Prevalence and trends of substance abuse in Harris County, Texas, 1989 to 1991

In the late 1980s, Harris County, Texas began experiencing an escalation of drug-related activities. Various indicators used in this analysis tracked drug-related trends from 1989 to 1991 to determine patterns for comparison of local (Houston/Harris County, Texas) to national levels.^ An important indicator of the drug scenario was drug-related activities among youths, which increased during the period of this study. The Harris County Juvenile Probation Department showed that among arrests for drug-related activities, felonies increased from 25% in 1988 to 53% in 1991. With the rise in drug-related crimes, and substance abuse among the student body, school districts were forced to institute drug education programs in an effort to curtail such activities.^ Law enforcement agencies in the county saw increased demands for their services as a result of drug activities. Harris County Sheriffs Department reported a 32% plus increase in drug-related charges between 1986 and 1991. Houston Police Department reported an increase of 109% for the same period.^ Data from the Harris County Medical Examiner, the National Institute of Justice's Drug Use Forecasting System (Houston), and drug treatment facilities around Houston/Harris County, Texas indicated similar drug usage trends. Over a four-year period (1988-91), the drugs most frequently detected during blood and urine analyses were cocaine, followed by marijuana, heroin, LSD, and methamphetamines.^ From 1988 to 1991, most drug rehabilitation organizations experienced increased demands for their services by approximately 35%. Several other organizations experienced as much as a 70 percent increase. Males accounted for roughly 70% and females about 30% of persons seeking treatment. However, the number of females pursuing treatment increased, thereby reducing the gender gap.^ Blacks in Houston/Harris County were at higher risk for drug usage among the general population, but sought treatment more readily than other ethnic groups. Whites sought treatment in similar numbers as Blacks, but overall the risk appeared smaller because they made up a larger portion of the Houston/Harris County population.^ This analysis concluded that drug trends for the Houston/Harris County, Texas did not follow national trends, but showed patterns of its own. It was recommended that other communities carry out similar studies to determine drug use trends particular to their local. ^

The identification of child abuse in Harris County in 1998

Characteristics of child abuse cases are not well known. In this study I collected data on 70 child abuse cases that were reported to Children's Protective Services in Harris County in 1998. The purpose of this study was to determine the factors in Harris County that lead to the identification of physical and sexual abuse. In order to answer the questions of who, what, where and when relative to the discovery of abuse I applied the same questionnaire (see Appendix) to each of 35 Sexual Abuse case reports and to each of 35 Physical Abuse/Neglect case reports. Answers to the first four questions were arranged by frequency distribution to show the predominant reporter, the 10 most common indicators, the most common locale, and the most frequent timing. Tables of the age, sex, and ethnicity of the children indicate the identity of those whose victimization was most reported. In addition the relationship between the form questions and the characteristics of the children was explored. A comparison of Sexual Abuse cases with Physical Abuse/Neglect cases was conducted and the results were analyzed and recorded in the Tables. ^ Child maltreatment often has negative short and long term effects on children's mental health and development. Suicide, violence, delinquency, drug and alcohol abuse and other forms of criminality are frequently child abuse related. Early detection and treatment helps to alleviate the myriad mental and physical ailments that untreated victims present as adults. This translates into medical dollar savings. ^ The long term objectives of my research were to reduce the number of undetected and unreported child abuse cases in Harris County by formulating better educational programs and literature for medical professionals and other personnel who are in contact with children. ^

A categorical data analysis approach to estimation of demographic characteristics for Texas county populations

The need for timely population data for health planning and Indicators of need has Increased the demand for population estimates. The data required to produce estimates is difficult to obtain and the process is time consuming. Estimation methods that require less effort and fewer data are needed. The structure preserving estimator (SPREE) is a promising technique not previously used to estimate county population characteristics. This study first uses traditional regression estimation techniques to produce estimates of county population totals. Then the structure preserving estimator, using the results produced in the first phase as constraints, is evaluated.^ Regression methods are among the most frequently used demographic methods for estimating populations. These methods use symptomatic indicators to predict population change. This research evaluates three regression methods to determine which will produce the best estimates based on the 1970 to 1980 indicators of population change. Strategies for stratifying data to improve the ability of the methods to predict change were tested. Difference-correlation using PMSA strata produced the equation which fit the data the best. Regression diagnostics were used to evaluate the residuals.^ The second phase of this study is to evaluate use of the structure preserving estimator in making estimates of population characteristics. The SPREE estimation approach uses existing data (the association structure) to establish the relationship between the variable of interest and the associated variable(s) at the county level. Marginals at the state level (the allocation structure) supply the current relationship between the variables. The full allocation structure model uses current estimates of county population totals to limit the magnitude of county estimates. The limited full allocation structure model has no constraints on county size. The 1970 county census age - gender population provides the association structure, the allocation structure is the 1980 state age - gender distribution.^ The full allocation model produces good estimates of the 1980 county age - gender populations. An unanticipated finding of this research is that the limited full allocation model produces estimates of county population totals that are superior to those produced by the regression methods. The full allocation model is used to produce estimates of 1986 county population characteristics. ^

Effect of primary care availability and health insurance coverage on risk and cost of Preventable Hospitalizations in Harris County

Preventable Hospitalizations (PHs) are hospitalizations that can be avoided with appropriate and timely care in the ambulatory setting and hence are closely associated with primary care access in a community. Increased primary care availability and health insurance coverage may increase primary care access, and consequently may be significantly associated with risks and costs of PHs. Objective. To estimate the risk and cost of preventable hospitalizations (PHs); to determine the association of primary care availability and health insurance coverage with the risk and costs of PHs, first alone and then simultaneously; and finally, to estimate the impact of expansions in primary care availability and health insurance coverage on the burden of PHs among non-elderly adult residents of Harris County. Methods. The study population was residents of Harris County, age 18 to 64, who had at least one hospital discharge in a Texas hospital in 2008. The primary independent variables were availability of primary care physicians, availability of primary care safety net clinics and health insurance coverage. The primary dependent variables were PHs and associated hospitalization costs. The Texas Health Care Information Collection (THCIC) Inpatient Discharge data was used to obtain information on the number and costs of PHs in the study population. Risk of PHs in the study population, as well as average and total costs of PHs were calculated. Multivariable logistic regression models and two-step Heckman regression models with log-transformed costs were used to determine the association of primary care availability and health insurance coverage with the risk and costs of PHs respectively, while controlling for individual predisposing, enabling and need characteristics. Predicted PH risk and cost were used to calculate the predicted burden of PHs in the study population and the impact of expansions in primary care availability and health insurance coverage on the predicted burden. Results. In 2008, hospitalized non-elderly adults in Harris County had 11,313 PHs and a corresponding PH risk of 8.02%. Congestive heart failure was the most common PH. PHs imposed a total economic burden of $84 billion at an average of $7,449 per PH. Higher primary care safety net availability was significantly associated with the lower risk of PHs in the final risk model, but only in the uninsured. A unit increase in safety net availability led to a 23% decline in PH odds in the uninsured, compared to only a 4% decline in the insured. Higher primary care physician availability was associated with increased PH costs in the final cost model (β=0.0020; p<0.05). Lack of health insurance coverage increased the risk of PH, with the uninsured having 30% higher odds of PHs (OR=1.299; p<0.05), but reduced the cost of a PH by 7% (β=-0.0668; p<0.05). Expansions in primary care availability and health insurance coverage were associated with a reduction of about $1.6 million in PH burden at the highest level of expansion. Conclusions. Availability of primary care resources and health insurance coverage in hospitalized non-elderly adults in Harris County are significantly associated with the risk and costs of PHs. Expansions in these primary care access factors can be expected to produce significant reductions in the burden of PHs in Harris County.^

Family to Family: Child Welfare for the 21st Century

Child welfare services have undergone many revisions and transformations since their initiation. Some scholars trace the beginning of child welfare in the United States to events such as a 1655 Massachusetts conviction for maltreatment leading to the death of a 12-year-old boy (Watkins, 1990). The predominant philosophy of child welfare has shifted over time from an early emphasis on child saving, to child protection, to family preservation. Building on family preservation, one of the current transformations in child welfare that is taking place in isolated pockets to whole states, is family-centered, neighborhood-based services. One force behind implementation of this transformation is the Family to Family Initiative of the Annie E. Casey Foundation. This paper places family-centered, neighborhood-based child welfare services within the historical context of development of child welfare and within the recent move to reinvent human services (Adams & Nelson, 1995). Against this backdrop, a locality-based implementation of the Family to Family Initiative is described.