Evaluating Primary Care Physician Performance in Diabetes Glucose Control

Should we screen aging physicians for cognitive decline?

OBJECTIVES

To synthesize evidence relevant for informed decisions concerning cognitive testing of older physicians.

METHODS

Relevant literature was systematically searched in Medline, EMBASE, PsycInfo, and ERIC, with key findings abstracted and synthesized.

RESULTS

Cognitive abilities of physicians may decline in an age range where they are still practicing. Physician competence and clinical performance may also decline with age. Cognitive scores are lower in physicians referred for assessment because of competency or performance concerns. Many physicians do not accurately self-assess and continue to practice despite declining quality of care; however, perceived cognitive decline, although not an accurate indicator of ability, may accelerate physicians' decision to retire. Physicians are reluctant to report colleagues' cognitive problems. Several issues should be considered in implementing cognitive screening. Most cognitive assessment tools lack normative data for physicians. Scientific evidence linking cognitive test results with physician performance is limited. There is no known level of cognitive decline at which a doctor is no longer fit to practice. Finally, relevant domains of cognitive ability vary across medical specialties.

CONCLUSION

Physician cognitive decline may impact clinical performance. If cognitive assessment of older physicians is to be implemented, it should consider challenges of cognitive test result interpretation.

Characteristics of exceptionally good Doctors-A survey of public adults

Background

Systematic reviews have found that doctors can have a substantial effect on patients' physical health, beyond what can be explained by known factors. In a previous qualitative study, 13 medical doctors were interviewed on their experiences of exceptionally good doctors, and all had met at least one such doctor.

Objective

To determine how common it is for exceptionally good doctors to be encountered by patients and what are the characteristics of exceptionally good doctors.

Design

Mixed methods cross-sectional survey of 580 Amazon Mechanical Turk participants. Questions included doctor and participant demographics, and 34 Likert questions on characteristics of exceptionally good and average doctors. Free-text questions allowed participants to describe exceptional doctors, record their experience, and provide survey feedback. Stratified sampling ensured gender parity and 33% of participants aged ≥55 years. Analysis included descriptive statistics, statistical modelling of associations between Likert scale scores and patient demographics, and factor analysis.

Results

Of 580 responses, 505 (86%) were included in the analysis. Factor analysis confirmed internal validity. Most respondents (86%) had met at least two exceptionally good doctors, of whom 55% were specialists. 58% of respondents regarded doctors as exceptional based on an overall impression with multiple reasons. Doctors were most commonly considered exceptional based on one or more of their personality, diagnostic, or intervention ability. Respondents who reported the doctors "willingly listened to them to the end" scored their doctors higher on 33 of 34 Likert questions, except for popularity. They also rated average doctors lower throughout.

Conclusions

Exceptionally good doctors appear to be commonly encountered by the adult public. Listening to patients willingly to the end is a highly rated and influential characteristic, suggesting that listening could be targeted for quality improvement.

Characteristics of Exceptionally Good Doctors: A Protocol for a Cross-Sectional Survey of Adults

Background

Doctors constitute a significant proportion of a very large number of medical interactions. They are known to vary in the quality of their work, with some having an exceptionally beneficial effect on patients' physical health. In a qualitative study, we interviewed medical doctors on their opinions and experiences of exceptionally good doctors. Their responses and the results from previous research are used as a basis for this proposed cross-sectional survey directed to members of the public on their encounters with exceptionally good doctors. The primary aim of this cross-sectional study is to describe the characteristics of exceptional doctors as reported by a large representative sample of adult patients.

Methods and Analysis

A mixed qualitative and quantitative anonymous cross-sectional survey of 500 Amazon Mechanical Turk (MTurk) respondents, who have met one or more exceptionally good doctors in their life, will be conducted. Information requested will include reasons for nominating a particular doctor; experience of how that doctor differs from other and average doctors; and 34 5-point Likert scale questions on the characteristics of that doctor and the same Likert questions for the average doctor. An opportunity to report their experience in free-text form will be provided. Sample size will be sufficient to obtain a margin of error of 4%. The authors will provide descriptive statistics, including graphs of the Likert scale question responses; conduct factor analysis for internal validity; investigate satisficing and logical inconsistencies; and explore whether there are multiple types of exceptionally good doctors.

Discussion

Previous surveys of patients' perceptions of doctors exist though none have focused on exceptionally good doctors. The expected results will include a list of characteristics that are important to patients in determining exceptionally good doctors.

Is There a Doctors' Effect on Patients' Physical Health, Beyond the Intervention and All Known Factors? A Systematic Review

Purpose

Despite billions of doctor visits worldwide each year, little is known on whether doctors themselves affect patients' physical health after accounting for intervention and confounders such as patients' and doctors' data, hospital effects, nor how strong that doctors' effect is. Knowledge of surgeons' and psychotherapists' effects exists, but not for 102 other medical specialties notwithstanding the importance of such knowledge.

Methods

Eligibility Criteria: Randomized controlled trials (RCTs), case-control, and cohort studies including medical doctors except surgeons for any intervention, reporting the proportion of variance in patients' outcomes owing to the doctors (random effects), or the fixed effects of grading doctors by outcomes, after multivariate adjustment. Exclusions: studies of <15 doctors or solely reporting doctors' effects for known variables.

Sources

Medline, Embase, PsycINFO, inception to June 2020. Manual search for papers referring/referred to by resulting studies.

Risk of Bias

Using Newcastle-Ottawa scale.

Results

Despite all medical interventions bar surgery being eligible, only thirty cohort papers were found, covering 36,239 doctors, with 10 specialties, 21 interventions, 60 outcomes (17 unique). Studies reported doctors' effects by grading doctors from best to worst, or by diversely calculating the doctor-attributed percentage of patients' outcome variation, ie the intra-class correlation coefficient (ICC). Sixteen studies presented fixed effects, 18 random effects, and 3 another approach. No RCTs found. Thirteen studies reported exceptionally good and/or poor performers with confidence intervals wholly outside the average performance. ICC range 0 to 33%, mean 3.9%. Highly diverse reporting, meta-analysis therefore not applicable.

Conclusion

Doctors, on their own, can affect patients' physical health for many interventions and outcomes. Effects range from negligible to substantial, even after accounting for all known variables. Many published cohorts may reveal valuable information by reanalyzing their data for doctors' effects. Positive and negative doctor outliers appear regularly. Therefore, it can matter which doctor is chosen.

The Doctors' Effect on Patients' Physical Health Outcomes Beyond the Intervention: A Methodological Review

Background

Previous research suggests that when a treatment is delivered, patients' outcomes may vary systematically by medical practitioner.

Objective

To conduct a methodological review of studies reporting on the effect of doctors on patients' physical health outcomes and to provide recommendations on how this effect could be measured and reported in a consistent and appropriate way.

Methods

The data source was 79 included studies and randomized controlled trials from a systematic review of doctors' effects on patients' physical health. We qualitatively assessed the studies and summarized how the doctors' effect was measured and reported.

Results

The doctors' effects on patients' physical health outcomes were reported as fixed effects, identifying high and low outliers, or random effects, which estimate the variation in patient health outcomes due to the doctor after accounting for all available variables via the intra-class correlation coefficient. Multivariable multilevel regression is commonly used to adjust for patient risk, doctor experience and other demographics, and also to account for the clustering effect of hospitals in estimating both fixed and random effects.

Conclusion

This methodological review identified inconsistencies in how the doctor's effect on patients' physical health outcomes is measured and reported. For grading doctors from worst to best performances and estimating random effects, specific recommendations are given along with the specific data points to report.

Qualitative Study of Medical Doctors on Their Experiences and Opinions of the Characteristics of Exceptionally Good Doctors

Background

It is generally accepted that there is a therapist effect in psychotherapy, with master therapists being studied using qualitative methods. There are surgeons with exceptionally positive patients' physical health outcomes, and qualitative research on what makes good doctors. However, characteristics of exceptionally good doctors are less studied and understood.

Objective

To qualitatively study the opinions of physicians on exceptionally good doctors.

Methods

Thirteen semi-structured interviews of English-speaking medical doctors of any specialty were conducted. Recruitment was achieved through the authors' network; contacting authors of relevant research papers; and Bond University's General Practitioner recruitment program. Their opinion was sought on what makes an exceptionally good doctor, whether they have met such a person, what was their experience of that person, and whether they consider themselves as exceptionally good doctors.

Analysis

A six-phase thematic analysis in an experiential framework, as per Braun and Clarke, was implemented to identify themes and their details in an inductive approach with a realist epistemological position, ie, assuming truthful knowledge on what makes exceptionally good doctors can be obtained.

Results

Each interviewee had met and been inspired by exceptionally good doctors. Descriptions covered six themes: character traits; other characteristics; patient relationships; peer and health care system relations; education; and treatment examples. Exceptionally good doctors were found to have up-to-date extensive medical knowledge and skills, relate well with patients, and have excellent diagnostic abilities. They tend to be humble, approachable, inspiring, and are long-remembered role models. However, they may not always be appreciated by their peers and their health care system because of their exceptional abilities.

Discussion and Conclusion

Exceptional doctors are beneficial for their peers, their patients, and their health care system. Identifying, acknowledging, and making such doctors more accessible to medical students and junior doctors could have a positive impact on medical practice.

Self-efficacy remains a vital factor in reducing the risk of dialysis in type 2 diabetes care

Studies have provided promising outcomes of the pay-for-performance (P4P) program or with good continuity of care levels in diabetes control.We investigate the different exposures in continuity of care (COC) with their providers and those who participate in the P4P program and its effects on the risk of diabetes diabetic nephropathy in the future.We obtained COC and P4P information from the annual database, to which we applied a hierarchical linear modeling (HLM) in 3 levels adjusted to account for other covariates as well as the effects of hospital clustering and accumulating time.Newly diagnosed type 2 diabetes in 2003At the individual level, those with a higher Diabetes Complications Severity Index (DCSI) score have a higher likelihood of diabetic nephropathy than those with a lower DCSI (OR, 1.46), whereas contrasting results were obtained for the Charlson Comorbidity Index (CCI) (odds ratio[OR], 0.88). Patients who visited family physicians, endocrinologists, and gastroenterologists showed a lower likelihood of diabetic nephropathy (OR, 0.664, 0.683, and 0.641, respectively), whereas those who continued to visit neurologists showed an increased risk of diabetic nephropathy by 4 folds. At the hospital level, patients with diabetes visiting primary care clinics had a lower risk of diabetic nephropathy with an OR of 0.584 than those visiting hospitals of other higher levels. Regarding the repeat time level, the patients who had a higher COC score and participated in the P4P program had a reduced diabetic nephropathy risk with an OR of 0.339 and 0.775, respectively.Diabetes control necessitates long-term care involving the patients' healthcare providers for the management of their conditions to reduce the risk of diabetic nephropathy. Indeed, most contributing factors are related to patients, but we cannot eliminate the optimal outcomes related to good relationships with healthcare providers and participation in the P4P program.

From Testing to Decision-Making: A Data-Driven Analytics COVID-19 Response

In March 2020, NorthShore University Health System laboratories mobilized to develop and validate polymerase chain reaction based testing for detection of SARS-CoV-2. Using laboratory data, NorthShore University Health System created the Data Coronavirus Analytics Research Team to track activities affected by SARS-CoV-2 across the organization. Operational leaders used data insights and predictions from Data Coronavirus Analytics Research Team to redeploy critical care resources across the hospital system, and real-time data were used daily to make adjustments to staffing and supply decisions. Geographical data were used to triage patients to other hospitals in our system when COVID-19 detected pavilions were at capacity. Additionally, one of the consequences of COVID-19 was the inability for patients to receive elective care leading to extended periods of pain and uncertainty about a disease or treatment. After shutting down elective surgeries beginning in March of 2020, NorthShore University Health System set a recovery goal to achieve 80% of our historical volumes by October 1, 2020. Using the Data Coronavirus Analytics Research Team, our operational and clinical teams were able to achieve 89% of our historical volumes a month ahead of schedule, allowing rapid recovery of surgical volume and financial stability. The Data Coronavirus Analytics Research Team also was used to demonstrate that the accelerated recovery period had no negative impact with regard to iatrogenic COVID-19 infection and did not result in increased deep vein thrombosis, pulmonary embolisms, or cerebrovascular accident. These achievements demonstrate how a coordinated and transparent data-driven effort that was built upon a robust laboratory testing capability was essential to the operational response and recovery from the COVID-19 crisis.

Are characteristics of team members important for quality management of chronic patients at primary care level?

AIMS AND OBJECTIVES

To determine the possible associations between higher levels of selected quality indicators and the characteristics of providers.

BACKGROUND

In 2011, an ongoing project on a new model of family medicine practice was launched in Slovenia; the family physicians' working team (a family physician and a practice nurse) was extended by a nurse practitioner working 0.5 full-time equivalents. This was an example of a personalised team approach to managing chronic patients.

METHODS

We included all family medicine practices in the six units of the Community Health Centre Ljubljana which were participating in the project in December 2015 (N = 66). Data were gathered from automatic electronic reports on quality indicators provided monthly by each practice. We also collected demographic data.

RESULTS

There were 66 family medicine teams in the sample, with 165 members of their teams (66 family physicians, 33 nurse practitioners and 66 practice nurses). Fifty-six (84.4%) of the family physicians were women, as were 32 (97.0%) of the nurse practitioners, and 86 (95.5%) of the practice nurses. Multivariate analysis showed that a higher level of the quality indicator "Examination of diabetic foot once per year" was independently associated with nurse practitioners having attended additional education on diabetes, duration of participation in the project, age and years worked since graduation of nurse practitioners, working in the Center unit and not working in the Bezigrad unit.

CONCLUSIONS

Characteristics of team members are important in fostering quality management of chronic patients. Nurse practitioners working in new model family practices need obligatory, continuous professional education in the management of chronic patients.

RELEVANCE TO CLINICAL PRACTICE

The quality of care of chronic patients depends on the specific characteristics of the members of the team, which should be taken into account when planning quality improvements.