Nursing Informatics, Outcomes, and Quality Improvement

Charters, Kathleen G.

doi:10.1097/00044067-200308000-00003

Cited by 20 publications

(8 citation statements)

References 2 publications

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“…Nursing language development began to standardize the way nurses document patient care activities, and this standardized language allows the comparison of patient populations across various electronic record systems. Analysis of extracted data may lead to quality improvement activities, research, and evidence‐based practice guidelines 3 . A standardized language can measure and describe what nurses do within the larger multidisciplinary context of health care and health care professionals.…”

Section: Statement Of Purpose and Research Questionmentioning

confidence: 99%

“…We recommend that the data elements be added to the PNDS taxonomy. Charters 3 stated that standardized data elements can be used to evaluate the quality and context of perioperative patient care. The elements being added now are not an exhaustive list, and more elements will be added to meet evolving quality measures.…”

Section: Statement Of Purpose and Research Questionmentioning

confidence: 99%

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Validation of the Data Elements for the Health System Domain of the PNDS

Morton¹,

Petersen²,

Chard³

et al. 2013

AORN Journal

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This research study established the data elements for the health system domain in the Perioperative Nursing Data Set. A sample of AORN members were asked to confirm the clarity, necessity, measurability, and accuracy of each proposed data element. As a result of this study, the health system domain contains 114 data elements with definitions. When integrated into an electronic health record, data elements can be used to identify, compare, and evaluate the context in which patient care is delivered across settings.

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Section: Statement Of Purpose and Research Questionmentioning

confidence: 99%

Section: Statement Of Purpose and Research Questionmentioning

confidence: 99%

Validation of the Data Elements for the Health System Domain of the PNDS

Morton¹,

Petersen²,

Chard³

et al. 2013

AORN Journal

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“…Linking these entities together can facilitate planning and evaluation of care so nurses can identify opportunities for quality improvement (Charters, 2003). The same high-quality data set can be used for clinical routine, quality assurance, and outcomes research, thus providing a multipurpose EMR.…”

Section: Orthopaedicsmentioning

confidence: 99%

The Use of Handheld Technology in Nursing Research and Practice

Hardwick

Pulido

Adelson

2007

Orthopaedic Nursing

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Use of handheld devices with electronic patient diaries (EPDs) can improve the quality of patient-reported information collected in clinical and research settings. EPDs have advantages compared with traditional paper-based instruments that include decreased data entry error and decreased time spent on data management. Orthopaedic pain management, which is often dependent on patient-reported pain levels, can benefit from the use of EPDs. A pilot survey was conducted to compare two self-report pain diary methods in shoulder surgery patients: (a) EPD or (b) paper entry. Compliance was lower in the EPD group, which was attributed to insufficient ease of use. Handheld technology can be used by nurses to improve and streamline patient care by capturing clinical data, by organizing and reporting home health services, and by providing references for evidence-based practice. Handheld technology can facilitate the transformation of clinical documentation of assessments, interventions, and outcomes into evidence-based decision making in orthopaedic nursing.

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“…There is also an increased interest in how information techniques can help model and monitor patient health outcomes to improve the quality of care. For example, it has been shown that the findings from computer-driven analyses of patient health outcomes can lead to quality improvement [ 9 ]. Another example of such research analyses has shown that home healthcare agencies which direct their efforts on key risk factors (such as for specific clinical, functional and demographic factors) can help understand and therefore decrease the rate of patients' re-hospitalizations [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

A data mining approach in home healthcare: outcomes and service use

Madigan

Curet

2006

BMC Health Serv Res

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BackgroundThe purpose of this research is to understand the performance of home healthcare practice in the US. The relationships between home healthcare patient factors and agency characteristics are not well understood. In particular, discharge destination and length of stay have not been studied using a data mining approach which may provide insights not obtained through traditional statistical analyses.MethodsThe data were obtained from the 2000 National Home and Hospice Care Survey data for three specific conditions (chronic obstructive pulmonary disease, heart failure and hip replacement), representing nearly 580 patients from across the US. The data mining approach used was CART (Classification and Regression Trees). Our aim was twofold: 1) determining the drivers of home healthcare service outcomes (discharge destination and length of stay) and 2) examining the applicability of induction through data mining to home healthcare data.ResultsPatient age (85 and older) was a driving force in discharge destination and length of stay for all three conditions. There were also impacts from the type of agency, type of payment, and ethnicity.ConclusionPatients over 85 years of age experience differential outcomes depending on the condition. There are also differential effects related to agency type by condition although length of stay was generally lower for hospital-based agencies. The CART procedure was sufficiently accurate in correctly classifying patients in all three conditions which suggests continuing utility in home health care.

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Nursing Informatics, Outcomes, and Quality Improvement

Cited by 20 publications

References 2 publications

Validation of the Data Elements for the Health System Domain of the PNDS

Validation of the Data Elements for the Health System Domain of the PNDS

The Use of Handheld Technology in Nursing Research and Practice

A data mining approach in home healthcare: outcomes and service use

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