A quantification model for home health care nursing visits
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Abstract
Home care managers are faced with an unprecedented challenge to provide quality care at reduced costs at the same time that their case mix is becoming more complex. Since the major expense in home care is nursing labor, improving nursing productivity is a primary method of reducing costs. However, the elements of a home visit have never been defined in such a way that they could be priced appropriately or so that productivity could be measured more precisely than identifying the number of home visits made per day or calculating the average cost per visit.
This exploratory study was designed to develop a quantification model for measuring home visits using three parameters: types of nursing activities, complexity, and time. Through use of interaction analysis, nursing activities were recorded every minute during 75 home visits, made by 26 nurses, in eight agencies. Data analysis revealed (a) a significant relationship between visit time and complexity, suggesting that time is an appropriate unit of measurement for home visits, (b) considerable time variation in a timed task model and an activity/complexity taxonomy, (c) four potentially useful visit profile models, and (d) critical indicators predictive of visit profiles.
The four visit profile models identified through cluster analysis and regression techniques included: (a) visit content clusters based on percentage of visit time utilized in five activity categories, (b) visit clusters based on total visit-related time and complexity, (c) initial/repeat visits by payer, and (d) initial/repeat visit time/complexity clusters. Both of the time/complexity profiles identified clusters of visits with low time and high complexity, suggesting that in spite of the over-all relationship found between visit time and complexity, there are groups of visits where complexity and time are not related.
The major predictors of visit time were found to be initial visits and Medicare reimbursement. Other critical indicators of time, visit profiles, and complexity included: nurse's education; number of health care providers, physician orders, medications, and home health disciplines; visit complexity; client age and sex; agency type; visit frequency; caregiver availability; prior surgery; prognosis; and admission status.
Description
This dissertation has also been disseminated through the ProQuest Dissertations and Theses database. Dissertation/thesis number: 8801424; ProQuest document ID: 303594198. The author still retains copyright.
Repository Posting Date
2020-06-26T22:01:08Z
Notes
This item has not gone through this repository's peer-review process, but has been accepted by the indicated university or college in partial fulfillment of the requirements for the specified degree.
Type Information
Type | Dissertation |
Acquisition | Proxy-submission |
Review Type | None: Degree-based Submission |
Format | Text-based Document |
Category Information
Evidence Level | Case Study/Series |
Research Approach | Quantitative Research |
Keywords | In-home Nursing; Nursing Management; Quality of Care |
Degree Information
Grantor | University of Michigan |
Advisor | Simms, Lillian M. |
Level | PhD |
Year | 1987 |
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