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PubMed2001

Fifteen years of drug information in Christchurch Hospital.

AIM: To determine changes in numbers, demography and type of questions posed to the drug information service (DIS) at Christchurch Hospital over the last fifteen years. METHODS: The database of the DIS was used to retrieve data for one-year periods including the period of establishment in 1985/1986, 1993/1994 and 1999/2000. RESULTS: The number of questions per month increased from 26 in 1985/1986 to 284 in 1999/2000. The majority of questions have related to adverse drug reactions, contraindications/precautions, drug selection, interactions, and administration/dosage. Questions on drug interactions showed the greatest relative increase, from 8% to 19% of all questions. A disproportionate increase in requests came from primary care, which provided 14% of questions in 1985/1986 and 38% in 1999/2000. Computer databases are the major resource used currently whereas journal articles and textbooks dominated in 1985/1986. CONCLUSIONS: There has been a marked increase in use of the DIS despite a relatively constant population base. This may reflect an increased awareness of both the availability of the service and recognition of the complexity of medicines. The computer database is a useful reference source, decreasing repetition of search pathways and allowing audit to assist in the ongoing improvement of the service.

Data Interpretation, Statistical↗
PubMed2001

Operative acute small bowel obstruction: admitting service impacts outcome.

Early surgical intervention in acute small bowel obstruction (SBO) has long been recognized as an important factor in preventing morbidity and mortality. Factors associated with surgically managed acute SBO were analyzed for delay in intervention and impact on outcome. A retrospective review of all patients evaluated for SBO on the surgical teaching service of the Greenville Hospital System from July 1, 1997 to June 30, 2000 was performed. Data were collected on patient demographics, admission information (date, admitting service, physical examination, and laboratory values), comorbidity, diagnostic studies, surgery date, operative findings, postoperative complications, operative mortality, and discharge date. Analysis of the data revealed 157 cases of presumed SBO of which 61 were managed nonoperatively and 96 required surgery. Acute SBO was diagnosed in 65 patients who constitute the basis for this review. Of these 65 patients 43 (66%) were admitted to the surgical service, 25 (38%) required small bowel resection, and 17 (26%) developed morbidity and/or mortality. When analyzed for morbidity and mortality the only characteristics that were statistically significant were the admitting service (P = 0.003) and length of stay (P = 0.003). On further analysis of admitting service and patient outcomes several factors were significant when we compared medical service admissions to surgical service admissions. These included days from admission to surgery (P = 0.003), length of stay (P = 0.019), morbidity (P = 0.004), mortality (P = 0.005), and combined morbidity and mortality (P = 0.003). Mortality of patients admitted to the medical service was 27 per cent compared with 2 per cent for the surgical service. There were no differences in morbidity and mortality when analyzed by the need for small bowel resection, patient age, etiology of obstruction, or presence of comorbidities. None of the factors studied were useful in predicting the need for small bowel resection. Our findings agree with those of previous investigators with regard to 1) lack of association between the preoperative evaluation and the need for small bowel resection and 2) the association between delay in diagnosis and increased morbidity and mortality. In addition we have found that one of the primary causes of delay in treatment for SBO was admission to the medical service. This delay led to significantly higher mortality in these patients. We recommend early surgical evaluation for any patient admitted with SBO as a differential diagnosis.

Acute Disease↗
PubMed1995

Hospital service scope expansion and market share improvement: a dynamic modeling and multivariate approach.

In a national trend, large, acute-care hospitals located in urban areas of the nation were continuously broadening their service scope, adding services at the rate of one each year, from 1982 to 1987. This study proposes that the underlying rationale of hospital service-scope expansion is status-gap minimization. This perspective was quantitatively interpreted and tested by a dynamic modeling analysis. Findings support status-gap minimization as the rationale for service-scope expansion. Using multivariate regression and dynamic modeling analysis, the study demonstrates that the cross-sectional relationship between two steady states--the relationship between service scope and market share--is positive and statistically significant. However, the market share change is not related to hospital service scope. The interpretation offered is that hospitals expand the scope of services looking not so much to increase their market share benefit in the short run as to raise their organizational status. In the long run, higher organizational status such as broader service scope then benefits market share.

Catchment Area, Health↗
PubMed2005

Validity and usefulness of a method to monitor surgical services' average bias in scheduled case durations.

PURPOSE: Unbiased prediction of case durations is an integral part of matching operating room (OR) staffing to workload. Monitoring systematic bias in surgeons' scheduled case durations can identify those services with estimates sufficiently inaccurate that statistical analysis of historical data may be useful in preference to the surgeons' estimates. We describe a method to monitor surgical services' average bias in scheduled case durations. METHODS: Actual case duration, predicted (scheduled) case duration, and service were obtained for all 58,291 cases during 39 four-week periods at an academic hospital. For each four-week period, a ratio was computed for each service. The numerator for each service equalled the sum of the differences in minutes between actual case duration and scheduled case duration. The denominator equalled the sum in hours of the actual durations of all of the service's cases. The ratio was multiplied by eight hours to yield the number of minutes of underestimated case duration per eight hours of OR time during the four-week period. RESULTS: The ratios followed a normal distribution for each service. Using the Student's t distribution, the 95% lower confidence bounds for the average underestimate of case duration ranged from three to 65 min per eight hours of used OR time. CONCLUSIONS: To reduce over-utilized OR time, we recommend monitoring each service's 95% lower confidence bound of the bias in scheduled case durations. For services consistently underestimating their case durations, schedule their cases using statistical estimates of case durations based on their historical data, and disregard their own estimates.

Academic Medical Centers↗
PubMed1988

Problem visits to a family planning clinic.

In order to obtain information necessary for optimum delivery of services, data were collected on the nature of the services provided at a family planing clinic. Clinic visits were divided into initial, annual, routine, problem, supply, educational and unknown. An analysis of the "problem" visits was undertaken to assess various epidemiologic aspects of such visits and to identify areas of clinic efficiency that could be improved. Problem visits were defined as any visits for which the patient had a presenting complaint. Age, level of education, method of contraception and parity were statistically associated with problem visits. When compared to Pill users, diaphragm users, intrauterine device users and non-users had a higher-than-expected number of problem visits. Less educated women and teenagers had a lower-than-expected number of problem visits when compared to more educated and older women. Socioeconomic status and problem visits were not statistically associated. Problem visits required more time, utilized more medical services and resulted in more referrals to the gynecology clinic than did other visit types. As a result of this analysis, we have increased our educational efforts for patients at high risk of problem visits and have instituted a special problem-oriented family planning clinic in which a full complement of house staff and ancillary personnel are available. This arrangement makes the uncomplicated family planning clinic run more smoothly and efficiently and obviates the need for time-consuming and cost-ineffective referrals.

Adolescent↗
PubMed2006

Spreadsheets, service providers, and the Statehouse: using data and the wraparound process to reform systems for children and families.

Evaluation descriptions in the research literature tend to ignore the full context of the community change efforts from which they emerged. In this paper, we describe a range of evaluation studies and data collection activities conducted over the course of one state's effort to reform its child welfare system on behalf of families with children experiencing serious mental health problems. Initial activities included studies of the prevalence of unmet mental health need in children and youth in the state. As these needs were addressed, evaluation activities examined the impact of a pilot wraparound program that became a major part of systems reform. Later efforts included implementation analysis of wraparound programs and assessment of priorities for continued systems reform. As we describe this set of evaluation activities, we discuss how data collection evolved to meet the needs of stakeholders over time and consider lessons learned about the roles of research and information sharing in shaping community change efforts.

Child↗
PubMed2004

Explaining the diffusion of Medicaid home care waiver programs using VPRS decision rules.

While public preferences and legal decisions require extended Medicaid Home and Community-Based Services (HCBS), uneven program development is a major concern of policy makers and consumers. This paper presents the first Variable Precision Rough Sets (VPRS) analysis of national data to examine inter-state variation in the Medicaid HCBS waiver program. The exposition provides a detailed discussion of the methodological options and processes, tests the generated rules using a leave-one-out cross-validation, and compares VPRS classification accuracy with regression analyses of the same dataset. The results demonstrate that VPRS offers a robust method with two distinctive features for health care research. First, for policy makers and their audiences, VPRS results are presented as "if...then..." decision rules with likelihoods stated as percentages. Because this output form can be easily understood by non-specialists, the potential impact of research is enhanced. Second, for analysts generating evidence for health policy, VPRS provides a rigorous data mining tool and acknowledges inherent analytical uncertainty in the field.

Community Health Services↗
PubMed1996

Selection of key community descriptors for community-orientated primary care.

BACKGROUND: Community-oriented primary care (COPC) requires the development of practical tools if it is to be carried out. A previous study demonstrated a practical approach to carrying out one portion of a community assessment for COPC using a few representative health indicators. OBJECTIVE: To determine the validity of this process elsewhere, we tested whether these findings were generalizable to other settings and to the same setting a decade later. METHOD: In a cross-sectional study design, data on 18 health indicators were collected for census tracts in two target areas and for the entire state of Ohio, USA, for 1990. A factor analysis was performed to identify factors underlying the health indicators in the three areas examined. RESULTS: Two underlying factors, termed age and poverty, were present in all locations and over time. Each factor was defined by core indicators and a cluster of associated indicators. CONCLUSIONS: These results suggest that one part of a COPC community assessment can be done by selecting very few indicators. The distribution of indicators of age and income explains the variability of most of the health related indicators studied. These factors are stable over time and location. A community assessment should include indicators which, at a minimum, provide information on these two factors.

Adolescent↗
PubMedDate not supplied

CAN'T MISS--conquer any number task by making important statistics simple. Part 1. Types of variables, mean, median, variance, and standard deviation.

Healthcare quality improvement professionals need to understand and use inferential statistics to interpret sample data from their organizations. In quality improvement and healthcare research studies all the data from a population often are not available, so investigators take samples and make inferences about the population by using inferential statistics. This three-part series will give readers an understanding of the concepts of inferential statistics as well as the specific tools for calculating confidence intervals for samples of data. This article, Part 1, presents basic information about data including a classification system that describes the four major types of variables: continuous quantitative variable, discrete quantitative variable, ordinal categorical variable (including the binomial variable), and nominal categorical variable. A histogram is a graph that displays the frequency distribution for a continuous variable. The article also demonstrates how to calculate the mean, median, standard deviation, and variance for a continuous variable.

Analysis of Variance↗
PubMedDate not supplied

CAN'T MISS: conquer any number task by making important statistics simple. Part 7. Statistical process control: x-s control charts.

Statistical process control (SPC) can be thought of as the frequent monitoring of processes using inferential statistics. The feature that distinguishes SPC from the typical use of inferential statistics for analyzing populations is that in the former frequent samples are taken over time, whereas in inferential statistics a single sample is generaLLy taken before and after some intervention or treatment. An x-s control chart is used to monitor a continuous variable that reflects the output of a process. The x-s control chart is a graph that includes serial sample means (x) as the variables of interest, a centerline that represents the grand mean of the samples (x), and upper control limit (UCL) and lower control limit (LCL) that represent three standard errors (SEx) above and below the centerline. An x-s control chart is used to estimate with 99.7% confidence that the population mean of a continuous output variable was within the interval defined by the UCL and LCL during a period of baseline monitoring. It is further assumed that if the process remains stable, future population means wiLL remain between the control Limits for additional process outputs. Control charts allow the evaluation of both common- and special-cause variation. AnaLysis of the common-cause variation aLLows an assessment of the current process performance. Special-cause variation is identified when there is a sample mean that is beyond the UCL or LCL.

Confidence Intervals↗
PubMed1994

Consumer involvement in nonprescription medicine purchase decisions.

As self-medication with nonprescription drugs becomes increasingly popular and important in this era of escalating health care costs and growing consumer sophistication, the degree of consumer involvement in the purchase decision becomes an important factor. High involvement suggests active information-seeking behavior and, therefore, a greater likelihood of appropriate nonprescription drug use. The authors assess consumer involvement in nonprescription medicine purchase decisions and the use of expert sources of information.

Community Participation↗