目的　COVID-19流行期における診療所の発熱外来の運営体制と患者数の関連性を検討する．

方法　当法人診療所のレセプトデータを集積したデータベースを用い，集団軌跡分析により2022年1月～2023年5月の医師1人当たり月間発熱外来患者数の推移パターンを分類し，質問紙調査（2025年4月）で得た診療所特性を群間比較した．

結果　集団軌跡分析の結果，11診療所は発熱外来患者数の少ない群（8診療所）と多い群（3診療所）に分類され，医師1人当たり月平均患者数はそれぞれ22.9±18.2人，66.2±33.1人だった．多い群では，医師数（3.0±1.0人 vs 1.5±0.7人）が多く，一般外来と別の医師が発熱外来を担当する割合が高く（100% vs 0%），受け入れ制限基準の運用が少なく（0% vs 37.5%），自施設の地域にとっての重要性をより強く感じていた（5.0±0.0 vs 4.3±1.2）．

結論　感染症流行期の診療所の発熱外来対応能力は，人的資源だけでなく，実質的な業務負荷，役割分担，診療や業務の運用方法にも影響されることが示唆された．

Aim/Introduction: Integrating physiological data from continuous glucose monitoring (CGM) with real-world behavioral data may offer new insights into health management. This study examined longitudinal changes in CGM-derived glycemic metrics and characterized patterns in participant-generated communication using a social networking platform.

Patients and Methods: Seven participants (five females, two males; mean age 60.0 ± 4.4 years) using the FreeStyle Libre 2 CGM system and LINE were included. CGM metrics were compared between early (days 2–7) and later (days 8–15) periods. Text data were analyzed for need categories, sentiment (positive, neutral, negative), temporal patterns, and interaction networks. Paired t-tests with Cohen’s d were used for comparisons, and Spearman’s rank correlation assessed associations.

Results: All seven participants were analyzed in both periods. Mean glucose management indicator (GMI) was 6.1% (SD 0.2), and none had diabetes. CGM metrics showed no significant differences between periods, although hAUC and MODD tended to decrease. Total word count was not associated with glycemic metrics. However, the proportion of positive words was negatively correlated with changes in mean glucose (r = −0.809, P = 0.028), while neutral words showed a borderline positive association. Text analysis revealed that a limited number of need categories accounted for most posts, with activity peaking in the evening and on weekends. Network analysis indicated that a few participants played central roles in communication.

Conclusions: While glycemic control remained stable, communication data revealed distinct behavioral patterns. Integrating physiological and digital behavioral data may improve understanding of engagement and support personalized management strategies.

大腸内視鏡挿入手技でしばしば遭遇する挿入困難例の多くは，Ｓ状結腸でのループ形成によるものである．水浸法と内視鏡挿入形状観測システム（ScopeGuide UPD-3）を併用することで，ループ形成を最小限に抑え，疼痛を軽減しつつループの解除が可能となる．内視鏡画像とUPD-3による走行画像を併せて提示し，ループ解除法を視覚的に理解しやすく構成した．疼痛を軽減しつつループを解除するコツを習得することで，高齢者や認知症患者に対しても無鎮静下で安全に施行可能となり，地域診療所という限られた医療資源の環境でも実践可能な手技となる．