Measuring up Implementing a dental quality measure in the electronic health record context

被引:21
|
作者
Bhardwaj, Aarti [1 ,2 ]
Ramoni, Rachel [3 ]
Kalenderian, Elsbeth [3 ]
Neumann, Ana [4 ]
Hebballi, Nutan B. [1 ]
White, Joel M. [5 ]
McClellan, Lyle [6 ]
Walji, Muhammad F. [1 ,7 ]
机构
[1] Univ Texas Hlth Sci Ctr Houston, Dept Diagnost & Biomed Sci, Sch Dent, 7500 Cambridge St,Suite 4184, Houston, TX 77054 USA
[2] Univ Calif Los Angeles, Los Angeles, CA USA
[3] Harvard Univ, Sch Dent Med, Dept Oral Hlth Policy & Epidemiol, 188 Longwood Ave, Boston, MA 02115 USA
[4] Univ Texas Hlth Sci Ctr Houston, Sch Dent, Dept Gen Practice & Dent Publ Hlth, Houston, TX 77054 USA
[5] Univ Calif San Francisco, Sch Dent, Dept Prevent & Restorat Dent Sci, San Francisco, CA USA
[6] Willamette Dent Grp, Doctor Dev, Portland, OR USA
[7] Univ Texas Hlth Sci Ctr Houston, Technol Serv & Informat, 7500 Cambridge St,Suite 4184, Houston, TX 77054 USA
来源
基金
美国国家卫生研究院;
关键词
Dental care for children; dental public health; informatics; DIAGNOSTIC TERMINOLOGY; CARE;
D O I
10.1016/j.adaj.2015.06.023
中图分类号
R78 [口腔科学];
学科分类号
1003 ;
摘要
Background. Quality improvement requires using quality measures that can be implemented in a valid manner. Using guidelines set forth by the Meaningful Use portion of the Health Information Technology for Economic and Clinical Health Act, the authors assessed the feasibility and performance of an automated electronic Meaningful Use dental clinical quality measure to determine the percentage of children who received fluoride varnish. Methods. The authors defined how to implement the automated measure queries in a dental electronic health record. Within records identified through automated query, the authors manually reviewed a subsample to assess the performance of the query. Results. The automated query results revealed that 71.0% of patients had fluoride varnish compared with the manual chart review results that indicated 77.6% of patients had fluoride varnish. The automated quality measure performance results indicated 90.5% sensitivity, 90.8% specificity, 96.9% positive predictive value, and 75.2% negative predictive value. Conclusions. The authors' findings support the feasibility of using automated dental quality measure queries in the context of sufficient structured data. Information noted only in free text rather than in structured data would require using natural language processing approaches to effectively query electronic health records. Practical Implications. To participate in self-directed quality improvement, dental clinicians must embrace the accountability era. Commitment to quality will require enhanced documentation to support near-term automated calculation of quality measures.
引用
收藏
页码:35 / 40
页数:6
相关论文
共 50 条
  • [31] Developing and Implementing an Interoperable Document-based Electronic Health Record
    Campos, Fernando
    Plazzotta, Fernando
    Luna, Daniel
    Baum, Analia
    Bernaldo de Quiros, Fernan Gonzalez
    MEDINFO 2013: PROCEEDINGS OF THE 14TH WORLD CONGRESS ON MEDICAL AND HEALTH INFORMATICS, PTS 1 AND 2, 2013, 192 : 1169 - 1169
  • [32] Implementing Machine Learning in the Electronic Health Record: Checklist of Essential Considerations
    Kawamoto, Kensaku
    Finkelstein, Joseph
    Fiol, Guilherme Del
    MAYO CLINIC PROCEEDINGS, 2023, 98 (03) : 366 - 369
  • [33] How up-to-date is the Electronic Health Record?
    Albers, Maarit
    Bucsan, C. C.
    Van Der Palen, J.
    EUROPEAN RESPIRATORY JOURNAL, 2023, 62
  • [34] Improved quality and comprehensiveness in nursing documentation of pressure ulcers after implementing an electronic health record in hospital care
    Gunningberg, Lena
    Fogelberg-Dahm, Marie
    Ehrenberg, Anna
    JOURNAL OF CLINICAL NURSING, 2009, 18 (11) : 1557 - 1564
  • [35] Measuring the Impact of Electronic Health Record Adoption on Charge Capture
    Edwardson, Nicholas
    Kash, Bita A.
    Janakiraman, Ramkumar
    MEDICAL CARE RESEARCH AND REVIEW, 2017, 74 (05) : 582 - 594
  • [36] Measuring Acute Care Nurses' Electronic Health Record Use Patterns, Electronic Health Record Satisfaction, and Relationship to Nurse Burnout
    Summers, Donna
    Stocker-Schneider, Julia
    CIN-COMPUTERS INFORMATICS NURSING, 2019, 37 (11) : 559 - 559
  • [37] Measuring Diabetes Care Performance Using Electronic Health Record Data: The Impact of Diabetes Definitions on Performance Measure Outcomes
    Hirsch, Annemarie Gregory
    McAlearney, Ann Scheck
    AMERICAN JOURNAL OF MEDICAL QUALITY, 2014, 29 (04) : 292 - 299
  • [38] Perceived critical success factors of electronic health record system implementation in a dental clinic context: An organisational management perspective
    Sidek, Yusof Haji
    Martins, Jorge Tiago
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2017, 107 : 88 - 100
  • [39] Use of Electronic Health Record Data for Quality Reporting
    Abernethy, Amy P.
    Gippetti, James
    Parulkar, Rohit
    Revol, Cindy
    JOURNAL OF ONCOLOGY PRACTICE, 2017, 13 (08) : 530 - +
  • [40] Automating Electronic Health Record Data Quality Assessment
    Obinwa Ozonze
    Philip J. Scott
    Adrian A. Hopgood
    Journal of Medical Systems, 47