M

Mpho Ratshikana-Moloko

University of the Witwatersrand

ORCID: 0000-0001-5943-3562

Publishes on Palliative Care and End-of-Life Issues, Cancer survivorship and care, Patient Dignity and Privacy. 18 papers and 174 citations.

18Publications
174Total Citations

Is this you? Claim your profile.

Add your photo, update your bio, and get notified when your ranking changes.

Top publicationsby citations

Illness Understanding and End-of-Life Care Communication and Preferences for Patients With Advanced Cancer in South Africa
Megan Johnson Shen, Holly G. Prigerson, Mpho Ratshikana-Moloko et al.|Journal of Global Oncology|2018
Cited by 36Open Access

PURPOSE: The understanding of patients with cancer of their condition and their wishes regarding care as they approach end of life (EoL) have been studied more in high-income countries than in low- and middle-income countries (LMICs). PATIENTS AND METHODS: Data were analyzed from a cohort study (N = 221) of patients with advanced cancer who were recruited from a palliative care center in Soweto, South Africa (LMIC), between May 2016 and June 2017. Patients were asked about their understanding of their illness, estimated life expectancy, EoL care communication, and EoL care preferences. RESULTS: Only 13 patients (5.9%) acknowledged that they were terminally ill; nine patients (4.1%) estimated accurately that they had months, not years, left to live. A total of 216 patients (97.7%) reported that they had not had an EoL care discussion with their physician, and 170 patients (76.9%) did not want to know their prognosis even if the doctor knew it. Most patients preferred comfort care (72.9%; n = 161) to life-extending care (14.0%; n = 31), and did not want to be kept alive using extreme measures (80.5%; n = 178) or have their doctors do everything possible to extend their lives (78.3%; n = 173). Finally, 127 patients (57.5%) preferred to die at home, and 51 (23.1%) preferred to die in the hospital. Most patients (81.0%; n = 179) had funeral plans. CONCLUSION: South African patients demonstrated less awareness of the fact that they were terminally ill, were less likely to have discussed their prognosis with their doctor, and more strongly preferred comfort care to life-extending EoL care than US and other LMIC patients in prior research. These differences highlight the need for culturally appropriate, patient-centered EoL care for South African patients with advanced cancer as well as to determine individual preferences and needs in all EoL settings.

Consensus study on the health system and patient-related barriers for lung cancer management in South Africa
Cited by 23Open Access

BACKGROUND: Lung cancer is the highest incident cancer globally and is associated with significant morbidity and mortality particularly if identified at a late stage. Poor patient outcomes in low- and middle-income countries (LMIC's) might reflect contextual patient and health system constraints at multiple levels, that act as barriers to prevention, disease recognition, diagnosis, and treatment. Lung cancer screening, even for high-risk patients, is not available in the public health sector in South Africa (SA), where the current HIV and tuberculosis (TB) epidemics often take precedence. Yet, there has been no formal assessment of the individual and health-system related barriers that may delay patients with lung cancer from seeking and accessing help within the public health care system and receiving the appropriate and effective diagnosis and treatment. This study aimed to derive consensus from health-system stakeholders in the urban Gauteng Province of SA on the most important challenges faced by the health services and patients in achieving optimum lung cancer management and to identify potential solutions. METHODS: The study was undertaken among 27 participant stakeholders representing clinical managers, clinicians, opinion leaders from the public health sector and non-governmental organisation (NGO) representatives. The study compromised two components: consensus and engagement. For the consensus component, the Delphi Technique was employed with open-ended questions and item ranking from five rounds of consensus-seeking, to achieve collective agreement on the most important challenges faced by patients and the health services in achieving optimal lung cancer management. For the engagement component, the Nominal Group Technique was used to articulate ideas and reach an agreement on the group's recommendations for solution strategies and approaches. RESULTS: Public health sector stakeholders suggested that a lack of knowledge and awareness of lung cancer, and the apparent stigma associated with the disease and its risk factors, as well as symptoms and signs, are critical to treatment delay. Furthermore, delays in up-referral of patients with suspected lung cancer from district health care level were attributed to inadequate knowledge arising from a lack of in-service training of nurses and doctors regarding oncologic symptoms, risk factors, need for further investigation, interpretation of x-rays and available treatments. At a tertiary level, participants suggested that insufficient availability of specialised diagnostic resources (imaging, cytological and pathological services including biomolecular assessment of lung cancer), theatres, cardiothoracic surgeons, and appropriate therapeutic modalities (chemotherapeutic agents and radiation oncology) are the main barriers to the provision of optimal care. It was suggested that a primary prevention programme initiated by the government that involves private-public partnerships may improve lung cancer management nationally. CONCLUSIONS: Considerable barriers to the early identification and treatment of lung cancer exist. Finding solutions to overcome both individual and health-system level obstacles to lung cancer screening and management are vital to facilitate early identification and treatment, and to improve survival. Furthermore, research on inexpensive biomarkers for asymptomatic disease detection, the introduction of diagnostic imaging tools that utilise artificial intelligence to compensate for inadequate human resources and improving clinical integration across all levels of the healthcare system are essential.