|Year : 2017 | Volume
| Issue : 3 | Page : 498-500
A study to evaluate resource draining “no shows”
Alok Anil Chand1, Krishna M Kamble1, Ashok K Diwan1, Vijay K Mahobia1, Dipti Anil Chand2
1 Department of Radiation Therapy and Oncology, GMC, Nagpur, Maharashtra, India
2 Department of Internal Medicine, GMC, Nagpur, Maharashtra, India
|Date of Web Publication||31-Aug-2017|
Alok Anil Chand
A-1, Jeevan Jyoti Colony, Clarke Town, Nagpur - 440 004, Maharashtra
Source of Support: None, Conflict of Interest: None
Introduction: Waiting lists are problems that plague all government radiation therapy centers across the country, leading to disease progression, and reduced treatment efficacy. No shows for appointments create artificial access issues, reduce revenues, waste staff time, and negatively affect patient care.
Methodology: A Retrospective analysis of 180 patients, who were given an appointment and were to be started for radiation therapy at the Department of Radiation Therapy and Oncology, at our institute from May 1, 2013 to July 31, 2013, was done. Patients were divided into two Groups; Group A (n = 104, 57.8%) that complied for treatment and Group B (n = 76, 42.2%) that did not comply for treatment on the scheduled date. The Group B (“no shows”) patients were contacted telephonically and were evaluated for the primary reasons for their failure to comply for treatment through a preformed questionnaire.
Results: The mean age, gender distribution and patient's habitat in both the groups were comparable. On Group B analysis, the average waiting period for the appointment was 74 days; 31.4% had died within an average of 31 days; 37.1% said they were better; 10% said their condition was the same; 18.6% said their disease had progressed. Patients were also evaluated for various factors responsible for their not reporting for treatment at the institute.
Conclusion: Better communication and constant reminders between patients and the departmental staff can go a long way in helping to curb the problem of no shows and mitigate the artificial access issues. This would lead to better patient care and better resource utilization.
Keywords: Limited radiation therapy facilities, no shows, waiting list
|How to cite this article:|
Chand AA, Kamble KM, Diwan AK, Mahobia VK, Chand DA. A study to evaluate resource draining “no shows”. J Can Res Ther 2017;13:498-500
| > Introduction|| |
Rising longevity, alterations in lifestyles and progressive control of communicable diseases has led to the emergence of cancer and noncommunicable diseases as an important health problem in India and other developing countries.
The burden of cancer is increasing worldwide. Broadly the main goals of a cancer diagnosis and treatment program are to cure or considerably prolong the life of patients with the best possible quality of life. This requires a careful selection of one or more of the major treatment modalities, that is, surgery, radiation therapy or systemic chemotherapy.
Most developing countries do not have enough radiation therapy facilities and hence have a long waiting period before treatment is started [Figure 1]. This is more so in government setups with large patient loads. This leads to disease progression and reduced treatment efficacy.
Adding to the problem of waiting lists are the patients who fail to show up for their appointments, that is, the “no shows.” The patient does not call or does not cancel the appointment; he or she simply does not show up leaving a gap in the scheduled appointments. This creates an artificial access problem, reduces revenues, wastes staff time, and negatively affects patient care. Contributing to the problem of “no shows” may also be the factor that there is no system of advance payments against the appointment given.
“Most hospitals do not know what their no-show rate is.” Analyzing 3–6 months' data of radiation therapy appointments, hospitals can start to address the root causes of no shows. This would lead to an improvement in the efficiency of treatment delivery. This study of evaluation of resource-draining “no shows” was undertaken with the following aims and objectives:
- To identify various factors contributing to patients not reporting on their scheduled appointment days
- To derive possible solutions that can lead to improvement in the situation.
| > Methodology|| |
It is a retrospective analysis of 180 patients, who were given an appointment and were to be started on radiation therapy from May 1, 2013 to July 31, 2013. Patients were divided into: Group A (n = 104, 57.7%) who “complied” with the prescribed treatment; Group B (n = 76, 42.2%) who “did not comply” with the prescribed treatment on the scheduled date. The Group B (“no shows”) patients were contacted telephonically and were evaluated for the primary reason(s) for their failure to comply with the treatment, through a preformed questionnaire. Statistical analysis was done by calculating percentages and mean ± SD.
| > Results|| |
The compliance rate at our institute was 57.7% (Group A). Both the groups were similar in their age, gender, and disease distribution. 76 patients (Group B) who did not turn up for their appointments were further evaluated. Only 70 patients or their relatives could be contacted telephonically. Six patients of Group B could not be contacted.
Group A patients were not contacted.
Significantly more patients were from a rural habitat in Group B compared to Group A. The average distance between their residence and the institute was significantly more in the case of Group B patients as compared to that of Group A patients.
On Group B analysis: The mean waiting period for the appointment was 74 ± 12.6 days. Of these patients, 22 (31.4%) had died within an average of 31 days, the variation ranging from 9 to 72 days and a median of 27 days. Of the patients who died, 13 (18.5%) were scheduled for palliative radiation therapy and 9 (12.8%) were scheduled for radical radiation therapy. 37.1% said they were better. 10% said their condition was the same. 18.5% said their disease had progressed.
The Group B patients comprised a heterogeneous patient population. Some patients had taken treatment outside and some had not. Hence, they were further divided into Group B1 (n = 28) taking treatment elsewhere and Group B2 (n = 42) not taking treatment elsewhere.
92.8% of patients of Group B1 were feeling better; 3.5% had died and 3.5% said their disease had progressed. None of them said that their condition was same. This was in stark contrast to the Group B2 where the patients were not taking treatment elsewhere. Of these none were feeling better; 54.7% had died and 28.7% said their disease had progressed. 16.6% said that their condition remained the same.
Of the 28 patients in Group B1, the main reason for taking treatment elsewhere in the case of 96.4% was that they had got a delayed appointment; 21.4% reported lodging and boarding problems; 10.7% reported transport problems; 3.5% reported distance problem and 3.5% had an apprehension of government setup.
The literacy rate and financial status of the patients taking treatment outside, that is, Group B1 was significantly better as compared to Group B2. Significantly more patients, who had not taken treatment elsewhere, belonged to a rural habitat. However, the distance from the hospital in the both the groups was comparable.
Of the 42 patients in Group B2 the reasons for not taking treatment was cost factors in 69% cases; lodging and boarding problems in 28.5% cases while 26.1% cases did not understand that taking radiation therapy was important; no family support, transport problems, apprehensions of the side effects of radiation therapy were cited by 9.5% of patients; 9.5% of patients also reported that they had to wait for a long time to see the doctor; 7.1% said that they had a delayed appointment, no rapport with the doctors or the hospital staff and were taking alternative medications. 2.3% had a depressive outlook toward life and had an apprehension of government setup.
However, with all the limitations, of the total 180 patients, 132 that is, 73.3% (overall compliance rate) did receive treatment in government or other setups.
| > Discussion and Conclusion|| |
The global cancer incidence is predicted to double between now and the year 2020 at which time there will be over 20,000,000 new cases diagnosed each year. Majority of these will be in developing countries. Treatment strategies for cancers have evolved mainly during the last 50 years.
Radiotherapy is one of the major modalities of cancer treatment and every alternate cancer patient will require radiation during the course of treatment. By 2020, 70% of the global need for radiotherapy will be in that part of the world currently defined as the developing world.
At present, the treatment machine to population ratio ranges from 12 machines per million in the US to fewer than 0.3 machines per million in China. In India, we have around 290 teletherapy machines spread over 62 cities/towns for a billion population against a requirement of 1059. Together with surgery, radiotherapy currently remains the most cost-effective way of curing cancer.
Patients not turning up (“no shows”) for their scheduled radiotherapy appointments add to the inadequate utilization of the available deficient resources. It has a negative impact on the workflow of the hospital in many ways. Physical and emotional barriers to keeping appointments may account for the “no shows.”
“No shows” also have a negative impact on patient care of those who comply with their appointments, that is, artificial access problem; it eats up the staff time, productivity, and government revenue. Patient's anticipatory fear and anxiety about the procedure, prognosis and finances need to be addressed. We also need to focus on the following points:
- Creating an environment for better communication
- Taking the time to develop a rapport with patients
- Selective early appointments for the needy
- Educating the patients about the benefits of therapy by the departmental staff
- Patient counseling
- Improving workflow to reduce waiting periods
- Setting up reminders and being in touch during the waiting period.,,,
These steps if implemented judiciously can mitigate the problem of “no shows” and will help in curbing the artificial access problem and ultimately will lead to better patient care with better available resource utilization. The only way to fight this scourge under such circumstances is to have pragmatic programs and policies based on currently available scientific information and sound public health principles.
| > Acknowledgments|| |
Dr. Subeera Khan, Dr. Rohit Kabre.
| > References|| |
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