CMS-10250 Supporting Statement Part B 06_01_2015 CLEAN

Supporting Statement - Part B
Submission of Information for the Hospital Outpatient Quality Reporting (OQR)
Program
Collection of Information Employing Statistical Methods
1.

Describe potential respondent universe.

All subsection (d) hospitals receiving reimbursement under the Outpatient Prospective
Payment System (OPPS) in the United States constitute the potential respondent
universe; approximately 3,300 hospitals.
2.

Describe procedures for collecting information.

Data are submitted via a secure Web site (QualityNet). Data may be: patient-level
submitted directly to CMS, summary or aggregate data submitted directly to CMS or the
Centers for Disease Control and Prevention (CDC) National Health Safety Network
(NHSN) via Web-based tools. Electronic data conforming to a specified format will be
collected in a secure Oracle-based relational database.
3.

Describe methods to maximize response rates.

To maximize response rates, the Hospital OQR Program provides payment incentives for
meeting participation. Hospitals that do not meet program requirements may have a 2.0
percentage point reduction in their OPPS annual payment update. In addition, CMS
provides abstraction and submission tools, education, and technical assistance to any
hospitals requiring assistance with program requirements.
4.

Describe any tests of procedures or methods.

CMS has validation requirements for patient-level data submitted directly to CMS. A
comparison of the data the hospital submitted to what is independently abstracted from
the supporting medical record documentation is made. A measure match rate is calculated
from the abstracted data so that a verification of the measure information is made.
A confidence interval using a binomial approach is used in calculation validation scores
to account for sample variability, the data being analyzed are binary (match, do not
match) and to account for the possibility of small sample sizes.
5.

Provide name and telephone number of individuals consulted on statistical
aspects.

Elizabeth Bainger, MS
410-786-0529

James Poyer, MS, MBA
410-786-2261