Instrumen Audit Kualitas Rekam Medis Elektronik Menggunakan Content Validity Index (CVI)

Yuniana Eka Pratiwi; Hosizah Hosizah; Sri Jumiati Agustina

doi:10.25047/j-remi.v7i4.6748

Penulis

Yuniana Eka Pratiwi Universitas Esa Unggul
Hosizah Hosizah Universitas Esa Unggul
Sri Jumiati Agustina RSPON Mahar Mardjono Jakarta

DOI:

https://doi.org/10.25047/j-remi.v7i4.6748

Kata Kunci:

Audit Kualitas Data, Content Validity Index, Data Quality Management, Rekam Medis Elektronik, Stroke Iskemik

Abstrak

RSPON Mahar Mardjono Jakarta telah menerapkan Rekam Medis Elektronik (RME), namun kualitas data yang dihasilkan belum memenuhi standar kelengkapan yang ditetapkan oleh Kementerian Kesehatan. Stroke iskemik merupakan penyakit dengan angka kejadian tertinggi yang memerlukan dokumentasi medis secara akurat untuk mendukung pengambilan keputusan klinis, sehingga diperlukan instrumen audit RME untuk memantau kualitas data secara komprehensif. Penelitian ini bertujuan merancang dan menguji instrumen audit kualitas RME pada pasien stroke iskemik di RSPON Mahar Mardjono Jakarta. Metode penelitian menggunakan Research and Development (R&D) dengan pendekatan Data Quality Management (DQM) berdasarkan karakteristik kualitas data menurut AHIMA. Rancangan instrumen divalidasi menggunakan Content Validity Index (CVI) oleh enam pakar melalui penilaian Item-Level Content Validity Index (I-CVI) dan Scale-Level Content Validity Index (S-CVI) berdasarkan konstruk kualitas data yang mengacu pada clinical pathway stroke iskemik. Hasil uji validitas menunjukkan nilai I-CVI sebesar 0,83–1,00 dan S-CVI sebesar 0,99 dengan kategori sangat tinggi, sehingga instrumen dinyatakan sangat valid dan layak digunakan sebagai dasar audit kualitas data RME secara sistematis untuk meningkatkan mutu dokumentasi medis.

Referensi

[1] M. Mashoufi, H. Ayatollahi, D. Khorasani-Zavareh, and T. T. A. Boni, “Data Quality in Health Care: Main Concepts and Assessment Methodologies,” Methods Inf. Med., vol. 62, no. 01/02, pp. 5–18, May 2023, doi: 10.1055/s-0043-1761500.

[2] N. Makeleni and L. Cilliers, “Critical success factors to improve data quality of electronic medical records in public healthcare institutions,” SA J. Inf. Manag., vol. 23, no. 1, pp. 1–8, Mar. 2021, doi: 10.4102/sajim.v23i1.1230.

[3] O. Ozonze, P. J. Scott, and A. A. Hopgood, “Automating Electronic Health Record Data Quality Assessment,” J. Med. Syst., vol. 47, no. 1, pp. 1–16, Feb. 2023, doi: 10.1007/s10916-022-01892-2.

[4] L. Ehrlinger and W. Wöß, “A Survey of Data Quality Measurement and Monitoring Tools,” Front. Big Data, vol. 5, pp. 1–30, Mar. 2022, doi: 10.3389/fdata.2022.850611.

[5] H. Aerts et al., “Quality of Hospital Electronic Health Record (EHR) Data Based on the International Consortium for Health Outcomes Measurement (ICHOM) in Heart Failure: Pilot Data Quality Assessment Study,” JMIR Med. Informatics, vol. 9, no. 8, pp. 1–14, Aug. 2021, doi: 10.2196/27842.

[6] A. Azzahra, W. Astuti, R. Djamaludin, and K. Okky, “Implementasi Penggunaan Rekam Medis Eletronik Rawat Jalan Dalam Masa Peralihan Rekam Medis Konvensional Menuju Rekam Medis Elektronik Di Rumah Sakit Gotong Royong Surabaya,” Mejor. Med. J. Awatara, vol. 1, no. 1, pp. 17–24, Aug. 2023, doi: 10.61434/mejora.v1i1.49.

[7] Kementerian Kesehatan Republik Indonesia, Peraturan Menteri Kesehatan Nomor 24 Tahun 2022 tentang Rekam Medis. Jakarta: Kementerian Kesehatan Republik Indonesia, 2022.

[8] S. Davoudi et al., “Data Quality Management Model (2015 Update) - Retired,” J. AHIMA, vol. 86, no. 10, pp. 1–15, 2015.

[9] S. Henley-Smith, D. Boyle, and K. Gray, “Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework,” eGEMs (Generating Evid. Methods to Improv. patient outcomes), vol. 7, no. 1, pp. 1–18, Aug. 2019, doi: 10.5334/egems.298.

[10] Wang Zhan, Dagtas Serhan, Talburt John, Baghal Ahmad, and Zozus Meredith, “Rule-Based Data Quality Assessment and Monitoring System in Healthcare Facilities,” 2019. doi: 10.3233/978-1-61499-951-5-460.

[11] M. G. Kahn et al., “A Harmonized Data Quality Assessment Terminology and Framework for the Secondary Use of Electronic Health Record Data,” eGEMs (Generating Evid. Methods to Improv. patient outcomes), vol. 4, no. 1, pp. 1–21, Sep. 2016, doi: 10.13063/2327-9214.1244.

[12] W. D. Puspitasari and F. Febrinita, “Pengujian Validasi Isi (Content Validity) Angket Persepsi Mahasiswa terhadap Pembelajaran Daring Matakuliah Matematika Komputasi,” J. Focus Action Res. Math. (Factor M), vol. 4, no. 1, pp. 77–90, Dec. 2021, doi: 10.30762/factor_m.v4i1.3254.

[13] M. R. Lynn, “Determination and Quantification Of Content Validity,” Nurs. Res., vol. 35, no. 6, pp. 382–386, Nov. 1986, doi: 10.1097/00006199-198611000-00017.

[14] D. F. Polit and C. T. Beck, “The content validity index: Are you sure you know what’s being reported? critique and recommendations,” Res. Nurs. Health, vol. 29, no. 5, pp. 489–497, Oct. 2006, doi: 10.1002/nur.20147.

[15] A. Torsello et al., “A Hospital Medical Record Quality Scoring Tool (MeReQ): Development, Validation, and Results of a Pilot Study,” Healthcare, vol. 12, no. 3, pp. 1–13, Jan. 2024, doi: 10.3390/healthcare12030331.

[16] B. S. Marie, A. Jimmerson, Y. Perkhounkova, and K. Herr, “Developing and Establishing Content Validity of Vignettes for Health Care Education and Research,” West. J. Nurs. Res., vol. 43, no. 7, pp. 677–685, Jul. 2021, doi: 10.1177/0193945920969693.

[17] P. Karthik and V. R. Devi, “Content Validity of Assessment Instrument for High-Performance Work Systems in Health Care Industry,” J. Nurs. Meas., vol. 32, no. 1, pp. 28–37, Mar. 2024, doi: 10.1891/JNM-2022-0034.