<p> Radiation oncology has evolved as an advanced tool in treating chronic diseases from a mere experimental application of X-rays. These advances were made possible due to combined efforts of physicians, clinicians and information technology professionals. The Radiation Oncologist depends on clinical and information technology disciplines to solve complex health conditions. This creates demand for consulting work for information technology professionals who can design, customize and deploy software applications that are used in radiation oncology departments at hospitals. Hri-Tech Consultants, LLC a consulting firm, intends to offer consulting services to medium sized hospitals in Orange County area in design, development and deployment of radiation oncology software applications. The firm&rsquo;s unique strength in Radiation Oncology workflow coupled with Lean Six Sigma and ITIL processes will be rarely matched by other providers in the target market.</p><p>

<p><b>Introduction</b>: Cancer registries collect tumor-related data to monitor incident rates and support population-based research. A common concern with using population-based registry data for research is reporting timeliness. Data timeliness have been recognized as an important data characteristic by both the Centers for Disease Control and Prevention (CDC) and the Institute of Medicine (IOM). Yet, few recent studies in the United States (U.S.) have systemically measured timeliness. </p><p> The goal of this research is to evaluate the quality of cancer data and examine methods by which the reporting process can be improved. The study aims are: 1- evaluate the timeliness of cancer cases at the Indiana State Department of Health (ISDH) Cancer Registry, 2- identify the perceived barriers and facilitators to timely reporting, and 3-reengineer the current reporting process to improve turnaround time. </p><p> <b>Method</b>: For Aim 1: Using the ISDH dataset from 2000 to 2009, we evaluated the reporting timeliness and subtask within the process cycle. For Aim 2: Certified cancer registrars reporting for ISDH were invited to a semi-structured interview. The interviews were recorded and qualitatively analyzed. For Aim 3: We designed a reengineered workflow to minimize the reporting timeliness and tested it using simulation. </p><p> <b>Result</b>: The results show variation in the mean reporting time, which ranged from 426 days in 2003 to 252 days in 2009. The barriers identified were categorized into six themes and the most common barrier was accessing medical records at external facilities. </p><p> We also found that cases reside for a few months in the local hospital database while waiting for treatment data to become available. The recommended workflow focused on leveraging a health information exchange for data access and adding a notification system to inform registrars when new treatments are available. </p>

<p> Lung cancer is the leading cause of cancer death in the United States and survival rates of American Indian and Alaska Native (AIAN) patients are worse than those of non-Hispanic White (NHW) patients. A contributing factor to the worse outcomes may be lower healthcare utilization of AIAN patients. But improving healthcare utilization of AIAN to levels used comparable to those of NHW might increase costs of their care to amounts comparable to those of NHW. <b>Objectives:</b> 1) To examine differences in total healthcare costs and healthcare utilization 12 months following lung cancer diagnosis between AIAN patients and NHW patients, 2) To examine differences in total healthcare costs and healthcare utilization during the end-of-life period (last 6 months of life) between AIAN patients and NHW patients who died from lung cancer or any cause, and 3) To compare the incidence of depression disorder 60 months after cancer diagnosis and determine depression treatment utilization among those with a depression disorder. <b>Methods:</b> The Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset was used. Patients included in the study were those age 65 years and older, diagnosed with lung cancer between 2000 and 2011, Part A coverage, Part B coverage and no managed care plan before. Diagnosis and procedure codes were used to identify costs, utilization, and depression diagnoses. The propensity score matching method was used to balance groups. A generalized linear model (GLM) was used for costs analysis and the negative binomial regression model was used to analyze healthcare utilization. A Cox proportional hazards regression model was used to identify risk factors for new diagnosis of depression. <b>Results:</b> Being AIAN was associated with lower total healthcare costs 12 months following lung cancer diagnosis. In contrast, being AIAN was not associated with total healthcare costs six months before date of death among patients diagnosed with lung cancer and &le; 6 month survival time. The incidence of diagnosis of depression disorder 60 months after lung cancer diagnosis was 3.67% for AIAN patients and 6.16% for NHW patients. The mean number of depression treatment visits suggests higher utilization among AIAN patients compared with NHW patients. AIAN patients were not at increased risk for depression after cancer diagnosis. <b>Conclusions:</b> The healthcare utilization of AIAN patients with lung cancer could be improved while keeping costs of care no higher than those of NHW patients. But any improvements of health care use would need to take account of the variability among AIAN patients receiving health care 12 months following cancer diagnosis, in the last six months of life, and after depression disorder diagnosis.</p><p>