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Modeling return on investment for an electronic medical record system in Lilongwe, Malawi
OBJECTIVE: To model the financial effects of implementing a hospital-wide electronic medical record (EMR) system in a tertiary facility in Malawi. MATERIALS AND METHODS: We evaluated three areas of impact: length of stay, transcription time, and laboratory use. We collected data on expenditures in t...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Publishing Group
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3721156/ https://www.ncbi.nlm.nih.gov/pubmed/23144335 http://dx.doi.org/10.1136/amiajnl-2012-001242 |
Sumario: | OBJECTIVE: To model the financial effects of implementing a hospital-wide electronic medical record (EMR) system in a tertiary facility in Malawi. MATERIALS AND METHODS: We evaluated three areas of impact: length of stay, transcription time, and laboratory use. We collected data on expenditures in these categories under the paper-based (pre-EMR) system, and then estimated reductions in each category based on findings from EMR systems in the USA and backed by ambulatory data from low-income settings. We compared these potential savings accrued over a period of 5 years with the costs of implementing the touchscreen point-of-care EMR system at that site. RESULTS: Estimated cost savings in length of stay, transcription time, and laboratory use totaled US$284 395 annually. When compared with the costs of installing and sustaining the EMR system, there is a net financial gain by the third year of operation. Over 5 years the estimated net benefit was US$613 681. DISCUSSION: Despite considering only three categories of savings, this analysis demonstrates the potential financial benefits of EMR systems in low-income settings. The results are robust to higher discount rates, and a net benefit is realized even under more conservative assumptions. CONCLUSIONS: This model demonstrates that financial benefits could be realized with an EMR system in a low-income setting. Further studies will examine these and other categories in greater detail, study the financial effects at different levels of organization, and benefit from post-implementation data. This model will be further improved by substituting its assumptions for evidence as we conduct more detailed studies. |
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