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One Practice (one + practice)
Selected AbstractsDesign of a clustered observational study to predict emergency admissions in the elderly: statistical reasoning in clinical practiceJOURNAL OF EVALUATION IN CLINICAL PRACTICE, Issue 2 2007Gillian A. Lancaster MSc PhD CStat Abstract Objective, To describe the statistical design issues and practical considerations that had to be addressed in setting up a clustered observational study of emergency admission to hospital of elderly people. Study design and setting, Clustered observational study (sample survey) of elderly people registered with 18 general practices in Halton Primary Care Trust in the north-west of England. Results, The statistical design features that warranted particular attention were sample size determination, intra-class correlation, sampling and recruitment, bias and confounding. Pragmatic decisions based on derived scenarios of different design effects are discussed. A pilot study was carried out in one practice. From the remaining practices, a total of 4000 people were sampled, stratified by gender. The average cluster size was 200 and the intra-class correlation coefficient for the emergency admission outcome was 0.00034, 95% confidence interval (0,0.008). Conclusion, Studies that involve sampling from clusters of people are common in a wide range of healthcare settings. The clustering adds an extra level of complexity to the study design. This study provides an empirical illustration of the importance of statistical as well as clinical reasoning in study design in clinical practice. [source] Developing a measure of patient access to primary care: the access response index (AROS)JOURNAL OF EVALUATION IN CLINICAL PRACTICE, Issue 1 2003Glyn Elwyn BA MSc PhD FRCGP Abstract Access to appointments in primary care is not routinely measured, and there is no one standardized method for doing so. Any measurement tool has to take account of the dynamic status of appointment availability and the definitional problems of appointment types. The aim of this study was to develop and trial a method for measuring access that is valid, reliable, quick and provides a daily longitudinal record of access on an organizational basis (not for individual clinicians). Using the results of a literature review and following discussions with clinicians and managers a tool was designed following agreed specifications. After initial adjustments of the tool a feasibility study tested the acceptability of a data collection exercise on 11 practices of varying types, over a 4- to 8-week period. The development phase led to the design of a tool named the access response index (AROS). The method was well received in the practices, with a low incidence of missed days and only one practice failing to return data. The index measures the number of days' wait to the next available appointment with any general practitioner. The inclusion in the score of urgent appointments was abandoned due to definitional problems. A 5-day moving average was chosen to represent the data in graph form to demonstrate overall trends. AROS is a useful tool usable in any practice, and our feasibility study points to it being widely acceptable in the field. Data are represented in clear graphical daily format, either just for one practice or as an anonymous composite graph with other practices in the locality. [source] Employed Family Physician Satisfaction and Commitment to Their Practice, Work Group, and Health Care OrganizationHEALTH SERVICES RESEARCH, Issue 2 2010Ben-Tzion Karsh Objective. Test a model of family physician job satisfaction and commitment. Data Sources/Study Setting. Data were collected from 1,482 family physicians in a Midwest state during 2000,2001. The sampling frame came from the membership listing of the state's family physician association, and the analyzed dataset included family physicians employed by large multispecialty group practices. Study Design and Data Collection. A cross-sectional survey was used to collect data about physician working conditions, job satisfaction, commitment, and demographic variables. Principal Findings. The response rate was 47 percent. Different variables predicted the different measures of satisfaction and commitment. Satisfaction with one's health care organization (HCO) was most strongly predicted by the degree to which physicians perceived that management valued and recognized them and by the extent to which physicians perceived the organization's goals to be compatible with their own. Satisfaction with one's workgroup was most strongly predicted by the social relationship with members of the workgroup; satisfaction with one's practice was most strongly predicted by relationships with patients. Commitment to one's workgroup was predicted by relationships with one's workgroup. Commitment to one's HCO was predicted by relationships with management of the HCO. Conclusions. Social relationships are stronger predictors of employed family physician satisfaction and commitment than staff support, job control, income, or time pressure. [source] Recruiting and Retaining Physicians in Very Rural AreasTHE JOURNAL OF RURAL HEALTH, Issue 2 2010Carolyn M. Pepper PhD Abstract Context: Recruiting and retaining physicians is a challenge in rural areas. Growing up in a rural area and completing medical training in a rural area have been shown to predict decisions to practice in rural areas. Little is known, though, about factors that contribute to physicians' decisions to locate in very sparsely populated areas. Purpose: In this study, we investigated whether variables associated with rural background and training predicted physicians' decisions to practice in very rural areas. We also examined reasons given for plans to leave the study state. Methods: Physicians in the State of Wyoming (N = 693) completed a questionnaire assessing their background, current practice, and future practice plans. Findings: Being raised in a rural area and training in nearby states predicted practicing in very rural areas. High malpractice insurance rates predicted planning to move one's practice out of state rather than within state. Conclusions: Rural backgrounds and training independently predict practice location decisions, but high malpractice rates are the most crucial factor in future plans to leave the state. [source] | ||||||||||