Developing Application Software for Detecting and Documenting Diabetic Foot Complications for Use by Nurses

Abstract

Background

With the increasing number of diabetes cases worldwide, developing application software that detects diabetic foot complications can improve the effectiveness and efficiency of nursing care services, especially in Indonesia.

Objective

This study aimed to compare a software-assisted documentation method to a paper-based method in early diabetic foot complications detection according to documentation time and the accuracy of determining diabetic foot risk factors.

Methods

This study was comprised of two stages, namely application software development with expert test methods and application software testing using a quasi-experimental design. The sample was selected purposively, consisting of documentation data from 80 type-2 diabetes mellitus foot examinations. The data were divided into two groups, namely paper-based documentation data and software-assisted documentation data. The documentation time and accuracy of determining diabetic foot risk factors were analyzed by the Mann-Whitney test and Kappa test at a confidence interval of 95% using SPSS.

Results

There was a significant difference between the software-assisted documentation method and paper-based documentation method in the documentation time (p value < 0.001). The strength index of accuracy shows that the software-assisted documentation was stronger than the paper-based documentation in determining risk factors for diabetic foot complications (1.00 > 0.373).

Conclusion

The software-assisted documentation method was more time-effective in detecting diabetic feet complications and had greater accuracy than the paper-based documentation method.

Introduction

Indonesia ranks among the top 10 countries in the world according to the number of people having diabetes mellitus (DM) (Guariguata et al., 2014). The increasing prevalence of diabetes is a big challenge for the health care system in Indonesia, thus a system that supports prevention efforts, including prevention of DM complications, needs to be developed (Soewondo, Ferrario, & Tahapary, 2013). DM is a global, serious threat that can cause diabetic foot complications. The prevalence of diabetic foot ulcer risk factors is 54%, while the prevalence of diabetic foot ulcers is 12% (Yusuf et al., 2016). There is a significant relationship between the duration of diabetes mellitus and diabetic neuropathy, which contributes to diabetic foot complications (Tarigan, Yunir, Subekti, Pramono, & Martina, 2015). Early diabetic foot detection programs do not work well in developing countries. One reason is that the existing facility for documentation of diabetic foot examinations has yet to apply an information technology approach. This condition is exacerbated by the uneven distribution of diabetic foot clinic services throughout hospitals in Indonesia. Until now, diabetic foot services have only centered on type A hospitals or private hospitals that provide diabetic foot care and education services; these hospitals are usually only in large cities. Some examples of diabetes services have begun to develop with information technology approaches. For instance, mobile phone messages are now used for the prevention and control of diabetes, and mobile technology is used to monitor and help improve nutritional status (Fottrell et al., 2016).

The current model for early detection of diabetic foot complications still relies on conventional methods, namely paper-based documentation. This method has disadvantages, in that it requires a long time to check the history, making it less effective and efficient. which can cause an increase in the queue of patients in diabetes polyclinics, which reduces quality of service. The development of information technology in various fields, including the health sector, is growing quickly. This provides an opportunity for increased assessment expertise in the documentation of technology-based diabetic foot detection, increasing diabetic foot complications visibility and making it easier and faster to draw inferences on the problems in a more precise, accurate manner. This is a form of integration of information technology (IT) applications with nursing practices aimed to support quality of care (Kokol & Vošner, 2017). The development of application software to detect diabetic foot complications will assist hospitals to provide more reliable patient record data. Based on the above-mentioned phenomena, the researchers were interested in developing application software to detect diabetic foot complication early and to help with the nursing documentation process. The purpose of this study was to compare the software-assisted documentation method and the paper-based documentation method in diabetic foot complication early detection according to documentation time and the accuracy of determining diabetic foot risk factors.

Methods

Stage 1: Application Software Development

The documentation of diabetic foot status consisted of 11 parts, namely basic data collection, history check, complications history check, physical examination, vascular examination, neuropathy examination, pedis classification, investigation, risk factors, formulation of foot problems and management. The baseline data assessed included name, gender, date of birth, medical record and diabetes status, education, employment, family income, address, telephone number, body mass index, blood pressure, race/ethnicity, date of entry and length of stay. The history section included type of diabetes, time after diabetes known, type of diabetes drug, smoking history, length of injury, diabetes education history, type of footwear, ulcer cause, ulcer history and amputation history. The history of complications included eye disorders, kidney disorders, coronary heart diseases, stroke, peripheral arterial diseases or hypertension.

In the physical examination, the diabetic foot type, location of abnormalities and changes in the foot skin, toenails, soles and toes were examined. Vascular examination included measurements of dorsalis pedis pulse, posterior tibialis pulse, brachialis pulse, Ankle Brachial Index (ABI) and pulse strength. In the neuropathy examination, 10g monofilament, 128HZ tuning fork and Achilles tendon reflex measurements were carried out. In the pedis examination, peripheral perfusion, wound area, degree of injury, infection and sensation were measured. Data from laboratory result records for the last three months were reviewed for hemoglobin, hematocrit, leukocyte, erythrocyte sedimentation rate, blood glucose, A1C, albumin, globulin, SGPT, total cholesterol, HDL, LDL, triglyceride, albuminuria, urea, creatinine and complete urine test, foot X-ray, microbiological results, chest x-ray and ECG. According to the assessment results, risk factors were classified into four categories: category 0, in which no sensory neuropathy existed; category 1, in which sensory neuropathy with normal ABI existed; category 2, in which sensory neuropathy with signs of vascular diseases and/or foot deformity existed; and category 3, in which history of ulcer or amputation existed. The final results of these foot examinations were determined by the frequency of check-ups, formulation of foot problems, and management. The product of the application software development was subjected to an expert test to align perceptions. The application software development process is shown in Figure 1.

Stage 2: Application Software Testing

This study used a quasi-experimental design with two treatment groups, namely paper-based documentation (control) and software-assisted documentation (intervention). The study used a purposive sample of type 2 diabetes mellitus patients living in select areas of community health centers of some Malang districts. The sample included documentation data from 80 type-2 diabetes mellitus foot examinations. These diabetic foot examinations were performed by health workers who had been trained and declared competent to conduct early detection of diabetic foot complications. Documentation was carried out using the paper-based method and the software-assisted method by two data collectors who previously performed the Kappa test in relation to understanding the inspection parameters. The dependent variables in this study were the documentation time and the risk factors determination accuracy, while the independent variable was the paper-based and software-assisted diabetic foot assessment documentation. The results of the observation were the documentation time and the accuracy of determining diabetic foot complication risk factors. The documentation time was measured by a stopwatch in seconds. Risk factors were divided into four categories. Data were analyzed by the Kappa test to see the accuracy of the results of the software-assisted method and paper-based method compared to expert conclusions. To see differences in the documentation time, the Mann-Whitney U test was carried out with SPSS 20.

Results

Kappa Test to Equate Data Collectors’ Perceptions

Before the data were collected, equalization of perception between researchers and data collectors were conducted. This analysis was carried out to minimize errors in performing the procedures for paper-based and software-assisted documentation of the early detection of DM foot complications. The data were analyzed using the Kappa test. The results of the data analysis in the equation of data collectors' perceptions are shown in Table 1.

According to the Kappa test results, there was no difference in perception between collectors 1 (researchers) and 2, 3 and 4 (data collectors) with a p value of 0,001 and a Kappa coefficient of 1,00. This means that the agreement index between the researchers and the data collectors was very strong. In other words, there was a very strong agreement between the researchers and the data collectors in the early detection of diabetic foot complications.

Documentation Time Difference Test

The next step was to analyze the difference in the documentation time between the software-assisted documentation method and the paper-based documentation method with the Mann-Whitney test. The results showed that there was a significant difference in the documentation time between the two methods (p value <0,001). The data analysis results are shown in Table 2.

Different Accuracy Test in Determining DM Foot Risk Factors

The next step was to measure the accuracy of determining diabetic foot risk factors to see the level of closeness between the paper-based documentation method, software-assisted method and expert conclusions. The results showED that there was no difference in perceptions between the paper-based documentation method, software-assisted documentation method and expert conclusions in measuring and determining the accuracy of diabetic foot risk factors. The Kappa coefficient between experts and software-assisted documentation method was 1,00, which means that the accuracy index was very strong. This indicated that the accuracy between experts and software-assisted documentation method in the early detection of diabetic foot complications was very strong. The Kappa coefficient between experts and paper-based documentation method was 0.373, which means that the accuracy index was not strong enough to be significant. This indicated that there were interpretation errors in the early detection of diabetic foot complications. These analysis results showed that although there were no statistically different perceptions in software-assisted method and paper-based method perceptions, the strength index of accuracy indicate that the software-assisted method was stronger than the paper-based counterpart. The data analysis results of the accuracy in determining DM foot risk factors are shown in Table 3.

Discussion

In the early stages of application software development, conducting an expert test on the application software content is necessary. This testing aims to validate whether the model developed in the system is in accordance with the desired application software standards for detecting diabetic foot complications (Sarma et al., 2016). In this study, the expert test involved a computer field and medical-surgical nursing field as a form of collaborative research with informatics applications in nursing. Expert test activities included expert discussion, system modeling and software analysis results.

Based on this study’s results, the paper-based method took longer than the software-assisted method to complete foot examination documentation. This was due to the paper-based method involving manual processes in the assessment, for example, the calculation of the Ankle Brachial Index (ABI), and in drawing conclusions regarding the risk factors. Meanwhile, in the software-assisted method, modeling was incorporated into an integrated system to make it easy to display and process some procedures in a concise manner, for example in a tabular form. This offered an advantage in terms of accuracy, comfort and alertness of data users (Giordano, 2018). The system modeling showed the relationship between basic data, complications history, physical examination, vascular examination, neuropathy examination, pedis classification, investigation, risk factors, formulation of foot problems and management. In the software-assisted method, the system was automatically able to read and make inferences about the presence of DM foot abnormalities. This made it easy for diabetic foot specialist nurses to detect problems according to correct data input, which increased effectiveness and efficiency. Research on the effectiveness and efficiency of the use of IT in various areas have been carried out in the health sector (Kazi et al., 2017; Maduka, Akpan, & Maleghemi, 2017; Norgan, Okeson, Juskewitch, Shah, & Sukov, 2017; Oza et al., 2017).

According to the results of this study, the index of accuracy in detecting diabetic foot risk factors using the software-assisted method was stronger than using the paper-based method. This information can be useful for improving the quality of nursing care in early detection of diabetic foot disorders in many ways: for example, in improving the efficiency in the transcription and documentation processes, minimizing repetition of examinations, streamlining the administration system, improving communication, reducing medical errors in therapy provision, cutting administrative costs, guaranteeing document reports, helping establish nursing diagnoses and therapies, and increasing data security. Therefore, the provision of training to nurses on how to use software to detect diabetic foot complications can improve the quality of nursing care.

Several studies show that nurses who were given IT training were able to improve their professional practices, and in turn, enhance the quality of nursing care and the ability to communicate (Ahmad, Musallam, & Allah, 2018). Providing high quality services can improve patient safety (Lee, Sun, Kou, & Yeh, 2017; Ten Haken, Ben Allouch, & van Harten, 2018). The use of the diabetic foot complications detection software is expected to improve the quality of nursing care for the early detection of diabetic foot disorders. Online-based health assessment development is currently in high demand. Therefore, the development of application software as a means to detect diabetic foot complications is deemed fitting and is in line with the role of nurses as part of the development of informatics in the field of nursing. According to Lee (2017), the roles of nurses in nursing informatics include planning, analysis, design /development/ revision, and implementation/ assessment/ support/ maintenance. The development of diabetic foot detection application software strongly supports the role of nurses in developing the field of informatics.

Conclusion

According to the results of this study, there was a significant difference in the effectiveness of the software-assisted documentation method and paper-based documentation method in the early detection of diabetic feet complications according to documentation time and the accuracy of determining DM foot risk factors. There was no difference in perceptions between experts, the software-assisted method and the paper-based method in the early detection of diabetic feet complications, but the index of accuracy shows that the software-assisted method was better than the paper-based method in identifying risk factors for diabetic foot complications. Further research needs to be carried out on a broader scale to improve diabetes services in an integrated manner.

Acknowledgment

I would like to express my gratitude to the heads of community health centers of Malang districts for helping with the licensing for this research.

Funding

This work was supported by the Institution of Research and Community Service, Faculty of Medicine, Universitas Brawijaya, Malang, Indonesia.

Citation: Kristianto, H., Waluyo, A., Gayatri, D., Cholissodin, I., Adhitama Putra, V., Supriati, L. & Ahsan, A. (Summer, 2019). Developing Application Software for Detecting and Documenting Diabetic Foot Complications for Use by Nurses. Online Journal of Nursing Informatics (OJNI), 23(2).  Available at http://www.himss.org/ojni

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