<p> <b>Background:</b> Obesity has recently been classified by the American Medical Association (AMA) as a disease which, if unrecognized and unaddressed in childhood, causes multiple medical and psychological complications that can impact both personal and population health. Unprecedented funding is being invested in electronic health records to improve quality, safety, and delivery of healthcare and reduce healthcare costs. Scant literature has evaluated the use of aids in the electronic health record (EHR) to identify obesity. </p><p> <b>Objectives:</b> The purpose of this study was to determine to what extent the tools available in an EHR for automatic Body Mass Index (BMI) calculation based on height and weight documentation are used by pediatricians to correctly identify obesity in children. Secondary objectives were to evaluate quality of data input (discrete vs. free text) and see if there is any variation in rates of identification among patients of different socio-demographic characteristics and trainees of different levels. </p><p> <b>Methods:</b> We conducted a retrospective chart review for patients aged 2&ndash;18 years seen for a well-child visit at New York Presbyterian Hospital between January 2011 and January 2014, where it is standard practice at these visits to take height and weight measurements. The EHR automatically populates these values onto growth curves, converting them into BMI with percentiles. Standardized definitions from the Centers for Disease Control and Prevention (CDC) 2010 were used to qualify overweight and obese based on BMI. We determined the percentage of patients who were overweight or obese (based on CDC percentiles) that had the diagnosis identified by the pediatrician, and then assessed the quality of data input. We assessed laboratory follow up and referrals for all patients, and assessed for demographic differences among patients properly and not properly documented by providers as obese or overweight. </p><p> <b>Results:</b> We reviewed 700 charts in total. Inclusion criteria were all of the patients who had a BMI between 85&ndash;95% (these were grouped as overweight) and a BMI over 95% (obese). 209 patients were overweight or obese and therefore eligible for inclusion. Of the 209 clinically overweight/obese children, 72.2% had some form of documentation of this diagnosis, although the diagnosis was documented more often in the obese vs. overweight child. The diagnosis was most often captured electronically in the free text progress note. Over half of clinically overweight/obese children aged &ge;8 years did not receive follow-up standard laboratory testing, and only about one-quarter of clinically overweight/obese children had documented in-office nutrition guidance. Diagnosis of overweight was higher in females, but it was almost twice as likely that an obese male would be documented as such. Results showed no identification variation based on age or race/ethnicity. There was no difference in recognition of obesity/overweight based on postgraduate year (PGY) or nurse practitioner (NP) status. </p><p> <b>Conclusion:</b> Despite its importance as a public health priority for children, automatic calculation of BMI by use of an EHR led to documentation by a provider as a child being overweight/obese only three quarters of the time. This study suggests that despite increasing focus on using EHRs to improve individual and population health, including for obesity, clinical decision support remains underutilized.</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> Global explosion of mobile technology has engendered a new instrument to address the challenges in public health and to revolutionize the paradigm of healthcare access and delivery system. Today mobile phone coverage has increased to a significant 90% of the world&rsquo;s population. The rising ubiquity and infiltration of mobile phones has kindled the beginning of a new era in healthcare, mobile health (mHealth). mHealth is the amalgamation of mobile telecommunication and multimedia into an on the go mobile health care delivery system. </p><p> Pediatric Pal is a mHealth application targeted to care for children and help build a healthier tomorrow for them. Pediatric Pal is designed to be the &ldquo;Drive Thru&rdquo; for the pediatric healthcare system. The mhealth app focuses on giving patients access to a highly sophisticated medical diagnosis tool. By using latest searching technologies, the system can take a pattern of symptoms in everyday language and instantly compute from our vast database. The app design and development will be outsourced to a web design Hyperlink solutions agency. Database for the app will be maintained in house and test runs will be run within the house. </p><p> The main source of revenue for the app will be from user subscription and upfront cash payment. Premium downloads will bring in the extra revenue as well. </p><p> Pediatric Pal puts world&rsquo;s medical knowledge at the patients fingertips and enables them to make sense of your symptoms. It will change the way patients speak to their doctor forever.</p><p>

<p> Ambulatory care comprises a major and increasingly important part of the U.S. and other countries&rsquo; health care sectors. Every year in the U.S., about 80% of the population seeks care at a doctor&rsquo;s office, amounting to one billion visits. These visits divide almost equally between primary care and specialty clinic organizations. Diagnostic work is part of most ambulatory care, and central to over 40% of patient visits that originate due to a new problem or a flare-up of an ongoing chronic problem. Yet, the risks associated with diagnostic failures have not garnered much attention from health care leaders and policy makers until a recent National Academy of Medicine (NAM 2015) report synthesized research data with the statement that &ldquo;most people will experience at least one diagnostic error in their lifetime, sometimes with devastating consequences.&rdquo; This dissertation first reviews organizational theories and measurement challenges relevant to diagnostic safety and quality in the context of ambulatory care, and then presents three papers analyzing specific organizational factors hypothesized to enable or thwart an accurate and timely diagnosis. The first paper targets delayed diagnosis from missed evidence-based monitoring in high-risk conditions (e.g., cancer) within five specialty clinics in an urban publicly funded health system. The second paper analyzes staff-reported office problems that could lead to diagnostic error (e.g., not having test results when needed) in over 900 primary and specialty clinics across the nation. The third paper examines the associations between two types of time pressure (i.e., encounter-level and practice-level), organizational factors, and patient effects including perceptions of missed diagnostic opportunities. The three primary conclusions from this work are 1) organizational vulnerabilities for missed monitoring common to the different clinics included challenges with data systems, communications handoffs, population-level tracking, and patient activities, leading to the development of &lsquo;design seeds&rsquo; for context-flexible solutions to improve diagnostic quality; 2) two organizational factors&mdash;stage of health information technology (HIT) deployment and patient safety culture are associated with diagnostic-related office problems, and 3) encounter and practice-level time stressors in primary care clinics are associated with perceptions of greater adverse effects on diagnosis and treatment, and worse patients&rsquo; experiences of chronic care from the clinic team, respectively, as well as associated with several organizational factors including HIT, patient-centered culture, relational coordination for interdependent teamwork, and leadership facilitation of changes to address frontline practice challenges. Taken together, the dissertation papers also demonstrate the applicability of the NAM Improving Diagnosis Conceptual Framework for research on ambulatory care organizations. </p><p>

Thesis (Masters Diploma in Technology (Public Health)) -- Cape Technikon, Cape Town, 1992 / In order to evaluate a health education programme for food handlers at a meat plant, a bakery/confectionery and a catering premises, changes in hygiene were assessed by the bacteriological analysis of swabs for hygiene indicator organisms from food contact surfaces. In this evaluation three phases were established on the basis of bacteriological assessment prior to, during and after the education programme. The first phase involved the establishment of a base line for hygiene indicator organisms prior to the education programme by taking 5 sets of bacteriological swabs over a two month period at each of the three premises, each swab set consisting of 14 swabs of food contact surfaces making a total of 210 swabs. During this time the food hygiene educational needs of the employees were assessed and on this basis a set of three video taped presentations were produced relating respectively to personal hygiene, environmental hygiene and food handling practices. The second phase consisted of the implementation of a health education programme involving consecutive tutorial sessions at one month intervals during which the video taped programme was presented. At this stage a further 5 sets of bacteriological swabs was taken at each of the premises. The third phase involved the assessment of hygiene shortly after completion of the education programme by taking a final 5 sets of bacteriological swabs of food contact surfaces at each of the premises over a further two month period. Statistically significant reductions in a number of the indicator organisms were observed during the course of the study.