Many hospitals and healthcare facilities are pursuing process improvement initiatives to streamline operations and improve the effectiveness of services provided. Some of these initiatives involve applying Lean thinking and other process improvement techniques to reduce waste and non-value adding activity, thereby increasing efficiency and quality.
A key question for healthcare providers is, how should the quality of healthcare services be measured? There are basically three ways.
The first way uses measures of structure to describe input use. Measuring the number of full-time equivalent nurses per hospital bed is an example of a structural measure.
A second way of measuring healthcare quality is to use process measures. Process measures include wait times, medication errors, and the like.
The final way to measure healthcare quality is to use outcome measures. Outcome measures assess the effects of care provided. They include such things as the frequency of hospital-acquired infections, the frequency of surgeries on wrong body parts, etc.
While outcome measures are often used to gauge the quality of hospital services, these measures often have limitations. The data needed to compile such measures is often lacking and, more importantly, adverse outcomes often arise for reasons other than poor quality care. For example, cancer patients vary in their disease staging, and comparing survival outcomes across facilities must take into account these differences. In addition, outcomes measured at a specific point in time may be attributable to factors other than care quality. For example, the mortality rates of heart attack patients following admission to a hospital is not only dependent on the quality of care, but also upon the patient’s condition upon admission and events that may occur following discharge.
The bottom line is that healthcare managers need to carefully consider how they will measure healthcare quality. Because healthcare quality is complex and multi-dimensional. it may be impractical to adequately measure every relevant aspect of quality.
Technological change often takes the form of new methods of producing existing products together with new techniques of organization. These changes can result in greater productivity, giving a firm the ability to increase its ratio of output to input. Thus, the rate of technological change is often measured by changes in productivity. Measuring the impact of technological change, and its resulting impact on productivity, is a key challenge for firms.
In our practice at ALCG, we utilize two key methods for measuring the impact of changes in a firm’s technology. These methods arise from the key insight that any change to a firm’s technology should impact the ratio of output to input. Too often, continuous improvement activities are measured by means that do not reveal how a firm’s underlying productivity has been changed. This usually stems from managers having little or no information about their firm’s production function or factor productivity.
A firm’s production function shows the relationship between the quantities of various inputs per period of time and the maximum quantity of goods that can be produced per period of time. Given the production function for a particular firm, one can calculate the average product of an input and its marginal product. To maximize profit, a firm should utilize the amount of an input that results in making the marginal revenue product equal to the marginal expenditure.
From the production function, we can derive isoquants that show all possible (efficient) combinations of inputs that are capable of producing a particular quantity of output.
Once a firm’s production function is observable, comparison of the production function at two different time can show the amount of technological change that has occurred in the intervening time. If there are only two inputs, capital and labour, and constant returns to scale, the production function at a given time can be captured by a single isoquant. One can then simply look at the position of this isoquant at a later date to see the impact of technological change. The degree to which the isoquant shifts inwards is a measure of the impact of technological change that has taken place.
A second method we often use is to assess the impact of technological change is to measure total factor productivity. Total factor productivity relates changes in output to changes in both labour and capital inputs. The principal advantage of using total factor productivity over labour productivity as a measure is that, unlike the latter, it includes more types of inputs and not just labour alone.
Changes in total factor productivity measure changes in efficiency. because it is important for a firm’s managers to be aware of the extent to which productivity has increased in response to new techniques and methods, total factor productivity can be used over time to measure changes in the efficiency of a firm’s operations.