title: Implementation of a Cloud-Based Electronic Medical Record to Reduce Gaps in the HIV Treatment Continuum in Rural Kenya.
abstract: BACKGROUND
  Electronic medical record (EMR) systems are increasingly being adopted to support the delivery of health care in developing countries and their implementation can help to strengthen pathways of care and close gaps in the HIV treatment cascade by improving access to and use of data to inform clinical and public health decision-making.
  
  
  METHODS
  This study implemented a novel cloud-based electronic medical record system in an HIV outpatient setting in Western Kenya and evaluated its impact on reducing gaps in the HIV treatment continuum including missing data and patient eligibility for ART. The impact of the system was assessed using a two-sample test of proportions pre- and post-implementation of EMR-based data verification and clinical decision support.
  
  
  RESULTS
  Significant improvements in data quality and provision of clinical care were recorded through implementation of the EMR system, helping to ensure patients who are eligible for HIV treatment receive it early. A total of 2,169 and 764 patient records had missing data pre-implementation and post-implementation of EMR-based data verification and clinical decision support respectively. A total of 1,346 patients were eligible for ART, but not yet started on ART, pre-implementation compared to 270 patients pre-implementation.
  
  
  CONCLUSIONS
  EMR-based data verification and clinical decision support can reduce gaps in HIV care, including missing data and eligibility for ART. A cloud-based model of EMR implementation removes the need for local clinic infrastructure and has the potential to enhance data sharing at different levels of health care to inform clinical and public health decision-making. A number of issues, including data management and patient confidentiality, must be considered but significant improvements in data quality and provision of clinical care are recorded through implementation of this EMR model.
authors.affiliation: Uamuzi Bora, Kakamega, Kenya.
authors.forename: John
authors.initials: J
authors.lastname: Haskew
authors.affiliation: Uamuzi Bora, Kakamega, Kenya; University of Durham, Durham, United Kingdom.
authors.forename: Gunnar
authors.initials: G
authors.lastname: Rø
authors.affiliation: British Antarctic Survey Medical Unit, Plymouth, United Kingdom.
authors.forename: Kenrick
authors.initials: K
authors.lastname: Turner
authors.affiliation: Elizabeth Glazer Paediatric AIDS Foundation, Nairobi, Kenya.
authors.forename: Davies
authors.initials: D
authors.lastname: Kimanga
authors.affiliation: National AIDS and STI Control Program, Nairobi, Kenya.
authors.forename: Martin
authors.initials: M
authors.lastname: Sirengo
authors.affiliation: Ministry of Health, Nairobi, Kenya.
authors.forename: Shahnaaz
authors.initials: S
authors.lastname: Sharif
mesh_terms: D022126:Access to Information; D000293:Adolescent; D000328:Adult; D000368:Aged; D003266:Continuity of Patient Care; D003657:Decision Making; D020000:Decision Support Systems, Clinical; D003906:Developing Countries; D057286:Electronic Health Records; D005260:Female; D015658:HIV Infections / Q000628:therapy*; D006801:Humans; D020407:Internet; D007630:Kenya; D008297:Male; D008875:Middle Aged; D011634:Public Health; D019035:Rural Health Services / Q000458:organization & administration*; D012424:Rural Population; D055815:Young Adult