The Impact of the Clinical Miscoding on Inpatient Reimbursement

Document Type: Original Article

Authors

1 Assistant Professor, Department of Health Information Sciences, Faculty of Management and Medical Information Sciences, Kerman University of Medical Sciences, Kerman, Iran

2 Assistant Professor, Department of Health Information Technology, Faculty of Paramedical Sciences, Kermanshah University of Medical Sciences, Kermanshah, Iran

3 Assistant Professor, Department of Health Information Technology, Paramedical School, Kermanshah University of Medical Sciences, Kermanshah, Iran

Abstract

Background: The purpose of this study was to investigate the rate of coding errors and its effect on the amount of correct reimbursement to patients.
Methods: This descriptive and cross-sectional study was performed in 2018. Research resources were records in compensation units in medical documents center of social security organization. A total of 546 records were reviewed of which, 118 records met the research criteria and were selected through census method. Instrument for data collection was a checklist composed of six parts. Data were collected by compensation unit coders.
Results: In total, 118 records met the inclusion criteria. The highest rate of documentation error was related to unconfirmed errors with 106 items and a coefficient of 3845.44. The cost issued to patients based on tariff codes with a coefficient of 9696.4 was estimated as 3684632000 Rials, which only 2416154000 Rials was reimbursed to the patients with the coefficient of 6358.3.
Conclusion: Since coding of diagnostic measures had a high percentage of errors, and the recording of services was not accepted, some proper policies must be adopted to reduce procedure miscoding.

 
 

Keywords


1.       Murray CJ, Frenk J. A framework for assessing the performance of health systems. Bulletin of the world Health Organization. 2000;78(6):717-31.

2.       Nazari R, Amini J, Babaalipour Mouziraji F, Akbari S. A comparative study on patient satisfaction with hospital services in Amol. The Journal of Urmia Nursing and Midwifery Faculty. 2011;9(3):188-95.

3.       Mathauer I, Wittenbecher F. Hospital payment systems based on diagnosis-related groups: experiences in low-and middle-income countries. Bulletin of the World Health Organization. 2013;91:746-56A.

4.       Khorrmmy F, Hosseini Eshpala R, Baniasadi T, Azarmehr N, Mohammady F. Prioritizing insurance deductions factors of Shahid Mohammadi hospital inpatients records using Shannon Entropy, Bandar Abbas, Iran. Bimonthly Journal of Hormozgan University of Medical Sciences. 2013;17(1):77-82.

5.       Rahsidian A, Doshmangir L. Substitution of ‘California’book, the First Clinical and Diagnosis Tariff Reference book in Iran: Expert’s View Points. Medicine and cultivation Research Journal. 2013;22(3):59-78.

6.       AlipourJ, Karimi A, Erfannia L, Shahrakipour M, Hayavi HMH, Kadkhoda A, et al. Reliability of medical diagnosis with international classification of diseases 10th version in 2011. 2013.

7.       Abdelhak M, Grostick S, Hanken M, Gacobs E. Health Information Management of a Strategic Resource. 4, editor. Philadelphia: Elsevier; 2012.

8.       Mohammadi A, AziziAA, Cheraghbaigi R, Mohammadi R, Zaret J, Valinejadi A. Analyzing the deductions applied by the medical services and social security organization insurance toward receivable bills by University Hospitals of Khorramabad. 2013.

9.       Tabibi S MM. Strategic Planing. 4 ed: Termeh; 2012.

10.     Cheng P, Gilchrist A, Robinson KM, Paul L. The risk and consequences of clinical miscoding due to inadequate medical documentation: a case study of the impact on health services funding. Health Information Management Journal. 2009;38(1):35-46.

11.     Karami M, Moini M, Safdari R. Impact of hospital deductions imposed by the social security insurance on patient’s teaching hospitals of Kashan. The Journal of Urmia Nursing and Midwifery Faculty. 2011;8(4):220-8.

12.     Heywood NA, Gill MD, Charlwood N, Brindle R KC, Allen N. Improving accuracy of clinical coding in surgery: collaboration is key. Journal of Surgical Research. 2016;204(2):490-5.

13.     Cheema ZA KS. Implications of miscoding urological procedures in an era of financial austerity–‘Every Penny Counts’. JRSM 2015;6(6).

14.     Fakhry SM, Robinson L, Hendershot K, Reines HD. Surgical residents’ knowledge of documentation and coding for professional services: an opportunity for a focused educational offering. The American journal of surgery. 2007;194(2):263-7.

15.     Rezaei S, Arab M. Effects of the New Health Reform Plan on the Performance Indicators of Hamedan University Hospitals. Journal of School of Public Health and Institute of Public Health Research. 2016;14(2):51-60.