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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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Westley-Wise V, Lago L, Mullan J, Facci F, Zingel R, Eagar K. Trends in unplanned readmissions over 15 years: a regional Australian perspective. AUST HEALTH REV 2019; 44:241-247. [PMID: 30827332 DOI: 10.1071/ah18072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 11/19/2018] [Indexed: 11/23/2022]
Abstract
Objective The aim of this study was to assess 15-year trends in unplanned readmissions in an Australian regional health service. Methods Drawing on data held in the Illawarra Health Information Platform (IHIP), this longitudinal retrospective study of adults admitted to hospital between 2001-02 and 2015-16 assessed rates of unplanned all-cause readmissions within 30 days ('early') and 1-6 months ('late') following discharge. Rates were compared over time and between patient groups. Results Age-adjusted early readmission rates declined over the 15 years by an average of 1.3% per annum, whereas late readmission rates increased by an average of 0.6% per annum. Together, there was an overall decline in readmission rates. The entire decline in early readmission rates and a reversal of the increasing trend in late readmission rates occurred since 2010-11. Similar trends occurred across age groups, but were most pronounced among those aged ≥75 years. Conclusions The decline in readmissions since 2010-11 suggests that the region has achieved improvements in discharge planning and in continuity between hospitals and community-based care. These improvements have occurred across broad patient groups. The longitudinal and linked data held in the IHIP provides a unique opportunity to examine patterns of service utilisation at a regional level. What is known about the topic? Published reports of longitudinal trends in readmissions are typically limited by short study periods and narrow criteria used to define study populations and readmissions. Australian longitudinal data suggest rates of early readmission have remained relatively unchanged in recent years, despite the focus on readmission rates as a metric to assess the quality and continuity of care. What does this paper add? This unique longitudinal study reports on long-term readmission trends over 15 years to hospitals within a single geographic area, with trends reported for both early (30-day) and late (1- to 6-month) readmissions by age group and major diagnostic categories. The findings reflect more complex patterns than are typically reported in cross-sectional and more limited longitudinal studies. What are the implications for practitioners? The results suggest improvements at a regional level that may be associated with care during the initial hospitalisation and discharge (reflected particularly in early readmissions) and in the community (reflected particularly in late readmissions). Future investigations will explore specific patient groups and the effects of specific initiatives, services and models of care to better predict those at risk of readmission and to inform translation locally and further afield. The relationship between readmissions and the use of ambulatory services (primary care, emergency department and out-patient) also warrants further investigation.
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Affiliation(s)
- Victoria Westley-Wise
- Illawarra Shoalhaven Local Health District, Level 1, 67-71 King Street, Warrawong, NSW 2502, Australia. ; ; and Centre for Health Services Research Illawarra Shoalhaven Population, University of Wollongong, Building 234, Innovation Campus, Wollongong, NSW 2522, Australia. , ; and Corresponding author.
| | - Luise Lago
- Centre for Health Services Research Illawarra Shoalhaven Population, University of Wollongong, Building 234, Innovation Campus, Wollongong, NSW 2522, Australia. ,
| | - Judy Mullan
- Centre for Health Services Research Illawarra Shoalhaven Population, University of Wollongong, Building 234, Innovation Campus, Wollongong, NSW 2522, Australia. ,
| | - Franca Facci
- Illawarra Shoalhaven Local Health District, Level 1, 67-71 King Street, Warrawong, NSW 2502, Australia. ;
| | - Rebekah Zingel
- Illawarra Shoalhaven Local Health District, Level 1, 67-71 King Street, Warrawong, NSW 2502, Australia. ;
| | - Kathy Eagar
- Australian Health Services Research Institute, University of Wollongong, Building 234, Innovation Campus, Wollongong, NSW 2522, Australia.
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