Since 2001, the Universal Coverage (UC) scheme has provided health benefits to approximately three quarters of Thailand's citizens. The scheme is financed from general taxation and administered by the National Health Security Office (NHSO), under the supervision of the Public Health Minister. Hospital providers are mainly from the public sector and are paid for outpatient and preventive services based on prospective capitation whereas the Diagnosis Related Group (DRG)-based retrospective payment was used to compensate for the cost of inpatient care.

The DRG system can work well if the diagnosis and procedure codes could reflect both the patient's clinical condition and the actual cost of care incurred by hospital providers. In addition, coding practice in hospitals has to be reliable and capable of producing consistent and reliable coding quality. In an ideal setting, physicians would carefully review relevant clinical information to prepare a discharge summary, which would then be used by certified coders to produce appropriate diagnosis and procedure codes to be submitted for reimbursement. However, such an ideal condition is unlikely, at least in resource-limited settings like Thailand.

In a related qualitative study, we detailed the variation of coding practice in 10 hospitals and then defined the concept of Hospital Coding Practice as comprising elements of both structure and process [1]. In terms of structure, we identified at least eight health care professional disciplines (Medical Statisticians, Nurse, Physician, Public Health Staff/Paramedics, Medical Record Staff, Information Technology Staff, Finance/Accounting Staff, and others) as well as IT infrastructure specifically relevant to coding practice. We also described seven major steps of the coding process (Discharge Summarization, Completeness Checking, Diagnosis and Procedure Coding, Code Checking, Relative Weight Challenging, Coding Report, and Internal Summary and Coding Audit). The findings demonstrated that coding practice is not a simple two-step activity as had been assumed before by payers, but rather a multi-step process that involves many overlapping responsibilities across health care professional disciplines, especially in a resource-limited setting [1].

Although DRG has been applied in many countries and has been improved over the decades, it still is an imperfect system and a number of concerns have therefore been raised. Discrepancies between the submitted codes and the information in medical records revealed during the coding audit--especially when the submitted codes can result in larger reimbursements than would be consistent with the actual condition--have triggered a number of concerns about quality of medical records, cooperation of physicians, knowledge and skill of coders, as well as hospital intentions to "game the system" (also known as "DRG Creep") [2]. While most of these issues can be objectively verified, the last concern seems to be both the most important and the most difficult to measure.

Hospital coding practice can be affected by some factors beyond a hospital's control [1]. Simply because the hospitals were chosen to be audited based on the above inclusion criteria does not necessarily mean they intended to cheat or were incapable of producing quality coding. Understanding what might distinguish SCAD hospitals from the non-SCAD counterparts was an appropriate and feasible next step. This nationwide hospital survey has two main objectives: (1) to describe and compare the characteristics of both groups of hospitals and (2) to develop a simplified scale to measure hospital coding practice.

As a preferred method for provider payment in both developed and developing countries [12], DRG assumes that hospitals are well equipped with physicians and certified coders and therefore able to submit diagnosis and procedure codes with high quality. Literature on DRG implementation has been mostly from countries with abundant resource or mainly about its macro-level effects whereas study on how DRG codes are actually produced by hospitals is lacking.

DRG creep has been a major concern in resource-rich setting, in which hospital is suspected of being profit maximizer. As this kind of organizational intention is difficult to assess directly, it is not surprising to see mixed findings on the extent of DRG creep based on surrogate outcome measures [13–18]. While some studies investigated organizational behavior and reported potential influence of hospital management and payer on coding process [19, 20], other studies tried to demonstrate potential upcoding of some specific diagnoses such as pneumonia and heart failure [21, 22].

Poor coding quality is not only because of DRG creep, but also sicker patients, improvements in coding, and changes instituted by the payer [13]. We added that variation in hospital coding practices in an under-resourced health system is another major determinant of DRG coding quality. It was not fair for a hospital to be assumed 'capable' of producing good codes without qualified physicians and/or coders.

To our knowledge, this study is the first national survey to explore the structural and process components of coding practice, that might affect DRG coding quality. In terms of structure, we found that the use of software, number of medical statisticians, and experience of physicians seemed to be the most important. SCAD hospitals are more likely to have fewer medical statisticians, fewer certified coders, and less experienced physicians. Our previous case study revealed that, with inadequate numbers and inequitable distribution of certified coders, hospitals have tried to survive by using part-time coders from other disciplines, especially nurses [1]. This survey expanded the point further by suggesting that SCAD hospitals are more likely to face such problems than non-SCAD hospitals.

The current production of medical statisticians has been limited whereas the actual task is not necessarily about coding. In Thailand medical statistician is a job position that requires undergraduate-level training and usually is responsible for analyzing patient information [1]. Although the Thai DRG anticipated medical statisticians to be trained and certified to work as coder, a survey of 322 hospitals in 2001 revealed that only 59.87% of the hospital had medical statisticians worked as coders; but as many as 46% of them were considered 'part-time coders' as they had to be responsible for other jobs as well [23].

Based on the seven steps of the hospital coding process we reported earlier [1], the cross-function phenomenon also occurs with other health care professional disciplines as well. This study adds to the case study findings by quantifying the number of hospitals that allows such phenomenon to occur. For example, discharge summary has been assumed to be done by physicians and therefore used as a gold standard to see if the codes assigned by hospital coders are correct. However, nurses or medical statisticians are indeed the primarily responsible staff for discharge summary in some hospitals. Nurses have played important roles in almost all steps of the hospital coding process but they have not been formally recognized. While an experienced nurses can become certified coders, their contribution might not be counted toward job promotion in public hospitals.

We also are proposing development of a new tool called Hospital Coding Practice Scale, which can indirectly explore the DRG creep phenomenon. The audit by external peers has been a main mechanism to assess the quality of discharge summary as well as diagnosis and procedure codes but the results cannot be used to judge hospital intention to game the system. By using this measurement model, one can classify hospitals based on the domains they focused on and the profiles they fall into. We hypothesize that DRG creep is more likely among hospitals who focus mainly on reimbursement (profiles 3, 5, 6; Table 3). Further studies are required to ensure the validity, reliability, and feasibility of this tool.

The generalizability of the findings from this study is limited by low response rate. This was actually anticipated because some hospitals might be cautious to provide such detailed and confidential information about coding practices. The difference in both response rates and characteristics between SCAD and non-SCAD hospitals is another limitation of this study that does not allow a direct comparison of various aspects between the two groups. Also, we were unable to explore some other factors that might affect hospital coding practice. For example, various functionality of the software can affect the hospital coding practice.

SCAD and Non-SCAD hospitals were different in many aspects, especially the number of medical statisticians, experience of medical statisticians and physicians, as well as number of certified coders. The findings suggested that hospital providers should not be assumed capable of producing high quality DRG codes, especially in resource-limited settings.