SUPPLEMENTARY INFORMATION:

When submitting comments or requesting information, please include the information request collection title for reference.

Information Collection Request Title: HRSA Uniform Data System (UDS) OMB No. 0915-0193—Revision.

Abstract: The Health Center Program, administered by HRSA, is authorized under section 330 of the Public Health Service (PHS) Act (42 U.S.C. 254b). Health centers are community-based and patient-directed organizations that deliver affordable, accessible, quality, and cost-effective primary health care services to patients regardless of their ability to pay. Nearly 1,400 health centers operate approximately 12,000 service delivery sites that provide primary health care to more than 30 million people in every U.S. state, the District of Columbia, Puerto Rico, the U.S. Virgin Islands, and the Pacific Basin. HRSA uses the UDS ^[1] for annual reporting by Health Center Program awardees (those funded under section 330 of the PHS Act), Health Center Program look-alikes, and Nurse Education, Practice, Quality and Retention ^[2] (NEPQR) Program awardees (specifically those funded under the practice priority areas of section 831(b) of the PHS Act). Look-alikes do not routinely receive Federal funding under section 330 of the PHS Act, but meet the Health Center Program requirements for designation under the program (42 U.S.C. 1395x(aa)(4)(A)(ii) and 42 U.S.C. 1396d(l)(2)(B)(ii)).

Need and Proposed Use of the Information: UDS data collection updates must be completed in a timely manner in order for health centers to fulfill Health Center Program requirements. Approval of these ( printed page 875) changes is needed by February 1, 2023, to implement the changes in the data collection system and to provide adequate information on UDS reporting guidance to health centers, partners, and key stakeholders. HRSA plans to make the following updates for the performance year 2023 UDS data collection:

• Table 3B (Demographic Characteristics), will be updated to include additional subpopulations selection options to better reflect the diversity of patients served by health centers. Race/ethnicity categories will be updated to align with U.S. Department of Health and Human Services (HHS) data standards.^[3] In accordance with section 4302 within the Office of the Assistant Secretary for Planning and Evaluation (ASPE)  ⁴ Implementation Guidance on Data Standards for Race, Ethnicity, Sex, Primary Language, and Disability Status, the UDS will be updated to include subpopulations categories for: Asian, Native Hawaiian, Other Pacific Islanders as well as a broader selection for Hispanic ethnicity.

The 2011 HHS race and ethnicity categories maintains alignment with the 1997 OMB ^[5] minimum categories for race and ethnicity allow for a better understanding of the cultural diversity of patients served by health centers.

• Table 5 (Staffing and Utilization), will be updated to include four distinct lines for reporting Pharmacy Personnel categorized by Pharmacists, Clinical Pharmacist, Pharmacy Technicians, and Other Pharmacy Personnel. Health center personnel are critical to the functioning of health centers, collecting inclusive information about the health center workforce, will allow HRSA's Bureau of Primary Health Care to better understand workforce composition as well as improve the ability to articulate the role that pharmacy personnel play in an integrated primary care.
• Table 6A (Selected Diagnoses and Services Rendered), will be updated to include a diagnostic measure representing long COVID. This measure is labeled Post COVID-19 condition, unspecified, within the Selected Infectious and Parasitic Diseases grouping of measures. With this measure, health centers are able to report both number of patients with this diagnosis as well as the number of patient visits related to the diagnosis.^[6] The Centers for Disease Control and Prevention classifies long COVID, also known as post-COVID, conditions as a wide range of new, returning, or ongoing health problems people can experience four or more weeks after first being infected with the virus that causes COVID-19.^[7] Data on this measure will lead to better understanding the impact of COVID-19 post-acute infection on health center patients.

• Table 6A (Selected Diagnoses and Services Rendered), will be updated to include a measure that tracks the number of patients who receive pediatric developmental screening and evaluation services. The 2023 UDS will include developmental screening, behavioral screening/testing, and administrative assessment International Classification of Diseases diagnostic and Current Procedural Terminology billing codes for use to track the changes in the number of children who receive developmental screening and evaluation services. Early childhood is a critical period for physical, cognitive, and social development, laying the foundation for life-long health and well-being.^[8] Children who experience poverty, particularly during early life are at risk of adverse health and developmental outcomes.

• Table 6B ( Quality of Care Measures), and Table 7 ( Health Outcomes and Disparities ), collected UDS clinical quality measures ^[9] (CQMs) where applicable. Collected UDS CQMs will be updated in alignment with specifications of the issued performance year 2023 electronic-specified clinical quality measures, released by the Centers for Medicare and Medicaid Services for use by eligible providers. Clinical performance measure alignment across national programs promotes data standardization, quality, and transparency, and decreases reporting burden for providers and organizations participating in multiple Federal programs.

• Appendix D: (Health Center Health Information Technology {HIT} Capabilities Form), will be updated with a question asking health centers to provide the total number of patients that were screened for social risk factors, using a standardized screener, during the calendar year. This question provides a more accurate view of the impact of social risk on the health center patient population and continues to reinforce Social Determinates of Health as a priority area intrinsically linked with health equity.
• Beginning with the2023 UDS, health centers will be able to submit patient-level data in fulfillment of data elements on Tables:

○ Table PBZC (Patients by Zip Code)

○ Table 3A (Patients by Age and Sex Assigned at Birth)

○ Table 3B (Demographic Characteristics)

○ Table 4 (Selected Characteristics)

○ Table 6A (Selected Diagnoses and Services Rendered)

○ Table 6B (Quality of Care Measures)

○ Table 7 (Health Outcomes and Disparities

UDS+ Patent Level Reporting leverages a methodological shift in the process by which health centers submit their annual UDS report, while maintaining historic UDS measures. High-quality accessible data are critical to strategically meeting the needs of patients and identifying opportunities for clinical process improvement. The growth in health information technology coupled with the increased adoption of electronic health records has transformed patient care delivery and underscored the need for secure and rapid exchange of health data between disparate systems. Health Level Seven International ^[10] developed Fast Healthcare Interoperability Resources ^[11] (FHIR) to standardize the electronic exchange of patient data across systems. FHIR, which is the current gold standard, has the flexibility to support a variety of user needs and enhances interoperability by transmitting health data rapidly and more securely than ever before. It is important for the collection of UDS data to align with interoperability standards and reporting requirements across HHS and the healthcare industry. Leveraging FHIR to collect UDS patient-level data will improve data granularity, allow for the development of robust patient management programs, and improve equitable access to high-quality, cost-effective primary care services.

This electronic reporting mechanism will reduce reliance on manual data entry to populate the annual UDS report, in turn yielding a reduction in reporting effort burden, and will greatly ( printed page 876) increase the analytical value of UDS data for informing policy and Program decision-making.

Likely Respondents: Likely respondents will include Health Center Program award recipients, Health Center Program look-alikes, and Nurse Education, Practice, Quality and Retention Program awardees funded under the practice priority areas of section 831(b) of the PHS Act.

Burden Statement: Burden includes the time expended by persons to generate, maintain, retain, disclose, or provide the information requested. This includes the time needed to review instructions; to develop, acquire, install, and use technology and systems for the purpose of collecting, validating, and verifying information, processing, and maintaining information, disclosing, and providing information. FHIR standards align with the Centers for Medicare and Medicaid Services electronic clinical quality measures, allow for standardization of data, and reduce the potential for misinterpretation of measures or calculation errors. FHIR also accounts for time to train personnel, respond to a collection of information, search data sources, complete and review the collection of information, and transmit or otherwise disclose the information. FHIR will also include testing information necessary to support the UDS Test Cooperative. No more than three tests will be conducted each calendar year and no more than one hundred health centers will participate in one test. Participation is voluntary and will not affect their funding status. The total annual burden hours estimated for this Information Collection Request are summarized in the forthcoming table.

HRSA specifically requests comments on: (1) the necessity and feasibility of the proposed information collection for the proper performance of the agency's functions; (2) the accuracy of the estimated burden; (3) ways to enhance the quality, utility, and clarity of the information to be collected; and (4) the use of automated collection techniques or other forms of information technology to minimize the information collection burden.

88 FR 874