Controlling Variation

How do you control variation to improve outcomes? How might health care administration leaders implement approaches to control for variation for their health services organization?
Within a health services organization different processes and workflows contribute to the overall aim of delivering health services. Not surprisingly, when resources become constrained—for example, with influxes of new patients or even changes in health care policy and law—these changes may result in differences, that is, variation in how these workflows and processes are executed for health care delivery. As a current or future health care administration leader, you may encounter the need to control for variation to maximize the efficiency and effectiveness of health care delivery for your health services organization.’

For this Discussion, reflect on the approaches health care administration leaders may use to control for variation. Then, select a health process or outcome that might benefit from variance reduction and consider how you might measure the effectiveness of variation reduction for this health process or outcome. Reflect on the McWilliams, Chernew, Landon, & Schwartz (2015) article and consider how accountable care organizations (ACOs) may compare in relation to non-ACOs.

 

Sample Solution

Controlling Variation

In health care, quality improvement is the framework used to systematically improve the way care is delivered to patients. Quality improvement entails continuous efforts to achieve stable and predictable process results, that is, to reduce process variation and improve the outcomes of these processes both for patients and the health care organization and system. Reducing unnecessary variation continues to be a hot topic in healthcare. Knowing where and how your organization plans to address variation is key to measurable, sustainable improvement. Steps to successfully reducing clinical variation include: identify opportunity – understand which areas are not meeting benchmarks, and dive into what actions and procedures are driving the variation outcomes; align initiatives; change behavior; and assess outcomes.

protozoa at 4 hrs post feeding were not significant among all groups. The differences of microbial protein were not significant among all groups in the 1st stage. The highest cost value of feed consumption was recorded with control. The daily body gain(DBG) were 156.1, 150.3, 154 and 154.8 gm/h/d for lamb groups which fed rations A, B, C and D respectively and the differences of DBG among four groups were not significant. The best feed conversion and economical efficiency were recorded with ration D. The green forage yield of Sesbania pure, Sesbania-Sorghum mixture and Sesbania-Millet mixture were 10.85, 15.31 and 15.30 ton/feddan, dry yield were 2.22, 3.32 and 3.34 ton/feddan, and crude protein yield were 403, 451 and 478kg/feddan, respectively.
Keywords: Sesbania, Sorghum, Millet, Rams, Lambs, Digestion coefficients, Rumen, DBG, Feed conversion, yield.

INTRODUCTION

The animals suffer from shortage of feed especially during summer season in Egypt. Most of animal feeding in this period depends on concentrate feed mixtures and agricultural residues. The expensive price of energy sources as grains or protein sources as Soybean meal and Cotton seed meal tend to increase feed cost of animals. The green forage is cheap food for ruminant feeding. The most green forages in summer season in Egypt are grasses as Sorghum, Sudan grass and Millet. Grasses have higher yield than legumes, but they are considered poor in quality due to low protein content and essential amino acids, therefore sowing legumes in mixtures with grasses improves the quality of forage by increasing protein content and reducing crude fiber content.

Some practical studies were carried out to utilization some mixtures of le

This question has been answered.

Get Answer
WeCreativez WhatsApp Support
Our customer support team is here to answer your questions. Ask us anything!
👋 Hi, Welcome to Compliant Papers.