背景：台灣健保署於2015年開始要求醫療院所上傳檢驗結果資料，可以加值原本申報資料國際疾病分類編碼不準確與缺乏嚴重度資訊的限制。但是，健保署上傳規定持續改變，且無上傳檢驗結果資料品質相關資訊。
目的：一、比較月批次上傳與日即時上傳資料格式差異與改變。二、檢視逐年不同醫療院所層級別上傳完整性。三、評估變項內容符合變項名稱的合理可接受程度。四、分析不同醫院上傳方式之改變與內容。
方法：本研究是全人口描述性研究，擷取2015至2021年每年12月高屏業務組轄區醫療院所上傳「醫令代碼」為血清肌酸酐檢驗結果。首先計算不同年代上傳完整性，分子是檢驗結果上傳數目，分母是該檢驗項目的申報數目。接著針對「檢體採檢方法來源類別」與「檢驗項目名稱」進行檢視內容是否合理可接受。第三選擇18家醫院，進行不同條件的比對，探討月批次上傳與日即時上傳資料內容的差異。
結果：一、關於兩種上傳方式格式差異，月批次有收載醫療費用申報欄位，日即時多了健保IC卡就醫資料內容，部分實驗室檢驗欄位名稱及型態有差異。二、不同層級別醫療院所逐年上傳完整性，在月批次資料中，醫學中心從2015年至2021年皆100%上傳，區域及地區醫院在2016至2018年是100%，但是在2019年下降至58%與52%，2021年是72%與49%。主要原因是從2019年至2021年所有醫院都100%改為日即時上傳。診所日即時上傳由2019年的33%增加至2021年的75%。三、「檢體採檢方法/來源/類別」共134種內容形式，經人工判定內容符合血液合理可接受率在醫中，區域，地區，診所2016年分別是99.96%，99.90%，93.90%，100.00%，2021年分別是99.95%，99.97%，99.99%，94.83%。「檢驗項目名稱」有440種形式，經人工判定名稱符合血清肌酸酐合理可接受率在醫中，區域，地區，診所2016年分別是100.00%，98.55%，99.64%，100.00%，2021年分別是99.87%，99.79%，99.46%，99.96%。四、18家醫院上傳型態可將其歸為「突然轉型」（3家區域醫院）與「漸進轉型」（3家醫學中心及12家區域醫院）兩類。三家醫學中心在2021年以月批次上傳數為分母，與日即時上傳沒有交集數為分子的比例分別是1.08%，6.69%，2.98%。反之，以日即時上傳數為分母，與月批次上傳沒有交集數為分子的比例分別是19.49%，14.51%，16.07%。
結論：健保署2015年開始要求上傳檢驗結果，以申報血清肌肝酸數目為分母檢視完整性，由2015至2021年不同層級醫院上傳完整性都達100%，惟基層醫療院所上傳完整性到2021年還不到八成。由於沒有標準化申報格式，不同醫院上傳內容有相當大差異，但是經人工判斷合理可接受程度也都高達99%。月批次上傳與日即時上傳資料大多重疊，但是還是有少部分各自獨有資料，使用者應該都要採用。

Background: National Health Insurance Administration requested contracted hospitals and clinics to upload laboratory results data in 2015. However, the regulations on upload changed afterward and little is known on the quality of uploaded laboratory results data.
Objectives: This study had four objectives: First, to check the differences and changes in the formats of monthly batch and daily real-time upload. Seconds, to examine the completeness of upload by different level of hospitals and clinics from 2015 to 2021. Third, to assess the acceptability of the content with the variable name. Lastly, to evaluate the changes in number uploading by two methods in different hospitals.
Methods: This population-based descriptive study first extracted order code of the serum creatinine from laboratory results database of December from 2015 to 2021 in each hospital and clinics in Kaohsiung, Pingtung and Penghu. We then manually checked the INSPECT MODE and then ASSAY ITEM NAME to determine whether the contents were acceptable. Thirdly, we used 12 key variables to examine the mapping between the monthly batch and daily upload data in 18 hospitals.
Results: First, the format difference, the monthly batches uploads include the claim data, while daily real-time uploads can link to health insurance Card. Second, the completeness rate of monthly batch uploads in medical centers were 100% throughout the study years. For regional and district hospitals, the completeness rate was 100% from 2016 to 2018 and declined to 58% and 52%, respectively in 2019 and 72% and 49%, respectively in 2021. The main reason of the changes was that most hospitals changed to daily upload method. The completeness rates in clinics using daily upload method was 33% in 2019 and increased to 75% in 2021. Third, there were 134 forms for INSPECT MODE and 440 forms of ASSAY ITEM NAME with an acceptable rate of 85% and 75%, respectively. Fourth, the uploading patterns of 18 hospitals can be classified into two categories: “sudden transformation” and “gradual transformation”.
Conclusions: By 2021, the completeness rate of uploads in clinics was still less than 80%. About 99% of the contents were acceptable. Most of the monthly batch uploads and daily real-time uploads data overlap, but there were still some data existed in only one uploaded dataset, therefore the users of these data should use both uploaded methods.

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