The Environmental Impacts of Electronic Medical Records Versus Paper Records at a Large Eye Hospital in India: Life Cycle Assessment Study.

BACKGROUND: Health care providers worldwide are rapidly adopting electronic medical record (EMR) systems, replacing paper record-keeping systems. Despite numerous benefits to EMRs, the environmental emissions associated with medical record-keeping are unknown. Given the need for urgent climate action, understanding the carbon footprint of EMRs will assist in decarbonizing their adoption and use. OBJECTIVE: We aimed to estimate and compare the environmental emissions associated with paper medical record-keeping and its replacement EMR system at a high-volume eye care facility in southern India. METHODS: We conducted the life cycle assessment methodology per the ISO (International Organization for Standardization) 14040 standard, with primary data supplied by the eye care facility. Data on the paper record-keeping system include the production, use, and disposal of paper and writing utensils in 2016. The EMR system was adopted at this location in 2018. Data on the EMR system include the allocated production and disposal of capital equipment (such as computers and routers); the production, use, and disposal of consumable goods like paper and writing utensils; and the electricity required to run the EMR system. We excluded built infrastructure and cooling loads (eg. buildings and ventilation) from both systems. We used sensitivity analyses to model the effects of practice variation and data uncertainty and Monte Carlo assessments to statistically compare the 2 systems, with and without renewable electricity sources. RESULTS: This location's EMR system was found to emit substantially more greenhouse gases (GHGs) than their paper medical record system (195,000 kg carbon dioxide equivalents [CO2e] per year or 0.361 kg CO2e per patient visit compared with 20,800 kg CO2e per year or 0.037 kg CO2e per patient). However, sensitivity analyses show that the effect of electricity sources is a major factor in determining which record-keeping system emits fewer GHGs. If the study hospital sourced all electricity from renewable sources such as solar or wind power rather than the Indian electric grid, their EMR emissions would drop to 24,900 kg CO2e (0.046 kg CO2e per patient), a level comparable to the paper record-keeping system. Energy-efficient EMR equipment (such as computers and monitors) is the next largest factor impacting emissions, followed by equipment life spans. Multimedia Appendix 1 includes other emissions impact categories. CONCLUSIONS: The climate-changing emissions associated with an EMR system are heavily dependent on the sources of electricity. With a decarbonized electricity source, the EMR system's GHG emissions are on par with paper medical record-keeping, and decarbonized grids would likely have a much broader benefit to society. Though we found that the EMR system produced more emissions than a paper record-keeping system, this study does not account for potential expanded environmental gains from EMRs, including expanding access to care while reducing patient travel and operational efficiencies that can reduce unnecessary or redundant care.

Community Group-Based Models of Medication Delivery: Applicability to Cardiovascular Diseases.

The rising global burden of chronic non-communicable diseases (NCDs) has put a strain on healthcare systems globally, especially in low- and middle-income countries, which have seen disproportionate mortality rates due to non-communicable diseases. These deaths are in part due to challenges with medication adherence, which are compounded by lack of access to medication and weak community support systems. This paper aims to propose a potential solution using models of service delivery in HIV/AIDS, given the many similarities between NCD and HIV/AIDS. Models that have been particularly effective in HIV/AIDS are the community-based peer-support medication delivery groups: medication adherence clubs and community antiretroviral therapy (ART) groups. The positive outcomes from these models, including improved medication adherence and patient satisfaction, provide evidence for their potential success when applied to non-communicable diseases, particularly hypertension and cardiovascular disease.