| Literature DB >> 30621693 |
Daniel Mbuthia1, Sassy Molyneux2,3, Maureen Njue4, Salim Mwalukore2, Vicki Marsh5,6.
Abstract
BACKGROUND: Increasing adoption of electronic health records in hospitals provides new opportunities for patient data to support public health advances. Such learning healthcare models have generated ethical debate in high-income countries, including on the role of patient and public consent and engagement. Increasing use of electronic health records in low-middle income countries offers important potential to fast-track healthcare improvements in these settings, where a disproportionate burden of global morbidity occurs. Core ethical issues have been raised around the role and form of information sharing processes for learning healthcare systems, including individual consent and individual and public general notification processes, but little research has focused on this perspective in low-middle income countries.Entities:
Keywords: Acceptability; Africa; Comparative effectiveness research; Electronic health records; General notification; Informed consent; Kenya; Learning healthcare systems; Public engagement; Quality improvement research; Trust
Mesh:
Year: 2019 PMID: 30621693 PMCID: PMC6325859 DOI: 10.1186/s12910-018-0343-9
Source DB: PubMed Journal: BMC Med Ethics ISSN: 1472-6939 Impact factor: 2.652
Summary of participant characteristics
| Location | Role | Total | Women | Highest qualification | Nationality |
|---|---|---|---|---|---|
| Kilifi | Researchers | 8 | 4 | Diploma × 2; MSc × 2; PhD × 4 | Kenyan 6 |
| Health providers | 9 | 6 | BSc ×1; Diploma × 6; MSc × 2 | Kenyan 9 | |
| Health managers | 7 | 3 | Diploma ×6; MSc ×1 | Kenyan 7 | |
| Malindi | Researchers | 2 | 0 | MSc ×1; Diploma × 1 | Kenyan 2 |
| Health providers | 3 | 2 | BSc ×1; Diploma ×2 | Kenyan 2 | |
| Health managers | 5 | 2 | MSc ×1; Diploma ×2; BSc × 2 | Kenyan 5 |
Scenarios used to facilitate discussions
| Scenario 1: Use for routine audit | |
| Clinical hospital data (with people’s names taken off) being used by the County Health Team to assess and report on patterns of different diseases at different times, such as the number of people admitted to hospital with malaria in a given time period. | |
| Scenario 2: Use for evaluations | |
| A public health manager in the County Health Team uses clinical and laboratory data from individual patients who have been treated for malaria in hospital (with names taken off) to evaluate whether new guidelines that have been introduced for the in-patient treatment of malaria are improving clinical outcomes overall and over time. | |
| Scenario 3: CER: Non-randomized Pragmatic Clinical Trials | |
| It is common in medical practice that there are several different treatments available to treat a given condition, without clear evidence that one treatment works better than the other. For example, many different antibiotics are recommended to treat particular infections, like boils, ear infections or lung infections. In this situation, doctors tend to choose a treatment based on their own or their patients’ personal experiences/preferences. If there was more evidence about which treatments work best and in which situations, both patients and doctors would benefit. One way for researchers to do this is to compare routine clinical data on patient outcomes (e.g. how quickly or completely patients got better after being treated by one drug compared to another). In this kind of research, the researchers DON’T introduce anything different to the normal practice. They only analyze clinical data from patients who were treated to compare the effectiveness of different antibiotics used. | |
| Scenario 4: CER: Randomized Pragmatic Clinical Trials | |
| There are many different antibiotics currently approved and used routinely for treating pneumonia. For some of these antibiotics, it’s not known if they work better than others available. For example, let’s think about two such treatments, and call them antibiotic X and antibiotic Y. Both are already approved drugs and are in use at the moment. They are given in similar ways and have similar types and risks of any side effects or more serious reactions. (Serious reactions are very rare). It is therefore unlikely that patients or physicians would have a personal preference for one drug over the other. To find out if there are any differences between these treatments, researchers can ask physicians to prescribe one of these drugs based on a system of chance, and observe over time how well patients respond to the treatments. Over time, the outcomes of patients being treated with one of these two antibiotics can be compared to learn which treatment works best. Once this is known, all the patients can be given the option to change to that treatment. |
Summary of the main emerging arguments for and against sharing information about clinical data re-use with patients and the public
| ‘Sharing information is important’ | ‘Sharing information is not (so) important’ |
|---|---|
| Ownership/rights/trust in patient-physician relationships | Data must be used for public good |
Complexities seen for patient autonomy in routine public health reporting
| Example 1 Multiple drug-resistant TB cases: Where exact information on the patient’s location (residence) must be shared to allow adequate follow up. This type of reporting would be done without seeking the patient’s permission or necessarily informing them that the report had been made. Any infringement of rights to confidentiality or increased risks of stigma in this case were felt to be reasonable given the wider public health benefits as well as the individual’s own health risks. |