Purpose: Patients availing insurance with commercial insurance providers constitute just 3.6 percent. These insured patients become prime targets of private hospitals. Thus, satisfaction of these patients is of prime importance. Yet, many hospitals struggle to manage the one key process, which could spoil the overall favourable experience that patients have during their stay in the hospital, i.e., the discharge process. In this study, time tracking for the discharge process of insured patients is done, using the shadowing technique, with the objective of finding out the major causes of delay, and to recommend solutions for reducing them.

Methodology: This study is cross sectional and is carried out for the period of three months, i.e., from March 2018 to May 2018. A sample size of 174 patients is taken, using the systematic random sampling technique; unadjusted linear regression is used so as to find out major sub processes affecting the overall discharge process time. For finding out vital categories of queries sent by the external TPA department, Pareto analysis is used.

Findings: The two main sub processes explaining the maximum variance in the overall discharge process are the time taken for discharge summary to reach the in-house TPA department, and its approval by the external TPA after submission of the discharge summary, with adjusted R2  .554 and .219 respectively. Additionally, from the Pareto analysis, it was found that out of total 128 categories of queries, 5 categories accounted for 64 percent of total queries.

Practical Implications: Hospitals need to focus on the time taken for the discharge summary to reach the in-house TPA department. In fact, they can opt for technological solutions, such as the “electronic discharge system”, which can facilitate the stages of typing, review, revision and submission to the in house TPA department. Similarly, hospitals should collect the data of the queries raised by the external TPA and analyse them with Pareto technique so as to find out the major categories accounting for the maximum number of queries. In this way, they can develop a tool such as a checklist, which, when implemented in its intended form and spirit, will result in significant saving of time and efforts.

Keywords: TPA, Health Insurance, TAT, Query, IRDA