PhD Student, University of Miami Health Systems in Urban Poverty Zones Industrial Engineering Proposals for Integrated mHealth Solutions Caitlin Augustin PhD Student, University of Miami c.augustin@umiami.edu Dulce Sanchez Industrial Engineer, Macys Corporation Shihab Asfour, PhD Chair, University of Miami Department of Industrial Engineering Nina Miville, DBA Associate Professor, University of Miami Department of Industrial Engineering

Project Background Partnership with Project Medishare Hospital in Port au Prince, Haiti and Department of Community Service at the University of Miami Miller School of Medicine to identify key problems with free clinic operations and present innovative engineering solutions Funding provided by Neighbors for Neighbors, International

Key Discoveries Free health clinics (also called safety net clinics) are severely understaffed which leads to record keeping errors, misdiagnosis, and minimal patient retention A solution to these problems can be found through the use of mHealth technologies. mHealth technologies can be developed in house and customized to the clinic’s specific needs Training and education materials can be provided through a web platform.

Structure of the Presentation Project Introduction Site Studies Recommendations Applications Data Analytics Web Platform Conclusion

Project Introduction The Universal Declaration of Human Rights, adopted by the United Nations in 1948, proclaimed that "everyone has the right to a standard of living adequate for the health and well-being of oneself and one's family, including food, clothing, housing, and medical care."

Problem Statement The most severe problem in global public health is the profound lack of trained local healthcare workers. The World Health Organization notes critical healthcare workforce shortages in 57 countries—and a global deficit of 2.4 million doctors, nurses, and midwives.

Project Objectives Identify barriers to operations in free clinics Analyze key problems in patient retention in free clinics Apply industrial engineering tools to enhance operational efficiency Develop telemedicine tools for patient management in free clinics

General Assessment Methodology Performed a literature review Selected four free clinic sites Employed industrial engineering tools of facilities layout, time studies, and work studies for onsite data collection Conducted on-site interviews with the directors, administrators and other personnel of the mobile clinics and hospitals. Developed analysis tools for cost analysis, resource allocation, patients seen

Industrial Engineering Tools Used Risk Assessment Models: Failure Mode and Effects Analysis, health and safety risk assessment Time studies :Patient in system and operations of the telemedicine operators Work sampling studies: Current system analysis from doctor, nurse, check in perspectice Time and motion studies: Therblig analysis and design to better suite the ergonomic needs of telemedicine operators. Statistical Quality Control: Xbar and R charts created Cost Analysis: Created a cost analysis of the cost required to implement telemedicine in various situations. Optimization models: Usage of population density, safety and availability of routes were identify to created the optimum routes for the telemedicine operators to travel. Models include traveling salesman and product-mix Decision Support Systems: Programs were designed in VBA/Excel for managers to create ARENA simulation model: Model was created to analyze the impact of the telemedicine. Engineering Project Management: Project was organized and managed using software such as Microsoft Project, and Microsoft Visio.

Study Sites Eight hundred thirty-seven million urbanites currently reside in densely populated, overcrowded unsanitary conditions often lacking access to basic health, water and sanitation services. -United Nations

Project Medishare Hospital Little Haiti DOCS Clinic Study Locations Project Medishare Hospital San Juan Bosco Clinic Little Haiti DOCS Clinic South Dade DOCS Clinic

General Study Observations Fundamental functions 1) providing cost-effective quality care, 2) educating the community on health issues 3) providing a medical and social structure deeply embedded in the neighborhoods Backgrounds of clinic directors vary from certified physicians to individuals with no professional background in the medical fields Medical record management varies between clinics but each dealt with inadequate storage, incomplete records and follow up care All clinics are consistently understaffed and rely on volunteers to provide services Each clinic relied on grants and donations for the bulk of its annual budget

Data Collection Barriers to Health Care Access Population according to economic class lowest 25% 26-50th % 51-75% 75-100% Distance from Health Center (miles)  6.7 10  10  x Usage of Public Transportation as Primary form of transport 74.3% 39% 6.3% x Uninsured  36.64% 27.42% 19.85% Immigrant Population 92.90%  85% 50.32% No Citizenship 49.38% Patients 60% 25%  15%  Adapted from Cervantes-Rodriguez, M. Free Clinics: Their Role as Safety Net Providers 2009

Data Collection Hospital Services Provided

Data Collection Hospital Utilization Data

General Recommendations Let’s send in doctors to save people from cholera. Let’s send in aid workers to build sustainable sanitation and water systems to help people help themselves. Let’s help educate Haitian children and improve the port so that it can become an exporter. But, above all, let’s send in business investors to create jobs. -Nick Kristof

Recommendations Adoption of mHealth technologies to reduce bottlenecks in clinic, have a consistent patient record, and increase follow-up care Integration of patient records into OpenMRS Provision of training to managers on mHealth and optimization Usage of tools developed for data management and maximize existing clinic resources

Tools Recommended and Designed End To End mHealth Applications Android-based Sana General Form Iphone-based mHealth engineering General Form HTML 5 application Data Analytics Decision support systems for optimization of travel and ordering Data mining tools for disease vector analysis Arena simulation for evaluation of new techniques Web Platform Tools and apps for download Videos Presentations Training Materials Literature Review

Applications “Biggest impacts of mhealth: patient reminders, supply chains for commodities, health records” -Bill Gates

Application Design Designed to promote patient care by providing doctor designed forms for patient intake/triage that can be operated from a mobile device by unskilled workers Upload capability to OpenMRS Required information Demographic information: patient name, sex, birth date, location Vitals: patient height, weight, blood pressure, temperature Medical History: past surgeries, family history Triage: why the patient is seeking treatment that day.

Applications Designed SANA Android App SeattleClouds Iphone App

Decision Support Systems Data in isolation is not very meaningful. It does not reveal the total picture. You need to present data in some context. Suppose you are presenting this data; India's military budget is $ XYZ billion. This makes less sense in isolation. But once you look at it in relation to some other data point (say military budget of US) then you get a better picture. Comparison makes data more meaningful. -David McCandless

Decision Support System General Questions Distance to Care Routes Patients seen/day mHealth technology purchases per hospital Distance: traveling salesman Patients: lp optimization problem Phones: inventory control problem

Ordering Optimization Product-mix model Inputs of hours open, investment budget, total staff, current patients seen With a $10,000 investment budget, Project Medishare could purchase Two tablets Three phones One computer training course 4.45 FTE Nurse for one year

Patient Maximization Maximin model Inputs of hours open, investment budget, total staff, current patients seen Using mHealth Project Medishare could increase the number of patients seen per day up to 43%

Distance to Care Minimization Traveling salesman problem model Five mobile clinics maintained by Project Medishare Travel distance to mobile clinics maintained in Haiti’s most poverty stricken areas can be reduced by over 70%

Disease Mapping Program The power of mHealth allows data to be collected, stored, and analyzed virtually everywhere. This DSS is designed for the healthcare worker with limited excel experience to create a map of disease populations and assess risk to determine treatment. Input of latitude and longitude, type of disease (from selection menu), notes

we are at the very beginning of the Information Revolution. Conclusions we are at the very beginning of the Information Revolution. This third revolution rewards those who control and process information. It gives them a competitive advantage, and a road to national affluence. -William Kennard

Web Platform mHealthengineering.com is a platform that hosts all applications, data tools, and troubleshooting materials for mHealth projects.

Project Impacts Dissemination of viable mHealth smartphone applications Education provided to free clinic managers A reduction in supply costs due to the reduced use of paper and photocopying. Maximization of existing resources Elimination of redundancies in patient flow, mobile clinic delivery Increases in patients seen/day Increase in patient retention and follow up care

Questions? "We need to focus on the uninsured and those who suffer from health care disparities that we so inadequately addressed in the past." — Sen. Bill Frist (R-Tenn.), Senate majority leader on his priorities for the 108th Congress