The Potential Effects of HEDIS Performance Measures on the Quality of Care
Archimedes Inc., San Francisco, California, USA. Health Affairs
(Impact Factor: 4.97).
09/2008; 27(5):1429-41. DOI: 10.1377/hlthaff.27.5.1429
We analyzed the potential effects of different levels of performance on eight Health Care Employer Data and Information Set (HEDIS) measures for cardiovascular disease and diabetes during 1995-2005. The measures targeted 3.3 million (25 percent) heart attacks. Improvements in performance to those achieved by the median plan in 2005 imply prevention of 1.9 million myocardial infarctions (MIs, 15 percent), 0.8 million strokes (8 percent), and 0.1 million cases of end-stage renal disease (17 percent). If performance had been 100 percent, 1.4 million more MIs would have been prevented. Control of blood pressure has the largest potential effect on quality at the national level.
Available from: Barbara Yawn
- "· Patients’ hemoglobin A1c, lipids, blood pressure, & body mass index. Medical records will be the source of information about these commonly used intermediate outcome measures for diabetes [26,27]. "
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ABSTRACT: Shared decision making contributes to high quality healthcare by promoting a patient-centered approach. Patient involvement in selecting the components of a diabetes medication program that best match the patient's values and preferences may also enhance medication adherence and improve outcomes. Decision aids are tools designed to involve patients in shared decision making, but their adoption in practice has been limited. In this study, we propose to obtain a preliminary estimate of the impact of patient decision aids vs. usual care on measures of patient involvement in decision making, diabetes care processes, medication adherence, glycemic and cardiovascular risk factor control, and resource utilization. In addition, we propose to identify, describe, and explain factors that promote or inhibit the routine embedding of decision aids in practice.
We will be conducting a mixed-methods study comprised of a cluster-randomized, practical, multicentered trial enrolling clinicians and their patients (n = 240) with type 2 diabetes from rural and suburban primary care practices (n = 8), with an embedded qualitative study to examine factors that influence the incorporation of decision aids into routine practice. The intervention will consist of the use of a decision aid (Statin Choice and Aspirin Choice, or Diabetes Medication Choice) during the clinical encounter. The qualitative study will include analysis of video recordings of clinical encounters and in-depth, semi-structured interviews with participating patients, clinicians, and clinic support staff, in both trial arms.
Upon completion of this trial, we will have new knowledge about the effectiveness of diabetes decision aids in these practices. We will also better understand the factors that promote or inhibit the successful implementation and normalization of medication choice decision aids in the care of chronic patients in primary care practices.
BMC Health Services Research 05/2012; 12(1):130. DOI:10.1186/1472-6963-12-130 · 1.71 Impact Factor
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ABSTRACT: We propose ontology for which agents communicate with human and other agents according to an environmental information situation. Recently, various types of robot and information tool are developed and used. But still now, the system is promoted by human and is developed by human. The system cannot build interaction between human. And the agent processes information all by itself, which cannot utilize relationship with human or other agents. Therefore, we focus attention on ontology technology. Human can communicate with other that combined with a situation and body language. This is because human has the ontology. The agent created the ontology from observed human motion and situation, and communication with human or other agents use ontology. In this paper, we show the composition of ontology from the interaction between human and agent, and experiment of the communication with robot using ontology.
Intelligent Robots and Systems, 2004. (IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on; 01/2004
Available from: Cynthia D. Lamberth
Public Health Reports 09/2010; 125(5):628-33. DOI:10.2307/41434818 · 1.55 Impact Factor
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