Social influence on 5-year survival in a longitudinal chemotherapy ward co-presence network

A passive monitoring tool using hospital administrative data enables earlier specific detection of healthcare-acquired infections

BACKGROUND

Healthcare-associated infections impose a significant burden on the healthcare system. Current methods for detecting these infections are constrained by combinations of high cost, long processing times and imperfect accuracy, reducing their effectiveness.

METHODS

This study examined whether the amount of time a patient spends on a ward with other patients clinically suspected of infection, termed 'co-presence', can be used as a tool to predict subsequent healthcare-associated infection. Compared with contact tracing, this leverages passively collected electronic data rather than manually collected data, allowing for improved monitoring. All 133,304 inpatient records between 2011 and 2015 were abstracted from a healthcare system in the UK. The area under the receiver-operator curve (AUROC) for each of five pathogens was calculated based on co-presence time, sensitivity and specificity of the test, and how much earlier co-presence would have predicted infection for the true-positive cases.

FINDINGS

For the five pathogens, AUROC ranged from 0.92 to 0.99, and was 0.52 for the negative control. Optimal cut-points of co-presence ranged from 25 to 59 h, and would have led to detection of true-positive cases up to an average of 1 day earlier.

INTERPRETATION

These findings show that co-presence time would help to predict healthcare-acquired infection, and would do so earlier than the current standard of care. Using this measure prospectively in hospitals based on real-time data could limit the consequences of infection, both by being able to treat individual infected patients earlier, and by preventing potential secondary infections stemming from the original infected patient.

Evaluating spillover of HIV knowledge from study participants to their network members in a stepped-wedge behavioural intervention in Tanzania

OBJECTIVES

We aim to describe the social network members of participants of a behavioural intervention, and examine how the effects of the intervention may spillover among network members.

DESIGN

Secondary analysis of a step-wedge randomised controlled trial.

SETTING

Change agents (CAs) were recruited from waiting rooms of HIV treatment facilities in Dar es Salaam, Tanzania, and their network members (NMs) were recruited directly by CAs.

PARTICIPANTS

We enrolled 662 CAs in an HIV behavioural intervention. They, along with 710 of their NMs, completed baseline and follow-up interviews from 2011 to 2013.

PRIMARY AND SECONDARY OUTCOMES

The primary outcome of this study was change in NMs' HIV knowledge, and the secondary outcome was whether the NM was lost to follow-up.

RESULTS

At baseline, many characteristics were different between NMs and CAs. We found a number of NM characteristics significantly associated with follow-up of NMs, particularly female gender (OR=1.64, 95% CI: 1.02 to 2.63) and HIV knowledge (OR=20.0, 95% CI: 3.70 to 125); only one CA variable was significantly associated with NM follow-up: having a private source of water (OR=2.17, 95% CI: 1.33 to 3.57). The 14.2% increase in NMs' HIV knowledge was largely due to CAs feeling empowered to pass on prior knowledge, rather than transmitting new knowledge to their NMs.

CONCLUSIONS

Characteristics of social network members of persons living with HIV persons living with HIV may play a role in study retention. Additionally, the HIV knowledge of these NMs increased largely as a function of CA participation in the intervention, suggesting that intervening among highly-connected individuals may maximise benefits to the potential population for whom spillover can occur.

TRIAL REGISTRATION NUMBER

Clinical Trial: NCT01693458; Post-results.

Patient Phenotypes Help Explain Variation in Response to a Social Gamification Weight Loss Intervention

PURPOSE

This study aims to determine latent classes of study participants using baseline characteristics, explore the patterns within the groups, and determine whether the intervention had differential effects on weight loss across the groups.

DESIGN

Secondary analysis of a completed randomized clinical trial.

SETTING

Participants in a gamification intervention with social incentives who were recruited as pairs and given an intervention for 24 weeks. Participants were randomized to control, gamification, or gamification with primary care physician sharing arms.

PARTICIPANTS

All 196 participants in the Lose It trial (recruited as 98 pairs).

MEASURES

Outcome variable-participants' weight change after 24 and 36 weeks. Factors-intervention arm and latent class.

ANALYSIS

Latent class analysis on both participants' and teams' characteristics. This was followed by 1-sample t tests of weight at 24 and 36 weeks, stratified by latent class.

RESULTS

Three groups of participants were identified: "Kin teams," "Distant teams," and "Married teams." "Kin teams" lost more weight after the intervention in the gamification and gamification with PCP sharing arms. The "Distant teams" lost similar amounts of weight in all 3 arms but did not keep it off during maintenance. The "Married teams" lost the most weight across all 3 arms and kept it off following the intervention.

CONCLUSIONS

Patient phenotypes can identify variations in response to a gamification weight loss intervention. Future intervention studies may benefit from leveraging this during participant recruitment and allocation.

Using hospital administrative data to infer patient-patient contact via the consistent co-presence algorithm

In health care settings, patients who are physically proximate to other patients (co-presence) for a meaningful amount of time may have differential health outcomes depending on who they are in contact with. How to best measure this co-presence, however is an open question and previous approaches have limitations that may make them inappropriate for complex health care settings. Here, we introduce a novel method which we term "consistent co-presence", that implicitly models the many complexities of patient scheduling and movement through a hospital by randomly perturbing the timing of patients' entry time into the health care system. This algorithm generates networks that can be employed in models of patient outcomes, such as 1-year mortality, and are preferred over previously established alternative algorithms from a model comparison perspective. These results indicate that consistent co-presence retains meaningful information about patient-patient interaction, which may affect outcomes relevant to health care practice. Furthermore, the generalizabiity of this approach allows it to be applied to a wide variety of complex systems.

Aromatherapy, massage and reflexology: A systematic review and thematic synthesis of the perspectives from people with palliative care needs

BACKGROUND

Effectiveness evidence of complementary therapies in people with advanced disease is uncertain, and yet people are still keen to engage in complementary therapy. Insights into people's experiences of complementary therapy in palliative care, the perceived benefits, and how they want it delivered, can inform clinical guidelines and suggest ways to test therapies more appropriately in future evaluations.

AIMS

Explore in people with advanced disease (1) the experiences and perceptions of benefits and harms of aromatherapy, massage, and reflexology and (2) how they would like these therapies delivered.

DESIGN

A systematic review and thematic synthesis of qualitative studies. Database search terms were related to palliative care, aromatherapy, reflexology and massage. Citations and full texts were reviewed independently against predefined inclusion criteria. Studies were appraised for quality. This review is registered at PROSPERO (22/11/2017 CRD42017081409).

DATA SOURCES

MEDLINE, EMBASE, PsycINFO, AMED, CINAHL, KoreaMed and ProQuest with a bibliography search to June 2018.

RESULTS

Five qualitative studies in advanced cancer were identified. Three analytical themes were identified: (1) Experience during the therapy (enhanced well-being and escapism), (2) beyond the complementary therapy session (lasting benefits and overall evaluation), and (3) delivery of complementary therapy in palliative care (value of the therapist and delivery of the complementary therapy).

CONCLUSIONS

People with advanced cancer experience benefits from aromatherapy, reflexology and massage including enhanced well-being, respite, and escapism from their disease. Complementary therapy interventions should be developed in consultation with the target population to ensure they are delivered and evaluated, where feasible, as they wish.