National Medical Care Utilization and Expenditure Survey.

Title from cover.

Implications of prospective payment for the health care system and health planning /

"HRP-0906516."

Are diagnosis specific outcome indicators based on administrative data useful in assessing quality of hospital care?

Background: Hospital performance reports based on administrative data should distinguish differences in quality of care between hospitals from case mix related variation and random error effects. A study was undertaken to determine which of 12 diagnosis-outcome indicators measured across all hospitals in one state had significant risk adjusted systematic ( or special cause) variation (SV) suggesting differences in quality of care. For those that did, we determined whether SV persists within hospital peer groups, whether indicator results correlate at the individual hospital level, and how many adverse outcomes would be avoided if all hospitals achieved indicator values equal to the best performing 20% of hospitals. Methods: All patients admitted during a 12 month period to 180 acute care hospitals in Queensland, Australia with heart failure (n = 5745), acute myocardial infarction ( AMI) ( n = 3427), or stroke ( n = 2955) were entered into the study. Outcomes comprised in-hospital deaths, long hospital stays, and 30 day readmissions. Regression models produced standardised, risk adjusted diagnosis specific outcome event ratios for each hospital. Systematic and random variation in ratio distributions for each indicator were then apportioned using hierarchical statistical models. Results: Only five of 12 (42%) diagnosis-outcome indicators showed significant SV across all hospitals ( long stays and same diagnosis readmissions for heart failure; in-hospital deaths and same diagnosis readmissions for AMI; and in-hospital deaths for stroke). Significant SV was only seen for two indicators within hospital peer groups ( same diagnosis readmissions for heart failure in tertiary hospitals and inhospital mortality for AMI in community hospitals). Only two pairs of indicators showed significant correlation. If all hospitals emulated the best performers, at least 20% of AMI and stroke deaths, heart failure long stays, and heart failure and AMI readmissions could be avoided. Conclusions: Diagnosis-outcome indicators based on administrative data require validation as markers of significant risk adjusted SV. Validated indicators allow quantification of realisable outcome benefits if all hospitals achieved best performer levels. The overall level of quality of care within single institutions cannot be inferred from the results of one or a few indicators.

Multisite, quality-improvement collaboration to optimise cardiac care in Queensland public hospitals

Objective: To evaluate changes in quality of in-hospital care of patients with either acute coronary syndromes (ACS) or congestive heart failure (CHF) admitted to hospitals participating in a multisite quality improvement collaboration. Design: Before-and-after study of changes in quality indicators measured on representative patient samples between June 2001 and January 2003. Setting: Nine public hospitals in Queensland. Study populations: Consecutive or randomly selected patients admitted to study hospitals during the baseline period (June 2001 to January 2002; n = 807 for ACS, n = 357 for CHF) and post-intervention period (July 2002 to January 2003; n = 717 for ACS, n = 220 for CHF). Intervention: Provision of comparative baseline feedback at a facilitative workshop combined with hospital-specific quality-improvement interventions supported by on-site quality officers and a central program management group. Main outcome measure: Changes in process-of-care indicators between baseline and post-intervention periods. Results: Compared with baseline, more patients with ACS in the post-intervention period received therapeutic heparin regimens (84% v 72%; P < 0.001), angiotensin-converting enzyme inhibitors (64% v 56%; P = 0.02), lipid-lowering agents (72% v 62%; P < 0.001), early use of coronary angiography (52% v 39%; P < 0.001), in-hospital cardiac counselling (65% v 43%; P < 0.001), and referral to cardiac rehabilitation (15% v 5%; P < 0.001). The numbers of patients with CHF receiving β-blockers also increased (52% v 34%; P < 0.001), with fewer patients receiving deleterious agents (13% v 23%; P = 0.04). Same-cause 30-day readmission rate decreased from 7.2% to 2.4% (P = 0.02) in patients with CHF. Conclusion: Quality-improvement interventions conducted as multisite collaborations may improve in-hospital care of acute cardiac conditions within relatively short time frames.

Trial of low-cost teledermatology in primary care

We examined the feasibility of a low-cost, store-and-forward teledermatology service for general practitioners (GPs) in regional Queensland. Digital pictures and a brief case history were transmitted by email. A service coordinator carried out quality control checks and then forwarded these email messages to a consultant dermatologist. On receiving a clinical response from the dermatologist, the service coordinator returned the message to the referring GP. The aim was to provide advice to rural Gps within one working day. Over six months, 63 referrals were processed by the teledermatology service, covering a wide range of dermatological conditions. In the majority of cases the referring doctors were able to treat the condition after receipt of email advice from the dermatologist; however, in 10 cases (16%) additional images or biopsy results were requested because image quality was inadequate. The average time between a referral being received and clinical advice being provided to the referring GPs was 46 hours. The number of referrals in the present study, 1.05 per month per site, was similar to that reported in other primary care studies. While the use of low-cost digital cameras and public email is feasible, there may be other issues, for example remuneration, which will militate against the widespread introduction of primary care teledermatology in Australia.

The costs of caring for patients in a tertiary referral Australian intensive care unit

We determined the direct cost of an Intensive Care Unit (ICU) bed in a tertiary referral Australian ICU and the cost drivers thereof, by retrospectively analysing a number of prospectively designed Hospital- and Unit-specific electronic databases. The study period was a financial year, from 1 July 2002 to 30 June 2003. There were 1615 patients occupying 5692 fractional occupied bed days at a total cost of A$15,915,964, with an average length of stay of 3.69 days (range 0.5-77, median 1.06, interquartile range 2.33). The main cost driver not incorporated into this analysis was blood products (paid for centrally). The average costs of an ICU day and total stay per patient were A$2670 and A$9852 respectively. Staff-related charges were 68.76%, with consumables related expenditure making up 19.65%, clinical support services 9.55% and capital equipment 2.04%. Overtime charges and nursing agency staff were 19.4% of staff-related charges (2.9% for agency staff), 3.9% lower than expenditure associated with full-time employment charges, such as pension and leave. The emergency nature of ICU means it is difficult to accurately set a nursing establishment to cater for all admissions and therefore it is hard to decide what is an acceptable percentage difference between agency/overtime costs compared with the costs associated with full-time staff appointments. Consumable expenditure is likely to increase the most with new innovation and therapies. Using protocol driven practices may tighten and control costs incurred in ICU.

Reduced between-hospital variation in short term survival after acute myocardial infarction: the result of improved cardiac care?

Objectives: To re-examine interhospital variation in 30 day survival after acute myocardial infarction ( AMI) 10 years on to see whether the appointment of new cardiologists and their involvement in emergency care has improved outcome after AMI. Design: Retrospective cohort study. Setting: Acute hospitals in Scotland. Participants: 61 484 patients with a first AMI over two time periods: 1988 - 1991; and 1998 - 2001. Main outcome measures: 30 day survival. Results: Between 1988 and 1991, median 30 day survival was 79.2% ( interhospital range 72.1 - 85.1%). The difference between highest and lowest was 13.0 percentage points ( age and sex adjusted, 12.1 percentage points). Between 1998 and 2001, median survival rose to 81.6% ( and range decreased to 78.0 - 85.6%) with a difference of 7.6 ( adjusted 8.8) percentage points. Admission hospital was an independent predictor of outcome at 30 days during the two time periods ( p< 0.001). Over the period 1988 - 1991, the odds ratio for death ranged, between hospitals, from 0.71 ( 95% confidence interval ( CI) 0.58 to 0.88) to 1.50 ( 95% CI 1.19 to 1.89) and for the period 1998 - 2001 from 0.82 ( 95% CI 0.60 to 1.13) to 1.46 ( 95% CI 1.07 to 1.99). The adjusted risk of death was significantly higher than average in nine of 26 hospitals between 1988 and 1991 but in only two hospitals between 1998 and 2001. Conclusions: The average 30 day case fatality rate after admission with an AMI has fallen substantially over the past 10 years in Scotland. Between-hospital variation is also considerably less notable because of better survival in the previously poorly performing hospitals. This suggests that the greater involvement of cardiologists in the management of AMI has paid dividends.

Carvedilol reduces the costs of medical care in severe heart failure: An economic analysis of the COPERNICUS study applied to the United Kingdom

Background: The aim of this study was to determine the effects of carvedilol on the costs related to the treatment of severe chronic heart failure (CHF). Methods: Costs for the treatment for heart failure within the National Health Service (NHS) in the United Kingdom (UK) were applied to resource utilisation data prospectively collected in all patients randomized into the Carvedilol Prospective Randomized Cumulative Survival (COPERNICUS) Study. Unit-specific, per them (hospital bed day) costs were used to calculate expenditures due to hospitalizations. We also included costs of carvedilol treatment, general practitioner surgery/office visits, hospital out-patient clinic visits and nursing home care based on estimates derived from validated patterns of clinical practice in the UK. Results: The estimated cost of carvedilol therapy and related ambulatory care for the 1156 patients assigned to active treatment was 530,771 pound (44.89 pound per patient/month of follow-up). However, patients assigned to carvedilol were hospitalised less often and accumulated fewer and less expensive days of admission. Consequently, the total estimated cost of hospital care was 3.49 pound million in the carvedilol group compared with 4.24 pound million for the 1133 patients in the placebo arm. The cost of post-discharge care was also less in the carvedilol than in the placebo group (479,200 pound vs. 548,300) pound. Overall, the cost per patient treated in the carvedilol group was 3948 pound compared to 4279 pound in the placebo group. This equated to a cost of 385.98 pound vs. 434.18 pound, respectively, per patient/month of follow-up: an 11.1% reduction in health care costs in favour of carvedilol. Conclusions: These findings suggest that not only can carvedilol treatment increase survival and reduce hospital admissions in patients with severe CHF but that it can also cut costs in the process.

The effect of music on preoperative anxiety in day surgery

Aim. This paper reports a study to test the hypothesis that day surgery patients who listen to music during their preoperative wait will have statistically significantly lower levels of anxiety than patients who receive routine care. Background. Although previous day surgery research suggests that music effectively reduces preoperative anxiety, methodological issues limit the generalizability of results. Methods. In early 2004, a randomized controlled trial design was conducted to assess anxiety before and after listening to patient preferred music. Participants were allocated to an intervention (n = 60), placebo (n = 60) or control group (n = 60). Pre- and post-test measures of anxiety were carried out using the State-Trait Anxiety Inventory. Results. Music statistically significantly reduced the state anxiety level of the music (intervention) group. No relationships were found between socio-demographic or clinical variables such as gender or type of surgery. Conclusion. The findings support the use of music as an independent nursing intervention for preoperative anxiety in patients having day surgery.

Adoption of a sedation scoring system and sedation guideline in an intensive care unit

Aim. The paper presents a study assessing the rate of adoption of a sedation scoring system and sedation guideline. Background. Clinical practice guidelines including sedation guidelines have been shown to improve patient outcomes by standardizing care. In particular sedation guidelines have been shown to be beneficial for intensive care patients by reducing the duration of ventilation. Despite the acceptance that clinical practice guidelines are beneficial, adoption rates are rarely measured. Adoption data may reveal other factors which contribute to improved outcomes. Therefore, the usefulness of the guideline may be more appropriately assessed by collecting adoption data. Method. A quasi-experimental pre-intervention and postintervention quality improvement design was used. Adoption was operationalized as documentation of sedation score every 4 hours and use of the sedation and analgesic medications suggested in the guideline. Adoption data were collected from patients' charts on a random day of the month; all patients in the intensive care unit on that day were assigned an adoption category. Sedation scoring system adoption data were collected before implementation of a sedation guideline, which was implemented using an intensive information-giving strategy, and guideline adoption data were fed back to bedside nurses. After implementation of the guideline, adoption data were collected for both the sedation scoring system and the guideline. The data were collected in the years 2002-2004. Findings. The sedation scoring system was not used extensively in the pre-intervention phase of the study; however, this improved in the postintervention phase. The findings suggest that the sedation guideline was gradually adopted following implementation in the postintervention phase of the study. Field notes taken during the implementation of the sedation scoring system and the guideline reveal widespread acceptance of both. Conclusion. Measurement of adoption is a complex process. Appropriate operationalization contributes to greater accuracy. Further investigation is warranted to establish the intensity and extent of implementation required to positively affect patient outcomes.