients were detected. RESULTS: 40% (292 of 735) of the patients tested for thyrotropin and 32% (107 of 333) of the patients tested for free thyroxin received potentially interfering medication during the tests. The most common potentially interfering medication was acetylsalicylic acid, but the daily dose was usually low, 100 mg. CONCLUSIONS: The coincidence of potentially interfering medication and thyroid function tests was substantial. On-line hints of drug effects on thyroid function tests might offer valuable decision support to clinicians, but further development of the system is needed to regulate the prevalence of warnings into a clinically optimal level.

Aspirin↗
PubMed1997

A medication database--a tool for detecting drug interactions in hospital.

OBJECTIVE: Drug interactions may lead to life-threatening injuries. More often, however, they lead to slow recovery, induce slight symptoms or result only in potential injury. Therefore, clinicians are not always aware of using potentially interacting drug combinations. An on-line alarming system of potential drug interactions was developed in Turku University Central Hospital. In the present study, we utilised the system to find out the incidence and nature of potential drug interactions occurring in a representative hospital patient population. METHODS: Computerised anatomical therapeutic chemical (ATC)-coded patient medication data of 2547 patients, treated in two internal medicine wards, were combined with an ATC-coded rule base of drug interactions. All potential drug interactions in the study population were searched for. RESULTS: A total of 326 potentially serious drug interactions were detected in the study population. The number of patients in this group was 173, i.e. 6.8% of all patients had one or several drug combinations which might have led to serious clinical consequences. Concomitant use of calcium and fluoroquinolones (decreased absorption) was the most common mistake (66 prescriptions). CONCLUSIONS: Potentially inappropriate drug combinations seem to occur frequently. Structured and coded medication data can be utilised efficiently to detect potential drug interactions in hospital. Computerised online monitoring and automatic alarming of potentially hazardous drug combinations might help clinicians to prescribe more safely, but further development of the system is needed to avoid unnecessary alarms.

Clinical Pharmacy Information Systems↗
PubMed1997

A PC program for automatic analysis of NMR spectrum series.

31P nuclear magnetic resonance (NMR) spectroscopy enables us to study intracellular energy metabolism noninvasively. The present work concerns the analysis of a series of 31P NMR spectra on human muscle during exercise. The spectra contain signals corresponding to certain metabolites in the sample and the aim is to identify and quantify these signals. We have written a PC program to perform this task automatically. With the program the results can be achieved substantially faster compared to operating with the spectrometer software. The methods implemented in the program and the functions of the program itself are described. Although we have focused on the 31P NMR spectrum series, the program can also be applied to other liquid state NMR spectra.

Automation↗
PubMed1997

Effects of ramipril on the hormone concentrations in serum of hypertensive patients.

The effects of the angiotensin-converting enzyme inhibitor ramipril on thirteen endocrinological tests were evaluated. These tests comprised serum follitropin, lutropin, prolactin, thyrotropin, free thyroxine, total thyroxine, free triiodothyronine, parathyrin, cortisol, testosterone, sex hormone binding globulin, androstenedione and dehydroepiandrosterone sulphate. Eleven hypertensive outpatients, 9 men and 2 women, treated at the department of internal medicine in Turku University Central Hospital, received 5 mg of ramipril once a day for the study period of four weeks. The above mentioned endocrinological tests were performed before and at the end of the ramipril treatment. Ramipril decreased the value of free thyroxine statistically significantly, p = 0.011, from the mean value of 17.1 pmol/l to the mean value of 16.0 pmol/l when measured with Amerlex-MAB* free thyroxine kit. The mean within-subject difference was -1.10 pmol/l with a 95% confidence interval of -1.87 - -0.33 pmol/l. With the AutoDELFIA free thyroxine kit and with the reference method dialysis+RIA no effect was detected. Other endocrinological tests examined were not affected by ramipril. Since the decreasing effect of ramipril on free thyroxine was detected only with Amerlex-MAB* but neither with AutoDELFIA nor with dialysis+RIA, the effect was concluded to be analytical. The underlying mechanism and the component ultimately interfering with the analysis is unknown.

Adult↗
PubMed1996

Linking patient medication data with laboratory information system.

Dozens of new drugs are taken into clinical use each year. Even if the clinicians were able to learn the most important therapeutic effects of the drugs they prescribe, they would still be unable to remember all of their minor effects. After storing patient related medication data on computerized patient records it is possible to build decision support modules which automatically remind of possible drug influences on laboratory tests and cause alarms or alerts of drug interactions. Medication profiles coded using the Anatomical Therapeutic Chemical-code (ATC-code) constitutes a valuable part of an Electronic Patient Record (EPR). In this paper, we describe the benefits of our system. By building links to commercially available drug and laboratory databases we can automatically inform clinicians on clinically relevant drug influences on laboratory test results.

Clinical Laboratory Information Systems↗
PubMed1995

Computational intelligence for laboratory information systems.

Non-linear models, such as given by neural networks and fuzzy logic, have established a good reputation for medical data analysis as computational and logical counterparts to statistical methods. Whereas multilayer perceptrons perform well with large data sets, a combination of neural learning together with fuzzy logical network interpretations provides a network reduction well suited for smaller data sets. The aim of this paper is to present an approach to neural fuzzy systems data analysis and knowledge acquisition in laboratory information systems. We also describe a software system, DiagaiD, which provides an analysis and development workbench involving laboratory data.

Clinical Laboratory Information Systems↗
PubMed1995

Using data preprocessing and single layer perceptron to analyze laboratory data.

During daily work in hospitals a large amount of clinical data is produced each day. Totally computerized patient records are not yet widely used but a large part of essential information is already stored on computer files. These include laboratory test results, diagnoses, codes for operations, codes of histopathological diagnoses and maybe even the patient's medication. Accordingly, these databases include much clinical knowledge that would be useful for clinicians. Laboratories try to support clinicians by producing reference values for laboratory tests. It is, of course, necessary information but, however, it does not give very much information about the weight of evidence that an abnormal laboratory test will give in special clinical settings. We have developed a software package - DiagaiD - in order to build a smart link between patient databases and clinicians. It utilizes neural network-based machine learning techniques and can produce decision support which meets the special needs of clinicians. From example cases it can learn clinically relevant transformations from original numeric values to logical values. By using data transformation together with a single layer perceptron it is possible to build nonlinear models from a set of preclassified example cases. In this paper, we use two small datasets to show how this scheme works in the diagnosis of acute appendicitis and in the diagnosis of myocardial infarction. Results are compared with those obtained using logistic regression or backpropagation neural networks. The performance of our neuro-fuzzy tool seemed to be slightly better in these two materials but the differences did not reach statistical significance.

Appendicitis↗
PubMed1995

Application of neural networks to the ranking of perinatal variables influencing birthweight.

In this paper we compare Multi-Layer Perceptrons (a neural network type) with Multivariate Linear Regression in predicting birthweight from nine perinatal variables which are thought to be related. Results show, that seven of the nine variables, i.e., gestational age, mother's body-mass index (BMI), sex of the baby, mother's height, smoking, parity and gravidity, are related to birthweight. We found no significant relationship between birthweight and each of the two variables, i.e., maternal age and social class.

Age Factors↗
PubMed1995

Artificial neural networks for decision support in clinical medicine.

Connectionist models such as neural networks are alternatives to linear, parametric statistical methods. Neural networks are computer-based pattern recognition methods with loose similarities with the nervous system. Individual variables of the network, usually called 'neurones', can receive inhibitory and excitatory inputs from other neurones. The networks can define relationships among input data that are not apparent when using other approaches, and they can use these relationships to improve accuracy. Thus, neural nets have substantial power to recognize patterns even in complex datasets. Neural network methodology has outperformed classical statistical methods in cases where the input variables are interrelated. Because clinical measurements usually derive from multiple interrelated systems it is evident that neural networks might be more accurate than classical methods in multivariate analysis of clinical data. This paper reviews the use of neural networks in medical decision support. A short introduction to the basics of neural networks is given, and some practical issues in applying the networks are highlighted. The current use of neural networks in image analysis, signal processing and laboratory medicine is reviewed. It is concluded that neural networks have an important role in image analysis and in signal processing. However, further studies are needed to determine the value of neural networks in the analysis of laboratory data.

Clinical Medicine↗
PubMed1995

Coding drug effects on laboratory tests for health care information systems.

Drugs interfere with laboratory diagnostics. This interference is not only confusing for clinicians but may lead to wrong diagnoses or treatments as well as unnecessary further tests. However, at the moment the drug-laboratory interferences are usually ignored in patient care because clinicians do not know or remember these properties of drugs. In Turku University Central Hospital we are now able to bring this information automatically available for clinicians by using a computerized system for linking individual patient medication data with laboratory information system. For this purpose, we are building a rule base containing the effects of drugs on laboratory tests. In order that the rule base would give the maximum benefit for all users, even other hospitals, the data included have to be classified and coded properly taking into account the various requirements and needs of all users. In this paper we introduce a coding scheme for classification and coding of drug effects on laboratory tests.

Classification↗
PubMed1994

Phospholipase A2, C-reactive protein, and white blood cell count in the diagnosis of acute appendicitis.

We compared the predictive value of determining group II phospholipase A2 (PLA2) in serum for diagnosing acute appendicitis with the predictive values of white blood cell count (WBC) and measurement of C-reactive protein (CRP). In this prospective study, we included 186 patients who were undergoing appendectomy after clinical diagnoses of acute appendicitis. The performance of each test was measured by receiver-operating characteristic curves. WBC was the test of choice in diagnosing uncomplicated acute appendicitis. However, in contrast to CRP and PLA2, which increased in patients with protracted inflammation, there was not a concomitant increase in WBC. Therefore, especially CRP, but also PLA2, were better indicators of appendiceal perforation or abscess formation than was WBC. Increased WBC, CRP, and PLA2 values did not unequivocally corroborate the clinical suspicion of appendicitis, but if all three values were within normal limits, acute appendicitis could be excluded with a 100% predictive value. PLA2 values showed a highly significant correlation with CRP but not with WBC values, which supports the view that PLA2 represents an acute-phase reactant.

Acute Disease↗