liu.seSearch for publications in DiVA
Change search
Link to record
Permanent link

Direct link
BETA
Gill, Hans
Publications (10 of 52) Show all publications
Hanberger, H., Arman, D., Gill, H., Jindrák, V., Kalenic, S., Kurcz, A., . . . Walther, S. M. (2009). Surveillance of microbial resistance in European Intensive Care Units: a first report from the Care-ICU programme for improved infection control. Intensive Care Medicine, 35(1), 91-100
Open this publication in new window or tab >>Surveillance of microbial resistance in European Intensive Care Units: a first report from the Care-ICU programme for improved infection control
Show others...
2009 (English)In: Intensive Care Medicine, ISSN 0342-4642, E-ISSN 1432-1238, Vol. 35, no 1, p. 91-100Article in journal (Refereed) Published
Abstract [en]

Purpose: To report initial results from a European ICU surveillance programme focussing on antibiotic consumption, microbial resistance and infection control.

Methods: Thirty-five ICUs participated during 2005. Microbial resistance, antibiotic consumption and infection control stewardship measures were entered locally into a web-application. Results were validated locally, aggregated by project leaders and fed back to support local audit and benchmarking.

Results: Median (range) antibiotic consumption was 1,254 (range 348–4,992) DDD per 1,000 occupied bed days. The proportion of MRSA was median 11.6% (range 0–100), for ESBL phenotype of E. coli and K. pneumoniae 3.9% (0–80) and 14.3% (0–77.8) respectively, and for carbapenem-resistant P. aeruginosa 22.5% (0–100). Screening on admission for alert pathogens was commonly omitted, and there was a lack of single rooms for isolation.

Conclusions: The surveillance programme demonstrated wide variation in antibiotic consumption, microbial resistance and infection control measures. The programme may, by providing rapid access to aggregated results, promote local and regional audit and benchmarking of antibiotic use and infection control practices.

Keywords
Intensive care, Antibiotic consumption, Microbial resistance, Infection control
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-12628 (URN)10.1007/s00134-008-1237-y (DOI)
Note
The original publication is available at www.springerlink.com: Håkan Hanberger, Dilek Arman, Hans Gill, Vlastimil Jindrák, Smilja Kalenic, Andrea Kurcz, Monica Licker, Paul Naaber, Elizabeth A. Scicluna, Václav Vanis and Sten M. Walther, Surveillance of microbial resistance in European Intensive Care Units: a first report from the Care-ICU programme for improved infection control, 2009, (35), 1, 91-100, Intensive Care Medicine. Copyright: Springer-Verlag, www.springerlink.com Available from: 2008-09-19 Created: 2008-09-19 Last updated: 2017-12-14
Erlandsson, M., Gill, H., Nilsson, L. E., Walther, S., Giske, C. G., Jonas, D., . . . Nordlinder, D. (2008). Antibiotic susceptibility patterns and clones of Pseudomonas aeruginosa in Swedish ICUs. Scandinavian Journal of Infectious Diseases, 40(6-7), 487-494
Open this publication in new window or tab >>Antibiotic susceptibility patterns and clones of Pseudomonas aeruginosa in Swedish ICUs
Show others...
2008 (English)In: Scandinavian Journal of Infectious Diseases, ISSN 0036-5548, E-ISSN 1651-1980, Vol. 40, no 6-7, p. 487-494Article in journal (Refereed) Published
Abstract [en]

Pseudomonas aeruginosa is 1 of the bacteria most adaptive to anti-bacterial treatment. Previous studies have shown nosocomial spread and transmission of clonal strains of P. aeruginosa in European hospitals. In this study we investigated antibiotic susceptibility and clonality in 101 P. aeruginosa isolates from 88 patients admitted to 8 Swedish ICUs during 2002. We also compared phenotypes and genotypes of P. aeruginosa and carried out cluster analysis to determine if phenotypic data can be used for surveillance of clonal spread. All isolates were collected on clinical indication as part of the NPRS II study in Sweden and were subjected to AFLP analysis for genotyping. 68 isolates with unique genotypes were found. Phenotyping was performed using MIC values for 5 anti-pseudomonal agents. Almost 6% of the isolates were multi-drug resistant (MDR), and this figure rose to almost 8% when intermediate isolates were also included. We found probable clonal spread in 9 cases, but none of them was found to be an MDR strain. Phenotypical cluster analysis produced 40 clusters. Comparing partitions did not demonstrate any significant concordance between the typing methods. The conclusion of our study is that cross-transmission and clonal spread of MDR P. aeruginosa does not present a clinical problem in Swedish ICUs, but probable cross-transmission of non-MDR clones indicate a need for improved hygiene routines bedside. The phenotype clusters were not concordant with genotype clusters, and genotyping is still recommended for epidemiological tracking.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-12666 (URN)10.1080/00365540701864641 (DOI)
Available from: 2007-10-18 Created: 2007-10-18 Last updated: 2017-12-14
Petersson, H., Gill, H. & Åhlfeldt, H. (2008). Improving Inter-Rater Reliability through Coding Scheme Reorganization: Managing Signs and Symptoms. In: The First Conference on Text and Data Mining of Clinical Documents Louhi08,2008 (pp. 54). Turku: TUCS General Publications
Open this publication in new window or tab >>Improving Inter-Rater Reliability through Coding Scheme Reorganization: Managing Signs and Symptoms
2008 (English)In: The First Conference on Text and Data Mining of Clinical Documents Louhi08,2008, Turku: TUCS General Publications , 2008, p. 54-Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Turku: TUCS General Publications, 2008
Keywords
medical informatics
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-42974 (URN)70359 (Local ID)70359 (Archive number)70359 (OAI)
Available from: 2009-10-10 Created: 2009-10-10
Razavi, A. R., Gill, H., Åhlfeldt, H. & Shahsavar, N. (2008). Non-compliance with a postmastectomy radiotherapy guideline: Decision tree and cause analysis. BMC Medical Informatics and Decision Making, 8(41)
Open this publication in new window or tab >>Non-compliance with a postmastectomy radiotherapy guideline: Decision tree and cause analysis
2008 (English)In: BMC Medical Informatics and Decision Making, ISSN 1472-6947, E-ISSN 1472-6947, Vol. 8, no 41Article in journal (Refereed) Published
Abstract [en]

Background: The guideline for postmastectomy radiotherapy (PMRT), which is prescribed to reduce recurrence of breast cancer in the chest wall and improve overall survival, is not always followed. Identifying and extracting important patterns of non-compliance are crucial in maintaining the quality of care in Oncology.

Methods: Analysis of 759 patients with malignant breast cancer using decision tree induction (DTI) found patterns of non-compliance with the guideline. The PMRT guideline was used to separate cases according to the recommendation to receive or not receive PMRT. The two groups of patients were analyzed separately. Resulting patterns were transformed into rules that were then compared with the reasons that were extracted by manual inspection of records for the non-compliant cases.

Results: Analyzing patients in the group who should receive PMRT according to the guideline did not result in a robust decision tree. However, classification of the other group, patients who should not receive PMRT treatment according to the guideline, resulted in a tree with nine leaves and three of them were representing non-compliance with the guideline. In a comparison between rules resulting from these three non-compliant patterns and manual inspection of patient records, the following was found:

In the decision tree, presence of perigland growth is the most important variable followed by number of malignantly invaded lymph nodes and level of Progesterone receptor. DNA index, age, size of the tumor and level of Estrogen receptor are also involved but with less importance. From manual inspection of the cases, the most frequent pattern for non-compliance is age above the threshold followed by near cut-off values for risk factors and unknown reasons.

Conclusion: Comparison of patterns of non-compliance acquired from data mining and manual inspection of patient records demonstrates that not all of the non-compliances are repetitive or important. There are some overlaps between important variables acquired from manual inspection of patient records and data mining but they are not identical. Data mining can highlight non-compliance patterns valuable for guideline authors and for medical audit. Improving guidelines by using feedback from data mining can improve the quality of care in oncology.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-15222 (URN)
Note
Original publication: Amir R Razavi, Hans Gill, Hans Åhlfeldt and Nosrat Shahsavar, Non-compliance with a postmastectomy radiotherapy guideline: Decision tree and cause analysis, 2008, BMC Medical Informatics and Decision Making, (8), 41.http://dx.doi.org/10.1186/1472-6947-8-41. Copyright: The authorsAvailable from: 2008-10-24 Created: 2008-10-24 Last updated: 2017-12-14Bibliographically approved
Razavi, A. R., Gill, H., Åhlfeldt, H. & Shahsavar, N. (2007). A Data Mining Approach to Analyze Non-compliance with a Guideline for the Treatment of Breast Cancer. Studies in Health Technology and Informatics, 129, 591-597
Open this publication in new window or tab >>A Data Mining Approach to Analyze Non-compliance with a Guideline for the Treatment of Breast Cancer
2007 (English)In: Studies in Health Technology and Informatics, ISSN 0926-9630, E-ISSN 1879-8365, Vol. 129, p. 591-597Article in journal (Refereed) Published
Abstract [en]

Postmastectomy radiotherapy (PMRT) is prescribed in order to reduce the local recurrence of breast cancer and improve overall survival. A guideline supports the trade-off between benefits and adverse effects of PMRT. However, this guideline is not always followed in practice. This study tries to find a method for revealing patterns of non-compliance between the actual treatment and the PMRT guideline.

Data from breast cancer patients admitted to Linköping University Hospital between 1990 and 2000 were analyzed in this study. Cases that were not treated in accordance with the guideline were selected and analyzed by decision tree induction (DTI). Thereafter, four resulting rules, as representations for groups of patients, were compared to the guideline.

Finding patterns of non-compliance with guidelines by means of rules can be an appropriate alternative to manual methods, i.e. a case-by-case comparison when studying very large datasets. The resulting rules can be used in a knowledge base of a guideline-based decision support system to alert when inconsistencies with the guidelines may appear.

National Category
Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:liu:diva-12709 (URN)
Available from: 2007-10-30 Created: 2007-10-30 Last updated: 2017-12-14
Razavi, A. R., Gill, H., Åhlfeldt, H. & Shahsavar, N. (2007). Data Mining Approach to Analyze Non-compliance with a Guideline for the Treatment of Breast Cancer. In: MEDINFO 2007: PROCEEDINGS OF THE 12TH WORLD CONGRESS ON HEALTH (MEDICAL) INFORMATICS, PTS 1 AND 2: . Paper presented at 12th World Congress on Health (Medical) Informatics (pp. 591-595). IOS Press
Open this publication in new window or tab >>Data Mining Approach to Analyze Non-compliance with a Guideline for the Treatment of Breast Cancer
2007 (English)In: MEDINFO 2007: PROCEEDINGS OF THE 12TH WORLD CONGRESS ON HEALTH (MEDICAL) INFORMATICS, PTS 1 AND 2, IOS Press, 2007, p. 591-595Conference paper, Published paper (Refereed)
Abstract [en]

Postmastectomy radiotherapy (PAMT) is prescribed in order to reduce the local recurrence of breast cancer and improve overall survival. A guideline supports the trade-off between benefits and adverse effects of PMRT However, this guideline is not always followed in practice. This study tries to find a method for revealing patterns of noncompliance between the actual treatment and the PMRT guideline.Data from breast cancer patients admitted to Linkoping University Hospital between 1990 and 2000 were analyzed in this study. Cases that were not treated in accordance with the guideline were selected and analyzed by decision tree induction (DTI). Thereafter, four resulting rules, as representations for groups of patients, were compared to the guideline.Finding patterns of non-compliance with guidelines by means of rules can be an appropriate alternative to manual methods, i.e. a case-by-case comparison when studying very large datasets. The resulting rules can be used in a knowledge base of a guideline-based decision support system to alert when inconsistencies with the guidelines may appear.

Place, publisher, year, edition, pages
IOS Press, 2007
Series
Studies in Health Technology and Informatics, ISSN 0926-9630
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-38015 (URN)41111 (Local ID)978-1-58603-774-1 (ISBN)41111 (Archive number)41111 (OAI)
Conference
12th World Congress on Health (Medical) Informatics
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-08-29
Fransson, G., Berkius, J., Gill, H., Kahlmeter, G., Hanberger, H. & Walther, S. (2007). Linking local microbiology databases with the Swedish Intensive Care Registry to examine impact of bacterial resistance on the critically ill.. In: Acta anaesthesiologica Scandinavica. Volume 51, Issue Supplement s118: . Paper presented at The 29th Congress of the Scandinavian Society of Anaesthesiology and Intensive Care Medicine Göteborg, Sweden 5–8 September 2007 (pp. 33-33 (Poster 25)). Malden, MA, United States: Wiley-Blackwell, 51
Open this publication in new window or tab >>Linking local microbiology databases with the Swedish Intensive Care Registry to examine impact of bacterial resistance on the critically ill.
Show others...
2007 (English)In: Acta anaesthesiologica Scandinavica. Volume 51, Issue Supplement s118, Malden, MA, United States: Wiley-Blackwell, 2007, Vol. 51, p. 33-33 (Poster 25)Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

Background and aims: Bacterial resistance to antibiotics hasemerged as an important factor influencing patient mortalityand morbidity. The overall purpose of this project is to exam-ine the impact of bacterial resistance on resource use andoutcome in the critically ill. The aims of the current report isto demonstrate that linkage of local microbiology databasesand the Swedish Intensive Care Registry (SIR) was possibleand to provide a preliminary analysis of data from a sub-group of ICU patients (chronic obstructive pulmonary dis-ease, COPD).

Methods: Admissions due to an acute exacerbation of COPDwere matched with bacteriology samples obtained 14 daysbefore ICU admission, during ICU stay and 14 days after dis-charge from ICU by linking six local microbiology databaseswith patient data in SIR. Linkage was by the patient’s uniquepersonal number and ICU admission and discharge days.

Results: We found 195 patients with median APACHE II prob-ability 0.22 (iqr 0.12–0.37), median length of stay (LOS) 46 (iqr 21–125) hours and 79% 30 day survival. Cultures from 2 weeks before (n=128), during ICU-stay (n=750) and from14 days after ICU discharge (n=228) were identified. During ICU stay airways (n=261), blood or intravascular devices (n=246) and other sites (n=243) were cultured. The totalnumber of airway cultures per patient increased linearly withlength of stay (P<0.01,r2= 0.61). Gram-negative bacteria were most common in positive airway cultures (41%) followedby Candida spp (22%), while positive blood cultures were pre-dominantly Gram-positive (71%). 30-day-mortality was 10/53 with positive and 10/29 with negative airway cultures(P=0.23).

Conclusion: Linkage of local microbiology databases and theSwedish Intensive Care Registry is possible and can generate information that may be used to examine relationships between bacterial resistance and outcomes in the critically illpatient.

Place, publisher, year, edition, pages
Malden, MA, United States: Wiley-Blackwell, 2007
Series
Acta anaesthesiologica Scandinavica, ISSN 0001-5172 ; 51
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-40367 (URN)10.1111/j.1399-6576.2007.01407.x (DOI)53165 (Local ID)53165 (Archive number)53165 (OAI)
Conference
The 29th Congress of the Scandinavian Society of Anaesthesiology and Intensive Care Medicine Göteborg, Sweden 5–8 September 2007
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2014-01-30Bibliographically approved
Hanberger, H., Burman, L., Cars, O., Erlandsson, M., Gill, H., Nilsson, L., . . . Walther, S. (2007). Low antibiotic resistance rates in Staphylococcus aureus, Escherichia coli and Klebsiella spp but not in Enterobacter spp and Pseudomonas aeruginosa: A prospective observational study in 14 Swedish ICUs over a 5-year period. Acta Anaesthesiologica Scandinavica, 51(7), 937-941
Open this publication in new window or tab >>Low antibiotic resistance rates in Staphylococcus aureus, Escherichia coli and Klebsiella spp but not in Enterobacter spp and Pseudomonas aeruginosa: A prospective observational study in 14 Swedish ICUs over a 5-year period
Show others...
2007 (English)In: Acta Anaesthesiologica Scandinavica, ISSN 0001-5172, E-ISSN 1399-6576, Vol. 51, no 7, p. 937-941Article in journal (Refereed) Published
Abstract [en]

Background: Intensive care units (ICUs) are hot zones for emergence and spread of antibiotic resistance because of frequent invasive procedures, antibiotic usage and transmission of bacteria. We report prospective data on antibiotic use and bacterial resistance from 14 academic and non-academic ICUs, participating in the ICU-STRAMA programme 1999-2003. Methods: The quantity of antibiotics delivered to each ICU was calculated as defined daily doses per 1000 occupied bed days (DDD1000). Specimens for culture were taken on clinical indications and only initial isolates were considered. Species-related breakpoints according to the Swedish Reference Group for Antibiotics were used. Antibiotic resistance was defined as the sum of intermediate and resistant strains. Results: Mean antibiotic use increased from 1245 DDD1000 in 1999 to 1510 DDD1000 in 2003 (P = 0.11 for trend). Of Staphylococcus aureus, 0-1.8% were methicillin resistant (MRSA). A presumptive extended spectrum beta-lactamase (ESBL) phenotype was found in <2.4% of Escherichia coli, based on cefotaxime susceptibility, except a peak in 2002 (4.6%). Cefotaxime resistance was found in 2.6-4.9% of Klebsiella spp. Rates of resistance among Enterobacter spp. to cefotaxime (20-33%) and among Pseudomonas aeruginosa to imipenem (22-33%) and ciprofloxacin (5-21%) showed no time trend. Conclusion: MRSA and cefotaxime-resistant E. coli and Klebsiella spp strains were few despite high total antibiotic consumption. This may be the result of a slow introduction of resistant strains into the ICUs, and good infection control. The cause of imipenem and ciprofloxacin resistance in P. aeruginosa could reflect the increased consumption of these agents plus spread of resistant clones. © 2007 The Authors.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-38187 (URN)10.1111/j.1399-6576.2007.01364.x (DOI)42370 (Local ID)42370 (Archive number)42370 (OAI)
Note
STRAM study group, ICUAvailable from: 2009-10-10 Created: 2009-10-10 Last updated: 2017-12-13
Razavi, A. R., Gill, H., Åhlfeldt, H. & Shahsavar, N. (2007). Predicting metastasis in breast cancer: comparing a decision tree with domain experts. Journal of Medical Systems, 31(4), 263-273
Open this publication in new window or tab >>Predicting metastasis in breast cancer: comparing a decision tree with domain experts
2007 (English)In: Journal of Medical Systems, ISSN 0148-5598, Vol. 31, no 4, p. 263-273Article in journal (Refereed) Published
Abstract [en]

Breast malignancy is the second most common cause of cancer death among women in Western countries. Identifying high-risk patients is vital in order to provide them with specialized treatment. In some situations, such as when access to experienced oncologists is not possible, decision support methods can be helpful in predicting the recurrence of cancer. Three thousand six hundred ninety-nine breast cancer patients admitted in south-east Sweden from 1986 to 1995 were studied. A decision tree was trained with all patients except for 100 cases and tested with those 100 cases. Two domain experts were asked for their opinions about the probability of recurrence of a certain outcome for these 100 patients. ROC curves, area under the ROC curves, and calibration for predictions were computed and compared. After comparing the predictions from a model built by data mining with predictions made by two domain experts, no significant differences were noted. In situations where experienced oncologists are not available, predictive models created with data mining techniques can be used to support physicians in decision making with acceptable accuracy.

Keywords
Data mining, Decision tree induction (DTI), Breast cancer, Classification, Prediction, Domain expert, Decision support
National Category
Biomedical Laboratory Science/Technology
Identifiers
urn:nbn:se:liu:diva-12708 (URN)10.1007/s10916-007-9064-1 (DOI)
Available from: 2007-10-30 Created: 2007-10-30 Last updated: 2009-05-12
Erlandsson, M., Burman, L. G., Cars, O., Gill, H., Nilsson, L. E., Walther, S., . . . ICU-STRAMA Study Group, . (2007). Prescription of antibiotic agents in Swedish intensive care units is empiric and adequate. Scandinavian Journal of Infectious Diseases, 39(1), 63-69
Open this publication in new window or tab >>Prescription of antibiotic agents in Swedish intensive care units is empiric and adequate
Show others...
2007 (English)In: Scandinavian Journal of Infectious Diseases, ISSN 0036-5548, E-ISSN 1651-1980, Vol. 39, no 1, p. 63-69Article in journal (Refereed) Published
Abstract [en]

Since the prescription of antibiotics in the hospital setting is often empiric, particularly in the critically ill, and therefore fraught with potential error, we analysed the use of antibiotic agents in Swedish intensive care units (ICUs). We examined indications for antibiotic treatment, agents and dosage prescribed among 393 patients admitted to 23 ICUs at 7 tertiary care centres, 11 secondary hospitals and 5 primary hospitals over a 2-week period in November 2000. Antibiotic consumption was higher among ICU patients in tertiary care centres with a median of 84% (range 58-87%) of patients on antibiotics compared to patients in secondary hospitals (67%, range 35-93%) and in primary hospitals (38%, range 24-80%). Altogether 68% of the patients received antibiotics during the ICU stay compared to 65% on admission. Cefuroxime was the most commonly prescribed antibiotic before and during admission (28% and 24% of prescriptions, respectively). A date for decision to continue or discontinue antibiotic therapy was set in 21% (6/29) of patients receiving prophylaxis, in 8% (16/205) receiving empirical treatment and in 3% (3/88) when culture-based therapy was given. No correlation between antibiotic prescription and laboratory parameters such as CRP levels, leukocyte and thrombocyte counts, was found. The treatment was empirical in 64% and prophylactic in 9% of cases. Microbiological data guided prescription more often in severe sepsis (median 50%, range 40-60% of prescriptions) than in other specified forms of infection (median 32%, range 21-50%). The empirically chosen antibiotic was found to be active in vitro against the pathogens found in 55 of 58 patients (95%) with a positive blood culture. This study showed that a high proportion of ICU patients receive antimicrobial agents and, as expected, empirical-based therapy is more common than culture-based therapy. Antibiotics given were usually active in vitro against the pathogen found in blood cultures. We ascribe this to a relatively modest antibiotic resistance problem in Swedish hospitals.

National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-12665 (URN)10.1080/00365540600740504 (DOI)
Available from: 2007-10-18 Created: 2007-10-18 Last updated: 2017-12-14
Organisations

Search in DiVA

Show all publications