ABSTRACT
Background:
With the rising prevalence of co-morbidities among the elderly, the traditional specialty-based healthcare system can no longer meet the needs for “early prevention, timely diagnosis and treatment,” and “holistic care.” Thus, there is an urgent need to develop geriatric teaching methods for general practitioners (GPs) that enable comprehensive, community-based care for elderly patients. This study aims to integrate a geriatric comorbidity management model into general practice training and evaluate the educational outcomes for GP trainees using the Mini-Clinical Evaluation Exercise (Mini-CEX) and case-based assessment methods.
Methods:
Cluster random sampling was used to select 80 GPs residents rotating in the Department of Geriatrics. After baseline assessment, the participants were divided into groups to receive either conventional teaching or training based on the geriatric comorbidity management model. Teaching outcomes were evaluated using the Mini-CEX and case analysis assessments.
Results:
After training with the comorbidity management model, trainees demonstrated significant improvements in both core case analysis competencies and clinical decision-making abilities. These enhancements were specifically observed across multiple dimensions, including supplementary history taking, supplementary inquiry of physical examination findings, supplementary inquiry of ancillary test results, and diagnosis and rationale. Furthermore, trainees who underwent this training model showed more favorable outcomes in terms of instructor satisfaction with student assessment and student satisfaction with the assessment process.
Conclusion:
Integrating the geriatric comorbidity management model into GPs can effectively enhance trainees’ multidisciplinary collaboration skills. The Mini-CEX and case-based serve as effective teaching evaluation tools, contributing to the overall improvement of teaching quality.
Keywords: Case-based assessment, clinical decision-making, general practice residency training, geriatric comorbidity, Mini-CEX
Background
As the aging process accelerates in China, the society has now entered an era of pronounced population aging, bringing geriatric medicine to the forefront of healthcare. Consequently, the need for geriatric medical education and practice has gained significant attention.[1] The prevalence of multimorbidity is particularly high among older adults, where multimorbidity refers to the coexistence of two or more chronic conditions, including physical diseases, geriatric syndromes, and mental health issues.[2] As concepts surrounding geriatric multimorbidity management evolve,[3] geriatric medical education has increasingly embraced a multimorbidity management model that centers on comprehensive geriatric assessment (CGA) and multidisciplinary collaboration.[4]
General practitioners (GPs), as the “gatekeepers” of public health, play a critical role in modern healthcare systems.[5,6,7] With the growing demand for “early prevention, timely diagnosis and treatment,” and “holistic care,” the traditional specialty-based medical model is no longer adequate to fully address these needs. Therefore, GPs are expected not only to diagnose and treat illnesses in elderly patients within the community but also to focus on preventive care and comprehensive patient management.[8] To improve the quality of general practice training, it is essential to provide GP residents with foundational knowledge in geriatric multimorbidity and integrate the principles of geriatric multimorbidity management into general practice education. By blending theory with practical application and drawing upon internationally established management models, the overall quality of geriatric medical education can be significantly enhanced. Thus, it is imperative to develop geriatric teaching methods that are well-suited to general practice training, ensuring these methods align with current healthcare needs and health management demands.[9,10]
This study integrates a geriatric comorbidity management model into the training of general practice residents. Using Mini-Clinical Evaluation Exercise (Mini-CEX)[11,12] and case analysis ability assessments, the educational effectiveness of this model was evaluated in a comparative group study involving 80 general practice residents. The aim is to establish a holistic principle-based clinical teaching model and explore an efficient geriatric medicine teaching approach suitable for standardized general practice residency training, thereby enhancing multidisciplinary collaboration skills and comprehensively improving teaching quality.[13]
Methods
Clinical data and study participants
A cluster random sampling method[14,15] was applied to select 80 qualified medical residents rotating in the geriatrics department at the Affiliated Hospital of Qinghai University from 2022 to 2023. Inclusion criteria required voluntary enrollment in the elderly comorbidity management training program, signing an informed consent, and active participation in all training activities. Exclusion criteria included advanced age, underlying health conditions, or unwillingness to participate in the study. Participants were randomly assigned into either an experimental group (n = 40) or a control group (n = 40) using a random number table method. In the experimental group, there were 15 males and 25 females, with an age range of 22–27 years (mean 23.83 ± 2.32 years). In the control group, there were 17 males and 24 females, with an age range of 21–28 years (mean 23.57 ± 2.65 years). No significant differences were found in age or gender between the two groups (P > 0.05), indicating comparability.
Teaching methods
Before training, the initial status of each participant was assessed using a case analysis ability test and Mini-CEX scores. Subsequently, the control group received conventional teaching methods during their clinical practice, which primarily consisted of lecture-based instruction by supervising physicians. The training curriculum covered foundational professional skills for healthcare practitioners, the diagnosis and management of common internal medicine diseases, and the application of doctor-patient communication techniques. Classes were scheduled biweekly, with each session lasting two academic hours. In the experimental group, additional training on elderly comorbidity management was incorporated as follows.
Design and implementation of comorbidity management training
Upon entering the geriatrics department, the intervention group first received a comprehensive introduction to geriatric comorbidity management, with training in CGA and multidisciplinary care planning,[16] followed by a 6-week clinical practicum under the guidance of attending physicians. During this period, residents independently managed elderly patients with multiple comorbidities, conducted CGA, and engaged in multidisciplinary care planning. Supervising physicians observed and provided guidance.
Implementation of comprehensive geriatric assessment
Trainees were required to complete a full CGA,[17,18] covering six major areas: general medical assessment, activities of daily living assessment[19] (including cognition, pressure ulcer risk, fall risk, swallowing ability, and nutrition), mental and psychological assessment, social evaluation, environmental evaluation, and quality of life assessment. The CGA was to be completed within 72 h of admission for general inpatients. For critically ill patients, assessments were performed immediately, with re-assessments on day eight for those hospitalized longer than a week. A discharge evaluation was conducted for all patients prior to release from the hospital.[20]
Implementation of multidisciplinary collaborative treatment
Participants in the experimental group took part in bi-weekly, 6-week-long multidisciplinary collaboration sessions on geriatric comorbidity management. This process included: Pre-session preparation: A case summary was distributed in advance to all members of the multidisciplinary team and participants. Session flow: The primary physician provided a 15–20 min case presentation, followed by a focused physical examination. Multidisciplinary experts then analyzed the case, focusing on psychological, nutritional, rehabilitation, and pharmacological interventions. Interaction with participants was facilitated through case-based teaching materials, including discussions, Q and A sessions, and a summary by the instructor, each lasting 50–60 and 15–20 min, respectively. Post-session Documentation: Detailed documentation of the multidisciplinary process and outcomes was maintained, followed by feedback and continuous improvement measures.
Teaching evaluation metrics
After completing a two-month geriatric comorbidity management training and clinical practice, we reassessed each participant’s case analysis ability and Mini-CEX scores based on standardized scoring criteria. The case analysis ability test covers the following eight dimensions: supplementary history taking, supplementary physical examination and ancillary test inquiries, synthesis of case characteristics, elaboration of diagnostic rationale, key differential diagnoses, treatment planning, humanistic care, and communication skills. The test format aligns with the comprehensive case analysis examination required for standardized resident training completion. Each module is scored out of 10 points, with a total score of 80 points. The Mini-CEX assessment includes the following ten dimensions: Key diagnostic and therapeutic Focus, clinical interview, physical examination, humanistic care, clinical judgment, communication skills, organizational effectiveness, holistic care, instructor satisfaction with student assessment, and student satisfaction with assessment. Each module is scored out of 10 points, with a total score of 100 points.
Statistical methods
Statistical analysis of Mini-CEX scores and case analysis scores for both groups was performed using SPSS 19.0 software (IBM Corp., Armonk, NY, USA). Quantitative data are presented as mean ± standard deviation (mean ± standard deviation). For data conforming to a normal distribution, paired t-tests were employed for comparisons, while the Wilcoxon rank-sum test was used for data that did not follow a normal distribution. A P < 0.05 was considered statistically significant. Data visualization was conducted using GraphPad Prism 9.0 software (GraphPad Software, San Diego, CA, USA). Statistical significance levels are indicated as follows: ns = not significant (P ≥ 0.05), *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001.
Results
Comparison of case analysis ability before training
Firstly, we assessed the case analysis skills of the two groups of participants before the training. An independent samples t-test was used to compare the baseline case analysis abilities between the control and experimental groups. The results showed that the case analysis abilities of both groups were at the same level prior to the training [Figure 1]. Specifically, as shown in Table 1, none of the indicators of case analysis ability showed statistically significant differences between the groups (all P > 0.05), indicating that the two groups were highly similar at baseline. This result established a reliable baseline for the subsequent evaluation of training effectiveness.
Figure 1.
Comparison of case analysis skills before and after training between control and experimental groups. Data are presented as mean scores with error bars indicating standard deviations. Statistical significance is indicated (ns = not significant (P ≥ 0.05), *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001)
Table 1.
Comparison of case analysis skills before training between control and experimental groups
| Indicator | Control | Experimental | t | P |
|---|---|---|---|---|
| Supplementary history taking | 7.08±0.62 | 7.23±0.62 | 1.086 | 0.281 |
| Supplementary physical examination findings inquiry | 7.1±0.84 | 6.95±0.64 | −0.898 | 0.372 |
| Supplementary inquiry of ancillary test results | 7.25±0.67 | 7.1±0.59 | −1.062 | 0.291 |
| Summary of key history findings | 6.85±0.58 | 7±0.68 | 1.062 | 0.291 |
| Diagnosis and rationale | 7.13±0.61 | 7.15±0.43 | 0.213 | 0.832 |
| Key points of differential diagnosis | 6.95±0.64 | 7±0.45 | 0.404 | 0.687 |
| Treatment measures | 7.05±0.68 | 7±0.51 | −0.374 | 0.71 |
| Humanistic care and communication skills | 7.03±1.03 | 6.93±0.53 | −0.549 | 0.585 |
Comparison of Mini-Clinical Evaluation Exercise scores before training
Subsequently, we evaluated the Mini-CEX scores of participants from both groups before the training and compared the scores between the control and experimental groups using an independent samples t-test. The results indicated that the Mini-CEX scores of the two groups were statistically comparable before the training [Figure 2]. Specifically, as shown in Table 2, all Mini-CEX indicators had P > 0.05, demonstrating no statistically significant differences between the two groups at baseline.[14] This result further confirms the high comparability of the two groups before the intervention, thereby establishing a reliable foundation for the subsequent.
Figure 2.
Comparison of Mini-CEX scores before and after training between control and experimental groups. Data are presented as mean scores with error bars indicating standard deviations. Statistical significance is indicated (ns = not significant (P ≥ 0.05), *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001). Mini-CEX = Mini-Clinical Evaluation Exercise
Table 2.
Comparison of Mini-Clinical Evaluation Exercise scores before training between control and experimental groups
| Indicator | Control | Experimental | t | P |
|---|---|---|---|---|
| Key points of diagnosis and treatment | 5.2±0.91 | 5.23±0.83 | 0.128 | 0.898 |
| Medical interview | 5±0.78 | 5.28±1.01 | 1.358 | 0.178 |
| Physical examination | 4.88±0.85 | 4.75±0.9 | −0.638 | 0.525 |
| Humanistic care | 4.98±0.86 | 4.85±0.92 | −0.627 | 0.533 |
| Clinical judgment | 4.93±0.83 | 4.9±0.81 | −0.136 | 0.892 |
| Communication skills | 5.08±0.69 | 5.28±0.64 | 1.34 | 0.184 |
| Organizational effectiveness | 5.03±0.95 | 5.18±0.96 | 0.704 | 0.483 |
| Holistic care | 6.43±0.96 | 6.25±0.93 | −0.83 | 0.409 |
| Instructor satisfaction with student evaluation | 6.15±1.03 | 5.78±1.17 | −1.527 | 0.131 |
| Student satisfaction with the evaluation | 5.98±0.97 | 5.9±1.22 | −0.305 | 0.761 |
Comparative effectiveness of training on case analysis abilities
Next, paired t-tests were conducted to evaluate changes in case analysis skill scores before and after training within the control and experimental groups, respectively. The results revealed that the control group showed significant improvement only in key areas such as summary of key history findings (P < 0.001), treatment measures (P < 0.001), and humanistic care and communication skills (P < 0.001). In contrast, no significant improvements were observed in supplementary history taking (P = 0.052), supplementary inquiry of physical examination findings (P = 0.062), supplementary inquiry of ancillary test results (P = 0.762), diagnosis and rationale (P = 0.421), or key points of differential diagnosis (P = 0.062) [Figure 3]. In comparison, the experimental group demonstrated significant progress across all assessed dimensions after training. The total score of the experimental group also increased significantly (P < 0.001) [Figure 3 and Table 3].[15]
Figure 3.
Comparison of case analysis abilities between the control and experimental groups before and after training. The bar chart illustrates the comparison of mean scores in various case analysis skills between the control and experimental groups before and after training. The key competency areas assessed include: Supplementary History Taking, Supplementary Physical Examination Findings Inquiry, Supplementary Inquiry of Ancillary Test Results, Summary of Key History Findings, Diagnosis and Rationale, Key Points of Differential Diagnosis, Treatment Measures, and Humanistic Care and Communication Skills. Data are presented as mean ± standard deviation, and error bars represent the standard deviation. (ns = not significant (P ≥ 0.05), *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001)
Table 3.
Comparison of case analysis abilities after training between the control and experimental groups
| Indicator | Clusters | Pre-test | Post-test | t | P |
|---|---|---|---|---|---|
| Supplementary history taking | Control | 7.08±0.62 | 7.43±0.64 | −2.333 | 0.052 |
| Experimental | 7.23±0.62 | 7.73±0.91 | −2.687 | 0.011 | |
| Supplementary physical examination Findings inquiry | Control | 7.1±0.84 | 7.43±0.59 | −1.918 | 0.062 |
| Experimental | 6.9 5±0.64 | 7.75±0.74 | −5.387 | <0.001 | |
| Supplementary inquiry of ancillary test results | Control | 7.25±0.67 | 7.3±0.65 | −0.305 | 0.762 |
| Experimental | 7.1±0.59 | 8.15±0.74 | −6.736 | <0.001 | |
| Summary of key history findings | Control | 6.85±0.58 | 7.3±0.52 | −4.201 | <0.001 |
| Experimental | 7±0.68 | 7.98±0.92 | −5.503 | <0.001 | |
| Diagnosis and rationale | Control | 7.13±0.61 | 7.23±0.48 | −0.813 | 0.421 |
| Experimental | 7.15±0.43 | 8.05±0.88 | −5.511 | <0.001 | |
| Key points of differential diagnosis | Control | 6.95±0.64 | 7.23±0.62 | −2.218 | 0.062 |
| Experimental | 7±0.45 | 8.08±0.66 | −9.315 | <0.001 | |
| Treatment measures | Control | 7.05±0.68 | 7.6±0.71 | −3.973 | <0.001 |
| Experimental | 7±0.51 | 7.93±0.66 | −7.656 | <0.001 | |
| Humanistic care and communication skills | Control | 7.03±1.03 | 7.83±0.64 | −4.135 | <0.001 |
| Experimental | 6.93±0.53 | 8.28±0.6 | −12.894 | <0.001 |
Further analysis using independent samples t-tests to compare post-training performance between the two groups indicated that although both groups showed improvements after training, the experimental group significantly outperformed the control group in the total score and multiple specific indicators [Figure 1]. These indicators included supplementary inquiry of ancillary test results, summary of key history findings, diagnosis and rationale, key points of differential diagnosis, and humanistic care and communication skills (P < 0.05) [Table 4]. These results indicate that trainees receiving the geriatric comorbidity management model showed significantly greater improvement in comprehensive case analysis abilities compared to those trained with traditional teaching methods.
Table 4.
Comparison of case analysis skills after training between control and experimental groups
| Indicator | Control | Experimental | t | P |
|---|---|---|---|---|
| Supplementary history taking | 7.43±0.64 | 7.73±0.91 | 1.715 | 0.09 |
| Supplementary physical examination findings inquiry | 7.43±0.59 | 7.75±0.74 | 2.161 | 0.258 |
| Supplementary inquiry of ancillary test results | 7.3±0.65 | 8.15±0.74 | 5.482 | <0.001 |
| Summary of key history findings | 7.3±0.52 | 7.98±0.92 | 4.048 | <0.001 |
| Diagnosis and rationale | 7.23±0.48 | 8.05±0.88 | 5.226 | <0.001 |
| Key points of differential diagnosis | 7.23±0.62 | 8.08±0.66 | 5.958 | <0.001 |
| Treatment measures | 7.6±0.71 | 7.93±0.66 | 2.128 | 0.258 |
| Humanistic care and communication skills | 7.83±0.64 | 8.28±0.6 | 3.259 | 0.031 |
Comparison of Mini-Clinical Evaluation Exercise scores between groups after training
Finally, paired t-tests were conducted to analyze the changes in Mini-CEX scores within the control and experimental groups after training. The results indicated that the control group showed no significant improvement in three areas: Holistic Care (P = 0.377), Instructor Satisfaction with Student Assessment (P = 0.542), and Student Satisfaction with Assessment (P = 0.16). However, significant progress was observed in all other domains, including Key Diagnostic and Therapeutic Focus, Clinical Interview, Physical Examination, Humanistic Care, Clinical Judgment, Communication Skills, and Organizational Effectiveness [Figure 4]. In the experimental group, all Mini-CEX indicators demonstrated significant improvement (P < 0.05), except for Holistic Care (P = 0.074), which did not reach statistical significance [Table 5].
Figure 4.
Comparison of Mini-CEX scores between control and experimental groups before and after training. The bar chart illustrates the comparison of mean Mini-CEX scores between the control and experimental groups before and after training. The core competencies assessed include: Key Diagnostic and Therapeutic Focus, Clinical Interview, Physical Examination, Humanistic Care, Clinical Judgment, Communication Skills, Organizational Effectiveness, Holistic Care, Instructor Satisfaction with Student Assessment, and Student Satisfaction with Assessment. Data are presented as mean ± standard deviation, and error bars represent the standard deviation (ns = not significant (P ≥ 0.05), *P < 0.05, **P < 0.01, ***P < 0.001, ****P < 0.0001)
Table 5.
Comparison of Mini-Clinical Evaluation Exercise scores after training between the control and experimental groups
| Indicator | Clusters | Pre-test | Post-test | t | P |
|---|---|---|---|---|---|
| Key diagnostic and therapeutic focus | Control | 5.2±0.91 | 6.3±1.32 | −4.997 | <0.001 |
| Experimental | 5.23±0.83 | 6±0.93 | −4.669 | <0.001 | |
| Clinical interview | Control | 5±0.78 | 7.1±1.17 | −10.929 | <0.001 |
| Experimental | 5.28±1.01 | 7.65±0.74 | −13.087 | <0.001 | |
| Physical examination | Control | 4.88±0.85 | 6.48±0.88 | −8.327 | <0.001 |
| Experimental | 4.75±0.9 | 6.6±1.17 | −8.016 | <0.001 | |
| Humanistic care | Control | 4.98±0.86 | 6.58±1.04 | −8.327 | <0.001 |
| Experimental | 4.85±0.92 | 7.33±1.02 | −12.222 | <0.001 | |
| Clinical judgment | Control | 4.93±0.83 | 6.25±1.01 | −7.344 | <0.001 |
| Experimental | 4.9±0.81 | 6.58±1.06 | −7.454 | <0.001 | |
| Communication skills | Control | 5.08±0.69 | 6.23±0.97 | −6.482 | <0.001 |
| Experimental | 5.28±0.64 | 6.75±1.13 | −7.787 | <0.001 | |
| Organizational effectiveness | Control | 5.03±0.95 | 6.4±1.26 | −5.561 | <0.001 |
| Experimental | 5.18±0.96 | 6.7±1.16 | −7.651 | <0.001 | |
| Holistic care | Control | 6.43±0.96 | 6.25±0.93 | 0.894 | 0.377 |
| Experimental | 6.25±0.93 | 6.68±1.21 | −1.834 | 0.074 | |
| Instructor satisfaction with student Assessment | Control | 6.15±1.03 | 6.28±1.09 | −0.615 | 0.542 |
| Experimental | 5.78±1.17 | 6.63±1.37 | −2.888 | 0.006 | |
| Student satisfaction with assessment | Control | 5.98±0.97 | 6.33±1.12 | −1.433 | 0.16 |
| Experimental | 5.9±1.22 | 6.58±1.3 | −2.533 | 0.015 |
To further compare the performance between the two groups after training, an independent samples t-test was performed on the Mini-CEX scores. As shown in Table 6, the experimental group scored significantly higher than the control group in Humanistic Care (P = 0.002). The total score of the experimental group was also superior to that of the control group [Figure 2]. These findings demonstrate that trainees receiving the geriatric comorbidity management model exhibited significant advantages across all aspects of Mini-CEX scores, outperforming those trained with traditional teaching methods.
Table 6.
Comparison of Mini-Clinical Evaluation Exercise scores after training between control and experimental groups
| Indicator | Control | Experimental | t | P |
|---|---|---|---|---|
| Key diagnostic and therapeutic focus | 6.3±1.32 | 6±0.93 | −1.171 | 0.245 |
| Clinical interview | 7.1±1.17 | 7.65±0.74 | 2.513 | 0.233 |
| Physical examination | 6.48±0.88 | 6.6±1.17 | 0.54 | 0.591 |
| Humanistic care | 6.58±1.04 | 7.33±1.02 | 3.26 | 0.024 |
| Clinical judgment | 6.25±1.01 | 6.58±1.06 | 1.407 | 0.164 |
| Communication skills | 6.23±0.97 | 6.75±1.13 | 2.23 | 0.291 |
| Organizational effectiveness | 6.4±1.26 | 6.7±1.16 | 1.11 | 0.271 |
| Holistic care | 6.25±0.93 | 6.68±1.21 | 1.767 | 0.591 |
| Instructor satisfaction with student assessment | 6.28±1.09 | 6.63±1.37 | 1.265 | 0.21 |
| Student satisfaction with assessment | 6.33±1.12 | 6.58±1.3 | 0.923 | 0.359 |
Discussion
The elderly population constitutes a significant proportion of China’s demographic, and the high prevalence of comorbid chronic diseases among older adults imposes a substantial economic burden on families and society.[21,22] Elderly comorbidities not only lead to increased mortality and disability rates and higher healthcare expenditures compared to the general adult population, but they also diminish quality of life by increasing the occurrence of adverse events, thereby intensifying demands on healthcare resources.[23] Many elderly patients suffer from various comorbid conditions, complicating medical decision-making.[21] Frequently, these patients must seek care from multiple specialties, with each specialist following treatment guidelines specific to their field, resulting in polypharmacy.[24] Interactions among drugs and between drugs and diseases often worsen treatment outcomes, impair prognoses, increase adverse reactions, and may lead to medical issues such as fragmented care and overtreatment.[25]
The development of general practice relies heavily on the standardized training of GPs,[26] yet geriatric medicine remains a relatively underdeveloped area within GP training. As the elderly population rapidly grows and presents unique pathophysiological characteristics, geriatric medicine has garnered increasing attention.[27,28] To address the healthcare demands of an aging society and to train GPs proficient in geriatric medicine, teaching practices must evolve to reflect the specific needs of geriatric medicine.[29] Integrating a comorbidity management model into GP standardized training programs represents a strategic yet challenging approach.[29,30]
In 2012, an expert panel from the American Geriatrics Society developed guidelines for clinical management of elderly comorbidities,[31,32,33] emphasizing five key areas: understanding patient preferences, conducting CGA, cautious application of evidence-based medicine, multidisciplinary collaboration to develop optimal treatment plans, and careful consideration of risks, burdens, benefits, and prognosis associated with interventions.[34,35] Applying the elderly comorbidity management model in GP training not only cultivates GPs with skills in CGA and multidisciplinary collaboration but also enhances the overall competencies of GPs, facilitating holistic management of elderly patients.[36] The geriatric comorbidity management training model proposed in this study can promote comprehensive thinking and clinical decision-making among trainees, thereby avoiding misdiagnosis and missed diagnoses caused by specialist-centered thinking.[37] Introducing the comorbidity management model in GP training expands students’ clinical perspectives and can benefit community-based elderly and other populations in need of community healthcare services.[38,39,40]
The comorbidity management strategy includes comprehensive CGA, judicious application of evidence-based medicine, multidisciplinary collaborative care, long-term follow-up, and ongoing evaluation and adjustment of treatment plans.[41,42] These strategies align with the GP philosophy of “whole-person care.”[43] Applying the principles of elderly comorbidity management to community-based elderly care, with continuous assessment and multidisciplinary collaboration, can improve GPs’ clinical skills and help resolve the issues and suffering faced by elderly patients, ultimately achieving whole-person care.[42,44] Evaluating the application of elderly comorbidity management concepts in GP training through Mini-CEX scores and case analysis represents an innovative approach, effectively promoting curriculum and teaching reform.[45,46]
In summary, incorporating the elderly comorbidity management model into standardized GP training, optimizing teaching methods based on established guidelines, and adapting them to local contexts, represents an effective training approach.[42,47] The results of this study indicate that this model significantly enhances GPs’ comprehensive diagnostic and treatment abilities across multiple dimensions.[48,49] Compared to traditional training methods, the comorbidity management model demonstrates clear advantages, holds promise for wider adoption in future GP training programs, and can support GP workforce development, improve diagnostic and treatment quality, and strengthen primary healthcare services.[49,50,51,52]
However, this study has several limitations. First, the relatively small sample size and its single-center design may limit the generalizability of our findings. Future research should involve larger, multi-center cohorts to validate and extend our conclusions. Second, the educational outcomes were assessed immediately upon completion of the 6-week training program. The long-term retention of the acquired skills and knowledge, as well as their translation into clinical practice, remain unknown. Therefore, subsequent studies should include long-term follow-up assessments to evaluate the sustained impact of this training model. Furthermore, incorporating more objective patient outcome measures in clinical settings represents a valuable direction for future research.
Ethics approval and consent to participate
This study was conducted in accordance with the Declaration of Helsinki. Ethical approval for this study was obtained from the Ethics Committee of Qinghai University Hospital (P-SL-2022-107). All participants received written and verbal information about the study, including the right to voluntary participation and withdrawal, and written and verbal informed consent. The questionnaire used in this study was developed for this study, and specific information can be viewed in the supplementary materials.
Conflicts of interest
There are no conflicts of interest.
Acknowledgement
We would like to express our gratitude to all the GPs who participated in this study without receiving any direct financial compensation. We wish them all the best in their future careers.
Funding Statement
This study was supported by the following research agencies: Qinghai Provincial Health Care Commission Guiding Programmed Project on Teaching and Rehabilitation (wjzdx-50).
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