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.

Comparison of clinical knowledge management capabilities of commercially-available and leading internally-developed electronic health records.

BACKGROUND: We have carried out an extensive qualitative research program focused on the barriers and facilitators to successful adoption and use of various features of advanced, state-of-the-art electronic health records (EHRs) within large, academic, teaching facilities with long-standing EHR research and development programs. We have recently begun investigating smaller, community hospitals and out-patient clinics that rely on commercially-available EHRs. We sought to assess whether the current generation of commercially-available EHRs are capable of providing the clinical knowledge management features, functions, tools, and techniques required to deliver and maintain the clinical decision support (CDS) interventions required to support the recently defined "meaningful use" criteria. METHODS: We developed and fielded a 17-question survey to representatives from nine commercially available EHR vendors and four leading internally developed EHRs. The first part of the survey asked basic questions about the vendor's EHR. The second part asked specifically about the CDS-related system tools and capabilities that each vendor provides. The final section asked about clinical content. RESULTS: All of the vendors and institutions have multiple modules capable of providing clinical decision support interventions to clinicians. The majority of the systems were capable of performing almost all of the key knowledge management functions we identified. CONCLUSION: If these well-designed commercially-available systems are coupled with the other key socio-technical concepts required for safe and effective EHR implementation and use, and organizations have access to implementable clinical knowledge, we expect that the transformation of the healthcare enterprise that so many have predicted, is achievable using commercially-available, state-of-the-art EHRs.

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. ^

Understanding treatment-related symptoms, symptom management techniques, and symptom management self-efficacy in a sample of non-muscle invasive bladder cancer patients

The current literature available on bladder cancer symptom management from the perspective of the patients themselves is limited. There is also limited psychosocial research specific to bladder cancer patients and no previous studies have developed and validated measures for bladder cancer patients’ symptom management self-efficacy. The purpose of this study was to investigate non-muscle invasive bladder cancer patients’ health related quality of life through two main study objectives: (1) to describe the treatment related symptoms, reported effectiveness of symptom-management techniques, and the advice a sample of non-muscle invasive bladder cancer patients would convey to physicians and future patients; and (2) to evaluate Lepore’s symptom management self-efficacy measure on a sample of non-muscle invasive bladder cancer patients. Methods. A total of twelve (n=12) non-muscle invasive bladder cancer patients participated in an in-depth interview and a sample of 46 (n=4) non-muscle invasive bladder cancer patients participated in the symptom-management self-efficacy survey. Results. A total of five symptom categories emerged for the participants’ 59 reported symptoms. Four symptom management categories emerged out of the 71 reported techniques. A total of 62% of the participants’ treatment related symptom-management techniques were reported as effective in managing their treatment-related symptoms. Five advice categories emerged out of the in-depth interviews: service delivery; medical advice; physician-patient communication; encouragement; and no advice. An exploratory factor analysis indicated a single-factor structure for the total population and a multiple factor structure for three subgroups: all males, married males, and all married participants. Conclusion. These findings can inform physicians and patients of effective symptom-management techniques thus improving patients’ health-related quality of life. The advice these patients’ impart can improve service-delivery and patient education.^

Correlates of post-diagnosis weight management among female breast cancer survivors: An Internet survey

Objective. Weight gain after cancer treatment is associated with breast cancer recurrence. In order to prolong cancer-free survivorship, interventions to manage post-diagnosis weight are sometimes conducted. However, little is known about what factors are associated with weight management behaviors among cancer survivors. In this study, we examined associations of demographic, clinical, and psychosocial variables with weight management behaviors in female breast cancer survivors. We also examined whether knowledge about post-diagnosis weight gain and its risk is associated with weight management behaviors. ^ Methods. 251 female breast cancer survivors completed an internet survey. They reported current performance of three weight management behaviors (general weight management, physical activity, and healthy diet). We also measured attitude, elf-efficacy, knowledge and social support regarding these behaviors along with demographic and clinical characteristics. ^ Results. Multiple regression models for the weight management behaviors explained 17% of the variance in general weight management, 45% in physical activity and 34% in healthy dieting. The models had 9–14 predictor variables which differed in each model. The variables associated with all three behaviors were social support and self-efficacy. Self-efficacy showed the strongest contribution in all models. The knowledge about weight gain and its risks was not associated with any weight management behaviors. However, women who obtained the knowledge during cancer treatment were more likely to engage in physical activity and healthy dieting. ^ Conclusions. The findings suggest that an intervention designed to increase their self-efficacy to manage weight, to be physically active, to eat healthy will effectively promote survivors to engage in these behaviors. Knowledge may motivate women to manage post-diagnosis weight about risk if information is provided during cancer treatment.^