Data analysis by hospitals. Data analysis by payers.

1. Data analysis by hospitals. Data analysis by payers. RIC

2. ELEMENTS OF DATA MANAGEMENT • Data reporting policies and specifications • Data dictionary • Data set specification (eg NMDS) • Data entry tools • Data extraction tools • Data edits and validation processes • Data warehousing functions • (incl) metadata management, data access • Data analysis reporting

3. INFORMATION SYSTEMS SCHEMA COGNOS,BRIO, EXCELL BUSINESS OBJECTS SAS ,SPSS, STATA, ACCESS CUBES PIVOT REPORT REPOSITORY REPORTING LAYER (MIS) STATISTICAL ANALYSIS DATA WAREHOUSE AED EMD ESIS Aggregate MH DW MH ODS MDSs MH CMI MPI Oracle, SAP, etc SUPPLY HR FMIS PAS EHR BUSINESS LAYER

4. Hospital Information Systems Hospital Financial Data Cost Sheet -Allocation Statistics • Minimum Basic Data Set-DRG Data Entry Tool • Clinical Data, DRG • Resource Consumption Data (preparecostsheet) (analysis tool) (volumefile) (costfile) (CASES) Diagnosis and procedures Analysis Reports PICQ Software Combo Software Cost Reports Coding Analysis Reports Data Analysis Reports

5. REPORTING FEEDBACK • The key to • GOOD DATA • EFFICIENCY GAINS • PERFORMANCE IMPROVEMENT • The basis for rational planning • A primary mechanism to assess innovation and investment priorities.

6. Standard reports may include • Productivity • Complexity • Allocative efficiency • Technical efficiency • Coding Completeness • And various quality indicators • Outcome – Process • Some examples follow …

7. Productivity • Performance in total Weighted Episode (WEs) of all hospitals • Overall performance in total WEs against target by hospital • WEs by Major Diagnostic Categories (MDC) for Medical Diagnosis Related Group (DRGs) by hospital • WEs by MDC for Procedural DRGs by hospital • Top 10 increment DRG families by hospital • Top 10 decrement DRG families by hospital

8. Complexity • Casemix Index of Medical and Procedural DRGs of all hospitals • Casemix Index (CMI) by MDC by hospital • Average WEs per patient by MDC in by hospital • Average number of episodes per patient by MDC by hospital • Casemix – “1 Year On”

9. Allocative Efficiency • Percentage same day episodes by MDC of Medical and Procedural DRGs by hospital • Change in same day episodes of Ambulatory Medical DRGs • Percentage of episodes admitted via A&E Department by MDC by hospital

10. Technical Efficiency • Average Length of Stay (ALOS) of Medical & Procedural DRGs of all hospitals • Change in ALOS by MDC by hospital • Cost per weighted DRG by hospital

11. Coding Completeness • Percentage of total multi-day episodes for Medical and Procedural DRGs by severity level in all hospitals • Percentage of total multi-day episodes with Major Co-morbidities and Complication (MCC) by MDC for Medical DRGs by hospital • Percentage of total multi-day episodes with MCC by MDC for Procedural DRGs in all hospitals • Percentage of total multi-day episodes with MCC by MDC by hospital • WE / CMI by discharged specialty: 4-year trend analysis by hospital

12. WHY IS PATIENT LEVEL COSTING SO IMPORTANT?

13. The proposition Tracking utilisation to patients is actually more important than simply accurate cost weights.

14. How can this be true? MP Ann Clwyd wept in the House of Commons as she described how her husband [Owen] died 'like a battery hen' Labour MP Ann Clwyd says her biggest regret was that she didn't 'stand in the hospital corridor and scream'3 in protest of the 'callous lack of care' the NHS nurses showed her husband, as he lay dying of hospital acquired pneumonia.
Ann describes her husband's final days, crushed 'like a battery hen' against the bars of his hospital bed, wearing an oxygen mask that was so tight it cut his face and pumped cold air in to his infected eye. Owen died after suffering 10 days of this treatment at the NHS University Hospital of Wales in Cardiff. Following her husband's death, the MP publicly spoke out on the 'normalisation of cruelty' that has become 'commonplace' in NHS hospitals.
Owen had battled MS for 30 years, yet died of hospital-borne pneumonia. Shockingly, around 100,0004 patients catch an infection in UK hospitals every year, from which 5,000 people sadly die. http://www.top10healthinsurance.com/article/factsabouthealthinsurance?src=tab

15. KEY POINTS • Good data for clinical care monitoring (inputs utilization analysis) is also good costing data. • Utilization by case type gives accurate detailed costing • AND benchmarking patient level variability is vital for both pricing and quality-of-care management. • Clinicians should be the primary users of utilization data and analyses • CLINICAL BEHAVIOURS << CLINICAL CULTURES << OPERATIONAL USE OF DATA • Key immediate strategies.

16. PRICING HEALTHCARE • 1. Improve data quality • 2. Increase comparability and consistency of data • 3. Improve transparency • 4. Develop the potential for new pricing mechanisms • 5. Proportionate regulatory cost • 6. Improve the use of cost data by managers and clinicians

21. The advent of the ‘S’ curve Figures in £000s) 2012/13 surplus/ deficit Scenario A 2014/15 projected surplus/ deficit (expected case) Scenario B Scenario C 2014/15 projected surplus/ deficit with 1% annual efficiency shortfall

22. Scenarios 2 and 3 Start and remain in deficit Start in surplus but move into deficit Start in surplus but move into deficit Remain in surplus

23. The two key questions •  How do we get the right data from costing systems into regular clinical review use? • How do we better enable clinicians to take the lead in performance improvement?

24. QUESTION 1. • How do we get the right data from costing systems into regular clinical review use?

25. RELEVANCE Kane Gorny, 22, left to die of thirst in an NHS London hospital Kane Gorny, an active 22-year-old, had already bravely beaten cancer the year before and needed a routine hip replacement due to the treatment. Whilst recovering from this simple operation, Kane suffered unthinkable neglect at the hands of his doctors and nurses in St. George's NHS hospital, Tooting.
Having been denied his medication and refused his pleas for water; driven by thirst and desperation, Kane called 999 from his hospital bed. But when the police arrived to his aide, they were maliciously turned away by hospital staff who claimed he was delirious. Kane died of dehydration just hours later! Whilst his grieving mother took a moment to sit with her son's body, a nurse then heartlessly asked if she was finished so that they could 'bag him up'1.
Disgustingly, Kane's case is not alone; 4 people die of dehydration every day in our hospitals2. …Health insurance is one way to ensure you receive the right treatment, when you need it. [!!!!!?????]http://www.top10healthinsurance.com/article/factsabouthealthinsurance?src=tab

26. The locus of efficiency and effectiveness “EVERY CLINICAL DECISION IS AN EXPENDITURE DECISION” Don Hindle

27. Look! You spent too much on patient 15644 But patient 15644 was different from normal Don Hindle

28. I've checked, and patient 15644 wasn't different at all! Sorry, I'll try not to do it again Don Hindle

29. Benchmarking by item cost only ..FINANCIAL VIEW … Mean cost/case Nursing Medical Allied health OR Pathology Imaging Pharmacy Consumables Overhead Other Total Our hospital 750 500 170 420 90 65 120 75 450 200 $2850 Other hospitals 550 420 180 340 80 50 110 90 380 200 $2400 Don Hindle

30. …and cost/utilisation benchmarking .. CLINICIAN VIEW Other hospitals 6 hours Nil Yes Yes Elements of cPaths Admitted how long before procedure? Post-op hours in CCU Review of discharge plan at admission? Discharge OK delegated? Our hospital 9 hours 6 hours No No financial data and clinical pathways From Don Hindle

31. TIMELINESS • We need to be able to review whether changes are working • We need to be able to correct and steer regularly – monthly – weekly • We need to be able to check immediate activity against norms – agreed protocols - to guide decisions and choices

32. EXAMPLE DATA FLOW SCHEMA eg. COGNOS,BRIO, EXCELL eg. BUSINESS OBJECTS eg. SAS ,SPSS, STATA, ACCESS CUBES PIVOT REPORT REPOSITORY REPORTING LAYER (MIS) AUDIT TRAIL STATISTICAL ANALYSIS AUDIT TRAIL AUDIT TRAIL AUDIT TRAIL DATA WAREHOUSE AED EMD ESIS Aggregate MH DW MH ODS MDSs MH CMI MPI eg. Oracle, SAP, etc SUPPLY HR FMIS PAS EHR BUSINESS LAYER

33. GRANULARITY • Why are the costs higher / lower? • What are we doing differently? • Are our patient-type ratios different? • Are we differentiating – tailoring the pathways to different patients – is our variability matching standard patterns

34. QUESTION 2. • How do we better enable clinicians to take the lead in performance improvement?

35. Clinical process review • Patient journey • Clinical pathway • Evidence based practice • Variance analysis

36. QUESTION 3 • How can clinicians match best practice and properly accommodate natural patient variability?

37. Culture eats reform for breakfast • “I am a doctor/nurse not a manager – I care for people not ‘cases’. Everyone is different.” • Is the care team or the individual responsible • “Why are we doing this type of case differently?” • What is the evidence that it works better? • “How can we redeploy the savings if we can achieve less costly practice?”

38. So ..how well are we doing? Elderly and frail 'Mrs H'5 bruised, soaked in her own urine and heavily dishevelled under NHS 'care' Mrs H was an independent 88-year-old, living in her own home - until she had a fall. Admitted to the Heart of England NHS Trust, Mrs H suffered further disturbing ailments, including a broken collar bone. Upon her transferral to a new care home, the manager voiced concern over her bruised, soiled and distressed state. She arrived in clothing that was not her own, held in place by large paper clips, along with several bags of dirty clothes. Sadly Mrs H died before the investigation into her cruel treatment was complete and the NHS Trust admitted their failings.
An astonishing 3,0006 complaints are made about the NHS every single week, illustrating that the core 'care' principle of nursing seems to be disappearing rapidly from its practice. NHS nurses even claim the new generation of university-trained nurses believe basic care tasks, such as bathing their patients, are 'beneath them'7. If you were to fall ill, it's only natural that you would want to be treated and cared for to a high standard: Private facilities have strong reputations to uphold and less time pressures, meaning consultants can dedicate more attention to individual patients. http://www.top10healthinsurance.com/article/factsabouthealthinsurance?src=tab

39. Definition of Clinical Pathways • Systematically developed written statements that: • Are evidence based • Incorporate the views of clinicians (medical, nursing, allied health) patients and managers • Prospectively describe how care will provided and how effectiveness, quality and efficiency will be monitored and assessed. From Pieter Degeling

40. A clinical pathway enables a clinical team to: • prospectively describe the sequence of diagnostic and therapeutic events whose occurrence or non-occurrence will significantly affect quality, cost and outcome. • prospectively define the quality and outcome indicators that it will use to judge its performance. • prospectively cost the care that it provides and in so doing defines the cost indicators that it will use to judge its efficiency. • routinely and consistently monitor its performance on quality and cost • alter its method for treating a condition, in light of what it [systematically] has learned about treating the condition. From Pieter Degeling

41. Prospectively Costed Quality indicators Routine Review of Variance Outcome Indicators Characteristics of Integrated care pathways Clinical Pathway From Pieter Degeling

42. Pathway Based Clinical Production Intermediate Products Imaging Pharmacy Path. Hotel services HipICP 1 Final Products Hip ICP 2 Knee ICP 1 # ICP 1 From Pieter Degeling

43. Important provisos • CPs are not immutable documents setting out inviolable treatment regimens. • The existence of a pathway does not obviate clinicians’ responsibility to make clinical judgements and to tailor care according to their assessment of the clinical needs of individual patients. • Thus clinical variation remains a ‘to be expected’ (in the sense of an often required) feature of clinical practice. • The matter at issue is what a clinical team can learn from these variations and how they can systematize this learning. • Accordingly, when the care process varies from that described in the pathway, the reasons for the variance are recorded and become the focus of structured across-profession conversations described above. From Pieter Degeling

44. High volume case types – how many pathways? Within a 600 -700 bed DGH in the NHS • Emergency admissions account for 53% of all inpatient episodes and 83% of all bed days consumed within the Trusts • 40 HRGs (of 603) account for 46% of emergency admissions and 42% emergency generated bed days • 40 HRGs account for 60% of in patient elective episodes and 40% of elective bed-days, and • 40 HRGs account for 84% of day elective episodes • 10 HRGs account for 98% of all maternity and births admissions and 97% of maternity and birth bed days From Pieter Degeling

47. Why high volume case types? High volume case types are those for which: • Pathways will produce the biggest ‘bang for the buck’ as we strive to improve: • Efficiency • Effectiveness • Quality • We can generate valid data for statistical analysis of variance From Pieter Degeling

48. Variance Analysis For each high volume case type collect, collate and analyze data on: - the occurrence and non occurrence of the events described in a pathway - quality indicators, clinical outcomes indicators and resource usage These data are then used to: - profile and compare performance within and between hospitals over time - identify changes in practice that will lift performance to the benefit of improvements in quality, appropriateness, safety and efficiency including changing the pathway From Pieter Degeling

49. QUESTION 4 • Which data on their caseload patterns and peer norms are most useful?

50. MACRO TO MICRO DRILLDOWNS • Totals to clinical units – individual clinical teams • Totals to particular DRGs – patient types – • Inputs across peers for sub sets of case categories