Background Mortality, incidence of most diseases, and prevalence of adverse health behaviours follow an inverse gradient with social class. Many proxies for socioeconomic status (SES) exist; however, each bears a different relation to health outcomes, probably following a different aetiological pathway. Additionally, data on SES can be quite difficult to gather. Five measures of SES were compared, including a novel measure, the HOUSES index, in the prediction of self-rated health (SRH) in two Midwestern settings, Olmsted County, Minnesota, and Jackson County, Missouri. Methods Using a probability sampling design, a cross-sectional telephone survey was administered to a randomised sample of households. The questionnaire collected a variety of sociodemographic and personal health information. The dependent variable, SRH, was dichotomised into excellent/very good/good versus fair/ poor health. Information for the HOUSES index was collected through public property records and corroborated through the telephone questionnaire. Participants were parents/guardians of children aged 1–17 residing in Olmsted County (n=746) and Jackson County (n=704). Results The HOUSES index was associated with adverse SRH in Jackson County adults. All five SES measures were significant predictors in this group. Composite SES indices showed significant associations with SRH in Olmsted County adults. Conclusions The HOUSES index makes a unique contribution to the measurement of SES and prediction of health outcomes. Its utility is qualified by specific social contexts, and it should be used in concert with other SES indices.
Purpose To determine the effectiveness of a shared decision-making (SDM) tool versus guideline-informed usual care in translating evidence into primary care, and to explore how use of the tool changed patient perspectives about diabetes medication decision making. Methods In this mixed methods multicenter cluster randomized trial, we included patients with type 2 diabetes mellitus and their primary care clinicians. We compared usual care with or without a within-encounter SDM conversation aid. We assessed participant-reported decisions made and quality of SDM (knowledge, satisfaction, and decisional conflict), clinical outcomes, adherence, and observer-based patient involvement in decision-making (OPTION12-scale). We used semi-structured interviews with patients to understand their perspectives. Results We enrolled 350 patients and 99 clinicians from 20 practices and interviewed 26 patients. Use of the conversation aid increased post-encounter patient knowledge (correct answers, 52% vs. 45%, p = 0.02) and clinician involvement of patients (Mean between-arm difference in OPTION12, 7.3 (95% CI 3, 12); p = 0.003). There were no between-arm differences in treatment choice, patient or clinician satisfaction, encounter length, medication adherence, or glycemic control. Qualitative analyses highlighted differences in how clinicians involved patients in decision making, with intervention patients noting how clinicians guided them through conversations using factors important to them. Conclusions Using an SDM conversation aid improved patient knowledge and involvement in SDM without impacting treatment choice, encounter length, medication adherence or improved diabetes control in patients with type 2 diabetes. Future interventions may need to focus specifically on patients with signs of poor treatment fit. Clinical trial registration ClinicalTrial.gov: NCT01502891.
Objective: To better understand the epidemiology of drug-resistant Escherichia coli across health care and community settings. Patients and Methods:We conducted a population-based cohort study of the incidence of antibiotic-resistant E coli bacteriuria among different patient groups. All urine cultures with monomicrobial growth of E coli obtained from Olmsted County, Minnesota, residents from January 1, 2005, through December 31, 2009, were identified. The initial isolate per patient per year was included. Analyses were stratified by patient age and location of infection onset (ie, nosocomial, health care associated, and community associated). Results: We evaluated 5619 E coli isolates and the associated patients. During the study period, the incidence of drug-resistant bacteriuria did not change among children but increased significantly among adults of all ages, most markedly among elderly patients older than 80 years. In elderly patients, the incidence of bacteriuria with isolates resistant to fluoroquinolones increased from 464 to 1116 per 100,000 person-years (PϽ.001), and the incidence of bacteriuria with isolates resistant to fluoroquinolones plus trimethoprim-sulfamethoxazole increased from 274 to 512 per 100,000 person-years (PϽ.05). When analyzed by location of infection onset, incidence of bacteriuria with isolates resistant to trimethoprim-sulfamethoxazole, fluoroquinolones, trimethoprim-sulfamethoxazole plus fluoroquinolones, extended-spectrum cephalosporins, and more than 3 drug classes increased significantly among communityassociated but not among nosocomial or health care-associated cases. Conclusion: In this population-based study, the incidence of antibiotic-resistant E coli bacteriuria nearly doubled during the 5-year study period among elderly patients and those with community-associated isolates. These patient groups should be targets of interventions to slow the emergence and spread of antibiotic-resistant E coli.
Objective This study explores how patient decision aids (DAs) for antihyperglycemic agents and statins, designed for use during clinical consultations, are embedded into practice, examining how patients and clinicians understand and experience DAs in primary care visits. Methods We conducted semistructured in-depth interviews with patients (n = 22) and primary care clinicians (n = 19), and videorecorded consultations (n = 44). Two researchers coded all transcripts. Inductive analyses guided by grounded theory led to the identification of themes. Video and interview data were compared and organized by themes. Results DAs used during consultations became flexible artifacts, incorporated into existing decision making roles for clinicians (experts, authority figures, persuaders, advisors) and patients (drivers of healthcare, learners, partners). DAs were applied to different decision making steps (deliberation, bargaining, convincing, case assessment), and introduced into an existing knowledge context (participants’ literacy regarding shared decision-making (SDM) and DAs). Conclusion DAs’ flexible use during consultations effectively provided space for discussion, even when SDM was not achieved. DAs can be used within any decision-making model. Practice implications Clinician training in DA use and SDM practice may be needed to facilitate DA implementation and promote more ideal-type forms of sharing in decision making.
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