MEASURING PRODUCTIVITY IN NURSING CARE.

Nursing care process has four components namely, assessment, diagnosis, intervention and evaluation. Nursing process enable nurses to provide holistic evidence-based care to patients and families. Information nursing process equally provides sufficient data to allow nurse managers measure productivity in nursing care. While knowledge of nursing process is high among nurses this has not been applied in measuring productivity in nursing care. This article looks at the role of measuring productivity in establishing the value of nursing care. 

What is measurement? Measurement can be defined as quantifying the value or level of a characteristic in the population. For example hospitals can quantify number of surgical patients developing surgical wound infection post-operative. There are 3 types of measurements; descriptive, diagnostics and predictive. In descriptive one simply describes elements as they are and perhaps assign them into categories. For example number of male and female patients with surgical wound infection post-op. Diagnostic measurement looks at the numbers (descriptive) and provides reason behind the numbers (how). For example, hospital can apply diagnostic measurement to determine why more male patients develop surgical wound infections post-op compared to female patients. Diagnostic measurement simply looks at the trend and seeks to establish reason behind the trends. Predictive measurement applies results from descriptive and predictive measurements in making decisions. For example, if male patients are more prone to surgical wound infection should a detail pre-op screening be done for male patients? Hospitals would apply predictive measurement in making such decisions. Looking at these 3 examples on application of measurements it’s critical to pose and ask if indeed there is sufficient measurement of productivity in nursing care.

Productivity on the other hand is defined as ratio of output vs input. In nursing care, output can include number of patients developing wound infection post-op. Input can be number of nurses per shift, or number of nurses trained on wound care in surgical ward amongst other inputs.

Why is measuring productivity important to nursing as a profession? Healthcare is dynamic and patients continue to demand for quality health-care. The cost of healthcare has increased with hospitals struggling to provide affordable healthcare. Nursing profession needs to demonstrate its value of its services in healthcare and how such services contributes to increased healthcare costs.  By measuring productivity nursing profession can help identify barriers to quality care and factors that increase cost of care. Nurses can also attain quality in care and also improve their level of satisfaction with care they provide. In addition, nurses can identify areas of weakness that need improvements and those areas where good performance is to be sustained.

The importance of measuring productivity in nursing care is more crucial in resource allocation. Nurse Managers can use data in making decision on planning shifts and staff allocation in wards/units. For example, data on number of patients developing post-op wound infections should alert nurse managers to review if nurses posted in surgical ward have received training on infection prevention and wound care.

In measuring productivity there has to be a framework in place. The framework should define what is to be measured, how it will be measured and when it will be measured. But most important is to have a plan on how results from measurement will be used in planning nursing care.  Many hospitals have quality indicators for use in patient care. However, in measuring productivity hospitals need to go beyond quality indicators. They need to consider impact of quality indicators on nursing care and productivity. Let us consider a quality indicator on reducing admission waiting time. A hospital would want to assess if attaining reduced admission waiting time would release more nurses to provide emergency care when needed or does it result in additional workload in the wards.  Using diagnostic and predictive approach nurse managers would then decide on what is the optimum waiting time with minimal impact/disruption on nursing care on both ends.

So if measuring productivity is important to nursing care, have we failed in measuring productivity or have we been measuring productivity without knowing. Both scenarios are true and do exist. In the first scenario nurses have not been measuring productivity and this manifests in shift planning in which only certain nurses continually work on night shift 4 weeks in month without rest. Other manifestations is in prolonged hospital stay among patients and also number of number of nurses reporting late to work in consecutive weeks.  Nurses have been measuring productivity unknowingly for example by assigning young or non-married nurses to work in out-patient emergency while married nurses are posted to work in less intensive areas. But while that has been happening, the question is whether the decision was informed by any data or just mere choice of the nurse manager.

How can nursing profession integrate measuring productivity in routine practice? To achieve and sustain measuring productivity nurse managers need to establish two kinds of database with different variables. The first database is nurse staffing database that contains variables such as age, level of training, work experience, health status, specialized training as well as other anthropometric variables such as height and weight. The second database is the patient data which comes from the hospital management systems.  Using data from the two database nurse managers would then review productivity of nurses against certain patient outcomes. The aim of doing this is not to punish non-performing nurse but to use the information to assign a nurse to an area they are more likely to be productive. By doing so nurse managers can help identify and eliminate barriers to quality nursing are.

Measuring productivity in nursing cannot be achieved if nurse managers are not equipped in use of data for decision making. Nurse Managers need to acquire basic data analysis and interpretation skills. Such skills would help nurse managers review data for trends and make decisions towards measuring productivity which would improve quality of care and also reduce wastage of nursing resources.

Some of the factors that have hindered nursing profession from measuring productivity has somehow been alluded to in the previous sections. However, literature shows that lack of awareness on importance of measuring productivity is the leading reason. It is lack of awareness since data and technology to measure productivity is readily available. In conclusion nurse managers need to take a bold step and begin measuring nursing productivity. Of course there will be obstacles or push-back from different quarters but the reality is that by measuring productivity nurse managers would help demonstrate the value of nursing profession in healthcare.

Emmanuel Owino Ochieng is a Clinical Research professional leading delivery of clinical trials on therapies for treatment and prevention of Malaria and Sickle in Africa. As part of his role Emmanuel drives training of nurses and other health workers on pharmacovigilance and adverse events detection. Emmanuel aspires  to be a leader in use of data driven strategies in delivery of clinical trials, public health programs and healthcare planning. Emmanuel is also passionate about helping local football clubs realise their business worth and value while creating competitive teams.

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