scholarly journals Measuring Quality of Healthcare Outcomes in Type 2 Diabetes from Routine Data: a Seven-nation Survey Conducted by the IMIA Primary Health Care Working Group

2017 ◽  
Vol 26 (01) ◽  
pp. 201-208
Author(s):  
W. Hinton ◽  
H. Liyanage ◽  
A. McGovern ◽  
S.-T. Liaw ◽  
C. Kuziemsky ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Data Quality ◽  
Healthcare Quality ◽  
Healthcare Outcomes ◽  
Patient Centred Care ◽  
Care Working Group ◽  
Timeliness Of Care

Summary Background: The Institute of Medicine framework defines six dimensions of quality for healthcare systems: (1) safety, (2) effectiveness, (3) patient centeredness, (4) timeliness of care, (5) efficiency, and (6) equity. Large health datasets provide an opportunity to assess quality in these areas. Objective: To perform an international comparison of the measurability of the delivery of these aims, in people with type 2 diabetes mellitus (T2DM) from large datasets. Method: We conducted a survey to assess healthcare outcomes data quality of existing databases and disseminated this through professional networks. We examined the data sources used to collect the data, frequency of data uploads, and data types used for identifying people with T2DM. We compared data completeness across the six areas of healthcare quality, using selected measures pertinent to T2DM management. Results: We received 14 responses from seven countries (Australia, Canada, Italy, the Netherlands, Norway, Portugal, Turkey and the UK). Most databases reported frequent data uploads and would be capable of near real time analysis of healthcare quality. The majority of recorded data related to safety (particularly medication adverse events) and treatment efficacy (glycaemic control and microvascular disease). Data potentially measuring equity was less well recorded. Recording levels were lowest for patient-centred care, timeliness of care, and system efficiency, with the majority of databases containing no data in these areas. Databases using primary care sources had higher data quality across all areas measured. Conclusion: Data quality could be improved particularly in the areas of patient-centred care, timeliness, and efficiency. Primary care derived datasets may be most suited to healthcare quality assessment.

scholarly journals Measuring Quality of Healthcare Outcomes in Type 2 Diabetes from Routine Data: a Seven-nation Survey Conducted by the IMIA Primary Health Care Working Group

2017 ◽  
Vol 26 (01) ◽  
pp. 201-208 ◽  
Author(s):  
W. Hinton ◽  
H. Liyanage ◽  
A. McGovern ◽  
S.-T. Liaw ◽  
C. Kuziemsky ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Data Quality ◽  
Healthcare Quality ◽  
Healthcare Outcomes ◽  
Patient Centred Care ◽  
Care Working Group ◽  
Timeliness Of Care

Summary Background: The Institute of Medicine framework defines six dimensions of quality for healthcare systems: (1) safety, (2) effectiveness, (3) patient centeredness, (4) timeliness of care, (5) efficiency, and (6) equity. Large health datasets provide an opportunity to assess quality in these areas. Objective: To perform an international comparison of the measurability of the delivery of these aims, in people with type 2 diabetes mellitus (T2DM) from large datasets. Method: We conducted a survey to assess healthcare outcomes data quality of existing databases and disseminated this through professional networks. We examined the data sources used to collect the data, frequency of data uploads, and data types used for identifying people with T2DM. We compared data completeness across the six areas of healthcare quality, using selected measures pertinent to T2DM management. Results: We received 14 responses from seven countries (Australia, Canada, Italy, the Netherlands, Norway, Portugal, Turkey and the UK). Most databases reported frequent data uploads and would be capable of near real time analysis of healthcare quality.The majority of recorded data related to safety (particularly medication adverse events) and treatment efficacy (glycaemic control and microvascular disease). Data potentially measuring equity was less well recorded. Recording levels were lowest for patient-centred care, timeliness of care, and system efficiency, with the majority of databases containing no data in these areas. Databases using primary care sources had higher data quality across all areas measured. Conclusion: Data quality could be improved particularly in the areas of patient-centred care, timeliness, and efficiency. Primary care derived datasets may be most suited to healthcare quality assessment.

scholarly journals Quality of Life and Associated Factors among Primary Care Asian Patients with Type 2 Diabetes Mellitus

2019 ◽  
Vol 16 (19) ◽  
pp. 3561 ◽  
Author(s):  
Hardesh Dhillon ◽  
Rusli Bin Nordin ◽  
Amutha Ramadas
Keyword(s):  
Quality Of Life ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Primary Care ◽  
Type 2 Diabetes Mellitus ◽  
Medication Adherence ◽  
Well Being ◽  
Care Clinic

Diabetes complications, medication adherence, and psychosocial well-being have been associated with quality of life (QOL) among several Western and Asian populations with diabetes, however, there is little evidence substantiating these relationships among Malaysia’s unique and diverse population. Therefore, a cross-sectional study was conducted in a Malaysian public primary care clinic among 150 patients diagnosed with type 2 diabetes mellitus (T2DM). Structured and validated questionnaires were used to investigate the associations between demographic, clinical, and psychological factors with QOL of the study participants. Approximately three-quarters of patients had a good-excellent QOL. Diabetes-related variables that were significantly associated with poor QOL scores included insulin containing treatment regimens, poor glycemic control, inactive lifestyle, retinopathy, neuropathy, abnormal psychosocial well-being, higher diabetes complication severity, and nonadherence (p < 0.05). The main predictors of a good-excellent QOL were HbA1c ≤ 6.5% (aOR = 20.78, 95% CI = 2.5175.9, p = 0.005), normal anxiety levels (aOR = 5.73, 95% CI = 1.8–18.5, p = 0.004), medication adherence (aOR = 3.35, 95% CI = 1.3–8.7, p = 0.012), and an aDCSI score of one and two as compared to those greater than or equal to four (aOR = 7.78, 95% CI = 1.5–39.2, p = 0.013 and aOR = 8.23, 95% CI = 2.1–32.8, p = 0.003), respectively. Medication adherence has also been found to be an effect modifier of relationships between HbA1c, depression, anxiety, disease severity, and QOL. These predictors of QOL are important factors to consider when managing patients with T2DM.

scholarly journals Prevalence of amputations amongst people with type 2 diabetes enrolled in primary care in England

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
B Meza-Torres ◽  
C Heiss ◽  
S Cunningham ◽  
F Carinci ◽  
S de Lusignan
Keyword(s):  
Type 2 Diabetes ◽  
Primary Care ◽  
Quality Of Care ◽  
General Practitioners ◽  
Distinct Pattern ◽  
National Database ◽  
Cross Sectional ◽  
Clinical Records

Abstract Background Different patterns of co-morbidities observed among people with type 2 diabetes (T2D) and lower extremity amputations (LEA) compared with those without may provide insights into the quality of care provided by general practitioners in England. We analysed routinely recorded clinical data to build predictive models for benchmarking and continuous improvement. Methods A cross-sectional computerized data extraction of clinical records from the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC) database of people with T2D in England. Key target cases were defined as adults with T2D and a record of major/minor LEA between 2008-2019 vs all subjects with T2D without amputation. Quality of care was assessed in terms of percentage of patients treated with optimal medical therapy and diagnostic procedures and referred to specialized care according to their clinical profile. The association between quality of care and outcomes was explored using a logistic regression model, adjusting for case-mix. Results During the last decade, in a sample covering approximately 7.4% of all general practitioners in England, a total of 1,052 subjects out of 127,100 adults with T2D had a LEA (832 per 100,000). The median time since amputation was 3.4 years. Only 410 (38%) patients had a recorded DFU diagnosis prior to the amputation, with a median of 2 years from diagnosis to amputation. Major LEA was recorded in 280 (27%) cases. People with a record of retinopathy, peripheral arterial disease, renal disease, neuropathy and DFU had a higher risk of amputations. Quality of care was heterogeneous between patients with and without LEA. Conclusions People with T2D and LEA have a distinct pattern of co-morbidities some of which may be sensitive to improved primary care management, and differential quality of care. Models built using this national database can routinely monitor amputations in England. Variation in treatment should be properly investigated. Key messages The automated extraction of clinical cases from a national database may help shed light on clinical patterns among people with diabetes at high risk of amputations, based on evidence-based criteria. Variation in treatment and quality of care among amputated vs non-amputated subjects can be rapidly explored using a cross-sectional analysis of current records.

Sign in / Sign up

Export Citation Format

Share Document