Appl Clin Inform 2014; 05(01): 284-298
DOI: 10.4338/ACI-2013-11-RA-0096
Research Article
Schattauer GmbH

Using a Scripted Data Entry Process to Transfer Legacy Immunization Data While Transitioning Between Electronic Medical Record Systems

J. Michel
1   Children‘s Hospital of Philadelphia, Pediatrics, Philadelphia, Pennsylvania, United States
,
A. Hsiao
2   Yale School of Medicine, Pediatrics and Emergency Medicine, New Haven, Connecticut, United States
,
A. Fenick
2   Yale School of Medicine, Pediatrics and Emergency Medicine, New Haven, Connecticut, United States
› Author Affiliations
Further Information

Publication History

received: 12 November 2013

accepted: 27 January 2014

Publication Date:
20 December 2017 (online)

Summary

Background: Transitioning between Electronic Medical Records (EMR) can result in patient data being stranded in legacy systems with subsequent failure to provide appropriate patient care. Manual chart abstraction is labor intensive, error-prone, and difficult to institute for immunizations on a systems level in a timely fashion.

Objectives: We sought to transfer immunization data from two of our health system’s soon to be replaced EMRs to the future EMR using a single process instead of separate interfaces for each facility.

Methods: We used scripted data entry, a process where a computer automates manual data entry, to insert data into the future EMR. Using the Center for Disease Control’s CVX immunization codes we developed a bridge between immunization identifiers within our system’s EMRs. We performed a two-step process evaluation of the data transfer using automated data comparison and manual chart review.

Results: We completed the data migration from two facilities in 16.8 hours with no data loss or corruption. We successfully populated the future EMR with 99.16% of our legacy immunization data – 500,906 records – just prior to our EMR transition date. A subset of immunizations, first recognized during clinical care, had not originally been extracted from the legacy systems. Once identified, this data – 1,695 records – was migrated using the same process with minimal additional effort.

Conclusions: Scripted data entry for immunizations is more accurate than published estimates for manual data entry and we completed our data transfer in 1.2% of the total time we predicted for manual data entry. Performing this process before EMR conversion helped identify obstacles to data migration. Drawing upon this work, we will reuse this process for other healthcare facilities in our health system as they transition to the future EMR.

Citation: Michel J, Hsiao A, Fenick A. Using a scripted data entry process to transfer legacy immunization data while transitioning between electronic medical record systems. Appl Clin Inf 2014; 5: 284–298 http://dx.doi.org/10.4338/ACI-2013-11-RA-0096

 
  • References

  • 1 Lehmann CU, Kim GR, Johnson KB. Pediatric Informatics: Computer Applications in Child Health:. Springer;; 2009
  • 2 Hinman AR, Orenstein WA. Adult Immunization: What Can We Learn from the Childhood Immunization Program?. Clinical Infectious Diseases 2007; 44 (12) 1532-1535.
  • 3 Stokley S, Rodewald LE, Maes EF. The impact of record scattering on the measurement of immunization coverage. Pediatrics 2001; 107 (01) 91-96.
  • 4 Wilton R, Pennisi AJ. Evaluating the Accuracy of Transcribed Computer-Stored Immunization Data. Pediatrics 1994; 94 (06) 902-906.
  • 5 Center for Disease Control and Prevention.. General recommendations on immunization --- recommendations of the Advisory Committee on Immunization Practices (ACIP). MMWR Recomm Rep 2011; 60 (02) 1-64.
  • 6 National Vaccine Advisory Committee.. Protecting the Public’s Health: Critical Functions of the Section 317 Immunization Program — A Report of the National Vaccine Advisory Committee. In: Services USDoHH, editor.. 2012
  • 7 Orenstein WA, Hinman AR. The immunization system in the United States — The role of school immunization laws. Vaccine 1999; 17 Supplement 3 (Suppl. 00) S19-S24.
  • 8 Center for Disease Control and Prevention.. Noninfluenza vaccination coverage among adults –United States, 2011. MMWR Morb Mortal Wkly Rep 2013; 62 (04) 66-72.
  • 9 De Serres G, Markowski F, Toth E, Landry M, Auger D, Mercier M, Belanger P, Turmel B, Arruda H, Boulianne N, Ward B, Skowronski D. Largest measles epidemic in North America in a decade - Quebec, Canada, 2011: contribution of susceptibility, serendipity, and superspreading events. J Infect Dis 2013; 207 (06) 990-998.
  • 10 Center for Disease Control and Prevention.. Outbreak of measles--San Diego, California, January-February 2008. MMWR Morb Mortal Wkly Rep 2008; 57 (08) 203-206.
  • 11 Sugerman D, Barskey A, Delea M, Ortega-Sanchez I, Bi D, Ralston K, Rota P, Waters-Montijo K, Lebaron C.. Measles outbreak in a highly vaccinated population, San Diego, 2008: role of the intentionally under-vaccinated. Pediatrics 2010; 125 (Suppl. 04) 747-755.
  • 12 Nguyen MD, Perella D, Watson B, Marin M, Renwick M, Spain CV. Incremental effectiveness of second dose varicella vaccination for outbreak control at an elementary school in Philadelphia, pennsylvania, 2006. Pediatr Infect Dis J 2010; 29 (08) 685-689.
  • 13 Lu L, Suo L, Li J, Zhai L, Zheng Q, Pang X, Bialek SR, Wang C. A varicella outbreak in a school with high one-dose vaccination coverage, Beijing, China. Vaccine 2012; 30 (34) 5094-5098.
  • 14 Chiappini E, Stival A, Galli L, de Martino M. Pertussis re-emergence in the post-vaccination era. BMC Infect Dis 2013; 13: 151.
  • 15 Glanz JM, McClure DL, Magid DJ, Daley MF, France EK, Salmon DA, Hambidge SJ. Parental Refusal of Pertussis Vaccination Is Associated With an Increased Risk of Pertussis Infection in Children. Pediatrics 2009; 123 (06) 1446-1451.
  • 16 Molinari N-AM, Kolasa M, Messonnier ML, Schieber RA. Out-of-Pocket Costs of Childhood Immunizations: A Comparison by Type of Insurance Plan. Pediatrics 2007; 120 (05) e1148-e1156.
  • 17 Loughlin AM, Marchant CD, Adams W, Barnett E, Baxter R, Black S, Casey C, Dekker C, Edwards KM, Klein J, Klein NP, LaRussa P, Sparks R, Jakob K. Causality assessment of adverse events reported to the Vaccine Adverse Event Reporting System (VAERS). Vaccine 2012; 30 (50) 7253-7259.
  • 18 Center for Disease Control and Prevention.. Possible Side-effects from Vaccines. Center for Disease Control and Prevention,2012; Available from: http://www.cdc.gov/vaccines/vac-gen/side-effects.htm.
  • 19 Darden PM, Gustafson KK, Nietert PJ, Jacobson RM. Extra-immunization as a clinical indicator for fragmentation of care. Public Health Rep 2011; 126 (Suppl. 02) 48-59.
  • 20 Borrow R, Joseph H, Andrews N, Acuna M, Longworth E, Martin S, Peake N, Rahim R, Richmond P, Kaczmarski E, Miller E. Reduced antibody response to revaccination with meningococcal serogroup A polysaccharide vaccine in adults. Vaccine 2000; 19 9–10 1129-1132.
  • 21 Abedi GR, Mutuc JD, Lawler J, Leroy ZC, Hudson JM, Blog DS, Schulte CR, Rausch-Phung E, Ogbuanu IU, Gallagher K, Kutty PK. Adverse events following a third dose of measles, mumps, and rubella vaccine in a mumps outbreak. Vaccine 2012; 30 (49) 7052-7058.
  • 22 Goldman GS, Miller NZ. Relative trends in hospitalizations and mortality among infants by the number of vaccine doses and age, based on the Vaccine Adverse Event Reporting System (VAERS), 1990–2010. Hum Exp Toxicol 2012; 31 (10) 1012-1021.
  • 23 Atkinson I. Accuracy of data transfer: double data entry and estimating levels of error. J Clin Nurs 2012; 21 19–20 2730-2735.
  • 24 Goldberg SI, Niemierko A, Turchin A. Analysis of data errors in clinical research databases. AMIA Annu Symp Proc 2008: 242-246.
  • 25 Wahi MM, Parks DV, Skeate RC, Goldin SB. Reducing errors from the electronic transcription of data collected on paper forms: a research data case study. J Am Med Inform Assoc 2008; 15 (03) 386-389.
  • 26 Mead CN. Data interchange standards in healthcare IT--computable semantic interoperability: now possible but still difficult, do we really need a better mousetrap?. J Healthc Inf Manag 2006; 20 (01) 71-78.
  • 27 Namli T, Aluc G, Dogac A. An interoperability test framework for HL7-based systems. IEEE Trans Inf Technol Biomed 2009; 13 (03) 389-399.
  • 28 Scott P, Worden R. Semantic mapping to simplify deployment of HL7 v3 Clinical Document Architecture. J Biomed Inform 2012; 45 (04) 697-702.
  • 29 Dombkowski KJ, Cowan AE, Harrington LB, Allred NJ, Hudson E, Clark SJ. Feasibility of initiating and sustaining registry-based immunization recall in private practices. Acad Pediatr 2012; 12 (02) 104-109.
  • 30 McCoy AB, Wright A, Kahn MG, Shapiro JS, Bernstam EV, Sittig DF. Matching identifiers in electronic health records: implications for duplicate records and patient safety. BMJ Qual Saf 2013; 22 (03) 219-224.
  • 31 Kijsanayotin B, Speedie SM, Connelly DP. Linking patients’ records across organizations while maintaining anonymity. AMIA Annu Symp Proc. 2007 11. (1008).
  • 32 King G, O’Donnell C, Boddy D, Smith F, Heaney D, Mair FS. Boundaries and e-health implementation in health and social care. BMC Med Inform Decis Mak 2012; 12 (100) 1472-6947.
  • 33 Giannangelo K, Fenton SH. SNOMED CT Survey: An Assessment of Implementation in EMR/EHR Applications. Perspectives in Health Information Management 2008; 5 (07) 1-13.
  • 34 Augustin W. Examples for Open Office Automation with Scripting Languages. 2005
  • 35 Case Study: Automating Lab Results. 2013.
  • 36 Case Study: CPOE Implementation During System Migration. 2013.
  • 37 Automation Improves the Continuum of Care: Riverside Health System. Newport News, VA2011. p. 1-2.
  • 38 HL7. IIS: HL7 Standard Code Set CVX - Vaccines Administered. HL7 Table 0292: CDC’s National Center of Immunization and Respiratory Diseases; 2013.
  • 39 Center for Disease Control and Prevention.. Understanding the Rules for Creating CVX and MVX Codes. In: Control. CfD, editor. 2010
  • 40 Washington State Department of Health. Complete List of Vaccine Names and CPT/CVX Codes. 2013.
  • 41 Lowry R. Vassar Stats: Website for Statistical Computation. Poughkeepsie, NY2013.
  • 42 Kushinka S. Chart Abstraction: EHR Deployment Techniques. California HealthCare Foundation,; 2010
  • 43 Shelby-James TM, Abernethy AP, McAlindon A, Currow DC. Handheld computers for data entry: high tech has its problems too. Trials 2007; 8: 5.
  • 44 Hills RA, Revere D, Altamore R, Abernethy NF, Lober WB. Timeliness and data element completeness of immunization data in Washington State in 2010: a comparison of data exchange methods. AMIA Annu Symp Proc 2012; 2012: 340-349.
  • 45 Smith LB, Banner L, Lozano D, Olney CM, Friedman B. Connected care: reducing errors through automated vital signs data upload. Comput Inform Nurs 2009; 27 (05) 318-323.
  • 46 Heidebrecht CL, Quach S, Pereira JA, Quan SD, Kolbe F, Finkelstein M, Buckeridge DL, Kwong JC. Incorporating scannable forms into immunization data collection processes: a mixed-methods study. PLoS One 2012; 7 (12) e49627.
  • 47 Cole D. The Real Cost of Manual Asset Management. No Limits Software 2011.
  • 48 State of CT DoPH.. DPH: Connecticut Immunization Registry and Tracking System (CIRTS). State of CT, Department of Public Health;; 2013 ; Available from: http://www.ct.gov/dph/cwp/view.asp?a=3136&q=388268.
  • 49 State of CT DoPH.. DPH: CIRTS –FAQs. State of CT, Department of Public Health; 2013; Available from: http://www.ct.gov/dph/cwp/view.asp?a=3136&q=388268.
  • 50 Christ A. Tuberculosis, Tuberculin Skin Test, and BCG Vaccine. Military Vaccine Agency; 2007
  • 51 Wiley KE, Zuo Y, Macartney KK, McIntyre PB. Sources of pertussis infection in young infants: a review of key evidence informing targeting of the cocoon strategy. Vaccine 2013; 31 (04) 618-625.
  • 52 Center for Disease Control and Prevention.. CDC Health Information for International Travel 2012 2011. Available from: http://wwwnc.cdc.gov/travel/yellowbook/2012/chapter-3-infectious-diseases-related-totravel/typhoid-and-paratyphoid-fever.htm.