39 research outputs found
Suicide-related behaviors in older patients with new anti-epileptic drug use: data from the VA hospital system
<p>Abstract</p> <p>Background</p> <p>The U.S. Food and Drug Administration (FDA) recently linked antiepileptic drug (AED) exposure to suicide-related behaviors based on meta-analysis of randomized clinical trials. We examined the relationship between suicide-related behaviors and different AEDs in older veterans receiving new AED monotherapy from the Veterans Health Administration (VA), controlling for potential confounders.</p> <p>Methods</p> <p>VA and Medicare databases were used to identify veterans 66 years and older, who received a) care from the VA between 1999 and 2004, and b) an incident AED (monotherapy) prescription. Previously validated ICD-9-CM codes were used to identify suicidal ideation or behavior (suicide-related behaviors cases), epilepsy, and other conditions previously associated with suicide-related behaviors. Each case was matched to controls based on prior history of suicide-related behaviors, year of AED prescription, and epilepsy status.</p> <p>Results</p> <p>The strongest predictor of suicide-related behaviors (N = 64; Controls N = 768) based on conditional logistic regression analysis was affective disorder (depression, anxiety, or post-traumatic stress disorder (PTSD); Odds Ratio 4.42, 95% CI 2.30 to 8.49) diagnosed before AED treatment. Increased suicide-related behaviors were not associated with individual AEDs, including the most commonly prescribed AED in the US - phenytoin.</p> <p>Conclusion</p> <p>Our extensive diagnostic and treatment data demonstrated that the strongest predictor of suicide-related behaviors for older patients newly treated with AED monotherapy was a previous diagnosis of affective disorder. Additional, research using a larger sample is needed to clearly determine the risk of suicide-related behaviors among less commonly used AEDs.</p
The effect of clinician-patient alliance and communication on treatment adherence in mental health care: a systematic review
Background
Nonadherence to mental health treatment incurs clinical and economic burdens. The clinician-patient alliance, negotiated through clinical interaction, presents a critical intervention point. Recent medical reviews of communication and adherence behaviour exclude studies with psychiatric samples. The following examines the impact of clinician-patient alliance and communication on adherence in mental health, identifying the specific mechanisms that mobilise patient engagement.
Methods
In December 2010, a systematic search was conducted in Pubmed, PsychInfo, Web of Science, Cochrane Library, Embase and Cinahl and yielded 6672 titles. A secondary hand search was performed in relevant journals, grey literature and reference.
Results
23 studies met the inclusion criteria for the review. The methodological quality overall was moderate. 17 studies reported positive associations with adherence, only four of which employed intervention designs. 10 studies examined the association between clinician-patient alliance and adherence. Subjective ratings of clinical communication styles and messages were assessed in 12 studies. 1 study examined the association between objectively rated communication and adherence. Meta-analysis was not possible due to heterogeneity of methods. Findings were presented as a narrative synthesis.
Conclusions
Clinician-patient alliance and communication are associated with more favourable patient adherence. Further research of observer rated communication would better facilitate the application of findings in clinical practice. Establishing agreement on the tasks of treatment, utilising collaborative styles of communication and discussion of treatment specifics may be important for clinicians in promoting cooperation with regimens. These findings align with those in health communication. However, the benefits of shared decision making for adherence in mental health are less conclusive than in general medicine
Participation of older newly-diagnosed cancer patients in an observational prospective pilot study: an example of recruitment and retention
<p>Abstract</p> <p>Background</p> <p>There have been few prospective observational studies which recruited older newly-diagnosed cancer patients, and of these only some have reported information on the number needed to screen to recruit their study sample, and the number and reasons for refusal and drop-out. This paper reports on strategies to recruit older newly-diagnosed cancer patients prior to treatment into an observational prospective pilot study and to retain them during a six-month period.</p> <p>Methods</p> <p>Medical charts of all patients in the Segal Cancer Centre aged 65 and over were screened and evaluated for inclusion. Several strategies to facilitate recruitment and retention were implemented. Reasons for exclusion, refusal and loss to follow-up were recorded. Descriptive statistics were used to report the reasons for refusal and loss to follow-up. A non-response analysis using chi-square tests and t-tests was conducted to compare respondents to those who refused to participate and to compare those who completed the study to those who were lost to follow-up. A feedback form with open-ended questions was administered following the last interview to obtain patient's opinions on the length of the interviews and conduct of this pilot study.</p> <p>Results</p> <p>3060 medical charts were screened and 156 eligible patients were identified. Of these 112 patients participated for a response rate of 72%. Reasons for refusal were: feeling too anxious (40%), not interested (25%), no time (12.5%), too sick (5%) or too healthy (5%) or other reasons (5%). Ninety-one patients participated in the six-month follow-up (retention 81.3%), seven patients refused follow-up (6.2%) and fourteen patients died (12.5%) during the course of the study. The median time to conduct the baseline interview was 45 minutes and 57% of baseline interviews were conducted at home. Most patients enjoyed participation and only five felt that the interviews were too long.</p> <p>Conclusion</p> <p>It was feasible to recruit newly-diagnosed cancer patients prior to treatment although it required considerable time and effort. Once patients were included, the retention rate was high despite the fact that most were undergoing active cancer treatment.</p
Sydney epilepsy incidence study to measure illness consequences: the SESIMIC observational epilepsy study protocol
Systematic review on quality control for drug management programs: Is quality reported in the literature?
<p>Abstract</p> <p>Background</p> <p>Maintaining quality of care while managing limited healthcare resources is an ongoing challenge in healthcare. The objective of this study was to evaluate how the impact of drug management programs is reported in the literature and to identify potentially existing quality standards.</p> <p>Methods</p> <p>This analysis relates to the published research on the impact of drug management on economic, clinical, or humanistic outcomes in managed care, indemnity insurance, VA, or Medicaid in the USA published between 1996 and 2007. Included articles were systematically analyzed for study objective, study endpoints, and drug management type. They were further categorized by drug management tool, primary objective, and study endpoints.</p> <p>Results</p> <p>None of the 76 included publications assessed the overall quality of drug management tools. The impact of 9 different drug management tools used alone or in combination was studied in pharmacy claims, medical claims, electronic medical records or survey data from either patient, plan or provider perspective using an average of 2.1 of 11 possible endpoints. A total of 68% of the studies reported the impact on plan focused endpoints, while the clinical, the patient or the provider perspective were studied to a much lower degree (45%, 42% and 12% of the studies). Health outcomes were only accounted for in 9.2% of the studies.</p> <p>Conclusion</p> <p>Comprehensive assessment of quality considering plan, patient and clinical outcomes is not yet applied. There is no defined quality standard. Benchmarks including health outcomes should be determined and used to improve the overall clinical and economic effectiveness of drug management programs.</p