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Schneberk T, Bolshakova M, Sloan K, Chang E, Stal J, Dinalo J, Jimenez E, Motala A, Hempel S. Quality Indicators for High-Need Patients: a Systematic Review. J Gen Intern Med 2022; 37:3147-3161. [PMID: 35260956 PMCID: PMC9485370 DOI: 10.1007/s11606-022-07454-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 02/03/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Healthcare systems are increasingly implementing programs for high-need patients, who often have multiple chronic conditions and complex social situations. Little, however, is known about quality indicators that might guide healthcare organizations and providers in improving care for high-need patients. We sought to conduct a systematic review to identify potential quality indicators for high-need patients. METHODS This systematic review (CRD42020215917) searched PubMed, CINAHL, and EMBASE; guideline clearing houses ECRI and GIN; and Google scholar. We included publications suggesting, evaluating, and utilizing indicators to assess quality of care for high-need patients. Critical appraisal of the indicators addressed the development process, endorsement and adoption, and characteristics, such as feasibility. We standardized indicators by patient population subgroups to facilitate comparisons across different indicator groups. RESULTS The search identified 6964 citations. Of these, 1382 publications were obtained as full text, and 53 studies met inclusion criteria. We identified over 1700 quality indicators across studies. Quality indicator characteristics varied widely. The scope of the selected indicators ranged from detailed criterion (e.g., "annual eye exam") to very broad categories (e.g., "care coordination"). Some publications suggested disease condition-specific indicators (e.g., diabetes), some used condition-independent criteria (e.g., "documentation of the medication list in the medical record available to all care agencies"), and some publications used a mixture of indicator types. DISCUSSION We identified and evaluated existing quality indicators for a complex, heterogeneous patient group. Although some quality indicators were not disease-specific, we found very few that accounted for social determinants of health and behavioral factors. More research is needed to develop quality indicators that address patient risk factors.
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Affiliation(s)
- Todd Schneberk
- Gehr Center for Health Systems Science and Innovation, Keck School of Medicine, University of Southern California, GNH 1011, 1200 N State Street Rm 1011, Los Angeles, CA, 90033, USA.
| | - Maria Bolshakova
- Southern California Evidence Review Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Kylie Sloan
- Southern California Evidence Review Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Evelyn Chang
- VA Greater Los Angeles Healthcare System, Sepulveda, CA, USA
| | - Julia Stal
- Southern California Evidence Review Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jennifer Dinalo
- Southern California Evidence Review Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Elvira Jimenez
- VA Greater Los Angeles Healthcare System, Sepulveda, CA, USA
| | - Aneesa Motala
- Gehr Center for Health Systems Science and Innovation, Keck School of Medicine, University of Southern California, GNH 1011, 1200 N State Street Rm 1011, Los Angeles, CA, 90033, USA
- Southern California Evidence Review Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Susanne Hempel
- Gehr Center for Health Systems Science and Innovation, Keck School of Medicine, University of Southern California, GNH 1011, 1200 N State Street Rm 1011, Los Angeles, CA, 90033, USA
- Southern California Evidence Review Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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Abstract
Numerous studies have identified a relationship between staffing levels and nurse-sensitive outcomes for medical and surgical patients, but little has been published on the impact of nurse-sensitive outcomes for the childbearing family and even less that examines the relationship of intrapartum staffing on adverse perinatal outcomes. Using a derivation of Donabedian's classic structure, process, and outcomes framework, a model is proposed, which would allow obstetrical primary care providers and administrators alike the opportunity to examine the influence of nurse staffing on adverse obstetrical events, including unanticipated cesarean birth in low-risk women or newborn intensive care unit admissions. It is recognized that hospitals carry a significant burden in the prevention of adverse outcomes that range from nurse staffing levels to the internal process and infrastructure of the hospital setting. Patient outcomes are a direct result not only of the patient's health status and characteristics (eg, socioeconomic position and ethnicity), but also of interactions with the healthcare delivery system. As such, the opportunity to examine hospital characteristics (structure and processes) that may be detrimental to safe patient outcomes is of paramount importance in providing optimal outcomes for childbearing women and their families.
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