Health policy issues and applications for evidence-based medicine and clinical practice guidelines

Lohr, Kathleen N; Eleazer, Kristen; Mauskopf, Josephine

doi:10.1016/s0168-8510(98)00044-x

Cited by 96 publications

(57 citation statements)

References 28 publications

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“…Alternatively, it may be more difficult to make healthy food choices or have an environment in which to exercise, thus impeding progress in achieving glycemic goals (12). Regardless of the mechanisms, our empirical findings indicate the difficulties in generalizing from landmark clinical trials with activated patients to real-world settings with more heterogeneous populations (28) for the purpose of public reporting and payment.…”

Section: Impact Of Patient Characteristics On Glycemiamentioning

confidence: 85%

Impact of Self-Reported Patient Characteristics Upon Assessment of Glycemic Control in the Veterans Health Administration

et al. 2007

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OBJECTIVE -The purpose of this article was to evaluate the impact of self-reported patient factors on quality assessment of Veterans Health Administration medical centers in achieving glycemic control.RESEARCH DESIGN AND METHODS -We linked survey data and administrative records for veterans who self-reported diabetes on a 1999 national weighted survey. Linear regression models were used to adjust A1C levels in fiscal year 2000 for socioeconomic status (education level, employment, and concerns of having enough food), social support (marital status and living alone), health behaviors (smoking, alcohol use, and exercise level), physical and mental health status, BMI, and diabetes duration. Medical centers were ranked by deciles, with and without adjustment for patient characteristics, on proportions of patients achieving A1C Ͻ7 or Ͻ8%. ). The final model had an R 2 of 7.8%. The Spearman rank coefficient comparing the thresholds adjusted only for age and sex to the full model was 0.71 for Ͻ7% and 0.64 for Ͻ8% (P Ͻ 0.0001). After risk adjustment, 4 of the 11 best-performing centers changed at least two deciles for the Ͻ7% threshold, and 2 of 11 changed two deciles for the Ͻ8% threshold. CONCLUSIONS -Adjustment for patient self-reported socioeconomic status and health impacts medical center rankings for glycemic control, suggesting the need for risk adjustment to assure valid inferences about quality. RESULTS Diabetes Care 30:245-251, 2007

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Section: Impact Of Patient Characteristics On Glycemiamentioning

confidence: 85%

Impact of Self-Reported Patient Characteristics Upon Assessment of Glycemic Control in the Veterans Health Administration

et al. 2007

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“…13 Barriers that hinder the implementation of guidelines are complex and multifactorial including: structural barriers (poor access to guidelines); personal barriers (psychological perception that the guidelines will not improve outcomes); and environmental/ social barriers (resistance to peer pressure to adhere to the guidelines). 6 Lohr et al 14 described the fear, on the part of clinicians, that guidelines rebut clinical intuition and pathophysiological rationale; Pollock et al 15 have attributed a causal connection to a lack of time for physicians to be able to read the latest research results. Forsetlund and Bjørndal 16 described the fact that physicians often attach more importance to clinical experience than to scientific evidence.…”

Section: G Bosse W Schmidbauer CD Spies Et Al Sop Adherence In Copmentioning

confidence: 99%

Adherence to Guideline-Based Standard Operating Procedures in Pre-Hospital Emergency Patients with Chronic Obstructive Pulmonary Disease

et al. 2011

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This study investigated improvements in pre-hospital care for patients with acute exacerbated chronic obstructive pulmonary disease (aeCOPD) achieved by using a standard operating procedure (SOP). An SOP for pre-hospital treatment of patients with aeCOPD was designed based on valid national guidelines. A total of 1000 Emergency Medical Service patient care reports were analysed prospectively: 500 before and 500 after introduction of the SOP. Overall guideline adherence was 34.6% before and 53.8% after introduction of the SOP; this increase was not statistically significant. After SOP introduction, the administration of β2-mimetics by inhalative, intravenous and subcutaneous routes increased significantly. The level of knowledge of the national guidelines was rated at 67% by emergency physicians during self-assessment, but was only 33% when physicians were asked specific questions during interview. Introducing the SOP for patients with aeCOPD did not significantly improve adherence to valid national guidelines, but did help to improve specific elements of therapy.

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“…As was postulated in a British Medical Journal editorial nearly two decades ago: "... at a time when ministers are arguing that medicine should be evidence based, is it not reasonable to suggest that this should also apply to health policy?" [20] A modest but sound literature on this has built up; see for instance [21][22][23]. However, using an evidence-based approach to policy is still not the rule, and regrettably this is particularly the case for health informatics (or e-Health) policy and investment decisions.…”

Section: An Evidence-based Approach In Health Informaticsmentioning

confidence: 99%

Health Informatics 3.0 and other Increasingly Dispersed Technologies Require Even Greater Trust: Promoting Safe Evidence-based Health Informatics

Rigby

Ammenwerth²,

Talmon³

et al. 2011

Yearb Med Inform

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SummaryBackground: Health informatics is generally less committed to a scientific evidence-based approach than any other area of health science, which is an unsound position. Introducing the new Web 3.0 paradigms into health IT applications can unleash a further great potential, able to integrate and distribute data from multiple sources. The counter side is that it makes the user and the patient evermore dependent on the ‚black box' of the system, and the re-use of the data remote from the author and initial context. Thus anticipatory consideration of uses, and proactive analysis of evidence of effects, are imperative, as only when a clinical technology can be proven to be trustworthy and safe should it be implemented widely -as is the case with other health technologies. Objectives: To argue for promoting evidence-based health informatics as systems become more powerful and pro-active yet more dispersed and remote; and evaluation as the means of generating the necessary scientific evidence base. To present ongoing IMIA and EFMI initiatives in this field. Methods: Critical overview of recent developments in health informatics evaluation, alongside the precedents of other health technologies, summarising current initiatives and the new challenges presented by Health Informatics 3.0. Results: Web 3.0 should be taken as an opportunity to move health informatics from being largely unaccountable to one of being an ethical and responsible science-based domain. Recent and planned activities of the EFMI and IMIA working groups have significantly progressed key initiatives. Conclusions: Concurrent with the emergence of Web 3.0 as a means of new-generation diffuse health information systems comes an increasing need for an evidence-based culture in health informatics.

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Health policy issues and applications for evidence-based medicine and clinical practice guidelines

Cited by 96 publications

References 28 publications

Impact of Self-Reported Patient Characteristics Upon Assessment of Glycemic Control in the Veterans Health Administration

Impact of Self-Reported Patient Characteristics Upon Assessment of Glycemic Control in the Veterans Health Administration

Adherence to Guideline-Based Standard Operating Procedures in Pre-Hospital Emergency Patients with Chronic Obstructive Pulmonary Disease

Health Informatics 3.0 and other Increasingly Dispersed Technologies Require Even Greater Trust: Promoting Safe Evidence-based Health Informatics

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