Validity of claims database compared with electronic medical record of private health clinics in Malaysia: A Pilot Study.

Nor Hidayah Mohd Taufek; Norny Syafinaz  Ab Rahman; Nor Ilyani  Mohamed Nazar; Siti Halimah  Bux; Che Suraya  Zin

doi:10.31436/jop.v2i1.107

Authors

Nor Hidayah Mohd Taufek Big Data Research Group, Department of Pharmacy Practice, Kulliyyah of Pharmacy, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia
Norny Syafinaz Ab Rahman Big Data Research Group, Department of Pharmacy Practice, Kulliyyah of Pharmacy, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia
Nor Ilyani Mohamed Nazar Big Data Research Group, Department of Pharmacy Practice, Kulliyyah of Pharmacy, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia
Siti Halimah Bux Big Data Research Group, Department of Pharmacy Practice, Kulliyyah of Pharmacy, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia
Che Suraya Zin Big Data Research Group, Department of Pharmacy Practice, Kulliyyah of Pharmacy, International Islamic University Malaysia, 25200 Kuantan, Pahang, Malaysia

DOI:

https://doi.org/10.31436/jop.v2i1.107

Keywords:

Validity, claim database, electronic medical record, private health clinics, accuracy

Abstract

Introduction: The validity of health insurance claims data in private health sectors has been widely reported in many developed countries to monitor details of private healthcare utilisation. Little is known regarding the data validity of private health care services and insurance claims in Malaysia. This pilot study aimed to validate the claims data from a private health insurance database, using electronic medical records (EMR) at the private clinics as the gold standard.

Materials and methods: Patients’ data were retrieved from the PMCare health insurance database from 2016-2019 recorded for International Islamic University Malaysia employees. Patients were sampled from the PMCare database and manually compared with data from EMR of selected private panel clinics. Data were analysed for descriptive statistics using Microsoft Excel 2013.

Results: A total of four panel clinics consented to the study, and data were available for 2016, 2017 and 2019. The number of observations obtained from 118 patients (male = 63, female = 55) was 386, with the most common diagnosis reported in the PMCare database was acute upper respiratory tract infection (63.6%). Total accuracy between PMCare and EMR data was 91.5%, with an 8.5% difference or inaccuracy. Percentage accuracy was varied between different clinics (A= 92.6%, B=84.7%, C=98.6%, D=82.6%).

Conclusion: Data submitted to PMCare claims by private health clinics had high accuracy (>90%) and is acceptable for research and other applications. Future studies should investigate the differences in clinic-based practice for documenting the identified types of discrepancies to improve the accuracy of private health insurance databases.

References

Chua, H.T., & Cheah J.C. H. (2012). Financing universal coverage in Malaysia: a case study. BMC Public Health, 12(Suppl 1), S7. https://doi.org/10.1186/1471-2458-12-S1-S7

Cook, S.F., Visscher, W.A., Hobbs, C.L., & Williams R.L. (2002). The Project IMPACT Clinical Implementation Committee Project IMPACT: Results from a Pilot Validity Study of a New Observational Database, Critical Care Medicine, 30 (12), 2765-2770. doi: 10.1097/00003246-200212000-00024

Du, X.L., Key, C.R., Dickie, L., Darling, R., Geraci, J.M., & Zhang, D. (2006). External validation of Medicare claims for breast cancer chemotherapy compared with medical chart reviews. Med Care., 44(2), 124–131. doi: 10.1097/01.mlr.0000196978.34283.a6

Gabriel, S.E., Amadio, P., & Ilstrup, D. (2005). The Feasibility and Validity Studies Comparing Orthopedists and Non-Orthopedists caring for musculoskeletal Injuries: Results of a Pilot study. Health Sciences Research, 10(3), 163-168. https://doi.org/10.1002/art.1790100303

Iwamoto, M., Higashi, T., Miura, H., Kawaguchi, T., Tanaka, S., Yamashita, I., Yoshimoto, T., Yoshida S., & Matoba, M. (2015). Accuracy of using diagnosis procedure combination administrative claims data for estimating the amount of opioid consumption among cancer patients in Japan. Japanese Journal of Clinical Oncology, 45(11), 1036–1041. https://doi.org/10.1093/jjco/hyv130

Koram, N., Delgado, M., Stark, J.H., Setoguchi, S., & de Luise, C. (2019). Validation studies of claims data in the Asia-Pacific region: A comprehensive review. Pharmacoepidemiology and Drug Safety, 28(2), 156–170. https://doi.org/10.1002/pds.4616

Miller, D.C., Saigal, C.S., Warren, J.L., Leventhal, M., Deapen, D., Banerjee, M., Lai, J., Hanley, J., & Litwin, M.S. (2009). External validation of a claims-based algorithm for classifying kidney-cancer surgeries. BMC Health Services Research, 9 (92). https://doi.org/10.1186/1472-6963-9-92

Thomas, S., Beh, L., & Nordin, R.B. (2011). Health care delivery in Malaysia: changes, challenges and champions. Journal of Public Health in Africa, 2(2), e23. https://doi.org/10.4081/jphia.2011.e23

Tomlin, A.M., Reith, D.M., Woods, D.J., Lloyd, H.S., Smith, A., Fountain, J.S. & Tilyard, M.W. (2017). Pharmacoepidemiology database system for monitoring risk due to the use of medicines by New Zealand primary care patients. Drug Safety, 40(12), 1259?1277. https://doi.org/10.1007/s40264-017-0579-1

Takeda, T., Mihara N., Murata T., Shimai Y., Okada K., Manabe, S., & Matsumura, Y. (2016). Estimating the ratio of patients with a certain disease between hospitals for the allocation of patients to clinical trials using health insurance claims data in Japan. Studies in Health Technology and Informatics, 228, 537?541. Doi: 10.3233/978-1-61499-678-1-537

Widdifield, J., Labrecque, J., Lix, L., Paterson, J.M., Bernatsky, S., Tu, K., Ivers, N., Bombardier, C. (2013). Systematic review and critical appraisal of validation studies to identify rheumatic diseases in health administrative databases. Arthritis Care & Research, 65(9), 1490-1503. https://doi.org/10.1002/acr.21993

Yamana, H., Moriwaki, M., Horiguchi, H., Kodan, M., Fushimi, K., & Yasunaga, H. (2017). Validity of diagnoses, procedures, and laboratory data in Japanese administrative data. Journal of Epidemiology, 10, 476–482. https://doi.org/10.1016/j.je.2016.09.009