Nursing Practice Problem and PICOT Question

Research Critiques and PICOT Statement Final Draft
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Institution
Nursing Practice Problem and PICOT Question
The use of electronic health records plays a significant role in enhancing diagnosis and patient outcomes. As a health worker, proper documentation improves diagnosis, reduces medical errors, and facilitates positive patient outcomes. Hospitals rely on medical information and patient's personal information to deliver treatment. Lack of proper sharing and recording information would lead to medical errors, prompting patient readmission. PICOT question: In a population of patients treated in hospitals (P) with Electronic Health Records (HER) (I) compared to non-HER hospitals (C), what is the prevalence of readmission rates (O) measured over one year period (T).
Quantitative Studies
Background
The first study of the quantitative research appraisal, A Public-Private Partnership Develops and Externally Validates A 30-Day Hospital Readmission Risk Prediction Model. In the Online Journal of Public Health Informatics, the researchers assessed the efficiency of electronic health records in predicting readmission risk. The research was carried out by advocate health care in Chicago and Cerner. The researchers conducted a systematic review to evaluate the performance of prediction models used to assess hospital readmission risk. The problem to be solved was the poor performance of prediction models for hospital readmission risk (Chaudhry, Li, Davis, Erdmann, Sikka & Sutariya, 2013). The research focused on establishing effective hospital readmission risk prediction models for admission and before discharge.
Moreover, the study also aimed at assessing the performance of prediction models using key metrics. The research question was, How efficient are the prediction models used in hospital readmission risk? (Chaudhry et al., 2013). The research question is significant to nursing since it helps identify gaps within the management of population risk. Integration of effective prediction models in EHR's is a step towards ensuring low readmission rates.
In the second quantitative study, Relationship Between Hospital Performance Measures and 30-Day Readmission Rates, the research focused on "Examining the relationship between computerized physician order entry scores medication reconciliation scores and 30-day readmission rates" (Carter, 2016). Therefore, the research aimed to investigate whether the use of EHR impacted medication reconciliation and readmission rates. The research problem was the occurrence of medical errors during prescription, which lead to patient readmission within 30 days of discharge. The research question was, "What is the relationship between computerized physician order entry scores, medication reconciliation scores, and 30-day readmission rates? (Carter, 2016)" The research question related to the study's problem was essential to help hospital leaders improve business performance and mitigate financial losses.
Article Support
In the first article, the quantitative study relates to the PICOT question. It applies readmission models to identify patients eligible for interventional measures; hence reducing readmission rates proves that EHRs are useful. In the second article, the qu...