温州市口腔医疗用户预约分析数据
收藏资源简介：
一、医院端核心价值：提升资源利用率：通过监测预约未到率，结合用户等级推送提醒（D级用户双提醒，A/B级用户保权益），降低未到率，减少医生/设备闲置。优化排班服务：按科室履约率、取消预约率调整排班（如种植科留弹性时段），减少冲突，降低投诉。联动营收：将履约率、失约率纳入医生考核，提升整体履约率，增加复购和营收。二、分用户等级运营方案（聚焦服务与优先级）：A级（90-100分）：①预约优先——优先锁定旺季热门医生/时段，支持1次/季度7天内临时调时段；②服务优先——到店免排队登记，享专属客服对接，年度1次免费口腔检查。B级（80-89分）：①预约优先——可约15天内热门时段，每月1次提前24小时调约免记录；②服务优先——到店优先叫号（比普通用户快15分钟），诊疗后赠洗牙9折券。C级（70-79分）：①预约服务——可约非高峰时段，预约前分3次推送提醒（避免失约）；D级（≤69分）：①预约服务——可约7天后非热门时段，预约后电话确认（确保有效）；三、行业价值：帮中小机构建标准化用户标签，替代人工记忆，降低未到率。履约率等指标成行业参考标准，助机构对标改进，释放诊疗产能。推动行业分层服务，留存优质用户、转化待改进用户，实现体验与效益双提升。1.数据收集和预处理：（1）数据收集：收集医院预约管理系统中的预约相关数据，具体包括统计、总预约次数、预约未到数、履约数、取消预约数、失约数。（2）数据预处理：对采集到的原始数据进行处理，去除医院主动取消预约、用户提交未确认预约、测试订单等无效数据，同时排除用户因突发疾病等特殊情况并提供证明的豁免数据。2. 核心率类指标计算：（1）计算预约未到率：预约未到率＝（预约未到数÷总预约次数）×100%；（2）计算履约率：履约率＝（履约数÷总预约次数）×100%；（3）计算取消预约率：取消预约率＝（取消预约数÷总预约次数）×100%；（4）计算失约率：失约率＝（失约数÷总预约次数）×100%。3.计算各率类指标评分（四舍五入保留两位小数）：（1）履约评分=履约率x40（满分为40分）、（2）预约未到评分=（100%-预约未到率）x20（满分20分）、（3）取消预约评分=（100%-取消预约率）x20（满分20分）、（4）失约评分=（100%-失约率）x20（满分为20分）；4. 建立综合评分与用户等级判定模型：（1）计算综合评分=履约评分+预约未到评分+取消预约评分+失约评分。（2）用户评级：基于医院运营需求及用户管理目标，确定当综合评分 90-100 分，则用户等级为 “A 级（优质）”；当综合评分 80-89 分，则用户等级为 “B 级（良好）”；当综合评分 70-79 分，则用户等级为 “C 级（一般）”；当综合评分 69 分及以下，则用户等级为 “D 级（限制）”。
I. Core Values for Hospital Side: 1. Improve Resource Utilization: Monitor the no-show rate of appointments, and push reminders based on user tiers (double reminders for Tier D users, while preserving rights for Tier A and B users) to reduce the no-show rate and cut down idle time of doctors and medical equipment. 2. Optimize Scheduling Services: Adjust scheduling based on departmental fulfillment rate and cancellation rate (e.g., reserving flexible time slots for the Stomatology Department) to reduce scheduling conflicts and patient complaints. 3. Link to Revenue: Incorporate fulfillment rate and no-show rate into doctor performance assessments, thereby improving the overall fulfillment rate, increasing repeat customer purchases and total revenue. II. User Tier-based Operation Plan (Focus on Service and Priority): - Tier A (90-100 points): ① Appointment Priority: Secure priority access to popular doctors and time slots during peak seasons, and support 1 temporary time adjustment within 7 days per quarter; ② Service Priority: Skip in-store check-in queues, enjoy dedicated customer service support, and receive 1 free oral examination per year. - Tier B (80-89 points): ① Appointment Priority: Book popular time slots within 15 days, and enjoy 1 free time adjustment 24 hours in advance per month without any record; ② Service Priority: Be called ahead of regular users (15 minutes earlier), and receive a 10% discount coupon for teeth cleaning after treatment. - Tier C (70-79 points): ① Appointment Service: Book non-peak time slots, and send 3 reminder notifications before the appointment to avoid missed visits. - Tier D (≤69 points): ① Appointment Service: Book non-popular time slots 7 days in advance, and confirm the appointment via phone after booking to ensure validity. III. Industry Value: Help small and medium-sized medical institutions build standardized user tags instead of relying on manual memory, thereby reducing the no-show rate. Allow indicators such as fulfillment rate to become industry reference standards, assisting institutions to benchmark and optimize their operations, and releasing clinical treatment capacity. Promote hierarchical service in the industry, retain high-quality users, and convert users in need of improvement, achieving dual improvements in service experience and economic benefits. 1. Data Collection and Preprocessing: (1) Data Collection: Collect appointment-related data from the hospital appointment management system, including total number of appointments, number of no-shows, number of fulfilled appointments, number of cancelled appointments, and number of missed appointments (along with relevant statistics). (2) Data Preprocessing: Process the collected raw data by removing invalid entries such as hospital-initiated cancelled appointments, user-submitted unconfirmed appointments, and test orders. Additionally, exclude exempted data where users provide proof of special circumstances such as sudden illness. 2. Calculation of Core Rate-based Indicators: (1) No-show Rate = (Number of no-shows / Total number of appointments) × 100%; (2) Fulfillment Rate = (Number of fulfilled appointments / Total number of appointments) × 100%; (3) Cancellation Rate = (Number of cancelled appointments / Total number of appointments) × 100%; (4) Missed Appointment Rate = (Number of missed appointments / Total number of appointments) × 100%. 3. Calculation of Indicator Scores (rounded to two decimal places): (1) Fulfillment Score = Fulfillment Rate × 40 (full score: 40 points); (2) No-show Score = (100% - No-show Rate) × 20 (full score: 20 points); (3) Cancellation Score = (100% - Cancellation Rate) × 20 (full score: 20 points); (4) Missed Appointment Score = (100% - Missed Appointment Rate) × 20 (full score: 20 points). 4. Establishment of Comprehensive Score and User Tier Determination Model: (1) Comprehensive Score = Fulfillment Score + No-show Score + Cancellation Score + Missed Appointment Score. (2) User Rating: Based on hospital operation needs and user management objectives, the user tier is determined as follows: - "Tier A (Excellent)" for a comprehensive score of 90-100; - "Tier B (Good)" for a comprehensive score of 80-89; - "Tier C (Average)" for a comprehensive score of 70-79; - "Tier D (Restricted)" for a comprehensive score of 69 or below.
