Health care organizations are faced with the challenge of complying to laws and policies that are formulated by the state or federal government to measure their performance matrix, yet, most of the variables that affect this performance matrix are beyond the control of the organization. However, a competent health care firm comprises of a strong leadership team that transcribes the laws and policies into figures that can be integrated into the hospital’s daily activities. These figures are then used to measure the performance of the respective healthcare organization. The Agency for Healthcare Research and Quality (2013) suggests that benchmarking stimulates healthy competition among health care organizations which directly reflects the performance of the different staff in the institution. In this article, different performance matrices shall be discussed in contrast to the national set goals, reviewing some of the challenges that lead to the non-conformities and finally, an ethical proposal of the various ways the problems can be mitigated.
Taking an example of a hypothetical institution that specializes in diabetes and diabetic related conditions, the performance matrices for this institution will be somewhat similar to the ones listed below:
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Number of hospital admissions for uncontrolled diabetes without complications
Number of in-patient cares resulting from diabetic related complications
Number of amputations due to long-term unmanaged diabetic related complications
Number of deaths per 1000 patients admitted with diabetes and diabetic related complications
All these can be represented in figures to the population of interest, which gives percentages and ratios, which can then be contrasted to the national set benchmarks to evaluate the quality. For instance, in the most recent fiscal year of 2017/2018, the institution reported its matrices as follows: out of 100, 000 adults, 12 were admitted in the hospital for uncontrolled sugars without any other medical complications, and 184 adults were admitted due to diabetic related complications. Amputations of extremities due to uncontrolled sugars was at 25 out of 1000, and the death rate was 10 for every 1000 diabetic cases. At face value, these figures look impressive; however, when compared to the national set estimates, gaps can be spotted.
The Agency for Healthcare Research and Quality (2016) reports the corresponding institutional matrices as 12.7, 115.9, 19.3 and 13.2 respectively. Two of the arrays were not met by the institution, suggesting the presence of challenges that hindered the delivery of the services. Commonly reported challenges that affect healthcare systems include: limited resources, this is in terms of staffing and finances and also unforeseen patient characteristics that may facilitate advancement of the morbidities. Such symptoms can consist of, denial, abscondment and also drug nonadherence. Additionally, in rare cases, the stakeholders may overshoot the performance matrix targets due to statistical bias. This can occur in areas where a particular disease is rampant, and statistical conclusions were drawn without acknowledging the prevalence figures.
In terms of staffing as a limitation, Iyiola et al. (2016) affirm that adequate staffing is an essential aspect for any health care organization if quality services are to be provided. The study associates code-blue stress among nurses working in hospitals due to understaffing and overworking, leading to reduced quality of services hence compromised healthcare delivery. In a diabetic institution where patients are admitted due to uncontrolled sugar complications, adequate staffing is vital to meet the needs of the patient such as constant observation, especially in patients diagnosed with diabetic ketoacidosis who require their sugars taken in hourly intervals. Failure to this, the number of inpatient complications will shoot up, leading to morbidities such as amputations and in severe cases, death.
In financial limitations, we think of broad aspects such as specialized equipment purchases. If an institution is poorly financed, the chances are that it will lack the necessary equipment to offer adequate healthcare to its patients, leading to disease progression. Moreover, finances dictate the staffing levels of any institution. Correia, Dussault, and Pontes (2015) conducted a study in three European countries in regards to funds and human resource. The findings were that in countries where the financial crisis was felt, health workforce policies were impaired, leading to understaffing. As initially discussed, understaffing directly correlates with the quality of healthcare services being offered at an institution.
While staffing and financial limitations are within the control of the institution, patient characteristics are not, yet they affect the benchmarking of quality. Diabetes being a terminal condition, some patient may exhibit denial and resistance to change their lifestyle, leading to negative results on the hospital. Pene and Kissane (2019) note that denial in cancer patients has detrimental effects on the treatment regimen, hence necessitating the need for an emotional response as part of the treatment in patients who are terminally ill. Patients in denial will aggravate the condition and become part of the negative statistics, thus affecting the overall institution’s performance quality benchmarks.
Of the four performance matrices of the institution, the number of in-patient cares resulting from diabetic related complications has the most significant potential for improving the overall quality of services. This matrix is the borderline in which the other models are derived. It is the complications of uncontrolled sugars in diabetic patients that lead amputations and in severe cases death. Controlling this matrix for the better outcome will benefit not only the institution but also the community since fewer resources will be used in treating admitted patients. The patients can also lead their healthy lives, hence strengthening the socio-economic structure of the community in which the organization is based.
As a solution to the above-discussed matrix, the steering committee can address the financial constraints the hospital might be facing. Financial constraints do not necessarily mean that the hospital lacks adequate funds; in some cases, spending the available funds inefficiently, leads to the limitations. As initially discussed, finances dictate the staffing level and also the amount of technology at the disposal of an organization. All these directly affect quality, leading to underperformance benchmarks. To alleviate the effects of underperformance benchmarks such as lack of clients and failure to meet the set standards of quality, the stakeholder group is tasked with ensuring the institution has enough funds at its disposal.
To achieve this, the financial officer, together with the team, is responsible for ensuring all the revenue generated is accounted for and efficiently used for the betterment of the institution. Corrupt officials should be done away with to prevent revenue losses due to a few greedy individuals. More so, the human resource department should liaise with the finance team to secure adequate personnel that is within the attainable limits of the organization. Consequently, each staff shall be expected to perform their due task diligently to promote the set goals of the organization. Implementing these measures is a practical way in which the organization can meet its set objectives. Achieving the performance goals will also promote healthy competition among facilities offering similar services, leading to meeting the universal health coverage goal.
References
Agency for Healthcare Research and Quality. (2013, May 28). Module 7. Measuring and Benchmarking Clinical Performance. Retrieved from https://www.ahrq.gov/professionals/prevention-chronic- care/improve/system/pfhandbook/mod7.html
Agency for Healthcare Research and Quality. (2016 ). National Healthcare Quality and Disparities Reports . Retrieved from https://nhqrnet.ahrq.gov/inhqrdr/National/benchmark/table/Diseases_and_Conditions/Dia betes
Correia, T., Dussault, G., & Pontes, C. (2015). The impact of the financial crisis on human resources for health policies in three southern-Europe countries. Health Policy , 119 (12), 1600-1605.
Iyiola, O. O., Osibanjo, A. O., Oyewunmi, A. E., Kehinde, O. J., & Igbinoba, A. O. (2016). Code blue-stress among nurses in a teaching hospital and its effects on healthcare delivery. The Social Sciences , 11 (7), 1312-1317.
Pene, C. T. H., & Kissane, D. (2019). Communication in cancer: its impact on the experience of cancer care: communicating with the angry patient and the patient in denial. Current Opinion in Supportive and Palliative Care , 13 (1), 46-52.
