Rahman, Ahmed S.

Background: Blood pressure (BP) measurement is a national core quality measure for hypertension care and hypertension control rates remain a major performance measure. It remains unclear whether improving measurement directly results in better control rates in hypertension management. Purpose: To utilize electronic medical records to explore the relationship between measurement of blood pressure and hypertension control rates among 4 eligible primary care providers groups - Primary Care Internal Medicine (PCIM), Family medicine (FM), General Internal Medicine (GIM), Preventive Medicine (PREV) - and 2 eligible specialist groups - Cardiology (CARD), Nephrology (NEPH) at an academic group medical practice. Methods: A two year cross sectional study involving adults seen by eligible primary or specialist providers at 2 or more office visits with a hypertension ICD-9 code in two years with at least one office visit in the measurement year. We measured the proportion of patients who had their BP measured at their last hypertension visit (LHV) in 2009 and 2010. We compared measurement rates with control rates as defined by the proportion of hypertension patients with BP < 140/90 mmHg at their LHV. Results: In 2009, 84.2% of 17989 patients (95% CI 83.6 - 84.7%) had their BP measured at their LHV compared to 85.3% (95% CI 84.8 - 85.8%) of 17992 patients in 2010, an increase of 1.2% (p=0.0026). Measurement rates varied widely across the different provider groups. PCIM, a high performing group, had significant improvement in measurement rates from 2009 to 2010 and demonstrated improvement in control rates. Lower performing groups, Nephrology and GIM, had significant improvement in measurement but did not see a direct translation to improved control rates. There was an associated worsening of the control rates for Preventive medicine along with a decrease in the measurement rates from 2009 to 2010. Conclusion: High BP measurement rates are associated with high hypertension control rates. Prioritizing BP measurement may result in improved intermediate outcomes in hypertension management.

Background: The diagnosis of hypertension requires systolic blood pressure (SBP) ≥ 140 mmHg or diastolic blood pressure (DBP) ≥ 90 mmHg on at least 2 different occasions. Therefore, there is the possibility of patients with elevated BP remaining undiagnosed if not seen by the same provider. Purpose: To utilize electronic medical records (EMR) to identify patients not previously diagnosed with hypertension that have elevated blood pressure meeting criteria for a diagnosis of hypertension using a threshold of SBP ≥ 140mmHg or DBP ≥ 90 mmHg (high BP) on 2 or more occasions. Methods: This was a cross sectional design utilizing retrospective multi-year billing and clinical data from a large multi-specialty center in the Midwest. Using electronic records of all outpatient visits in each year from 2009 - 2011, patients with at least 2 visits with SBP ≥ 140mmHg or DBP ≥ 90 mmHg (2HBP) in the measurement year were identified. These patients were compared with previously identified cohorts of known hypertension patients (Known HTN) compiled using the EMR problem list. A sensitivity analysis was done using patients with high BP at 2 consecutive visits (2CHBP) and also those with high BP at 3 consecutive visits (3CHBP). We compared proportions of patients with high BP without a prior diagnosis of hypertension (UDHTN). Results: The proportion of patients with SBP ≥ 140mmHg or DBP ≥ 90 mmHg without a prior diagnosis of hypertension (UDHTN) when compared to the cohort of known patients with a diagnosis of hypertension (Known HTN) was 25% in 2009, 26% in 2010, and 28% in 2011 in the 2CHBP cohort compared to 27% in 2009, 28% in 2010, and 30% in 2011 in the 2HBP cohort and 18% in 2009, 19% in 2010 and 23% in 2011 in the 3CHBP cohort. Conclusion: About a quarter of patients meeting current thresholds on multiple and consecutive visits did not have a known diagnosis of hypertension. The use of EMR can identify these patients for commencement of appropriate management. Table 1

Background: Hypertension (HTN) control rate is a core clinical quality measure. It is presently assessed by manual review of a random sample of patients with HTN billing claims. There is an increasing push by regulators towards the use of electronic medical records (EMR) to assess quality of care. Purpose: To use EMR to obtain a more in-depth assessment of quality of hypertension care. Methods: Cross sectional study involving adults with HTN seen at 2 or more office visits in 2009 by eligible primary or specialist providers at a large medical group practice. We measured the proportion of HTN patients with blood pressure (BP) at goal (BP < 140/90 mm Hg) at their last hypertension visit (LHV). Results: Of a total of 10,401 patients, 5970 (57%) were controlled and 1959 (19%) were uncontrolled at their LHV. Control could not be assessed in 2472 (24%) as BP values were unavailable from the vital signs section of the visit notes in the EMR. Of a random sample of 250 patients with unavailable BP, only 94 (37.6%) had BP values documented in other parts of the visit note. In 29 patients (11.6%) billing for HTN was done without adequate evidence that it was addressed at that visit. Control rates were highest for primary care providers where measurement and documentation of BP was a focus - Family Medicine 77% controlled, 1% unavailable; Primary Care Internal Medicine 71% controlled, 4% unavailable. A considerable proportion of patients in the other four provider groups did not have BP available from their last hypertension visit - Cardiology 59% controlled, 22% unavailable; Nephrology 38% controlled, 47% unavailable; Preventive Medicine 48% controlled, 39% unavailable; General Internal Medicine 41% controlled, 45% unavailable. Control rates were similar across provider groups when patients with unavailable BP were excluded: Family Medicine 78%, Primary Care 74%, Cardiology 75%, Nephrology 73%, Preventive Medicine 79%, and General Medicine 75%. Conclusions: Up to a quarter of HTN patients did not have properly documented BP in the EMR at their LHV. For those with measurements recorded, control rates were similar across primary care and specialty clinics, but measurement rates were higher for primary care practices. Use of the EMR facilitates efficient and granular assessment of the measurement process and control rates for HTN among various provider groups.

Background and Aims. Colorectal cancer, a leading cause of cancer death, is preventable with colonoscopic screening. Colonoscopy cost is high, and optimizing resource utilization for colonoscopy is important. This study’s aim is to evaluate resource allocation for optimal use of facilities for colonoscopy screening. Method. The authors used data from a computerized colonoscopy database to develop a discrete event simulation model of a colonoscopy suite. Operational configurations were compared by varying the number of endoscopists, procedure rooms, the patient arrival times, and procedure room turnaround time. Performance measures included the number of patients served during the clinic day and utilization of key resources. Further analysis included considering patient waiting time tradeoffs as well as the sensitivity of the system to procedure room turnaround time. Results. The maximum number of patients served is linearly related to the number of procedure rooms in the colonoscopy suite, with a fixed room to endoscopist ratio. Utilization of intake and recovery resources becomes more efficient as the number of procedure rooms increases, indicating the potential benefits of large colonoscopy suites. Procedure room turnaround time has a significant influence on patient throughput, procedure room utilization, and endoscopist utilization for varying ratios between 1:1 and 2:1 rooms per endoscopist. Finally, changes in the patient arrival schedule can reduce patient waiting time while not requiring a longer clinic day. Conclusions. Suite managers should keep a procedure room to endoscopist ratio between 1:1 and 2:1 while considering the utilization of related key resources as a decision factor as well. The sensitivity of the system to processes such as turnaround time should be evaluated before improvement efforts are made.