248,921 research outputs found

    Alignment of patient and primary care practice member perspectives of chronic illness care: a cross-sectional analysis

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    Polly H. Noel and Luci K. Leykum are with the South Texas Veterans Health Care System, 7400 Merton Minter Blvd, San Antonio, TX 78229, USA -- Polly H. Noel, Ray F. Palmer, Raquel L. Romero, Luci K. Leykum, Holly J. Lanham, and Krista W. Bowers are with the Department of Medicine, University of Texas Health Science Center at San Antonio, 7703 Floyd Curl Dr, San Antonio, TX 78229, USA -- Michael L. Parchman is with the MacColl Center for Healthcare Innovation, Group Health Research Institute, Group Health Cooperative, 1730 Minor Ave 1600, Seattle, WA 98101, USA -- Holly J. Leykum is with the The McCombs School of Business, The University of Texas at Austin, 2110 Speedway, Stop B6000, Austin, TX 78712, USA -- John E. Zeber is with the Central Texas Veterans Health Care System, 1901 S. 1st St, Temple, TX 76504, USA and Scott and White Healthcare Center for Applied Health Research, 2401 S. 31st St, Temple, TX 76508, USABackground: Little is known as to whether primary care teams’ perceptions of how well they have implemented the Chronic Care Model (CCM) corresponds with their patients’ own experience of chronic illness care. We examined the extent to which practice members’ perceptions of how well they organized to deliver care consistent with the CCM were associated with their patients’ perceptions of the chronic illness care they have received. Methods: Analysis of baseline measures from a cluster randomized controlled trial testing a practice facilitation intervention to implement the CCM in small, community-based primary care practices. All practice “members” (i.e., physician providers, non-physician providers, and staff) completed the Assessment of Chronic Illness Care (ACIC) survey and adult patients with 1 or more chronic illnesses completed the Patient Assessment of Chronic Illness Care (PACIC) questionnaire. Results: Two sets of hierarchical linear regression models accounting for nesting of practice members (N = 283) and patients (N = 1,769) within 39 practices assessed the association between practice member perspectives of CCM implementation (ACIC scores) and patients’ perspectives of CCM (PACIC). ACIC summary score was not significantly associated with PACIC summary score or most of PACIC subscale scores, but four of the ACIC subscales were consistently associated with PACIC summary score and the majority of PACIC subscale scores after controlling for patient characteristics. The magnitude of the coefficients, however, indicates that the level of association is weak. Conclusions: The ACIC and PACIC scales appear to provide complementary and relatively unique assessments of how well clinical services are aligned with the CCM. Our findings underscore the importance of assessing both patient and practice member perspectives when evaluating quality of chronic illness care.Information, Risk, and Operations Management (IROM)[email protected]

    Supporting Special-Purpose Health Care Models via Web Interfaces

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    The potential of the Web, via both the Internet and intranets, to facilitate development of clinical information systems has been evident for some time. Most Web-based clinical workstations interfaces, however, provide merely a loose collection of access channels. There are numerous examples of systems for access to either patient data or clinical guidelines, but only isolated cases where clinical decision support is presented integrally with the process of patient care, in particular, in the form of active alerts and reminders based on patient data. Moreover, pressures in the health industry are increasing the need for doctors to practice in accordance with Âżbest practiceÂż guidelines and often to operate under novel health-care arrangements. We present the Care Plan On-Line (CPOL) system, which provides intranet-based support for the SA HealthPlus Coordinated Care model for chronic disease management. We describe the interface design rationale of CPOL and its implementation framework, which is flexible and broadly applicable to support new health care models over intranets or the Internet

    Development and preliminary evaluation of a clinical guidance programme for the decision about prophylactic oophorectomy in women undergoing a hysterectomy

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    Objectives: To develop a decision analysis based and computerised clinical guidance programme (CGP) that provides patient specific guidance on the decision whether or not to undergo a prophylactic oophorectomy to reduce the risk of subsequent ovarian cancer and to undertake a preliminary pilot and evaluation. Subjects: Women who had already agreed to have a hysterectomy who otherwise had no ovarian pathology. Setting: Oophorectomy decision consultation at the outpatient or pre-admission clinic. Methods: A CGP was developed with advice from gynaecologists and patient groups, incorporating a set of Markov models within a decision analytical framework to evaluate the benefits of undergoing a prophylactic oophorectomy or not on the basis of quality adjusted life expectancy, life expectancy, and for varying durations of hormone replacement therapy. Sensitivity analysis and preliminary testing of the CGP were undertaken to compare its overall performance with established guidelines and practice. A small convenience sample of women invited to use the CGP were interviewed, the interviews were taped and transcribed, and a thematic analysis was undertaken. Results: The run time of the programme was 20 minutes, depending on the use of opt outs to default values. The CGP functioned well in preliminary testing. Women were able to use the programme and expressed overall satisfaction with it. Some had reservations about the computerised format and some were surprised at the specificity of the guidance given. Conclusions: A CGP can be developed for a complex healthcare decision. It can give evidence-based health guidance which can be adjusted to account for individual risk factors and reflects a patient’s own values and preferences concerning health outcomes. Future decision aids and support systems need to be developed and evaluated in a way which takes account of the variation in patients’ preferences for inclusion in the decision making process
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