1
|
Garrison GM, Meunier MR, Boswell CL, Greenwood JD, Nordin T, Angstman KB. Continuity of Care: A Primer for Family Medicine Residencies. Fam Med 2024; 56:76-83. [PMID: 38055847 DOI: 10.22454/fammed.2023.913197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Abstract
Continuity of care has been an identifying characteristic of family medicine since its inception and is an essential ingredient for high-functioning health care teams. Many benefits, including the quadruple aim of enhancing patient experience, improving population health, reducing costs, and improving care team well-being, are ascribed to continuity of care. In 2023, the Accreditation Council for Graduate Medical Education (ACGME) added two new continuity requirements-annual patient-sided continuity and annual resident-sided continuity-in family medicine training programs. This article reviews continuity of care as it applies to family medicine training programs. We discuss the various types of continuity and issues surrounding the measurement of continuity. A generally agreed upon definition of patient-sided and resident-sided continuity is presented to allow programs to begin to collect the necessary data. Especially within resident training programs, intricacies associated with maintaining continuity of care, such as empanelment, resident turnover, and scheduling, are discussed. The importance of right-sizing resident panels is highlighted, and a mechanism for accomplishing this is presented. The recent ACGME requirements represent a cultural shift from measuring resident experience based on volume to measuring resident continuity. This cultural shift forces family medicine training programs to adapt their various systems, policies, and procedures to emphasize continuity. We hope this manuscript's review of several facets of contuinuity, some unique to training programs, helps programs ensure compliance with the ACGME requirements.
Collapse
Affiliation(s)
| | | | | | | | - Terri Nordin
- Department of Family Medicine, Mayo Clinic Health System, Eau Claire, WI
| | | |
Collapse
|
2
|
Guo HH, Shen HR, Wang LL, Luo ZG, Zhang JL, Zhang HJ, Gao TL, Han YX, Jiang JD. Berberine is a potential alternative for metformin with good regulatory effect on lipids in treating metabolic diseases. Biomed Pharmacother 2023; 163:114754. [PMID: 37094549 DOI: 10.1016/j.biopha.2023.114754] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/18/2023] [Accepted: 04/20/2023] [Indexed: 04/26/2023] Open
Abstract
Metformin (MTF) and berberine (BBR) share several therapeutic benefits in treating metabolic-related disorders. However, as the two agents have very different chemical structure and bioavailability in oral route, the goal of this study is to learn their characteristics in treating metabolic disorders. The therapeutic efficacy of BBR and MTF was systemically investigated in the high fat diet feeding hamsters and/or ApoE(-/-) mice; in parallel, gut microbiota related mechanisms were studied for both agents. We discovered that, although both two drugs had almost identical effects on reducing fatty liver, inflammation and atherosclerosis, BBR appeared to be superior over MTF in alleviating hyperlipidemia and obesity, but MTF was more effective than BBR for the control of blood glucose. Association analysis revealed that the modulation of intestinal microenvironment played a crucial role in the pharmacodynamics of both drugs, in which their respective superiority on the regulation of gut microbiota composition and intestinal bile acids might contribute to their own merits on lowering glucose or lipids. This study shows that BBR may be a good alternative for MTF in treating diabetic patients, especially for those complicated with dyslipidemia and obesity.
Collapse
Affiliation(s)
- Hui-Hui Guo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Hao-Ran Shen
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Lu-Lu Wang
- Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Zhi-Gang Luo
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Jin-Lan Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Hong-Juan Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China
| | - Tian-Le Gao
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
| | - Yan-Xing Han
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
| | - Jian-Dong Jiang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China; Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, China.
| |
Collapse
|
3
|
Greenwood J, Zurek KI, Grimm JM, Wi CI, Vogel JT, Garrison GM. Association of a housing based individual socioeconomic status measure with diabetic control in primary care practices. Prim Care Diabetes 2022; 16:78-83. [PMID: 34802978 DOI: 10.1016/j.pcd.2021.10.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 08/12/2021] [Accepted: 10/05/2021] [Indexed: 11/26/2022]
Abstract
AIMS Socioeconomic status (SES) is an important variable that impacts healthcare outcomes. However, grouped SES data is not always representative of all members and it is difficult to obtain individual level data. A validated individual housing-based measure termed HOUSES is available, but has not been studied in diabetes. We hypothesize that patients in the lowest HOUSES quartile are associated with worse diabetic control as measured by the D5. METHODS A retrospective cohort study of 5463 patients with diabetes in 5 patient centered medical home practices in southeast Minnesota was conducted. HOUSES is a validated, standardized housing-based SES measure constructed from publicly available county assessor's office data. Diabetic control was assessed by the D5 (HgbA1c < 8, BP < 140/90, statin use, nonsmoking status, and antiplatelet therapy). RESULTS In the lowest HOUSES quartile, more patients had an uncontrolled D5 (56.4%) than any of the other quartiles (49.2%, 49.8%, 49.6% respectively, p < 0.001). A multivariate analysis shows the adjusted odds of D5 control for patients in the 2nd, 3rd or 4th HOUSES quartiles as opposed to the 1st quartile are 1.28, 1.21, and 1.20, respectively. CONCLUSION Lower SES as represented by the first quartile of HOUSES index, is associated with lower odds of D5 control and thus worse diabetic outcomes. Using the HOUSES index to identify these individuals in a patient centered medical home might prove useful in deciding where to focus diabetic control efforts.
Collapse
Affiliation(s)
- Jason Greenwood
- Department of Family Medicine, Mayo Clinic, Rochester, MN, United States
| | - Kaitlyn I Zurek
- Department of Family Medicine, Mayo Clinic, Rochester, MN, United States
| | - Jade M Grimm
- Department of Family Medicine, Mayo Clinic, Rochester, MN, United States
| | - Chung-Il Wi
- Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN, United States; Precision Population Science Lab, Mayo Clinic, Rochester, MN, United States
| | - John T Vogel
- Department of Family Medicine, Mayo Clinic, Rochester, MN, United States
| | - Gregory M Garrison
- Department of Family Medicine, Mayo Clinic, Rochester, MN, United States.
| |
Collapse
|
4
|
|
5
|
Bernard ME, Laabs SB, Nagaraju D, Allen SV, Halasy MP, Rushlow DR, Garrison GM, Maxson JA, Matthews MR, Sobolik GJ, Lampman MA, Foss RM, Rosas SL, Thacher TD. Clinician Care Team Composition and Health Care Utilization. Mayo Clin Proc Innov Qual Outcomes 2021; 5:338-346. [PMID: 33997633 PMCID: PMC8105520 DOI: 10.1016/j.mayocpiqo.2021.01.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Objective To test the hypothesis that a greater proportion of physician time on primary care teams are associated with decreased emergency department (ED) visits, hospital admissions, and readmissions, and to determine clinician and care team characteristics associated with greater utilization. Patients and Methods We retrospectively analyzed administrative data collected from January 1 to December 31, 2017, of 420 family medicine clinicians (253 physicians, 167 nurse practitioners/physician assistants [NP/PAs]) with patient panels in an integrated health system in 59 Midwestern communities serving rural and urban areas in Minnesota, Wisconsin, and Iowa. These clinicians cared for 419,581 patients through 110 care teams, with varying numbers of physicians and NP/PAs. Primary outcome measures were rates of ED visits, hospitalizations, and readmissions. Results The proportion of physician full-time equivalents on the team was unrelated to rates of ED visits (rate ratio [RR] = 0.826; 95% confidence interval [CI], 0.624 to 1.063), hospitalizations (RR = 0.894; 95% CI, 0.746 to 1.072), or readmissions (RR = –0.026; 95% CI, 0.364 to 0.312). In separate multivariable models adjusted for clinician and practice-level characteristics, the rate of ED visits was positively associated with mean panel hierarchical condition category (HCC) score, urban vs rural setting, NP/PA vs physician, and lower years in practice. The rate of inpatient admissions was associated with HCC score, and 30-day hospital readmissions were positively associated with HCC score, lower years in practice, and male clinicians. Conclusion Care team physician and NP/PA composition was not independently related to utilization. More complex panels had higher rates of ED visits, hospitalization, and readmissions. Statistically significant differences between physician and NP/PA panels were only evident for ED visits.
Collapse
Affiliation(s)
| | - Susan B Laabs
- Department of Family Medicine, Mayo Clinic, Rochester, MN
| | | | - Summer V Allen
- Department of Family Medicine, Mayo Clinic, Rochester, MN
| | | | | | | | - Julie A Maxson
- Department of Family Medicine, Mayo Clinic, Rochester, MN
| | | | - Gerald J Sobolik
- Department of Health Care Administration, Mayo Clinic, Rochester, MN
| | | | - Randy M Foss
- Department of Family Medicine, Mayo Clinic, Rochester, MN
| | - Steven L Rosas
- Department of Family Medicine, Mayo Clinic, Rochester, MN
| | - Tom D Thacher
- Department of Family Medicine, Mayo Clinic, Rochester, MN
| |
Collapse
|
6
|
Meyerink BD, Lampman MA, Laabs SB, Foss RM, Garrison GM, Angstman KB, Sobolik GJ, Halasy MP, Fischer KJ, Rosas SL, Maxson JA, Rushlow DR, Horn JL, Matthews MR, Nagaraju D, Thacher TD. Relationship of Clinician Care Team Composition and Diabetes Quality Outcomes. Popul Health Manag 2020; 24:502-508. [PMID: 33216689 DOI: 10.1089/pop.2020.0229] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The objective was to determine if a greater proportion of physician full-time equivalent (FTE%) relative to nurse practitioners/physician assistants (NPs/PAs) on care teams was associated with improved individual clinician diabetes quality outcomes. The authors conducted a retrospective cross-sectional study of 420 family medicine clinicians in 110 care teams in a Midwest health system, using administrative data from January 1, 2017 to December 31, 2017. Poisson regression was used to examine the relationship between physician FTE% and the number of patients meeting 5 criteria included in a composite metric for diabetes management (D5). Covariates included panel size, clinician type, sex, years in practice, region, patient satisfaction, care team size, rural location, and panel complexity. Of the 420 clinicians, 167 (40%) were NP/PA staff and 253 (60%) were physicians. D5 criteria were achieved in 37.9% of NP/PA panels compared with 44.5% of physician panels (P < .001). In adjusted analysis, rate of patients achieving D5 was unrelated to physician FTE% on the care team (P = .78). Physicians had a 1.082 (95% confidence interval 1.007-1.164) times greater rate of patients with diabetes achieving D5 than NPs/PAs. Clinicians at rural locations had a .904 (.852-.959) times lower rate of achieving D5 than those at urban locations. Physicians had a greater rate of patients achieving D5 compared with NPs/PAs, but physician FTE% on the care team was unrelated to D5 outcomes. This suggests that clinician team composition matters less than team roles and the dynamics of collaborative care between members.
Collapse
Affiliation(s)
| | - Michelle A Lampman
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Susan B Laabs
- Department of Family Medicine, Mayo Clinic, Mankato, Minnesota, USA
| | - Randy M Foss
- Department of Family Medicine, Mayo Clinic, Lake City, Minnesota, USA
| | - Gregory M Garrison
- Department of Family Medicine and Mayo Clinic, Rochester, Minnesota, USA
| | - Kurt B Angstman
- Department of Family Medicine and Mayo Clinic, Rochester, Minnesota, USA
| | - Gerald J Sobolik
- Primary Care and Population Health, Mayo Clinic, Rochester, Minnesota, USA
| | - Michael P Halasy
- Department of Physical Medicine and Rehabilitation, Spine Center, Mayo Clinic, Rochester, Minnesota, USA
| | - Kristin J Fischer
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Steven L Rosas
- Department of Family Medicine, Mayo Clinic, Menomonie, Wisconsin, USA
| | - Julie A Maxson
- Department of Family Medicine and Mayo Clinic, Rochester, Minnesota, USA
| | - David R Rushlow
- Department of Family Medicine and Mayo Clinic, Rochester, Minnesota, USA
| | - Jennifer L Horn
- Department of Family Medicine and Mayo Clinic, Rochester, Minnesota, USA
| | - Marc R Matthews
- Department of Family Medicine and Mayo Clinic, Rochester, Minnesota, USA
| | - Darshan Nagaraju
- Department of Family Medicine and Mayo Clinic, Rochester, Minnesota, USA
| | - Tom D Thacher
- Department of Family Medicine and Mayo Clinic, Rochester, Minnesota, USA
| |
Collapse
|
7
|
Garrison GM, Dilger BT. Quantifying organization of care in a complex healthcare environment. J Eval Clin Pract 2020; 26:1548-1551. [PMID: 32216171 DOI: 10.1111/jep.13392] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 03/14/2020] [Indexed: 11/28/2022]
Affiliation(s)
| | - Benjamin T Dilger
- Department of Family Medicine, Mayo Clinic, Rochester, Minnesota, USA
| |
Collapse
|
8
|
Rosenberg NA, Zulman DM. Measures of care fragmentation: Mathematical insights from population genetics. Health Serv Res 2020; 55:318-327. [PMID: 31970757 DOI: 10.1111/1475-6773.13263] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE To identify novel properties of health care fragmentation measures, drawing on insights from mathematically equivalent measures of genetic diversity. STUDY DESIGN We describe mathematical relationships between two measures: (a) Breslau's Usual Provider of Care (UPC), the proportion of care with the most frequently visited provider, analogous to the "frequency of the most frequent allele" at a genetic locus; and (b) Bice-Boxerman's Continuity of Care Index (COCI), a measure of care dispersion across multiple providers, analogous to "Nei's estimator of homozygosity" in genetics. PRINCIPAL FINDINGS Just as the frequency of the most frequent allele places a tight constraint on homozygosity, the proportion of care with the most frequently visited provider (UPC) places lower and upper bounds on dispersion of care (COCI), and vice versa. This property presents the possibility of a normalized COCI given UPC (NCGU) measure, which reflects a bounded range of care dispersion dependent on the number of visits with the most frequently visited provider. Mathematical aspects of UPC and COCI also suggest thresholds for the minimal number of patient visits to use when studying fragmentation. CONCLUSIONS Applying knowledge from population genetics elucidated relationships between care fragmentation measures and produced novel insights for care fragmentation studies.
Collapse
Affiliation(s)
- Noah A Rosenberg
- Department of Biology, Stanford University, Stanford, California
| | - Donna M Zulman
- Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford, California.,Center for Innovation to Implementation, VA Palo Alto Health Care System, Menlo Park, California
| |
Collapse
|