THE MULTIPLE LOCATION TIME WEIGHTED INDEX: USING PATIENT ACTIVITY SPACES TO CALCULATE PRIMARY CARE SERVICE AREAS

Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering “free or low cost visits”, meeting “all of the patient’s health care needs”, and seeing “the patient quickly” were all ranked higher than geographic reasons. Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts.

The multiple location time weighted index: Using patient activity spaces to calculate primary care service areas

Geographic health planning analyses, such as service area calculations, are hampered by a lack of patient-specific geographic data. Using the limited patient address information in patient management systems, planners analyze patient origin based on home address. But activity space research done sparingly in public health and extensively in non-health related arenas uses multiple addresses per person when analyzing accessibility. Also, health care access research has shown that there are many non-geographic factors that influence choice of provider. Most planning methods, however, overlook non-geographic factors influencing choice of provider, and the limited data mean the analyses can only be related to home address. This research attempted to determine to what extent geography plays a part in patient choice of provider and to determine if activity space data can be used to calculate service areas for primary care providers. ^ During Spring 2008, a convenience sample of 384 patients of a locally-funded Community Health Center in Houston, Texas, completed a survey that asked about what factors are important when he or she selects a health care provider. A subset of this group (336) also completed an activity space log that captured location and time data on the places where the patient regularly goes. ^ Survey results indicate that for this patient population, geography plays a role in their choice of health care provider, but it is not the most important reason for choosing a provider. Other factors for choosing a health care provider such as the provider offering "free or low cost visits", meeting "all of the patient's health care needs", and seeing "the patient quickly" were all ranked higher than geographic reasons. ^ Analysis of the patient activity locations shows that activity spaces can be used to create service areas for a single primary care provider. Weighted activity-space-based service areas have the potential to include more patients in the service area since more than one location per patient is used. Further analysis of the logs shows that a reduced set of locations by time and type could be used for this methodology, facilitating ongoing data collection for activity-space-based planning efforts. ^

Function of GCIP (CCNDBP1), a helix -loop -helix leucine -zip protein, in cell differentiation and tumorigenesis

Cell growth and differentiation are complex and well-organized processes in which cells respond to stimuli from the environment by carrying out genetic programs. Transcription factors with helix-loop-helix (HLH) motif play critical roles in controlling the expression of genes involved in lineage commitment, cell fate determination, proliferation and tumorigenesis. This study has examined the roles of GCIP (CCNDBP1) in cell differentiation and tumorigenesis. GCIP is a recently identified HLH-leucine zipper protein without a basic region like the Id family of proteins. However, GCIP shares little sequence homology with the Id proteins and has domains with high acidic amino acids and leucine-rich regions following the HLH domain like c-Myc. Here we firstly demonstrate that GCIP is a transcription regulator related to muscle differentiation program. Overexpression of GCIP in C2C12 cells not only promotes myotube formation but also upregulates myogenic differentiation biomarkers, including MHC and myogenein. On the other hand, our finding also suggests that GCIP is a potential tumor suppressor related to cell cycle control. Expression of GCIP was significantly down-regulated in colon tumors as compared to normal colon tissues. Overexpression of GCIP in SW480 colon cancer cell line resulted in a significant inhibition on tumor cell colony formation on soft agar assays while silencing of GCIP expression by siRNA can promote cell proliferation and colony formation. In addition, results from transgenic mice specifically expressing GCIP in liver also support the idea that GCIP is involved in the early stage of hepatocarcinogenesis and decreased susceptibility to chemical hepatocarcinogenesis. ^