METHODS: This is a quasi-experimental study conducted in 20 intervention and 20 matched control clinics. We surveyed all HCPs who were directly involved in patient management. A self-administered questionnaire which included six questions on job satisfaction were assessed on a scale of 1-4 at baseline (April and May 2017) and post-intervention phase (March and April 2019). Unadjusted intervention effect was calculated based on absolute differences in mean scores between intervention and control groups after implementation. Difference-in-differences analysis was used in the multivariable linear regression model and adjusted for providers and clinics characteristics to detect changes in job satisfaction following EnPHC interventions. A negative estimate indicates relative decrease in job satisfaction in the intervention group compared with control group.
RESULTS: A total of 1042 and 1215 HCPs responded at baseline and post-intervention respectively. At post-intervention, the intervention group reported higher level of stress with adjusted differences of - 0.139 (95% CI -0.266,-0.012; p = 0.032). Nurses, being the largest workforce in public clinics were the only group experiencing dissatisfaction at post-intervention. In subgroup analysis, nurses from intervention group experienced increase in work stress following EnPHC interventions with adjusted differences of - 0.223 (95% CI -0.419,-0.026; p = 0.026). Additionally, the same group were less likely to perceive their profession as well-respected at post-intervention (β = - 0.175; 95% CI -0.331,-0.019; p = 0.027).
CONCLUSIONS: Our findings suggest that EnPHC interventions had resulted in some untoward effect on HCPs' job satisfaction. Job dissatisfaction can have detrimental effects on the organisation and healthcare system. Therefore, provider experience and well-being should be considered before introducing healthcare delivery reforms to avoid overburdening of HCPs.
METHODS: A cross-sectional survey was conducted among primary care physicians (PCPs) in public primary care clinics in Kuala Lumpur, Malaysia. A 30-item self-administered questionnaire was used to assess the knowledge and practice of CRC screening.
RESULTS: The response rate was 86.4% (n = 197/228). Less than half (39.1%) of the respondents answered correctly for all risk stratification scenarios. Mean knowledge score on CRC screening modalities was 48.7% ± 17.7%. The knowledge score was positively associated with having postgraduate educational qualification and usage of screening guidelines. Overall, 69.9% of PCPs reported that they practised screening. However, of these, only 25.9% of PCPs screened over 50% of all eligible patients. PCPs who agreed that screening was cost-effective (odds ratio [OR] 3.34, 95% confidence interval [CI] 1.69‒6.59) and those who agreed that they had adequate resources in their locality (OR 1.92, 95% CI 1.01‒3.68) were more likely to practise screening. Knowledge score was not associated with the practice of screening (p = 0.185).
CONCLUSION: Knowledge and practice of CRC screening was inadequate among PCPs. Knowledge of screening did not translate into its practice. PCPs' perceptions about cost-effectiveness of screening and adequate resources were important determinants of the practice of screening.
METHOD: This study was conducted using an exploratory qualitative approach on purposely selected healthcare providers at primary healthcare clinics. Twenty focus group discussions and three in-depth interviews were conducted using a semi-structured interview guide. Consent was obtained prior to interviews and for audio-recordings. Interviews were transcribed verbatim and thematically analysed, guided by the Consolidated Framework for Implementation Research (CFIR), a framework comprised of five major domains promoting implementation theory development and verification across multiple contexts.
RESULTS: The study revealed via CFIR that most primary healthcare providers were receptive towards any proposed changes or intervention for the betterment of NCD care management. However, many challenges were outlined across four CFIR domains-intervention characteristics, outer setting, inner setting, and individual characteristics-that included perceived barriers to implementation. Perception of issues that triggered proposed changes reflected the current situation, including existing facilitating aspects that can support the implementation of any future intervention. The importance of strengthening the primary healthcare delivery system was also expressed.
CONCLUSION: Understanding existing situations faced at the primary healthcare setting is imperative prior to implementation of any intervention. Healthcare providers' receptiveness to change was explored, and using CFIR framework, challenges or perceived barriers among healthcare providers were identified. CFIR was able to outline the clinics' setting, individual behaviour and external agency factors that have direct impact to the organisation. These are important indicators in ensuring feasibility, effectiveness and sustainability of any intervention, as well as future scalability considerations.
DESIGN: Cross-sectional survey conducted between April and May 2017.
SETTING: Forty public clinics in Malaysia.
PARTICIPANTS: A total of 956 adult patients with T2D and/or hypertension were interviewed.
MAIN OUTCOME MEASURES: Patient experience on SMS was evaluated using a structured questionnaire of the short version Patient Assessment of Chronic Illness Care instrument, PACIC-M11. Linear regression analysis adjusting for complex survey design was used to determine the association of patient and clinic factors with PACIC-M11 scores.
RESULTS: The overall PACIC-M11 mean was 2.3(SD,0.8) out of maximum of 5. The subscales' mean scores were lowest for patient activation (2.1(SD,1.1)) and highest for delivery system design/decision support (2.9(SD,0.9)). Overall PACIC-M11 score was associated with age, educational level and ethnicity. Higher overall PACIC-M11 ratings was observed with increasing difference between actual and expected consultation duration [β = 0.01; 95% CI (0.001, 0.03)]. Better scores were also observed among patients who would recommend the clinic to friends and family [β = 0.19; 95% CI (0.03, 0.36)], when health providers were able to explain things in ways that were easy to understand [β = 0.34; 95% CI (0.10, 0.59)] and knew about patients' living conditions [β = 0.31; 95% CI (0.15, 0.47)].
CONCLUSIONS: Our findings indicated patients received low levels of SMS. PACIC-M11 ratings were associated with age, ethnicity, educational level, difference between actual and expected consultation length, willingness to recommend the clinic and provider communication skills.