Author
Listed:
- Hiromitsu Kaneko
(Faculty of Medicine, Osaka University, Suita, Osaka 565-0871, Japan)
- Akiko Hanamoto
(Independent Researcher, Kita-ku, Kyoto 603-8233, Japan)
- Sachiko Yamamoto-Kataoka
(Department of Health Informatics, Kyoto University Graduate School of Medicine/School of Public Health, Yoshida Konoe-cho, Sakyo-ku, Kyoto 606-8501, Japan)
- Yuki Kataoka
(Department of Internal Medicine, Kyoto Min-Iren Asukai Hospital, Tanaka Asukai-cho 89, Kyoto 606-8226, Japan
Scientific Research Works Peer Support Group (SRWS-PSG), Osaka 541-0043, Japan
Section of Clinical Epidemiology, Department of Community Medicine, Kyoto University Graduate School of Medicine, Shogoin Kawara-cho 54, Kyoto 606-8507, Japan
Department of Healthcare Epidemiology, Kyoto University Graduate School of Medicine/School of Public Health, Yoshida Konoe-cho, Kyoto 606-8501, Japan)
- Takuya Aoki
(Section of Clinical Epidemiology, Department of Community Medicine, Kyoto University Graduate School of Medicine, Shogoin Kawara-cho 54, Kyoto 606-8507, Japan
Division of Clinical Epidemiology, Research Center for Medical Sciences, The Jikei University School of Medicine, 3-25-8 Nishishimbashi, Minato-ku, Tokyo 105-8461, Japan)
- Kokoro Shirai
(Department of Social Medicine, Osaka University Graduate School of Medicine, Osaka 565-0871, Japan)
- Hiroyasu Iso
(Department of Social Medicine, Osaka University Graduate School of Medicine, Osaka 565-0871, Japan
Institute for Global Health Policy Research, Bureau of International Health Cooperation, National Center for Global Health and Medicine, Tokyo 162-8655, Japan)
Abstract
Various tools to measure patient complexity have been developed. Primary care physicians often deal with patient complexity. However, their usefulness in primary care settings is unclear. This study explored complexity measurement tools in general adult and patient populations to investigate the correlations between patient complexity and outcomes, including health-related patient outcomes, healthcare costs, and impacts on healthcare providers. We used a five-stage scoping review framework, searching MEDLINE and CINAHL, including reference lists of identified studies. A total of 21 patient complexity management tools were found. Twenty-five studies examined the correlation between patient complexity and health-related patient outcomes, two examined healthcare costs, and one assessed impacts on healthcare providers. No studies have considered sharing information or action plans with multidisciplinary teams while measuring outcomes for complex patients. Of the tools, eleven used face-to-face interviews, seven extracted data from medical records, and three used self-assessments. The evidence of correlations between patient complexity and outcomes was insufficient for clinical implementation. Self-assessment tools might be convenient for conducting further studies. A multidisciplinary approach is essential to develop effective intervention protocols. Further research is required to determine these correlations in primary care settings.
Suggested Citation
Hiromitsu Kaneko & Akiko Hanamoto & Sachiko Yamamoto-Kataoka & Yuki Kataoka & Takuya Aoki & Kokoro Shirai & Hiroyasu Iso, 2022.
"Evaluation of Complexity Measurement Tools for Correlations with Health-Related Outcomes, Health Care Costs and Impacts on Healthcare Providers: A Scoping Review,"
IJERPH, MDPI, vol. 19(23), pages 1-18, December.
Handle:
RePEc:gam:jijerp:v:19:y:2022:i:23:p:16113-:d:991092
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