Burden of diabetes in cancer inpatients

Inpatient hyperglycemia has been shown to be associated with higher morbidity and mortality. Treatment of inpatient hyperglycemia reduces morbidity and mortality at least in the intensive care unit. Burden and severity of hyperglycemia in an inpatient population of a cancer center is not known. The study is a secondary analysis of the primary study 'Prevalence of Diabetes in cancer inpatient'. Finger-stick glucose concentration and pharmacy data were collected prospectively for all hospitalizations to a large cancer center. Demographic, clinical and laboratory data were collected in a retrospective fashion. Between May 1 and July 31, 2006; 3,940 patients were admitted 5,489 times. Prior to their first admissions, 920(23.4%) of the 3940 patients had unrecognized or recognized hyperglycemia. Glucose was never tested during 1714 (31.8%) hospitalizations, including 170 (12%) of the 1414 admissions of the 920 patients with previous hyperglycemia, and, 109 (58%) of 188 patients who were not tested for glucose prior to their index admissions. Overall, sustained significant hyperglycemia (>= 200 mg/dL on two separate days) was present in 765 (13.9%). Antidiabetic treatment was dispensed in 1168 (21.3%), though 627 (53.7%) of these received only short/rapid acting insulin, and, 951 (17.3%)diabetes code before and in another 80 (1.5%) during stay in hospital, out of total 5489 admissions. Therefore diabetes mellitus or hyperglycemia affected 1525 (27.8%) out of all admissions and coding alone as a criterion for diagnosis of hyperglycemia would have underreported it by 32%. Hyperglycemia occurred more commonly during hospitalization of patients with older age, males, ethnic minorities, advanced malignancies, and those receiving glucocorticoids, parenteral nutrition, and those who had a past history of coding for diabetes or past hyperglycemia, but not in those with the cancers reported to be associated with diabetes mellitus. Of the recognized diabetics half had sustained significant hyperglycemia and 10% had three quarters glucoses tested above 180 mg/dL. To conclude, diabetes affects at least 27.8% of inpatients at our cancer center. Coding for diabetes significantly underreports the burden of the disease. Significant sustained hyperglycemia of >=200 mg/dL among inpatients at a cancer center is common, under-recognized, and either untreated or inadequately treated with suboptimal glycemic control. The implications of hyperglycemia in cancer inpatient populations need further investigations. Fasting serum or plasma glucose should be checked routinely for every patient admitted to a cancer hospital, to recognize and treat hyperglycemia as clinically appropriate.^

Outcomes assessment of a pediatric practice guideline

Objective. This study examines the structure, processes, and data necessary to assess the outcome variables, length of stay and total cost, for a pediatric practice guideline. The guideline was developed by a group of physicians and ancillary staff members representing the services that most commonly provide treatment for asthma patients at Texas Children's Hospital, as a means of standardizing care. Outcomes have needed to be assessed to determine the practice guideline's effectiveness.^ Data sources and study design. Data for the study were collected retrospectively from multiple hospital data bases and from inpatient chart reviews. All patients in this quasi-experimental study had a diagnosis of Asthma (ICD-9-CM Code 493.91) at the time of admission.^ The study examined data for 100 patients admitted between September 15, 1995 and November 15, 1995, whose physician had elected to apply the asthma practice guideline at the time of the patient's admission. The study examined data for 66 inpatients admitted between September 15, 1995 and November 15, 1995, whose physician elected not to apply the asthma practice guideline. The principal outcome variables were identified as "Length of Stay" and "Cost".^ Principal findings. The mean length of stay for the group in which the practice guideline was applied was 2.3 days, and 3.1 days for the comparison group, who did not receive care directed by the practice guideline. The difference was statistically significant (p value = 0.008). There was not a demonstrable difference in risk factors, health status, or quality of care between the groups. Although not showing statistical significance in the univariate analysis, private insurance showed a significant difference in the logistic regression model presenting an elevated odds ratio (odds ratio = 2.2 for a hospital stay $\le$2 days to an odds ratio = 4.7 for a hospital stay $\le$3 days) showing that patients with private insurance experienced greater risk of a shorter hospital stay than the patients with public insurance in each of the logistic regression models. Public insurance included; Medicaid, Medicare, and charity cases. Private insurance included; private insurance policies whether group, individual, or managed care. The cost of an admission was significantly less for the group in which the practice guideline was applied, with a mean difference between the two groups of $1307 per patient.^ Conclusion. The implementation and utilization of a pediatric practice guideline for asthma inpatients at Texas Children's Hospital has a significant impact in terms of reducing the total cost of the hospital stay and length of the hospital stay for asthma patients admitted to Texas Children's Hospital. ^

A comparison of Markov and generalized linear models of hospital mortality

This paper reports a comparison of three modeling strategies for the analysis of hospital mortality in a sample of general medicine inpatients in a Department of Veterans Affairs medical center. Logistic regression, a Markov chain model, and longitudinal logistic regression were evaluated on predictive performance as measured by the c-index and on accuracy of expected numbers of deaths compared to observed. The logistic regression used patient information collected at admission; the Markov model was comprised of two absorbing states for discharge and death and three transient states reflecting increasing severity of illness as measured by laboratory data collected during the hospital stay; longitudinal regression employed Generalized Estimating Equations (GEE) to model covariance structure for the repeated binary outcome. Results showed that the logistic regression predicted hospital mortality as well as the alternative methods but was limited in scope of application. The Markov chain provides insights into how day to day changes of illness severity lead to discharge or death. The longitudinal logistic regression showed that increasing illness trajectory is associated with hospital mortality. The conclusion is reached that for standard applications in modeling hospital mortality, logistic regression is adequate, but for new challenges facing health services research today, alternative methods are equally predictive, practical, and can provide new insights. ^

Development and evaluation of a cervical cancer screening program for Chinese women

Despite of the proven efficacy of the Pap test, Asian populations still have low Pap screening compliance. The purpose of this dissertation was to investigate factors that influencing women's decision to obtain a Pap test, and to describe the development and evaluation of a cervical cancer educational program promoting the Pap screening behavior among women in Taiwan. ^ The first study examined factors associated with Pap screening compliance. Psychometric properties of measurement instruments were also assessed. The scale reliabilities were as the follows: Cronbach alpha 0.70 for knowledge scale, 0.88 for pros scale, 0.68 for cons scale, and 0.72 for perceived norms scale. Results from multiple logistic regression analysis, after adjusted for marital status, showed women who compliant to Pap screening guidelines had significantly higher knowledge, higher perceived benefits (pros), lower perceived barriers (cons), and higher perceived norms to receive a Pap test. ^ The second study described the development of a program called “Love yourself before you take care of your family”, designed to increase Pap screening behavior among women in Taiwan. The development of this program was guided by Intervention Mapping (IM), an innovative process of intervention design. The program used methods such as information transmission, modeling, persuasion, and facilitation. Strategies included direct mail campaigns, role model stories with women's testimonials, and phone intervention. ^ The third study examined the effectiveness of a randomized trial of the carefully-designed intervention (N = 424). Participants were female family members of inpatients admitted to one of the major teaching hospitals in Taiwan during August and September 1999. Women in the intervention group reported a higher rate of receiving a Pap test than women in the control group (50% versus 32%) after a three-month intervention (p = 0.002). Women in the intervention group showed increased knowledge (p = .016), perceived pros (p = 0.008), and susceptibility (p = .011) between baseline and follow-up. They also showed higher perceived pros of Pap tests than women in control group at follow-up (p = .031). This result suggested that program development based on theories and evidences could maximize the intervention impact for a specific target population. ^

Epidemiological trends of influenza A positive patients hospitalized at St. Luke's Episcopal Hospital, Houston, Texas September, 2009--January, 2010

This study was a descriptive analysis of 437 influenza A positive inpatients and outpatients during the five month period between September, 2009 and January, 2010. The objective of the study was to describe the epidemiological trends of the total influenza A positive population and more specifically the clinical features of patients hospitalized with influenza A at St. Luke's Episcopal Hospital in Houston, Texas from September 2009 through January 2010. Eligible cases were included if they tested positive for influenza A test using the rapid antigen test and/or rRT-PCR. Hospitalized cases were included based on the laboratory confirmation of influenza A as well as hospital admission for at least 24 hours. Data was collected from medical record abstraction and included patient demographics, clinical history and history of chronic disease. Clinical findings in the differential diagnosis that led to laboratory-confirmation of influenza A as well as course of treatment during the hospital admission were summarized. Finally, co-morbid conditions charted during the hospital visit were reviewed and evaluated for associations with influenza A complications. During the study period, forty-eight patients were included in the study of which 27 tested positive for the H1N1 subtype. Females were more likely to be hospitalized than men. The median age of all patients admitted to St. Luke's Episcopal Hospital with influenza A was 42. The distribution for admitted cases was 15 White, 15 Black, and 18 Hispanic. Patients with co-morbid disease constituted 81% of the admissions for Influenza A. The presence of an underlying medical condition remains a risk factor for both seasonal and H1N1 influenza. Although respiratory conditions such as asthma and COPD are commonly associated with complications of seasonal influenza, patients with metabolic disorders such as kidney disease and/or diabetes were admitted more frequently (58%) during the study period. The patients in the study also of a much younger age than the age that is usually associated with complications of influenza infection, i.e. no patients greater than 65 years of age were admitted with a diagnosis of influenza A. Lower infection rates among elderly populations were similarly reported in other studies of influenza during the same time period. Older patient populations may benefit from antibodies to previous H1N1 strains that have circulated during the twentieth century, whereas younger age groups lack these exposures.^

A comparison of techniques for forecasting utilization of Veterans Affairs hospitals

This study demonstrated that accurate, short-term forecasts of Veterans Affairs (VA) hospital utilization can be made using the Patient Treatment File (PTF), the inpatient discharge database of the VA. Accurate, short-term forecasts of two years or less can reduce required inventory levels, improve allocation of resources, and are essential for better financial management. These are all necessary achievements in an era of cost-containment.^ Six years of non-psychiatric discharge records were extracted from the PTF and used to calculate four indicators of VA hospital utilization: average length of stay, discharge rate, multi-stay rate (a measure of readmissions) and days of care provided. National and regional levels of these indicators were described and compared for fiscal year 1984 (FY84) to FY89 inclusive.^ Using the observed levels of utilization for the 48 months between FY84 and FY87, five techniques were used to forecast monthly levels of utilization for FY88 and FY89. Forecasts were compared to the observed levels of utilization for these years. Monthly forecasts were also produced for FY90 and FY91.^ Forecasts for days of care provided were not produced. Current inpatients with very long lengths of stay contribute a substantial amount of this indicator and it cannot be accurately calculated.^ During the six year period between FY84 and FY89, average length of stay declined substantially, nationally and regionally. The discharge rate was relatively stable, while the multi-stay rate increased slightly during this period. FY90 and FY91 forecasts show a continued decline in the average length of stay, while the discharge rate is forecast to decline slightly and the multi-stay rate is forecast to increase very slightly.^ Over a 24 month ahead period, all three indicators were forecast within a 10 percent average monthly error. The 12-month ahead forecast errors were slightly lower. Average length of stay was less easily forecast, while the multi-stay rate was the easiest indicator to forecast.^ No single technique performed significantly better as determined by the Mean Absolute Percent Error, a standard measure of error. However, Autoregressive Integrated Moving Average (ARIMA) models performed well overall and are recommended for short-term forecasting of VA hospital utilization. ^

TECHNOLOGY ASSESSMENT: SMALL-VOLUME INFUSION PUMPS

"Technology assessment is a comprehensive form of policy research that examines the short- and long-term social consequences of the application or use of technology" (US Congress 1967).^ This study explored a research methodology appropriate for technology assessment (TA) within the health industry. The case studied was utilization of external Small-Volume Infusion Pumps (SVIP) at a cancer treatment and research center. Primary and secondary data were collected in three project phases. In Phase I, hospital prescription records (N = 14,979) represented SVIP adoption and utilization for the years 1982-1984. The Candidate Adoption-Use (CA-U) diffusion paradigm developed for this study was germane. Compared to classic and unorthodox curves, CA-U more accurately simulated empiric experience. The hospital SVIP 1983-1984 trends denoted assurance in prescribing chemotherapy and concomitant balloon SVIP efficacy and efficiency. Abandonment of battery pumps was predicted while exponential demand for balloon SVIP was forecast for 1985-1987. In Phase II, patients using SVIP (N = 117) were prospectively surveyed from July to October 1984; the data represented a single episode of therapy. The questionnaire and indices, specifically designed to measure the impact of SVIP, evinced face validity. Compeer group data were from pre-SVIP case reviews rather than from an inpatient sample. Statistically significant results indicated that outpatients using SVIP interacted socially more than inpatients using the alternative technology. Additionally, the hospital's education program effectively taught clients to discriminate between self care and professional SVIP services. In these contexts, there was sufficient evidence that the alternative technology restricted patients activity whereas SVIP permitted patients to function more independently and in a social lifestyle, thus adding quality to life. In Phase III, diffusion forecast and patient survey findings were combined with direct observation of clinic services to profile some economic dimensions of SVIP. These three project phases provide a foundation for executing: (1) cost effectiveness analysis of external versus internal infusors, (2) institutional resource allocation, and (3) technology deployment to epidemiology-significant communities. The models and methods tested in this research of clinical technology assessment are innovative and do assess biotechnology. ^

DISCHARGE PLANNING: A PROCESS MODEL

As the requirements for health care hospitalization have become more demanding, so has the discharge planning process become a more important part of the health services system. A thorough understanding of hospital discharge planning can, then, contribute to our understanding of the health services system. This study involved the development of a process model of discharge planning from hospitals. Model building involved the identification of factors used by discharge planners to develop aftercare plans, and the specification of the roles of these factors in the development of the discharge plan. The factors in the model were concatenated in 16 discrete decision sequences, each of which produced an aftercare plan.^ The sample for this study comprised 407 inpatients admitted to the M. D. Anderson Hospital and Tumor Institution at Houston, Texas, who were discharged to any site within Texas during a 15 day period. Allogeneic bone marrow donors were excluded from the sample. The factors considered in the development of discharge plans were recorded by discharge planners and were used to develop the model. Data analysis consisted of sorting the discharge plans using the plan development factors until for some combination and sequence of factors all patients were discharged to a single site. The arrangement of factors that led to that aftercare plan became a decision sequence in the model.^ The model constructs the same discharge plans as those developed by hospital staff for every patient in the study. Tests of the validity of the model should be extended to other patients at the MDAH, to other cancer hospitals, and to other inpatient services. Revisions of the model based on these tests should be of value in the management of discharge planning services and in the design and development of comprehensive community health services.^

Clostridium difficile infection (CDI) in HIV-positive patients

The main aim of this study was to look at the association of Clostridium difficile infection (CDI) and HIV. A secondary goal was to look at the trend of CDI-related deaths in Texas from 1999-2011. To evaluate the coinfection of CDI and HIV, we looked at 2 datasets provided by CHS-TDSHS, for 13 years of study period from 1999-2011: 1) Texas death certificate data and 2) Texas hospital discharge data. An ancillary source of data was national level death data from CDC. We did a secondary data analysis and reported the age-adjusted death rates (mortality) and hospital discharge frequencies (morbidity) for CDI, HIV and for CDI+HIV coinfection.^ Since the turn of the century, CDI has reemerged as an important public health challenge due to the emergence of hypervirulent epidemic strains. From 1999-2011, there has been a significant upward trend in CDI-related death rates; in the state of Texas alone, CDI mortality rate has increased 8.7 fold in this time period at the rate of 0.2 deaths per year per 100,000 individuals. On the contrary, mortality due to HIV has decreased by 46% and has been trending down. The demographic groups in Texas with the highest CDI mortality rates were elderly aged 65+, males, whites and hospital inpatients. The epidemiology of C. difficile has changed in such a way that it is not only staying confined to these traditional high-risk groups, but is also being increasingly reported in low-risk populations such as healthy people in the community (community acquired C. difficile), and most recently immunocompromised patients. Among the latter, HIV can worsen the adverse health outcomes of CDI and vice versa. In patients with CDI and HIV coinfection, higher mortality and morbidity was found in young & middle-aged adults, blacks and males, the same demographic population that is at higher risk for HIV. As with typical CDI, the coinfection was concentrated in the hospital inpatients. Of all the CDI-related deaths in USA from 1999-2010, in the 25-44 year age group, 13% had HIV infection. Of all CDI-related inpatient hospital discharges in Texas from 1999-2011, in patients 44 years and younger, 17% had concomitant HIV infection. Therefore, HIV is a possible novel emerging risk factor for CDI.^

Indeterminate QunatiFERON-TB Gold In-Tube assay results in association with procedural specimen collection in children

BACKGROUND. The development of interferon-gamma release assays (IGRA) has introduced powerful tools in diagnosing latent tuberculosis infection (LTBI) and may play a critical role in the future of tuberculosis diagnosis. However, there have been reports of high indeterminate results in young patient populations (0-18 years). This study investigated results of the QunatiFERON-TB Gold In-Tube (QFT-GIT) IGRA in a population of children (0-18 years) at Texas Children's Hospital in association with specimen collection procedures using surrogate variables. ^ METHODS. A retrospective case-control study design was used for this investigation. Cases were defined as having QFT-GIT indeterminate results. Controls were defined as having either positive or negative results (determinates). Patients' admission status, staff performing specimen collection, and specific nurse performing specimen collection were used as surrogates to measure specimen collection procedures. ^ To minimize potential confounding, abstraction of patients' electronic medical records was performed. Abstracted data included patients' medications and evaluation at the time of QFT-GIT specimen collection in addition to their medical history. QFT-GIT related data was also abstracted. Cases and controls were characterized using chi-squared tests or Fisher's exact tests across categorical variables. Continuous variables were analyzed using one-way ANOVA and t-tests for continuous variables. A multivariate model was constructed by backward stepwise removal of statistically significant variables from univariate analysis. ^ RESULTS. Patient data was abstracted from 182 individuals aged 0-18 years from July 2010 to August 2011 at Texas Children's Hospital. 56 cases (indeterminates) and 126 controls (determinates) were enrolled. Cancer was found to be an effect modifier with subsequent stratification resulting in a cancer patient population too small to analyze (n=13). Subsequent analyses excluded these patients. ^ The exclusion of cancer patients resulted in a population of 169 patients with 49 indeterminates (28.99%) and 120 determinates (71.01%), with mean ages of 9.73 (95% CI: 8.03, 11.43) years and 11.66 (95% CI: 10.75, 12.56) years (p = 0.033), respectively. Median age of patients who were indeterminates and determinates were 12.37 and 12.87 years, respectively. Lack of data for our specific nurse surrogate (QFTNurse) resulted in its exclusion from analysis. The final model included only our remaining surrogate variables (QFTStaff and QFTInpatientOutpatient). The staff collecting surrogate (QFTStaff) was found to be modestly associated with indeterminates when nurses collected the specimen (OR = 1.54, 95% CI: 0.51, 4.64, p = 0.439) in the final model. Inpatients were found to have a strong and statistically significant association with indeterminates (OR = 11.65, 95% CI: 3.89, 34.9, p < 0.001) in the final model. ^ CONCLUSION. Inpatient status was used as a surrogate for indication of nurse drawn blood specimens. Nurses have had little to no training regarding shaking of tubes versus phlebotomists regarding QFT-GIT testing procedures. This was also measured by two other surrogates; specifically a medical note stating whether a nurse or phlebotomist collected the specimen (QFTStaff) and the name and title of the specific nurse if collection was performed by a nurse (QFTNurse). Results indicated that inpatient status was a strong and statistically significant factor for indeterminates, however, nurse collected specimens and indeterminate results had no statistically significant association in non-cancer patients. The lack of data denoting the specific nurse performing specimen collection excluded the QFTNurse surrogate in our analysis. ^ Findings suggests training of staff personnel in specimen procedures may have little effect on the number of indeterminates while inpatient status and thus possibly illness severity may be the most important factor for indeterminate results in this population. The lack of congruence between our surrogate measures may imply that our inpatient surrogate gauged illness severity rather than collection procedures as intended. ^ Despite the lack of clear findings, our analysis indicated that more than half of indeterminates were found in specimens drawn by nurses and as such staff training may be explored. Future studies may explore methods in measuring modifiable variables during pre-analytical QFT-GIT procedures that can be discerned and controlled. Identification of such measures may provide insight into ways to lowering indeterminate QFT-GIT rates in children.^