Steven A Smith

Mayo Clinic - Rochester, Rochester, Minnesota, United States

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Publications (68)312.51 Total impact

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    ABSTRACT: The Patient Assessment of Chronic Illness Care (PACIC) survey is a widely used instrument to assess the patient experience with healthcare delivery.
    Annals of behavioral medicine : a publication of the Society of Behavioral Medicine. 09/2014;
  • Diabetes care. 09/2014; 37(9):e206-7.
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    ABSTRACT: OBJECTIVE While metformin is generally accepted as the first-line agent in treatment of type 2 diabetes, there are insufficient evidence and extensive debate about the best second-line agent. We aimed to assess the benefits and harms of four commonly used antihyperglycemia treatment regimens considering clinical effectiveness, quality of life, and cost.RESEARCH DESIGN AND METHODS We developed and validated a new population-based glycemic control Markov model that simulates natural variation in HbA1c progression. The model was calibrated using a U.S. data set of privately insured individuals diagnosed with type 2 diabetes. We compared treatment intensification of metformin monotherapy with sulfonylurea, dipeptidyl peptidase-4 inhibitor, glucagon-like peptide-1 receptor agonist, or insulin. Outcome measures included life-years (LYs), quality-adjusted life-years (QALYs), mean time to insulin dependence, and expected medication cost per QALY from diagnosis to first diabetes complication (ischemic heart disease, myocardial infarction, congestive heart failure, stroke, blindness, renal failure, amputation) or death.RESULTSAccording to our model, all regimens resulted in similar LYs and QALYs regardless of glycemic control goal, but the regimen with sulfonylurea incurred significantly lower cost per QALY and resulted in the longest time to insulin dependence. An HbA1c goal of 7% (53 mmol/mol) produced higher QALYs compared with a goal of 8% (64 mmol/mol) for all regimens.CONCLUSIONS Use of sulfonylurea as second-line therapy for type 2 diabetes generated glycemic control and QALYs comparable with those associated with other agents but at lower cost. A model that incorporates HbA1c and diabetes complications can serve as a useful clinical decision tool for selection of treatment options.
    Diabetes care 02/2014; · 7.74 Impact Factor
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    ABSTRACT: Population health data are used to profile local conditions, call attention to areas of need, and evaluate health-related programs. Demand for data to inform health care decision making has spurred development of data sources and online systems, but these are often poorly integrated or limited in scope. Our objective was to identify existing data about diabetes mellitus-related conditions in Minnesota, build an online data resource, and identify what data are currently missing that, if available, would better inform assessment of health conditions in the state. A Web site was developed and populated with existing data and data not available elsewhere. It features functionality identified as most important by users, such as maps and county profiles. The site could serve as a flexible tool for stakeholder engagement, but issues were identified during development, including concerns about interpreting map data and open questions about sustainability, that need to be addressed.
    Journal of public health management and practice: JPHMP 01/2014; · 1.47 Impact Factor
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    ABSTRACT: Jeff Sloan and colleagues describe the development of the Patient-Reported Outcomes Quality of Life (PROQOL) instrument, which captures and stores patient-recorded outcomes in the medical record for patients with diabetes. Please see later in the article for the Editors' Summary.
    PLoS Medicine 11/2013; 10(11):e1001548. · 15.25 Impact Factor
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    ABSTRACT: Objective: To establish the prevalence of patient-reported hypoglycemia among ambulatory patients with diabetes and assess its impact on health-related quality of life (HRQoL).Methods: This study was a cross-sectional analysis of a postal survey disbursed during quarter 1 of 2010 to 875 adults with type 1 or 2 diabetes identified on the basis of an index clinical encounter for diabetes management between August 1, 2005 and June 30, 2006. The survey included questions about hypoglycemia, self-rating of health, and questions adapted from the Confidence in Diabetes Self-Care, Generalized Anxiety Disorder-7, EuroQol5-D, and Hypoglycemic Fear Survey. Data was analyzed using two sample t-test for continuous and Chi-square for categorical variables, with multivariate analysis to adjust for age, gender, diabetes duration, and Charlson comorbidity index.Results: The survey was completed by 418 patients (47.8% response rate). Of the respondents, 26 of 92 (28.3%) with type 1 and 55 of 326 (16.9%) with type 2 diabetes reported at least one episode of severe hypoglycemia within 6 months. Fear of hypoglycemia, including engagement in anticipatory avoidance behaviors, was highest in patients with type 2 diabetes reporting severe hypoglycemia and all patients with type 1 diabetes (p < 0.001). HRQoL was lower in patients with type 2, but not type 1, diabetes reporting severe hypoglycemia (p < 0.01).Conclusion: Clinicians and health systems should incorporate screening for hypoglycemia into routine health assessment of all patients with diabetes. It places patients at risk for counterproductive behaviors, impairs HRQoL, and should be used in individualizing glycemic goals.
    Endocrine Practice 06/2013; · 2.49 Impact Factor
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    ABSTRACT: BACKGROUND: The extant literature lacks breadth on psychological variables associated with health outcome for type 2 diabetes mellitus (T2DM). This investigation extends the scope of psychological information by reporting on previously unpublished factors. OBJECTIVE: To investigate if intolerance of uncertainty, emotion regulation, or purpose in life differentiate T2DM adults with sustained high HbA1c (HH) vs. sustained acceptable HbA1c (AH). SUBJECTS AND METHODS: Cross-sectional observational study. Adult patients with diagnosed T2DM meeting inclusionary criteria for AH, HH, or a nondiabetic reference group (NDR) were randomly selected and invited to participate. Patients who consented and participated resulted in a final sample of 312 subgrouped as follows: HH (n=108); AH (n=98); and NDR (n=106). Data sources included a survey, self-report questionnaires, and electronic medical record (EMR). RESULTS: HH individuals with T2DM reported lower purpose in life satisfaction (p=0.005) compared to the NDR group. The effect size for this finding is in the small-to-medium range using Cohen's guidelines for estimating clinical relevance. The HH-AH comparison on purpose in life was nonsignificant. The emotion regulation and intolerance of uncertainty comparisons across the three groups were not significant. CONCLUSIONS: The present study determined that lower purpose in life satisfaction is associated with higher HbA1c. In a T2DM patient with sustained high HbA1c, the primary care clinician is encouraged to consider screening for purpose in life satisfaction by asking a single question such as "Do the things you do in your life seem important and worthwhile?" The patient's response will assist the clinician in determining if meaning or purpose in life distress may be interferring with diabetes self-care. If this is the case, the clinician can shift the conversation to the value of behavioral and emotional health counseling.
    Primary care diabetes. 05/2013;
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    ABSTRACT: Objective To report population burden of ambulance requiring hypoglycemia and long term outcomes in type 1 diabetes (T1DM) on different insulin therapeutic programs.Methods We retrieved all ambulance calls activated by T1DM for hypoglycemia in Olmsted County between 1/1/03 and 12/31/09 and reviewed medical records.Results 531 ambulance calls were made by 208 TIDM patients, age 47 ± 13 years, 54 % males. 137 (66%) were on multiple daily insulin injections (MDI), 50 (24%) on continuous subcutaneous insulin infusion (CSII), 15 (7%) on simple insulin (SI), 4 (2%) on Metformin + MDI, and 2 (1%) off treatment (post pancreas transplant). The latter 2 groups were excluded from further analysis due to small sample size. The remaining three treatments differed by age (p<0.02) with the oldest patients on SI. Repeated calls, emergency room transportation (ERT) and hospitalization was 32%, 51% and 19 % respectively, and did not differ between the treatment groups. In a multivariate model, mortality was significantly associated with treatment type [SI group had higher risk for mortality than MDI (p=0.03) after excluding 27 patients who changed treatment during follow-up], age (p<0.0001) and ERT (p=0.04).Conclusion Population burden of ambulance requiring hypoglycemia in T1DM is high. Medical resources utilization was similar among the three treatment groups. Mortality was higher in the SI group (limited by small sample size) and among ERT requiring patients and increased with age. Further research could be directed towards understanding the impact of expert evaluation of high risk patients on long term outcomes.
    Endocrine Practice 07/2012; · 2.49 Impact Factor
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    ABSTRACT: Hypoglycemia is a cause of significant morbidity among patients with diabetes and may be associated with greater risk of death. We conducted a retrospective study to determine whether patient self-report of severe hypoglycemia is associated with increased mortality. Adult patients (N = 1,020) seen in a specialty diabetes clinic between August 2005 and July 2006 were questioned about frequency of hypoglycemia during a preencounter interview; 7 were lost to follow-up and excluded from analysis. Mild hypoglycemia was defined as symptoms managed without assistance, and severe hypoglycemia was defined as symptoms requiring external assistance. Mortality data, demographics, clinical characteristics, and Charlson comorbidity index (CCI) were obtained from the electronic medical record after 5 years. Patients were stratified by self-report of hypoglycemia at baseline, demographics were compared using the two-sample t test, and risk of death was expressed as odds ratio (95% CI). Associations were controlled for age, sex, diabetes type and duration, CCI, HbA(1c), and report of severe hypoglycemia. In total, 1,013 patients with type 1 (21.3%) and type 2 (78.7%) diabetes were questioned about hypoglycemia. Among these, 625 (61.7%) reported any hypoglycemia, and 76 (7.5%) reported severe hypoglycemia. After 5 years, patients who reported severe hypoglycemia had 3.4-fold higher mortality (95% CI 1.5-7.4; P = 0.005) compared with those who reported mild/no hypoglycemia. Self-report of severe hypoglycemia is associated with 3.4-fold increased risk of death. Patient-reported outcomes, including patient-reported hypoglycemia, may therefore augment risk stratification and disease management of patients with diabetes.
    Diabetes care 06/2012; 35(9):1897-901. · 7.74 Impact Factor
  • Steven A Smith
    Annals of internal medicine 05/2012; 156(10):JC5-12. · 13.98 Impact Factor
  • Steven A Smith
    Annals of internal medicine 03/2012; 156(6):466-7. · 13.98 Impact Factor
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    ABSTRACT: Surveys of physicians are an important tool to assess opinions and self-reported behaviors of this policy-relevant population. However, this population is notoriously difficult to survey and plagued with low and falling response rates. In order to evaluate the potential import of response rate, we examine the presence of nonresponse bias in a survey of physicians providing diabetes care that achieved a 36% response rate. Unlike other studies examining differences in individual characteristics for responding and nonresponding physicians, we also assess differences with respect to aggregate patient demographic, clinical, and behavioral characteristics. We are unable to demonstrate nonresponse bias, even with what could be construed as a relative low response rate. Nonetheless as the threat of nonresponse bias can never be completely assuaged, we believe that it should be monitored as a matter of course in physician surveys and offer a new dimension by which it can be evaluated.
    Evaluation &amp the Health Professions 02/2012; · 1.48 Impact Factor
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    ABSTRACT: The objective is to report a contemporary population-based estimate of hypoglycemia requiring emergency medical services (EMS), its burden on medical resources, and its associated mortality in patients with or without diabetes mellitus (DM, non-DM), which will enable development of prospective strategies that will capture hypoglycemia promptly and provide an integrated approach for prevention of such episodes. We retrieved all ambulance calls activated for hypoglycemia in Olmsted County, Minnesota, between January 1, 2003 and December 31, 2009. A total of 1473 calls were made by 914 people (DM 8%, non-DM 16%, unknown DM status 3%). Mean age was 60 ± 16 years with 49% being female. A higher percentage of calls were made by DM patients (87%) with proportionally fewer calls coming from non-DM patients (11%) (chi-square test, p < .001), and the remaining 2% calls by people with unknown DM status. Emergency room transportation and hospitalization were significantly higher in non-DM patients compared to DM patients (p < .001) and type 2 diabetes mellitus compared to type 1 diabetes mellitus (p < .001). Sulphonylureas alone or in combination with insulin varied during the study period (p = .01). The change in incidence of EMS for hypoglycemia was tracked during this period. However, causality has not been established. Death occurred in 240 people, 1.2 (interquartile range 0.2-2.7) years after their first event. After adjusting for age, mortality was higher in non-DM patients compared with DM patients (p < .001) but was not different between the two types of DM. The population burden of EMS requiring hypoglycemia is high in both DM and non-DM patients, and imposes significant burden on medical resources. It is associated with long-term mortality.
    Journal of diabetes science and technology 01/2012; 6(1):65-73.
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    ABSTRACT: The patient portal is a web service which allows patients to view their electronic health record, communicate online with their care teams, and manage healthcare appointments and medications. Despite advantages of the patient portal, registrations for portal use have often been slow. Using a secure video system on our existing exam room electronic health record displays during regular office visits, the authors showed patients a video which promoted use of the patient portal. The authors compared portal registrations and portal use following the video to providing a paper instruction sheet and to a control (no additional portal promotion). From the 12,050 office appointments examined, portal registrations within 45 days of the appointment were 11.7%, 7.1%, and 2.5% for video, paper instructions, and control respectively (p<0.0001). Within 6 months following the interventions, 3.5% in the video cohort, 1.2% in the paper, and 0.75% of the control patients demonstrated portal use by initiating portal messages to their providers (p<0.0001).
    Journal of the American Medical Informatics Association 12/2011; 18 Suppl 1:i24-7. · 3.57 Impact Factor
  • Rozalina Grubina, Steven A Smith
    Annals of internal medicine 05/2011; 154(10):JC5-02. · 13.98 Impact Factor
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    ABSTRACT: Although US health care expenditures reached 17.6 percent of GDP in 2009, quality measurement in this important service sector remains limited. Studying quality changes associated with 11 years of health care for patients with diabetes, we find that the value of reduced mortality and avoided treatment spending, net of the increase in annual spending, was $9,094 for the average patient. These results suggest that the unit cost of diabetes treatment, adjusting for the value of health outcomes, has been roughly constant. Since input prices have not been declining, our results are consistent with productivity improvement in health care.
    American Economic Review 05/2011; 101(3):206-11. · 2.69 Impact Factor
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    ABSTRACT: Statins are an important part of the treatment plan for patients with type 2 diabetes. However, patients who are prescribed statins often take less than the prescribed amount or stop taking the drug altogether. This suboptimal adherence may decrease the benefit of statin initiation. To estimate the influence of adherence on the optimal timing of statin initiation for patients with type 2 diabetes. The authors use a Markov decision process (MDP) model to optimize the treatment decision for patients with type 2 diabetes. Their model incorporates a Markov model linking adherence to treatment effectiveness and long-term health outcomes. They determine the optimal time of statin initiation that minimizes expected costs and maximizes expected quality-adjusted life years (QALYs). In the long run, approximately 25% of patients remain highly adherent to statins. Based on the MDP model, generic statins lower costs in men and result in a small increase in costs in women relative to no treatment. Patients are able to noticeably increase their expected QALYs by 0.5 to 2 years depending on the level of adherence. Adherence-improving interventions can increase expected QALYs by as much as 1.5 years. Given suboptimal adherence to statins, it is optimal to delay the start time for statins; however, changing the start time alone does not lead to significant changes in costs or QALYs.
    Medical Decision Making 04/2011; 32(1):154-66. · 2.89 Impact Factor
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    ABSTRACT: Lipid abnormalities increase the risk of coronary heart disease (CHD) and stroke in patients with Type 2 diabetes. Statins can be used to treat these abnormalities, but may have adverse side effects. In this article, we consider the optimal timing of statin initiation for patients with Type 2 diabetes. We formulate an infinite-horizon Markov decision process to maximize the patient's quality-adjusted life years (QALYs) prior to the occurrence of the first CHD or stroke event. We describe the state of the process by the patient's lipid ratio levels, and derive structural properties of the resulting optimal stopping time model, including sufficient conditions for the optimality of control-limit policies with respect to patient's lipid ratio levels and age. We use a large clinical data set to parameterize our model and compute optimal treatment policies to demonstrate the clinical implications of our results. We illustrate the importance of individualized treatment factors by estimating the patients’ QALY gains using our customized policies rather than current U.S. guidelines.
    IIE Transactions on Healthcare Systems Engineering. 03/2011; 1(1):49-65.
  • Rozalina Grubina, Steven A Smith
    Annals of internal medicine 02/2011; 154(4):JC2-13. · 13.98 Impact Factor
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    ABSTRACT: Several guidelines to reduce cardiovascular risk in diabetes patients exist in North America, Europe, and Australia. Their ability to achieve this goal efficiently is unclear. Decision analysis was used to compare the efficiency and effectiveness of international contemporary guidelines for the management of hypertension and hyperlipidemia for patients aged 40-80 with type 2 diabetes. Measures of comparative effectiveness included the expected probability of a coronary or stroke event, incremental medication costs per event, and number-needed-to-treat (NNT) to prevent an event. All guidelines are equally effective, but they differ significantly in their medication costs. The range of NNT to prevent an event was small across guidelines (6.5-7.6 for males and 6.5-7.5 for females); a larger range of differences were observed for expected cost per event avoided (ranges, $117,269-$157,186 for males and $115,999-$163,775 for females). Australian and U.S. guidelines result in the highest and lowest expected costs, respectively. International guidelines based on the same evidence and seeking the same goal are similar in their effectiveness; however, there are large differences in expected medication costs.
    PLoS ONE 01/2011; 6(1):e16170. · 3.53 Impact Factor

Publication Stats

519 Citations
312.51 Total Impact Points

Institutions

  • 2003–2013
    • Mayo Clinic - Rochester
      • Department of Hospital Internal Medicine
      Rochester, Minnesota, United States
  • 2002–2013
    • Mayo Foundation for Medical Education and Research
      • • Division of Endocrinology, Diabetes, Metabolism, and Nutrition
      • • Department of Health Sciences Research
      • • Mayo Medical School
      Rochester, Michigan, United States
  • 2011
    • University of Minnesota Duluth
      Duluth, Minnesota, United States
  • 2009–2011
    • North Carolina State University
      Raleigh, North Carolina, United States
    • National University of Ireland, Galway
      Gaillimh, Connaught, Ireland
  • 2008
    • University of Minnesota Twin Cities
      • Department of Pharmaceutical Care and Health Systems
      Minneapolis, MN, United States