{"id":28420613,"url":"https://github.com/truongnhatbui/pharmacare","last_synced_at":"2026-01-30T17:31:35.113Z","repository":{"id":296483416,"uuid":"993546870","full_name":"truongnhatbui/pharmacare","owner":"truongnhatbui","description":"AI Improvements for Pharmacies","archived":false,"fork":false,"pushed_at":"2025-05-31T01:58:40.000Z","size":3,"stargazers_count":0,"open_issues_count":4,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-26T16:44:10.918Z","etag":null,"topics":["ai","artificial-intelligence","pharma","pharmacy"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/truongnhatbui.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-05-31T01:53:40.000Z","updated_at":"2025-05-31T01:59:34.000Z","dependencies_parsed_at":"2025-05-31T13:01:06.717Z","dependency_job_id":"c89a4f0f-ba40-48f8-b647-fc5c958b9f34","html_url":"https://github.com/truongnhatbui/pharmacare","commit_stats":null,"previous_names":["truongnhatbui/pharmacare"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/truongnhatbui/pharmacare","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/truongnhatbui%2Fpharmacare","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/truongnhatbui%2Fpharmacare/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/truongnhatbui%2Fpharmacare/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/truongnhatbui%2Fpharmacare/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/truongnhatbui","download_url":"https://codeload.github.com/truongnhatbui/pharmacare/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/truongnhatbui%2Fpharmacare/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28916076,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-30T16:37:38.804Z","status":"ssl_error","status_checked_at":"2026-01-30T16:37:37.878Z","response_time":66,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","artificial-intelligence","pharma","pharmacy"],"created_at":"2025-06-05T03:48:52.816Z","updated_at":"2026-01-30T17:31:35.106Z","avatar_url":"https://github.com/truongnhatbui.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# PharmaCare\nProgram Scenario: AI Improvements for Pharmacies\n\nProgram Overview\n\nA chain of pharmacies, PharmaCare, initiated a program to implement a series of AI improvements aimed at enhancing internal processes and management as well as providing better external customer support. The program included three main projects:\n\nAI-Driven Inventory Management System: To optimize stock levels, reduce waste, and ensure the availability of essential medications.\n\nAI-Based Customer Support Chatbot: To provide 24/7 assistance to customers, answer queries, and provide information on medication availability and usage.\n\nAI-Powered Analytics for Management: To offer insights into sales trends, customer preferences, and operational efficiencies, enabling better decision-making.\n\nProgram Outcome\n\nThe program was largely successful in achieving its goals, with significant improvements in inventory management, customer support, and data analytics. However, there were several notable issues that affected the overall success of the program.\n\nProgram Highlights and Issues\n\nThe AI-driven inventory management system effectively optimized stock levels, leading to a 20% reduction in expired medications and a 15% increase in the availability of essential drugs. However, one of the vendors selected for the AI systems had a personal relationship with a senior manager, and this conflict of interest was not disclosed. This raised concerns about the impartiality of the vendor selection process.\n\nThe AI chatbot successfully handled 80% of customer queries, improving response times and customer satisfaction. On the other hand, during the initial phase, some performance metrics were inaccurately reported to present a more favorable view of the progress. This led to unrealistic expectations and misinformed decision-making.\n\nThe AI-powered analytics provided valuable insights that helped management make informed decisions, resulting in a 10% increase in sales. However, the training materials and support provided were only available in English. This excluded non-English speaking employees from fully benefiting from the training sessions.\n\nComprehensive training programs were conducted to ensure staff were well-versed in using the new AI systems. This led to smoother implementation and operations. Despite this, adequate measures were not taken to ensure data privacy, leading to potential breaches of confidentiality as the AI systems collected and processed customer data.\n\nRegular updates and meetings with stakeholders ensured transparency and alignment with program goals, fostering a cooperative environment. Nevertheless, the implementation team faced an uneven distribution of work, with certain members being overloaded while others had significantly less to do. This affected team morale and productivity.\n\nSummary\n\nWhile the PharmaCare AI improvement program achieved many of its objectives and brought substantial benefits, the issues arising highlighted areas needing improvement. Addressing these ethical lapses would ensure not only the continued success of the program but also the maintenance of high ethical standards and stakeholder trust.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftruongnhatbui%2Fpharmacare","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftruongnhatbui%2Fpharmacare","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftruongnhatbui%2Fpharmacare/lists"}