thoughts about 病歷

對於病歷的看法，除了內容之外，還有對病歷的態度
在繁忙的治療工作之下，許多治療師把寫病歷這件事情當作重複性的routine，當作應付健保的requirement
但是，事實真的應該是如此嗎？

試想一天的工作中，治療師們花了多少時間在書寫病歷？
佔了工作的百分之多少？
你讓下一位治療師得到多少資訊可以真正幫助治療師來幫助個案？

我的工作經驗裡，是非常喜歡讀病歷的
有詳細的記錄，我不但拼湊出我必須知道的醫療的訊息，瞭解了「病」「障礙」」「困難」...可以讓我apply group level的專業知識，解決部分的難題．
甚至，可以拼湊出這個「人」，讓我用ＯＴ柔軟的心和以職能為主的中心思想，apply my knowledge to individual differences來真正提出有用的、有意義的建議來讓個案進入有功能的下一人生階段
我甚至在病歷當中學習到其他治療人員的策略及技巧，增加我自己專業知識的深度和廣度

若沒有詳細的紀錄，在治療的接力賽中，下一棒要花更長更久的時間，才能再度進入治療的狀況之中，其實長遠來看，真的是資源的浪費．

可惜，一份好的病歷，需要時間的投入，在緊迫的工作時間裡，如何取得平衡，實在是一大考驗．
直在是需要良好的病歷工具（不僅僅是評估工具）才能讓臨床人員做出有品質的病歷．

若你知道你的病歷真的有人在看，認真的在讀．你會改變你對病歷書寫紀錄的態度嗎？

Using a post-hoc power analysis, the study is slightly underpowered using cutoff of .80. Effect size is small.

reviewer的意見:

Power: Using a post-hoc power analysis, the study is slightly underpowered using cutoff of .80. Effect size is small.


回應:
Response:
  Cohen recommended to set the type I error α as 0.05 and type II error β as 0.2 (i.e. power=0.8) to present the acceptable possibility of type I and type II error. In our study, we used the data of the 157 patients who completed both the admission and discharge assessments and found effect size of the PDT was 0.4. Using the post-hoc power analysis with set value of type I error α = 0.05, we found that the power was 0.99 (i.e. type II error=0.01) in our study. So the possibilities of making an inferential mistake would be low.

Table 2. Convergent validity, predictive validity, and responsiveness of the PDT

reviewer's comment:

a. The authors present findings only associated with very restricted hypotheses. They often explain only significant findings, without exploring those that are null or not significant. It would be helpful if all data analyzed was presented, e.g., all correlations among variables, at each time point. This allows for more clear interpretation of positive findings and the relationship among variables. The lack of transparency confidence in presented results

以表格回應

Table 2. Convergent validity, predictive validity, and responsiveness of the PDT 

table for demographic data

Characteristic	Patients Who only Completed the Admission, Assessment (n=209)	Patients Who Completed the Admission and Discharge Assessment (n=157)	Patients Who Completed the Admission, Discharge, and One-year follow up Assessment (n=94)
	n (%), Mean ± SD
Sex
Male	134 (64%)	104 (66%)	60 (64%)
Female	75 (36%)	53 (34%)	34 (36%)
Age (years)	65.6 ± 12.8	61.76 ± 13.9	61.1 ± 14.0
Stroke type
Cerebral hemorrhage	72 (34%)	59 (38%)	36 (38%)
Cerebral infarction	137 (66%)	95 (62%)	58 (62%)
Affected side
Right	109 (52%)	80 (51%)	52 (55%)
Left	93 (45%)	72 (46%)	41 (44%)
Bilateral	7 (3%)	5 (3%)	1 (1%)
Days from onset to admission assessment	21.4 ± 18.0	23.0 ± 20.3	23.4 ± 23.2
Days from onset to discharge assessment	56.9 ± 51.1	51.8 ± 23.9	50.6 ± 25.5
Days of rehabilitation ward stay	33.12 ± 16.2	33.1 ± 14.81	31.2 ± 13.0
Admission PDT score	5.8 ± 2.1	5.9 ± 1.9	5.8 ± 2.0
Admission BI score	36.4 ± 19.7	36.5 ± 20.2	37.9 ± 18.6
Admission MMSE score	20.4 ± 7.8	20.5 ± 7.5	20.4 ± 7.8
Discharge PDT score	N/A	6.6 ± 2.0	6.6 ± 2.2
Discharge BI score	N/A	75.3 ± 19.9	77.1 ± 18.1
Discharge MMSE score	N/A	23.5 ± 6.2	23.2 ± 6.7
One-year follow-up BI score	N/A	N/A	87.5 ± 24.0

PDT change score 與 MMSE change score 與 BI change score 的 相關

external responsiveness of the PDT

Pearson 相關係數, N = 157 Prob > |r| (位於 H0 底下): Rho=0
	changePDT
chageMMSE	0.35518
	0.00002
changeBI	0.31089
	0.0002