Implementation of a Cloud-Based Medication Inventory System in Two NGO-Supported Clinics in El Salvador
Citation
Maul, Andrew Jordan. 2020. Implementation of a Cloud-Based Medication Inventory System in Two NGO-Supported Clinics in El Salvador. Doctoral dissertation, Harvard Medical School.Abstract
PURPOSE: Previous studies have demonstrated the utility of digital technology in resource- limited settings. This project sought to build upon that work through the design and implementation of a medication inventory system for two NGO-supported clinics (one urban and one rural) that had no prior experience using digital technology. The specific aims were to systematically and sustainably deploy cloud-based technology in El Salvador; measure trends in medication usage and expenses; and identify factors that impact the deployment of digital technology in resource-limited settings.METHODS: During observation of each clinic’s operations and meetings with stakeholders, I discovered that the clinics’ paper medication inventory records were limited and inaccurate. I decided to design a digital medication inventory system using Google Sheets, a free, cloud-based software, which I then implemented over three weeks. During this time, I accounted for inventory, taught staff to use the new system, and audited their work. While out-of-country, I have monitored the system online and communicated weekly with clinic staff to troubleshoot issues. At the end of 2019, I analyzed trends in medication usage and expenses using four different sources of available drug price data for medications from each clinic. A new spreadsheet was created for 2020.
RESULTS: After one year, the inventory system is being used by both clinics. It has anecdotally improved the workflow of both employees who use the system. The rural clinic saw 717 patients in 2019. The rural system accounts for 100 medications. A compiled annual medication usage cost estimate for 53 medications was $3,300.86 with inventory value of $23,386.84. The rural system is accurate based on random auditing of medications at the end of 2019. The urban clinic’s system accounts for 73 medications. Of those, a cost estimate for 47 medications for ~6 months was $9,560.80 with an inventory value of $3,595.06. The urban system is inaccurate based on auditing of all medications at the end of 2019. The most used WHO List medications were enalapril (rural) and ibuprofen (urban).
CONCLUSION: It is feasible to deploy cloud-based technology in a resource-limited setting. Simple solutions can positively impact a clinic’s workflow and the perceived experiences of employees. Collecting stakeholder perspectives and tailoring solutions to a clinic’s context is important to achieve buy-in and ensure sustainability. However, partial automation does not guarantee accuracy of a system and vigilance to identify and troubleshoot problems is required.
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