Patient entered data

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Many patients, health professionals, and other stakeholders are interested in the feasibility, scientific acceptability, usability, and usefulness of data entered directly by patients for review in the primary care summary. While the perception is that the practice has advanced considerably in the last decade, the evidence about use and best practices of use are not yet well specified. This review attempts to capture the state of the evidence and current practice in order to facilitate appropriate, beneficial use of patient entered data.

This is a review for the primary care informatics working group of AMIA.

Premise / justification

Scope of the work

Patient entered data for review in primary care setting

  • Information not knowledge? (e.g., there is a summary on electronic patient education – dispensing knowledge and evaluating)
  • Telemonitoring? (EPC review exists, even with update)
  • Other subdomains need to be specified ...

Questions Related to Patient-Entered Data

A number of questions have emerged related the issue of patient-entered data collection that would automatically populate the electronic health record. Major issues, each discussed below, include:

  • Trusting the data: Is the data valid and reliable?
  • Populations: What about patients with lower education, literacy or numeracy skills?
  • Privacy: This is major concern for PHRs; won’t this reduce participation?
  • Data Overload: Is it feasible to expect clinicians review all the data patients enter?
  • Responsibility: Who is liable for all data entered?

Review of Research Relevant to Questions

Research using computerized survey applications have measured feasibility, data capture, and patient satisfaction for risk factor screening, symptom findings, behavioral measures, and quality of life scores. Most results support using a computerized mode of data entry compared to paper or in-person surveys. Many cite increased speed of data collection and higher rates of user satisfaction. Computerized methods lead to higher rates of completion and reduce missing data, particularly for sensitive problems such as substance abuse and other behaviors.

There is a plausible concern about poorer data completion by individuals with lower levels of education, literacy or numeracy. Research shows computerized survey methods are a reasonable choice for most populations, but attention must be given to usability and technical assistance for those without prior computer experience.

Regarding privacy issues, research has demonstrated taht individuals taking computerized surveys feel they are more private than other modes of questioning. This may be a particularly valuable finding, given the concern about PHRs and privacy. Even with the implicit understanding that their answers will be reviewed, patients appear less inhibited about responding to a computer.

Patients have positive opinions about secure messaging and PHR applications, however, clinicians offer less positive assessments. Clinician concerns center on increased workload and inability to screen for relevant data and information.

Review of previous summaries

  • literature review of primary sources - needs to be completed immediately prior to advancement.


Structure and domains

  • By function? E.g., HL7 EHR-S function involved?
  • By domain of information entered? E.g.,
  • By activity? E.g., formal questionnaires, pre-visit assessment, specific quality / safety components, disease status, etc.

Literature review

Terms for lit review


  1. Connecting Americans to their healthcare. Connecting for Health, Markle Foundation. June 2004.
  2. Ralston JD, Carrell D, Reid R, Anderson M, Moran M, Hereford J. Patient Web Services Integrated with a Shared Medical Record: Patient Use and Satisfaction. J Am Med Inform Assoc. 2007;14(6):798-806.
  3. Weingart SN, Rind D, Tofias Z, Sands DZ. Who uses the patient internet portal? The PatientSite experience.J Am Med Inform Assoc. 2006 Jan-Feb;13(1):91-5.
  4. Zhou YY, Garrido T, Chin H, Wiesenthal AM, Liang LL. Patient access to an electronic health record with secure messaging: impact on primary care utilization. Am J Man Care 2007; 13:418-424.
  5. McGeady D, Kujala J, Ilvonen K. The impact of patient-physician web messaging on healthcare service provision. Int J Med Informatics 2008; 77:12-23.
  6. Halamka J, Mandl KD, Tang P. Early experiences with personal health records. J Am Med Inform Assoc. Oct 18, 2007.
  7. The transformative potential of personal health records. Am Med Inform Assoc. white paper, September 2006.
  8. Aiello EJ, Taplin S et al. In a randomized controlled trial, patients preferred electronic data collection of breast cancer risk factor information in a mammography setting. J Clin Epidem 2006; 59:77-81.
  9. Lee SJ, Kavanaugh L. Best Practice & Res Clin Rheum 2007; 21:637-647
  10. VanDenKerKhof EG, Goldstein DH, Blaine WC, Rimmer MJ. Anesth Analg 2005; 101:1075-80.
  11. Turner CF, Ku L, Rogers SM, Lindberg LD, Pleck JL, Sonenstein FL. Adolescent sexual behavior, drug use, and violence: increased reporting with computer survey technology. Science 1998; 280:867-873
  12. Edwards SL, Slattery ML, Murtaugh MA, et al. Development and use of touch-screen audio computer-assisted self-interviewing in a study of American Indians. Am J Epidemiology 2007; 165:1336-42.
  13. Tang PC, Ash JS, Bates DW, Overhage JM. Personal health records: definitions, benefits and strategies for overcoming barriers to adoption. JAMIA 2006;13:121-126.
  14. Presentation, Jantos L, Hereford J. Transforming healthcare through patient portals and an e-health strategy.
  15. Lauteslager M, Brouwe HJ, Mohrs J, Bindels PJE, Grundmeijer HGLM. The patient as a source to improve the medical record. Family Practice 2002; 19:167-171.
  16. Ralston JD, et al. Patients experience with diabetes support programme based on an interactive electronic medical record. BMJ 2004; 328

  • local brainstorming and contacts need to be one source


  • Recommend ABC abstract review
  • Then larger abstraction template with inclusion and exclusion criteria included

Formal inclusion and exclusion criteria

Current practice review

  • best practices (expert)
  • examples of archetype systems
  •  ?appendix with all discovered systems?



Contributors to date

David A. Dorr

Susan S. Woods