Audit of the Office of Medicaid (MassHealth)—Review of Claims Submitted by Dental Arts Lawrence: Dr. Snehal Pingle, Dr. Yuan Fu Shek, and Dr. Ke Wang Objectives, Scope, and Methodology

An overview of the purpose and process of auditing the Office of Medicaid (MassHealth)—Review of Claims Submitted by Dental Arts Lawrence: Dr. Snehal Pingle, Dr. Yuan Fu Shek, and Dr. Ke Wang.

Overview

In accordance with Section 12 of Chapter 11 of the Massachusetts General Laws, the Office of the State Auditor (OSA) has conducted a performance audit of certain activities of MassHealth for the period July 1, 2019 through June 30, 2023.

We conducted this performance audit in accordance with generally accepted government auditing standards. Those standards require that we plan and perform the audit to obtain sufficient, appropriate evidence to provide a reasonable basis for our findings and conclusions based on our audit objectives. We believe that the evidence obtained provides a reasonable basis for our findings and conclusions based on our audit objectives.

Below is our audit objective, indicating the question we intended our audit to answer; the conclusion we reached regarding our objective; and, if applicable, where our objective is discussed in the audit findings.

Objective	Conclusion
1.      Did Dr. Snehal Pingle, Dr. Yuan Fu Shek, and Dr. Ke Wang of Dental Arts Lawrence bill MassHealth for dental services in accordance with Section 420.414B of Title 130 of the Code of Massachusetts Regulations (CMR) and 130 CMR 420.425(B)(3)?	No; see Findings 1 and 2, as well as Other Matters

To accomplish our audit objective, we gained an understanding of the aspects of the internal control environment relevant to our objective by conducting inquiries with the practice manager at Dental Arts Lawrence. In addition, to obtain sufficient, appropriate evidence to address our audit objective, we performed the procedures described below.

Sample Strategy

We obtained data from the Medicaid Management Information System (MMIS)² regarding all dental claims paid by MassHealth to Dr. Snehal Pingle, Dr. Yuan Fu Shek, and Dr. Ke Wang for services provided during the audit period. This data showed that, during the audit period, there was a population of 164,633 claims totaling $13,998,338. We took this data and narrowed the population of claims to those that occurred on days that the service providers claimed to work over 12 hours, which came to 152,175 claims (totaling $13,281,599; we noted that 92% of all claims occurred on days when providers claimed to work longer than 12 hours in a single day). We considered 12 work hours the feasible maximum number of work hours able to be performed in a single 24-hour period based on service durations associated with certain dental procedural codes. After this, we then selected a random, statistical³ sample of 131 claims (totaling $10,626) from the 152,175 claims. To select the sample, we used a 90% confidence level,⁴ a 50% expected error rate,⁵ and a 15% desired precision range.⁶ 

Review of Dental Records

To determine whether the claims submitted to MassHealth were documented in accordance with 130 CMR 420.414(B), we took the following actions. We reviewed each dental record to determine whether they included the requirements outlined by 130 CMR 420.414(B). (See the “Authoritative Guidance” section under Finding 1 regarding specific information on these requirements.) In addition, during our review of dental records, we inspected the documentation to ensure that the frequency of restorations per member were within parameters of 130 CMR 420.425(B)(3) (i.e., restorations for the same tooth and same surface) and were performed within one year.

For our statistical sample, we did not project the error to the population.

Details related to the results of our testing can be found in Findings 1 and 2, as well as in Other Matters.

Data Reliability Assessment

To determine the reliability of the data from MMIS, we relied on the work performed by OSA in a separate project completed in 2023 that tested certain information system controls in MMIS. As part of this work, OSA reviewed existing information, tested selected system controls, and interviewed agency officials knowledgeable about the data. Additionally, we performed validity and integrity tests on all claim data relevant to the audit period, including (1) testing for blank fields, (2) scanning for duplicate records, and (3) looking for dates outside the audit period. We also selected a judgmental sample⁷ of 20 hardcopy supporting documents (e.g., dental records) and traced these to MMIS data (e.g., tooth numbers, tooth number codes and descriptions, dates of service, and procedural codes) for agreement. Additionally, we selected a judgmental sample of 20 claims from MMIS and traced these to hardcopy supporting documents (e.g., dental records) for agreement.

Based on the results of the data reliability assessment procedures described above, we determined that the information we obtained during the course of our audit was sufficiently reliable for the purposes of our audit. 

2.    MMIS is the claim processing and data warehouse system that MassHealth uses. MMIS contains various types of information, such as healthcare information about services provided to MassHealth members and billing submission data. It is used for processing data, verifying eligibility, and running reports that identify medical treatments.

3.   Auditors use statistical sampling to select items for audit testing when a population is large and contains similar items. Auditors generally use a statistical software program to choose a random sample when sampling is used. The results of testing using statistical sampling, unlike those from judgmental sampling, can usually be used to make conclusions or projections about entire populations.

4.    Confidence level is a mathematically based measure of the auditor’s assurance that the sample results (statistic) are representative of the population (parameter), expressed as a percentage.

5.    Expected error rate is the number of errors that are expected in the population, expressed as a percentage. It is based on the auditor’s knowledge of factors such as prior year results, the understanding of controls gained in planning, or a probe sample.

6.    Desired precision range is the range of likely values within which the true population value should lie; also called confidence interval. For example, if the interval is 90%, the auditor will set an upper confidence limit and a lower confidence where 90% of transactions fall within those limits.

7.    Auditors use judgmental sampling to select items for audit testing when a population is very small, the population items are not similar enough, or there are specific items in the population that the auditors want to review. Auditors use their knowledge and judgment to select the most appropriate sample. For example, an auditor might select items from areas of high risk. The results of testing using judgmental sampling cannot be used to make conclusions or projections about entire populations; however, they can be used to identify specific issues, risks, or weaknesses.

Date published:	April 2, 2025