scholarly journals Using Mobile Health to Support Clinical Decision-Making to Improve Maternal and Neonatal Health Outcomes in Ghana: Insights of Frontline Health Worker Information Needs

10.2196/12879 ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. e12879 ◽  
Author(s):  
Hannah Brown Amoakoh ◽  
Kerstin Klipstein-Grobusch ◽  
Diederick E Grobbee ◽  
Mary Amoakoh-Coleman ◽  
Ebenezer Oduro-Mensah ◽  
...  
Keyword(s):  
Decision Making ◽  
Health Outcomes ◽  
Health Worker ◽  
Mobile Health ◽  
Information Needs ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Neonatal Health ◽  
Maternal And Neonatal Health

scholarly journals Using Mobile Health to Support Clinical Decision-Making to Improve Maternal and Neonatal Health Outcomes in Ghana: Insights of Frontline Health Worker Information Needs (Preprint)

2018 ◽  
Author(s):  
Hannah Brown Amoakoh ◽  
Kerstin Klipstein-Grobusch ◽  
Diederick E Grobbee ◽  
Mary Amoakoh-Coleman ◽  
Ebenezer Oduro-Mensah ◽  
...  
Keyword(s):  
Decision Making ◽  
Health Outcomes ◽  
Information Needs ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Time Of Day ◽  
Neonatal Health ◽  
Facility Type ◽  
Maternal And Neonatal Health ◽  
The Relationship

BACKGROUND Developing and maintaining resilient health systems in low-resource settings like Ghana requires innovative approaches that adapt technology to context to improve health outcomes. One such innovation was a mobile health (mHealth) clinical decision-making support system (mCDMSS) that utilized text messaging (short message service, SMS) of standard emergency maternal and neonatal protocols via an unstructured supplementary service data (USSD) on request of the health care providers. This mCDMSS was implemented in a cluster randomized controlled trial (CRCT) in the Eastern Region of Ghana. OBJECTIVE This study aimed to analyze the pattern of requests made to the USSD by health workers (HWs). We assessed the relationship between requests made to the USSD and types of maternal and neonatal morbidities reported in health facilities (HFs). METHODS For clusters in the intervention arm of the CRCT, all requests to the USSD during the 18-month intervention period were extracted from a remote server, and maternal and neonatal health outcomes of interest were obtained from the District Health Information System of Ghana. Chi-square and Fisher exact tests were used to compare the proportion and type of requests made to the USSD by cluster, facility type, and location; whether phones accessing the intervention were shared facility phones or individual-use phones (type-of-phone); or whether protocols were accessed during the day or at night (time-of-day). Trends in requests made were analyzed over 3 6-month periods. The relationship between requests made and the number of cases reported in HFs was assessed using Spearman correlation. RESULTS In total, 5329 requests from 72 (97%) participating HFs were made to the intervention. The average number of requests made per cluster was 667. Requests declined from the first to the third 6-month period (44.96% [2396/5329], 39.82% [2122/5329], and 15.22% [811/5329], respectively). Maternal conditions accounted for the majority of requests made (66.35% [3536/5329]). The most frequently accessed maternal conditions were postpartum hemorrhage (25.23% [892/3536]), other conditions (17.82% [630/3536]), and hypertension (16.49% [583/3536]), whereas the most frequently accessed neonatal conditions were prematurity (20.08% [360/1793]), sepsis (15.45% [277/1793]), and resuscitation (13.78% [247/1793]). Requests made to the mCDMSS varied significantly by cluster, type of request (maternal or neonatal), facility type and its location, type-of-phone, and time-of-day at 6-month interval (P<.001 for each variable). Trends in maternal and neonatal requests showed varying significance over each 6-month interval. Only asphyxia and sepsis cases showed significant correlations with the number of requests made (r=0.44 and r=0.79; P<.001 and P=.03, respectively). CONCLUSIONS There were variations in the pattern of requests made to the mCDMSS over time. Detailed information regarding the use of the mCDMSS provides insight into the information needs of HWs for decision-making and an opportunity to focus support for HW training and ultimately improved maternal and neonatal health.

Partnerships with Patients: The Pros and Cons of Shared Clinical Decision-Making

1997 ◽  
Vol 2 (2) ◽  
pp. 112-121 ◽  
Author(s):  
Angela Coulter
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Information Needs ◽  
Clinical Decision Making ◽  
Treatment Options ◽  
Clinical Decision ◽  
Treatment Decisions ◽  
Medical Decision ◽  
Shared Decision ◽  
Pros And Cons

The traditional style of medical decision-making in which doctors take sole responsibility for treatment decisions is being challenged. Attempts are being made to promote shared decision-making in which patients are given the opportunity to express their values and preferences and to participate in decisions about their care. Critics of shared decision-making argue that most patients do not want to participate in decisions; that revealing the uncertainties inherent in medical care could be harmful; that it is not feasible to provide information about the potential risks and benefits of all treatment options; and that increasing patient involvement in decision-making will lead to greater demand for unnecessary, costly or harmful procedures which could undermine the equitable allocation of health care resources. This article examines the evidence for and against these claims. There is considerable evidence that patients want more information and greater involvement, although knowledge about the circumstances in which shared decision-making should be encouraged, and the effects of doing so, is sparse. There is an urgent need for more research into patients' information needs and preferences and for the development and evaluation of decision-support mechanisms to enable patients to become informed participants in treatment decisions.

scholarly journals How and why front-line health workers (did not) use a multifaceted mHealth intervention to support maternal and neonatal healthcare decision-making in Ghana

2019 ◽  
Vol 4 (2) ◽  
pp. e001153 ◽  
Author(s):  
Hannah Brown Amoakoh ◽  
Kerstin Klipstein-Grobusch ◽  
Evelyn Korkor Ansah ◽  
Diederick E Grobbee ◽  
Linda Yveoo ◽  
...  
Keyword(s):  
Decision Making ◽  
Health Outcomes ◽  
Health Worker ◽  
Clinical Decision Making ◽  
Eastern Region ◽  
Front Line ◽  
Mhealth Intervention ◽  
Phone Calls ◽  
Voice Calls ◽  
The Impact

IntroductionDespite increasing use of mHealth interventions, there remains limited documentation of ‘how and why’ they are used and therefore the explanatory mechanisms behind observed effects on beneficiary health outcomes. We explored ‘how and why’ an mHealth intervention to support clinical decision-making by front-line providers of maternal and neonatal healthcare services in a low-resource setting was used. The intervention consisted of phone calls (voice calls), text messaging (short messaging service (SMS)), internet access (data) and access to emergency obstetric and neonatal protocols via an Unstructured Supplementary Service Data (USSD). It was delivered through individual-use and shared facility mobile phones with unique Subscriber Identification Module (SIM) cards networked in a Closed User Group.MethodsA single case study with multiple embedded subunits of analysis within the context of a cluster randomised controlled trial of the impact of the intervention on neonatal health outcomes in the Eastern Region of Ghana was performed. We quantitatively analysed SIM card activity data for patterns of voice calls, SMS, data and USSD. We conducted key informant interviews and focus group discussions with intervention users and manually analysed the data for themes.ResultsOverall, the phones were predominantly used for voice calls (64%), followed by data (28%), SMS (5%) and USSD (2%), respectively. Over time, use of all intervention components declined. Qualitative analysis showed that individual health worker factors (demographics, personal and work-related needs, perceived timeliness of intervention, tacit knowledge), organisational factors (resource availability, information flow, availability, phone ownership), technological factors (attrition of phones, network quality) and client perception of health worker intervention usage explain the pattern of intervention use observed.ConclusionHow and why the mHealth intervention was used (or not) went beyond the technology itself and was influenced by individual and context-specific factors. These must be taken into account in designing similar interventions to optimise effectiveness.

Clinical Decision Making and Oral Motor Treatments

ASHA Leader ◽  
2005 ◽  
Vol 10 (8) ◽  
pp. 8-35 ◽  
Author(s):  
Heather M. Clark
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Oral Motor

Debates in Dysphagia Management: How Do You Use Evidence-Based Practice in Your Dysphagia Patient Care?

2011 ◽  
Vol 20 (4) ◽  
pp. 121-123
Author(s):  
Jeri A. Logemann
Keyword(s):  
Decision Making ◽  
Patient Care ◽  
Clinical Outcomes ◽  
Clinical Judgment ◽  
Clinical Decision Making ◽  
Evidence Based Practice ◽  
Clinical Decision ◽  
Evidence Based ◽  
Clinical Method ◽  
Do So

Evidence-based practice requires astute clinicians to blend our best clinical judgment with the best available external evidence and the patient's own values and expectations. Sometimes, we value one more than another during clinical decision-making, though it is never wise to do so, and sometimes other factors that we are unaware of produce unanticipated clinical outcomes. Sometimes, we feel very strongly about one clinical method or another, and hopefully that belief is founded in evidence. Some beliefs, however, are not founded in evidence. The sound use of evidence is the best way to navigate the debates within our field of practice.

Importance of Clinical Decision MakingImportance of Clinical Decision Making

PsycCRITIQUES ◽  
2015 ◽  
Vol 6060 (4444) ◽  
Author(s):  
Terence J. G. Tracey
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision
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