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Publications (12)9.7 Total impact

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    ABSTRACT: To test a virtual case-based Simulated Diabetes Education intervention (SimDE) developed to teach primary care residents how to manage diabetes.
    Academic medicine: journal of the Association of American Medical Colleges 07/2014; · 2.34 Impact Factor
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    ABSTRACT: Background/Aims The role of aspirin therapy for reducing risk of cardiovascular events among those with pre-existing cardiovascular disease is well-established. However, a more individualized approach is recommended for primary prevention based on estimated risks for cardiovascular disease and gastrointestinal bleeding. Methods The United States Preventive Services Task Force has published methods and tables to estimate the number of myocardial infarctions (MIs) and strokes prevented and estimated harms of using aspirin based on age categories in hypothetical cohorts of men and women. Translation of the guideline requires data and formulas to calculate risk which are not readily available to practicing clinicians. We took advantage of the opportunity to enhance the efficiency of provider and patient decision making regarding aspirin through the use of electronic health record data and computer program assistance to assess the risks and benefits. Results The decision support program for aspirin in HealthPartners Medical Group & Clinics was integrated with the electronic health record through a web-service called Cardiovascular (CV) Wizard. At the point of care, de-identified data including pertinent demographics, diagnosis codes, lab results, medications, and allergies are transmitted to the web service and run through a set of sophisticated algorithms to assess whether aspirin is indicated and to provide individualized treatment suggestions and safety alerts based on known allergies and intolerance, contraindications, and identification of previous bleeding risks. Conclusions Using electronic decision support algorithms, it is possible to provide patients and providers with printable information to engage them in more evidence-based decisions about aspirin use for primary prevention.
    Clinical Medicine &amp Research 09/2013; 11(3):136-137.
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    ABSTRACT: Background/Aims More than 30% of adults in the U.S. have a 10% risk or greater of having a heart attack in the next 10 years. The proportion of adults with moderate and high cardiovascular risk (CVR) accounts for nearly half of the first major cardiovascular (CV) events in the United States. Shared decision support tools may reduce CVR by facilitating and prioritizing provider-patient communication about CV risk. Methods CV Wizard was developed to identify and prioritize uncontrolled CVR factors and offer treatment suggestions. It was integrated into the electronic health record through a web-service and pilot tested with 14 providers at 6 HealthPartners Medical Group (HPMG) clinics. CV Wizard was triggered during patient visits for adults age 18-75 with known CV risk factors such as diabetes, heart disease, tobacco use, hypertension, and hyperlipidemia. Staff printed the patient and provider versions of the decision making support. Providers completed a satisfaction survey 6 weeks post-implementation. Results Eleven providers completed the survey. Ten said CV Wizard fit well in their workflow. All found the information on the form useful and would recommend it to others. Providers also reported that patients were receptive, all or most of the time, to using the tool. Several (n = 3) were encouraged that patients paid more attention to smoking risks. Conclusions Preliminary results show that the CV Wizard is promising for engaging patients in decisions to lower CV risk and providers had high satisfaction rates. The patient tool provides an easy to comprehend visual for communicating and prioritizing CV risk reduction, particularly around smoking.
    Clinical Medicine &amp Research 09/2013; 11(3):137.
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    ABSTRACT: Simulation is widely used to teach medical procedures. Our goal was to develop and implement an innovative virtual model to teach resident physicians the cognitive skills of type 1 and type 2 diabetes management. A diabetes educational activity was developed consisting of (a) a curriculum using 18 explicit virtual cases, (b) a web-based interactive interface, (c) a simulation model to calculate physiologic outcomes of resident actions, and (d) a library of programmed feedback to critique and guide resident actions between virtual encounters. Primary care residents in 10 U.S. residency programs received the educational activity. Satisfaction and changes in knowledge and confidence in managing diabetes were analyzed with mixed quantitative and qualitative methods. Pre- and post-education surveys were completed by 92/142 (65%) of residents. Likert scale (five-point) responses were favorably higher than neutral for general satisfaction (94%), recommending to colleagues (91%), training adequacy (91%), and navigation ease (92%). Finding time to complete cases was difficult for 50% of residents. Mean ratings of knowledge (on a five-point scale) posteducational activity improved by +0.5 (p < .01) for use of all available drug classes, +0.9 (p < .01) for how to start and adjust insulin, +0.8 (p < .01) for interpreting blood glucose values, +0.8 (p < .01) for individualizing treatment goals, and +0.7 (p < .01) for confidence in managing diabetes patients. A virtual diabetes educational activity to teach cognitive skills to manage diabetes to primary care residents was successfully developed, implemented, and well liked. It significantly improved self-assessed knowledge and confidence in diabetes management.
    Journal of diabetes science and technology 01/2013; 7(5):1243-1254.
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    ABSTRACT: Purpose Simulation training is prevalent in aviation and engineering industries, but acceptance by medical providers is unknown. Our objective was to design and evaluate resident physician satisfaction with simulated diabetes training. Methods This web-based learning program integrated these components: 18 unique diabetes learning cases, an interactive care management interface, a physiologic model to simulate outcomes of actions across a series of patient encounters, and a library of feedback messages to critique and guide provider actions. A total of 341 consented primary care residents in 19 U.S. residency programs were randomized to receive (n=177) or not receive (n=164) the learning intervention. A satisfaction survey evaluating program features was completed by 94 (53%) of intervention subjects. Responses to open-ended questions about features considered valuable and areas needing improvement were assessed using qualitative methods. Results Likert-scale responses were favorably higher than neutral for general satisfaction (93%), recommending to colleagues (91%), training adequacy (90%), navigation ease (95%), blood sugar displays (86%), drug info and help links (76%), goal progress graphs (49%), and feedback received (81%). Difficulty finding time to do cases was an issue for (51%) of responders. Open-ended responses (n=87) indicated that the most valuable learning pertained to insulin management (n=35), general management (n=23), and goal- achievement (n=10). Suggested improvements included software enhancements (n=34) and nothing bad to report (n=27). Discussion Learning through case simulations in a web-based dynamic environment is rated highly for satisfaction and ease of use by resident physicians. Most would recommend it to colleagues.
    Clinical Medicine &amp Research 08/2012; 10(3):164.
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    ABSTRACT: Background/Aims Provider performance on diabetes measures is variable, and is at least partially due to differences in provider knowledge and confidence in managing patients with diabetes and multiple co-morbidities. Objective To evaluate whether a simulated learning program can improve provider knowledge and self-confidence in diabetes management. Methods 19 primary care residency programs and 341 consented residents were randomized to (a) intervention (177 residents) or (b) control (164 residents) conditions. Intervention subjects were assigned 18 learning cases using SimCare Diabetes, a web-based immersive simulation program that challenges providers to achieve blood sugar, blood pressure, and lipid goals in 6 months of simulated time, as well as to address other issues such as severe obesity and insulin resistance, hypoglycemia, depression, obstructive sleep apnea, and non-adherence. Between simulated encounters with a patient, providers receive personalized feedback on progress to goals and treatment actions taken or omitted. 92 intervention and 128 control subjects completed a post-intervention follow-up online survey with 10 multiple choice knowledge and 5 self-confidence assessment questions using a 5-point Likert scale (1=not at all confident, 5=very confident). Mean (95% CI) knowledge test and self- confidence measures, adjusting for residency program clustering, were compared by group. Results On knowledge testing, 46% of the intervention group answered more than half the answers correctly compared to 16% of the control group. The mean knowledge score (95% CI) was 5.31 (4.87-5.75) for intervention and 4.1 (3.69-4.50) for control subjects (p<.001). Self-confidence measures were higher for intervention compared to control subjects for: use of all available drug classes to manage diabetes (3.64 vs. 3.09, p<.001), insulin use (4.12 vs. 3.36, p<.001), interpretation of blood sugars (4.21 vs. 3.58, p< .001), setting individualized treatment goals (4.06 vs. 3.42, p< .001), and overall confidence in managing diabetes (3.97 vs. 3.28, p< .001). Discussion An immersive online simulated diabetes learning program was effective at improving knowledge and self-confidence for diabetes management in primary care residents. Support and partnerships to maintain and spread the technology are desirable.
    Clinical Medicine &amp Research 08/2012; 10(3):166.
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    ABSTRACT: Background/Aims Shared decision making (SDM) tools are advantageous to support clinical decisions consistent with patient values and preferences. Numerous tools that convey cardiovascular risk have been developed and tested while showing mixed results. Aims To develop and assess a simple SDM tool that helps patients identify and prioritize lifestyle or pharmacological actions that will most effectively reduce their cardiovascular (CV) risk. Methods A prototype patient SDM tool developed for point of care use is presented to the patient as a companion piece that is congruent with a physician clinical decision support tool called CV Wizard. The patient tool was designed to convey clear, succinct and personalized information about blood pressure, lipids, blood sugar, weight, smoking, and aspirin use. Reversible CV risk associated with each of these risk factors is conveyed using a combination of symbols and text accommodating a range of patient educational and literacy levels. The patient tool was presented to the HealthPartners Patient Council (HPC), the patient education specialist and a number of physician and leadership groups for feedback on content and design. Results The HPC found the initial version confusing. They wanted more specific information on the values of their current CV risk factors and preferred the more complex tool like the CV Wizard physician tool because of its quantitative detail on reversible CV risk and pharmacologic recommendations. However, they did acknowledge that not every patient would understand that level of detail. They noted that dialogue between the patient and the physician in conjunction with the tool was more important than the tool itself. Others thought the tool was a good start with minor modifications suggested. Conclusion The HPC preferred more specific CV risk factor values and recommendations than were included on the low literacy, or simple tool we presented. Tools that are tailored or able to accommodate a wide range of educational and literacy levels may be desirable to facilitate provider-patient shared decision making discussions. The version of the patient tool discussed here will be implemented in summer of 2012.
    Clinical Medicine &amp Research 08/2012; 10(3):163.
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    ABSTRACT: BACKGROUND AND OBJECTIVE: Medical groups have invested billions of dollars in electronic medical records (EMRs), but few studies have examined the cost-effectiveness of EMR-based clinical decision support (CDS). This study examined the cost-effectiveness of EMR-based CDS for adults with diabetes from the perspective of the health care system. DATA SOURCES/SETTING: Clinical outcome and cost data from a randomized clinical trial of EMR-based CDS were used as inputs into a diabetes simulation model. The simulation cohort included 1,092 patients with diabetes with A1c above goal at baseline. STUDY DESIGN: The United Kingdom Prospective Diabetes Study Outcomes Model, a validated simulation model of diabetes, was used to evaluate remaining life years, quality-adjusted life years (QALYs), and health care costs over patient lifetimes (40-year time horizon) from the health system perspective. PRINCIPAL FINDINGS: Patients in the intervention group had significantly lowered A1c (0.26 percent, p = .014) relative to patients in the control arm. Intervention costs were $120 (SE = 45) per patient in the first year and $76 (SE = 45) per patient in the following years. In the base case analysis, EMR-based CDS increased lifetime QALYs by 0.04 (SE = 0.01) and increased lifetime costs by $112 (SE = 660), resulting in an incremental cost-effectiveness ratio of $3,017 per QALY. The cost-effectiveness of EMR-based CDS persisted in one-way, two-way, and probabilistic sensitivity analyses. CONCLUSIONS: Widespread adoption of sophisticated EMR-based CDS has the potential to modestly improve the quality of care for patients with chronic conditions without substantially increasing costs to the health care system.
    Health Services Research 05/2012; · 2.29 Impact Factor
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    ABSTRACT: Background: A1c results are often not available until after the outpatient visit is completed. Despite the potential for rapid point- of- care (POC) A1c testing to improve the process of diabetes care, published results have not conclusively shown a link to improved diabetes care in primary care settings. Methods: All HealthPartners Medical Group primary care clinics use protocols for nurses to remind patients with diabetes to have A1c tested before upcoming medical appointments. In June 2007, one clinic began POC A1c testing for all diabetic patients who did not have an A1c in the previous six months or if the most recent A1c was more than 1 month ago and >7%. Using generalized linear mixed model regression, we compared diabetes medication intensification at encounters with diabetes patients in the pre testing period (PRE, 6/1/06 5/31/07, 22932 encounters) and post testing period (POST, 6/1/07 5/31/08, 27056 encounters) at the intervention clinic and five comparison clinics with no POC A1c testing capability. Results: The analysis included 3261 patients (mean age 57, 29% minority, median encounters 8/year) seen by 42 primary care physicians (PCP). The median A1c PRE was 7.2% at the intervention clinic, 6.9% at comparison clinics. At intervention clinic encounters, mean days since A1c testing fell from 72 to 44 (with 60% of POST encounters preceded by an A1c less than 1 month old), while there was no change PRE to POST at the comparison clinics. Medication was intensified at 16.3% of PRE encounters with the PCP when A1c was >7% at the intervention clinic, compared to 15.6% at the comparison clinics. Medication was intensified at 12.8% of POST encounters with the PCP when A1c was >7% at the intervention clinic, compared to 12.6% at the comparison clinics (P=0.92). Medication intensification also did not differ at other types of encounters (A1c <7%, not with PCP). Conclusions: These results add to previous research by examining a mediating step between POC A1c testing and improved glycemic control. Despite more recent A1c test results, medication intensification was not greater in the primary care clinic using POC A1c testing.
    Clinical Medicine &amp Research 03/2010; 8(1):47.
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    ABSTRACT: Introduction: While it is well documented that disparities exist across racial groups of diabetes patients relative to glucose control, the underlying causative factors are not well understood. The purpose of this study was to examine differences in physician orders for adjustments of glucose control medications in diabetes patients between African Americans and Caucasians. Methods: A cohort of 434 African American and 1,471 Caucasian diabetes patients was followed for a period of 18 months from 6/1/2006 through 11/30/2007. All patients were being treated in one of 6 primary care clinics within a large mid-western medical group. First and last A1c values were collected during the study period and an A1c change score was calculated. Patients were also classified as to whether English was their primary language and whether they were on medical assistance at any time during the study period. The presence of a medication adjustment was tracked for metformin, thiazolidinediones, sulfonylureas (initiation or titration) and insulins (initiation only). Medication adjustment data was from the prescribing data in the medical record and thus represents physician actions. Results: There was a significant difference between African Americans and Caucasians on their initial A1c values (8.2% vs 7.3%; P<0.0001). Adjusted for the initial A1c, mean number of visits was similar between the two groups (16.9 vs. 15.8, P=.50). When change in A1c was calculated while controlling for initial A1c African Americans had less than half the decline found in Caucasians (.20% vs .45%; P=0.0009). English as a primary language (P=.81) and medical assistance (P=.81) status were not related to the disparity in change value. Examination of medication adjustment for African Americans relative to Caucasians found that they were less likely to have adjustments of metformin (OR .69; P=.0021) and TZDs (OR .65; P=.0122) but no differences were found for Sulfonylureas (P=.49) or insulins (P=.30). Conclusions: This study suggests that part of the racial disparity in glucose control is related to physician orders for medication intensification. This indicates a need for better understanding of the reasons for medication adjustment disparities and effective interventions to reduce them.
    Clinical Medicine &amp Research 03/2010; 8(1):48-9.
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    ABSTRACT: We wanted to assess the impact of an electronic health record-based diabetes clinical decision support system on control of hemoglobin A(1c) (glycated hemoglobin), blood pressure, and low-density lipoprotein (LDL) cholesterol levels in adults with diabetes. We conducted a clinic-randomized trial conducted from October 2006 to May 2007 in Minnesota. Included were 11 clinics with 41 consenting primary care physicians and the physicians' 2,556 patients with diabetes. Patients were randomized either to receive or not to receive an electronic health record (EHR)-based clinical decision support system designed to improve care for those patients whose hemoglobin A(1c), blood pressure, or LDL cholesterol levels were higher than goal at any office visit. Analysis used general and generalized linear mixed models with repeated time measurements to accommodate the nested data structure. The intervention group physicians used the EHR-based decision support system at 62.6% of all office visits made by adults with diabetes. The intervention group diabetes patients had significantly better hemoglobin A(1c) (intervention effect -0.26%; 95% confidence interval, -0.06% to -0.47%; P=.01), and better maintenance of systolic blood pressure control (80.2% vs 75.1%, P=.03) and borderline better maintenance of diastolic blood pressure control (85.6% vs 81.7%, P =.07), but not improved low-density lipoprotein cholesterol levels (P = .62) than patients of physicians randomized to the control arm of the study. Among intervention group physicians, 94% were satisfied or very satisfied with the intervention, and moderate use of the support system persisted for more than 1 year after feedback and incentives to encourage its use were discontinued. EHR-based diabetes clinical decision support significantly improved glucose control and some aspects of blood pressure control in adults with type 2 diabetes.
    The Annals of Family Medicine 9(1):12-21. · 4.61 Impact Factor
  • Canadian Journal of Diabetes 33(3):197. · 0.46 Impact Factor