The utility of rapid participatory appraisal for community assessment, diagnosis, and policy development

The selection of a model to guide the understanding and resolution of community problems is an important issue relating to the foundation of public health practice: assessment, policy development, and assurance. Many assessment models produce a diagnosis of community weaknesses, but fail to promote planning and interventions. Rapid Participatory Appraisal (RPA) is a participatory action research model which regards assessment as the first step in the problem solving process, and claims to achieve assessment and policy development within limited resources of time and money. Literature documenting the fulfillment of these claims, and thereby supporting the utility of the model, is relatively sparse and difficult to obtain. Very few articles discuss the changes resulting from RPA assessments in urban areas, and those that do describe studies conducted outside the U.S.A. ^ This study examines the utility of the RPA model and its underlying theories: systems theory, grounded theory, and principles of participatory change, as illustrated by the case study of a community assessment conducted for the Texas Diabetes Institute (TDI), San Antonio, Texas, and subsequent outcomes. Diabetes has a high prevalence and is a major issue in San Antonio. Faculty and students conducted the assessment by informal collaboration between two nursing and public health assessment courses, providing practical student experiences. The study area was large, and the flexibility of the model tested by its use in contiguous sub-regions, reanalyzing aggregated results for the study area. Official TDI reports, and a mail survey of agency employees, described policy development resulting from community diagnoses revealed by the assessment. ^ The RPA model met the criteria for utility from the perspectives of merit, worth, efficiency, and effectiveness. The RPA model best met the agencies' criteria (merit), met the data needs of TDI in this particular situation (worth), provided valid results within budget, time, and personnel constraints (efficiency), and stimulated policy development by TDI (effectiveness). ^ The RPA model appears to have utility for community assessment, diagnosis, and policy development in circumstances similar to the TDI diabetes study. ^

Near infra-red-activatable nanocarriers for selective cancer diagnosis and treatment

Standard treatment strategies for cancer patients include surgery, radiation therapy, and chemotherapy. Although these strategies have been proven effective, they also have associated limitations. An attractive and innovative approach that can be used alone or in combination with the above modalities is based on the systemic or topical administration of a nanomaterial-based photoactive compound. Interaction with light in the near infrared (NIR) region results in either emission of fluorescence, which can be used for photodetection, or absorption of light which results in phototherapy. Nanomaterials have the advantage of providing multi-functional and unique properties in a single device that cannot be readily acquired with conventional small molecular weight compounds. ^ In this study, three different novel nanocarrier systems were designed and evaluated in mediating photodetection and phototherapy in the NIR. The first compound synthesized was a dual-labeled magnetic resonance/optical imaging agent for sentinel lymph node mapping and biopsy. This dual-labeled agent combines the high resolution of magnetic resonance imaging with the highly sensitive detection of optical imaging. The second imaging agent was an activatable optical imaging agent used to monitor cathepsin B activity in vivo and to probe the degradation of poly(L-glutamic acid). This polymeric nanocarrier offers highly sensitive technique for the detection of enzymatic activity, with is not yet possible with small molecular weight compounds. The third agent was a C225-conjugated hollow nanoshell that is targeted to epidermal growth factor receptors. This targeting agent has been demonstrated to mediate photothermal therapy both in vitro and in vivo. ^ These nanocarrier systems are an invaluable tool for the detection of cancer and many other diseases. With improved targeted delivery of these agents, the ability to diagnose diseases will become more sensitive and more specific. Finally, when designed properly, these agents would allow concurrent diagnosis and treatment of patients of various diseases. ^

PROJECTION OF HEALTH DEMAND IN TERMS OF HOSPITAL ADMISSIONS FOR SELECTED DIAGNOSES IN HEALTH SYSTEMS AGENCY SERVICE AREAS

The National Health Planning and Resources Development Act of 1974 (Public Law 93-641) requires that health systems agencies (HSAs) plan for their health service areas by the use of existing data to the maximum extent practicable. Health planning is based on the identificaton of health needs; however, HSAs are, at present, identifying health needs in their service areas in some approximate terms. This lack of specificity has greatly reduced the effectiveness of health planning. The intent of this study is, therefore, to explore the feasibility of predicting community levels of hospitalized morbidity by diagnosis by the use of existing data so as to allow health planners to plan for the services associated with specific diagnoses.^ The specific objectives of this study are (a) to obtain by means of multiple regression analysis a prediction equation for hospital admission by diagnosis, i.e., select the variables that are related to demand for hospital admissions; (b) to examine how pertinent the variables selected are; and (c) to see if each equation obtained predicts well for health service areas.^ The existing data on hospital admissions by diagnosis are those collected from the National Hospital Discharge Surveys, and are available in a form aggregated to the nine census divisions. When the equations established with such data are applied to local health service areas for prediction, the application is subject to the criticism of the theory of ecological fallacy. Since HSAs have to rely on the availability of existing data, it is imperative to examine whether or not the theory of ecological fallacy holds true in this case.^ The results of the study show that the equations established are highly significant and the independent variables in the equations explain the variation in the demand for hospital admission well. The predictability of these equations is good when they are applied to areas at the same ecological level but become poor, predominantly due to ecological fallacy, when they are applied to health service areas.^ It is concluded that HSAs can not predict hospital admissions by diagnosis without primary data collection as discouraged by Public Law 93-641. ^