發(fā)布時間：2018-05-19 04:19

  本文選題：癥狀監(jiān)測 + 數(shù)據(jù)質(zhì)量　； 參考：《昆明醫(yī)科大學》2017年碩士論文

【摘要】：[背景]云南傳染病具有疾病譜廣、發(fā)病率高、危害嚴重、控制困難的特點。云南省西南部與緬甸、老撾、越南三國相鄰,經(jīng)貿(mào)往來頻繁,存在傳染病跨境傳播、引發(fā)突發(fā)公共衛(wèi)生事件的風險。為提高云南邊境地區(qū)傳染病暴發(fā)或流行的早期預警能力,云南省疾病預防與控制協(xié)同創(chuàng)新中心創(chuàng)建了“云南省邊境地區(qū)癥狀監(jiān)測預警防控體系開發(fā)與應用”項目。[目的]1.描述勐臘縣醫(yī)療機構“云南邊境地區(qū)癥狀監(jiān)測預警防控體系”的建立過程;2.評價2016年勐臘縣醫(yī)療機構監(jiān)測點“云南邊境地區(qū)癥狀監(jiān)測系統(tǒng)平臺”搜集的數(shù)據(jù)質(zhì)量;3.找出影響數(shù)據(jù)質(zhì)量的相關因素,提升數(shù)據(jù)質(zhì)量,為及時準確預警提供數(shù)據(jù)支持。[方法]通過專家咨詢法,選定監(jiān)測地點,確定癥狀監(jiān)測系統(tǒng)的目標疾病與目標癥狀,并建立了云南邊境地區(qū)癥狀監(jiān)測數(shù)據(jù)收集平臺。采用整群抽樣和目的抽樣的方法在勐臘縣抽取80家醫(yī)療機構作為監(jiān)測點,連續(xù)一年收集患者主訴癥狀并進行質(zhì)量控制,報告至云南邊境地區(qū)癥狀監(jiān)測數(shù)據(jù)收集平臺。從不同級別醫(yī)療機構及時間序列方面描述數(shù)據(jù),從完整性、及時性、準確性方面評估數(shù)據(jù)質(zhì)量;采用自行設計的調(diào)查表對數(shù)據(jù)收集者開展數(shù)據(jù)質(zhì)量影響因素的調(diào)查。[結果]選定勐臘縣作為監(jiān)測地點,確定16種目標疾病與14種目標癥狀作為監(jiān)測對象。從整體來看,系統(tǒng)平臺共收集到監(jiān)測癥狀患者記錄數(shù)227007條,其中及時報告數(shù)204228條,達89.96%;零報數(shù)2401條,占1.06%;遲報數(shù)20378條,占8.98%。從機構級別來看,縣級醫(yī)療機構數(shù)據(jù)報告質(zhì)量優(yōu)于鄉(xiāng)鎮(zhèn)衛(wèi)生院,鄉(xiāng)鎮(zhèn)衛(wèi)生院報告質(zhì)量顯著優(yōu)于村衛(wèi)生室。其中縣級監(jiān)測點完整性為98.59%,及時報告天數(shù)比率96.91%,及時報告例數(shù)比率97.95%,準確率93.33%;鄉(xiāng)鎮(zhèn)監(jiān)測點完整性為97.43%,及時報告天數(shù)比率95.32%,及時報告例數(shù)比率96.98%,準確率89.67%;村級監(jiān)測點完整性為54.70%,及時報告天數(shù)比率64.36%,及時報告例數(shù)比率78.02%,準確率87.25%;而在時間序列的分布上,監(jiān)測點數(shù)據(jù)報告質(zhì)量隨著時間推移逐步提高并逐漸穩(wěn)定,且每次督導過后數(shù)據(jù)完整性、及時性均升高。影響報告數(shù)據(jù)完整性的因素包括單位級別、日均門診量,影響數(shù)據(jù)及時性的因素包括日均門診量,報告員學歷、日均報告例數(shù)與每個單位參加癥狀監(jiān)測的人數(shù)。[結論]:從系統(tǒng)1年的運行情況來看,在云南邊境地區(qū)醫(yī)療機構中建立癥狀監(jiān)測系統(tǒng)是可行的�？h鄉(xiāng)醫(yī)療機構報告的數(shù)據(jù)質(zhì)量在完整性、及時性和準確性方面均達到較高水平,而村衛(wèi)生室存在的問題較多。提高數(shù)據(jù)質(zhì)量,需要加強對村衛(wèi)生室的管理,根據(jù)需要根據(jù)影響因素做出相應調(diào)整,并加強督導力度。
[Abstract]:Background: Yunnan infectious diseases have the characteristics of wide disease spectrum, high incidence, serious harm and difficult control. The southwest of Yunnan Province is adjacent to Burma, Laos and Vietnam, with frequent economic and trade exchanges, and there is a risk of cross-border spread of infectious diseases, which may trigger public health emergencies. In order to improve the ability of early warning of infectious disease outbreak or epidemic in Yunnan border area, Yunnan Provincial Cooperative Innovation Center for Disease Prevention and Control has established the project "Development and Application of symptom Monitoring, early warning and Control system in Yunnan Border area". [objective] 1. This paper describes the establishment process of Yunnan border area symptom monitoring, warning, prevention and control system for medical institutions in Mengla County. Evaluation of the 2016 Mengla County medical institutions monitoring point "Yunnan Border area symptom Monitoring system platform" collected data quality. Find out the relevant factors that affect the data quality, improve the data quality, and provide data support for timely and accurate early warning. [methods] the target disease and the target symptom of the symptom monitoring system were determined by the method of expert consultation, and the data collection platform of symptom monitoring in Yunnan border area was established. Cluster sampling and objective sampling were used to select 80 medical institutions in Mengla County as monitoring points. The main symptoms of patients were collected and quality control was carried out for one consecutive year, which was reported to the data collection platform of symptom monitoring in Yunnan border area. It describes the data from different levels of medical institutions and time series, evaluates the data quality from the aspects of completeness, timeliness and accuracy, and carries out a survey of the factors affecting the data quality of the data collectors by using a self-designed questionnaire. [results] Mengla County was selected as surveillance site, 16 target diseases and 14 target symptoms were selected as surveillance objects. As a whole, the system platform collected a total of 227007 records of patients monitoring symptoms, including 204228 reports in time, up to 89.96; 2401 reports in zero, accounting for 1.06; 20378 late reports, 8.98. From the level of organization, the data reporting quality of county-level medical institutions was better than that of township health centers, and the quality of township health centers was significantly better than that of village clinics. The integrity of county level monitoring points is 98.59, the rate of timely reporting days is 96.91, the timely reporting rate is 97.95 and the accuracy rate is 93.33; the integrity of township monitoring points is 97.43; the rate of timely reporting days is 95.32; the timely reporting number ratio is 96.98; the accuracy rate is 89.67; The integrity of the point is 54.70, the ratio of the number of days reported in time is 64.36, the ratio of the number of cases reported in time is 78.02, the accuracy rate is 87.25; but in the distribution of the time series, The quality of monitoring data report is improved and stabilized with time, and the data integrity and timeliness are improved after each supervision. The factors affecting the integrity of the report data include the unit level, the daily average number of outpatients, the factors affecting the timeliness of the data, including the daily average number of outpatients, the degree of the rapporteur, the number of daily reports and the number of patients participating in the symptom monitoring in each unit. Conclusion: it is feasible to establish the symptom monitoring system in the medical institutions of Yunnan border area from the operation of the system for one year. The quality of data reported by county and township medical institutions reached a higher level in terms of completeness, timeliness and accuracy, while there were more problems in village clinics. To improve the data quality, we should strengthen the management of village clinics, adjust according to the influence factors, and strengthen the supervision.
【學位授予單位】：昆明醫(yī)科大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R181.8

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