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1.
Tijdschr Gerontol Geriatr ; 48(5): 195-202, 2017 Oct.
Article in Dutch | MEDLINE | ID: mdl-28884457

ABSTRACT

Psychotropic drugs (hypno-sedatives, antidepressants and antipsychotics) are commonly used in the older population. On the long term, psychotropic drug use in older persons is associated with several negative functional outcomes such as an increased risk of falls. Gradual withdrawal of psychotropic drugs in older persons is feasible and leads to a significant reduction of falls. Both withdrawal of psychotropic drugs as well as the initiation of appropriate treatment with psychotropic drugs requires knowledge, consultation and cooperation between disciplines and a mentality change among healthcare professionals. In order to inform and support healthcare professionals, the Centre of Expertise for Fall and Fracture Prevention Flanders developed three clinical practice algorithms for the appropriate use of psychotropic drugs in older persons with high risk of falls and a fact sheet with background information.


Subject(s)
Accidental Falls/prevention & control , Algorithms , Psychotropic Drugs/adverse effects , Accidental Falls/statistics & numerical data , Aged , Female , Humans , Male , Risk Factors
2.
Eur J Clin Pharmacol ; 51(5): 355-8, 1997.
Article in English | MEDLINE | ID: mdl-9049574

ABSTRACT

OBJECTIVE: A randomised, controlled clinical trial was performed to study the long-term effect of gradual withdrawal from benzodiazepines on the daily functioning of residents of homes for the elderly. The planned sample size was not achieved due to recruitment and follow-up problems. RESULTS: The results in this small sample nevertheless suggest that gradual withdrawal from benzodiazepines is possible in residents of homes for the elderly, and that it can have a positive effect on their daily functioning. No major withdrawal symptoms were observed, although there was a decrease in sleep quality during withdrawal. CONCLUSION: The findings are promising for further research, but researchers should anticipate the problems inherent in executing a trial with institutionalised elderly subjects.


Subject(s)
Benzodiazepines/administration & dosage , Substance Withdrawal Syndrome , Aged , Aged, 80 and over , Cognition/drug effects , Double-Blind Method , Drug Utilization , Feasibility Studies , Female , Homes for the Aged , Humans , Male , Practice Patterns, Physicians' , Sleep Initiation and Maintenance Disorders/drug therapy , Time Factors
3.
Tijdschr Gerontol Geriatr ; 26(6): 253-8, 1995 Dec.
Article in Dutch | MEDLINE | ID: mdl-8553435

ABSTRACT

The Dutch Behaviour Observation Scale-Geriatrics (GOS-G) is designed to give a detailed description of the functioning of geriatric patients. This article reports the psychometric properties of the GOS-G for use in homes for the elderly. Analysed were data on 71 residents of 11 homes (they participated in a study on withdrawal of benzodiazepines). They were free of serious physical and psychological complaints. For 55 persons from 10 different homes the observation scale was filled out by two different care takers at three different occasions: twice at the start of the study with a time interval of one to three weeks, and once more after eight months. Sixteen residents from another rest home were evaluated with the GOS-G by two different care takers at one occasion. The findings in this selective sample suggest the total scale to be a reliable and valid measure of the daily functioning in homes for the elderly. Moreover, the total scale appears sensitive to change. The scores on the subscales 'psychotic behaviour' and 'disoriented behaviour' were unreliable. Observation of a more heterogeneous and larger sample is needed to confirm the usefulness of the GOS-G in homes for the elderly.


Subject(s)
Aged/psychology , Geriatric Assessment , Neuropsychological Tests , Social Behavior , Activities of Daily Living , Aged, 80 and over , Female , Humans , Male , Nursing Homes , Reproducibility of Results , Sensitivity and Specificity
4.
Med Care ; 33(3): 297-310, 1995 Mar.
Article in English | MEDLINE | ID: mdl-7861831

ABSTRACT

Involving patients in their health care decisions improves patient satisfaction and outcomes, but can be costly because of the materials and time needed to discuss the many issues that constitute a medical problem. The authors present a framework for identifying the minimum data needed on patient preferences for accurate medical decision making. The method is illustrated for the decision of whether patients with end-stage renal disease should undergo short or long hemodialysis treatments. The value of health states to patients was modeled as a function of six outcomes: survival, uremic symptoms, hospital days per year, the inconvenience associated with long dialysis treatment duration, presence of hypotension during dialysis, and presence of other symptoms during dialysis. The relative importance of each outcome was characterized in a value function by weights referred to as preference-scaling factors. These factors were varied at random over a uniform distribution to simulate different patterns of patient preferences on the six outcomes. The decision model's recommendation was recorded for each simulation. Classification and regression-tree (CART) and stepwise logistic regression analyses were applied to these recommendations to determine the scaling-factor levels that predict short or long treatments. Knowledge of scaling factors on only the inconvenience of long dialysis treatment duration, the worst alive state of health on hemodialysis, and presence of hypotension identified the correct treatment in more than 97% of simulations. Fifty-five patients undergoing hemodialysis were then surveyed for their scaling factors on the six dimensions of well-being. When patients' scaling factors were applied to the predictive rule generated by CART using simulated scaling factors, more than 94% of treatment decisions were classified correctly--sensitivity and specificity of predicting long dialysis were 89% and 100%, respectively. These statistical techniques applied to results of a decision model help identify the minimum data needed on patient preferences to involve patients in efficient and accurate decisions about their health care.


Subject(s)
Decision Support Techniques , Patient Participation/statistics & numerical data , Patient Satisfaction/statistics & numerical data , Renal Dialysis/statistics & numerical data , Adult , California , Computer Simulation , Female , Health Status , Humans , Kidney Failure, Chronic/psychology , Kidney Failure, Chronic/therapy , Male , Middle Aged , Renal Dialysis/psychology , Sensitivity and Specificity
5.
Eur J Clin Pharmacol ; 46(6): 501-5, 1994.
Article in English | MEDLINE | ID: mdl-7995315

ABSTRACT

In order to measure the effect of industry-independent information on the prescribing of benzodiazepines in general practice, 128 primary practitioners were randomly allocated to three intervention groups after stratification by year of graduation. One third of the participating physicians were forwarded written information about the indications and limitations of benzodiazepines, another third received both written and oral information, and the remaining third (the control group) obtained no information at all. A comparison of the number of benzodiazepines prescribed per 100 patient contacts with prescription before and after the intervention showed an average decrease of 3% in the control group, of 14% in physicians who received only written information, and of 24% in physicians who were given additional oral information. Post hoc pair-wise comparisons revealed a significant difference at the 1% level in the number of benzodiazepines prescribed between physicians who received both written and oral information and the control group. A follow-up survey conducted 4 weeks after the intervention showed that the oral information campaign positively affected physicians' attitudes about the value of oral drug information from an industry-independent source.


Subject(s)
Benzodiazepines/therapeutic use , Drug Utilization , Family Practice , Drug Industry , Drug Information Services , Female , Follow-Up Studies , Humans , Male
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