scholarly journals Documentation in a Medical Setting: Effects of Technology on Perceived Quality of Care

2011 ◽  
Author(s):  
Julia DeBlasio Olsheski ◽  
Bruce N. Walker
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Noorfariza Nordin ◽  
Suhaily Mohd Hairon ◽  
Najib Majdi Yaacob ◽  
Anees Abdul Hamid ◽  
Seoparjoo Azmel Mohd Isa ◽  
...  

Abstract Background People with type 2 diabetes mellitus (T2DM) are best managed by a chronic care model that is associated with enhanced quality of care and improved patient outcome. Assessing patients’ perceived quality of care is crucial in improving the healthcare delivery system. Hence, this study determined the perceived quality of care among people with T2DM and explored its associations with (i) sociodemographic and clinical characteristics and (ii) types of healthcare clinics to guide future planning. Methods A cross-sectional study involving 20 primary healthcare clinics in the North East Region of Peninsular Malaysia and people with T2DM as the sampling unit was conducted from February to May 2019. The pro forma checklist, interview-guided Skala Kepuasan Interaksi Perubatan-11, and Patient Assessment of Chronic Illness Care (Malay version; PACIC-M) questionnaire were used for data collection. Univariate analysis and linear regression were used to determine the status of perceived quality of care and the factors associated with the perceived quality of care, respectively. Results Overall, data from 772 participants were analyzed. The majority was from the Malay ethnic group (95.6%) with a mean (standard deviation [SD]) glycated hemoglobin A1c (HbA1c) level of 8.91% (2.30). The median (interquartile range [IQR]) of the number of medical officers available at each clinic was 6 (7), with Family Doctor Concept (FDC) clinics having a higher number of medical officers than non-FDC clinics (p = 0.001). The overall mean (SD) PACIC-M score was 2.65 (0.54) with no significant difference between scores of patients treated in the two clinic types (p = 0.806). Higher perceived quality of care was associated with lower number of medical officers (adjusted regression coefficient [Adj.β], − 0.021; p-value [p], 0.001), and greater doctor–patient interaction in all domains: distress relief (Adj.β, 0.033; p, < 0.001), rapport (Adj.β, 0.056; p, < 0.001), and interaction outcome (Adj.β, 0.022; p, 0.003). Conclusion Although there was no significant difference found between clinic type, this study reflects that patients are comfortable when managed by the same doctor, which may support a better doctor-patient interaction. A larger specialized primary care workforce could improve diabetes care in Malaysia.


BMJ Open ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. e037708
Author(s):  
Ira Helena Saarinen ◽  
Jaana-Maija Koivisto ◽  
Antti Kaipia ◽  
Elina Haavisto

ObjectiveTo study if patient-related factors are associated with patient-evaluated quality of care in surgery. To examine if there is an association with postoperative complications and patient-evaluated low quality of care.DesignA correlation cross-sectional study, in addition, a phone call interview at 30 days postoperatively to examine complications.SettingThe data on patients admitted for non-cardiac general and orthopaedic surgery at a central hospital in Southwestern Finland were collected in two phases during an 8-month period.Participants436 consecutive consenting and eligible in-ward non-cardiac general surgery and orthopaedic surgery adult patients. Ambulatory, paediatric and memory disorder patients were excluded. 378 patients completed the questionnaire (Good Nursing Care Scale for Patients (GNCS-P)).MethodsPerceived quality of care was examined by the GNCS-P questionnaire. Patient-related factors were obtained from electronic patient records and questionnaire. A telephone interview related to postdischarge complications was conducted 30 days after discharge.Main outcome measuresPatient evaluation of quality of care at discharge, its association with patient-related factors and patient-reported postdischarge complications.ResultsThe overall quality was evaluated high or very high by the patients. The lowest overall quality of care rate was assessed by surgical patients living alone (p=0.0088) and patients who evaluated their state of health moderate or poor (p=0.0047). Surgical patients reporting postoperative complications after discharge evaluated lower overall quality of care (p=0.0105) than patients with no complications.ConclusionPatient demographic factors do not seem to influence the perceptions of the quality of care. Instead, subjective state of health and living conditions (living alone) may have an influence on the patient experience of quality of care. The perceived quality of care in healthcare staff technical and communication skills may have an association with reported postoperative complications.


Medicine ◽  
2017 ◽  
Vol 96 (1) ◽  
pp. e5755 ◽  
Author(s):  
Xiaolin Wei ◽  
Jia Yin ◽  
Samuel Y.S. Wong ◽  
Sian M. Griffiths ◽  
Guanyang Zou ◽  
...  

2021 ◽  
Author(s):  
Rumei Yang ◽  
Kai Zeng ◽  
Yun Jiang

BACKGROUND Effective patient-provider communication is the core of high-quality patient-centered care. Communication through electronic platforms such as web, patient portal, or mobile phone (referring as e-communication) has become increasingly important as it extends traditional in-person communication with less limitation of timing and locations, and has the potential to facilitate more effective interactions between patients and providers. However, little is known about the current status of patients’ use of e-communication with healthcare providers and whether the use is related to better perceived quality of care at the population level. OBJECTIVE This study was designed to explore the prevalence of, and factors associated with e-communication and effect of e-communication on patient perceived quality of care, using the nationally representative sample of the 2019 Health Information National Trends Survey 5 (HINTS 5)-Cycle 3. METHODS Data from 5,438 survey responders aged 18 years+ (mean=49.04 years, range=18-98) were included in the analysis. All variables were measured using self-report surveys. Logistic and linear regression analyses were used to explore responders’ profile characteristics related to use of e-communication and that use related quality of care. Descriptive sub-analyses for e-communication according to age groups were also performed. All analyses considered the complex design using the jackknife replication method. RESULTS The overall prevalence of the use of e-communication was 60%, with the lowest prevalence in older adults aged 65 years or above (17%), significantly lower than adults younger than 45 years old (41%) and adults aged between 45-65 years (42%) (p<.001). American adults who had some college (OR=3.14, 95% CI 1.52–6.48, p=.003) or college graduate+ (OR=4.14, 95% CI 2.04–8.39, p<.001), household income at or greater than $50,000 (OR=1.75, 95% CI 1.25–2.46, p=.002), or a regular provider (OR=1.93, 95% CI 1.43–2.61, p<.001) were more likely to use e-communication. In contrast, those who reside in rural area (OR=0.59, 95% CI 0.39–0.89, p=.014) were less likely to use e-communication. After controlling for demographic (e.g., age, gender, education, income, and comorbidity) and relationship factors (e.g., regular provider, communication quality, and trust a doctor), the use of e-communication was statistically significantly associated with better quality of care (β=0.13, 95% CI 0.01-0.25, p=.039). CONCLUSIONS Our findings on factors associated with e-communication and the positive association between e-communication and quality of care suggest that policy-level attention is needed to engage the socially disadvantaged (i.e., those with lower levels of education and income, without a regular provider, and living rural area) to maximize the use of e-communication and to support better quality of care among American adults. CLINICALTRIAL NOT APPLICABLE


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