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At least 235 records · Page 13Linked to original sources
PubMed1993

How will I collect data? Methods for exploratory studies.

In summary, level I methods offer the investigator a way to navigate previously uncharted waters. They allow the investigator to answer questions about the phenomenon of interest from the point of view of the subjects. These methods are increasingly finding favor with nurse researchers.

Anthropology, Cultural↗
PubMedDate not supplied

Methodologic issues in collecting data from debilitated patients with cancer near the end of life.

PURPOSE/OBJECTIVES: To report the experience of a group of researchers who have had a year of experience in a clinical trial with homecare hospice patients. SAMPLE: 150 hospice patients with cancer and their primary caregivers who were accrued to a National Cancer Institute-funded clinical trial focusing on quality of life. METHODS: The investigative team kept careful records of the numbers of patient/caregiver dyads accrued to the study and the reasons for nonaccrual as well as reasons for attrition. Data were analyzed using descriptive statistics. FINDINGS: During a nine-month period, the hospice admitted 2,517 patients; 75% had cancer and 95% had caregivers, making them eligible for the study. However, after further screening, only 19% were eligible for contact and only 5% finally were accrued to the study. For the 125 patient/caregiver dyads actually accrued to the study, baseline data were obtained on only 50% and evaluable follow-up data on only 50%. CONCLUSIONS: Accruing patients to clinical trials and retaining them when they are critically ill and near death are extraordinarily difficult tasks. The inability to recruit and retain subjects for clinical trials has implications for integrity of data, data analysis, success of the project, and the cost of conducting such projects in the future.

Clinical Trials as Topic↗
PubMed1999

Supplemental grant to continue cooperative agreements with 10 predictor variables grantees and their research coordinating center. CSAP, SAMHSA, HHS. Supplement to support an additional year of intervention follow-up and data collection among the Predictor Variables by Developmental Stage grantees and their Research Coordinating Center.

This notice is to inform the public that an estimated $1.65 million will be available to support up to 11 supplemental awards to 10 existing Predictor Variables Study Sites and one existing Research Coordinating Center in FY 1999. The purpose of the award is to support enhancement of current programs and allow the collection and analyses of additional follow-up data for children currently included in these studies. CSAP will make the awards based on the recommendations of the initial review group and the CSAP National Advisory Council. Supplemental awards will be made in Fiscal Year 1999, by September 30, 1999. The studies funded under this supplement are projected to end September 30, 2000. Eligibility is limited to existing SAMHSA/CSAP's Predictor Variables by Developmental Stage study sites, and their Research Coordinating Center. All currently active Predictor Variables grantees are eligible to apply for supplemental funds under this GFA. Given the short implementation time frame and limited funds available for this activity, as well as existing research protocols that limit the scope of new activities that could be introduced at this point in the study, the existing Predictor Variables projects are the only projects that can effectively implement the required booster sessions and follow-up data collection activities. These studies have already demonstrated that they can make a positive impact on children within selected developmental parameters. It is important to document that this impact on these same children can be maintained as they enter the next developmental stages. The Research Coordinating Center has put considerable effort into developing cross-site rapport and collecting process data from the individual sites; an effort that would be redundant and not cost-effective if attempted by another entity at this point in the project. Additionally, it is important to the continuity of the study that the Research Coordinating Center be able to continue its current analyses and be able to conduct secondary analyses based on the totality of the data submitted throughout the life of the study.

Child↗
PubMed1999

Collect data, monitor claims receipts to ensure prompt Medicare, Medicaid payment.

What to do when your Medicare or Medicaid plan pays claims late. Doctors in New Mexico say they're going broke because health plans don't pay for months. But managed care plans with commercial lives aren't the only plans that pay claims late. Plans with Medicare and Medicaid lives also can have payment problems. Find out how the physicians in New Mexico are tackling the problem, and see what you can do to prevent it from happening to you.

Accounts Payable and Receivable↗
PubMedDate not supplied

Collecting data on the abuse and neglect of American Indian children.

A survey of 10% of federally recognized American Indian tribes and the states in which they are located indicates national data systems receive reports of approximately 61% of data on the abuse or neglect of American Indian children, 42% by states and 19% by counties. The author recommends that American Indians develop culturally sound definitions of abuse and neglect and that the government provide the resources and assistance necessary to develop data tracking and reporting systems on the abuse and neglect of American Indian children.

Child↗
PubMedDate not supplied

Collecting data on pregnancy loss: a review of evidence from the World Fertility Survey.

Estimates of levels and differentials of pregnancy loss are presented for 40 developing countries participating in the World Fertility Survey (WFS) program. Judged against agreed-upon levels of spontaneous loss in human populations, WFS surveys measured from 50 to 80 percent of recognizable losses. The coverage of induced abortions appears to be much worse. Consistent with data from other sources and settings, the probability of loss is strongly correlated with maternal demographic characteristics: age, pregnancy order, pregnancy spacing, and pregnancy loss history. Despite incomplete coverage, the WFS data on pregnancy loss provide considerable, and largely unexploited, insight on the dynamics of the reproductive career.

Data Collection↗