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Results for “Service Statistics”

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At least 973 records · Page 54Linked to original sources
PubMed2000

Utilization of out-of-hours services by patients with mental health problems.

BACKGROUND: This study was designed to provide information about how out-of-hours services are used by those with mental health problems. METHOD: Data were collected from agencies that patients with a mental health problem could directly access out of hours in an inner London health authority area. Data on all contacts were collected for a period of 4 weeks using various methods, including routinely collected data and specially designed data collection sheets. RESULTS: There were a total of 556 contacts across all of the services with 45 per cent of contacts presenting to an accident and emergency department. The type of service accessed was influenced by the sex of the patient, and the presenting complaint, so that females were more likely to contact their general practitioner and those with deliberate self-harm were more likely to attend an accident and emergency department. Females were more likely to present with deliberate self-harm, whereas men were more likely to present with suicidal feelings and depression. CONCLUSIONS: The study highlights some clear patterns in how out-of-hours services are used for mental health problems. The data may be useful in helping providers to plan their services more appropriately. The study also highlighted some of the problems in collecting routine data of this nature.

Adolescent↗
PubMedDate not supplied

Adult clients' recall of oral health education services received in private practice.

PURPOSE: The purpose of this study was to determine adult clients' recall of oral health education services they received in private practice settings. METHODS: A written questionnaire was completed by a convenience sample of 199 adult clients who each had an appointment at a university dental hygiene clinic. Responses were statistically analyzed to generate frequency distributions of recall of oral health education services received in private practice and to determine if statistical differences existed in the number of services recalled according to selected client characteristics. RESULTS: The results indicated that 14 of the 22 oral health education services included on the questionnaire were reported to have been provided to fewer than half of the study participants when they were treated in their private dental care setting. The subjects were most likely to recall they were given a toothbrush. Chi-square analysis of selected client characteristic variables indicated that only four of the services were statistically significant between the reported frequencies and client age and periodontal health status. The differences between the reported frequency of services for females and males were not statistically significant. Subjects recalled that more oral health education services had been provided in conjunction with a prophylaxis by a dental hygienist; the differences in the reported frequencies for 16 of the 22 services were statistically significant. (p < or = .05) CONCLUSIONS: The convenience sample and data constraints, which depended on the clients' recall of services received in a private practice setting, must be considered in interpreting the results. Even though dental hygienists provide more oral health education services than other oral healthcare practitioners, the generally low frequencies of adult client recall of oral health education services received in private practice settings indicate that oral healthcare providers may not incorporate effective learning strategies into their health education programs.

Adult↗
PubMed1988

Status of menu item forecasting in dietetic education.

The status of forecasting techniques included in educational programs and the need for instructional material on this topic were investigated. A survey instrument was developed to determine which forecasting techniques were included in instructional programs. The validated questionnaire was mailed to directors of coordinated undergraduate programs or to Plan IV representatives at all universities with programs approved or accredited by the ADA. The response rate was 59%, or 156 dietetic programs. Analysis of the survey data revealed that mathematical techniques (Box-Jenkins, regression, exponential smoothing, moving average) were not taught in the majority of educational programs. Educators responded that forecasting was an important concept and that continuing education concerning forecasting techniques that may be employed in foodservice management was needed. As a result of the analysis of the data, two self-instructional modules that could be utilized by both practitioners and educators to enhance the level of practice and education were developed. Graduate and undergraduate students at 11 universities and 35 randomly selected practitioners tested the self-instructional modules. For all groups--undergraduate, graduate, and practitioners--the t-statistic was significant at the p less than .0000 level; thus the modules were effective in teaching foodservice forecasting concepts.

Dietary Services↗
PubMed1998

[Diagnosing community health by factorial analysis].

OBJECTIVE: To identify the needs of medical care and to determine priorities in the delivery of health services by the factorial analysis of the health indicators obtained from study of the demographic, economic and family features of those registered at a Primary Care Centre. DESIGN: Descriptive and crossover. SETTING: Tlalpan area, Federal District, Mexico, divided into geo-statistical zones. Patients and other participants. A randomised sample of 590 dwellings, with proportional coverage, based on 173,000 inhabitants and 17,895 ordinary dwellings. INTERVENTION: Survey conducted in the home (April-July, 1993). MEASUREMENTS AND MAIN RESULTS: 16 health markers were classified into four categories, demographic, social, health-damaging and family. Nine markers with a reading on the Pearson's correlation index over 0.40 were chosen. Factorial analysis determined two main factors. CONCLUSIONS: The identification of the main risk factors by means of factorial analysis helped in diagnosing community health. A project needs to be worked out to define a methodology for studying medically dysfunctional families and to introduce a prevention and early diagnosis programme for Diabetes Mellitus.

Cross-Over Studies↗
PubMed1994

Competing for patients: understanding consumer evaluation of primary care.

The introduction of a competitive market into primary care means that general practitioners must consider the way in which their patients evaluate the service which they receive. Reports the results of an exploratory study carried out in Scotland to investigate the evaluative strategies used by patients in assessing the service they receive. Identifies six particular dimensions of the care process which have implications for GPs protecting their existing patient lists and in understanding how to attract new patients. Suggests through its results that while communicating certain features of the service to potential patients is relatively straightforward, the experiential nature of primary care services leads to a reliance on word-of-mouth communication which depends on ensuring that existing patients are satisfied.

Economic Competition↗
PubMed2004

Untangling the web: an approach to analyzing the impacts of individually tailored, multicomponent treatment interventions.

In this paper the use of a maximum individualized change score is proposed as an analytic alternative to the more traditional MANOVA and latent variable approaches in studies examining the use of individually tailored interventions. This strategy offers a number of significant advantages when multiple indicators are used to assess a broad array of potential outcomes that might result from client-specific treatments. Data on 146 children from a study examining the effectiveness of 3 short-term intensive in-home services were used to contrast the results of our proposed analytic strategy with those from the MANOVA and latent variable approaches. Results indicate that the maximum individualized change score approach improves the outcome comparisons among the 3 treatment interventions and eliminates some concerns regarding subjectivity that exists with procedures such as goal-attainment scaling. A simulation study suggests the maximum change score statistics is a nonbiased estimate for assessing between-group differences in program effectiveness and has more power than MANOVA to produce significant differences when smaller program effects exist. Suggestions for strengthening this analytic approach as well as examples regarding use of this technique in other research contexts are also provided.

Adolescent↗
PubMed1995

Exploring patient role behaviors for health care services: the assertive, activated and passive patient.

Several conceptual models describing how patients ought to behave have been discussed in the literature. Less attention has been devoted to classifying and profiling the primary types of actual patient behavior. This study develops and tests a patient role behavior scale which is used to group patients into three behavioral categories: assertive, activated, and submissive. Patient groups were found to differ significantly with respect to the kind of interaction they received from their physician during their office visits. However, perceptions of the amount of time spent with their doctor were not significantly different. These findings suggest that patients differ with respect to how they view their role in health care service encounters and that physicians may be able to accommodate differing patient roles without unduly influencing productivity.

Attitude to Health↗
PubMed1997

Interpreting health outcomes.

Interest in outcomes is universal. To patients, good outcomes represent their highest hopes for therapy; to health care professionals, good outcomes are the desired end-point of a complex web of care. More recently, politicians and health care managers too have shifted their emphasis away from health service activity and towards what is termed 'health gain'. The rise of the outcomes movement appears irresistible. However, the difficulties in interpreting outcomes data will not go away. Outcomes measured using routine data are subject to numerous biases and many practical difficulties. Despite recent statistical, methodological and technological advances, comparisons of outcomes at best provide us with weak evidence of either the effectiveness or the quality of health care. And sometimes they may frankly mislead. The apparent intuitiveness of outcomes monitoring has broad public appeal. But enthusiasm for outcomes needs to be tempered with a clear understanding of their limitations.

Data Interpretation, Statistical↗