A comparison of dental restoration outcomes after placement by restorative function auxiliaries versus dentists.

OBJECTIVES: To compare the outcomes of restorations placed by restorative function auxiliaries (RFAs) with those placed by dentists. METHODS: Between July 1, 2007, and June 30, 2008, we matched 455 restorations placed by RFAs working at HealthPartners Dental Group with the same number placed by dentists. Restorations were matched by tooth number, American Dental Association procedure code, and patient age-group. RESULTS: Of 910 restorations, 17 (1.9 percent) had problems potentially related to the filling or crown placement during the first year. Problem rates were not significantly different (p = 0.33) for restorations placed by RFAs (1.3 percent, 6 of 455) and those placed by dentists (2.4 percent, 11 of 455). CONCLUSIONS: There was no significant difference in problem rates for restorations placed by RFAs versus those placed by dentists. This finding may free dentists to handle more difficult cases, alleviating some of the pressures of daily practice and meeting the need for improved access.

Dental Decision Simulation (DDSim): Development of a virtual training environment.

PURPOSE: Case-based simulations are powerful training tools that can enhance learning and drive behavior change. This is an overview of the design/development of Dental Decision Simulation (DDSim), a web-based simulation of an electronic dental record (EDR). The purpose was to use DDSim to train dentists to make evidence-based treatment planning decisions consistent with current evidence. This simulated EDR provides case-based information in support of a set of defined evidence-based learning objectives. METHODS: The development of this complex simulation model required coordinated efforts to create several components: identify behavior changes, case authoring mechanism, create virtual patient visits, require users to make treatment plan decisions related to learning objectives, and a feedback mechanism to help users recognize departures from those learning objectives. This simulation was evaluated in a 2-arm, clinic-randomized, controlled pilot study examining the extent to which DDSim changed dentists' planned treatment to conform to evidence-based treatment guidelines relative to change in dentists not exposed to DDSim. Outcomes were measured by comparing preintervention and postintervention patient EDR treatment data. RESULTS: Changes in behavior over time did not favor intervention or control clinics. CONCLUSION: DDSim provides a standardized learning platform that cannot be achieved through the use of live patients. Both live patients and case-based simulations can be used to transfer knowledge and skill development. DDSim offers the advantage of providing a platform for developing treatment planning skills in a low-risk environment. However, further research examining behavior change is needed.

Practice change toward better adherence to evidence-based treatment of early dental decay in the National Dental PBRN.

BACKGROUND: Significant national investments have aided the development of practice-based research networks (PBRNs) in both medicine and dentistry. Little evidence has examined the translational impact of these efforts and whether PBRN involvement corresponds to better adoption of best available evidence. This study addresses that gap in knowledge and examines changes in early dental decay among PBRN participants and non-participants with access to the same evidence-based guideline. This study examines the following questions regarding PBRN participation: are practice patterns of providers with PBRN engagement in greater concordance with current evidence? Does provider participation in a PBRNs increase concordance with current evidence? Do providers who participate in PBRN activities disseminate knowledge to their colleagues? METHODS: Logistic regression models adjusting for clustering at the clinic and provider levels compared restoration (dental fillings) rates from 2005-2011 among 35 providers in a large staff model practice. All new codes for early-stage caries (dental decay) and co-occurring caries were identified. Treatment was determined by codes occurring up to 6 months following the date of diagnosis. Provider PBRN engagement was determined by study involvement and meeting attendance. RESULTS: In 2005, restoration rates were high (79.5%), decreased to 47.6% by 2011 (p < .01), and differed by level of PBRN engagement. In 2005, engaged providers were less likely to use restorations compared to the unengaged (73.1% versus 88.2%; p < .01). Providers with high PBRN involvement decreased use of restorations by 15.4% from 2005 to 2008 (2005: 73%, 2008: 63%; p < .01). Providers with no PBRN involvement decreased use by only 7.5% (2005: 88%, 2008: 82%; p = .041). During the latter half of 2008 following the May PBRN meeting, attendees reduced restorations by 7.5%, compared to a 2.4% among non-attendees (OR = .64, p < .01). CONCLUSIONS: Based on actual clinical data, PBRN engagement was associated with practice change consistent with current evidence on treatment of early dental decay. The impact of PBRN engagement was most significant for the most-engaged providers and consistent with a spillover effect onto same-clinic providers who were not PBRN-engaged. PBRNs can generate relevant evidence and expedite translation into practice.

Personalised physician learning intervention to improve hypertension and lipid control: randomised trial comparing two methods of physician profiling.

PURPOSE: To assess the impact of personalised physician learning (PPL) interventions using simulated learning cases on control of hypertension and dyslipidaemia in primary care settings. METHODS: A total of 132 primary care physicians, 4568 eligible patients with uncontrolled hypertension, and 15 392 eligible patients with uncontrolled dyslipidaemia were cluster-randomised to one of three conditions: (a) no intervention, (b) PPL-electronic medical record (EMR) intervention in which 12 PPL cases were assigned to each physician based on observed patterns of care in the EMR in the previous year, or (c) PPL-ASSESS intervention in which 12 PPL cases were assigned to each physician based on their performance on four standardised assessment cases. General and generalised linear mixed models were used to account for clustering and to model differences in patient outcomes in the study arms. RESULTS: Among patients with uncontrolled hypertension at baseline, 49.1%, 46.6% and 47.3% (p=0.43) achieved blood pressure (BP) targets at follow-up. Among patients with uncontrolled dyslipidaemia at baseline, 37.5%, 37.3% and 38.1% (p=0.72) achieved low density lipoprotein cholesterol targets at follow-up in PPL-EMR, PPL-ASSESS and the control group, respectively. Although systolic (BP) (p<0.001) and lipid (p<0.001) values significantly improved during the study, the group-by-time interaction term showed no differential change in systolic BP values (p=0.51) or lipid values (p=0.61) among the three study arms. No difference in intervention effect was noted when comparing the PPL-EMR with the PPL-ASSESS intervention (p=0.47). CONCLUSIONS: The two PPL interventions tested in this study did not lead to improved control of hypertension or dyslipidaemia in primary care clinics during a mean 14-month follow-up period. This null result may have been due in part to substantial overall improvement in BP and lipid control at the study sites during the study. TRIAL REGISTRATION NUMBER: NCT00903071.

Effects of paroxetine and sertraline on low-density lipoprotein cholesterol: an observational cohort study.

Antidepressant use in US adults increased 3-fold from 2.5% in 1988-94 to 8.1% in 1999-2002, based on National Health and Nutrition Examination Surveys. As the use of antidepressants increases, a comprehensive understanding of the potential health risks that may be associated with their use becomes increasingly important. This study evaluated the effects of paroxetine and sertraline on low-density lipoprotein cholesterol (LDL-C). An observational cohort study (1997-2004) of adults who had taken paroxetine or sertraline for at least 60 continuous days and had > or =2 LDL-C values measured during the study period, one while taking and one while not taking paroxetine or sertraline. A total of 13 634 LDL-C values clustered within 2682 patients were studied. We conducted mixed model regression analyses to quantify the relationship between antidepressant use and LDL-C values. The number of days taking paroxetine (beta = 0.0045; 95% CI 0.0018, 0.0073) and sertraline (beta = 0.0074; 95% CI 0.0054, 0.0093) prior to the LDL-C test were related to higher LDL-C values, after accounting for age, sex, year LDL-C was tested, co-morbidity, depression and lipid medication. The number of days that had passed since exposure to paroxetine (beta = -0.0013; 95% CI -0.0020, -0.00061) or sertraline (beta = -0.00093; 95% CI -0.016, -0.00022) were related to lower LDL-C values. The significant interaction between exposure to an antidepressant and taking a lipid medication demonstrates that the increase in LDL-C values associated with antidepressant use is ameliorated among patients who were taking a lipid medication when LDL-C was measured. Our study showed that long-term use of paroxetine or sertraline may have a measurable adverse impact on cardiovascular risk in adults. Clinical strategies should be used to address cardiovascular risk while maintaining effective treatment of major depression. In light of these findings, attention to LDL-C values should accompany antidepressant use.